set binding protein: Topics by Science.gov

Sample records for set binding protein

Functional assignment of solute-binding proteins of ABC transporters using a fluorescence-based thermal shift assay.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giulliani, S. E.; Frank, A. E.; Collart, F. R.

2008-12-08

We have used a fluorescence-based thermal shift (FTS) assay to identify amino acids that bind to solute-binding proteins in the bacterial ABC transporter family. The assay was validated with a set of six proteins with known binding specificity and was consistently able to map proteins with their known binding ligands. The assay also identified additional candidate binding ligands for several of the amino acid-binding proteins in the validation set. We extended this approach to additional targets and demonstrated the ability of the FTS assay to unambiguously identify preferential binding for several homologues of amino acid-binding proteins with known specificity andmore » to functionally annotate proteins of unknown binding specificity. The assay is implemented in a microwell plate format and provides a rapid approach to validate an anticipated function or to screen proteins of unknown function. The ABC-type transporter family is ubiquitous and transports a variety of biological compounds, but the current annotation of the ligand-binding proteins is limited to mostly generic descriptions of function. The results illustrate the feasibility of the FTS assay to improve the functional annotation of binding proteins associated with ABC-type transporters and suggest this approach that can also be extended to other protein families.« less
In Planta Determination of the mRNA-Binding Proteome of Arabidopsis Etiolated Seedlings

PubMed Central

Evers, Maurits; Alleaume, Anne-Marie; Horos, Rastislav

2016-01-01

RNA binding proteins (RBPs) control the fate and expression of a transcriptome. Despite this fundamental importance, our understanding of plant RBPs is rudimentary, being mainly derived via bioinformatic extrapolation from other kingdoms. Here, we adapted the mRNA-protein interactome capture method to investigate the RNA binding proteome in planta. From Arabidopsis thaliana etiolated seedlings, we captured more than 700 proteins, including 300 with high confidence that we have defined as the At-RBP set. Approximately 75% of these At-RBPs are bioinformatically linked with RNA biology, containing a diversity of canonical RNA binding domains (RBDs). As no prior experimental RNA binding evidence exists for the majority of these proteins, their capture now authenticates them as RBPs. Moreover, we identified protein families harboring emerging and potentially novel RBDs, including WHIRLY, LIM, ALBA, DUF1296, and YTH domain-containing proteins, the latter being homologous to animal RNA methylation readers. Other At-RBP set proteins include major signaling proteins, cytoskeleton-associated proteins, membrane transporters, and enzymes, suggesting the scope and function of RNA-protein interactions within a plant cell is much broader than previously appreciated. Therefore, our foundation data set has provided an unbiased insight into the RNA binding proteome of plants, on which future investigations into plant RBPs can be based. PMID:27729395
A tool for calculating binding-site residues on proteins from PDB structures.

PubMed

Hu, Jing; Yan, Changhui

2009-08-03

In the research on protein functional sites, researchers often need to identify binding-site residues on a protein. A commonly used strategy is to find a complex structure from the Protein Data Bank (PDB) that consists of the protein of interest and its interacting partner(s) and calculate binding-site residues based on the complex structure. However, since a protein may participate in multiple interactions, the binding-site residues calculated based on one complex structure usually do not reveal all binding sites on a protein. Thus, this requires researchers to find all PDB complexes that contain the protein of interest and combine the binding-site information gleaned from them. This process is very time-consuming. Especially, combing binding-site information obtained from different PDB structures requires tedious work to align protein sequences. The process becomes overwhelmingly difficult when researchers have a large set of proteins to analyze, which is usually the case in practice. In this study, we have developed a tool for calculating binding-site residues on proteins, TCBRP http://yanbioinformatics.cs.usu.edu:8080/ppbindingsubmit. For an input protein, TCBRP can quickly find all binding-site residues on the protein by automatically combining the information obtained from all PDB structures that consist of the protein of interest. Additionally, TCBRP presents the binding-site residues in different categories according to the interaction type. TCBRP also allows researchers to set the definition of binding-site residues. The developed tool is very useful for the research on protein binding site analysis and prediction.
The DINGO dataset: a comprehensive set of data for the SAMPL challenge

NASA Astrophysics Data System (ADS)

Newman, Janet; Dolezal, Olan; Fazio, Vincent; Caradoc-Davies, Tom; Peat, Thomas S.

2012-05-01

Part of the latest SAMPL challenge was to predict how a small fragment library of 500 commercially available compounds would bind to a protein target. In order to assess the modellers' work, a reasonably comprehensive set of data was collected using a number of techniques. These included surface plasmon resonance, isothermal titration calorimetry, protein crystallization and protein crystallography. Using these techniques we could determine the kinetics of fragment binding, the energy of binding, how this affects the ability of the target to crystallize, and when the fragment did bind, the pose or orientation of binding. Both the final data set and all of the raw images have been made available to the community for scrutiny and further work. This overview sets out to give the parameters of the experiments done and what might be done differently for future studies.
Structure-Templated Predictions of Novel Protein Interactions from Sequence Information

PubMed Central

Betel, Doron; Breitkreuz, Kevin E; Isserlin, Ruth; Dewar-Darch, Danielle; Tyers, Mike; Hogue, Christopher W. V

2007-01-01

The multitude of functions performed in the cell are largely controlled by a set of carefully orchestrated protein interactions often facilitated by specific binding of conserved domains in the interacting proteins. Interacting domains commonly exhibit distinct binding specificity to short and conserved recognition peptides called binding profiles. Although many conserved domains are known in nature, only a few have well-characterized binding profiles. Here, we describe a novel predictive method known as domain–motif interactions from structural topology (D-MIST) for elucidating the binding profiles of interacting domains. A set of domains and their corresponding binding profiles were derived from extant protein structures and protein interaction data and then used to predict novel protein interactions in yeast. A number of the predicted interactions were verified experimentally, including new interactions of the mitotic exit network, RNA polymerases, nucleotide metabolism enzymes, and the chaperone complex. These results demonstrate that new protein interactions can be predicted exclusively from sequence information. PMID:17892321
Hydration in drug design. 3. Conserved water molecules at the ligand-binding sites of homologous proteins

NASA Astrophysics Data System (ADS)

Poornima, C. S.; Dean, P. M.

1995-12-01

Water molecules are known to play an important rôle in mediating protein-ligand interactions. If water molecules are conserved at the ligand-binding sites of homologous proteins, such a finding may suggest the structural importance of water molecules in ligand binding. Structurally conserved water molecules change the conventional definition of `binding sites' by changing the shape and complementarity of these sites. Such conserved water molecules can be important for site-directed ligand/drug design. Therefore, five different sets of homologous protein/protein-ligand complexes have been examined to identify the conserved water molecules at the ligand-binding sites. Our analysis reveals that there are as many as 16 conserved water molecules at the FAD binding site of glutathione reductase between the crystal structures obtained from human and E. coli. In the remaining four sets of high-resolution crystal structures, 2-4 water molecules have been found to be conserved at the ligand-binding sites. The majority of these conserved water molecules are either bound in deep grooves at the protein-ligand interface or completely buried in cavities between the protein and the ligand. All these water molecules, conserved between the protein/protein-ligand complexes from different species, have identical or similar apolar and polar interactions in a given set. The site residues interacting with the conserved water molecules at the ligand-binding sites have been found to be highly conserved among proteins from different species; they are more conserved compared to the other site residues interacting with the ligand. These water molecules, in general, make multiple polar contacts with protein-site residues.
Feature selection and classification of protein-protein complexes based on their binding affinities using machine learning approaches.

PubMed

Yugandhar, K; Gromiha, M Michael

2014-09-01

Protein-protein interactions are intrinsic to virtually every cellular process. Predicting the binding affinity of protein-protein complexes is one of the challenging problems in computational and molecular biology. In this work, we related sequence features of protein-protein complexes with their binding affinities using machine learning approaches. We set up a database of 185 protein-protein complexes for which the interacting pairs are heterodimers and their experimental binding affinities are available. On the other hand, we have developed a set of 610 features from the sequences of protein complexes and utilized Ranker search method, which is the combination of Attribute evaluator and Ranker method for selecting specific features. We have analyzed several machine learning algorithms to discriminate protein-protein complexes into high and low affinity groups based on their Kd values. Our results showed a 10-fold cross-validation accuracy of 76.1% with the combination of nine features using support vector machines. Further, we observed accuracy of 83.3% on an independent test set of 30 complexes. We suggest that our method would serve as an effective tool for identifying the interacting partners in protein-protein interaction networks and human-pathogen interactions based on the strength of interactions. © 2014 Wiley Periodicals, Inc.
A general and fast scoring function for protein-ligand interactions: a simplified potential approach.

PubMed

Muegge, I; Martin, Y C

1999-03-11

A fast, simplified potential-based approach is presented that estimates the protein-ligand binding affinity based on the given 3D structure of a protein-ligand complex. This general, knowledge-based approach exploits structural information of known protein-ligand complexes extracted from the Brookhaven Protein Data Bank and converts it into distance-dependent Helmholtz free interaction energies of protein-ligand atom pairs (potentials of mean force, PMF). The definition of an appropriate reference state and the introduction of a correction term accounting for the volume taken by the ligand were found to be crucial for deriving the relevant interaction potentials that treat solvation and entropic contributions implicitly. A significant correlation between experimental binding affinities and computed score was found for sets of diverse protein-ligand complexes and for sets of different ligands bound to the same target. For 77 protein-ligand complexes taken from the Brookhaven Protein Data Bank, the calculated score showed a standard deviation from observed binding affinities of 1.8 log Ki units and an R2 value of 0.61. The best results were obtained for the subset of 16 serine protease complexes with a standard deviation of 1.0 log Ki unit and an R2 value of 0.86. A set of 33 inhibitors modeled into a crystal structure of HIV-1 protease yielded a standard deviation of 0.8 log Ki units from measured inhibition constants and an R2 value of 0.74. In contrast to empirical scoring functions that show similar or sometimes better correlation with observed binding affinities, our method does not involve deriving specific parameters that fit the observed binding affinities of protein-ligand complexes of a given training set. We compared the performance of the PMF score, Böhm's score (LUDI), and the SMOG score for eight different test sets of protein-ligand complexes. It was found that for the majority of test sets the PMF score performs best. The strength of the new approach presented here lies in its generality as no knowledge about measured binding affinities is needed to derive atomic interaction potentials. The use of the new scoring function in docking studies is outlined.
QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation.

PubMed

Votano, Joseph R; Parham, Marc; Hall, L Mark; Hall, Lowell H; Kier, Lemont B; Oloff, Scott; Tropsha, Alexander

2006-11-30

Four modeling techniques, using topological descriptors to represent molecular structure, were employed to produce models of human serum protein binding (% bound) on a data set of 1008 experimental values, carefully screened from publicly available sources. To our knowledge, this data is the largest set on human serum protein binding reported for QSAR modeling. The data was partitioned into a training set of 808 compounds and an external validation test set of 200 compounds. Partitioning was accomplished by clustering the compounds in a structure descriptor space so that random sampling of 20% of the whole data set produced an external test set that is a good representative of the training set with respect to both structure and protein binding values. The four modeling techniques include multiple linear regression (MLR), artificial neural networks (ANN), k-nearest neighbors (kNN), and support vector machines (SVM). With the exception of the MLR model, the ANN, kNN, and SVM QSARs were ensemble models. Training set correlation coefficients and mean absolute error ranged from r2=0.90 and MAE=7.6 for ANN to r2=0.61 and MAE=16.2 for MLR. Prediction results from the validation set yielded correlation coefficients and mean absolute errors which ranged from r2=0.70 and MAE=14.1 for ANN to a low of r2=0.59 and MAE=18.3 for the SVM model. Structure descriptors that contribute significantly to the models are discussed and compared with those found in other published models. For the ANN model, structure descriptor trends with respect to their affects on predicted protein binding can assist the chemist in structure modification during the drug design process.
Crossing borders to bind proteins--a new concept in protein recognition based on the conjugation of small organic molecules or short peptides to polypeptides from a designed set.

PubMed

Baltzer, Lars

2011-06-01

A new concept for protein recognition and binding is highlighted. The conjugation of small organic molecules or short peptides to polypeptides from a designed set provides binder molecules that bind proteins with high affinities, and with selectivities that are equal to those of antibodies. The small organic molecules or peptides need to bind the protein targets but only with modest affinities and selectivities, because conjugation to the polypeptides results in molecules with dramatically improved binder performance. The polypeptides are selected from a set of only sixteen sequences designed to bind, in principle, any protein. The small number of polypeptides used to prepare high-affinity binders contrasts sharply with the huge libraries used in binder technologies based on selection or immunization. Also, unlike antibodies and engineered proteins, the polypeptides have unordered three-dimensional structures and adapt to the proteins to which they bind. Binder molecules for the C-reactive protein, human carbonic anhydrase II, acetylcholine esterase, thymidine kinase 1, phosphorylated proteins, the D-dimer, and a number of antibodies are used as examples to demonstrate that affinities are achieved that are higher than those of the small molecules or peptides by as much as four orders of magnitude. Evaluation by pull-down experiments and ELISA-based tests in human serum show selectivities to be equal to those of antibodies. Small organic molecules and peptides are readily available from pools of endogenous ligands, enzyme substrates, inhibitors or products, from screened small molecule libraries, from phage display, and from mRNA display. The technology is an alternative to established binder concepts for applications in drug development, diagnostics, medical imaging, and protein separation.
Visualisation of variable binding pockets on protein surfaces by probabilistic analysis of related structure sets.

PubMed

Ashford, Paul; Moss, David S; Alex, Alexander; Yeap, Siew K; Povia, Alice; Nobeli, Irene; Williams, Mark A

2012-03-14

Protein structures provide a valuable resource for rational drug design. For a protein with no known ligand, computational tools can predict surface pockets that are of suitable size and shape to accommodate a complementary small-molecule drug. However, pocket prediction against single static structures may miss features of pockets that arise from proteins' dynamic behaviour. In particular, ligand-binding conformations can be observed as transiently populated states of the apo protein, so it is possible to gain insight into ligand-bound forms by considering conformational variation in apo proteins. This variation can be explored by considering sets of related structures: computationally generated conformers, solution NMR ensembles, multiple crystal structures, homologues or homology models. It is non-trivial to compare pockets, either from different programs or across sets of structures. For a single structure, difficulties arise in defining particular pocket's boundaries. For a set of conformationally distinct structures the challenge is how to make reasonable comparisons between them given that a perfect structural alignment is not possible. We have developed a computational method, Provar, that provides a consistent representation of predicted binding pockets across sets of related protein structures. The outputs are probabilities that each atom or residue of the protein borders a predicted pocket. These probabilities can be readily visualised on a protein using existing molecular graphics software. We show how Provar simplifies comparison of the outputs of different pocket prediction algorithms, of pockets across multiple simulated conformations and between homologous structures. We demonstrate the benefits of use of multiple structures for protein-ligand and protein-protein interface analysis on a set of complexes and consider three case studies in detail: i) analysis of a kinase superfamily highlights the conserved occurrence of surface pockets at the active and regulatory sites; ii) a simulated ensemble of unliganded Bcl2 structures reveals extensions of a known ligand-binding pocket not apparent in the apo crystal structure; iii) visualisations of interleukin-2 and its homologues highlight conserved pockets at the known receptor interfaces and regions whose conformation is known to change on inhibitor binding. Through post-processing of the output of a variety of pocket prediction software, Provar provides a flexible approach to the analysis and visualization of the persistence or variability of pockets in sets of related protein structures.
Identification of distinct SET/TAF-Iβ domains required for core histone binding and quantitative characterisation of the interaction

PubMed Central

Karetsou, Zoe; Emmanouilidou, Anastasia; Sanidas, Ioannis; Liokatis, Stamatis; Nikolakaki, Eleni; Politou, Anastasia S; Papamarcaki, Thomais

2009-01-01

Background The assembly of nucleosomes to higher-order chromatin structures is finely tuned by the relative affinities of histones for chaperones and nucleosomal binding sites. The myeloid leukaemia protein SET/TAF-Iβ belongs to the NAP1 family of histone chaperones and participates in several chromatin-based mechanisms, such as chromatin assembly, nucleosome reorganisation and transcriptional activation. To better understand the histone chaperone function of SET/TAF-Iβ, we designed several SET/TAF-Iβ truncations, examined their structural integrity by circular Dichroism and assessed qualitatively and quantitatively the histone binding properties of wild-type protein and mutant forms using GST-pull down experiments and fluorescence spectroscopy-based binding assays. Results Wild type SET/TAF-Iβ binds to histones H2B and H3 with Kd values of 2.87 and 0.15 μM, respectively. The preferential binding of SET/TAF-Iβ to histone H3 is mediated by its central region and the globular part of H3. On the contrary, the acidic C-terminal tail and the amino-terminal dimerisation domain of SET/TAF-Iβ, as well as the H3 amino-terminal tail, are dispensable for this interaction. Conclusion This type of analysis allowed us to assess the relative affinities of SET/TAF-Iβ for different histones and identify the domains of the protein required for effective histone recognition. Our findings are consistent with recent structural studies of SET/TAF-Iβ and can be valuable to understand the role of SET/TAF-Iβ in chromatin function. PMID:19358706
Identification of distinct SET/TAF-Ibeta domains required for core histone binding and quantitative characterisation of the interaction.

PubMed

Karetsou, Zoe; Emmanouilidou, Anastasia; Sanidas, Ioannis; Liokatis, Stamatis; Nikolakaki, Eleni; Politou, Anastasia S; Papamarcaki, Thomais

2009-04-09

The assembly of nucleosomes to higher-order chromatin structures is finely tuned by the relative affinities of histones for chaperones and nucleosomal binding sites. The myeloid leukaemia protein SET/TAF-Ibeta belongs to the NAP1 family of histone chaperones and participates in several chromatin-based mechanisms, such as chromatin assembly, nucleosome reorganisation and transcriptional activation. To better understand the histone chaperone function of SET/TAF-Ibeta, we designed several SET/TAF-Ibeta truncations, examined their structural integrity by circular Dichroism and assessed qualitatively and quantitatively the histone binding properties of wild-type protein and mutant forms using GST-pull down experiments and fluorescence spectroscopy-based binding assays. Wild type SET/TAF-Ibeta binds to histones H2B and H3 with Kd values of 2.87 and 0.15 microM, respectively. The preferential binding of SET/TAF-Ibeta to histone H3 is mediated by its central region and the globular part of H3. On the contrary, the acidic C-terminal tail and the amino-terminal dimerisation domain of SET/TAF-Ibeta, as well as the H3 amino-terminal tail, are dispensable for this interaction. This type of analysis allowed us to assess the relative affinities of SET/TAF-Ibeta for different histones and identify the domains of the protein required for effective histone recognition. Our findings are consistent with recent structural studies of SET/TAF-Ibeta and can be valuable to understand the role of SET/TAF-Ibeta in chromatin function.
A genome-wide structure-based survey of nucleotide binding proteins in M. tuberculosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhagavat, Raghu; Kim, Heung -Bok; Kim, Chang -Yub

Nucleoside tri-phosphates (NTP) form an important class of small molecule ligands that participate in, and are essential to a large number of biological processes. Here, we seek to identify the NTP binding proteome (NTPome) in M. tuberculosis (M.tb), a deadly pathogen. Identifying the NTPome is useful not only for gaining functional insights of the individual proteins but also for identifying useful drug targets. From an earlier study, we had structural models of M.tb at a proteome scale from which a set of 13,858 small molecule binding pockets were identified. We use a set of NTP binding sub-structural motifs derived frommore » a previous study and scan the M.tb pocketome, and find that 1,768 proteins or 43% of the proteome can theoretically bind NTP ligands. Using an experimental proteomics approach involving dye-ligand affinity chromatography, we confirm NTP binding to 47 different proteins, of which 4 are hypothetical proteins. Our analysis also provides the precise list of binding site residues in each case, and the probable ligand binding pose. In conclusion, as the list includes a number of known and potential drug targets, the identification of NTP binding can directly facilitate structure-based drug design of these targets.« less
A genome-wide structure-based survey of nucleotide binding proteins in M. tuberculosis

DOE PAGES

Bhagavat, Raghu; Kim, Heung -Bok; Kim, Chang -Yub; ...

2017-10-02

Nucleoside tri-phosphates (NTP) form an important class of small molecule ligands that participate in, and are essential to a large number of biological processes. Here, we seek to identify the NTP binding proteome (NTPome) in M. tuberculosis (M.tb), a deadly pathogen. Identifying the NTPome is useful not only for gaining functional insights of the individual proteins but also for identifying useful drug targets. From an earlier study, we had structural models of M.tb at a proteome scale from which a set of 13,858 small molecule binding pockets were identified. We use a set of NTP binding sub-structural motifs derived frommore » a previous study and scan the M.tb pocketome, and find that 1,768 proteins or 43% of the proteome can theoretically bind NTP ligands. Using an experimental proteomics approach involving dye-ligand affinity chromatography, we confirm NTP binding to 47 different proteins, of which 4 are hypothetical proteins. Our analysis also provides the precise list of binding site residues in each case, and the probable ligand binding pose. In conclusion, as the list includes a number of known and potential drug targets, the identification of NTP binding can directly facilitate structure-based drug design of these targets.« less
Electrostatic contribution to the binding stability of protein-protein complexes.

PubMed

Dong, Feng; Zhou, Huan-Xiang

2006-10-01

To investigate roles of electrostatic interactions in protein binding stability, electrostatic calculations were carried out on a set of 64 mutations over six protein-protein complexes. These mutations alter polar interactions across the interface and were selected for putative dominance of electrostatic contributions to the binding stability. Three protocols of implementing the Poisson-Boltzmann model were tested. In vdW4 the dielectric boundary between the protein low dielectric and the solvent high dielectric is defined as the protein van der Waals surface and the protein dielectric constant is set to 4. In SE4 and SE20, the dielectric boundary is defined as the surface of the protein interior inaccessible to a 1.4-A solvent probe, and the protein dielectric constant is set to 4 and 20, respectively. In line with earlier studies on the barnase-barstar complex, the vdW4 results on the large set of mutations showed the closest agreement with experimental data. The agreement between vdW4 and experiment supports the contention of dominant electrostatic contributions for the mutations, but their differences also suggest van der Waals and hydrophobic contributions. The results presented here will serve as a guide for future refinement in electrostatic calculation and inclusion of nonelectrostatic effects. Proteins 2006. (c) 2006 Wiley-Liss, Inc.
GalaxyDock BP2 score: a hybrid scoring function for accurate protein-ligand docking

NASA Astrophysics Data System (ADS)

Baek, Minkyung; Shin, Woong-Hee; Chung, Hwan Won; Seok, Chaok

2017-07-01

Protein-ligand docking is a useful tool for providing atomic-level understanding of protein functions in nature and design principles for artificial ligands or proteins with desired properties. The ability to identify the true binding pose of a ligand to a target protein among numerous possible candidate poses is an essential requirement for successful protein-ligand docking. Many previously developed docking scoring functions were trained to reproduce experimental binding affinities and were also used for scoring binding poses. However, in this study, we developed a new docking scoring function, called GalaxyDock BP2 Score, by directly training the scoring power of binding poses. This function is a hybrid of physics-based, empirical, and knowledge-based score terms that are balanced to strengthen the advantages of each component. The performance of the new scoring function exhibits significant improvement over existing scoring functions in decoy pose discrimination tests. In addition, when the score is used with the GalaxyDock2 protein-ligand docking program, it outperformed other state-of-the-art docking programs in docking tests on the Astex diverse set, the Cross2009 benchmark set, and the Astex non-native set. GalaxyDock BP2 Score and GalaxyDock2 with this score are freely available at http://galaxy.seoklab.org/softwares/galaxydock.html.
A signaling role of histone-binding proteins and INHAT subunits pp32 and Set/TAF-Ibeta in integrating chromatin hypoacetylation and transcriptional repression.

PubMed

Kutney, Sara N; Hong, Rui; Macfarlan, Todd; Chakravarti, Debabrata

2004-07-16

Various post-translational modifications of histones significantly influence gene transcription. Although un- or hypoacetylated histones are tightly linked to transcriptional repression, the mechanisms and identities of chromatin signal transducer proteins integrating histone hypoacetylation into repression in humans have remained largely unknown. Here we show that the mammalian histone-binding proteins and inhibitor of acetyltransferases (INHAT) complex subunits, Set/template-activating factor-Ibeta (TAF-Ibeta) and pp32, specifically bind to unacetylated, hypoacetylated, and repressively marked histones but not to hyperacetylated histones. Additionally, Set/TAF-Ibeta and pp32 associate with histone deacetylases in vitro and in vivo and repress transcription from a chromatin-integrated template in vivo. Finally, Set/TAF-Ibeta and pp32 associate with an endogenous estrogen receptor-regulated gene, EB1, in the hypoacetylated transcriptionally inactive state but not with the hyperacetylated transcriptionally active form. Together, these data define a novel in vivo mechanistic role for the mammalian Set/TAF-Ibeta and pp32 proteins as transducers of chromatin signaling by integrating chromatin hypoacetylation and transcriptional repression.
Template-Based Modeling of Protein-RNA Interactions.

PubMed

Zheng, Jinfang; Kundrotas, Petras J; Vakser, Ilya A; Liu, Shiyong

2016-09-01

Protein-RNA complexes formed by specific recognition between RNA and RNA-binding proteins play an important role in biological processes. More than a thousand of such proteins in human are curated and many novel RNA-binding proteins are to be discovered. Due to limitations of experimental approaches, computational techniques are needed for characterization of protein-RNA interactions. Although much progress has been made, adequate methodologies reliably providing atomic resolution structural details are still lacking. Although protein-RNA free docking approaches proved to be useful, in general, the template-based approaches provide higher quality of predictions. Templates are key to building a high quality model. Sequence/structure relationships were studied based on a representative set of binary protein-RNA complexes from PDB. Several approaches were tested for pairwise target/template alignment. The analysis revealed a transition point between random and correct binding modes. The results showed that structural alignment is better than sequence alignment in identifying good templates, suitable for generating protein-RNA complexes close to the native structure, and outperforms free docking, successfully predicting complexes where the free docking fails, including cases of significant conformational change upon binding. A template-based protein-RNA interaction modeling protocol PRIME was developed and benchmarked on a representative set of complexes.
Exploring the free-energy landscape of carbohydrate-protein complexes: development and validation of scoring functions considering the binding-site topology

NASA Astrophysics Data System (ADS)

Eid, Sameh; Saleh, Noureldin; Zalewski, Adam; Vedani, Angelo

2014-12-01

Carbohydrates play a key role in a variety of physiological and pathological processes and, hence, represent a rich source for the development of novel therapeutic agents. Being able to predict binding mode and binding affinity is an essential, yet lacking, aspect of the structure-based design of carbohydrate-based ligands. We assembled a diverse data set comprising 273 carbohydrate-protein crystal structures with known binding affinity and evaluated the prediction accuracy of a large collection of well-established scoring and free-energy functions, as well as combinations thereof. Unfortunately, the tested functions were not capable of reproducing binding affinities in the studied complexes. To simplify the complex free-energy surface of carbohydrate-protein systems, we classified the studied proteins according to the topology and solvent exposure of the carbohydrate-binding site into five distinct categories. A free-energy model based on the proposed classification scheme reproduced binding affinities in the carbohydrate data set with an r 2 of 0.71 and root-mean-squared-error of 1.25 kcal/mol ( N = 236). The improvement in model performance underlines the significance of the differences in the local micro-environments of carbohydrate-binding sites and demonstrates the usefulness of calibrating free-energy functions individually according to binding-site topology and solvent exposure.

Transport capabilities of environmental Pseudomonads for sulfur compounds

DOE PAGES

Zerbs, Sarah; Korajczyk, Peter J.; Noirot, Philippe H.; ...

2017-01-27

Sulfur is an essential element in plant rhizospheres and microbial activity plays a key role in increasing the biological availability of sulfur in soil environments. To better understand the mechanisms facilitating the exchange of sulfur-containing molecules in soil, we profiled the binding specificities of eight previously uncharacterized ABC transporter solute-binding proteins from plant-associated Pseudomonads. A high-throughput screening procedure indicated eighteen significant organosulfur binding ligands, with at least one high-quality screening hit for each protein target. Calorimetric and spectroscopic methods were used to validate the best ligand assignments and catalog the thermodynamic properties of the protein-ligand interactions. Two novel high-affinity ligandmore » binding activities were identified and quantified in this set of solute binding proteins. Bacteria were cultured in minimal media with screening library components supplied as the sole sulfur sources, demonstrating that these organosulfur compounds can be metabolized and confirming the relevance of ligand assignments. These results expand the set of experimentally validated ligands amenable to transport by this ABC transporter family and demonstrate the complex range of protein-ligand interactions that can be accomplished by solute-binding proteins. As a result, characterizing new nutrient import pathways provides insight into Pseudomonad metabolic capabilities which can be used to further interrogate bacterial survival and participation in soil and rhizosphere communities.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)

Zerbs, Sarah; Korajczyk, Peter J.; Noirot, Philippe H.

Sulfur is an essential element in plant rhizospheres and microbial activity plays a key role in increasing the biological availability of sulfur in soil environments. To better understand the mechanisms facilitating the exchange of sulfur-containing molecules in soil, we profiled the binding specificities of eight previously uncharacterized ABC transporter solute-binding proteins from plant-associated Pseudomonads. A high-throughput screening procedure indicated eighteen significant organosulfur binding ligands, with at least one high-quality screening hit for each protein target. Calorimetric and spectroscopic methods were used to validate the best ligand assignments and catalog the thermodynamic properties of the protein-ligand interactions. Two novel high-affinity ligandmore » binding activities were identified and quantified in this set of solute binding proteins. Bacteria were cultured in minimal media with screening library components supplied as the sole sulfur sources, demonstrating that these organosulfur compounds can be metabolized and confirming the relevance of ligand assignments. These results expand the set of experimentally validated ligands amenable to transport by this ABC transporter family and demonstrate the complex range of protein-ligand interactions that can be accomplished by solute-binding proteins. As a result, characterizing new nutrient import pathways provides insight into Pseudomonad metabolic capabilities which can be used to further interrogate bacterial survival and participation in soil and rhizosphere communities.« less
PepComposer: computational design of peptides binding to a given protein surface

PubMed Central

Obarska-Kosinska, Agnieszka; Iacoangeli, Alfredo; Lepore, Rosalba; Tramontano, Anna

2016-01-01

There is a wide interest in designing peptides able to bind to a specific region of a protein with the aim of interfering with a known interaction or as starting point for the design of inhibitors. Here we describe PepComposer, a new pipeline for the computational design of peptides binding to a given protein surface. PepComposer only requires the target protein structure and an approximate definition of the binding site as input. We first retrieve a set of peptide backbone scaffolds from monomeric proteins that harbor the same backbone arrangement as the binding site of the protein of interest. Next, we design optimal sequences for the identified peptide scaffolds. The method is fully automatic and available as a web server at http://biocomputing.it/pepcomposer/webserver. PMID:27131789
RNA-binding Protein Immunoprecipitation (RIP) to Examine AUF1 Binding to Senescence-Associated Secretory Phenotype (SASP) Factor mRNA

PubMed Central

Alspach, Elise; Stewart, Sheila A.

2016-01-01

Immunoprecipitation and subsequent isolation of nucleic acids allows for the investigation of protein:nucleic acid interactions. RNA-binding protein immunoprecipitation (RIP) is used for the analysis of protein interactions with mRNA. Combining RIP with quantitative real-time PCR (qRT-PCR) further enhances the RIP technique by allowing for the quantitative assessment of RNA-binding protein interactions with their target mRNAs, and how these interactions change in different cellular settings. Here, we describe the immunoprecipitation of the RNA-binding protein AUF1 with several different factors associated with the senescence-associated secretory phenotype (SASP) (Alspach and Stewart, 2013), specifically IL6 and IL8. This protocol was originally published in Alspach et al. (2014). PMID:27453911
Extracting sets of chemical substructures and protein domains governing drug-target interactions.

PubMed

Yamanishi, Yoshihiro; Pauwels, Edouard; Saigo, Hiroto; Stoven, Véronique

2011-05-23

The identification of rules governing molecular recognition between drug chemical substructures and protein functional sites is a challenging issue at many stages of the drug development process. In this paper we develop a novel method to extract sets of drug chemical substructures and protein domains that govern drug-target interactions on a genome-wide scale. This is made possible using sparse canonical correspondence analysis (SCCA) for analyzing drug substructure profiles and protein domain profiles simultaneously. The method does not depend on the availability of protein 3D structures. From a data set of known drug-target interactions including enzymes, ion channels, G protein-coupled receptors, and nuclear receptors, we extract a set of chemical substructures shared by drugs able to bind to a set of protein domains. These two sets of extracted chemical substructures and protein domains form components that can be further exploited in a drug discovery process. This approach successfully clusters protein domains that may be evolutionary unrelated but that bind a common set of chemical substructures. As shown in several examples, it can also be very helpful for predicting new protein-ligand interactions and addressing the problem of ligand specificity. The proposed method constitutes a contribution to the recent field of chemogenomics that aims to connect the chemical space with the biological space.
Structural deformation upon protein-protein interaction: A structural alphabet approach

PubMed Central

Martin, Juliette; Regad, Leslie; Lecornet, Hélène; Camproux, Anne-Claude

2008-01-01

Background In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding. Results In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%). This proportion is even greater in the interface regions (41%). Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins. Conclusion Our study provides qualitative information about induced fit. These results could be of help for flexible docking. PMID:18307769
Structural deformation upon protein-protein interaction: a structural alphabet approach.

PubMed

Martin, Juliette; Regad, Leslie; Lecornet, Hélène; Camproux, Anne-Claude

2008-02-28

In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding. In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%). This proportion is even greater in the interface regions (41%). Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins. Our study provides qualitative information about induced fit. These results could be of help for flexible docking.
Accurate prediction of RNA-binding protein residues with two discriminative structural descriptors.

PubMed

Sun, Meijian; Wang, Xia; Zou, Chuanxin; He, Zenghui; Liu, Wei; Li, Honglin

2016-06-07

RNA-binding proteins participate in many important biological processes concerning RNA-mediated gene regulation, and several computational methods have been recently developed to predict the protein-RNA interactions of RNA-binding proteins. Newly developed discriminative descriptors will help to improve the prediction accuracy of these prediction methods and provide further meaningful information for researchers. In this work, we designed two structural features (residue electrostatic surface potential and triplet interface propensity) and according to the statistical and structural analysis of protein-RNA complexes, the two features were powerful for identifying RNA-binding protein residues. Using these two features and other excellent structure- and sequence-based features, a random forest classifier was constructed to predict RNA-binding residues. The area under the receiver operating characteristic curve (AUC) of five-fold cross-validation for our method on training set RBP195 was 0.900, and when applied to the test set RBP68, the prediction accuracy (ACC) was 0.868, and the F-score was 0.631. The good prediction performance of our method revealed that the two newly designed descriptors could be discriminative for inferring protein residues interacting with RNAs. To facilitate the use of our method, a web-server called RNAProSite, which implements the proposed method, was constructed and is freely available at http://lilab.ecust.edu.cn/NABind .
Predicting "Hot" and "Warm" Spots for Fragment Binding.

PubMed

Rathi, Prakash Chandra; Ludlow, R Frederick; Hall, Richard J; Murray, Christopher W; Mortenson, Paul N; Verdonk, Marcel L

2017-05-11

Computational fragment mapping methods aim to predict hotspots on protein surfaces where small fragments will bind. Such methods are popular for druggability assessment as well as structure-based design. However, to date researchers developing or using such tools have had no clear way of assessing the performance of these methods. Here, we introduce the first diverse, high quality validation set for computational fragment mapping. The set contains 52 diverse examples of fragment binding "hot" and "warm" spots from the Protein Data Bank (PDB). Additionally, we describe PLImap, a novel protocol for fragment mapping based on the Protein-Ligand Informatics force field (PLIff). We evaluate PLImap against the new fragment mapping test set, and compare its performance to that of simple shape-based algorithms and fragment docking using GOLD. PLImap is made publicly available from https://bitbucket.org/AstexUK/pli .
Template-Based Modeling of Protein-RNA Interactions

PubMed Central

Zheng, Jinfang; Kundrotas, Petras J.; Vakser, Ilya A.

2016-01-01

Protein-RNA complexes formed by specific recognition between RNA and RNA-binding proteins play an important role in biological processes. More than a thousand of such proteins in human are curated and many novel RNA-binding proteins are to be discovered. Due to limitations of experimental approaches, computational techniques are needed for characterization of protein-RNA interactions. Although much progress has been made, adequate methodologies reliably providing atomic resolution structural details are still lacking. Although protein-RNA free docking approaches proved to be useful, in general, the template-based approaches provide higher quality of predictions. Templates are key to building a high quality model. Sequence/structure relationships were studied based on a representative set of binary protein-RNA complexes from PDB. Several approaches were tested for pairwise target/template alignment. The analysis revealed a transition point between random and correct binding modes. The results showed that structural alignment is better than sequence alignment in identifying good templates, suitable for generating protein-RNA complexes close to the native structure, and outperforms free docking, successfully predicting complexes where the free docking fails, including cases of significant conformational change upon binding. A template-based protein-RNA interaction modeling protocol PRIME was developed and benchmarked on a representative set of complexes. PMID:27662342
How Proteins Bind Macrocycles

PubMed Central

Villar, Elizabeth A.; Beglov, Dmitri; Chennamadhavuni, Spandan; Porco, John A.; Kozakov, Dima; Vajda, Sandor; Whitty, Adrian

2014-01-01

The potential utility of synthetic macrocycles as drugs, particularly against low druggability targets such as protein-protein interactions, has been widely discussed. There is little information, however, to guide the design of macrocycles for good target protein-binding activity or bioavailability. To address this knowledge gap we analyze the binding modes of a representative set of macrocycle-protein complexes. The results, combined with consideration of the physicochemical properties of approved macrocyclic drugs, allow us to propose specific guidelines for the design of synthetic macrocycles libraries possessing structural and physicochemical features likely to favor strong binding to protein targets and also good bioavailability. We additionally provide evidence that large, natural product derived macrocycles can bind to targets that are not druggable by conventional, drug-like compounds, supporting the notion that natural product inspired synthetic macrocycles can expand the number of proteins that are druggable by synthetic small molecules. PMID:25038790
Structured and Unstructured Binding of an Intrinsically Disordered Protein as Revealed by Atomistic Simulations.

PubMed

Ithuralde, Raúl Esteban; Roitberg, Adrián Enrique; Turjanski, Adrián Gustavo

2016-07-20

Intrinsically disordered proteins (IDPs) are a set of proteins that lack a definite secondary structure in solution. IDPs can acquire tertiary structure when bound to their partners; therefore, the recognition process must also involve protein folding. The nature of the transition state (TS), structured or unstructured, determines the binding mechanism. The characterization of the TS has become a major challenge for experimental techniques and molecular simulations approaches since diffusion, recognition, and binding is coupled to folding. In this work we present atomistic molecular dynamics (MD) simulations that sample the free energy surface of the coupled folding and binding of the transcription factor c-myb to the cotranscription factor CREB binding protein (CBP). This process has been recently studied and became a model to study IDPs. Despite the plethora of available information, we still do not know how c-myb binds to CBP. We performed a set of atomistic biased MD simulations running a total of 15.6 μs. Our results show that c-myb folds very fast upon binding to CBP with no unique pathway for binding. The process can proceed through both structured or unstructured TS's with similar probabilities. This finding reconciles previous seemingly different experimental results. We also performed Go-type coarse-grained MD of several structured and unstructured models that indicate that coupled folding and binding follows a native contact mechanism. To the best of our knowledge, this is the first atomistic MD simulation that samples the free energy surface of the coupled folding and binding processes of IDPs.
Proteomic analysis of trichloroethylene-induced alterations in expression, distribution, and interactions of SET/TAF-Iα and two SET/TAF-Iα-binding proteins, eEF1A1 and eEF1A2, in hepatic L-02 cells.

PubMed

Hong, Wen-Xu; Yang, Liang; Chen, Moutong; Yang, Xifei; Ren, Xiaohu; Fang, Shisong; Ye, Jinbo; Huang, Haiyan; Peng, Chaoqiong; Zhou, Li; Huang, Xinfeng; Yang, Fan; Wu, Desheng; Zhuang, Zhixiong; Liu, Jianjun

2012-09-01

Emerging evidence indicates that trichloroethylene (TCE) exposure causes severe hepatotoxicity. However, the mechanisms of TCE hepatotoxicity remain unclear. Recently, we reported that TCE exposure up-regulated the expression of the oncoprotein SET/TAF-Iα and SET knockdown attenuated TCE-induced cytotoxicity in hepatic L-02 cells. To decipher the function of SET/TAF-Iα and its contributions to TCE-induced hepatotoxicity, we employed a proteomic analysis of SET/TAF-Iα with tandem affinity purification to identify SET/TAF-Iα-binding proteins. We identified 42 novel Gene Ontology co-annotated SET/TAF-Iα-binding proteins. The identifications of two of these proteins (eEF1A1, elongation factor 1-alpha 1; eEF1A2, elongation factor 1-alpha 2) were confirmed by Western blot analysis and co-immunoprecipitation (Co-IP). Furthermore, we analyzed the effects of TCE on the expression, distribution and interactions of eEF1A1, eEF1A2 and SET in L-02 cells. Western blot analysis reveals a significant up-regulation of eEF1A1, eEF1A2 and two isoforms of SET, and immunocytochemical analysis reveals that eEF1A1 and SET is redistributed by TCE. SET is redistributed from the nucleus to the cytoplasm, while eFE1A1 is translocated from the cytoplasm to the nucleus. Moreover, we find by Co-IP that TCE exposure significantly increases the interaction of SET with eEF1A2. Our data not only provide insights into the physiological functions of SET/TAF-Iα and complement the SET interaction networks, but also demonstrate that TCE exposure induces alterations in the expression, distribution and interactions of SET and its binding partners. These alterations may constitute the mechanisms of TCE cytotoxicity. Copyright © 2012 Elsevier Inc. All rights reserved.
Biotin-c10-AppCH2ppA is an effective new chemical proteomics probe for diadenosine polyphosphate binding proteins.

PubMed

Azhar, M Ameruddin; Wright, Michael; Kamal, Ahmed; Nagy, Judith; Miller, Andrew D

2014-07-01

Here we report on the synthesis of a synthetic, stable biotin-c10-AppCH2ppA conjugate involving an unusual Cannizzaro reaction step. This conjugate is used to bind prospective Ap4A binding proteins from Escherichia coli bacterial cell lyzates. Following binding, identities of these proteins are then determined smoothly by a process of magnetic bio-panning and electrospray mass spectrometry. Protein hits appear to be a definitive set of stress protein related targets. While this hit list may not be exclusive, and may vary with the nature of sampling conditions and organism status, nevertheless hits do appear to correspond with bona fide Ap4A-binding proteins. Therefore these hits represent a sound basis on which to construct new hypotheses concerning the cellular importance of Ap4A to bacterial cells and the potential biological significance of Ap4A-protein binding interactions. Copyright © 2014. Published by Elsevier Ltd.
Prediction of fatty acid-binding residues on protein surfaces with three-dimensional probability distributions of interacting atoms.

PubMed

Mahalingam, Rajasekaran; Peng, Hung-Pin; Yang, An-Suei

2014-08-01

Protein-fatty acid interaction is vital for many cellular processes and understanding this interaction is important for functional annotation as well as drug discovery. In this work, we present a method for predicting the fatty acid (FA)-binding residues by using three-dimensional probability density distributions of interacting atoms of FAs on protein surfaces which are derived from the known protein-FA complex structures. A machine learning algorithm was established to learn the characteristic patterns of the probability density maps specific to the FA-binding sites. The predictor was trained with five-fold cross validation on a non-redundant training set and then evaluated with an independent test set as well as on holo-apo pair's dataset. The results showed good accuracy in predicting the FA-binding residues. Further, the predictor developed in this study is implemented as an online server which is freely accessible at the following website, http://ismblab.genomics.sinica.edu.tw/. Copyright © 2014 Elsevier B.V. All rights reserved.
Computation of pH-Dependent Binding Free Energies

PubMed Central

Kim, M. Olivia; McCammon, J. Andrew

2015-01-01

Protein-ligand binding accompanies changes in the surrounding electrostatic environments of the two binding partners and may lead to changes in protonation upon binding. In cases where the complex formation results in a net transfer of protons, the binding process is pH-dependent. However, conventional free energy computations or molecular docking protocols typically employ fixed protonation states for the titratable groups in both binding partners set a priori, which are identical for the free and bound states. In this review, we draw attention to these important yet largely ignored binding-induced protonation changes in protein-ligand association by outlining physical origins and prevalence of the protonation changes upon binding. Following a summary of various theoretical methods for pKa prediction, we discuss the theoretical framework to examine the pH dependence of protein-ligand binding processes. PMID:26202905
Large scale analysis of protein-binding cavities using self-organizing maps and wavelet-based surface patches to describe functional properties, selectivity discrimination, and putative cross-reactivity.

PubMed

Kupas, Katrin; Ultsch, Alfred; Klebe, Gerhard

2008-05-15

A new method to discover similar substructures in protein binding pockets, independently of sequence and folding patterns or secondary structure elements, is introduced. The solvent-accessible surface of a binding pocket, automatically detected as a depression on the protein surface, is divided into a set of surface patches. Each surface patch is characterized by its shape as well as by its physicochemical characteristics. Wavelets defined on surfaces are used for the description of the shape, as they have the great advantage of allowing a comparison at different resolutions. The number of coefficients to describe the wavelets can be chosen with respect to the size of the considered data set. The physicochemical characteristics of the patches are described by the assignment of the exposed amino acid residues to one or more of five different properties determinant for molecular recognition. A self-organizing neural network is used to project the high-dimensional feature vectors onto a two-dimensional layer of neurons, called a map. To find similarities between the binding pockets, in both geometrical and physicochemical features, a clustering of the projected feature vector is performed using an automatic distance- and density-based clustering algorithm. The method was validated with a small training data set of 109 binding cavities originating from a set of enzymes covering 12 different EC numbers. A second test data set of 1378 binding cavities, extracted from enzymes of 13 different EC numbers, was then used to prove the discriminating power of the algorithm and to demonstrate its applicability to large scale analyses. In all cases, members of the data set with the same EC number were placed into coherent regions on the map, with small distances between them. Different EC numbers are separated by large distances between the feature vectors. A third data set comprising three subfamilies of endopeptidases is used to demonstrate the ability of the algorithm to detect similar substructures between functionally related active sites. The algorithm can also be used to predict the function of novel proteins not considered in training data set. 2007 Wiley-Liss, Inc.
Fascin- and α-Actinin-Bundled Networks Contain Intrinsic Structural Features that Drive Protein Sorting.

PubMed

Winkelman, Jonathan D; Suarez, Cristian; Hocky, Glen M; Harker, Alyssa J; Morganthaler, Alisha N; Christensen, Jenna R; Voth, Gregory A; Bartles, James R; Kovar, David R

2016-10-24

Cells assemble and maintain functionally distinct actin cytoskeleton networks with various actin filament organizations and dynamics through the coordinated action of different sets of actin-binding proteins. The biochemical and functional properties of diverse actin-binding proteins, both alone and in combination, have been increasingly well studied. Conversely, how different sets of actin-binding proteins properly sort to distinct actin filament networks in the first place is not nearly as well understood. Actin-binding protein sorting is critical for the self-organization of diverse dynamic actin cytoskeleton networks within a common cytoplasm. Using in vitro reconstitution techniques including biomimetic assays and single-molecule multi-color total internal reflection fluorescence microscopy, we discovered that sorting of the prominent actin-bundling proteins fascin and α-actinin to distinct networks is an intrinsic behavior, free of complicated cellular signaling cascades. When mixed, fascin and α-actinin mutually exclude each other by promoting their own recruitment and inhibiting recruitment of the other, resulting in the formation of distinct fascin- or α-actinin-bundled domains. Subdiffraction-resolution light microscopy and negative-staining electron microscopy revealed that fascin domains are densely packed, whereas α-actinin domains consist of widely spaced parallel actin filaments. Importantly, other actin-binding proteins such as fimbrin and espin show high specificity between these two bundle types within the same reaction. Here we directly observe that fascin and α-actinin intrinsically segregate to discrete bundled domains that are specifically recognized by other actin-binding proteins. Copyright © 2016 Elsevier Ltd. All rights reserved.
RNABindRPlus: a predictor that combines machine learning and sequence homology-based methods to improve the reliability of predicted RNA-binding residues in proteins.

PubMed

Walia, Rasna R; Xue, Li C; Wilkins, Katherine; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2014-01-01

Protein-RNA interactions are central to essential cellular processes such as protein synthesis and regulation of gene expression and play roles in human infectious and genetic diseases. Reliable identification of protein-RNA interfaces is critical for understanding the structural bases and functional implications of such interactions and for developing effective approaches to rational drug design. Sequence-based computational methods offer a viable, cost-effective way to identify putative RNA-binding residues in RNA-binding proteins. Here we report two novel approaches: (i) HomPRIP, a sequence homology-based method for predicting RNA-binding sites in proteins; (ii) RNABindRPlus, a new method that combines predictions from HomPRIP with those from an optimized Support Vector Machine (SVM) classifier trained on a benchmark dataset of 198 RNA-binding proteins. Although highly reliable, HomPRIP cannot make predictions for the unaligned parts of query proteins and its coverage is limited by the availability of close sequence homologs of the query protein with experimentally determined RNA-binding sites. RNABindRPlus overcomes these limitations. We compared the performance of HomPRIP and RNABindRPlus with that of several state-of-the-art predictors on two test sets, RB44 and RB111. On a subset of proteins for which homologs with experimentally determined interfaces could be reliably identified, HomPRIP outperformed all other methods achieving an MCC of 0.63 on RB44 and 0.83 on RB111. RNABindRPlus was able to predict RNA-binding residues of all proteins in both test sets, achieving an MCC of 0.55 and 0.37, respectively, and outperforming all other methods, including those that make use of structure-derived features of proteins. More importantly, RNABindRPlus outperforms all other methods for any choice of tradeoff between precision and recall. An important advantage of both HomPRIP and RNABindRPlus is that they rely on readily available sequence and sequence-derived features of RNA-binding proteins. A webserver implementation of both methods is freely available at http://einstein.cs.iastate.edu/RNABindRPlus/.
Identification of protein-ligand binding sites by the level-set variational implicit-solvent approach.

PubMed

Guo, Zuojun; Li, Bo; Cheng, Li-Tien; Zhou, Shenggao; McCammon, J Andrew; Che, Jianwei

2015-02-10

Protein–ligand binding is a key biological process at the molecular level. The identification and characterization of small-molecule binding sites on therapeutically relevant proteins have tremendous implications for target evaluation and rational drug design. In this work, we used the recently developed level-set variational implicit-solvent model (VISM) with the Coulomb field approximation (CFA) to locate and characterize potential protein–small-molecule binding sites. We applied our method to a data set of 515 protein–ligand complexes and found that 96.9% of the cocrystallized ligands bind to the VISM-CFA-identified pockets and that 71.8% of the identified pockets are occupied by cocrystallized ligands. For 228 tight-binding protein–ligand complexes (i.e, complexes with experimental pKd values larger than 6), 99.1% of the cocrystallized ligands are in the VISM-CFA-identified pockets. In addition, it was found that the ligand binding orientations are consistent with the hydrophilic and hydrophobic descriptions provided by VISM. Quantitative characterization of binding pockets with topological and physicochemical parameters was used to assess the “ligandability” of the pockets. The results illustrate the key interactions between ligands and receptors and can be very informative for rational drug design.

Automated large-scale file preparation, docking, and scoring: evaluation of ITScore and STScore using the 2012 Community Structure-Activity Resource benchmark.

PubMed

Grinter, Sam Z; Yan, Chengfei; Huang, Sheng-You; Jiang, Lin; Zou, Xiaoqin

2013-08-26

In this study, we use the recently released 2012 Community Structure-Activity Resource (CSAR) data set to evaluate two knowledge-based scoring functions, ITScore and STScore, and a simple force-field-based potential (VDWScore). The CSAR data set contains 757 compounds, most with known affinities, and 57 crystal structures. With the help of the script files for docking preparation, we use the full CSAR data set to evaluate the performances of the scoring functions on binding affinity prediction and active/inactive compound discrimination. The CSAR subset that includes crystal structures is used as well, to evaluate the performances of the scoring functions on binding mode and affinity predictions. Within this structure subset, we investigate the importance of accurate ligand and protein conformational sampling and find that the binding affinity predictions are less sensitive to non-native ligand and protein conformations than the binding mode predictions. We also find the full CSAR data set to be more challenging in making binding mode predictions than the subset with structures. The script files used for preparing the CSAR data set for docking, including scripts for canonicalization of the ligand atoms, are offered freely to the academic community.
Predicting and analyzing DNA-binding domains using a systematic approach to identifying a set of informative physicochemical and biochemical properties

PubMed Central

2011-01-01

Background Existing methods of predicting DNA-binding proteins used valuable features of physicochemical properties to design support vector machine (SVM) based classifiers. Generally, selection of physicochemical properties and determination of their corresponding feature vectors rely mainly on known properties of binding mechanism and experience of designers. However, there exists a troublesome problem for designers that some different physicochemical properties have similar vectors of representing 20 amino acids and some closely related physicochemical properties have dissimilar vectors. Results This study proposes a systematic approach (named Auto-IDPCPs) to automatically identify a set of physicochemical and biochemical properties in the AAindex database to design SVM-based classifiers for predicting and analyzing DNA-binding domains/proteins. Auto-IDPCPs consists of 1) clustering 531 amino acid indices in AAindex into 20 clusters using a fuzzy c-means algorithm, 2) utilizing an efficient genetic algorithm based optimization method IBCGA to select an informative feature set of size m to represent sequences, and 3) analyzing the selected features to identify related physicochemical properties which may affect the binding mechanism of DNA-binding domains/proteins. The proposed Auto-IDPCPs identified m=22 features of properties belonging to five clusters for predicting DNA-binding domains with a five-fold cross-validation accuracy of 87.12%, which is promising compared with the accuracy of 86.62% of the existing method PSSM-400. For predicting DNA-binding sequences, the accuracy of 75.50% was obtained using m=28 features, where PSSM-400 has an accuracy of 74.22%. Auto-IDPCPs and PSSM-400 have accuracies of 80.73% and 82.81%, respectively, applied to an independent test data set of DNA-binding domains. Some typical physicochemical properties discovered are hydrophobicity, secondary structure, charge, solvent accessibility, polarity, flexibility, normalized Van Der Waals volume, pK (pK-C, pK-N, pK-COOH and pK-a(RCOOH)), etc. Conclusions The proposed approach Auto-IDPCPs would help designers to investigate informative physicochemical and biochemical properties by considering both prediction accuracy and analysis of binding mechanism simultaneously. The approach Auto-IDPCPs can be also applicable to predict and analyze other protein functions from sequences. PMID:21342579
Integration of element specific persistent homology and machine learning for protein-ligand binding affinity prediction.

PubMed

Cang, Zixuan; Wei, Guo-Wei

2018-02-01

Protein-ligand binding is a fundamental biological process that is paramount to many other biological processes, such as signal transduction, metabolic pathways, enzyme construction, cell secretion, and gene expression. Accurate prediction of protein-ligand binding affinities is vital to rational drug design and the understanding of protein-ligand binding and binding induced function. Existing binding affinity prediction methods are inundated with geometric detail and involve excessively high dimensions, which undermines their predictive power for massive binding data. Topology provides the ultimate level of abstraction and thus incurs too much reduction in geometric information. Persistent homology embeds geometric information into topological invariants and bridges the gap between complex geometry and abstract topology. However, it oversimplifies biological information. This work introduces element specific persistent homology (ESPH) or multicomponent persistent homology to retain crucial biological information during topological simplification. The combination of ESPH and machine learning gives rise to a powerful paradigm for macromolecular analysis. Tests on 2 large data sets indicate that the proposed topology-based machine-learning paradigm outperforms other existing methods in protein-ligand binding affinity predictions. ESPH reveals protein-ligand binding mechanism that can not be attained from other conventional techniques. The present approach reveals that protein-ligand hydrophobic interactions are extended to 40Å away from the binding site, which has a significant ramification to drug and protein design. Copyright © 2017 John Wiley & Sons, Ltd.
Deciphering Cryptic Binding Sites on Proteins by Mixed-Solvent Molecular Dynamics.

PubMed

Kimura, S Roy; Hu, Hai Peng; Ruvinsky, Anatoly M; Sherman, Woody; Favia, Angelo D

2017-06-26

In recent years, molecular dynamics simulations of proteins in explicit mixed solvents have been applied to various problems in protein biophysics and drug discovery, including protein folding, protein surface characterization, fragment screening, allostery, and druggability assessment. In this study, we perform a systematic study on how mixtures of organic solvent probes in water can reveal cryptic ligand binding pockets that are not evident in crystal structures of apo proteins. We examine a diverse set of eight PDB proteins that show pocket opening induced by ligand binding and investigate whether solvent MD simulations on the apo structures can induce the binding site observed in the holo structures. The cosolvent simulations were found to induce conformational changes on the protein surface, which were characterized and compared with the holo structures. Analyses of the biological systems, choice of probes and concentrations, druggability of the resulting induced pockets, and application to drug discovery are discussed here.
The Importance of Being Tyrosine: Lessons in Molecular Recognition from Minimalist Synthetic Binding Proteins

PubMed Central

Koide, Shohei; Sidhu, Sachdev S.

2010-01-01

Summary Combinatorial libraries built with severely restricted chemical diversity have yielded highly functional synthetic binding proteins. Structural analyses of these minimalist binding sites have revealed the dominant role of large tyrosine residues for mediating molecular contacts and of small serine/glycine residues for providing space and flexibility. The concept of using limited residue types to construct optimized binding proteins mirrors findings in the field of small molecule drug development, where it has been proposed that most drugs are built from a limited set of side chains presented by diverse frameworks. The physicochemical properties of tyrosine make it the amino acid that is most effective for mediating molecular recognition, and protein engineers have taken advantage of these characteristics to build tyrosine-rich protein binding sites that outperform natural proteins in terms of affinity and specificity. Knowledge from preceding studies can be used to improve current designs, and thus, synthetic protein libraries will continue to evolve and improve. In the near future, it seems likely that synthetic binding proteins will supersede natural antibodies for most purposes, and moreover, synthetic proteins will enable many new applications beyond the scope of natural proteins. PMID:19298050
Structural motif screening reveals a novel, conserved carbohydrate-binding surface in the pathogenesis-related protein PR-5d.

PubMed

Doxey, Andrew C; Cheng, Zhenyu; Moffatt, Barbara A; McConkey, Brendan J

2010-08-03

Aromatic amino acids play a critical role in protein-glycan interactions. Clusters of surface aromatic residues and their features may therefore be useful in distinguishing glycan-binding sites as well as predicting novel glycan-binding proteins. In this work, a structural bioinformatics approach was used to screen the Protein Data Bank (PDB) for coplanar aromatic motifs similar to those found in known glycan-binding proteins. The proteins identified in the screen were significantly associated with carbohydrate-related functions according to gene ontology (GO) enrichment analysis, and predicted motifs were found frequently within novel folds and glycan-binding sites not included in the training set. In addition to numerous binding sites predicted in structural genomics proteins of unknown function, one novel prediction was a surface motif (W34/W36/W192) in the tobacco pathogenesis-related protein, PR-5d. Phylogenetic analysis revealed that the surface motif is exclusive to a subfamily of PR-5 proteins from the Solanaceae family of plants, and is absent completely in more distant homologs. To confirm PR-5d's insoluble-polysaccharide binding activity, a cellulose-pulldown assay of tobacco proteins was performed and PR-5d was identified in the cellulose-binding fraction by mass spectrometry. Based on the combined results, we propose that the putative binding site in PR-5d may be an evolutionary adaptation of Solanaceae plants including potato, tomato, and tobacco, towards defense against cellulose-containing pathogens such as species of the deadly oomycete genus, Phytophthora. More generally, the results demonstrate that coplanar aromatic clusters on protein surfaces are a structural signature of glycan-binding proteins, and can be used to computationally predict novel glycan-binding proteins from 3 D structure.
Kinetic rate constant prediction supports the conformational selection mechanism of protein binding.

PubMed

Moal, Iain H; Bates, Paul A

2012-01-01

The prediction of protein-protein kinetic rate constants provides a fundamental test of our understanding of molecular recognition, and will play an important role in the modeling of complex biological systems. In this paper, a feature selection and regression algorithm is applied to mine a large set of molecular descriptors and construct simple models for association and dissociation rate constants using empirical data. Using separate test data for validation, the predicted rate constants can be combined to calculate binding affinity with accuracy matching that of state of the art empirical free energy functions. The models show that the rate of association is linearly related to the proportion of unbound proteins in the bound conformational ensemble relative to the unbound conformational ensemble, indicating that the binding partners must adopt a geometry near to that of the bound prior to binding. Mirroring the conformational selection and population shift mechanism of protein binding, the models provide a strong separate line of evidence for the preponderance of this mechanism in protein-protein binding, complementing structural and theoretical studies.
Prediction of Carbohydrate Binding Sites on Protein Surfaces with 3-Dimensional Probability Density Distributions of Interacting Atoms

PubMed Central

Tsai, Keng-Chang; Jian, Jhih-Wei; Yang, Ei-Wen; Hsu, Po-Chiang; Peng, Hung-Pin; Chen, Ching-Tai; Chen, Jun-Bo; Chang, Jeng-Yih; Hsu, Wen-Lian; Yang, An-Suei

2012-01-01

Non-covalent protein-carbohydrate interactions mediate molecular targeting in many biological processes. Prediction of non-covalent carbohydrate binding sites on protein surfaces not only provides insights into the functions of the query proteins; information on key carbohydrate-binding residues could suggest site-directed mutagenesis experiments, design therapeutics targeting carbohydrate-binding proteins, and provide guidance in engineering protein-carbohydrate interactions. In this work, we show that non-covalent carbohydrate binding sites on protein surfaces can be predicted with relatively high accuracy when the query protein structures are known. The prediction capabilities were based on a novel encoding scheme of the three-dimensional probability density maps describing the distributions of 36 non-covalent interacting atom types around protein surfaces. One machine learning model was trained for each of the 30 protein atom types. The machine learning algorithms predicted tentative carbohydrate binding sites on query proteins by recognizing the characteristic interacting atom distribution patterns specific for carbohydrate binding sites from known protein structures. The prediction results for all protein atom types were integrated into surface patches as tentative carbohydrate binding sites based on normalized prediction confidence level. The prediction capabilities of the predictors were benchmarked by a 10-fold cross validation on 497 non-redundant proteins with known carbohydrate binding sites. The predictors were further tested on an independent test set with 108 proteins. The residue-based Matthews correlation coefficient (MCC) for the independent test was 0.45, with prediction precision and sensitivity (or recall) of 0.45 and 0.49 respectively. In addition, 111 unbound carbohydrate-binding protein structures for which the structures were determined in the absence of the carbohydrate ligands were predicted with the trained predictors. The overall prediction MCC was 0.49. Independent tests on anti-carbohydrate antibodies showed that the carbohydrate antigen binding sites were predicted with comparable accuracy. These results demonstrate that the predictors are among the best in carbohydrate binding site predictions to date. PMID:22848404
Nuclear proteins that bind the human gamma-globin gene promoter: alterations in binding produced by point mutations associated with hereditary persistence of fetal hemoglobin.

PubMed Central

Gumucio, D L; Rood, K L; Gray, T A; Riordan, M F; Sartor, C I; Collins, F S

1988-01-01

The molecular mechanisms responsible for the human fetal-to-adult hemoglobin switch have not yet been elucidated. Point mutations identified in the promoter regions of gamma-globin genes from individuals with nondeletion hereditary persistence of fetal hemoglobin (HPFH) may mark cis-acting sequences important for this switch, and the trans-acting factors which interact with these sequences may be integral parts in the puzzle of gamma-globin gene regulation. We have used gel retardation and footprinting strategies to define nuclear proteins which bind to the normal gamma-globin promoter and to determine the effect of HPFH mutations on the binding of a subset of these proteins. We have identified five proteins in human erythroleukemia cells (K562 and HEL) which bind to the proximal promoter region of the normal gamma-globin gene. One factor, gamma CAAT, binds the duplicated CCAAT box sequences; the -117 HPFH mutation increases the affinity of interaction between gamma CAAT and its cognate site. Two proteins, gamma CAC1 and gamma CAC2, bind the CACCC sequence. These proteins require divalent cations for binding. The -175 HPFH mutation interferes with the binding of a fourth protein, gamma OBP, which binds an octamer sequence (ATGCAAAT) in the normal gamma-globin promoter. The HPFH phenotype of the -175 mutation indicates that the octamer-binding protein may play a negative regulatory role in this setting. A fifth protein, EF gamma a, binds to sequences which overlap the octamer-binding site. The erythroid-specific distribution of EF gamma a and its close approximation to an apparent repressor-binding site suggest that it may be important in gamma-globin regulation. Images PMID:2468996
Measuring protein-protein and protein-nucleic Acid interactions by biolayer interferometry.

PubMed

Sultana, Azmiri; Lee, Jeffrey E

2015-02-02

Biolayer interferometry (BLI) is a simple, optical dip-and-read system useful for measuring interactions between proteins, peptides, nucleic acids, small molecules, and/or lipids in real time. In BLI, a biomolecular bait is immobilized on a matrix at the tip of a fiber-optic sensor. The binding between the immobilized ligand and another molecule in an analyte solution produces a change in optical thickness at the tip and results in a wavelength shift proportional to binding. BLI provides direct binding affinities and rates of association and dissociation. This unit describes an efficient approach using streptavidin-based BLI to analyze DNA-protein and protein-protein interactions. A quantitative set of equilibrium binding affinities (K(d)) and rates of association and dissociation (k(a)/k(d)) can be measured in minutes using nanomole quantities of sample. Copyright © 2015 John Wiley & Sons, Inc.
Postprocessing of docked protein-ligand complexes using implicit solvation models.

PubMed

Lindström, Anton; Edvinsson, Lotta; Johansson, Andreas; Andersson, C David; Andersson, Ida E; Raubacher, Florian; Linusson, Anna

2011-02-28

Molecular docking plays an important role in drug discovery as a tool for the structure-based design of small organic ligands for macromolecules. Possible applications of docking are identification of the bioactive conformation of a protein-ligand complex and the ranking of different ligands with respect to their strength of binding to a particular target. We have investigated the effect of implicit water on the postprocessing of binding poses generated by molecular docking using MM-PB/GB-SA (molecular mechanics Poisson-Boltzmann and generalized Born surface area) methodology. The investigation was divided into three parts: geometry optimization, pose selection, and estimation of the relative binding energies of docked protein-ligand complexes. Appropriate geometry optimization afforded more accurate binding poses for 20% of the complexes investigated. The time required for this step was greatly reduced by minimizing the energy of the binding site using GB solvation models rather than minimizing the entire complex using the PB model. By optimizing the geometries of docking poses using the GB(HCT+SA) model then calculating their free energies of binding using the PB implicit solvent model, binding poses similar to those observed in crystal structures were obtained. Rescoring of these poses according to their calculated binding energies resulted in improved correlations with experimental binding data. These correlations could be further improved by applying the postprocessing to several of the most highly ranked poses rather than focusing exclusively on the top-scored pose. The postprocessing protocol was successfully applied to the analysis of a set of Factor Xa inhibitors and a set of glycopeptide ligands for the class II major histocompatibility complex (MHC) A(q) protein. These results indicate that the protocol for the postprocessing of docked protein-ligand complexes developed in this paper may be generally useful for structure-based design in drug discovery.
The SPOR Domain, a Widely Conserved Peptidoglycan Binding Domain That Targets Proteins to the Site of Cell Division.

PubMed

Yahashiri, Atsushi; Jorgenson, Matthew A; Weiss, David S

2017-07-15

Sporulation-related repeat (SPOR) domains are small peptidoglycan (PG) binding domains found in thousands of bacterial proteins. The name "SPOR domain" stems from the fact that several early examples came from proteins involved in sporulation, but SPOR domain proteins are quite diverse and contribute to a variety of processes that involve remodeling of the PG sacculus, especially with respect to cell division. SPOR domains target proteins to the division site by binding to regions of PG devoid of stem peptides ("denuded" glycans), which in turn are enriched in septal PG by the intense, localized activity of cell wall amidases involved in daughter cell separation. This targeting mechanism sets SPOR domain proteins apart from most other septal ring proteins, which localize via protein-protein interactions. In addition to SPOR domains, bacteria contain several other PG-binding domains that can exploit features of the cell wall to target proteins to specific subcellular sites. Copyright © 2017 American Society for Microbiology.
Modeling Ionization Events iduced by Protein Protein Binding

NASA Astrophysics Data System (ADS)

Mitra, Rooplekha; Shyam, Radhey; Alexov, Emil

2009-11-01

The association of two or more biological macromolecules dramatically change the environment of the amino acids situated at binding interface and could change ionization states of titratable groups. The change of ionization due to the binding results in proton uptake/release and causes pH-dependence of the binding free energy. We apply computational method, as implemented in Multi Conformation Continuum Electrostatics (MCCE) algorithm, to study protonation evens on a large set of protein-protein complexes. Our results indicate that proton uptake/release is a common phenomena in protein binding since in vast majority of the cases (70%) the binding caused at least 0.5 units proton change. The proton uptake/release was further investigated with respect to interfacial area and charges of the monomers and it was found that macroscopic characteristics are not important determinants. Instead, charge complementarity across the interface and the number of unpaired ionizable groups at the interface are the primary source of proton uptake/release.
DIVERSITY in binding, regulation, and evolution revealed from high-throughput ChIP.

PubMed

Mitra, Sneha; Biswas, Anushua; Narlikar, Leelavati

2018-04-01

Genome-wide in vivo protein-DNA interactions are routinely mapped using high-throughput chromatin immunoprecipitation (ChIP). ChIP-reported regions are typically investigated for enriched sequence-motifs, which are likely to model the DNA-binding specificity of the profiled protein and/or of co-occurring proteins. However, simple enrichment analyses can miss insights into the binding-activity of the protein. Note that ChIP reports regions making direct contact with the protein as well as those binding through intermediaries. For example, consider a ChIP experiment targeting protein X, which binds DNA at its cognate sites, but simultaneously interacts with four other proteins. Each of these proteins also binds to its own specific cognate sites along distant parts of the genome, a scenario consistent with the current view of transcriptional hubs and chromatin loops. Since ChIP will pull down all X-associated regions, the final reported data will be a union of five distinct sets of regions, each containing binding sites of one of the five proteins, respectively. Characterizing all five different motifs and the corresponding sets is important to interpret the ChIP experiment and ultimately, the role of X in regulation. We present diversity which attempts exactly this: it partitions the data so that each partition can be characterized with its own de novo motif. Diversity uses a Bayesian approach to identify the optimal number of motifs and the associated partitions, which together explain the entire dataset. This is in contrast to standard motif finders, which report motifs individually enriched in the data, but do not necessarily explain all reported regions. We show that the different motifs and associated regions identified by diversity give insights into the various complexes that may be forming along the chromatin, something that has so far not been attempted from ChIP data. Webserver at http://diversity.ncl.res.in/; standalone (Mac OS X/Linux) from https://github.com/NarlikarLab/DIVERSITY/releases/tag/v1.0.0.
Mapping specificity landscapes of RNA-protein interactions by high throughput sequencing.

PubMed

Jankowsky, Eckhard; Harris, Michael E

2017-04-15

To function in a biological setting, RNA binding proteins (RBPs) have to discriminate between alternative binding sites in RNAs. This discrimination can occur in the ground state of an RNA-protein binding reaction, in its transition state, or in both. The extent by which RBPs discriminate at these reaction states defines RBP specificity landscapes. Here, we describe the HiTS-Kin and HiTS-EQ techniques, which combine kinetic and equilibrium binding experiments with high throughput sequencing to quantitatively assess substrate discrimination for large numbers of substrate variants at ground and transition states of RNA-protein binding reactions. We discuss experimental design, practical considerations and data analysis and outline how a combination of HiTS-Kin and HiTS-EQ allows the mapping of RBP specificity landscapes. Copyright © 2017 Elsevier Inc. All rights reserved.
Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations

NASA Astrophysics Data System (ADS)

Misini Ignjatović, Majda; Caldararu, Octav; Dong, Geng; Muñoz-Gutierrez, Camila; Adasme-Carreño, Francisco; Ryde, Ulf

2016-09-01

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970-1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.
Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations.

PubMed

Misini Ignjatović, Majda; Caldararu, Octav; Dong, Geng; Muñoz-Gutierrez, Camila; Adasme-Carreño, Francisco; Ryde, Ulf

2016-09-01

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970-1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.
Alignment-independent comparison of binding sites based on DrugScore potential fields encoded by 3D Zernike descriptors.

PubMed

Nisius, Britta; Gohlke, Holger

2012-09-24

Analyzing protein binding sites provides detailed insights into the biological processes proteins are involved in, e.g., into drug-target interactions, and so is of crucial importance in drug discovery. Herein, we present novel alignment-independent binding site descriptors based on DrugScore potential fields. The potential fields are transformed to a set of information-rich descriptors using a series expansion in 3D Zernike polynomials. The resulting Zernike descriptors show a promising performance in detecting similarities among proteins with low pairwise sequence identities that bind identical ligands, as well as within subfamilies of one target class. Furthermore, the Zernike descriptors are robust against structural variations among protein binding sites. Finally, the Zernike descriptors show a high data compression power, and computing similarities between binding sites based on these descriptors is highly efficient. Consequently, the Zernike descriptors are a useful tool for computational binding site analysis, e.g., to predict the function of novel proteins, off-targets for drug candidates, or novel targets for known drugs.
Hydration behavior at the ice-binding surface of the Tenebrio molitor antifreeze protein.

PubMed

Midya, Uday Sankar; Bandyopadhyay, Sanjoy

2014-05-08

Molecular dynamics (MD) simulations have been carried out at two different temperatures (300 and 220 K) to study the conformational rigidity of the hyperactive Tenebrio molitor antifreeze protein (TmAFP) in aqueous medium and the structural arrangements of water molecules hydrating its surface. It is found that irrespective of the temperature the ice-binding surface (IBS) of the protein is relatively more rigid than its nonice-binding surface (NIBS). The presence of a set of regularly arranged internally bound water molecules is found to play an important role in maintaining the flat rigid nature of the IBS. Importantly, the calculations reveal that the strategically located hydroxyl oxygens of the threonine (Thr) residues in the IBS influence the arrangements of five sets of ordered waters around it on two parallel planes that closely resemble the basal plane of ice. As a result, these waters can register well with the ice basal plane, thereby allowing the IBS to preferentially bind at the ice interface and inhibit its growth. This provides a possible molecular reason behind the ice-binding activity of TmAFP at the basal plane of ice.
New Parameters for Higher Accuracy in the Computation of Binding Free Energy Differences upon Alanine Scanning Mutagenesis on Protein-Protein Interfaces.

PubMed

Simões, Inês C M; Costa, Inês P D; Coimbra, João T S; Ramos, Maria J; Fernandes, Pedro A

2017-01-23

Knowing how proteins make stable complexes enables the development of inhibitors to preclude protein-protein (P:P) binding. The identification of the specific interfacial residues that mostly contribute to protein binding, denominated as hot spots, is thus critical. Here, we refine an in silico alanine scanning mutagenesis protocol, based on a residue-dependent dielectric constant version of the Molecular Mechanics/Poisson-Boltzmann Surface Area method. We have used a large data set of structurally diverse P:P complexes to redefine the residue-dependent dielectric constants used in the determination of binding free energies. The accuracy of the method was validated through comparison with experimental data, considering the per-residue P:P binding free energy (ΔΔG binding ) differences upon alanine mutation. Different protocols were tested, i.e., a geometry optimization protocol and three molecular dynamics (MD) protocols: (1) one using explicit water molecules, (2) another with an implicit solvation model, and (3) a third where we have carried out an accelerated MD with explicit water molecules. Using a set of protein dielectric constants (within the range from 1 to 20) we showed that the dielectric constants of 7 for nonpolar and polar residues and 11 for charged residues (and histidine) provide optimal ΔΔG binding predictions. An overall mean unsigned error (MUE) of 1.4 kcal mol -1 relative to the experiment was achieved in 210 mutations only with geometry optimization, which was further reduced with MD simulations (MUE of 1.1 kcal mol -1 for the MD employing explicit solvent). This recalibrated method allows for a better computational identification of hot spots, avoiding expensive and time-consuming experiments or thermodynamic integration/ free energy perturbation/ uBAR calculations, and will hopefully help new drug discovery campaigns in their quest of searching spots of interest for binding small drug-like molecules at P:P interfaces.

ETMB-RBF: discrimination of metal-binding sites in electron transporters based on RBF networks with PSSM profiles and significant amino acid pairs.

PubMed

Ou, Yu-Yen; Chen, Shu-An; Wu, Sheng-Cheng

2013-01-01

Cellular respiration is the process by which cells obtain energy from glucose and is a very important biological process in living cell. As cells do cellular respiration, they need a pathway to store and transport electrons, the electron transport chain. The function of the electron transport chain is to produce a trans-membrane proton electrochemical gradient as a result of oxidation-reduction reactions. In these oxidation-reduction reactions in electron transport chains, metal ions play very important role as electron donor and acceptor. For example, Fe ions are in complex I and complex II, and Cu ions are in complex IV. Therefore, to identify metal-binding sites in electron transporters is an important issue in helping biologists better understand the workings of the electron transport chain. We propose a method based on Position Specific Scoring Matrix (PSSM) profiles and significant amino acid pairs to identify metal-binding residues in electron transport proteins. We have selected a non-redundant set of 55 metal-binding electron transport proteins as our dataset. The proposed method can predict metal-binding sites in electron transport proteins with an average 10-fold cross-validation accuracy of 93.2% and 93.1% for metal-binding cysteine and histidine, respectively. Compared with the general metal-binding predictor from A. Passerini et al., the proposed method can improve over 9% of sensitivity, and 14% specificity on the independent dataset in identifying metal-binding cysteines. The proposed method can also improve almost 76% sensitivity with same specificity in metal-binding histidine, and MCC is also improved from 0.28 to 0.88. We have developed a novel approach based on PSSM profiles and significant amino acid pairs for identifying metal-binding sites from electron transport proteins. The proposed approach achieved a significant improvement with independent test set of metal-binding electron transport proteins.
ETMB-RBF: Discrimination of Metal-Binding Sites in Electron Transporters Based on RBF Networks with PSSM Profiles and Significant Amino Acid Pairs

PubMed Central

Ou, Yu-Yen; Chen, Shu-An; Wu, Sheng-Cheng

2013-01-01

Background Cellular respiration is the process by which cells obtain energy from glucose and is a very important biological process in living cell. As cells do cellular respiration, they need a pathway to store and transport electrons, the electron transport chain. The function of the electron transport chain is to produce a trans-membrane proton electrochemical gradient as a result of oxidation–reduction reactions. In these oxidation–reduction reactions in electron transport chains, metal ions play very important role as electron donor and acceptor. For example, Fe ions are in complex I and complex II, and Cu ions are in complex IV. Therefore, to identify metal-binding sites in electron transporters is an important issue in helping biologists better understand the workings of the electron transport chain. Methods We propose a method based on Position Specific Scoring Matrix (PSSM) profiles and significant amino acid pairs to identify metal-binding residues in electron transport proteins. Results We have selected a non-redundant set of 55 metal-binding electron transport proteins as our dataset. The proposed method can predict metal-binding sites in electron transport proteins with an average 10-fold cross-validation accuracy of 93.2% and 93.1% for metal-binding cysteine and histidine, respectively. Compared with the general metal-binding predictor from A. Passerini et al., the proposed method can improve over 9% of sensitivity, and 14% specificity on the independent dataset in identifying metal-binding cysteines. The proposed method can also improve almost 76% sensitivity with same specificity in metal-binding histidine, and MCC is also improved from 0.28 to 0.88. Conclusions We have developed a novel approach based on PSSM profiles and significant amino acid pairs for identifying metal-binding sites from electron transport proteins. The proposed approach achieved a significant improvement with independent test set of metal-binding electron transport proteins. PMID:23405059
DOE Office of Scientific and Technical Information (OSTI.GOV)

Giuliani, Sarah E; Frank, Ashley M; Corgliano, Danielle M

Abstract Background: Transporter proteins are one of an organism s primary interfaces with the environment. The expressed set of transporters mediates cellular metabolic capabilities and influences signal transduction pathways and regulatory networks. The functional annotation of most transporters is currently limited to general classification into families. The development of capabilities to map ligands with specific transporters would improve our knowledge of the function of these proteins, improve the annotation of related genomes, and facilitate predictions for their role in cellular responses to environmental changes. Results: To improve the utility of the functional annotation for ABC transporters, we expressed and purifiedmore » the set of solute binding proteins from Rhodopseudomonas palustris and characterized their ligand-binding specificity. Our approach utilized ligand libraries consisting of environmental and cellular metabolic compounds, and fluorescence thermal shift based high throughput ligand binding screens. This process resulted in the identification of specific binding ligands for approximately 64% of the purified and screened proteins. The collection of binding ligands is representative of common functionalities associated with many bacterial organisms as well as specific capabilities linked to the ecological niche occupied by R. palustris. Conclusion: The functional screen identified specific ligands that bound to ABC transporter periplasmic binding subunits from R. palustris. These assignments provide unique insight for the metabolic capabilities of this organism and are consistent with the ecological niche of strain isolation. This functional insight can be used to improve the annotation of related organisms and provides a route to evaluate the evolution of this important and diverse group of transporter proteins.« less
CaMELS: In silico prediction of calmodulin binding proteins and their binding sites.

PubMed

Abbasi, Wajid Arshad; Asif, Amina; Andleeb, Saiqa; Minhas, Fayyaz Ul Amir Afsar

2017-09-01

Due to Ca 2+ -dependent binding and the sequence diversity of Calmodulin (CaM) binding proteins, identifying CaM interactions and binding sites in the wet-lab is tedious and costly. Therefore, computational methods for this purpose are crucial to the design of such wet-lab experiments. We present an algorithm suite called CaMELS (CalModulin intEraction Learning System) for predicting proteins that interact with CaM as well as their binding sites using sequence information alone. CaMELS offers state of the art accuracy for both CaM interaction and binding site prediction and can aid biologists in studying CaM binding proteins. For CaM interaction prediction, CaMELS uses protein sequence features coupled with a large-margin classifier. CaMELS models the binding site prediction problem using multiple instance machine learning with a custom optimization algorithm which allows more effective learning over imprecisely annotated CaM-binding sites during training. CaMELS has been extensively benchmarked using a variety of data sets, mutagenic studies, proteome-wide Gene Ontology enrichment analyses and protein structures. Our experiments indicate that CaMELS outperforms simple motif-based search and other existing methods for interaction and binding site prediction. We have also found that the whole sequence of a protein, rather than just its binding site, is important for predicting its interaction with CaM. Using the machine learning model in CaMELS, we have identified important features of protein sequences for CaM interaction prediction as well as characteristic amino acid sub-sequences and their relative position for identifying CaM binding sites. Python code for training and evaluating CaMELS together with a webserver implementation is available at the URL: http://faculty.pieas.edu.pk/fayyaz/software.html#camels. © 2017 Wiley Periodicals, Inc.
Heparin-Binding Protein Measurement Improves the Prediction of Severe Infection With Organ Dysfunction in the Emergency Department

PubMed Central

Arnold, Ryan; Boyd, John H.; Zindovic, Marko; Zindovic, Igor; Lange, Anna; Paulsson, Magnus; Nyberg, Patrik; Russell, James A.; Pritchard, David; Christensson, Bertil; Åkesson, Per

2015-01-01

Objectives: Early identification of patients with infection and at risk of developing severe disease with organ dysfunction remains a difficult challenge. We aimed to evaluate and validate the heparin-binding protein, a neutrophil-derived mediator of vascular leakage, as a prognostic biomarker for risk of progression to severe sepsis with circulatory failure in a multicenter setting. Design: A prospective international multicenter cohort study. Setting: Seven different emergency departments in Sweden, Canada, and the United States. Patients: Adult patients with a suspected infection and at least one of three clinical systemic inflammatory response syndrome criteria (excluding leukocyte count). Intervention: None. Measurements and Main Results: Plasma levels of heparin-binding protein, procalcitonin, C-reactive protein, lactate, and leukocyte count were determined at admission and 12–24 hours after admission in 759 emergency department patients with suspected infection. Patients were defined depending on the presence of infection and organ dysfunction. Plasma samples from 104 emergency department patients with suspected sepsis collected at an independent center were used to validate the results. Of the 674 patients diagnosed with an infection, 487 did not have organ dysfunction at enrollment. Of these 487 patients, 141 (29%) developed organ dysfunction within the 72-hour study period; 78.0% of the latter patients had an elevated plasma heparin-binding protein level (> 30 ng/mL) prior to development of organ dysfunction (median, 10.5 hr). Compared with other biomarkers, heparin-binding protein was the best predictor of progression to organ dysfunction (area under the receiver operating characteristic curve = 0.80). The performance of heparin-binding protein was confirmed in the validation cohort. Conclusion: In patients presenting at the emergency department, heparin-binding protein is an early indicator of infection-related organ dysfunction and a strong predictor of disease progression to severe sepsis within 72 hours. PMID:26468696
Construction of proteins with molecular recognition capabilities using α3β3 de novo protein scaffolds.

PubMed

Okura, Hiromichi; Mihara, Hisakazu; Takahashi, Tsuyoshi

2013-10-01

The molecular recognition ability of proteins is essential in biological systems, and therefore a considerable amount of effort has been devoted to constructing desired target-binding proteins using a variety of naturally occurring proteins as scaffolds. However, since generating a binding site in a native protein can often affect its structural properties, highly stable de novo protein scaffolds may be more amenable than the native proteins. We previously reported the generation of de novo proteins comprising three α-helices and three β-strands (α3β3) from a genetic library coding simplified amino acid sets. Two α3β3 de novo proteins, vTAJ13 and vTAJ36, fold into a native-like stable and molten globule-like structures, respectively, even though the proteins have similar amino acid compositions. Here, we attempted to create binding sites for the vTAJ13 and vTAJ36 proteins to prove the utility of de novo designed artificial proteins as a molecular recognition tool. Randomization of six amino acids at two linker sites of vTAJ13 and vTAJ36 followed by biopanning generated binding proteins that recognize the target molecules, fluorescein and green fluorescent protein, with affinities of 10(-7)-10(-8) M. Of note, the selected proteins from the vTAJ13-based library tended to recognize the target molecules with high specificity, probably due to the native-like stable structure of vTAJ13. Our studies provide an example of the potential of de novo protein scaffolds, which are composed of a simplified amino acid set, to recognize a variety of target compounds.
Force spectroscopy studies on protein-ligand interactions: a single protein mechanics perspective.

PubMed

Hu, Xiaotang; Li, Hongbin

2014-10-01

Protein-ligand interactions are ubiquitous and play important roles in almost every biological process. The direct elucidation of the thermodynamic, structural and functional consequences of protein-ligand interactions is thus of critical importance to decipher the mechanism underlying these biological processes. A toolbox containing a variety of powerful techniques has been developed to quantitatively study protein-ligand interactions in vitro as well as in living systems. The development of atomic force microscopy-based single molecule force spectroscopy techniques has expanded this toolbox and made it possible to directly probe the mechanical consequence of ligand binding on proteins. Many recent experiments have revealed how ligand binding affects the mechanical stability and mechanical unfolding dynamics of proteins, and provided mechanistic understanding on these effects. The enhancement effect of mechanical stability by ligand binding has been used to help tune the mechanical stability of proteins in a rational manner and develop novel functional binding assays for protein-ligand interactions. Single molecule force spectroscopy studies have started to shed new lights on the structural and functional consequence of ligand binding on proteins that bear force under their biological settings. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
A comparative study of family-specific protein-ligand complex affinity prediction based on random forest approach

NASA Astrophysics Data System (ADS)

Wang, Yu; Guo, Yanzhi; Kuang, Qifan; Pu, Xuemei; Ji, Yue; Zhang, Zhihang; Li, Menglong

2015-04-01

The assessment of binding affinity between ligands and the target proteins plays an essential role in drug discovery and design process. As an alternative to widely used scoring approaches, machine learning methods have also been proposed for fast prediction of the binding affinity with promising results, but most of them were developed as all-purpose models despite of the specific functions of different protein families, since proteins from different function families always have different structures and physicochemical features. In this study, we proposed a random forest method to predict the protein-ligand binding affinity based on a comprehensive feature set covering protein sequence, binding pocket, ligand structure and intermolecular interaction. Feature processing and compression was respectively implemented for different protein family datasets, which indicates that different features contribute to different models, so individual representation for each protein family is necessary. Three family-specific models were constructed for three important protein target families of HIV-1 protease, trypsin and carbonic anhydrase respectively. As a comparison, two generic models including diverse protein families were also built. The evaluation results show that models on family-specific datasets have the superior performance to those on the generic datasets and the Pearson and Spearman correlation coefficients ( R p and Rs) on the test sets are 0.740, 0.874, 0.735 and 0.697, 0.853, 0.723 for HIV-1 protease, trypsin and carbonic anhydrase respectively. Comparisons with the other methods further demonstrate that individual representation and model construction for each protein family is a more reasonable way in predicting the affinity of one particular protein family.
Protein-ligand binding free energy estimation using molecular mechanics and continuum electrostatics. Application to HIV-1 protease inhibitors

NASA Astrophysics Data System (ADS)

Zoete, V.; Michielin, O.; Karplus, M.

2003-12-01

A method is proposed for the estimation of absolute binding free energy of interaction between proteins and ligands. Conformational sampling of the protein-ligand complex is performed by molecular dynamics (MD) in vacuo and the solvent effect is calculated a posteriori by solving the Poisson or the Poisson-Boltzmann equation for selected frames of the trajectory. The binding free energy is written as a linear combination of the buried surface upon complexation, SAS bur, the electrostatic interaction energy between the ligand and the protein, Eelec, and the difference of the solvation free energies of the complex and the isolated ligand and protein, ΔGsolv. The method uses the buried surface upon complexation to account for the non-polar contribution to the binding free energy because it is less sensitive to the details of the structure than the van der Waals interaction energy. The parameters of the method are developed for a training set of 16 HIV-1 protease-inhibitor complexes of known 3D structure. A correlation coefficient of 0.91 was obtained with an unsigned mean error of 0.8 kcal/mol. When applied to a set of 25 HIV-1 protease-inhibitor complexes of unknown 3D structures, the method provides a satisfactory correlation between the calculated binding free energy and the experimental pIC 50 without reparametrization.
Predicting nucleic acid binding interfaces from structural models of proteins

PubMed Central

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2011-01-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared to patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. PMID:22086767
Impact of germline and somatic missense variations on drug binding sites.

PubMed

Yan, C; Pattabiraman, N; Goecks, J; Lam, P; Nayak, A; Pan, Y; Torcivia-Rodriguez, J; Voskanian, A; Wan, Q; Mazumder, R

2017-03-01

Advancements in next-generation sequencing (NGS) technologies are generating a vast amount of data. This exacerbates the current challenge of translating NGS data into actionable clinical interpretations. We have comprehensively combined germline and somatic nonsynonymous single-nucleotide variations (nsSNVs) that affect drug binding sites in order to investigate their prevalence. The integrated data thus generated in conjunction with exome or whole-genome sequencing can be used to identify patients who may not respond to a specific drug because of alterations in drug binding efficacy due to nsSNVs in the target protein's gene. To identify the nsSNVs that may affect drug binding, protein-drug complex structures were retrieved from Protein Data Bank (PDB) followed by identification of amino acids in the protein-drug binding sites using an occluded surface method. Then, the germline and somatic mutations were mapped to these amino acids to identify which of these alter protein-drug binding sites. Using this method we identified 12 993 amino acid-drug binding sites across 253 unique proteins bound to 235 unique drugs. The integration of amino acid-drug binding sites data with both germline and somatic nsSNVs data sets revealed 3133 nsSNVs affecting amino acid-drug binding sites. In addition, a comprehensive drug target discovery was conducted based on protein structure similarity and conservation of amino acid-drug binding sites. Using this method, 81 paralogs were identified that could serve as alternative drug targets. In addition, non-human mammalian proteins bound to drugs were used to identify 142 homologs in humans that can potentially bind to drugs. In the current protein-drug pairs that contain somatic mutations within their binding site, we identified 85 proteins with significant differential gene expression changes associated with specific cancer types. Information on protein-drug binding predicted drug target proteins and prevalence of both somatic and germline nsSNVs that disrupt these binding sites can provide valuable knowledge for personalized medicine treatment. A web portal is available where nsSNVs from individual patient can be checked by scanning against DrugVar to determine whether any of the SNVs affect the binding of any drug in the database.
Allosteric Coupling of CARMIL and V-1 Binding to Capping Protein Revealed by Hydrogen-Deuterium Exchange.

PubMed

Johnson, Britney; McConnell, Patrick; Kozlov, Alex G; Mekel, Marlene; Lohman, Timothy M; Gross, Michael L; Amarasinghe, Gaya K; Cooper, John A

2018-05-29

Actin assembly is important for cell motility. The ability of actin subunits to join or leave filaments via the barbed end is critical to actin dynamics. Capping protein (CP) binds to barbed ends to prevent subunit gain and loss and is regulated by proteins that include V-1 and CARMIL. V-1 inhibits CP by sterically blocking one binding site for actin. CARMILs bind at a distal site and decrease the affinity of CP for actin, suggested to be caused by conformational changes. We used hydrogen-deuterium exchange with mass spectrometry (HDX-MS) to probe changes in structural dynamics induced by V-1 and CARMIL binding to CP. V-1 and CARMIL induce changes in both proteins' binding sites on the surface of CP, along with a set of internal residues. Both also affect the conformation of CP's ββ subunit "tentacle," a second distal actin-binding site. Concerted regulation of actin assembly by CP occurs through allosteric couplings between CP modulator and actin binding sites. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.
DNA motif elucidation using belief propagation.

PubMed

Wong, Ka-Chun; Chan, Tak-Ming; Peng, Chengbin; Li, Yue; Zhang, Zhaolei

2013-09-01

Protein-binding microarray (PBM) is a high-throughout platform that can measure the DNA-binding preference of a protein in a comprehensive and unbiased manner. A typical PBM experiment can measure binding signal intensities of a protein to all the possible DNA k-mers (k=8∼10); such comprehensive binding affinity data usually need to be reduced and represented as motif models before they can be further analyzed and applied. Since proteins can often bind to DNA in multiple modes, one of the major challenges is to decompose the comprehensive affinity data into multimodal motif representations. Here, we describe a new algorithm that uses Hidden Markov Models (HMMs) and can derive precise and multimodal motifs using belief propagations. We describe an HMM-based approach using belief propagations (kmerHMM), which accepts and preprocesses PBM probe raw data into median-binding intensities of individual k-mers. The k-mers are ranked and aligned for training an HMM as the underlying motif representation. Multiple motifs are then extracted from the HMM using belief propagations. Comparisons of kmerHMM with other leading methods on several data sets demonstrated its effectiveness and uniqueness. Especially, it achieved the best performance on more than half of the data sets. In addition, the multiple binding modes derived by kmerHMM are biologically meaningful and will be useful in interpreting other genome-wide data such as those generated from ChIP-seq. The executables and source codes are available at the authors' websites: e.g. http://www.cs.toronto.edu/∼wkc/kmerHMM.
Interolog interfaces in protein–protein docking

PubMed Central

Alsop, James D.

2015-01-01

ABSTRACT Proteins are essential elements of biological systems, and their function typically relies on their ability to successfully bind to specific partners. Recently, an emphasis of study into protein interactions has been on hot spots, or residues in the binding interface that make a significant contribution to the binding energetics. In this study, we investigate how conservation of hot spots can be used to guide docking prediction. We show that the use of evolutionary data combined with hot spot prediction highlights near‐native structures across a range of benchmark examples. Our approach explores various strategies for using hot spots and evolutionary data to score protein complexes, using both absolute and chemical definitions of conservation along with refinements to these strategies that look at windowed conservation and filtering to ensure a minimum number of hot spots in each binding partner. Finally, structure‐based models of orthologs were generated for comparison with sequence‐based scoring. Using two data sets of 22 and 85 examples, a high rate of top 10 and top 1 predictions are observed, with up to 82% of examples returning a top 10 hit and 35% returning top 1 hit depending on the data set and strategy applied; upon inclusion of the native structure among the decoys, up to 55% of examples yielded a top 1 hit. The 20 common examples between data sets show that more carefully curated interolog data yields better predictions, particularly in achieving top 1 hits. Proteins 2015; 83:1940–1946. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. PMID:25740680
Comprehensive comparative analysis and identification of RNA-binding protein domains: multi-class classification and feature selection.

PubMed

Jahandideh, Samad; Srinivasasainagendra, Vinodh; Zhi, Degui

2012-11-07

RNA-protein interaction plays an important role in various cellular processes, such as protein synthesis, gene regulation, post-transcriptional gene regulation, alternative splicing, and infections by RNA viruses. In this study, using Gene Ontology Annotated (GOA) and Structural Classification of Proteins (SCOP) databases an automatic procedure was designed to capture structurally solved RNA-binding protein domains in different subclasses. Subsequently, we applied tuned multi-class SVM (TMCSVM), Random Forest (RF), and multi-class ℓ1/ℓq-regularized logistic regression (MCRLR) for analysis and classifying RNA-binding protein domains based on a comprehensive set of sequence and structural features. In this study, we compared prediction accuracy of three different state-of-the-art predictor methods. From our results, TMCSVM outperforms the other methods and suggests the potential of TMCSVM as a useful tool for facilitating the multi-class prediction of RNA-binding protein domains. On the other hand, MCRLR by elucidating importance of features for their contribution in predictive accuracy of RNA-binding protein domains subclasses, helps us to provide some biological insights into the roles of sequences and structures in protein-RNA interactions.
Predicting a small molecule-kinase interaction map: A machine learning approach

PubMed Central

2011-01-01

Background We present a machine learning approach to the problem of protein ligand interaction prediction. We focus on a set of binding data obtained from 113 different protein kinases and 20 inhibitors. It was attained through ATP site-dependent binding competition assays and constitutes the first available dataset of this kind. We extract information about the investigated molecules from various data sources to obtain an informative set of features. Results A Support Vector Machine (SVM) as well as a decision tree algorithm (C5/See5) is used to learn models based on the available features which in turn can be used for the classification of new kinase-inhibitor pair test instances. We evaluate our approach using different feature sets and parameter settings for the employed classifiers. Moreover, the paper introduces a new way of evaluating predictions in such a setting, where different amounts of information about the binding partners can be assumed to be available for training. Results on an external test set are also provided. Conclusions In most of the cases, the presented approach clearly outperforms the baseline methods used for comparison. Experimental results indicate that the applied machine learning methods are able to detect a signal in the data and predict binding affinity to some extent. For SVMs, the binding prediction can be improved significantly by using features that describe the active site of a kinase. For C5, besides diversity in the feature set, alignment scores of conserved regions turned out to be very useful. PMID:21708012
Simultaneous in vitro molecular screening of protein-peptide interactions by flow cytometry, using six Bcl-2 family proteins as examples.

PubMed

Simons, Peter C; Young, Susan M; Carter, Mark B; Waller, Anna; Zhai, Dayong; Reed, John C; Edwards, Bruce S; Sklar, Larry A

2011-06-09

The B-cell lymphoma-2 (Bcl-2) family contains six antiapoptotic members, each with a hydrophobic pocket in which Bcl-2 homology region 3 (BH3) helices bind. This binding quenches apoptotic signals from activated BH3 family members. Many tumor cells either have increased expression of one of these six proteins or become overexpressed under treatment. Six fusion proteins made up of glutathione-S-transferase and each of the Bcl-2 members are bound individually to six glutathione bead sets, each set being easily distinguished by its different intensity of red fluorescence. The coated bead sets are washed, combined and incubated with green fluorescent Bim-BH3 peptide and a small molecule in 10-μl wells for 1 h. The green fluorescence signal for each bead set is resolved, and selective inhibitors are expected to reduce the signal for individual bead sets. Each 384-well plate is analyzed in 12 min, measuring 200 of 2,000 beads (∼10%) of each type per well.
The poly(C)-binding proteins: a multiplicity of functions and a search for mechanisms.

PubMed Central

Makeyev, Aleksandr V; Liebhaber, Stephen A

2002-01-01

The poly(C) binding proteins (PCBPs) are encoded at five dispersed loci in the mouse and human genomes. These proteins, which can be divided into two groups, hnRNPs K/J and the alphaCPs (alphaCP1-4), are linked by a common evolutionary history, a shared triple KH domain configuration, and by their poly(C) binding specificity. Given these conserved characteristics it is remarkable to find a substantial diversity in PCBP functions. The roles of these proteins in mRNA stabilization, translational activation, and translational silencing suggest a complex and diverse set of post-transcriptional control pathways. Their additional putative functions in transcriptional control and as structural components of important DNA-protein complexes further support their remarkable structural and functional versatility. Clearly the identification of additional binding targets and delineation of corresponding control mechanisms and effector pathways will establish highly informative models for further exploration. PMID:12003487
The poly(C)-binding proteins: a multiplicity of functions and a search for mechanisms.

PubMed

Makeyev, Aleksandr V; Liebhaber, Stephen A

2002-03-01

The poly(C) binding proteins (PCBPs) are encoded at five dispersed loci in the mouse and human genomes. These proteins, which can be divided into two groups, hnRNPs K/J and the alphaCPs (alphaCP1-4), are linked by a common evolutionary history, a shared triple KH domain configuration, and by their poly(C) binding specificity. Given these conserved characteristics it is remarkable to find a substantial diversity in PCBP functions. The roles of these proteins in mRNA stabilization, translational activation, and translational silencing suggest a complex and diverse set of post-transcriptional control pathways. Their additional putative functions in transcriptional control and as structural components of important DNA-protein complexes further support their remarkable structural and functional versatility. Clearly the identification of additional binding targets and delineation of corresponding control mechanisms and effector pathways will establish highly informative models for further exploration.
Ligand-protein docking using a quantum stochastic tunneling optimization method.

PubMed

Mancera, Ricardo L; Källblad, Per; Todorov, Nikolay P

2004-04-30

A novel hybrid optimization method called quantum stochastic tunneling has been recently introduced. Here, we report its implementation within a new docking program called EasyDock and a validation with the CCDC/Astex data set of ligand-protein complexes using the PLP score to represent the ligand-protein potential energy surface and ScreenScore to score the ligand-protein binding energies. When taking the top energy-ranked ligand binding mode pose, we were able to predict the correct crystallographic ligand binding mode in up to 75% of the cases. By using this novel optimization method run times for typical docking simulations are significantly shortened. Copyright 2004 Wiley Periodicals, Inc. J Comput Chem 25: 858-864, 2004

Crystallization and preliminary X-ray diffraction studies of choline-binding protein F from Streptococcus pneumoniae

DOE Office of Scientific and Technical Information (OSTI.GOV)

Molina, Rafael; González, Ana; Moscoso, Miriam

2007-09-01

The modular choline-binding protein F (CbpF) from S. pneumoniae has been crystallized by the hanging-drop vapour-diffusion method. A SAD data set from a gadolinium-complex derivative has been collected to 2.1 Å resolution. Choline-binding protein F (CbpF) is a modular protein that is bound to the pneumococcal cell wall through noncovalent interactions with choline moieties of the bacterial teichoic and lipoteichoic acids. Despite being one of the more abundant proteins on the surface, along with the murein hydrolases LytA, LytB, LytC and Pce, its function is still unknown. CbpF has been crystallized using the hanging-drop vapour-diffusion method at 291 K. Diffraction-qualitymore » orthorhombic crystals belong to space group P2{sub 1}2{sub 1}2, with unit-cell parameters a = 49.13, b = 114.94, c = 75.69 Å. A SAD data set from a Gd-HPDO3A-derivatized CbpF crystal was collected to 2.1 Å resolution at the gadolinium L{sub III} absorption edge using synchrotron radiation.« less
Prediction of kinase-inhibitor binding affinity using energetic parameters

PubMed Central

Usha, Singaravelu; Selvaraj, Samuel

2016-01-01

The combination of physicochemical properties and energetic parameters derived from protein-ligand complexes play a vital role in determining the biological activity of a molecule. In the present work, protein-ligand interaction energy along with logP values was used to predict the experimental log (IC50) values of 25 different kinase-inhibitors using multiple regressions which gave a correlation coefficient of 0.93. The regression equation obtained was tested on 93 kinase-inhibitor complexes and an average deviation of 0.92 from the experimental log IC50 values was shown. The same set of descriptors was used to predict binding affinities for a test set of five individual kinase families, with correlation values > 0.9. We show that the protein-ligand interaction energies and partition coefficient values form the major deterministic factors for binding affinity of the ligand for its receptor. PMID:28149052
Differential Binding between Volatile Ligands and Major Urinary Proteins Due to Genetic Variation in Mice

DTIC Science & Technology

2012-06-20

a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. a ...previous studies have examined only one of the classes at a time. No study has analyzed these two sets simultaneously, and consequently binding...previous studies have examined only one of the classes at a time. No study has analyzed these two sets simultaneously, and consequently binding
Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.

PubMed

Qu, Kaiyang; Han, Ke; Wu, Song; Wang, Guohua; Wei, Leyi

2017-09-22

DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.
Characterization of DNA-protein interactions using high-throughput sequencing data from pulldown experiments

NASA Astrophysics Data System (ADS)

Moreland, Blythe; Oman, Kenji; Curfman, John; Yan, Pearlly; Bundschuh, Ralf

Methyl-binding domain (MBD) protein pulldown experiments have been a valuable tool in measuring the levels of methylated CpG dinucleotides. Due to the frequent use of this technique, high-throughput sequencing data sets are available that allow a detailed quantitative characterization of the underlying interaction between methylated DNA and MBD proteins. Analyzing such data sets, we first found that two such proteins cannot bind closer to each other than 2 bp, consistent with structural models of the DNA-protein interaction. Second, the large amount of sequencing data allowed us to find rather weak but nevertheless clearly statistically significant sequence preferences for several bases around the required CpG. These results demonstrate that pulldown sequencing is a high-precision tool in characterizing DNA-protein interactions. This material is based upon work supported by the National Science Foundation under Grant No. DMR-1410172.
Spring-loaded model revisited: paramyxovirus fusion requires engagement of a receptor binding protein beyond initial triggering of the fusion protein.

PubMed

Porotto, Matteo; Devito, Ilaria; Palmer, Samantha G; Jurgens, Eric M; Yee, Jia L; Yokoyama, Christine C; Pessi, Antonello; Moscona, Anne

2011-12-01

During paramyxovirus entry into a host cell, receptor engagement by a specialized binding protein triggers conformational changes in the adjacent fusion protein (F), leading to fusion between the viral and cell membranes. According to the existing paradigm of paramyxovirus membrane fusion, the initial activation of F by the receptor binding protein sets off a spring-loaded mechanism whereby the F protein progresses independently through the subsequent steps in the fusion process, ending in membrane merger. For human parainfluenza virus type 3 (HPIV3), the receptor binding protein (hemagglutinin-neuraminidase [HN]) has three functions: receptor binding, receptor cleaving, and activating F. We report that continuous receptor engagement by HN activates F to advance through the series of structural rearrangements required for fusion. In contrast to the prevailing model, the role of HN-receptor engagement in the fusion process is required beyond an initiating step, i.e., it is still required even after the insertion of the fusion peptide into the target cell membrane, enabling F to mediate membrane merger. We also report that for Nipah virus, whose receptor binding protein has no receptor-cleaving activity, the continuous stimulation of the F protein by a receptor-engaged binding protein is key for fusion. We suggest a general model for paramyxovirus fusion activation in which receptor engagement plays an active role in F activation, and the continued engagement of the receptor binding protein is essential to F protein function until the onset of membrane merger. This model has broad implications for the mechanism of paramyxovirus fusion and for strategies to prevent viral entry.
Exploiting protein flexibility to predict the location of allosteric sites

PubMed Central

2012-01-01

Background Allostery is one of the most powerful and common ways of regulation of protein activity. However, for most allosteric proteins identified to date the mechanistic details of allosteric modulation are not yet well understood. Uncovering common mechanistic patterns underlying allostery would allow not only a better academic understanding of the phenomena, but it would also streamline the design of novel therapeutic solutions. This relatively unexplored therapeutic potential and the putative advantages of allosteric drugs over classical active-site inhibitors fuel the attention allosteric-drug research is receiving at present. A first step to harness the regulatory potential and versatility of allosteric sites, in the context of drug-discovery and design, would be to detect or predict their presence and location. In this article, we describe a simple computational approach, based on the effect allosteric ligands exert on protein flexibility upon binding, to predict the existence and position of allosteric sites on a given protein structure. Results By querying the literature and a recently available database of allosteric sites, we gathered 213 allosteric proteins with structural information that we further filtered into a non-redundant set of 91 proteins. We performed normal-mode analysis and observed significant changes in protein flexibility upon allosteric-ligand binding in 70% of the cases. These results agree with the current view that allosteric mechanisms are in many cases governed by changes in protein dynamics caused by ligand binding. Furthermore, we implemented an approach that achieves 65% positive predictive value in identifying allosteric sites within the set of predicted cavities of a protein (stricter parameters set, 0.22 sensitivity), by combining the current analysis on dynamics with previous results on structural conservation of allosteric sites. We also analyzed four biological examples in detail, revealing that this simple coarse-grained methodology is able to capture the effects triggered by allosteric ligands already described in the literature. Conclusions We introduce a simple computational approach to predict the presence and position of allosteric sites in a protein based on the analysis of changes in protein normal modes upon the binding of a coarse-grained ligand at predicted cavities. Its performance has been demonstrated using a newly curated non-redundant set of 91 proteins with reported allosteric properties. The software developed in this work is available upon request from the authors. PMID:23095452
Exploiting protein flexibility to predict the location of allosteric sites.

PubMed

Panjkovich, Alejandro; Daura, Xavier

2012-10-25

Allostery is one of the most powerful and common ways of regulation of protein activity. However, for most allosteric proteins identified to date the mechanistic details of allosteric modulation are not yet well understood. Uncovering common mechanistic patterns underlying allostery would allow not only a better academic understanding of the phenomena, but it would also streamline the design of novel therapeutic solutions. This relatively unexplored therapeutic potential and the putative advantages of allosteric drugs over classical active-site inhibitors fuel the attention allosteric-drug research is receiving at present. A first step to harness the regulatory potential and versatility of allosteric sites, in the context of drug-discovery and design, would be to detect or predict their presence and location. In this article, we describe a simple computational approach, based on the effect allosteric ligands exert on protein flexibility upon binding, to predict the existence and position of allosteric sites on a given protein structure. By querying the literature and a recently available database of allosteric sites, we gathered 213 allosteric proteins with structural information that we further filtered into a non-redundant set of 91 proteins. We performed normal-mode analysis and observed significant changes in protein flexibility upon allosteric-ligand binding in 70% of the cases. These results agree with the current view that allosteric mechanisms are in many cases governed by changes in protein dynamics caused by ligand binding. Furthermore, we implemented an approach that achieves 65% positive predictive value in identifying allosteric sites within the set of predicted cavities of a protein (stricter parameters set, 0.22 sensitivity), by combining the current analysis on dynamics with previous results on structural conservation of allosteric sites. We also analyzed four biological examples in detail, revealing that this simple coarse-grained methodology is able to capture the effects triggered by allosteric ligands already described in the literature. We introduce a simple computational approach to predict the presence and position of allosteric sites in a protein based on the analysis of changes in protein normal modes upon the binding of a coarse-grained ligand at predicted cavities. Its performance has been demonstrated using a newly curated non-redundant set of 91 proteins with reported allosteric properties. The software developed in this work is available upon request from the authors.
Nature and function of insulator protein binding sites in the Drosophila genome

PubMed Central

Schwartz, Yuri B.; Linder-Basso, Daniela; Kharchenko, Peter V.; Tolstorukov, Michael Y.; Kim, Maria; Li, Hua-Bing; Gorchakov, Andrey A.; Minoda, Aki; Shanower, Gregory; Alekseyenko, Artyom A.; Riddle, Nicole C.; Jung, Youngsook L.; Gu, Tingting; Plachetka, Annette; Elgin, Sarah C.R.; Kuroda, Mitzi I.; Park, Peter J.; Savitsky, Mikhail; Karpen, Gary H.; Pirrotta, Vincenzo

2012-01-01

Chromatin insulator elements and associated proteins have been proposed to partition eukaryotic genomes into sets of independently regulated domains. Here we test this hypothesis by quantitative genome-wide analysis of insulator protein binding to Drosophila chromatin. We find distinct combinatorial binding of insulator proteins to different classes of sites and uncover a novel type of insulator element that binds CP190 but not any other known insulator proteins. Functional characterization of different classes of binding sites indicates that only a small fraction act as robust insulators in standard enhancer-blocking assays. We show that insulators restrict the spreading of the H3K27me3 mark but only at a small number of Polycomb target regions and only to prevent repressive histone methylation within adjacent genes that are already transcriptionally inactive. RNAi knockdown of insulator proteins in cultured cells does not lead to major alterations in genome expression. Taken together, these observations argue against the concept of a genome partitioned by specialized boundary elements and suggest that insulators are reserved for specific regulation of selected genes. PMID:22767387
Characterization of Protein-Carbohydrate Interactions by NMR Spectroscopy.

PubMed

Grondin, Julie M; Langelaan, David N; Smith, Steven P

2017-01-01

Solution-state nuclear magnetic resonance (NMR) spectroscopy can be used to monitor protein-carbohydrate interactions. Two-dimensional 1 H- 15 N heteronuclear single quantum coherence (HSQC)-based techniques described in this chapter can be used quickly and effectively to screen a set of possible carbohydrate binding partners, to quantify the dissociation constant (K d ) of any identified interactions, and to map the carbohydrate binding site on the structure of the protein. Here, we describe the titration of a family 32 carbohydrate binding module from Clostridium perfringens (CpCBM32) with the monosaccharide N-acetylgalactosamine (GalNAc), in which we calculate the apparent dissociation of the interaction, and map the GalNAc binding site onto the structure of CpCBM32.
Predicting nucleic acid binding interfaces from structural models of proteins.

PubMed

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2012-02-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Copyright © 2011 Wiley Periodicals, Inc.
Spring-Loaded Model Revisited: Paramyxovirus Fusion Requires Engagement of a Receptor Binding Protein beyond Initial Triggering of the Fusion Protein▿

PubMed Central

Porotto, Matteo; DeVito, Ilaria; Palmer, Samantha G.; Jurgens, Eric M.; Yee, Jia L.; Yokoyama, Christine C.; Pessi, Antonello; Moscona, Anne

2011-01-01

During paramyxovirus entry into a host cell, receptor engagement by a specialized binding protein triggers conformational changes in the adjacent fusion protein (F), leading to fusion between the viral and cell membranes. According to the existing paradigm of paramyxovirus membrane fusion, the initial activation of F by the receptor binding protein sets off a spring-loaded mechanism whereby the F protein progresses independently through the subsequent steps in the fusion process, ending in membrane merger. For human parainfluenza virus type 3 (HPIV3), the receptor binding protein (hemagglutinin-neuraminidase [HN]) has three functions: receptor binding, receptor cleaving, and activating F. We report that continuous receptor engagement by HN activates F to advance through the series of structural rearrangements required for fusion. In contrast to the prevailing model, the role of HN-receptor engagement in the fusion process is required beyond an initiating step, i.e., it is still required even after the insertion of the fusion peptide into the target cell membrane, enabling F to mediate membrane merger. We also report that for Nipah virus, whose receptor binding protein has no receptor-cleaving activity, the continuous stimulation of the F protein by a receptor-engaged binding protein is key for fusion. We suggest a general model for paramyxovirus fusion activation in which receptor engagement plays an active role in F activation, and the continued engagement of the receptor binding protein is essential to F protein function until the onset of membrane merger. This model has broad implications for the mechanism of paramyxovirus fusion and for strategies to prevent viral entry. PMID:21976650
Detecting Local Ligand-Binding Site Similarity in Non-Homologous Proteins by Surface Patch Comparison

PubMed Central

Sael, Lee; Kihara, Daisuke

2012-01-01

Functional elucidation of proteins is one of the essential tasks in biology. Function of a protein, specifically, small ligand molecules that bind to a protein, can be predicted by finding similar local surface regions in binding sites of known proteins. Here, we developed an alignment free local surface comparison method for predicting a ligand molecule which binds to a query protein. The algorithm, named Patch-Surfer, represents a binding pocket as a combination of segmented surface patches, each of which is characterized by its geometrical shape, the electrostatic potential, the hydrophobicity, and the concaveness. Representing a pocket by a set of patches is effective to absorb difference of global pocket shape while capturing local similarity of pockets. The shape and the physicochemical properties of surface patches are represented using the 3D Zernike descriptor, which is a series expansion of mathematical 3D function. Two pockets are compared using a modified weighted bipartite matching algorithm, which matches similar patches from the two pockets. Patch-Surfer was benchmarked on three datasets, which consist in total of 390 proteins that bind to one of 21 ligands. Patch-Surfer showed superior performance to existing methods including a global pocket comparison method, Pocket-Surfer, which we have previously introduced. Particularly, as intended, the accuracy showed large improvement for flexible ligand molecules, which bind to pockets in different conformations. PMID:22275074
Detecting local ligand-binding site similarity in nonhomologous proteins by surface patch comparison.

PubMed

Sael, Lee; Kihara, Daisuke

2012-04-01

Functional elucidation of proteins is one of the essential tasks in biology. Function of a protein, specifically, small ligand molecules that bind to a protein, can be predicted by finding similar local surface regions in binding sites of known proteins. Here, we developed an alignment free local surface comparison method for predicting a ligand molecule which binds to a query protein. The algorithm, named Patch-Surfer, represents a binding pocket as a combination of segmented surface patches, each of which is characterized by its geometrical shape, the electrostatic potential, the hydrophobicity, and the concaveness. Representing a pocket by a set of patches is effective to absorb difference of global pocket shape while capturing local similarity of pockets. The shape and the physicochemical properties of surface patches are represented using the 3D Zernike descriptor, which is a series expansion of mathematical 3D function. Two pockets are compared using a modified weighted bipartite matching algorithm, which matches similar patches from the two pockets. Patch-Surfer was benchmarked on three datasets, which consist in total of 390 proteins that bind to one of 21 ligands. Patch-Surfer showed superior performance to existing methods including a global pocket comparison method, Pocket-Surfer, which we have previously introduced. Particularly, as intended, the accuracy showed large improvement for flexible ligand molecules, which bind to pockets in different conformations. Copyright © 2011 Wiley Periodicals, Inc.
Synthesis and Evaluation of a Novel Adenosine-Ribose Probe for Global-Scale Profiling of Nucleoside and Nucleotide-Binding Proteins

PubMed Central

Mahajan, Shikha; Manetsch, Roman; Merkler, David J.; Stevens Jr., Stanley M.

2015-01-01

Proteomics is a powerful approach used for investigating the complex molecular mechanisms of disease pathogenesis and progression. An important challenge in modern protein profiling approaches involves targeting of specific protein activities in order to identify altered molecular processes associated with disease pathophysiology. Adenosine-binding proteins represent an important subset of the proteome where aberrant expression or activity changes of these proteins have been implicated in numerous human diseases. Herein, we describe an affinity-based approach for the enrichment of adenosine-binding proteins from a complex cell proteome. A novel N 6-biotinylated-8-azido-adenosine probe (AdoR probe) was synthesized, which contains a reactive group that forms a covalent bond with the target proteins, as well as a biotin tag for affinity enrichment using avidin chromatography. Probe specificity was confirmed with protein standards prior to further evaluation in a complex protein mixture consisting of a lysate derived from mouse neuroblastoma N18TG2 cells. Protein identification and relative quantitation using mass spectrometry allowed for the identification of small variations in abundance of nucleoside- and nucleotide-binding proteins in these samples where a significant enrichment of AdoR-binding proteins in the labeled proteome from the neuroblastoma cells was observed. The results from this study demonstrate the utility of this method to enrich for nucleoside- and nucleotide-binding proteins in a complex protein mixture, pointing towards a unique set of proteins that can be examined in the context of further understanding mechanisms of disease, or fundamental biological processes in general. PMID:25671571
Rational design of a colorimetric pH sensor from a soluble retinoic acid chaperone.

PubMed

Berbasova, Tetyana; Nosrati, Meisam; Vasileiou, Chrysoula; Wang, Wenjing; Lee, Kin Sing Stephen; Yapici, Ipek; Geiger, James H; Borhan, Babak

2013-10-30

Reengineering of cellular retinoic acid binding protein II (CRABPII) to be capable of binding retinal as a protonated Schiff base is described. Through rational alterations of the binding pocket, electrostatic perturbations of the embedded retinylidene chromophore that favor delocalization of the iminium charge lead to exquisite control in the regulation of chromophoric absorption properties, spanning the visible spectrum (474-640 nm). The pKa of the retinylidene protonated Schiff base was modulated from 2.4 to 8.1, giving rise to a set of proteins of varying colors and pH sensitivities. These proteins were used to demonstrate a concentration-independent, ratiometric pH sensor.
Architecture and dynamics of overlapped RNA regulatory networks.

PubMed

Lapointe, Christopher P; Preston, Melanie A; Wilinski, Daniel; Saunders, Harriet A J; Campbell, Zachary T; Wickens, Marvin

2017-11-01

A single protein can bind and regulate many mRNAs. Multiple proteins with similar specificities often bind and control overlapping sets of mRNAs. Yet little is known about the architecture or dynamics of overlapped networks. We focused on three proteins with similar structures and related RNA-binding specificities-Puf3p, Puf4p, and Puf5p of S. cerevisiae Using RNA Tagging, we identified a "super-network" comprised of four subnetworks: Puf3p, Puf4p, and Puf5p subnetworks, and one controlled by both Puf4p and Puf5p. The architecture of individual subnetworks, and thus the super-network, is determined by competition among particular PUF proteins to bind mRNAs, their affinities for binding elements, and the abundances of the proteins. The super-network responds dramatically: The remaining network can either expand or contract. These strikingly opposite outcomes are determined by an interplay between the relative abundance of the RNAs and proteins, and their affinities for one another. The diverse interplay between overlapping RNA-protein networks provides versatile opportunities for regulation and evolution. © 2017 Lapointe et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.
Structural studies of the effect that dimethyl sulfoxide (DMSO) has on cisplatin and carboplatin binding to histidine in a protein.

PubMed

Tanley, Simon W M; Schreurs, Antoine M M; Kroon-Batenburg, Loes M J; Meredith, Joanne; Prendergast, Richard; Walsh, Danielle; Bryant, Patrick; Levy, Colin; Helliwell, John R

2012-05-01

The anticancer complexes cisplatin and carboplatin target the DNA major groove, forming intrastrand and interstrand cross-links between guanine bases through their N7 atoms, causing distortion of the DNA helix and apoptotic cell death. A major side effect of these drugs is toxicity, which is caused via binding to many proteins in the body. A range of crystallographic studies have been carried out involving the cocrystallization of hen egg-white lysozyme (HEWL) as a test protein with cisplatin and carboplatin in aqueous and dimethyl sulfoxide (DMSO) conditions. Different cryoprotectants, glycerol and Paratone, were used for each of the cisplatin and carboplatin cocrystallization cases, while silicone oil was used for studies involving N-acetylglucosamine (NAG). Both cisplatin and carboplatin do not bind to HEWL in aqueous media on the timescales of the conditions used here, but upon addition of DMSO two molecules of cisplatin or carboplatin bind either side of His15, which is the only His residue in lysozyme and is assumed to be an imidazolyl anion or a chemical resonance moiety, i.e. both imidazole N atoms are chemically reactive. To identify the platinum-peak positions in the 'with DMSO conditions', anomalous scattering maps were calculated as a cross-check with the F(o) - F(c) OMIT maps. Platinum-occupancy σ values were established using three different software programs in each case. The use of EVAL15 to process all of the diffraction data sets provided a consistent platform for a large ensemble of data sets for the various protein and platinum-compound model refinements with REFMAC5 and then SHELXTL. Overall, this extensive set of crystallization and cryoprotectant conditions allowed a systematic evaluation of cisplatin and carboplatin binding to lysozyme as a test protein via detailed X-ray crystal structure characterizations. DMSO is used as a super-solvent for drug delivery as it is deemed to cause no effect upon drug binding. However, these results show that addition of DMSO causes the platinum anticancer drugs to bind to HEWL. This effect should be considered in toxicity assessments of these drugs and perhaps more widely. © 2012 International Union of Crystallography
Seten: a tool for systematic identification and comparison of processes, phenotypes, and diseases associated with RNA-binding proteins from condition-specific CLIP-seq profiles.

PubMed

Budak, Gungor; Srivastava, Rajneesh; Janga, Sarath Chandra

2017-06-01

RNA-binding proteins (RBPs) control the regulation of gene expression in eukaryotic genomes at post-transcriptional level by binding to their cognate RNAs. Although several variants of CLIP (crosslinking and immunoprecipitation) protocols are currently available to study the global protein-RNA interaction landscape at single-nucleotide resolution in a cell, currently there are very few tools that can facilitate understanding and dissecting the functional associations of RBPs from the resulting binding maps. Here, we present Seten, a web-based and command line tool, which can identify and compare processes, phenotypes, and diseases associated with RBPs from condition-specific CLIP-seq profiles. Seten uses BED files resulting from most peak calling algorithms, which include scores reflecting the extent of binding of an RBP on the target transcript, to provide both traditional functional enrichment as well as gene set enrichment results for a number of gene set collections including BioCarta, KEGG, Reactome, Gene Ontology (GO), Human Phenotype Ontology (HPO), and MalaCards Disease Ontology for several organisms including fruit fly, human, mouse, rat, worm, and yeast. It also provides an option to dynamically compare the associated gene sets across data sets as bubble charts, to facilitate comparative analysis. Benchmarking of Seten using eCLIP data for IGF2BP1, SRSF7, and PTBP1 against their corresponding CRISPR RNA-seq in K562 cells as well as randomized negative controls, demonstrated that its gene set enrichment method outperforms functional enrichment, with scores significantly contributing to the discovery of true annotations. Comparative performance analysis using these CRISPR control data sets revealed significantly higher precision and comparable recall to that observed using ChIP-Enrich. Seten's web interface currently provides precomputed results for about 200 CLIP-seq data sets and both command line as well as web interfaces can be used to analyze CLIP-seq data sets. We highlight several examples to show the utility of Seten for rapid profiling of various CLIP-seq data sets. Seten is available on http://www.iupui.edu/∼sysbio/seten/. © 2017 Budak et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.
Genome-wide Analysis Reveals SR Protein Cooperation and Competition in Regulated Splicing

PubMed Central

Pandit, Shatakshi; Zhou, Yu; Shiue, Lily; Coutinho-Mansfield, Gabriela; Li, Hairi; Qiu, Jinsong; Huang, Jie; Yeo, Gene W.; Ares, Manuel; Fu, Xiang-Dong

2013-01-01

Summary SR proteins are well-characterized RNA binding proteins that promote exon inclusion by binding to exonic splicing enhancers (ESEs). However, it has been unclear whether regulatory rules deduced on model genes apply generally to activities of SR proteins in the cell. Here, we report global analyses of two prototypical SR proteins SRSF1 (SF2/ASF) and SRSF2 (SC35) using splicing-sensitive arrays and CLIP-seq on mouse embryo fibroblasts (MEFs). Unexpectedly, we find that these SR proteins promote both inclusion and skipping of exons in vivo, but their binding patterns do not explain such opposite responses. Further analyses reveal that loss of one SR protein is accompanied by coordinated loss or compensatory gain in the interaction of other SR proteins at the affected exons. Therefore, specific effects on regulated splicing by one SR protein actually depend on a complex set of relationships with multiple other SR proteins in mammalian genomes. PMID:23562324

Relationship between Hot Spot Residues and Ligand Binding Hot Spots in Protein-Protein Interfaces

PubMed Central

Zerbe, Brandon S.; Hall, David R.

2013-01-01

In the context of protein-protein interactions, the term “hot spot” refers to a residue or cluster of residues that makes a major contribution to the binding free energy, as determined by alanine scanning mutagenesis. In contrast, in pharmaceutical research a hot spot is a site on a target protein that has high propensity for ligand binding and hence is potentially important for drug discovery. Here we examine the relationship between these two hot spot concepts by comparing alanine scanning data for a set of 15 proteins with results from mapping the protein surfaces for sites that can bind fragment-sized small molecules. We find the two types of hot spots are largely complementary; the residues protruding into hot spot regions identified by computational mapping or experimental fragment screening are almost always themselves hot spot residues as defined by alanine scanning experiments. Conversely, a residue that is found by alanine scanning to contribute little to binding rarely interacts with hot spot regions on the partner protein identified by fragment mapping. In spite of the strong correlation between the two hot spot concepts, they fundamentally differ, however. In particular, while identification of a hot spot by alanine scanning establishes the potential to generate substantial interaction energy with a binding partner, there are additional topological requirements to be a hot spot for small molecule binding. Hence, only a minority of hot spots identified by alanine scanning represent sites that are potentially useful for small inhibitor binding, and it is this subset that is identified by experimental or computational fragment screening. PMID:22770357
Relationship between hot spot residues and ligand binding hot spots in protein-protein interfaces.

PubMed

Zerbe, Brandon S; Hall, David R; Vajda, Sandor; Whitty, Adrian; Kozakov, Dima

2012-08-27

In the context of protein-protein interactions, the term "hot spot" refers to a residue or cluster of residues that makes a major contribution to the binding free energy, as determined by alanine scanning mutagenesis. In contrast, in pharmaceutical research, a hot spot is a site on a target protein that has high propensity for ligand binding and hence is potentially important for drug discovery. Here we examine the relationship between these two hot spot concepts by comparing alanine scanning data for a set of 15 proteins with results from mapping the protein surfaces for sites that can bind fragment-sized small molecules. We find the two types of hot spots are largely complementary; the residues protruding into hot spot regions identified by computational mapping or experimental fragment screening are almost always themselves hot spot residues as defined by alanine scanning experiments. Conversely, a residue that is found by alanine scanning to contribute little to binding rarely interacts with hot spot regions on the partner protein identified by fragment mapping. In spite of the strong correlation between the two hot spot concepts, they fundamentally differ, however. In particular, while identification of a hot spot by alanine scanning establishes the potential to generate substantial interaction energy with a binding partner, there are additional topological requirements to be a hot spot for small molecule binding. Hence, only a minority of hot spots identified by alanine scanning represent sites that are potentially useful for small inhibitor binding, and it is this subset that is identified by experimental or computational fragment screening.
Protein pharmacophore selection using hydration-site analysis

PubMed Central

Hu, Bingjie; Lill, Markus A.

2012-01-01

Virtual screening using pharmacophore models is an efficient method to identify potential lead compounds for target proteins. Pharmacophore models based on protein structures are advantageous because a priori knowledge of active ligands is not required and the models are not biased by the chemical space of previously identified actives. However, in order to capture most potential interactions between all potentially binding ligands and the protein, the size of the pharmacophore model, i.e. number of pharmacophore elements, is typically quite large and therefore reduces the efficiency of pharmacophore based screening. We have developed a new method to select important pharmacophore elements using hydration-site information. The basic premise is that ligand functional groups that replace water molecules in the apo protein contribute strongly to the overall binding affinity of the ligand, due to the additional free energy gained from releasing the water molecule into the bulk solvent. We computed the free energy of water released from the binding site for each hydration site using thermodynamic analysis of molecular dynamics (MD) simulations. Pharmacophores which are co-localized with hydration sites with estimated favorable contributions to the free energy of binding are selected to generate a reduced pharmacophore model. We constructed reduced pharmacophore models for three protein systems and demonstrated good enrichment quality combined with high efficiency. The reduction in pharmacophore model size reduces the required screening time by a factor of 200–500 compared to using all protein pharmacophore elements. We also describe a training process using a small set of known actives to reliably select the optimal set of criteria for pharmacophore selection for each protein system. PMID:22397751
Reprogramming cellular events by poly(ADP-ribose)-binding proteins

PubMed Central

Pic, Émilie; Ethier, Chantal; Dawson, Ted M.; Dawson, Valina L.; Masson, Jean-Yves; Poirier, Guy G.; Gagné, Jean-Philippe

2013-01-01

Poly(ADP-ribosyl)ation is a posttranslational modification catalyzed by the poly(ADP-ribose) polymerases (PARPs). These enzymes covalently modify glutamic, aspartic and lysine amino acid side chains of acceptor proteins by the sequential addition of ADP-ribose (ADPr) units. The poly(ADP-ribose) (pADPr) polymers formed alter the physico-chemical characteristics of the substrate with functional consequences on its biological activities. Recently, non-covalent binding to pADPr has emerged as a key mechanism to modulate and coordinate several intracellular pathways including the DNA damage response, protein stability and cell death. In this review, we describe the basis of non-covalent binding to pADPr that has led to the emerging concept of pADPr-responsive signaling pathways. This review emphasizes the structural elements and the modular strategies developed by pADPr-binding proteins to exert a fine-tuned control of a variety of pathways. Poly(ADP-ribosyl)ation reactions are highly regulated processes, both spatially and temporally, for which at least four specialized pADPr-binding modules accommodate different pADPr structures and reprogram protein functions. In this review, we highlight the role of well-characterized and newly discovered pADPr-binding modules in a diverse set of physiological functions. PMID:23268355
Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge-Modified MM/PBSA Method.

PubMed

Petukh, Marharyta; Li, Minghui; Alexov, Emil

2015-07-01

A new methodology termed Single Amino Acid Mutation based change in Binding free Energy (SAAMBE) was developed to predict the changes of the binding free energy caused by mutations. The method utilizes 3D structures of the corresponding protein-protein complexes and takes advantage of both approaches: sequence- and structure-based methods. The method has two components: a MM/PBSA-based component, and an additional set of statistical terms delivered from statistical investigation of physico-chemical properties of protein complexes. While the approach is rigid body approach and does not explicitly consider plausible conformational changes caused by the binding, the effect of conformational changes, including changes away from binding interface, on electrostatics are mimicked with amino acid specific dielectric constants. This provides significant improvement of SAAMBE predictions as indicated by better match against experimentally determined binding free energy changes over 1300 mutations in 43 proteins. The final benchmarking resulted in a very good agreement with experimental data (correlation coefficient 0.624) while the algorithm being fast enough to allow for large-scale calculations (the average time is less than a minute per mutation).
LSD1 demethylase and the methyl-binding protein PHF20L1 prevent SET7 methyltransferase-dependent proteolysis of the stem-cell protein SOX2.

PubMed

Zhang, Chunxiao; Hoang, Nam; Leng, Feng; Saxena, Lovely; Lee, Logan; Alejo, Salvador; Qi, Dandan; Khal, Anthony; Sun, Hong; Lu, Fei; Zhang, Hui

2018-03-09

The pluripotency-controlling stem-cell protein SRY-box 2 (SOX2) plays a pivotal role in maintaining the self-renewal and pluripotency of embryonic stem cells and also of teratocarcinoma or embryonic carcinoma cells. SOX2 is monomethylated at lysine 119 (Lys-119) in mouse embryonic stem cells by the SET7 methyltransferase, and this methylation triggers ubiquitin-dependent SOX2 proteolysis. However, the molecular regulators and mechanisms controlling SET7-induced SOX2 proteolysis are unknown. Here, we report that in human ovarian teratocarcinoma PA-1 cells, methylation-dependent SOX2 proteolysis is dynamically regulated by the LSD1 lysine demethylase and a methyl-binding protein, PHD finger protein 20-like 1 (PHF20L1). We found that LSD1 not only removes the methyl group from monomethylated Lys-117 (equivalent to Lys-119 in mouse SOX2), but it also demethylates monomethylated Lys-42 in SOX2, a reaction that SET7 also regulated and that also triggered SOX2 proteolysis. Our studies further revealed that PHF20L1 binds both monomethylated Lys-42 and Lys-117 in SOX2 and thereby prevents SOX2 proteolysis. Down-regulation of either LSD1 or PHF20L1 promoted SOX2 proteolysis, which was prevented by SET7 inactivation in both PA-1 and mouse embryonic stem cells. Our studies also disclosed that LSD1 and PHF20L1 normally regulate the growth of pluripotent mouse embryonic stem cells and PA-1 cells by preventing methylation-dependent SOX2 proteolysis. In conclusion, our findings reveal an important mechanism by which the stability of the pluripotency-controlling stem-cell protein SOX2 is dynamically regulated by the activities of SET7, LSD1, and PHF20L1 in pluripotent stem cells. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.
Effect of fullerenol surface chemistry on nanoparticle binding-induced protein misfolding

NASA Astrophysics Data System (ADS)

Radic, Slaven; Nedumpully-Govindan, Praveen; Chen, Ran; Salonen, Emppu; Brown, Jared M.; Ke, Pu Chun; Ding, Feng

2014-06-01

Fullerene and its derivatives with different surface chemistry have great potential in biomedical applications. Accordingly, it is important to delineate the impact of these carbon-based nanoparticles on protein structure, dynamics, and subsequently function. Here, we focused on the effect of hydroxylation -- a common strategy for solubilizing and functionalizing fullerene -- on protein-nanoparticle interactions using a model protein, ubiquitin. We applied a set of complementary computational modeling methods, including docking and molecular dynamics simulations with both explicit and implicit solvent, to illustrate the impact of hydroxylated fullerenes on the structure and dynamics of ubiquitin. We found that all derivatives bound to the model protein. Specifically, the more hydrophilic nanoparticles with a higher number of hydroxyl groups bound to the surface of the protein via hydrogen bonds, which stabilized the protein without inducing large conformational changes in the protein structure. In contrast, fullerene derivatives with a smaller number of hydroxyl groups buried their hydrophobic surface inside the protein, thereby causing protein denaturation. Overall, our results revealed a distinct role of surface chemistry on nanoparticle-protein binding and binding-induced protein misfolding.Fullerene and its derivatives with different surface chemistry have great potential in biomedical applications. Accordingly, it is important to delineate the impact of these carbon-based nanoparticles on protein structure, dynamics, and subsequently function. Here, we focused on the effect of hydroxylation -- a common strategy for solubilizing and functionalizing fullerene -- on protein-nanoparticle interactions using a model protein, ubiquitin. We applied a set of complementary computational modeling methods, including docking and molecular dynamics simulations with both explicit and implicit solvent, to illustrate the impact of hydroxylated fullerenes on the structure and dynamics of ubiquitin. We found that all derivatives bound to the model protein. Specifically, the more hydrophilic nanoparticles with a higher number of hydroxyl groups bound to the surface of the protein via hydrogen bonds, which stabilized the protein without inducing large conformational changes in the protein structure. In contrast, fullerene derivatives with a smaller number of hydroxyl groups buried their hydrophobic surface inside the protein, thereby causing protein denaturation. Overall, our results revealed a distinct role of surface chemistry on nanoparticle-protein binding and binding-induced protein misfolding. Electronic supplementary information (ESI) is available: Fluorescence spectra, ITC, CD spectra and other data as described in the text. See DOI: 10.1039/c4nr01544d
Discovering rules for protein-ligand specificity using support vector inductive logic programming.

PubMed

Kelley, Lawrence A; Shrimpton, Paul J; Muggleton, Stephen H; Sternberg, Michael J E

2009-09-01

Structural genomics initiatives are rapidly generating vast numbers of protein structures. Comparative modelling is also capable of producing accurate structural models for many protein sequences. However, for many of the known structures, functions are not yet determined, and in many modelling tasks, an accurate structural model does not necessarily tell us about function. Thus, there is a pressing need for high-throughput methods for determining function from structure. The spatial arrangement of key amino acids in a folded protein, on the surface or buried in clefts, is often the determinants of its biological function. A central aim of molecular biology is to understand the relationship between such substructures or surfaces and biological function, leading both to function prediction and to function design. We present a new general method for discovering the features of binding pockets that confer specificity for particular ligands. Using a recently developed machine-learning technique which couples the rule-discovery approach of inductive logic programming with the statistical learning power of support vector machines, we are able to discriminate, with high precision (90%) and recall (86%) between pockets that bind FAD and those that bind NAD on a large benchmark set given only the geometry and composition of the backbone of the binding pocket without the use of docking. In addition, we learn rules governing this specificity which can feed into protein functional design protocols. An analysis of the rules found suggests that key features of the binding pocket may be tied to conformational freedom in the ligand. The representation is sufficiently general to be applicable to any discriminatory binding problem. All programs and data sets are freely available to non-commercial users at http://www.sbg.bio.ic.ac.uk/svilp_ligand/.
Understanding the mechanisms of protein-DNA interactions

NASA Astrophysics Data System (ADS)

Lavery, Richard

2004-03-01

Structural, biochemical and thermodynamic data on protein-DNA interactions show that specific recognition cannot be reduced to a simple set of binary interactions between the partners (such as hydrogen bonds, ion pairs or steric contacts). The mechanical properties of the partners also play a role and, in the case of DNA, variations in both conformation and flexibility as a function of base sequence can be a significant factor in guiding a protein to the correct binding site. All-atom molecular modeling offers a means of analyzing the role of different binding mechanisms within protein-DNA complexes of known structure. This however requires estimating the binding strengths for the full range of sequences with which a given protein can interact. Since this number grows exponentially with the length of the binding site it is necessary to find a method to accelerate the calculations. We have achieved this by using a multi-copy approach (ADAPT) which allows us to build a DNA fragment with a variable base sequence. The results obtained with this method correlate well with experimental consensus binding sequences. They enable us to show that indirect recognition mechanisms involving the sequence dependent properties of DNA play a significant role in many complexes. This approach also offers a means of predicting protein binding sites on the basis of binding energies, which is complementary to conventional lexical techniques.
Massively parallel de novo protein design for targeted therapeutics.

PubMed

Chevalier, Aaron; Silva, Daniel-Adriano; Rocklin, Gabriel J; Hicks, Derrick R; Vergara, Renan; Murapa, Patience; Bernard, Steffen M; Zhang, Lu; Lam, Kwok-Ho; Yao, Guorui; Bahl, Christopher D; Miyashita, Shin-Ichiro; Goreshnik, Inna; Fuller, James T; Koday, Merika T; Jenkins, Cody M; Colvin, Tom; Carter, Lauren; Bohn, Alan; Bryan, Cassie M; Fernández-Velasco, D Alejandro; Stewart, Lance; Dong, Min; Huang, Xuhui; Jin, Rongsheng; Wilson, Ian A; Fuller, Deborah H; Baker, David

2017-10-05

De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37-43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing.
Massively parallel de novo protein design for targeted therapeutics

NASA Astrophysics Data System (ADS)

Chevalier, Aaron; Silva, Daniel-Adriano; Rocklin, Gabriel J.; Hicks, Derrick R.; Vergara, Renan; Murapa, Patience; Bernard, Steffen M.; Zhang, Lu; Lam, Kwok-Ho; Yao, Guorui; Bahl, Christopher D.; Miyashita, Shin-Ichiro; Goreshnik, Inna; Fuller, James T.; Koday, Merika T.; Jenkins, Cody M.; Colvin, Tom; Carter, Lauren; Bohn, Alan; Bryan, Cassie M.; Fernández-Velasco, D. Alejandro; Stewart, Lance; Dong, Min; Huang, Xuhui; Jin, Rongsheng; Wilson, Ian A.; Fuller, Deborah H.; Baker, David

2017-10-01

De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37-43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing.
Massively parallel de novo protein design for targeted therapeutics

PubMed Central

Chevalier, Aaron; Silva, Daniel-Adriano; Rocklin, Gabriel J.; Hicks, Derrick R.; Vergara, Renan; Murapa, Patience; Bernard, Steffen M.; Zhang, Lu; Lam, Kwok-Ho; Yao, Guorui; Bahl, Christopher D.; Miyashita, Shin-Ichiro; Goreshnik, Inna; Fuller, James T.; Koday, Merika T.; Jenkins, Cody M.; Colvin, Tom; Carter, Lauren; Bohn, Alan; Bryan, Cassie M.; Fernández-Velasco, D. Alejandro; Stewart, Lance; Dong, Min; Huang, Xuhui; Jin, Rongsheng; Wilson, Ian A.; Fuller, Deborah H.; Baker, David

2018-01-01

De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37–43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing. PMID:28953867
Initiation of Phage Infection by Partial Unfolding and Prolyl Isomerization*♦

PubMed Central

Hoffmann-Thoms, Stephanie; Weininger, Ulrich; Eckert, Barbara; Jakob, Roman P.; Koch, Johanna R.; Balbach, Jochen; Schmid, Franz X.

2013-01-01

Infection of Escherichia coli by the filamentous phage fd starts with the binding of the N2 domain of the phage gene-3-protein to an F pilus. This interaction triggers partial unfolding of the gene-3-protein, cis → trans isomerization at Pro-213, and domain disassembly, thereby exposing its binding site for the ultimate receptor TolA. The trans-proline sets a molecular timer to maintain the binding-active state long enough for the phage to interact with TolA. We elucidated the changes in structure and local stability that lead to partial unfolding and thus to the activation of the gene-3-protein for phage infection. Protein folding and TolA binding experiments were combined with real-time NMR spectroscopy, amide hydrogen exchange measurements, and phage infectivity assays. In combination, the results provide a molecular picture of how a local unfolding reaction couples with prolyl isomerization not only to generate the activated state of a protein but also to maintain it for an extended time. PMID:23486474
From small sweeteners to sweet proteins: anatomy of the binding sites of the human T1R2_T1R3 receptor.

PubMed

Morini, Gabriella; Bassoli, Angela; Temussi, Piero A

2005-08-25

The sweet taste receptor, a heterodimeric G protein coupled receptor (GPCR) protein, formed by the T1R2 and T1R3 subunits, recognizes several sweet compounds including carbohydrates, amino acids, peptides, proteins, and synthetic sweeteners. Its similarity with the metabotropic glutamate mGluR1 receptor allowed us to build homology models. All possible dimers formed by combinations of the human T1R2 and T1R3 subunits, modeled on the A (closed) or B (open) chains of the extracellular ligand binding domain of the mGluR1 template, yield four ligand binding sites for low-molecular-weight sweeteners. These sites were probed by docking a set of molecules representative of all classes of sweet compounds and calculating the free energy of ligand binding. These sites are not easily accessible to sweet proteins, but docking experiments in silico showed that sweet proteins can bind to a secondary site without entering the deep cleft. Our models account for many experimental observations on the tastes of sweeteners, including sweetness synergy, and can help to design new sweeteners.
A kinesin-1 binding motif in vaccinia virus that is widespread throughout the human genome

PubMed Central

Dodding, Mark P; Mitter, Richard; Humphries, Ashley C; Way, Michael

2011-01-01

Transport of cargoes by kinesin-1 is essential for many cellular processes. Nevertheless, the number of proteins known to recruit kinesin-1 via its cargo binding light chain (KLC) is still quite small. We also know relatively little about the molecular features that define kinesin-1 binding. We now show that a bipartite tryptophan-based kinesin-1 binding motif, originally identified in Calsyntenin is present in A36, a vaccinia integral membrane protein. This bipartite motif in A36 is required for kinesin-1-dependent transport of the virus to the cell periphery. Bioinformatic analysis reveals that related bipartite tryptophan-based motifs are present in over 450 human proteins. Using vaccinia as a surrogate cargo, we show that regions of proteins containing this motif can function to recruit KLC and promote virus transport in the absence of A36. These proteins interact with the kinesin light chain outside the context of infection and have distinct preferences for KLC1 and KLC2. Our observations demonstrate that KLC binding can be conferred by a common set of features that are found in a wide range of proteins associated with diverse cellular functions and human diseases. PMID:21915095
Phage display of engineered binding proteins.

PubMed

Levisson, Mark; Spruijt, Ruud B; Winkel, Ingrid Nolla; Kengen, Servé W M; van der Oost, John

2014-01-01

In current purification processes optimization of the capture step generally has a large impact on cost reduction. At present, valuable biomolecules are often produced in relatively low concentrations and, consequently, the eventual selective separation from complex mixtures can be rather inefficient. A separation technology based on a very selective high-affinity binding may overcome these problems. Proteins in their natural environment manifest functionality by interacting specifically and often with relatively high affinity with other molecules, such as substrates, inhibitors, activators, or other proteins. At present, antibodies are the most commonly used binding proteins in numerous applications. However, antibodies do have limitations, such as high production costs, low stability, and a complex patent landscape. A novel approach is therefore to use non-immunoglobulin engineered binding proteins in affinity purification. In order to obtain engineered binders with a desired specificity, a large mutant library of the new to-be-developed binding protein has to be created and screened for potential binders. A powerful technique to screen and select for proteins with desired properties from a large pool of variants is phage display. Here, we indicate several criteria for potential binding protein scaffolds and explain the principle of M13 phage display. In addition, we describe experimental protocols for the initial steps in setting up a M13 phage display system based on the pComb3X vector, including construction of the phagemid vector, production of phages displaying the protein of interest, and confirmation of display on the M13 phage.
Computational Design of Ligand Binding Proteins with High Affinity and Selectivity

PubMed Central

Dou, Jiayi; Doyle, Lindsey; Nelson, Jorgen W.; Schena, Alberto; Jankowski, Wojciech; Kalodimos, Charalampos G.; Johnsson, Kai; Stoddard, Barry L.; Baker, David

2014-01-01

The ability to design proteins with high affinity and selectivity for any given small molecule would have numerous applications in biosensing, diagnostics, and therapeutics, and is a rigorous test of our understanding of the physiochemical principles that govern molecular recognition phenomena. Attempts to design ligand binding proteins have met with little success, however, and the computational design of precise molecular recognition between proteins and small molecules remains an “unsolved problem”1. We describe a general method for the computational design of small molecule binding sites with pre-organized hydrogen bonding and hydrophobic interfaces and high overall shape complementary to the ligand, and use it to design protein binding sites for the steroid digoxigenin (DIG). Of 17 designs that were experimentally characterized, two bind DIG; the highest affinity design has the lowest predicted interaction energy and the most pre-organized binding site in the set. A comprehensive binding-fitness landscape of this design generated by library selection and deep sequencing was used to guide optimization of binding affinity to a picomolar level, and two X-ray co-crystal structures of optimized complexes show atomic level agreement with the design models. The designed binder has a high selectivity for DIG over the related steroids digitoxigenin, progesterone, and β-estradiol, which can be reprogrammed through the designed hydrogen-bonding interactions. Taken together, the binding fitness landscape, co-crystal structures, and thermodynamic binding parameters illustrate how increases in binding affinity can result from distal sequence changes that limit the protein ensemble to conformers making the most energetically favorable interactions with the ligand. The computational design method presented here should enable the development of a new generation of biosensors, therapeutics, and diagnostics. PMID:24005320
Multiple binding modes for palmitate to barley lipid transfer protein facilitated by the presence of proline 12.

PubMed

Smith, Lorna J; Gunsteren, Wilfred F Van; Allison, Jane R

2013-01-01

Molecular dynamics simulations have been used to characterise the binding of the fatty acid ligand palmitate in the barley lipid transfer protein 1 (LTP) internal cavity. Two different palmitate binding modes (1 and 2), with similar protein-ligand interaction energies, have been identified using a variety of simulation strategies. These strategies include applying experimental protein-ligand atom-atom distance restraints during the simulation, or protonating the palmitate ligand, or using the vacuum GROMOS 54B7 force-field parameter set for the ligand during the initial stages of the simulations. In both the binding modes identified the palmitate carboxylate head group hydrogen bonds with main chain amide groups in helix A, residues 4 to 19, of the protein. In binding mode 1 the hydrogen bonds are to Lys 11, Cys 13, and Leu 14 and in binding mode 2 to Thr 15, Tyr 16, Val 17, Ser 24 and also to the OH of Thr 15. In both cases palmitate binding exploits irregularity of the intrahelical hydrogen-bonding pattern in helix A of barley LTP due to the presence of Pro 12. Simulations of two variants of barley LTP, namely the single mutant Pro12Val and the double mutant Pro12Val Pro70Val, show that Pro 12 is required for persistent palmitate binding in the LTP cavity. Overall, the work identifies key MD simulation approaches for characterizing the details of protein-ligand interactions in complexes where NMR data provide insufficient restraints. Copyright © 2012 The Protein Society.
Protein design on computers. Five new proteins: Shpilka, Grendel, Fingerclasp, Leather, and Aida.

PubMed

Sander, C; Vriend, G; Bazan, F; Horovitz, A; Nakamura, H; Ribas, L; Finkelstein, A V; Lockhart, A; Merkl, R; Perry, L J

1992-02-01

What is the current state of the art in protein design? This question was approached in a recent two-week protein design workshop sponsored by EMBO and held at the EMBL in Heidelberg. The goals were to test available design tools and to explore new design strategies. Five novel proteins were designed: Shpilka, a sandwich of two four-stranded beta-sheets, a scaffold on which to explore variations in loop topology; Grendel, a four-helical membrane anchor, ready for fusion to water-soluble functional domains; Finger-clasp, a dimer of interdigitating beta-beta-alpha units, the simplest variant of the "handshake" structural class; Aida, an antibody binding surface intended to be specific for flavodoxin; Leather--a minimal NAD binding domain, extracted from a larger protein. Each design is available as a set of three-dimensional coordinates, the corresponding amino acid sequence and a set of analytical results. The designs are placed in the public domain for scrutiny, improvement, and possible experimental verification.
ProMateus—an open research approach to protein-binding sites analysis

PubMed Central

Neuvirth, Hani; Heinemann, Uri; Birnbaum, David; Tishby, Naftali; Schreiber, Gideon

2007-01-01

The development of bioinformatic tools by individual labs results in the abundance of parallel programs for the same task. For example, identification of binding site regions between interacting proteins is done using: ProMate, WHISCY, PPI-Pred, PINUP and others. All servers first identify unique properties of binding sites and then incorporate them into a predictor. Obviously, the resulting prediction would improve if the most suitable parameters from each of those predictors would be incorporated into one server. However, because of the variation in methods and databases, this is currently not feasible. Here, the protein-binding site prediction server is extended into a general protein-binding sites research tool, ProMateus. This web tool, based on ProMate's infrastructure enables the easy exploration and incorporation of new features and databases by the user, providing an evaluation of the benefit of individual features and their combination within a set framework. This transforms the individual research into a community exercise, bringing out the best from all users for optimized predictions. The analysis is demonstrated on a database of protein protein and protein-DNA interactions. This approach is basically different from that used in generating meta-servers. The implications of the open-research approach are discussed. ProMateus is available at http://bip.weizmann.ac.il/promate. PMID:17488838

Identification and characterization of intracellular proteins that bind oligonucleotides with phosphorothioate linkages

PubMed Central

Liang, Xue-hai; Sun, Hong; Shen, Wen; Crooke, Stanley T.

2015-01-01

Although the RNase H-dependent mechanism of inhibition of gene expression by chemically modified antisense oligonucleotides (ASOs) has been well characterized, little is known about the interactions between ASOs and intracellular proteins that may alter cellular localization and/or potency of ASOs. Here, we report the identification of 56 intracellular ASO-binding proteins using multi-step affinity selection approaches. Many of the tested proteins had no significant effect on ASO activity; however, some proteins, including La/SSB, NPM1, ANXA2, VARS and PC4, appeared to enhance ASO activities, likely through mechanisms related to subcellular distribution. VARS and ANXA2 co-localized with ASOs in endocytic organelles, and reduction in the level of VARS altered lysosome/ASO localization patterns, implying that these proteins may facilitate ASO release from the endocytic pathway. Depletion of La and NPM1 reduced nuclear ASO levels, suggesting potential roles in ASO nuclear accumulation. On the other hand, Ku70 and Ku80 proteins inhibited ASO activity, most likely by competition with RNase H1 for ASO/RNA duplex binding. Our results demonstrate that phosphorothioate-modified ASOs bind a set of cellular proteins that affect ASO activity via different mechanisms. PMID:25712094
Organic bioelectronics probing conformational changes in surface confined proteins

NASA Astrophysics Data System (ADS)

Macchia, Eleonora; Alberga, Domenico; Manoli, Kyriaki; Mangiatordi, Giuseppe F.; Magliulo, Maria; Palazzo, Gerardo; Giordano, Francesco; Lattanzi, Gianluca; Torsi, Luisa

2016-06-01

The study of proteins confined on a surface has attracted a great deal of attention due to its relevance in the development of bio-systems for laboratory and clinical settings. In this respect, organic bio-electronic platforms can be used as tools to achieve a deeper understanding of the processes involving protein interfaces. In this work, biotin-binding proteins have been integrated in two different organic thin-film transistor (TFT) configurations to separately address the changes occurring in the protein-ligand complex morphology and dipole moment. This has been achieved by decoupling the output current change upon binding, taken as the transducing signal, into its component figures of merit. In particular, the threshold voltage is related to the protein dipole moment, while the field-effect mobility is associated with conformational changes occurring in the proteins of the layer when ligand binding occurs. Molecular Dynamics simulations on the whole avidin tetramer in presence and absence of ligands were carried out, to evaluate how the tight interactions with the ligand affect the protein dipole moment and the conformation of the loops surrounding the binding pocket. These simulations allow assembling a rather complete picture of the studied interaction processes and support the interpretation of the experimental results.
Organic bioelectronics probing conformational changes in surface confined proteins

PubMed Central

Macchia, Eleonora; Alberga, Domenico; Manoli, Kyriaki; Mangiatordi, Giuseppe F.; Magliulo, Maria; Palazzo, Gerardo; Giordano, Francesco; Lattanzi, Gianluca; Torsi, Luisa

2016-01-01

The study of proteins confined on a surface has attracted a great deal of attention due to its relevance in the development of bio-systems for laboratory and clinical settings. In this respect, organic bio-electronic platforms can be used as tools to achieve a deeper understanding of the processes involving protein interfaces. In this work, biotin-binding proteins have been integrated in two different organic thin-film transistor (TFT) configurations to separately address the changes occurring in the protein-ligand complex morphology and dipole moment. This has been achieved by decoupling the output current change upon binding, taken as the transducing signal, into its component figures of merit. In particular, the threshold voltage is related to the protein dipole moment, while the field-effect mobility is associated with conformational changes occurring in the proteins of the layer when ligand binding occurs. Molecular Dynamics simulations on the whole avidin tetramer in presence and absence of ligands were carried out, to evaluate how the tight interactions with the ligand affect the protein dipole moment and the conformation of the loops surrounding the binding pocket. These simulations allow assembling a rather complete picture of the studied interaction processes and support the interpretation of the experimental results. PMID:27312768
Identification of a Novel Hypocholesterolemic Protein, Major Royal Jelly Protein 1, Derived from Royal Jelly

PubMed Central

Asai, Saori; Kusada, Mio; Watanabe, Suzuyo; Kawashima, Takuji; Nakamura, Tadashi; Shimada, Masaya; Goto, Tsuyoshi; Nagaoka, Satoshi

2014-01-01

Royal jelly (RJ) intake lowers serum cholesterol levels in animals and humans, but the active component in RJ that lowers serum cholesterol level and its molecular mechanism are unclear. In this study, we set out to identify the bile acid-binding protein contained in RJ, because dietary bile acid-binding proteins including soybean protein and its peptide are effective in ameliorating hypercholesterolemia. Using a cholic acid-conjugated column, we separated some bile acid-binding proteins from RJ and identified the major RJ protein 1 (MRJP1), MRJP2, and MRJP3 as novel bile acid-binding proteins from RJ, based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Purified MRJP1, which is the most abundant protein of the bile acid-binding proteins in RJ, exhibited taurocholate-binding activity in vitro. The micellar solubility of cholesterol was significantly decreased in the presence of MRJP1 compared with casein in vitro. Liver bile acids levels were significantly increased, and cholesterol 7α-hydroxylase (CYP7A1) mRNA and protein tended to increase by MRJP1 feeding compared with the control. CYP7A1 mRNA and protein levels were significantly increased by MRJP1 tryptic hydrolysate treatment compared with that of casein tryptic hydrolysate in hepatocytes. MRJP1 hypocholesterolemic effect has been investigated in rats. The cholesterol-lowering action induced by MRJP1 occurs because MRJP1 interacts with bile acids induces a significant increase in fecal bile acids excretion and a tendency to increase in fecal cholesterol excretion and also enhances the hepatic cholesterol catabolism. We have identified, for the first time, a novel hypocholesterolemic protein, MRJP1, in RJ. Interestingly, MRJP1 exhibits greater hypocholesterolemic activity than the medicine β-sitosterol in rats. PMID:25144734
A new test set for validating predictions of protein-ligand interaction.

PubMed

Nissink, J Willem M; Murray, Chris; Hartshorn, Mike; Verdonk, Marcel L; Cole, Jason C; Taylor, Robin

2002-12-01

We present a large test set of protein-ligand complexes for the purpose of validating algorithms that rely on the prediction of protein-ligand interactions. The set consists of 305 complexes with protonation states assigned by manual inspection. The following checks have been carried out to identify unsuitable entries in this set: (1) assessing the involvement of crystallographically related protein units in ligand binding; (2) identification of bad clashes between protein side chains and ligand; and (3) assessment of structural errors, and/or inconsistency of ligand placement with crystal structure electron density. In addition, the set has been pruned to assure diversity in terms of protein-ligand structures, and subsets are supplied for different protein-structure resolution ranges. A classification of the set by protein type is available. As an illustration, validation results are shown for GOLD and SuperStar. GOLD is a program that performs flexible protein-ligand docking, and SuperStar is used for the prediction of favorable interaction sites in proteins. The new CCDC/Astex test set is freely available to the scientific community (http://www.ccdc.cam.ac.uk). Copyright 2002 Wiley-Liss, Inc.
Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation

NASA Astrophysics Data System (ADS)

Grudinin, Sergei; Kadukova, Maria; Eisenbarth, Andreas; Marillet, Simon; Cazals, Frédéric

2016-09-01

The 2015 D3R Grand Challenge provided an opportunity to test our new model for the binding free energy of small molecules, as well as to assess our protocol to predict binding poses for protein-ligand complexes. Our pose predictions were ranked 3-9 for the HSP90 dataset, depending on the assessment metric. For the MAP4K dataset the ranks are very dispersed and equal to 2-35, depending on the assessment metric, which does not provide any insight into the accuracy of the method. The main success of our pose prediction protocol was the re-scoring stage using the recently developed Convex-PL potential. We make a thorough analysis of our docking predictions made with AutoDock Vina and discuss the effect of the choice of rigid receptor templates, the number of flexible residues in the binding pocket, the binding pocket size, and the benefits of re-scoring. However, the main challenge was to predict experimentally determined binding affinities for two blind test sets. Our affinity prediction model consisted of two terms, a pairwise-additive enthalpy, and a non pairwise-additive entropy. We trained the free parameters of the model with a regularized regression using affinity and structural data from the PDBBind database. Our model performed very well on the training set, however, failed on the two test sets. We explain the drawback and pitfalls of our model, in particular in terms of relative coverage of the test set by the training set and missed dynamical properties from crystal structures, and discuss different routes to improve it.
Protein-RNA specificity by high-throughput principal component analysis of NMR spectra.

PubMed

Collins, Katherine M; Oregioni, Alain; Robertson, Laura E; Kelly, Geoff; Ramos, Andres

2015-03-31

Defining the RNA target selectivity of the proteins regulating mRNA metabolism is a key issue in RNA biology. Here we present a novel use of principal component analysis (PCA) to extract the RNA sequence preference of RNA binding proteins. We show that PCA can be used to compare the changes in the nuclear magnetic resonance (NMR) spectrum of a protein upon binding a set of quasi-degenerate RNAs and define the nucleobase specificity. We couple this application of PCA to an automated NMR spectra recording and processing protocol and obtain an unbiased and high-throughput NMR method for the analysis of nucleobase preference in protein-RNA interactions. We test the method on the RNA binding domains of three important regulators of RNA metabolism. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
An overview on the delivery of antitumor drug doxorubicin by carrier proteins.

PubMed

Agudelo, D; Bérubé, G; Tajmir-Riahi, H A

2016-07-01

Serum proteins play an increasing role as drug carriers in the clinical settings. In this review, we have compared the binding modalities of anticancer drug doxorubicin (DOX) to three model carrier proteins, human serum albumin (HSA), bovine serum albumin (BSA) and milk beta-lactoglobulin (β-LG) in order to determine the potential application of these model proteins in DOX delivery. Molecular modeling studies showed stronger binding of DOX with HSA than BSA and β-LG with the free binding energies of -10.75 (DOX-HSA), -9.31 (DOX-BSA) and -8.12kcal/mol (DOX-β-LG). Extensive H-boding network stabilizes DOX-protein conjugation and played a major role in drug-protein complex formation. DOX complexation induced major alterations of HSA and BSA conformations, while did not alter β-LG secondary structure. The literature review shows that these proteins can potentially be used for delivery of DOX in vitro and in vivo. Copyright © 2016 Elsevier B.V. All rights reserved.
Genome scale enzyme–metabolite and drug–target interaction predictions using the signature molecular descriptor

DOE PAGES

Faulon, Jean-Loup; Misra, Milind; Martin, Shawn; ...

2007-11-23

Motivation: Identifying protein enzymatic or pharmacological activities are important areas of research in biology and chemistry. Biological and chemical databases are increasingly being populated with linkages between protein sequences and chemical structures. Additionally, there is now sufficient information to apply machine-learning techniques to predict interactions between chemicals and proteins at a genome scale. Current machine-learning techniques use as input either protein sequences and structures or chemical information. We propose here a method to infer protein–chemical interactions using heterogeneous input consisting of both protein sequence and chemical information. Results: Our method relies on expressing proteins and chemicals with a common cheminformaticsmore » representation. We demonstrate our approach by predicting whether proteins can catalyze reactions not present in training sets. We also predict whether a given drug can bind a target, in the absence of prior binding information for that drug and target. Lastly, such predictions cannot be made with current machine-learning techniques requiring binding information for individual reactions or individual targets.« less
On the nature of cavities on protein surfaces: application to the identification of drug-binding sites.

PubMed

Nayal, Murad; Honig, Barry

2006-06-01

In this article we introduce a new method for the identification and the accurate characterization of protein surface cavities. The method is encoded in the program SCREEN (Surface Cavity REcognition and EvaluatioN). As a first test of the utility of our approach we used SCREEN to locate and analyze the surface cavities of a nonredundant set of 99 proteins cocrystallized with drugs. We find that this set of proteins has on average about 14 distinct cavities per protein. In all cases, a drug is bound at one (and sometimes more than one) of these cavities. Using cavity size alone as a criterion for predicting drug-binding sites yields a high balanced error rate of 15.7%, with only 71.7% coverage. Here we characterize each surface cavity by computing a comprehensive set of 408 physicochemical, structural, and geometric attributes. By applying modern machine learning techniques (Random Forests) we were able to develop a classifier that can identify drug-binding cavities with a balanced error rate of 7.2% and coverage of 88.9%. Only 18 of the 408 cavity attributes had a statistically significant role in the prediction. Of these 18 important attributes, almost all involved size and shape rather than physicochemical properties of the surface cavity. The implications of these results are discussed. A SCREEN Web server is available at http://interface.bioc.columbia.edu/screen. 2006 Wiley-Liss, Inc.
Characterizing carbohydrate-protein interactions by NMR

PubMed Central

Bewley, Carole A.; Shahzad-ul-Hussan, Syed

2013-01-01

Interactions between proteins and soluble carbohydrates and/or surface displayed glycans are central to countless recognition, attachment and signaling events in biology. The physical chemical features associated with these binding events vary considerably, depending on the biological system of interest. For example, carbohydrate-protein interactions can be stoichiometric or multivalent, the protein receptors can be monomeric or oligomeric, and the specificity of recognition can be highly stringent or rather promiscuous. Equilibrium dissociation constants for carbohydrate binding are known to vary from micromolar to millimolar, with weak interactions being far more prevalent; and individual carbohydrate binding sites can be truly symmetrical or merely homologous, and hence, the affinities of individual sites within a single protein can vary, as can the order of binding. Several factors, including the weak affinities with which glycans bind their protein receptors, the dynamic nature of the glycans themselves, and the non-equivalent interactions among oligomeric carbohydrate receptors, have made NMR an especially powerful tool for studying and defining carbohydrate-protein interactions. Here we describe those NMR approaches that have proven to be the most robust in characterizing these systems, and explain what type of information can (or cannot) be obtained from each. Our goal is to provide to the reader the information necessary for selecting the correct experiment or sets of experiments to characterize their carbohydrate-protein interaction of interest. PMID:23784792
Coherent Conformational Degrees of Freedom as a Structural Basis for Allosteric Communication

PubMed Central

Mitternacht, Simon; Berezovsky, Igor N.

2011-01-01

Conformational changes in allosteric regulation can to a large extent be described as motion along one or a few coherent degrees of freedom. The states involved are inherent to the protein, in the sense that they are visited by the protein also in the absence of effector ligands. Previously, we developed the measure binding leverage to find sites where ligand binding can shift the conformational equilibrium of a protein. Binding leverage is calculated for a set of motion vectors representing independent conformational degrees of freedom. In this paper, to analyze allosteric communication between binding sites, we introduce the concept of leverage coupling, based on the assumption that only pairs of sites that couple to the same conformational degrees of freedom can be allosterically connected. We demonstrate how leverage coupling can be used to analyze allosteric communication in a range of enzymes (regulated by both ligand binding and post-translational modifications) and huge molecular machines such as chaperones. Leverage coupling can be calculated for any protein structure to analyze both biological and latent catalytic and regulatory sites. PMID:22174669
BcL-xL Conformational Changes upon Fragment Binding Revealed by NMR

PubMed Central

Aguirre, Clémentine; ten Brink, Tim; Walker, Olivier; Guillière, Florence; Davesne, Dany; Krimm, Isabelle

2013-01-01

Protein-protein interactions represent difficult but increasingly important targets for the design of therapeutic compounds able to interfere with biological processes. Recently, fragment-based strategies have been proposed as attractive approaches for the elaboration of protein-protein surface inhibitors from fragment-like molecules. One major challenge in targeting protein-protein interactions is related to the structural adaptation of the protein surface upon molecular recognition. Methods capable of identifying subtle conformational changes of proteins upon fragment binding are therefore required at the early steps of the drug design process. In this report we present a fast NMR method able to probe subtle conformational changes upon fragment binding. The approach relies on the comparison of experimental fragment-induced Chemical Shift Perturbation (CSP) of amine protons to CSP simulated for a set of docked fragment poses, considering the ring-current effect from fragment binding. We illustrate the method by the retrospective analysis of the complex between the anti-apoptotic Bcl-xL protein and the fragment 4′-fluoro-[1,1′-biphenyl]-4-carboxylic acid that was previously shown to bind one of the Bcl-xL hot spots. The CSP-based approach shows that the protein undergoes a subtle conformational rearrangement upon interaction, for residues located in helices 2, 3 and the very beginning of 5. Our observations are corroborated by residual dipolar coupling measurements performed on the free and fragment-bound forms of the Bcl-xL protein. These NMR-based results are in total agreement with previous molecular dynamic calculations that evidenced a high flexibility of Bcl-xL around the binding site. Here we show that CSP of protein amine protons are useful and reliable structural probes. Therefore, we propose to use CSP simulation to assess protein conformational changes upon ligand binding in the fragment-based drug design approach. PMID:23717610
Big domains are novel Ca²+-binding modules: evidences from big domains of Leptospira immunoglobulin-like (Lig) proteins.

PubMed

Raman, Rajeev; Rajanikanth, V; Palaniappan, Raghavan U M; Lin, Yi-Pin; He, Hongxuan; McDonough, Sean P; Sharma, Yogendra; Chang, Yung-Fu

2010-12-29

Many bacterial surface exposed proteins mediate the host-pathogen interaction more effectively in the presence of Ca²+. Leptospiral immunoglobulin-like (Lig) proteins, LigA and LigB, are surface exposed proteins containing Bacterial immunoglobulin like (Big) domains. The function of proteins which contain Big fold is not known. Based on the possible similarities of immunoglobulin and βγ-crystallin folds, we here explore the important question whether Ca²+ binds to a Big domains, which would provide a novel functional role of the proteins containing Big fold. We selected six individual Big domains for this study (three from the conserved part of LigA and LigB, denoted as Lig A3, Lig A4, and LigBCon5; two from the variable region of LigA, i.e., 9(th) (Lig A9) and 10(th) repeats (Lig A10); and one from the variable region of LigB, i.e., LigBCen2. We have also studied the conserved region covering the three and six repeats (LigBCon1-3 and LigCon). All these proteins bind the calcium-mimic dye Stains-all. All the selected four domains bind Ca²+ with dissociation constants of 2-4 µM. Lig A9 and Lig A10 domains fold well with moderate thermal stability, have β-sheet conformation and form homodimers. Fluorescence spectra of Big domains show a specific doublet (at 317 and 330 nm), probably due to Trp interaction with a Phe residue. Equilibrium unfolding of selected Big domains is similar and follows a two-state model, suggesting the similarity in their fold. We demonstrate that the Lig are Ca²+-binding proteins, with Big domains harbouring the binding motif. We conclude that despite differences in sequence, a Big motif binds Ca²+. This work thus sets up a strong possibility for classifying the proteins containing Big domains as a novel family of Ca²+-binding proteins. Since Big domain is a part of many proteins in bacterial kingdom, we suggest a possible function these proteins via Ca²+ binding.
Big Domains Are Novel Ca2+-Binding Modules: Evidences from Big Domains of Leptospira Immunoglobulin-Like (Lig) Proteins

PubMed Central

Palaniappan, Raghavan U. M.; Lin, Yi-Pin; He, Hongxuan; McDonough, Sean P.; Sharma, Yogendra; Chang, Yung-Fu

2010-01-01

Background Many bacterial surface exposed proteins mediate the host-pathogen interaction more effectively in the presence of Ca2+. Leptospiral immunoglobulin-like (Lig) proteins, LigA and LigB, are surface exposed proteins containing Bacterial immunoglobulin like (Big) domains. The function of proteins which contain Big fold is not known. Based on the possible similarities of immunoglobulin and βγ-crystallin folds, we here explore the important question whether Ca2+ binds to a Big domains, which would provide a novel functional role of the proteins containing Big fold. Principal Findings We selected six individual Big domains for this study (three from the conserved part of LigA and LigB, denoted as Lig A3, Lig A4, and LigBCon5; two from the variable region of LigA, i.e., 9th (Lig A9) and 10th repeats (Lig A10); and one from the variable region of LigB, i.e., LigBCen2. We have also studied the conserved region covering the three and six repeats (LigBCon1-3 and LigCon). All these proteins bind the calcium-mimic dye Stains-all. All the selected four domains bind Ca2+ with dissociation constants of 2–4 µM. Lig A9 and Lig A10 domains fold well with moderate thermal stability, have β-sheet conformation and form homodimers. Fluorescence spectra of Big domains show a specific doublet (at 317 and 330 nm), probably due to Trp interaction with a Phe residue. Equilibrium unfolding of selected Big domains is similar and follows a two-state model, suggesting the similarity in their fold. Conclusions We demonstrate that the Lig are Ca2+-binding proteins, with Big domains harbouring the binding motif. We conclude that despite differences in sequence, a Big motif binds Ca2+. This work thus sets up a strong possibility for classifying the proteins containing Big domains as a novel family of Ca2+-binding proteins. Since Big domain is a part of many proteins in bacterial kingdom, we suggest a possible function these proteins via Ca2+ binding. PMID:21206924
Detection and characterization of nonspecific, sparsely-populated binding modes in the early stages of complexation

PubMed Central

Cardone, A.; Bornstein, A.; Pant, H. C.; Brady, M.; Sriram, R.; Hassan, S. A.

2015-01-01

A method is proposed to study protein-ligand binding in a system governed by specific and non-specific interactions. Strong associations lead to narrow distributions in the proteins configuration space; weak and ultra-weak associations lead instead to broader distributions, a manifestation of non-specific, sparsely-populated binding modes with multiple interfaces. The method is based on the notion that a discrete set of preferential first-encounter modes are metastable states from which stable (pre-relaxation) complexes at equilibrium evolve. The method can be used to explore alternative pathways of complexation with statistical significance and can be integrated into a general algorithm to study protein interaction networks. The method is applied to a peptide-protein complex. The peptide adopts several low-population conformers and binds in a variety of modes with a broad range of affinities. The system is thus well suited to analyze general features of binding, including conformational selection, multiplicity of binding modes, and nonspecific interactions, and to illustrate how the method can be applied to study these problems systematically. The equilibrium distributions can be used to generate biasing functions for simulations of multiprotein systems from which bulk thermodynamic quantities can be calculated. PMID:25782918
Characterization of domain-peptide interaction interface: a case study on the amphiphysin-1 SH3 domain.

PubMed

Hou, Tingjun; Zhang, Wei; Case, David A; Wang, Wei

2008-02-29

Many important protein-protein interactions are mediated by peptide recognition modular domains, such as the Src homology 3 (SH3), SH2, PDZ, and WW domains. Characterizing the interaction interface of domain-peptide complexes and predicting binding specificity for modular domains are critical for deciphering protein-protein interaction networks. Here, we propose the use of an energetic decomposition analysis to characterize domain-peptide interactions and the molecular interaction energy components (MIECs), including van der Waals, electrostatic, and desolvation energy between residue pairs on the binding interface. We show a proof-of-concept study on the amphiphysin-1 SH3 domain interacting with its peptide ligands. The structures of the human amphiphysin-1 SH3 domain complexed with 884 peptides were first modeled using virtual mutagenesis and optimized by molecular mechanics (MM) minimization. Next, the MIECs between domain and peptide residues were computed using the MM/generalized Born decomposition analysis. We conducted two types of statistical analyses on the MIECs to demonstrate their usefulness for predicting binding affinities of peptides and for classifying peptides into binder and non-binder categories. First, combining partial least squares analysis and genetic algorithm, we fitted linear regression models between the MIECs and the peptide binding affinities on the training data set. These models were then used to predict binding affinities for peptides in the test data set; the predicted values have a correlation coefficient of 0.81 and an unsigned mean error of 0.39 compared with the experimentally measured ones. The partial least squares-genetic algorithm analysis on the MIECs revealed the critical interactions for the binding specificity of the amphiphysin-1 SH3 domain. Next, a support vector machine (SVM) was employed to build classification models based on the MIECs of peptides in the training set. A rigorous training-validation procedure was used to assess the performances of different kernel functions in SVM and different combinations of the MIECs. The best SVM classifier gave satisfactory predictions for the test set, indicated by average prediction accuracy rates of 78% and 91% for the binding and non-binding peptides, respectively. We also showed that the performance of our approach on both binding affinity prediction and binder/non-binder classification was superior to the performances of the conventional MM/Poisson-Boltzmann solvent-accessible surface area and MM/generalized Born solvent-accessible surface area calculations. Our study demonstrates that the analysis of the MIECs between peptides and the SH3 domain can successfully characterize the binding interface, and it provides a framework to derive integrated prediction models for different domain-peptide systems.
Composite Structural Motifs of Binding Sites for Delineating Biological Functions of Proteins

PubMed Central

Kinjo, Akira R.; Nakamura, Haruki

2012-01-01

Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs that represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures. PMID:22347478
GuiTope: an application for mapping random-sequence peptides to protein sequences.

PubMed

Halperin, Rebecca F; Stafford, Phillip; Emery, Jack S; Navalkar, Krupa Arun; Johnston, Stephen Albert

2012-01-03

Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC) at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.
BloodChIP: a database of comparative genome-wide transcription factor binding profiles in human blood cells.

PubMed

Chacon, Diego; Beck, Dominik; Perera, Dilmi; Wong, Jason W H; Pimanda, John E

2014-01-01

The BloodChIP database (http://www.med.unsw.edu.au/CRCWeb.nsf/page/BloodChIP) supports exploration and visualization of combinatorial transcription factor (TF) binding at a particular locus in human CD34-positive and other normal and leukaemic cells or retrieval of target gene sets for user-defined combinations of TFs across one or more cell types. Increasing numbers of genome-wide TF binding profiles are being added to public repositories, and this trend is likely to continue. For the power of these data sets to be fully harnessed by experimental scientists, there is a need for these data to be placed in context and easily accessible for downstream applications. To this end, we have built a user-friendly database that has at its core the genome-wide binding profiles of seven key haematopoietic TFs in human stem/progenitor cells. These binding profiles are compared with binding profiles in normal differentiated and leukaemic cells. We have integrated these TF binding profiles with chromatin marks and expression data in normal and leukaemic cell fractions. All queries can be exported into external sites to construct TF-gene and protein-protein networks and to evaluate the association of genes with cellular processes and tissue expression.

EWS and FUS bind a subset of transcribed genes encoding proteins enriched in RNA regulatory functions.

PubMed

Luo, Yonglun; Blechingberg, Jenny; Fernandes, Ana Miguel; Li, Shengting; Fryland, Tue; Børglum, Anders D; Bolund, Lars; Nielsen, Anders Lade

2015-11-14

FUS (TLS) and EWS (EWSR1) belong to the FET-protein family of RNA and DNA binding proteins. FUS and EWS are structurally and functionally related and participate in transcriptional regulation and RNA processing. FUS and EWS are identified in translocation generated cancer fusion proteins and involved in the human neurological diseases amyotrophic lateral sclerosis and fronto-temporal lobar degeneration. To determine the gene regulatory functions of FUS and EWS at the level of chromatin, we have performed chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq). Our results show that FUS and EWS bind to a subset of actively transcribed genes, that binding often is downstream the poly(A)-signal, and that binding overlaps with RNA polymerase II. Functional examinations of selected target genes identified that FUS and EWS can regulate gene expression at different levels. Gene Ontology analyses showed that FUS and EWS target genes preferentially encode proteins involved in regulatory processes at the RNA level. The presented results yield new insights into gene interactions of EWS and FUS and have identified a set of FUS and EWS target genes involved in pathways at the RNA regulatory level with potential to mediate normal and disease-associated functions of the FUS and EWS proteins.
MUSI: an integrated system for identifying multiple specificity from very large peptide or nucleic acid data sets.

PubMed

Kim, Taehyung; Tyndel, Marc S; Huang, Haiming; Sidhu, Sachdev S; Bader, Gary D; Gfeller, David; Kim, Philip M

2012-03-01

Peptide recognition domains and transcription factors play crucial roles in cellular signaling. They bind linear stretches of amino acids or nucleotides, respectively, with high specificity. Experimental techniques that assess the binding specificity of these domains, such as microarrays or phage display, can retrieve thousands of distinct ligands, providing detailed insight into binding specificity. In particular, the advent of next-generation sequencing has recently increased the throughput of such methods by several orders of magnitude. These advances have helped reveal the presence of distinct binding specificity classes that co-exist within a set of ligands interacting with the same target. Here, we introduce a software system called MUSI that can rapidly analyze very large data sets of binding sequences to determine the relevant binding specificity patterns. Our pipeline provides two major advances. First, it can detect previously unrecognized multiple specificity patterns in any data set. Second, it offers integrated processing of very large data sets from next-generation sequencing machines. The results are visualized as multiple sequence logos describing the different binding preferences of the protein under investigation. We demonstrate the performance of MUSI by analyzing recent phage display data for human SH3 domains as well as microarray data for mouse transcription factors.
BeAtMuSiC: Prediction of changes in protein-protein binding affinity on mutations.

PubMed

Dehouck, Yves; Kwasigroch, Jean Marc; Rooman, Marianne; Gilis, Dimitri

2013-07-01

The ability of proteins to establish highly selective interactions with a variety of (macro)molecular partners is a crucial prerequisite to the realization of their biological functions. The availability of computational tools to evaluate the impact of mutations on protein-protein binding can therefore be valuable in a wide range of industrial and biomedical applications, and help rationalize the consequences of non-synonymous single-nucleotide polymorphisms. BeAtMuSiC (http://babylone.ulb.ac.be/beatmusic) is a coarse-grained predictor of the changes in binding free energy induced by point mutations. It relies on a set of statistical potentials derived from known protein structures, and combines the effect of the mutation on the strength of the interactions at the interface, and on the overall stability of the complex. The BeAtMuSiC server requires as input the structure of the protein-protein complex, and gives the possibility to assess rapidly all possible mutations in a protein chain or at the interface, with predictive performances that are in line with the best current methodologies.
Mutational analysis of vaccinia virus E3 protein: the biological functions do not correlate with its biochemical capacity to bind double-stranded RNA.

PubMed

Dueck, Kevin J; Hu, YuanShen Sandy; Chen, Peter; Deschambault, Yvon; Lee, Jocelyn; Varga, Jessie; Cao, Jingxin

2015-05-01

Vaccinia E3 protein has the biochemical capacity of binding to double-stranded RNA (dsRNA). The best characterized biological functions of the E3 protein include its host range function, suppression of cytokine expression, and inhibition of interferon (IFN)-induced antiviral activity. Currently, the role of the dsRNA binding capacity in the biological functions of the E3 protein is not clear. To further understand the mechanism of the E3 protein biological functions, we performed alanine scanning of the entire dsRNA binding domain of the E3 protein to examine the link between its biochemical capacity of dsRNA binding and biological functions. Of the 115 mutants examined, 20 were defective in dsRNA binding. Although the majority of the mutants defective in dsRNA binding also showed defective replication in HeLa cells, nine mutants (I105A, Y125A, E138A, F148A, F159A, K171A, L182A, L183A, and I187/188A) retained the host range function to various degrees. Further examination of a set of representative E3L mutants showed that residues essential for dsRNA binding are not essential for the biological functions of E3 protein, such as inhibition of protein kinase R (PKR) activation, suppression of cytokine expression, and apoptosis. Thus, data described in this communication strongly indicate the E3 protein performs its biological functions via a novel mechanism which does not correlate with its dsRNA binding activity. dsRNAs produced during virus replication are important pathogen-associated molecular patterns (PAMPs) for inducing antiviral immune responses. One of the strategies used by many viruses to counteract such antiviral immune responses is achieved by producing dsRNA binding proteins, such as poxvirus E3 family proteins, influenza virus NS1, and Ebola virus V35 proteins. The most widely accepted model for the biological functions of this class of viral dsRNA binding proteins is that they bind to and sequester viral dsRNA PAMPs; thus, they suppress the related antiviral immune responses. However, no direct experimental data confirm such a model. In this study of vaccinia E3 protein, we found that the biological functions of the E3 protein are not necessarily linked to its biochemical capacity of dsRNA binding. Thus, our data strongly point to a new concept of virus modulation of cellular antiviral responses triggered by dsRNA PAMPs. Copyright © 2015, American Society for Microbiology. All Rights Reserved.
Conformational Heterogeneity of Unbound Proteins Enhances Recognition in Protein-Protein Encounters.

PubMed

Pallara, Chiara; Rueda, Manuel; Abagyan, Ruben; Fernández-Recio, Juan

2016-07-12

To understand cellular processes at the molecular level we need to improve our knowledge of protein-protein interactions, from a structural, mechanistic, and energetic point of view. Current theoretical studies and computational docking simulations show that protein dynamics plays a key role in protein association and support the need for including protein flexibility in modeling protein interactions. Assuming the conformational selection binding mechanism, in which the unbound state can sample bound conformers, one possible strategy to include flexibility in docking predictions would be the use of conformational ensembles originated from unbound protein structures. Here we present an exhaustive computational study about the use of precomputed unbound ensembles in the context of protein docking, performed on a set of 124 cases of the Protein-Protein Docking Benchmark 3.0. Conformational ensembles were generated by conformational optimization and refinement with MODELLER and by short molecular dynamics trajectories with AMBER. We identified those conformers providing optimal binding and investigated the role of protein conformational heterogeneity in protein-protein recognition. Our results show that a restricted conformational refinement can generate conformers with better binding properties and improve docking encounters in medium-flexible cases. For more flexible cases, a more extended conformational sampling based on Normal Mode Analysis was proven helpful. We found that successful conformers provide better energetic complementarity to the docking partners, which is compatible with recent views of binding association. In addition to the mechanistic considerations, these findings could be exploited for practical docking predictions of improved efficiency.
Relating drug–protein interaction network with drug side effects

PubMed Central

Mizutani, Sayaka; Pauwels, Edouard; Stoven, Véronique; Goto, Susumu; Yamanishi, Yoshihiro

2012-01-01

Motivation: Identifying the emergence and underlying mechanisms of drug side effects is a challenging task in the drug development process. This underscores the importance of system–wide approaches for linking different scales of drug actions; namely drug-protein interactions (molecular scale) and side effects (phenotypic scale) toward side effect prediction for uncharacterized drugs. Results: We performed a large-scale analysis to extract correlated sets of targeted proteins and side effects, based on the co-occurrence of drugs in protein-binding profiles and side effect profiles, using sparse canonical correlation analysis. The analysis of 658 drugs with the two profiles for 1368 proteins and 1339 side effects led to the extraction of 80 correlated sets. Enrichment analyses using KEGG and Gene Ontology showed that most of the correlated sets were significantly enriched with proteins that are involved in the same biological pathways, even if their molecular functions are different. This allowed for a biologically relevant interpretation regarding the relationship between drug–targeted proteins and side effects. The extracted side effects can be regarded as possible phenotypic outcomes by drugs targeting the proteins that appear in the same correlated set. The proposed method is expected to be useful for predicting potential side effects of new drug candidate compounds based on their protein-binding profiles. Supplementary information: Datasets and all results are available at http://web.kuicr.kyoto-u.ac.jp/supp/smizutan/target-effect/. Availability: Software is available at the above supplementary website. Contact: yamanishi@bioreg.kyushu-u.ac.jp, or goto@kuicr.kyoto-u.ac.jp PMID:22962476
Specialized Dynamical Properties of Promiscuous Residues Revealed by Simulated Conformational Ensembles

PubMed Central

2013-01-01

The ability to interact with different partners is one of the most important features in proteins. Proteins that bind a large number of partners (hubs) have been often associated with intrinsic disorder. However, many examples exist of hubs with an ordered structure, and evidence of a general mechanism promoting promiscuity in ordered proteins is still elusive. An intriguing hypothesis is that promiscuous binding sites have specific dynamical properties, distinct from the rest of the interface and pre-existing in the protein isolated state. Here, we present the first comprehensive study of the intrinsic dynamics of promiscuous residues in a large protein data set. Different computational methods, from coarse-grained elastic models to geometry-based sampling methods and to full-atom Molecular Dynamics simulations, were used to generate conformational ensembles for the isolated proteins. The flexibility and dynamic correlations of interface residues with a different degree of binding promiscuity were calculated and compared considering side chain and backbone motions, the latter both on a local and on a global scale. The study revealed that (a) promiscuous residues tend to be more flexible than nonpromiscuous ones, (b) this additional flexibility has a higher degree of organization, and (c) evolutionary conservation and binding promiscuity have opposite effects on intrinsic dynamics. Findings on simulated ensembles were also validated on ensembles of experimental structures extracted from the Protein Data Bank (PDB). Additionally, the low occurrence of single nucleotide polymorphisms observed for promiscuous residues indicated a tendency to preserve binding diversity at these positions. A case study on two ubiquitin-like proteins exemplifies how binding promiscuity in evolutionary related proteins can be modulated by the fine-tuning of the interface dynamics. The interplay between promiscuity and flexibility highlighted here can inspire new directions in protein–protein interaction prediction and design methods. PMID:24250278
Fusion of NUP98 and the SET binding protein 1 (SETBP1) gene in a paediatric acute T cell lymphoblastic leukaemia with t(11;18)(p15;q12).

PubMed

Panagopoulos, Ioannis; Kerndrup, Gitte; Carlsen, Niels; Strömbeck, Bodil; Isaksson, Margareth; Johansson, Bertil

2007-01-01

Three NUP98 chimaeras have previously been reported in T cell acute lymphoblastic leukaemia (T-ALL): NUP98/ADD3, NUP98/CCDC28A, and NUP98/RAP1GDS1. We report a T-ALL with t(11;18)(p15;q12) resulting in a novel NUP98 fusion. Fluorescent in situ hybridisation showed NUP98 and SET binding protein 1(SETBP1) fusion signals; other analyses showed that exon 12 of NUP98 was fused in-frame with exon 5 of SETBP1. Nested polymerase chain reaction did not amplify the reciprocal SETBP1/NUP98, suggesting that NUP98/SETBP1 transcript is pathogenetically important. SETBP1 has previously not been implicated in leukaemias; however, it encodes a protein that specifically interacts with SET, fused to NUP214 in a case of acute undifferentiated leukaemia.
Proteomic analysis of the gamma human papillomavirus type 197 E6 and E7 associated cellular proteins

PubMed Central

Grace, Miranda; Munger, Karl

2016-01-01

Gamma HPV197 was the most frequently identified HPV when human skin cancer specimens were analyzed by deep sequencing. To gain insight into the biological activities of HPV197, we investigated the cellular interactomes of HPV197 E6 and E7. HPV197 E6 protein interacts with a broad spectrum of cellular LXXLL domain proteins, including UBE3A and MAML1. HPV197 E6 also binds and inhibits the TP53 tumor suppressor and interacts with the CCR4-NOT ubiquitin ligase and deadenylation complex. Despite lacking a canonical retinoblastoma (RB1) tumor suppressor binding site, HPV197 E7 binds RB1 and activates E2F transcription. Hence, HPV197 E6 and E7 proteins interact with a similar set of cellular proteins as E6 and E7 proteins encoded by HPVs that have been linked to human carcinogenesis and/or have transforming activities in vitro. PMID:27771561
Ensemble-based virtual screening reveals dual-inhibitors for the p53-MDM2/MDMX interactions.

PubMed

Barakat, Khaled; Mane, Jonathan; Friesen, Douglas; Tuszynski, Jack

2010-02-26

The p53 protein, a guardian of the genome, is inactivated by mutations or deletions in approximately half of human tumors. While in the rest of human tumors, p53 is expressed in wild-type form, yet it is inhibited by over-expression of its cellular regulators MDM2 and MDMX proteins. Although the p53-binding sites within the MDMX and MDM2 proteins are closely related, known MDM2 small-molecule inhibitors have been shown experimentally not to bind to its homolog, MDMX. As a result, the activity of these inhibitors including Nutlin3 is compromised in tumor cells over-expressing MDMX, preventing these compounds from fully activating the p53 protein. Here, we applied the relaxed complex scheme (RCS) to allow for the full receptor flexibility in screening for dual-inhibitors that can mutually antagonize the two p53-regulator proteins. First, we filtered the NCI diversity set, DrugBank compounds and a derivative library for MDM2-inhibitors against 28 dominant MDM2-conformations. Then, we screened the MDM2 top hits against the binding site of p53 within the MDMX target. Results described herein identify a set of compounds that have been computationally predicted to ultimately activate the p53 pathway in tumor cells retaining the wild-type protein. Crown Copyright 2009. Published by Elsevier Inc. All rights reserved.
Competitive tuning: Competition's role in setting the frequency-dependence of Ca2+-dependent proteins

PubMed Central

Patel, Neal M.; Kinzer-Ursem, Tamara L.

2017-01-01

A number of neurological disorders arise from perturbations in biochemical signaling and protein complex formation within neurons. Normally, proteins form networks that when activated produce persistent changes in a synapse’s molecular composition. In hippocampal neurons, calcium ion (Ca2+) flux through N-methyl-D-aspartate (NMDA) receptors activates Ca2+/calmodulin signal transduction networks that either increase or decrease the strength of the neuronal synapse, phenomena known as long-term potentiation (LTP) or long-term depression (LTD), respectively. The calcium-sensor calmodulin (CaM) acts as a common activator of the networks responsible for both LTP and LTD. This is possible, in part, because CaM binding proteins are “tuned” to different Ca2+ flux signals by their unique binding and activation dynamics. Computational modeling is used to describe the binding and activation dynamics of Ca2+/CaM signal transduction and can be used to guide focused experimental studies. Although CaM binds over 100 proteins, practical limitations cause many models to include only one or two CaM-activated proteins. In this work, we view Ca2+/CaM as a limiting resource in the signal transduction pathway owing to its low abundance relative to its binding partners. With this view, we investigate the effect of competitive binding on the dynamics of CaM binding partner activation. Using an explicit model of Ca2+, CaM, and seven highly-expressed hippocampal CaM binding proteins, we find that competition for CaM binding serves as a tuning mechanism: the presence of competitors shifts and sharpens the Ca2+ frequency-dependence of CaM binding proteins. Notably, we find that simulated competition may be sufficient to recreate the in vivo frequency dependence of the CaM-dependent phosphatase calcineurin. Additionally, competition alone (without feedback mechanisms or spatial parameters) could replicate counter-intuitive experimental observations of decreased activation of Ca2+/CaM-dependent protein kinase II in knockout models of neurogranin. We conclude that competitive tuning could be an important dynamic process underlying synaptic plasticity. PMID:29107982
Fungal-type carbohydrate binding modules from the coccolithophore Emiliania huxleyi show binding affinity to cellulose and chitin

PubMed Central

Rooijakkers, Bart J. M.

2018-01-01

Six fungal-type cellulose binding domains were found in the genome of the coccolithophore Emiliania huxleyi and cloned and expressed in Escherichia coli. Sequence comparison indicate high similarity to fungal cellulose binding domains, raising the question of why these domains exist in coccolithophores. The proteins were tested for binding with cellulose and chitin as ligands, which resulted in the identification of two functional carbohydrate binding modules: EHUX2 and EHUX4. Compared to benchmark fungal cellulose binding domain Cel7A-CBM1 from Trichoderma reesei, these proteins showed slightly lower binding to birch and bacterial cellulose, but were more efficient chitin binders. Finally, a set of cellulose binding domains was created based on the shuffling of one well-functioning and one non-functional domain. These were characterized in order to get more information of the binding domain’s sequence–function relationship, indicating characteristic differences between the molecular basis of cellulose versus chitin recognition. As previous reports have showed the presence of cellulose in coccoliths and here we find functional cellulose binding modules, a possible connection is discussed. PMID:29782536
Fungal-type carbohydrate binding modules from the coccolithophore Emiliania huxleyi show binding affinity to cellulose and chitin.

PubMed

Rooijakkers, Bart J M; Ikonen, Martina S; Linder, Markus B

2018-01-01

Six fungal-type cellulose binding domains were found in the genome of the coccolithophore Emiliania huxleyi and cloned and expressed in Escherichia coli. Sequence comparison indicate high similarity to fungal cellulose binding domains, raising the question of why these domains exist in coccolithophores. The proteins were tested for binding with cellulose and chitin as ligands, which resulted in the identification of two functional carbohydrate binding modules: EHUX2 and EHUX4. Compared to benchmark fungal cellulose binding domain Cel7A-CBM1 from Trichoderma reesei, these proteins showed slightly lower binding to birch and bacterial cellulose, but were more efficient chitin binders. Finally, a set of cellulose binding domains was created based on the shuffling of one well-functioning and one non-functional domain. These were characterized in order to get more information of the binding domain's sequence-function relationship, indicating characteristic differences between the molecular basis of cellulose versus chitin recognition. As previous reports have showed the presence of cellulose in coccoliths and here we find functional cellulose binding modules, a possible connection is discussed.
Identification and characterization of intracellular proteins that bind oligonucleotides with phosphorothioate linkages.

PubMed

Liang, Xue-hai; Sun, Hong; Shen, Wen; Crooke, Stanley T

2015-03-11

Although the RNase H-dependent mechanism of inhibition of gene expression by chemically modified antisense oligonucleotides (ASOs) has been well characterized, little is known about the interactions between ASOs and intracellular proteins that may alter cellular localization and/or potency of ASOs. Here, we report the identification of 56 intracellular ASO-binding proteins using multi-step affinity selection approaches. Many of the tested proteins had no significant effect on ASO activity; however, some proteins, including La/SSB, NPM1, ANXA2, VARS and PC4, appeared to enhance ASO activities, likely through mechanisms related to subcellular distribution. VARS and ANXA2 co-localized with ASOs in endocytic organelles, and reduction in the level of VARS altered lysosome/ASO localization patterns, implying that these proteins may facilitate ASO release from the endocytic pathway. Depletion of La and NPM1 reduced nuclear ASO levels, suggesting potential roles in ASO nuclear accumulation. On the other hand, Ku70 and Ku80 proteins inhibited ASO activity, most likely by competition with RNase H1 for ASO/RNA duplex binding. Our results demonstrate that phosphorothioate-modified ASOs bind a set of cellular proteins that affect ASO activity via different mechanisms. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Trans‐acting translational regulatory RNA binding proteins

PubMed Central

Harvey, Robert F.; Smith, Tom S.; Mulroney, Thomas; Queiroz, Rayner M. L.; Pizzinga, Mariavittoria; Dezi, Veronica; Villenueva, Eneko; Ramakrishna, Manasa

2018-01-01

The canonical molecular machinery required for global mRNA translation and its control has been well defined, with distinct sets of proteins involved in the processes of translation initiation, elongation and termination. Additionally, noncanonical, trans‐acting regulatory RNA‐binding proteins (RBPs) are necessary to provide mRNA‐specific translation, and these interact with 5′ and 3′ untranslated regions and coding regions of mRNA to regulate ribosome recruitment and transit. Recently it has also been demonstrated that trans‐acting ribosomal proteins direct the translation of specific mRNAs. Importantly, it has been shown that subsets of RBPs often work in concert, forming distinct regulatory complexes upon different cellular perturbation, creating an RBP combinatorial code, which through the translation of specific subsets of mRNAs, dictate cell fate. With the development of new methodologies, a plethora of novel RNA binding proteins have recently been identified, although the function of many of these proteins within mRNA translation is unknown. In this review we will discuss these methodologies and their shortcomings when applied to the study of translation, which need to be addressed to enable a better understanding of trans‐acting translational regulatory proteins. Moreover, we discuss the protein domains that are responsible for RNA binding as well as the RNA motifs to which they bind, and the role of trans‐acting ribosomal proteins in directing the translation of specific mRNAs. This article is categorized under: 1RNA Interactions with Proteins and Other Molecules > RNA–Protein Complexes2Translation > Translation Regulation3Translation > Translation Mechanisms PMID:29341429
Trans-acting translational regulatory RNA binding proteins.

PubMed

Harvey, Robert F; Smith, Tom S; Mulroney, Thomas; Queiroz, Rayner M L; Pizzinga, Mariavittoria; Dezi, Veronica; Villenueva, Eneko; Ramakrishna, Manasa; Lilley, Kathryn S; Willis, Anne E

2018-05-01

The canonical molecular machinery required for global mRNA translation and its control has been well defined, with distinct sets of proteins involved in the processes of translation initiation, elongation and termination. Additionally, noncanonical, trans-acting regulatory RNA-binding proteins (RBPs) are necessary to provide mRNA-specific translation, and these interact with 5' and 3' untranslated regions and coding regions of mRNA to regulate ribosome recruitment and transit. Recently it has also been demonstrated that trans-acting ribosomal proteins direct the translation of specific mRNAs. Importantly, it has been shown that subsets of RBPs often work in concert, forming distinct regulatory complexes upon different cellular perturbation, creating an RBP combinatorial code, which through the translation of specific subsets of mRNAs, dictate cell fate. With the development of new methodologies, a plethora of novel RNA binding proteins have recently been identified, although the function of many of these proteins within mRNA translation is unknown. In this review we will discuss these methodologies and their shortcomings when applied to the study of translation, which need to be addressed to enable a better understanding of trans-acting translational regulatory proteins. Moreover, we discuss the protein domains that are responsible for RNA binding as well as the RNA motifs to which they bind, and the role of trans-acting ribosomal proteins in directing the translation of specific mRNAs. This article is categorized under: RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes Translation > Translation Regulation Translation > Translation Mechanisms. © 2018 Medical Research Council and University of Cambridge. WIREs RNA published by Wiley Periodicals, Inc.
Group Additivity in Ligand Binding Affinity: An Alternative Approach to Ligand Efficiency.

PubMed

Reynolds, Charles H; Reynolds, Ryan C

2017-12-26

Group additivity is a concept that has been successfully applied to a variety of thermochemical and kinetic properties. This includes drug discovery, where functional group additivity is often assumed in ligand binding. Ligand efficiency can be recast as a special case of group additivity where ΔG/HA is the group equivalent (HA is the number of non-hydrogen atoms in a ligand). Analysis of a large data set of protein-ligand binding affinities (K i ) for diverse targets shows that in general ligand binding is distinctly nonlinear. It is possible to create a group equivalent scheme for ligand binding, but only in the context of closely related proteins, at least with regard to size. This finding has broad implications for drug design from both experimental and computational points of view. It also offers a path forward for a more general scheme to assess the efficiency of ligand binding.
Drug Promiscuity in PDB: Protein Binding Site Similarity Is Key.

PubMed

Haupt, V Joachim; Daminelli, Simone; Schroeder, Michael

2013-01-01

Drug repositioning applies established drugs to new disease indications with increasing success. A pre-requisite for drug repurposing is drug promiscuity (polypharmacology) - a drug's ability to bind to several targets. There is a long standing debate on the reasons for drug promiscuity. Based on large compound screens, hydrophobicity and molecular weight have been suggested as key reasons. However, the results are sometimes contradictory and leave space for further analysis. Protein structures offer a structural dimension to explain promiscuity: Can a drug bind multiple targets because the drug is flexible or because the targets are structurally similar or even share similar binding sites? We present a systematic study of drug promiscuity based on structural data of PDB target proteins with a set of 164 promiscuous drugs. We show that there is no correlation between the degree of promiscuity and ligand properties such as hydrophobicity or molecular weight but a weak correlation to conformational flexibility. However, we do find a correlation between promiscuity and structural similarity as well as binding site similarity of protein targets. In particular, 71% of the drugs have at least two targets with similar binding sites. In order to overcome issues in detection of remotely similar binding sites, we employed a score for binding site similarity: LigandRMSD measures the similarity of the aligned ligands and uncovers remote local similarities in proteins. It can be applied to arbitrary structural binding site alignments. Three representative examples, namely the anti-cancer drug methotrexate, the natural product quercetin and the anti-diabetic drug acarbose are discussed in detail. Our findings suggest that global structural and binding site similarity play a more important role to explain the observed drug promiscuity in the PDB than physicochemical drug properties like hydrophobicity or molecular weight. Additionally, we find ligand flexibility to have a minor influence.
Kinetic analysis of a monoclonal therapeutic antibody and its single-chain homolog by surface plasmon resonance.

PubMed

Patel, Rekha; Andrien, Bruce A

2010-01-01

Monoclonal antibodies (mAbs) and antibody fragments have become an emerging class of therapeutics since 1986. Their versatility enables them to be engineered for optimal efficiency and decreased immunogenicity, and the path to market has been set by recent regulatory approvals. One of the initial criteria for success of any protein or antibody therapeutic is to understand its binding characteristics to the target antigen. Surface plasmon resonance (SPR) has been widely used and is an important tool for ligand-antigen binding characterization. In this work, the binding kinetics of a recombinant mAb and its single-chain antibody homolog, single-chain variable fragment (scFv), was analyzed by SPR. These two proteins target the same antigen. The binding kinetics of the mAb (bivalent antibody) and scFv (monovalent scFv) for this antigen was analyzed along with an assessment of the thermodynamics of the binding interactions. Alternative binding configurations were investigated to evaluate potential experimental bias because theoretically experimental binding configuration should have no impact on binding kinetics. Self-association binding kinetics in the proteins' respective formulation solutions and antigen epitope mapping were also evaluated. Functional characterization of monoclonal and single-chain antibodies has become just as important as structural characterization in the biotechnology field.
Free Energy Perturbation Calculation of Relative Binding Free Energy between Broadly Neutralizing Antibodies and the gp120 Glycoprotein of HIV-1.

PubMed

Clark, Anthony J; Gindin, Tatyana; Zhang, Baoshan; Wang, Lingle; Abel, Robert; Murret, Colleen S; Xu, Fang; Bao, Amy; Lu, Nina J; Zhou, Tongqing; Kwong, Peter D; Shapiro, Lawrence; Honig, Barry; Friesner, Richard A

2017-04-07

Direct calculation of relative binding affinities between antibodies and antigens is a long-sought goal. However, despite substantial efforts, no generally applicable computational method has been described. Here, we describe a systematic free energy perturbation (FEP) protocol and calculate the binding affinities between the gp120 envelope glycoprotein of HIV-1 and three broadly neutralizing antibodies (bNAbs) of the VRC01 class. The protocol has been adapted from successful studies of small molecules to address the challenges associated with modeling protein-protein interactions. Specifically, we built homology models of the three antibody-gp120 complexes, extended the sampling times for large bulky residues, incorporated the modeling of glycans on the surface of gp120, and utilized continuum solvent-based loop prediction protocols to improve sampling. We present three experimental surface plasmon resonance data sets, in which antibody residues in the antibody/gp120 interface were systematically mutated to alanine. The RMS error in the large set (55 total cases) of FEP tests as compared to these experiments, 0.68kcal/mol, is near experimental accuracy, and it compares favorably with the results obtained from a simpler, empirical methodology. The correlation coefficient for the combined data set including residues with glycan contacts, R 2 =0.49, should be sufficient to guide the choice of residues for antibody optimization projects, assuming that this level of accuracy can be realized in prospective prediction. More generally, these results are encouraging with regard to the possibility of using an FEP approach to calculate the magnitude of protein-protein binding affinities. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Ribonucleoprotein complexes in neurologic diseases.

PubMed

Ule, Jernej

2008-10-01

Ribonucleoprotein (RNP) complexes regulate the tissue-specific RNA processing and transport that increases the coding capacity of our genome and the ability to respond quickly and precisely to the diverse set of signals. This review focuses on three proteins that are part of RNP complexes in most cells of our body: TAR DNA-binding protein (TDP-43), the survival motor neuron protein (SMN), and fragile-X mental retardation protein (FMRP). In particular, the review asks the question why these ubiquitous proteins are primarily associated with defects in specific regions of the central nervous system? To understand this question, it is important to understand the role of genetic and cellular environment in causing the defect in the protein, as well as how the defective protein leads to misregulation of specific target RNAs. Two approaches for comprehensive analysis of defective RNA-protein interactions are presented. The first approach defines the RNA code or the collection of proteins that bind to a certain cis-acting RNA site in order to lead to a predictable outcome. The second approach defines the RNA map or the summary of positions on target RNAs where binding of a particular RNA-binding protein leads to a predictable outcome. As we learn more about the RNA codes and maps that guide the action of the dynamic RNP world in our brain, possibilities for new treatments of neurologic diseases are bound to emerge.
TRF1 and TRF2 use different mechanisms to find telomeric DNA but share a novel mechanism to search for protein partners at telomeres.

PubMed

Lin, Jiangguo; Countryman, Preston; Buncher, Noah; Kaur, Parminder; E, Longjiang; Zhang, Yiyun; Gibson, Greg; You, Changjiang; Watkins, Simon C; Piehler, Jacob; Opresko, Patricia L; Kad, Neil M; Wang, Hong

2014-02-01

Human telomeres are maintained by the shelterin protein complex in which TRF1 and TRF2 bind directly to duplex telomeric DNA. How these proteins find telomeric sequences among a genome of billions of base pairs and how they find protein partners to form the shelterin complex remains uncertain. Using single-molecule fluorescence imaging of quantum dot-labeled TRF1 and TRF2, we study how these proteins locate TTAGGG repeats on DNA tightropes. By virtue of its basic domain TRF2 performs an extensive 1D search on nontelomeric DNA, whereas TRF1's 1D search is limited. Unlike the stable and static associations observed for other proteins at specific binding sites, TRF proteins possess reduced binding stability marked by transient binding (∼ 9-17 s) and slow 1D diffusion on specific telomeric regions. These slow diffusion constants yield activation energy barriers to sliding ∼ 2.8-3.6 κ(B)T greater than those for nontelomeric DNA. We propose that the TRF proteins use 1D sliding to find protein partners and assemble the shelterin complex, which in turn stabilizes the interaction with specific telomeric DNA. This 'tag-team proofreading' represents a more general mechanism to ensure a specific set of proteins interact with each other on long repetitive specific DNA sequences without requiring external energy sources.
Gene encoding herbicide safener binding protein

DOEpatents

Walton, Jonathan D.; Scott-Craig, John S.

1999-01-01

The cDNA encoding safener binding protein (SafBP), also referred to as SBP1, is set forth in FIG. 5 and SEQ ID No. 1. The deduced amino acid sequence is provided in FIG. 5 and SEQ ID No. 2. Methods of making and using SBP1 and SafBP to alter a plant's sensitivity to certain herbicides or a plant's responsiveness to certain safeners are also provided, as well as expression vectors, transgenic plants or other organisms transfected with said vectors and seeds from said plants.
FINDSITE-metal: Integrating evolutionary information and machine learning for structure-based metal binding site prediction at the proteome level

PubMed Central

Brylinski, Michal; Skolnick, Jeffrey

2010-01-01

The rapid accumulation of gene sequences, many of which are hypothetical proteins with unknown function, has stimulated the development of accurate computational tools for protein function prediction with evolution/structure-based approaches showing considerable promise. In this paper, we present FINDSITE-metal, a new threading-based method designed specifically to detect metal binding sites in modeled protein structures. Comprehensive benchmarks using different quality protein structures show that weakly homologous protein models provide sufficient structural information for quite accurate annotation by FINDSITE-metal. Combining structure/evolutionary information with machine learning results in highly accurate metal binding annotations; for protein models constructed by TASSER, whose average Cα RMSD from the native structure is 8.9 Å, 59.5% (71.9%) of the best of top five predicted metal locations are within 4 Å (8 Å) from a bound metal in the crystal structure. For most of the targets, multiple metal binding sites are detected with the best predicted binding site at rank 1 and within the top 2 ranks in 65.6% and 83.1% of the cases, respectively. Furthermore, for iron, copper, zinc, calcium and magnesium ions, the binding metal can be predicted with high, typically 70-90%, accuracy. FINDSITE-metal also provides a set of confidence indexes that help assess the reliability of predictions. Finally, we describe the proteome-wide application of FINDSITE-metal that quantifies the metal binding complement of the human proteome. FINDSITE-metal is freely available to the academic community at http://cssb.biology.gatech.edu/findsite-metal/. PMID:21287609
The Carboxy-Terminal Domain of Hsc70 Provides Binding Sites for a Distinct Set of Chaperone Cofactors

PubMed Central

Demand, Jens; Lüders, Jens; Höhfeld, Jörg

1998-01-01

The modulation of the chaperone activity of the heat shock cognate Hsc70 protein in mammalian cells involves cooperation with chaperone cofactors, such as Hsp40; BAG-1; the Hsc70-interacting protein, Hip; and the Hsc70-Hsp90-organizing protein, Hop. By employing the yeast two-hybrid system and in vitro interaction assays, we have provided insight into the structural basis that underlies Hsc70’s cooperation with different cofactors. The carboxy-terminal domain of Hsc70, previously shown to form a lid over the peptide binding pocket of the chaperone protein, mediates the interaction of Hsc70 with Hsp40 and Hop. Remarkably, the two cofactors bind to the carboxy terminus of Hsc70 in a noncompetitive manner, revealing the existence of distinct binding sites for Hsp40 and Hop within this domain. In contrast, Hip interacts exclusively with the amino-terminal ATPase domain of Hsc70. Hence, Hsc70 possesses separate nonoverlapping binding sites for Hsp40, Hip, and Hop. This appears to enable the chaperone protein to cooperate simultaneously with multiple cofactors. On the other hand, BAG-1 and Hip have recently been shown to compete in binding to the ATPase domain. Our data thus establish the existence of a network of cooperating and competing cofactors regulating the chaperone activity of Hsc70 in the mammalian cell. PMID:9528774
Toward Improved Force-Field Accuracy through Sensitivity Analysis of Host-Guest Binding Thermodynamics

PubMed Central

Yin, Jian; Fenley, Andrew T.; Henriksen, Niel M.; Gilson, Michael K.

2015-01-01

Improving the capability of atomistic computer models to predict the thermodynamics of noncovalent binding is critical for successful structure-based drug design, and the accuracy of such calculations remains limited by non-optimal force field parameters. Ideally, one would incorporate protein-ligand affinity data into force field parametrization, but this would be inefficient and costly. We now demonstrate that sensitivity analysis can be used to efficiently tune Lennard-Jones parameters of aqueous host-guest systems for increasingly accurate calculations of binding enthalpy. These results highlight the promise of a comprehensive use of calorimetric host-guest binding data, along with existing validation data sets, to improve force field parameters for the simulation of noncovalent binding, with the ultimate goal of making protein-ligand modeling more accurate and hence speeding drug discovery. PMID:26181208
Prediction of Protein-Protein Interaction Sites Using Electrostatic Desolvation Profiles

PubMed Central

Fiorucci, Sébastien; Zacharias, Martin

2010-01-01

Abstract Protein-protein complex formation involves removal of water from the interface region. Surface regions with a small free energy penalty for water removal or desolvation may correspond to preferred interaction sites. A method to calculate the electrostatic free energy of placing a neutral low-dielectric probe at various protein surface positions has been designed and applied to characterize putative interaction sites. Based on solutions of the finite-difference Poisson equation, this method also includes long-range electrostatic contributions and the protein solvent boundary shape in contrast to accessible-surface-area-based solvation energies. Calculations on a large set of proteins indicate that in many cases (>90%), the known binding site overlaps with one of the six regions of lowest electrostatic desolvation penalty (overlap with the lowest desolvation region for 48% of proteins). Since the onset of electrostatic desolvation occurs even before direct protein-protein contact formation, it may help guide proteins toward the binding region in the final stage of complex formation. It is interesting that the probe desolvation properties associated with residue types were found to depend to some degree on whether the residue was outside of or part of a binding site. The probe desolvation penalty was on average smaller if the residue was part of a binding site compared to other surface locations. Applications to several antigen-antibody complexes demonstrated that the approach might be useful not only to predict protein interaction sites in general but to map potential antigenic epitopes on protein surfaces. PMID:20441756
Physicochemical characteristics of structurally determined metabolite-protein and drug-protein binding events with respect to binding specificity.

PubMed

Korkuć, Paula; Walther, Dirk

2015-01-01

To better understand and ultimately predict both the metabolic activities as well as the signaling functions of metabolites, a detailed understanding of the physical interactions of metabolites with proteins is highly desirable. Focusing in particular on protein binding specificity vs. promiscuity, we performed a comprehensive analysis of the physicochemical properties of compound-protein binding events as reported in the Protein Data Bank (PDB). We compared the molecular and structural characteristics obtained for metabolites to those of the well-studied interactions of drug compounds with proteins. Promiscuously binding metabolites and drugs are characterized by low molecular weight and high structural flexibility. Unlike reported for drug compounds, low rather than high hydrophobicity appears associated, albeit weakly, with promiscuous binding for the metabolite set investigated in this study. Across several physicochemical properties, drug compounds exhibit characteristic binding propensities that are distinguishable from those associated with metabolites. Prediction of target diversity and compound promiscuity using physicochemical properties was possible at modest accuracy levels only, but was consistently better for drugs than for metabolites. Compound properties capturing structural flexibility and hydrogen-bond formation descriptors proved most informative in PLS-based prediction models. With regard to diversity of enzymatic activities of the respective metabolite target enzymes, the metabolites benzylsuccinate, hypoxanthine, trimethylamine N-oxide, oleoylglycerol, and resorcinol showed very narrow process involvement, while glycine, imidazole, tryptophan, succinate, and glutathione were identified to possess broad enzymatic reaction scopes. Promiscuous metabolites were found to mainly serve as general energy currency compounds, but were identified to also be involved in signaling processes and to appear in diverse organismal systems (digestive and nervous system) suggesting specific molecular and physiological roles of promiscuous metabolites.
Physicochemical characteristics of structurally determined metabolite-protein and drug-protein binding events with respect to binding specificity

PubMed Central

Korkuć, Paula; Walther, Dirk

2015-01-01

To better understand and ultimately predict both the metabolic activities as well as the signaling functions of metabolites, a detailed understanding of the physical interactions of metabolites with proteins is highly desirable. Focusing in particular on protein binding specificity vs. promiscuity, we performed a comprehensive analysis of the physicochemical properties of compound-protein binding events as reported in the Protein Data Bank (PDB). We compared the molecular and structural characteristics obtained for metabolites to those of the well-studied interactions of drug compounds with proteins. Promiscuously binding metabolites and drugs are characterized by low molecular weight and high structural flexibility. Unlike reported for drug compounds, low rather than high hydrophobicity appears associated, albeit weakly, with promiscuous binding for the metabolite set investigated in this study. Across several physicochemical properties, drug compounds exhibit characteristic binding propensities that are distinguishable from those associated with metabolites. Prediction of target diversity and compound promiscuity using physicochemical properties was possible at modest accuracy levels only, but was consistently better for drugs than for metabolites. Compound properties capturing structural flexibility and hydrogen-bond formation descriptors proved most informative in PLS-based prediction models. With regard to diversity of enzymatic activities of the respective metabolite target enzymes, the metabolites benzylsuccinate, hypoxanthine, trimethylamine N-oxide, oleoylglycerol, and resorcinol showed very narrow process involvement, while glycine, imidazole, tryptophan, succinate, and glutathione were identified to possess broad enzymatic reaction scopes. Promiscuous metabolites were found to mainly serve as general energy currency compounds, but were identified to also be involved in signaling processes and to appear in diverse organismal systems (digestive and nervous system) suggesting specific molecular and physiological roles of promiscuous metabolites. PMID:26442281
A genome-wide interactome of DNA-associated proteins in the human liver.

PubMed

Ramaker, Ryne C; Savic, Daniel; Hardigan, Andrew A; Newberry, Kimberly; Cooper, Gregory M; Myers, Richard M; Cooper, Sara J

2017-11-01

Large-scale efforts like the ENCODE Project have made tremendous progress in cataloging the genomic binding patterns of DNA-associated proteins (DAPs), such as transcription factors (TFs). However, most chromatin immunoprecipitation-sequencing (ChIP-seq) analyses have focused on a few immortalized cell lines whose activities and physiology differ in important ways from endogenous cells and tissues. Consequently, binding data from primary human tissue are essential to improving our understanding of in vivo gene regulation. Here, we identify and analyze more than 440,000 binding sites using ChIP-seq data for 20 DAPs in two human liver tissue samples. We integrated binding data with transcriptome and phased WGS data to investigate allelic DAP interactions and the impact of heterozygous sequence variation on the expression of neighboring genes. Our tissue-based data set exhibits binding patterns more consistent with liver biology than cell lines, and we describe uses of these data to better prioritize impactful noncoding variation. Collectively, our rich data set offers novel insights into genome function in human liver tissue and provides a valuable resource for assessing disease-related disruptions. © 2017 Ramaker et al.; Published by Cold Spring Harbor Laboratory Press.
Discovering amino acid patterns on binding sites in protein complexes

PubMed Central

Kuo, Huang-Cheng; Ong, Ping-Lin; Lin, Jung-Chang; Huang, Jen-Peng

2011-01-01

Discovering amino acid (AA) patterns on protein binding sites has recently become popular. We propose a method to discover the association relationship among AAs on binding sites. Such knowledge of binding sites is very helpful in predicting protein-protein interactions. In this paper, we focus on protein complexes which have protein-protein recognition. The association rule mining technique is used to discover geographically adjacent amino acids on a binding site of a protein complex. When mining, instead of treating all AAs of binding sites as a transaction, we geographically partition AAs of binding sites in a protein complex. AAs in a partition are treated as a transaction. For the partition process, AAs on a binding site are projected from three-dimensional to two-dimensional. And then, assisted with a circular grid, AAs on the binding site are placed into grid cells. A circular grid has ten rings: a central ring, the second ring with 6 sectors, the third ring with 12 sectors, and later rings are added to four sectors in order. As for the radius of each ring, we examined the complexes and found that 10Å is a suitable range, which can be set by the user. After placing these recognition complexes on the circular grid, we obtain mining records (i.e. transactions) from each sector. A sector is regarded as a record. Finally, we use the association rule to mine these records for frequent AA patterns. If the support of an AA pattern is larger than the predetermined minimum support (i.e. threshold), it is called a frequent pattern. With these discovered patterns, we offer the biologists a novel point of view, which will improve the prediction accuracy of protein-protein recognition. In our experiments, we produced the AA patterns by data mining. As a result, we found that arginine (arg) most frequently appears on the binding sites of two proteins in the recognition protein complexes, while cysteine (cys) appears the fewest. In addition, if we discriminate the shape of binding sites between concave and convex further, we discover that patterns {arg, glu, asp} and {arg, ser, asp} on the concave shape of binding sites in a protein more frequently (i.e. higher probability) make contact with {lys} or {arg} on the convex shape of binding sites in another protein. Thus, we can confidently achieve a rate of at least 78%. On the other hand {val, gly, lys} on the convex surface of binding sites in proteins is more frequently in contact with {asp} on the concave site of another protein, and the confidence achieved is over 81%. Applying data mining in biology can reveal more facts that may otherwise be ignored or not easily discovered by the naked eye. Furthermore, we can discover more relationships among AAs on binding sites by appropriately rotating these residues on binding sites from a three-dimension to two-dimension perspective. We designed a circular grid to deposit the data, which total to 463 records consisting of AAs. Then we used the association rules to mine these records for discovering relationships. The proposed method in this paper provides an insight into the characteristics of binding sites for recognition complexes. PMID:21464838
Structural insights into binding of small molecule inhibitors to Enhancer of Zeste Homolog 2

NASA Astrophysics Data System (ADS)

Kalinić, Marko; Zloh, Mire; Erić, Slavica

2014-11-01

Enhancer of Zeste Homolog 2 (EZH2) is a SET domain protein lysine methyltransferase (PKMT) which has recently emerged as a chemically tractable and therapeutically promising epigenetic target, evidenced by the discovery and characterization of potent and highly selective EZH2 inhibitors. However, no experimental structures of the inhibitors co-crystallized to EZH2 have been resolved, and the structural basis for their activity and selectivity remains unknown. Considering the need to minimize cross-reactivity between prospective PKMT inhibitors, much can be learned from understanding the molecular basis for selective inhibition of EZH2. Thus, to elucidate the binding of small-molecule inhibitors to EZH2, we have developed a model of its fully-formed cofactor binding site and used it to carry out molecular dynamics simulations of protein-ligand complexes, followed by molecular mechanics/generalized born surface area calculations. The obtained results are in good agreement with biochemical inhibition data and reflect the structure-activity relationships of known ligands. Our findings suggest that the variable and flexible post-SET domain plays an important role in inhibitor binding, allowing possibly distinct binding modes of inhibitors with only small variations in their structure. Insights from this study present a good basis for design of novel and optimization of existing compounds targeting the cofactor binding site of EZH2.
Analysis and prediction of calcium-binding pockets from apo-protein structures exhibiting calcium-induced localized conformational changes

PubMed Central

Wang, Xue; Zhao, Kun; Kirberger, Michael; Wong, Hing; Chen, Guantao; Yang, Jenny J

2010-01-01

Calcium binding in proteins exhibits a wide range of polygonal geometries that relate directly to an equally diverse set of biological functions. The binding process stabilizes protein structures and typically results in local conformational change and/or global restructuring of the backbone. Previously, we established the MUG program, which utilized multiple geometries in the Ca2+-binding pockets of holoproteins to identify such pockets, ignoring possible Ca2+-induced conformational change. In this article, we first report our progress in the analysis of Ca2+-induced conformational changes followed by improved prediction of Ca2+-binding sites in the large group of Ca2+-binding proteins that exhibit only localized conformational changes. The MUGSR algorithm was devised to incorporate side chain torsional rotation as a predictor. The output from MUGSR presents groups of residues where each group, typically containing two to five residues, is a potential binding pocket. MUGSR was applied to both X-ray apo structures and NMR holo structures, which did not use calcium distance constraints in structure calculations. Predicted pockets were validated by comparison with homologous holo structures. Defining a “correct hit” as a group of residues containing at least two true ligand residues, the sensitivity was at least 90%; whereas for a “correct hit” defined as a group of residues containing at least three true ligand residues, the sensitivity was at least 78%. These data suggest that Ca2+-binding pockets are at least partially prepositioned to chelate the ion in the apo form of the protein. PMID:20512971
A Mixed QM/MM Scoring Function to Predict Protein-Ligand Binding Affinity

PubMed Central

Hayik, Seth A.; Dunbrack, Roland; Merz, Kenneth M.

2010-01-01

Computational methods for predicting protein-ligand binding free energy continue to be popular as a potential cost-cutting method in the drug discovery process. However, accurate predictions are often difficult to make as estimates must be made for certain electronic and entropic terms in conventional force field based scoring functions. Mixed quantum mechanics/molecular mechanics (QM/MM) methods allow electronic effects for a small region of the protein to be calculated, treating the remaining atoms as a fixed charge background for the active site. Such a semi-empirical QM/MM scoring function has been implemented in AMBER using DivCon and tested on a set of 23 metalloprotein-ligand complexes, where QM/MM methods provide a particular advantage in the modeling of the metal ion. The binding affinity of this set of proteins can be calculated with an R2 of 0.64 and a standard deviation of 1.88 kcal/mol without fitting and 0.71 and a standard deviation of 1.69 kcal/mol with fitted weighting of the individual scoring terms. In this study we explore using various methods to calculate terms in the binding free energy equation, including entropy estimates and minimization standards. From these studies we found that using the rotational bond estimate to ligand entropy results in a reasonable R2 of 0.63 without fitting. We also found that using the ESCF energy of the proteins without minimization resulted in an R2 of 0.57, when using the rotatable bond entropy estimate. PMID:21221417
Mapping small molecule binding data to structural domains

PubMed Central

2012-01-01

Background Large-scale bioactivity/SAR Open Data has recently become available, and this has allowed new analyses and approaches to be developed to help address the productivity and translational gaps of current drug discovery. One of the current limitations of these data is the relative sparsity of reported interactions per protein target, and complexities in establishing clear relationships between bioactivity and targets using bioinformatics tools. We detail in this paper the indexing of targets by the structural domains that bind (or are likely to bind) the ligand within a full-length protein. Specifically, we present a simple heuristic to map small molecule binding to Pfam domains. This profiling can be applied to all proteins within a genome to give some indications of the potential pharmacological modulation and regulation of all proteins. Results In this implementation of our heuristic, ligand binding to protein targets from the ChEMBL database was mapped to structural domains as defined by profiles contained within the Pfam-A database. Our mapping suggests that the majority of assay targets within the current version of the ChEMBL database bind ligands through a small number of highly prevalent domains, and conversely the majority of Pfam domains sampled by our data play no currently established role in ligand binding. Validation studies, carried out firstly against Uniprot entries with expert binding-site annotation and secondly against entries in the wwPDB repository of crystallographic protein structures, demonstrate that our simple heuristic maps ligand binding to the correct domain in about 90 percent of all assessed cases. Using the mappings obtained with our heuristic, we have assembled ligand sets associated with each Pfam domain. Conclusions Small molecule binding has been mapped to Pfam-A domains of protein targets in the ChEMBL bioactivity database. The result of this mapping is an enriched annotation of small molecule bioactivity data and a grouping of activity classes following the Pfam-A specifications of protein domains. This is valuable for data-focused approaches in drug discovery, for example when extrapolating potential targets of a small molecule with known activity against one or few targets, or in the assessment of a potential target for drug discovery or screening studies. PMID:23282026
Metal site occupancy and allosteric switching in bacterial metal sensor proteins.

PubMed

Guerra, Alfredo J; Giedroc, David P

2012-03-15

All prokaryotes encode a panel of metal sensor or metalloregulatory proteins that govern the expression of genes that allows an organism to quickly adapt to toxicity or deprivation of both biologically essential transition metal ions, e.g., Zn, Cu, Fe, and heavy metal pollutants. As such, metal sensor proteins can be considered arbiters of intracellular transition metal bioavailability and thus potentially control the metallation state of the metalloproteins in the cell. Metal sensor proteins are specialized allosteric proteins that regulate transcription as a result direct binding of one or two cognate metal ions, to the exclusion of all others. In most cases, the binding of the cognate metal ion induces a structural change in a protein oligomer that either activates or inhibits operator DNA binding. A quantitative measure of the degree to which a particular metal drives metalloregulation of operator DNA-binding is the allosteric coupling free energy, ΔGc. In this review, we summarize recent work directed toward understanding metal occupancy and metal selectivity of these allosteric switches in selected families of metal sensor proteins and examine the structural origins of ΔGc in the functional context a thermodynamic "set-point" model of intracellular metal homeostasis. Copyright Â© 2011 Elsevier Inc. All rights reserved.
ZP Domain Proteins in the Abalone Egg Coat Include a Paralog of VERL under Positive Selection That Binds Lysin and 18-kDa Sperm Proteins

PubMed Central

Aagaard, Jan E.; Vacquier, Victor D.; MacCoss, Michael J.; Swanson, Willie J.

2010-01-01

Identifying fertilization molecules is key to our understanding of reproductive biology, yet only a few examples of interacting sperm and egg proteins are known. One of the best characterized comes from the invertebrate archeogastropod abalone (Haliotis spp.), where sperm lysin mediates passage through the protective egg vitelline envelope (VE) by binding to the VE protein vitelline envelope receptor for lysin (VERL). Rapid adaptive divergence of abalone lysin and VERL are an example of positive selection on interacting fertilization proteins contributing to reproductive isolation. Previously, we characterized a subset of the abalone VE proteins that share a structural feature, the zona pellucida (ZP) domain, which is common to VERL and the egg envelopes of vertebrates. Here, we use additional expressed sequence tag sequencing and shotgun proteomics to characterize this family of proteins in the abalone egg VE. We expand 3-fold the number of known ZP domain proteins present within the VE (now 30 in total) and identify a paralog of VERL (vitelline envelope zona pellucida domain protein [VEZP] 14) that contains a putative lysin-binding motif. We find that, like VERL, the divergence of VEZP14 among abalone species is driven by positive selection on the lysin-binding motif alone and that these paralogous egg VE proteins bind a similar set of sperm proteins including a rapidly evolving 18-kDa paralog of lysin, which may mediate sperm–egg fusion. This work identifies an egg coat paralog of VERL under positive selection and the candidate sperm proteins with which it may interact during abalone fertilization. PMID:19767347
Arabidopsis SEPALLATA proteins differ in cooperative DNA-binding during the formation of floral quartet-like complexes

PubMed Central

Jetha, Khushboo; Theißen, Günter; Melzer, Rainer

2014-01-01

The SEPALLATA (SEP) genes of Arabidopsis thaliana encode MADS-domain transcription factors that specify the identity of all floral organs. The four Arabidopsis SEP genes function in a largely yet not completely redundant manner. Here, we analysed interactions of the SEP proteins with DNA. All of the proteins were capable of forming tetrameric quartet-like complexes on DNA fragments carrying two sequence elements termed CArG-boxes. Distances between the CArG-boxes for strong cooperative DNA-binding were in the range of 4–6 helical turns. However, SEP1 also bound strongly to CArG-box pairs separated by smaller or larger distances, whereas SEP2 preferred large and SEP4 preferred small inter-site distances for binding. Cooperative binding of SEP3 was comparatively weak for most of the inter-site distances tested. All SEP proteins constituted floral quartet-like complexes together with the floral homeotic proteins APETALA3 (AP3) and PISTILLATA (PI) on the target genes AP3 and SEP3. Our results suggest an important part of an explanation for why the different SEP proteins have largely, but not completely redundant functions in determining floral organ identity: they may bind to largely overlapping, but not identical sets of target genes that differ in the arrangement and spacing of the CArG-boxes in their cis-regulatory regions. PMID:25183521
Towards the elucidation of molecular determinants of cooperativity in the liver bile acid binding protein.

PubMed

Pedò, Massimo; D'Onofrio, Mariapina; Ferranti, Pasquale; Molinari, Henriette; Assfalg, Michael

2009-11-15

Bile acid binding proteins (BABPs) are cytosolic lipid chaperones contributing to the maintenance of bile acid homeostasis and functional distribution within the cell. Liver BABPs act in parallel with ileal transporters to ensure vectorial transport of bile salts in hepatocytes and enterocytes, respectively. We describe the investigation of ligand binding to liver BABP, an essential step in the understanding of intracellular bile salt transport. Binding site occupancies were monitored in NMR titration experiments using (15)N-labelled ligand, while the relative populations of differently bound BABP forms were assessed by mass spectrometry. This site-specific information allowed the determination of intrinsic thermodynamic parameters and the identification of an extremely high cooperativity between two binding sites. Protein-observed NMR experiments revealed a global structural rearrangement which suggests an allosteric mechanism at the basis of the observed cooperativity. The view of a molecular tool capable of buffering against significant concentrations of free bile salts in a large range of solution conditions emerges from the observed pH-dependence of binding. We set to determine the molecular determinants of cooperativity by analysing the binding properties of a protein containing a mutated internal histidine. Both mass spectrometry and NMR experiments are consistent with an overall decreased binding affinity of the mutant, while the measured diffusion coefficients of ligand species reveal that the affinity loss concerns essentially one of the two binding sites. We therefore identified a mutation able to disrupt energetic communication functional to efficient binding and conclude that the buried histidine establishes contacts that stabilize the ternary complex. 2009 Wiley-Liss, Inc.
The simulation approach to lipid-protein interactions.

PubMed

Paramo, Teresa; Garzón, Diana; Holdbrook, Daniel A; Khalid, Syma; Bond, Peter J

2013-01-01

The interactions between lipids and proteins are crucial for a range of biological processes, from the folding and stability of membrane proteins to signaling and metabolism facilitated by lipid-binding proteins. However, high-resolution structural details concerning functional lipid/protein interactions are scarce due to barriers in both experimental isolation of native lipid-bound complexes and subsequent biophysical characterization. The molecular dynamics (MD) simulation approach provides a means to complement available structural data, yielding dynamic, structural, and thermodynamic data for a protein embedded within a physiologically realistic, modelled lipid environment. In this chapter, we provide a guide to current methods for setting up and running simulations of membrane proteins and soluble, lipid-binding proteins, using standard atomistically detailed representations, as well as simplified, coarse-grained models. In addition, we outline recent studies that illustrate the power of the simulation approach in the context of biologically relevant lipid/protein interactions.

Prediction of small molecule binding property of protein domains with Bayesian classifiers based on Markov chains.

PubMed

Bulashevska, Alla; Stein, Martin; Jackson, David; Eils, Roland

2009-12-01

Accurate computational methods that can help to predict biological function of a protein from its sequence are of great interest to research biologists and pharmaceutical companies. One approach to assume the function of proteins is to predict the interactions between proteins and other molecules. In this work, we propose a machine learning method that uses a primary sequence of a domain to predict its propensity for interaction with small molecules. By curating the Pfam database with respect to the small molecule binding ability of its component domains, we have constructed a dataset of small molecule binding and non-binding domains. This dataset was then used as training set to learn a Bayesian classifier, which should distinguish members of each class. The domain sequences of both classes are modelled with Markov chains. In a Jack-knife test, our classification procedure achieved the predictive accuracies of 77.2% and 66.7% for binding and non-binding classes respectively. We demonstrate the applicability of our classifier by using it to identify previously unknown small molecule binding domains. Our predictions are available as supplementary material and can provide very useful information to drug discovery specialists. Given the ubiquitous and essential role small molecules play in biological processes, our method is important for identifying pharmaceutically relevant components of complete proteomes. The software is available from the author upon request.
Structure-based design, synthesis and crystallization of 2-arylquinazolines as lipid pocket ligands of p38α MAPK

PubMed Central

Bührmann, Mike; Wiedemann, Bianca M.; Müller, Matthias P.; Hardick, Julia; Ecke, Maria

2017-01-01

In protein kinase research, identifying and addressing small molecule binding sites other than the highly conserved ATP-pocket are of intense interest because this line of investigation extends our understanding of kinase function beyond the catalytic phosphotransfer. Such alternative binding sites may be involved in altering the activation state through subtle conformational changes, control cellular enzyme localization, or in mediating and disrupting protein-protein interactions. Small organic molecules that target these less conserved regions might serve as tools for chemical biology research and to probe alternative strategies in targeting protein kinases in disease settings. Here, we present the structure-based design and synthesis of a focused library of 2-arylquinazoline derivatives to target the lipophilic C-terminal binding pocket in p38α MAPK, for which a clear biological function has yet to be identified. The interactions of the ligands with p38α MAPK was analyzed by SPR measurements and validated by protein X-ray crystallography. PMID:28892510
Modulation of Enhancer Looping and Differential Gene Targeting by Epstein-Barr Virus Transcription Factors Directs Cellular Reprogramming

PubMed Central

McClellan, Michael J.; Wood, C. David; Ojeniyi, Opeoluwa; Cooper, Tim J.; Kanhere, Aditi; Arvey, Aaron; Webb, Helen M.; Palermo, Richard D.; Harth-Hertle, Marie L.; Kempkes, Bettina; Jenner, Richard G.; West, Michelle J.

2013-01-01

Epstein-Barr virus (EBV) epigenetically reprogrammes B-lymphocytes to drive immortalization and facilitate viral persistence. Host-cell transcription is perturbed principally through the actions of EBV EBNA 2, 3A, 3B and 3C, with cellular genes deregulated by specific combinations of these EBNAs through unknown mechanisms. Comparing human genome binding by these viral transcription factors, we discovered that 25% of binding sites were shared by EBNA 2 and the EBNA 3s and were located predominantly in enhancers. Moreover, 80% of potential EBNA 3A, 3B or 3C target genes were also targeted by EBNA 2, implicating extensive interplay between EBNA 2 and 3 proteins in cellular reprogramming. Investigating shared enhancer sites neighbouring two new targets (WEE1 and CTBP2) we discovered that EBNA 3 proteins repress transcription by modulating enhancer-promoter loop formation to establish repressive chromatin hubs or prevent assembly of active hubs. Re-ChIP analysis revealed that EBNA 2 and 3 proteins do not bind simultaneously at shared sites but compete for binding thereby modulating enhancer-promoter interactions. At an EBNA 3-only intergenic enhancer site between ADAM28 and ADAMDEC1 EBNA 3C was also able to independently direct epigenetic repression of both genes through enhancer-promoter looping. Significantly, studying shared or unique EBNA 3 binding sites at WEE1, CTBP2, ITGAL (LFA-1 alpha chain), BCL2L11 (Bim) and the ADAMs, we also discovered that different sets of EBNA 3 proteins bind regulatory elements in a gene and cell-type specific manner. Binding profiles correlated with the effects of individual EBNA 3 proteins on the expression of these genes, providing a molecular basis for the targeting of different sets of cellular genes by the EBNA 3s. Our results therefore highlight the influence of the genomic and cellular context in determining the specificity of gene deregulation by EBV and provide a paradigm for host-cell reprogramming through modulation of enhancer-promoter interactions by viral transcription factors. PMID:24068937
Nonlinear scoring functions for similarity-based ligand docking and binding affinity prediction.

PubMed

Brylinski, Michal

2013-11-25

A common strategy for virtual screening considers a systematic docking of a large library of organic compounds into the target sites in protein receptors with promising leads selected based on favorable intermolecular interactions. Despite a continuous progress in the modeling of protein-ligand interactions for pharmaceutical design, important challenges still remain, thus the development of novel techniques is required. In this communication, we describe eSimDock, a new approach to ligand docking and binding affinity prediction. eSimDock employs nonlinear machine learning-based scoring functions to improve the accuracy of ligand ranking and similarity-based binding pose prediction, and to increase the tolerance to structural imperfections in the target structures. In large-scale benchmarking using the Astex/CCDC data set, we show that 53.9% (67.9%) of the predicted ligand poses have RMSD of <2 Å (<3 Å). Moreover, using binding sites predicted by recently developed eFindSite, eSimDock models ligand binding poses with an RMSD of 4 Å for 50.0-39.7% of the complexes at the protein homology level limited to 80-40%. Simulations against non-native receptor structures, whose mean backbone rearrangements vary from 0.5 to 5.0 Å Cα-RMSD, show that the ratio of docking accuracy and the estimated upper bound is at a constant level of ∼0.65. Pearson correlation coefficient between experimental and predicted by eSimDock Ki values for a large data set of the crystal structures of protein-ligand complexes from BindingDB is 0.58, which decreases only to 0.46 when target structures distorted to 3.0 Å Cα-RMSD are used. Finally, two case studies demonstrate that eSimDock can be customized to specific applications as well. These encouraging results show that the performance of eSimDock is largely unaffected by the deformations of ligand binding regions, thus it represents a practical strategy for across-proteome virtual screening using protein models. eSimDock is freely available to the academic community as a Web server at http://www.brylinski.org/esimdock .
Resolving protein structure-function-binding site relationships from a binding site similarity network perspective.

PubMed

Mudgal, Richa; Srinivasan, Narayanaswamy; Chandra, Nagasuma

2017-07-01

Functional annotation is seldom straightforward with complexities arising due to functional divergence in protein families or functional convergence between non-homologous protein families, leading to mis-annotations. An enzyme may contain multiple domains and not all domains may be involved in a given function, adding to the complexity in function annotation. To address this, we use binding site information from bound cognate ligands and catalytic residues, since it can help in resolving fold-function relationships at a finer level and with higher confidence. A comprehensive database of 2,020 fold-function-binding site relationships has been systematically generated. A network-based approach is employed to capture the complexity in these relationships, from which different types of associations are deciphered, that identify versatile protein folds performing diverse functions, same function associated with multiple folds and one-to-one relationships. Binding site similarity networks integrated with fold, function, and ligand similarity information are generated to understand the depth of these relationships. Apart from the observed continuity in the functional site space, network properties of these revealed versatile families with topologically different or dissimilar binding sites and structural families that perform very similar functions. As a case study, subtle changes in the active site of a set of evolutionarily related superfamilies are studied using these networks. Tracing of such similarities in evolutionarily related proteins provide clues into the transition and evolution of protein functions. Insights from this study will be helpful in accurate and reliable functional annotations of uncharacterized proteins, poly-pharmacology, and designing enzymes with new functional capabilities. Proteins 2017; 85:1319-1335. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Characterization of the UGA-recoding and SECIS-binding activities of SECIS-binding protein 2.

PubMed

Bubenik, Jodi L; Miniard, Angela C; Driscoll, Donna M

2014-01-01

Selenium, a micronutrient, is primarily incorporated into human physiology as selenocysteine (Sec). The 25 Sec-containing proteins in humans are known as selenoproteins. Their synthesis depends on the translational recoding of the UGA stop codon to allow Sec insertion. This requires a stem-loop structure in the 3' untranslated region of eukaryotic mRNAs known as the Selenocysteine Insertion Sequence (SECIS). The SECIS is recognized by SECIS-binding protein 2 (SBP2) and this RNA:protein interaction is essential for UGA recoding to occur. Genetic mutations cause SBP2 deficiency in humans, resulting in a broad set of symptoms due to differential effects on individual selenoproteins. Progress on understanding the different phenotypes requires developing robust tools to investigate SBP2 structure and function. In this study we demonstrate that SBP2 protein produced by in vitro translation discriminates among SECIS elements in a competitive UGA recoding assay and has a much higher specific activity than bacterially expressed protein. We also show that a purified recombinant protein encompassing amino acids 517-777 of SBP2 binds to SECIS elements with high affinity and selectivity. The affinity of the SBP2:SECIS interaction correlated with the ability of a SECIS to compete for UGA recoding activity in vitro. The identification of a 250 amino acid sequence that mediates specific, selective SECIS-binding will facilitate future structural studies of the SBP2:SECIS complex. Finally, we identify an evolutionarily conserved core cysteine signature in SBP2 sequences from the vertebrate lineage. Mutation of multiple, but not single, cysteines impaired SECIS-binding but did not affect protein localization in cells.
Preferential binding effects on protein structure and dynamics revealed by coarse-grained Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Pandey, R. B.; Jacobs, D. J.; Farmer, B. L.

2017-05-01

The effect of preferential binding of solute molecules within an aqueous solution on the structure and dynamics of the histone H3.1 protein is examined by a coarse-grained Monte Carlo simulation. The knowledge-based residue-residue and hydropathy-index-based residue-solvent interactions are used as input to analyze a number of local and global physical quantities as a function of the residue-solvent interaction strength (f). Results from simulations that treat the aqueous solution as a homogeneous effective solvent medium are compared to when positional fluctuations of the solute molecules are explicitly considered. While the radius of gyration (Rg) of the protein exhibits a non-monotonic dependence on solvent interaction over a wide range of f within an effective medium, an abrupt collapse in Rg occurs in a narrow range of f when solute molecules rapidly bind to a preferential set of sites on the protein. The structure factor S(q) of the protein with wave vector (q) becomes oscillatory in the collapsed state, which reflects segmental correlations caused by spatial fluctuations in solute-protein binding. Spatial fluctuations in solute binding also modify the effective dimension (D) of the protein in fibrous (D ˜ 1.3), random-coil (D ˜ 1.75), and globular (D ˜ 3) conformational ensembles as the interaction strength increases, which differ from an effective medium with respect to the magnitude of D and the length scale.
TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions

PubMed Central

2017-01-01

Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/ PMID:28749969
Crystal structure of secretory abundant heat soluble protein 4 from one of the toughest “water bears” micro‐animals Ramazzottius Varieornatus

PubMed Central

Fukuda, Yohta

2018-01-01

Abstract Though anhydrobiotic tardigrades (micro‐animals also known as water bears) possess many genes of secretory abundant heat soluble (SAHS) proteins unique to Tardigrada, their functions are unknown. A previous crystallographic study revealed that a SAHS protein (RvSAHS1) from one of the toughest tardigrades, Ramazzottius varieornatus, has a β‐barrel architecture similar to fatty acid binding proteins (FABPs) and two putative ligand binding sites (LBS1 and LBS2) where fatty acids can bind. However, some SAHS proteins such as RvSAHS4 have different sets of amino acid residues at LBS1 and LBS2, implying that they prefer other ligands and have different functions. Here RvSAHS4 was crystallized and analyzed under a condition similar to that for RvSAHS1. There was no electron density corresponding to a fatty acid at LBS1 of RvSAHS4, where a putative fatty acid was observed in RvSAHS1. Instead, LBS2 of RvSAHS4, which was composed of uncharged residues, captured a putative polyethylene glycol molecule. These results suggest that RvSAHS4 mainly uses LBS2 for the binding of uncharged molecules. PMID:29493034
Crystal structures of the Erp protein family members ErpP and ErpC from Borrelia burgdorferi reveal the reason for different affinities for complement regulator factor H.

PubMed

Brangulis, Kalvis; Petrovskis, Ivars; Kazaks, Andris; Akopjana, Inara; Tars, Kaspars

2015-05-01

Borrelia burgdorferi is the causative agent of Lyme disease, which can be acquired after the bite of an infected Ixodes tick. As a strategy to resist the innate immunity and to successfully spread and proliferate, B. burgdorferi expresses a set of outer membrane proteins that are capable of binding complement regulator factor H (CFH), factor H-like protein 1 (CFHL-1) and factor H-related proteins (CFHR) to avoid complement-mediated killing. B. burgdorferi B31 contains three proteins that belong to the Erp (OspE/F-related) protein family and are capable of binding CFH and some CFHRs, namely ErpA, ErpC and ErpP. We have determined the crystal structure of ErpP at 2.53Å resolution and the crystal structure of ErpC at 2.15Å resolution. Recently, the crystal structure of the Erp family member OspE from B. burgdorferi N40 was determined in complex with CFH domains 19-20, revealing the residues involved in the complex formation. Despite the high sequence conservation between ErpA, ErpC, ErpP and the homologous protein OspE (78-80%), the affinity for CFH and CFHRs differs markedly among the Erp family members, suggesting that ErpC may bind only CFHRs but not CFH. A comparison of the binding site in OspE with those of ErpC and ErpP revealed that the extended loop region, which is only observed in the potential binding site of ErpC, plays an important role by preventing the binding of CFH. These results can explain the inability of ErpC to bind CFH, whereas ErpP and ErpA still possess the ability to bind CFH. Copyright © 2015 Elsevier B.V. All rights reserved.
Studying the Salt Dependence of the Binding of σ70 and σ32 to Core RNA Polymerase Using Luminescence Resonance Energy Transfer

PubMed Central

Glaser, Bryan T.; Bergendahl, Veit; Anthony, Larry C.; Olson, Brian; Burgess, Richard R.

2009-01-01

The study of protein-protein interactions is becoming increasingly important for understanding the regulation of many cellular processes. The ability to quantify the strength with which two binding partners interact is desirable but the accurate determination of equilibrium binding constants is a difficult process. The use of Luminescence Resonance Energy Transfer (LRET) provides a homogeneous binding assay that can be used for the detection of protein-protein interactions. Previously, we developed an LRET assay to screen for small molecule inhibitors of the interaction of σ70 with theβ' coiled-coil fragment (amino acids 100–309). Here we describe an LRET binding assay used to monitor the interaction of E. coli σ70 and σ32 with core RNA polymerase along with the controls to verify the system. This approach generates fluorescently labeled proteins through the random labeling of lysine residues which enables the use of the LRET assay for proteins for which the creation of single cysteine mutants is not feasible. With the LRET binding assay, we are able to show that the interaction of σ70 with core RNAP is much more sensitive to NaCl than to potassium glutamate (KGlu), whereas the σ32 interaction with core RNAP is insensitive to both salts even at concentrations >500 mM. We also find that the interaction of σ32 with core RNAP is stronger than σ70 with core RNAP, under all conditions tested. This work establishes a consistent set of conditions for the comparison of the binding affinities of the E.coli sigma factors with core RNA polymerase. The examination of the importance of salt conditions in the binding of these proteins could have implications in both in vitro assay conditions and in vivo function. PMID:19649256
SARNAclust: Semi-automatic detection of RNA protein binding motifs from immunoprecipitation data

PubMed Central

Dotu, Ivan; Adamson, Scott I.; Coleman, Benjamin; Fournier, Cyril; Ricart-Altimiras, Emma; Eyras, Eduardo

2018-01-01

RNA-protein binding is critical to gene regulation, controlling fundamental processes including splicing, translation, localization and stability, and aberrant RNA-protein interactions are known to play a role in a wide variety of diseases. However, molecular understanding of RNA-protein interactions remains limited; in particular, identification of RNA motifs that bind proteins has long been challenging, especially when such motifs depend on both sequence and structure. Moreover, although RNA binding proteins (RBPs) often contain more than one binding domain, algorithms capable of identifying more than one binding motif simultaneously have not been developed. In this paper we present a novel pipeline to determine binding peaks in crosslinking immunoprecipitation (CLIP) data, to discover multiple possible RNA sequence/structure motifs among them, and to experimentally validate such motifs. At the core is a new semi-automatic algorithm SARNAclust, the first unsupervised method to identify and deconvolve multiple sequence/structure motifs simultaneously. SARNAclust computes similarity between sequence/structure objects using a graph kernel, providing the ability to isolate the impact of specific features through the bulge graph formalism. Application of SARNAclust to synthetic data shows its capability of clustering 5 motifs at once with a V-measure value of over 0.95, while GraphClust achieves only a V-measure of 0.083 and RNAcontext cannot detect any of the motifs. When applied to existing eCLIP sets, SARNAclust finds known motifs for SLBP and HNRNPC and novel motifs for several other RBPs such as AGGF1, AKAP8L and ILF3. We demonstrate an experimental validation protocol, a targeted Bind-n-Seq-like high-throughput sequencing approach that relies on RNA inverse folding for oligo pool design, that can validate the components within the SLBP motif. Finally, we use this protocol to experimentally interrogate the SARNAclust motif predictions for protein ILF3. Our results support a newly identified partially double-stranded UUUUUGAGA motif similar to that known for the splicing factor HNRNPC. PMID:29596423
Superposition-free comparison and clustering of antibody binding sites: implications for the prediction of the nature of their antigen

PubMed Central

Di Rienzo, Lorenzo; Milanetti, Edoardo; Lepore, Rosalba; Olimpieri, Pier Paolo; Tramontano, Anna

2017-01-01

We describe here a superposition free method for comparing the surfaces of antibody binding sites based on the Zernike moments and show that they can be used to quickly compare and cluster sets of antibodies. The clusters provide information about the nature of the bound antigen that, when combined with a method for predicting the number of direct antibody antigen contacts, allows the discrimination between protein and non-protein binding antibodies with an accuracy of 76%. This is of relevance in several aspects of antibody science, for example to select the framework to be used for a combinatorial antibody library. PMID:28338016
Purification, crystallization and preliminary X-ray diffraction analysis of water-soluble chlorophyll-binding protein from Chenopodium album

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ohtsuki, Takayuki; Ohshima, Shigeru; Uchida, Akira, E-mail: auchida@biomol.sci.toho-u.ac.jp

2007-09-01

A water-soluble chlorophyll-binding protein with photoconvertibility from C. album was extracted, purified and crystallized in a darkroom. The crystal diffracted to around 2.0 Å resolution. A water-soluble chlorophyll-binding protein (WSCP) with photoconvertibility from Chenopodium album was extracted, purified and crystallized in a darkroom. Green crystals suitable for data collection appeared in about 10 d. A native data set was collected to 2.0 Å resolution at 100 K. The space group of the crystal was determined to be orthorhombic I222 or I2{sub 1}2{sub 1}2{sub 1}, with unit-cell parameters a = 48.13, b = 60.59, c = 107.21 Å. Preliminary analysis ofmore » the X-ray data indicated that there is one molecule per asymmetric unit.« less
Rapid comparison of protein binding site surfaces with Property Encoded Shape Distributions (PESD)

PubMed Central

Das, Sourav; Kokardekar, Arshad

2009-01-01

Patterns in shape and property distributions on the surface of binding sites are often conserved across functional proteins without significant conservation of the underlying amino-acid residues. To explore similarities of these sites from the viewpoint of a ligand, a sequence and fold-independent method was created to rapidly and accurately compare binding sites of proteins represented by property-mapped triangulated Gauss-Connolly surfaces. Within this paradigm, signatures for each binding site surface are produced by calculating their property-encoded shape distributions (PESD), a measure of the probability that a particular property will be at a specific distance to another on the molecular surface. Similarity between the signatures can then be treated as a measure of similarity between binding sites. As postulated, the PESD method rapidly detected high levels of similarity in binding site surface characteristics even in cases where there was very low similarity at the sequence level. In a screening experiment involving each member of the PDBBind 2005 dataset as a query against the rest of the set, PESD was able to retrieve a binding site with identical E.C. (Enzyme Commission) numbers as the top match in 79.5% of cases. The ability of the method in detecting similarity in binding sites with low sequence conservations were compared with state-of-the-art binding site comparison methods. PMID:19919089
A general approach for developing system-specific functions to score protein-ligand docked complexes using support vector inductive logic programming.

PubMed

Amini, Ata; Shrimpton, Paul J; Muggleton, Stephen H; Sternberg, Michael J E

2007-12-01

Despite the increased recent use of protein-ligand and protein-protein docking in the drug discovery process due to the increases in computational power, the difficulty of accurately ranking the binding affinities of a series of ligands or a series of proteins docked to a protein receptor remains largely unsolved. This problem is of major concern in lead optimization procedures and has lead to the development of scoring functions tailored to rank the binding affinities of a series of ligands to a specific system. However, such methods can take a long time to develop and their transferability to other systems remains open to question. Here we demonstrate that given a suitable amount of background information a new approach using support vector inductive logic programming (SVILP) can be used to produce system-specific scoring functions. Inductive logic programming (ILP) learns logic-based rules for a given dataset that can be used to describe properties of each member of the set in a qualitative manner. By combining ILP with support vector machine regression, a quantitative set of rules can be obtained. SVILP has previously been used in a biological context to examine datasets containing a series of singular molecular structures and properties. Here we describe the use of SVILP to produce binding affinity predictions of a series of ligands to a particular protein. We also for the first time examine the applicability of SVILP techniques to datasets consisting of protein-ligand complexes. Our results show that SVILP performs comparably with other state-of-the-art methods on five protein-ligand systems as judged by similar cross-validated squares of their correlation coefficients. A McNemar test comparing SVILP to CoMFA and CoMSIA across the five systems indicates our method to be significantly better on one occasion. The ability to graphically display and understand the SVILP-produced rules is demonstrated and this feature of ILP can be used to derive hypothesis for future ligand design in lead optimization procedures. The approach can readily be extended to evaluate the binding affinities of a series of protein-protein complexes. (c) 2007 Wiley-Liss, Inc.
Prediction of protein-protein interaction sites using electrostatic desolvation profiles.

PubMed

Fiorucci, Sébastien; Zacharias, Martin

2010-05-19

Protein-protein complex formation involves removal of water from the interface region. Surface regions with a small free energy penalty for water removal or desolvation may correspond to preferred interaction sites. A method to calculate the electrostatic free energy of placing a neutral low-dielectric probe at various protein surface positions has been designed and applied to characterize putative interaction sites. Based on solutions of the finite-difference Poisson equation, this method also includes long-range electrostatic contributions and the protein solvent boundary shape in contrast to accessible-surface-area-based solvation energies. Calculations on a large set of proteins indicate that in many cases (>90%), the known binding site overlaps with one of the six regions of lowest electrostatic desolvation penalty (overlap with the lowest desolvation region for 48% of proteins). Since the onset of electrostatic desolvation occurs even before direct protein-protein contact formation, it may help guide proteins toward the binding region in the final stage of complex formation. It is interesting that the probe desolvation properties associated with residue types were found to depend to some degree on whether the residue was outside of or part of a binding site. The probe desolvation penalty was on average smaller if the residue was part of a binding site compared to other surface locations. Applications to several antigen-antibody complexes demonstrated that the approach might be useful not only to predict protein interaction sites in general but to map potential antigenic epitopes on protein surfaces. Copyright (c) 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Calcyclin Binding Protein/Siah-1 Interacting Protein Is a Hsp90 Binding Chaperone

PubMed Central

Góral, Agnieszka; Bieganowski, Paweł; Prus, Wiktor; Krzemień-Ojak, Łucja; Kądziołka, Beata; Fabczak, Hanna; Filipek, Anna

2016-01-01

The Hsp90 chaperone activity is tightly regulated by interaction with many co-chaperones. Since CacyBP/SIP shares some sequence homology with a known Hsp90 co-chaperone, Sgt1, in this work we performed a set of experiments in order to verify whether CacyBP/SIP can interact with Hsp90. By applying the immunoprecipitation assay we have found that CacyBP/SIP binds to Hsp90 and that the middle (M) domain of Hsp90 is responsible for this binding. Furthermore, the proximity ligation assay (PLA) performed on HEp-2 cells has shown that the CacyBP/SIP-Hsp90 complexes are mainly localized in the cytoplasm of these cells. Using purified proteins and applying an ELISA we have shown that Hsp90 interacts directly with CacyBP/SIP and that the latter protein does not compete with Sgt1 for the binding to Hsp90. Moreover, inhibitors of Hsp90 do not perturb CacyBP/SIP-Hsp90 binding. Luciferase renaturation assay and citrate synthase aggregation assay with the use of recombinant proteins have revealed that CacyBP/SIP exhibits chaperone properties. Also, CacyBP/SIP-3xFLAG expression in HEp-2 cells results in the appearance of more basic Hsp90 forms in 2D electrophoresis, which may indicate that CacyBP/SIP dephosphorylates Hsp90. Altogether, the obtained results suggest that CacyBP/SIP is involved in regulation of the Hsp90 chaperone machinery. PMID:27249023
MNDA binds NPM/B23 and the NPM-MLF1 chimera generated by the t(3;5) associated with myelodysplastic syndrome and acute myeloid leukemia.

PubMed

Xie, J; Briggs, J A; Morris, S W; Olson, M O; Kinney, M C; Briggs, R C

1997-10-01

The myeloid cell nuclear differentiation antigen (MNDA) is a nuclear protein expressed specifically in developing cells of the human myelomonocytic lineage, including the end-stage monocytes/macrophages and granulocytes. Nuclear localization, lineage- and stage-specific expression, association with chromatin, and regulation by interferon alpha indicate that this protein is involved in regulating gene expression uniquely associated with the differentiation process and/or function of the monocyte/macrophage. MNDA does not bind specific DNA sequences, but rather a set of nuclear proteins that includes nucleolin (C23). Both in vitro binding assays and co-immunoprecipitation were used to demonstrate that MNDA also binds protein B23 (nucleophosmin/NPM). Three reciprocal chromosome translocations found in certain cases of leukemia/lymphoma involve fusions with the NPM/B23 gene, t(5;17) NPM-RARalpha, t(2;5) NPM-ALK, and the t(3;5) NPM-MLF1. In the current study, MNDA was not able to bind the NPM-ALK chimera originating from the t(2;5) and containing residues 1-117 of NPM. However, MNDA did bind the NPM-MLF1 product of the t(3;5) that contains the N-terminal 175 residues of NPM. The additional 58 amino acids (amino acids 117-175) of the NPM sequence that are contained in the product of the NPM-MLF1 fusion gene relative to the product of the NPM-ALK fusion appear responsible for MNDA binding. This additional NPM sequence contains a nuclear localization signal and clusters of acidic residues believed to bind nuclear localization signals of other proteins. Whereas NPM and nucleolin are primarily localized within the nucleolus, MNDA is distributed throughout the nucleus including the nucleolus, suggesting that additional interactions define overall MNDA localization.
Diverse RNA-binding proteins interact with functionally related sets of RNAs, suggesting an extensive regulatory system.

PubMed

Hogan, Daniel J; Riordan, Daniel P; Gerber, André P; Herschlag, Daniel; Brown, Patrick O

2008-10-28

RNA-binding proteins (RBPs) have roles in the regulation of many post-transcriptional steps in gene expression, but relatively few RBPs have been systematically studied. We searched for the RNA targets of 40 proteins in the yeast Saccharomyces cerevisiae: a selective sample of the approximately 600 annotated and predicted RBPs, as well as several proteins not annotated as RBPs. At least 33 of these 40 proteins, including three of the four proteins that were not previously known or predicted to be RBPs, were reproducibly associated with specific sets of a few to several hundred RNAs. Remarkably, many of the RBPs we studied bound mRNAs whose protein products share identifiable functional or cytotopic features. We identified specific sequences or predicted structures significantly enriched in target mRNAs of 16 RBPs. These potential RNA-recognition elements were diverse in sequence, structure, and location: some were found predominantly in 3'-untranslated regions, others in 5'-untranslated regions, some in coding sequences, and many in two or more of these features. Although this study only examined a small fraction of the universe of yeast RBPs, 70% of the mRNA transcriptome had significant associations with at least one of these RBPs, and on average, each distinct yeast mRNA interacted with three of the RBPs, suggesting the potential for a rich, multidimensional network of regulation. These results strongly suggest that combinatorial binding of RBPs to specific recognition elements in mRNAs is a pervasive mechanism for multi-dimensional regulation of their post-transcriptional fate.

Evaluation of several two-step scoring functions based on linear interaction energy, effective ligand size, and empirical pair potentials for prediction of protein-ligand binding geometry and free energy.

PubMed

Rahaman, Obaidur; Estrada, Trilce P; Doren, Douglas J; Taufer, Michela; Brooks, Charles L; Armen, Roger S

2011-09-26

The performances of several two-step scoring approaches for molecular docking were assessed for their ability to predict binding geometries and free energies. Two new scoring functions designed for "step 2 discrimination" were proposed and compared to our CHARMM implementation of the linear interaction energy (LIE) approach using the Generalized-Born with Molecular Volume (GBMV) implicit solvation model. A scoring function S1 was proposed by considering only "interacting" ligand atoms as the "effective size" of the ligand and extended to an empirical regression-based pair potential S2. The S1 and S2 scoring schemes were trained and 5-fold cross-validated on a diverse set of 259 protein-ligand complexes from the Ligand Protein Database (LPDB). The regression-based parameters for S1 and S2 also demonstrated reasonable transferability in the CSARdock 2010 benchmark using a new data set (NRC HiQ) of diverse protein-ligand complexes. The ability of the scoring functions to accurately predict ligand geometry was evaluated by calculating the discriminative power (DP) of the scoring functions to identify native poses. The parameters for the LIE scoring function with the optimal discriminative power (DP) for geometry (step 1 discrimination) were found to be very similar to the best-fit parameters for binding free energy over a large number of protein-ligand complexes (step 2 discrimination). Reasonable performance of the scoring functions in enrichment of active compounds in four different protein target classes established that the parameters for S1 and S2 provided reasonable accuracy and transferability. Additional analysis was performed to definitively separate scoring function performance from molecular weight effects. This analysis included the prediction of ligand binding efficiencies for a subset of the CSARdock NRC HiQ data set where the number of ligand heavy atoms ranged from 17 to 35. This range of ligand heavy atoms is where improved accuracy of predicted ligand efficiencies is most relevant to real-world drug design efforts.
Predicting Displaceable Water Sites Using Mixed-Solvent Molecular Dynamics.

PubMed

Graham, Sarah E; Smith, Richard D; Carlson, Heather A

2018-02-26

Water molecules are an important factor in protein-ligand binding. Upon binding of a ligand with a protein's surface, waters can either be displaced by the ligand or may be conserved and possibly bridge interactions between the protein and ligand. Depending on the specific interactions made by the ligand, displacing waters can yield a gain in binding affinity. The extent to which binding affinity may increase is difficult to predict, as the favorable displacement of a water molecule is dependent on the site-specific interactions made by the water and the potential ligand. Several methods have been developed to predict the location of water sites on a protein's surface, but the majority of methods are not able to take into account both protein dynamics and the interactions made by specific functional groups. Mixed-solvent molecular dynamics (MixMD) is a cosolvent simulation technique that explicitly accounts for the interaction of both water and small molecule probes with a protein's surface, allowing for their direct competition. This method has previously been shown to identify both active and allosteric sites on a protein's surface. Using a test set of eight systems, we have developed a method using MixMD to identify conserved and displaceable water sites. Conserved sites can be determined by an occupancy-based metric to identify sites which are consistently occupied by water even in the presence of probe molecules. Conversely, displaceable water sites can be found by considering the sites which preferentially bind probe molecules. Furthermore, the inclusion of six probe types allows the MixMD method to predict which functional groups are capable of displacing which water sites. The MixMD method consistently identifies sites which are likely to be nondisplaceable and predicts the favorable displacement of water sites that are known to be displaced upon ligand binding.
Multivariate Analysis of Conformational Changes Induced by Macromolecular Interactions

NASA Astrophysics Data System (ADS)

Mitra, Indranil; Alexov, Emil

2009-11-01

Understanding protein-protein binding and associated conformational changes is critical for both understanding thermodynamics of protein interactions and successful drug discovery. Our study focuses on computational analysis of plausible correlations between induced conformational changes and set of biophysical characteristics of interacting monomers. It was done by comparing 3D structures of unbound and bound monomers to calculate the RMSD which is used as measure of the structural changed induced by the binding. We correlate RMSD with volumetric and interfacial charge of the monomers, the amino acid composition, the energy of binding, and type of amino acids at the interface. as predictors. The data set was analyzed with SVM in R & SPSS which is trained on a combination of a new robust evolutionary conservation signal with the monomeric properties to predict the induced RMSD. The goal of this study is to undergo parametric tests and heirchiacal cluster and discriminant multivariate analysis to find key predictors which will be used to develop algorithm to predict the magnitude of conformational changes provided by the structure of interacting monomers. Results indicate that the most promising predictor is the net charge of the monomers, however, other parameters as the type of amino acids at the interface have significant contribution as well.
Optimization of binding electrostatics: Charge complementarity in the barnase-barstar protein complex

PubMed Central

lee, Lee-Peng; Tidor, Bruce

2001-01-01

Theoretical and experimental studies have shown that the large desolvation penalty required for polar and charged groups frequently precludes their involvement in electrostatic interactions that contribute strongly to net stability in the folding or binding of proteins in aqueous solution near room temperature. We have previously developed a theoretical framework for computing optimized electrostatic interactions and illustrated use of the algorithm with simplified geometries. Given a receptor and model assumptions, the method computes the ligand-charge distribution that provides the most favorable balance of desolvation and interaction effects on binding. In this paper the method has been extended to treat complexes using actual molecular shapes. The barnase-barstar protein complex was investigated with barnase treated as a target receptor. The atomic point charges of barstar were varied to optimize the electrostatic binding free energy. Barnase and natural barstar form a tight complex (Kd ∼ 10−14 M) with many charged and polar groups near the interface that make this a particularly relevant system for investigating the role of electrostatic effects on binding. The results show that sets of barstar charges (resulting from optimization with different constraints) can be found that give rise to relatively large predicted improvements in electrostatic binding free energy. Principles for enhancing the effect of electrostatic interactions in molecular binding in aqueous environments are discussed in light of the optima. Our findings suggest that, in general, the enhancements in electrostatic binding free energy resulting from modification of polar and charged groups can be substantial. Moreover, a recently proposed definition of electrostatic complementarity is shown to be a useful tool for examining binding interfaces. Finally, calculational results suggest that wild-type barstar is closer to being affinity optimized than is barnase for their mutual binding, consistent with the known roles of these proteins. PMID:11266622
Analysis of a two-domain binding site for the urokinase-type plasminogen activator-plasminogen activator inhibitor-1 complex in low-density-lipoprotein-receptor-related protein.

PubMed

Andersen, O M; Petersen, H H; Jacobsen, C; Moestrup, S K; Etzerodt, M; Andreasen, P A; Thøgersen, H C

2001-07-01

The low-density-lipoprotein-receptor (LDLR)-related protein (LRP) is composed of several classes of domains, including complement-type repeats (CR), which occur in clusters that contain binding sites for a multitude of different ligands. Each approximately 40-residue CR domain contains three conserved disulphide linkages and an octahedral Ca(2+) cage. LRP is a scavenging receptor for ligands from extracellular fluids, e.g. alpha(2)-macroglobulin (alpha(2)M)-proteinase complexes, lipoprotein-containing particles and serine proteinase-inhibitor complexes, like the complex between urokinase-type plasminogen activator (uPA) and the plasminogen activator inhibitor-1 (PAI-1). In the present study we analysed the interaction of the uPA-PAI-1 complex with an ensemble of fragments representing a complete overlapping set of two-domain fragments accounting for the ligand-binding cluster II (CR3-CR10) of LRP. By ligand blotting, solid-state competition analysis and surface-plasmon-resonance analysis, we demonstrate binding to multiple CR domains, but show a preferential interaction between the uPA-PAI-1 complex and a two-domain fragment comprising CR domains 5 and 6 of LRP. We demonstrate that surface-exposed aspartic acid and tryptophan residues at identical positions in the two homologous domains, CR5 and CR6 (Asp(958,CR5), Asp(999,CR6), Trp(953,CR5) and Trp(994,CR6)), are critical for the binding of the complex as well as for the binding of the receptor-associated protein (RAP) - the folding chaperone/escort protein required for transport of LRP to the cell surface. Accordingly, the present work provides (1) an identification of a preferred binding site within LRP CR cluster II; (2) evidence that the uPA-PAI-1 binding site involves residues from two adjacent protein domains; and (3) direct evidence identifying specific residues as important for the binding of uPA-PAI-1 as well as for the binding of RAP.
E-novo: an automated workflow for efficient structure-based lead optimization.

PubMed

Pearce, Bradley C; Langley, David R; Kang, Jia; Huang, Hongwei; Kulkarni, Amit

2009-07-01

An automated E-Novo protocol designed as a structure-based lead optimization tool was prepared through Pipeline Pilot with existing CHARMm components in Discovery Studio. A scaffold core having 3D binding coordinates of interest is generated from a ligand-bound protein structural model. Ligands of interest are generated from the scaffold using an R-group fragmentation/enumeration tool within E-Novo, with their cores aligned. The ligand side chains are conformationally sampled and are subjected to core-constrained protein docking, using a modified CHARMm-based CDOCKER method to generate top poses along with CDOCKER energies. In the final stage of E-Novo, a physics-based binding energy scoring function ranks the top ligand CDOCKER poses using a more accurate Molecular Mechanics-Generalized Born with Surface Area method. Correlation of the calculated ligand binding energies with experimental binding affinities were used to validate protocol performance. Inhibitors of Src tyrosine kinase, CDK2 kinase, beta-secretase, factor Xa, HIV protease, and thrombin were used to test the protocol using published ligand crystal structure data within reasonably defined binding sites. In-house Respiratory Syncytial Virus inhibitor data were used as a more challenging test set using a hand-built binding model. Least squares fits for all data sets suggested reasonable validation of the protocol within the context of observed ligand binding poses. The E-Novo protocol provides a convenient all-in-one structure-based design process for rapid assessment and scoring of lead optimization libraries.
A Point Mutation in the Exon Junction Complex Factor Y14 Disrupts Its Function in mRNA Cap Binding and Translation Enhancement*

PubMed Central

Chuang, Tzu-Wei; Lee, Kuo-Ming; Lou, Yuan-Chao; Lu, Chia-Chen; Tarn, Woan-Yuh

2016-01-01

Eukaryotic mRNA biogenesis involves a series of interconnected steps mediated by RNA-binding proteins. The exon junction complex core protein Y14 is required for nonsense-mediated mRNA decay (NMD) and promotes translation. Moreover, Y14 binds the cap structure of mRNAs and inhibits the activity of the decapping enzyme Dcp2. In this report, we show that an evolutionarily conserved tryptophan residue (Trp-73) of Y14 is critical for its binding to the mRNA cap structure. A Trp-73 mutant (W73V) bound weakly to mRNAs and failed to protect them from degradation. However, this mutant could still interact with the NMD and mRNA degradation factors and retained partial NMD activity. In addition, we found that the W73V mutant could not interact with translation initiation factors. Overexpression of W73V suppressed reporter mRNA translation in vitro and in vivo and reduced the level of a set of nascent proteins. These results reveal a residue of Y14 that confers cap-binding activity and is essential for Y14-mediated enhancement of translation. Finally, we demonstrated that Y14 may selectively and differentially modulate protein biosynthesis. PMID:26887951
Biochemistry of the tale transcription factors PREP, MEIS, and PBX in vertebrates.

PubMed

Longobardi, E; Penkov, D; Mateos, D; De Florian, G; Torres, M; Blasi, Francesco

2014-01-01

TALE (three amino acids loop extension) homeodomain transcription factors are required in various steps of embryo development, in many adult physiological functions, and are involved in important pathologies. This review focuses on the PREP, MEIS, and PBX sub-families of TALE factors and aims at giving information on their biochemical properties, i.e., structure, interactors, and interaction surfaces. Members of the three sets of protein form dimers in which the common partner is PBX but they can also directly interact with other proteins forming higher-order complexes, in particular HOX. Finally, recent advances in determining the genome-wide DNA-binding sites of PREP1, MEIS1, and PBX1, and their partial correspondence with the binding sites of some HOX proteins, are reviewed. These studies have generated a few general rules that can be applied to all members of the three gene families. PREP and MEIS recognize slightly different consensus sequences: PREP prefers to bind to promoters and to have PBX as a DNA-binding partner; MEIS prefers HOX as partner, and both PREP and MEIS drive PBX to their own binding sites. This outlines the clear individuality of the PREP and MEIS proteins, the former mostly devoted to basic cellular functions, the latter more to developmental functions. Copyright © 2013 Wiley Periodicals, Inc.
Energy design for protein-protein interactions

PubMed Central

Ravikant, D. V. S.; Elber, Ron

2011-01-01

Proteins bind to other proteins efficiently and specifically to carry on many cell functions such as signaling, activation, transport, enzymatic reactions, and more. To determine the geometry and strength of binding of a protein pair, an energy function is required. An algorithm to design an optimal energy function, based on empirical data of protein complexes, is proposed and applied. Emphasis is made on negative design in which incorrect geometries are presented to the algorithm that learns to avoid them. For the docking problem the search for plausible geometries can be performed exhaustively. The possible geometries of the complex are generated on a grid with the help of a fast Fourier transform algorithm. A novel formulation of negative design makes it possible to investigate iteratively hundreds of millions of negative examples while monotonically improving the quality of the potential. Experimental structures for 640 protein complexes are used to generate positive and negative examples for learning parameters. The algorithm designed in this work finds the correct binding structure as the lowest energy minimum in 318 cases of the 640 examples. Further benchmarks on independent sets confirm the significant capacity of the scoring function to recognize correct modes of interactions. PMID:21842951
When galectins recognize glycans: from biochemistry to physiology and back again.

PubMed

Di Lella, Santiago; Sundblad, Victoria; Cerliani, Juan P; Guardia, Carlos M; Estrin, Dario A; Vasta, Gerardo R; Rabinovich, Gabriel A

2011-09-20

In the past decade, increasing efforts have been devoted to the study of galectins, a family of evolutionarily conserved glycan-binding proteins with multifunctional properties. Galectins function, either intracellularly or extracellularly, as key biological mediators capable of monitoring changes occurring on the cell surface during fundamental biological processes such as cellular communication, inflammation, development, and differentiation. Their highly conserved structures, exquisite carbohydrate specificity, and ability to modulate a broad spectrum of biological processes have captivated a wide range of scientists from a wide spectrum of disciplines, including biochemistry, biophysics, cell biology, and physiology. However, in spite of enormous efforts to dissect the functions and properties of these glycan-binding proteins, limited information about how structural and biochemical aspects of these proteins can influence biological functions is available. In this review, we aim to integrate structural, biochemical, and functional aspects of this bewildering and ancient family of glycan-binding proteins and discuss their implications in physiologic and pathologic settings. © 2011 American Chemical Society
CLIP-related methodologies and their application to retrovirology.

PubMed

Bieniasz, Paul D; Kutluay, Sebla B

2018-05-02

Virtually every step of HIV-1 replication and numerous cellular antiviral defense mechanisms are regulated by the binding of a viral or cellular RNA-binding protein (RBP) to distinct sequence or structural elements on HIV-1 RNAs. Until recently, these protein-RNA interactions were studied largely by in vitro binding assays complemented with genetics approaches. However, these methods are highly limited in the identification of the relevant targets of RBPs in physiologically relevant settings. Development of crosslinking-immunoprecipitation sequencing (CLIP) methodology has revolutionized the analysis of protein-nucleic acid complexes. CLIP combines immunoprecipitation of covalently crosslinked protein-RNA complexes with high-throughput sequencing, providing a global account of RNA sequences bound by a RBP of interest in cells (or virions) at near-nucleotide resolution. Numerous variants of the CLIP protocol have recently been developed, some with major improvements over the original. Herein, we briefly review these methodologies and give examples of how CLIP has been successfully applied to retrovirology research.
bfr1+, a novel gene of Schizosaccharomyces pombe which confers brefeldin A resistance, is structurally related to the ATP-binding cassette superfamily.

PubMed Central

Nagao, K; Taguchi, Y; Arioka, M; Kadokura, H; Takatsuki, A; Yoda, K; Yamasaki, M

1995-01-01

We have isolated a Schizosaccharomyces pombe gene, bfr1+, which on a multicopy plasmid vector, pDB248', confers resistance to brefeldin A (BFA), an inhibitor of intracellular protein transport. This gene encodes a novel protein of 1,531 amino acids with an intramolecular duplicated structure, each half containing a single ATP-binding consensus sequence and a set of six transmembrane sequences. This structural characteristic of bfr1+ protein resembles that of mammalian P-glycoprotein, which, by exporting a variety of anticancer drugs, has been shown to be responsible for multidrug resistance in tumor cells. Consistent with this is that S. pombe cells harboring bfr1+ on pDB248' are resistant to actinomycin D, cerulenin, and cytochalasin B, as well as to BFA. The relative positions of the ATP-binding sequences and the clusters of transmembrane sequences within the bfr1+ protein are, however, transposed in comparison with those in P-glycoprotein; the bfr1+ protein has N-terminal ATP-binding sequence followed by transmembrane segments in each half of the molecule. The bfr1+ protein exhibited significant homology in primary and secondary structures with two recently identified multidrug resistance gene products of Saccharomyces cerevisiae, Snq2 and Sts1/Pdr5/Ydr1. The bfr1+ gene is not essential for cell growth or mating, but a delta bfr1 mutant exhibited hypersensitivity to BFA. We propose that the bfr1+ protein is another member of the ATP-binding cassette superfamily and serves as an efflux pump of various antibiotics. PMID:7883711
A Monte Carlo-based framework enhances the discovery and interpretation of regulatory sequence motifs

PubMed Central

2012-01-01

Background Discovery of functionally significant short, statistically overrepresented subsequence patterns (motifs) in a set of sequences is a challenging problem in bioinformatics. Oftentimes, not all sequences in the set contain a motif. These non-motif-containing sequences complicate the algorithmic discovery of motifs. Filtering the non-motif-containing sequences from the larger set of sequences while simultaneously determining the identity of the motif is, therefore, desirable and a non-trivial problem in motif discovery research. Results We describe MotifCatcher, a framework that extends the sensitivity of existing motif-finding tools by employing random sampling to effectively remove non-motif-containing sequences from the motif search. We developed two implementations of our algorithm; each built around a commonly used motif-finding tool, and applied our algorithm to three diverse chromatin immunoprecipitation (ChIP) data sets. In each case, the motif finder with the MotifCatcher extension demonstrated improved sensitivity over the motif finder alone. Our approach organizes candidate functionally significant discovered motifs into a tree, which allowed us to make additional insights. In all cases, we were able to support our findings with experimental work from the literature. Conclusions Our framework demonstrates that additional processing at the sequence entry level can significantly improve the performance of existing motif-finding tools. For each biological data set tested, we were able to propose novel biological hypotheses supported by experimental work from the literature. Specifically, in Escherichia coli, we suggested binding site motifs for 6 non-traditional LexA protein binding sites; in Saccharomyces cerevisiae, we hypothesize 2 disparate mechanisms for novel binding sites of the Cse4p protein; and in Halobacterium sp. NRC-1, we discoverd subtle differences in a general transcription factor (GTF) binding site motif across several data sets. We suggest that small differences in our discovered motif could confer specificity for one or more homologous GTF proteins. We offer a free implementation of the MotifCatcher software package at http://www.bme.ucdavis.edu/facciotti/resources_data/software/. PMID:23181585
Fast gradient HPLC method to determine compounds binding to human serum albumin. Relationships with octanol/water and immobilized artificial membrane lipophilicity.

PubMed

Valko, Klara; Nunhuck, Shenaz; Bevan, Chris; Abraham, Michael H; Reynolds, Derek P

2003-11-01

A fast gradient HPLC method (cycle time 15 min) has been developed to determine Human Serum Albumin (HSA) binding of discovery compounds using chemically bonded protein stationary phases. The HSA binding values were derived from the gradient retention times that were converted to the logarithm of the equilibrium constants (logK HSA) using data from a calibration set of molecules. The method has been validated using literature plasma protein binding data of 68 known drug molecules. The method is fully automated, and has been used for lead optimization in more than 20 company projects. The HSA binding data obtained for more than 4000 compounds were suitable to set up global and project specific quantitative structure binding relationships that helped compound design in early drug discovery. The obtained HSA binding of known drug molecules were compared to the Immobilized Artificial Membrane binding data (CHI IAM) obtained by our previously described HPLC-based method. The solvation equation approach has been used to characterize the normal binding ability of HSA, and this relationship shows that compound lipophilicity is a significant factor. It was found that the selectivity of the "baseline" lipophilicity governing HSA binding, membrane interaction, and octanol/water partition are very similar. However, the effect of the presence of positive or negative charges have very different effects. It was found that negatively charged compounds bind more strongly to HSA than it would be expected from the lipophilicity of the ionized species at pH 7.4. Several compounds showed stronger HSA binding than can be expected from their lipophilicity alone, and comparison between predicted and experimental binding affinity allows the identification of compounds that have good complementarities with any of the known binding sites. Copyright 2003 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 92:2236-2248, 2003
Overproduction, purification and crystallization of a chondroitin sulfate A-binding DBL domain from a Plasmodium falciparum var2csa-encoded PfEMP1 protein

DOE Office of Scientific and Technical Information (OSTI.GOV)

Higgins, Matthew K., E-mail: mkh20@cam.ac.uk

A chondroitin sulfate A-binding DBL important in placental malaria has been overproduced, purified and crystallized. Diffraction data were collected to 1.9 Å resolution. The PfEMP1 proteins of the malaria parasite Plasmodium falciparum are inserted into the membrane of infected red blood cells, where they mediate adhesion to a variety of human receptors. The DBL domains of the var2csa-encoded PfEMP1 protein play a critical role in malaria of pregnancy, tethering infected cells to the surface of the placenta through interactions with the glycosaminoglycan carbohydrate chondroitin sulfate A (CSA). A CSA-binding DBL domain has been overproduced in a bacterial expression system, purifiedmore » and crystallized. Native data sets extending to 1.9 Å resolution have been collected and phasing is under way.« less
Molecular mechanisms of floral organ specification by MADS domain proteins.

PubMed

Yan, Wenhao; Chen, Dijun; Kaufmann, Kerstin

2016-02-01

Flower development is a model system to understand organ specification in plants. The identities of different types of floral organs are specified by homeotic MADS transcription factors that interact in a combinatorial fashion. Systematic identification of DNA-binding sites and target genes of these key regulators show that they have shared and unique sets of target genes. DNA binding by MADS proteins is not based on 'simple' recognition of a specific DNA sequence, but depends on DNA structure and combinatorial interactions. Homeotic MADS proteins regulate gene expression via alternative mechanisms, one of which may be to modulate chromatin structure and accessibility in their target gene promoters. Copyright © 2015 Elsevier Ltd. All rights reserved.
Multiple solvent crystal structures of ribonuclease A: An assessment of the method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dechene, Michelle; Wink, Glenna; Smith, Mychal

2010-11-12

The multiple solvent crystal structures (MSCS) method uses organic solvents to map the surfaces of proteins. It identifies binding sites and allows for a more thorough examination of protein plasticity and hydration than could be achieved by a single structure. The crystal structures of bovine pancreatic ribonuclease A (RNAse A) soaked in the following organic solvents are presented: 50% dioxane, 50% dimethylformamide, 70% dimethylsulfoxide, 70% 1,6-hexanediol, 70% isopropanol, 50% R,S,R-bisfuran alcohol, 70% t-butanol, 50% trifluoroethanol, or 1.0M trimethylamine-N-oxide. This set of structures is compared with four sets of crystal structures of RNAse A from the protein data bank (PDB) andmore » with the solution NMR structure to assess the validity of previously untested assumptions associated with MSCS analysis. Plasticity from MSCS is the same as from PDB structures obtained in the same crystal form and deviates only at crystal contacts when compared to structures from a diverse set of crystal environments. Furthermore, there is a good correlation between plasticity as observed by MSCS and the dynamic regions seen by NMR. Conserved water binding sites are identified by MSCS to be those that are conserved in the sets of structures taken from the PDB. Comparison of the MSCS structures with inhibitor-bound crystal structures of RNAse A reveals that the organic solvent molecules identify key interactions made by inhibitor molecules, highlighting ligand binding hot-spots in the active site. The present work firmly establishes the relevance of information obtained by MSCS.« less
Crystallization of the avian reovirus double-stranded RNA-binding and core protein σA

PubMed Central

Hermo-Parrado, X. Lois; Guardado-Calvo, Pablo; Llamas-Saiz, Antonio L.; Fox, Gavin C.; Vazquez-Iglesias, Lorena; Martínez-Costas, José; Benavente, Javier; van Raaij, Mark J.

2007-01-01

The avian reovirus protein σA plays a dual role: it is a structural protein forming part of the transcriptionally active core, but it has also been implicated in the resistance of the virus to interferon by strongly binding double-stranded RNA and thus inhibiting the double-stranded RNA-dependent protein kinase. The σA protein has been crystallized from solutions containing ammonium sulfate at pH values around 6. Crystals belonging to space group P1, with unit-cell parameters a = 103.2, b = 129.9, c = 144.0 Å, α = 93.8, β = 105.1, γ = 98.2° were grown and a complete data set has been collected to 2.3 Å resolution. The self-rotation function suggests that σA may form symmetric arrangements in the crystals. PMID:17565188
Analysis of Protein Interactions with Picomolar Binding Affinity by Fluorescence-Detected Sedimentation Velocity

PubMed Central

2014-01-01

The study of high-affinity protein interactions with equilibrium dissociation constants (KD) in the picomolar range is of significant interest in many fields, but the characterization of stoichiometry and free energy of such high-affinity binding can be far from trivial. Analytical ultracentrifugation has long been considered a gold standard in the study of protein interactions but is typically applied to systems with micromolar KD. Here we present a new approach for the study of high-affinity interactions using fluorescence detected sedimentation velocity analytical ultracentrifugation (FDS-SV). Taking full advantage of the large data sets in FDS-SV by direct boundary modeling with sedimentation coefficient distributions c(s), we demonstrate detection and hydrodynamic resolution of protein complexes at low picomolar concentrations. We show how this permits the characterization of the antibody–antigen interactions with low picomolar binding constants, 2 orders of magnitude lower than previously achieved. The strongly size-dependent separation and quantitation by concentration, size, and shape of free and complex species in free solution by FDS-SV has significant potential for studying high-affinity multistep and multicomponent protein assemblies. PMID:24552356
Herpes simplex virus type 1 tegument protein VP22 interacts with TAF-I proteins and inhibits nucleosome assembly but not regulation of histone acetylation by INHAT.

PubMed

van Leeuwen, Hans; Okuwaki, Mitsuru; Hong, Rui; Chakravarti, Debabrata; Nagata, Kyosuke; O'Hare, Peter

2003-09-01

Affinity chromatography was used to identify cellular proteins that interact with the herpes simplex virus (HSV) tegument protein VP22. Among a small set of proteins that bind specifically to VP22, we identified TAF-I (template-activating factor I), a chromatin remodelling protein and close homologue of the histone chaperone protein NAP-1. TAF-I has been shown previously to promote more ordered transfer of histones to naked DNA through a direct interaction with histones. TAF-I, as a subunit of the INHAT (inhibitor of acetyltransferases) protein complex, also binds to histones and masks them from being substrates for the acetyltransferases p300 and PCAF. Using in vitro assays for TAF-I activity in chromatin assembly, we show that VP22 inhibits nucleosome deposition on DNA by binding to TAF-I. We also observed that VP22 binds non-specifically to DNA, an activity that is abolished by TAF-I. However, the presence of VP22 does not affect the property of INHAT in inhibiting the histone acetyltransferase activity of p300 or PCAF in vitro. We speculate that this interaction could be relevant to HSV DNA organization early in infection, for example, by interfering with nucleosomal deposition on the genome. Consistent with this possibility was the observation that overexpression of TAF-I in transfected cells interferes with the progression of HSV-1 infection.

Computational approaches for identification of conserved/unique binding pockets in the A chain of ricin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ecale Zhou, C L; Zemla, A T; Roe, D

2005-01-29

Specific and sensitive ligand-based protein detection assays that employ antibodies or small molecules such as peptides, aptamers, or other small molecules require that the corresponding surface region of the protein be accessible and that there be minimal cross-reactivity with non-target proteins. To reduce the time and cost of laboratory screening efforts for diagnostic reagents, we developed new methods for evaluating and selecting protein surface regions for ligand targeting. We devised combined structure- and sequence-based methods for identifying 3D epitopes and binding pockets on the surface of the A chain of ricin that are conserved with respect to a set ofmore » ricin A chains and unique with respect to other proteins. We (1) used structure alignment software to detect structural deviations and extracted from this analysis the residue-residue correspondence, (2) devised a method to compare corresponding residues across sets of ricin structures and structures of closely related proteins, (3) devised a sequence-based approach to determine residue infrequency in local sequence context, and (4) modified a pocket-finding algorithm to identify surface crevices in close proximity to residues determined to be conserved/unique based on our structure- and sequence-based methods. In applying this combined informatics approach to ricin A we identified a conserved/unique pocket in close proximity (but not overlapping) the active site that is suitable for bi-dentate ligand development. These methods are generally applicable to identification of surface epitopes and binding pockets for development of diagnostic reagents, therapeutics, and vaccines.« less
Parkin, A Top Level Manager in the Cell’s Sanitation Department

PubMed Central

Rankin, Carolyn A; Roy, Ambrish; Zhang, Yang; Richter, Mark

2011-01-01

Parkin belongs to a class of multiple RING domain proteins designated as RBR (RING, in between RING, RING) proteins. In this review we examine what is known regarding the structure/function relationship of the Parkin protein. Parkin contains three RING domains plus a ubiquitin-like domain and an in-between-RING (IBR) domain. RING domains are rich in cysteine amino acids that act as ligands to bind zinc ions. RING domains may interact with DNA or with other proteins and perform a wide range of functions. Some function as E3 ubiquitin ligases, participating in attachment of ubiquitin chains to signal proteasome degradation; however, ubiquitin may be attached for purposes other than proteasome degradation. It was determined that the C-terminal most RING, RING2, is essential for Parkin to function as an E3 ubiquitin ligase and a number of substrates have been identified. However, Parkin also participates in a number of other fiunctions, such as DNA repair, microtubule stabilization, and formation of aggresomes. Some functions, such as participation in a multi-protein complex implicated in NMDA activity at the post synaptic density, do not require ubiquitination of substrate molecules. Recent observations of RING proteins suggest their function may be regulated by zinc ion binding. We have modeled the three RING domains of Parkin and have identified a new set of RING2 ligands. This set allows for binding of two rather than just one zinc ion, opening the possibility that the number of zinc ions bound acts as a molecular switch to modulate Parkin function. PMID:21633666
Recognition of functional sites in protein structures.

PubMed

Shulman-Peleg, Alexandra; Nussinov, Ruth; Wolfson, Haim J

2004-06-04

Recognition of regions on the surface of one protein, that are similar to a binding site of another is crucial for the prediction of molecular interactions and for functional classifications. We first describe a novel method, SiteEngine, that assumes no sequence or fold similarities and is able to recognize proteins that have similar binding sites and may perform similar functions. We achieve high efficiency and speed by introducing a low-resolution surface representation via chemically important surface points, by hashing triangles of physico-chemical properties and by application of hierarchical scoring schemes for a thorough exploration of global and local similarities. We proceed to rigorously apply this method to functional site recognition in three possible ways: first, we search a given functional site on a large set of complete protein structures. Second, a potential functional site on a protein of interest is compared with known binding sites, to recognize similar features. Third, a complete protein structure is searched for the presence of an a priori unknown functional site, similar to known sites. Our method is robust and efficient enough to allow computationally demanding applications such as the first and the third. From the biological standpoint, the first application may identify secondary binding sites of drugs that may lead to side-effects. The third application finds new potential sites on the protein that may provide targets for drug design. Each of the three applications may aid in assigning a function and in classification of binding patterns. We highlight the advantages and disadvantages of each type of search, provide examples of large-scale searches of the entire Protein Data Base and make functional predictions.
Guanine nucleotide-binding protein (Gα) endocytosis by a cascade of ubiquitin binding domain proteins is required for sustained morphogenesis and proper mating in yeast.

PubMed

Dixit, Gauri; Baker, Rachael; Sacks, Carly M; Torres, Matthew P; Dohlman, Henrik G

2014-05-23

Heterotrimeric G proteins are well known to transmit signals from cell surface receptors to intracellular effector proteins. There is growing appreciation that G proteins are also present at endomembrane compartments, where they can potentially interact with a distinct set of signaling proteins. Here, we examine the cellular trafficking function of the G protein α subunit in yeast, Gpa1. Gpa1 contains a unique 109-amino acid insert within the α-helical domain that undergoes a variety of posttranslational modifications. Among these is monoubiquitination, catalyzed by the NEDD4 family ubiquitin ligase Rsp5. Using a newly optimized method for G protein purification together with biophysical measures of structure and function, we show that the ubiquitination domain does not influence enzyme activity. By screening a panel of 39 gene deletion mutants, each lacking a different ubiquitin binding domain protein, we identify seven that are necessary to deliver Gpa1 to the vacuole compartment including four proteins (Ede1, Bul1, Ddi1, and Rup1) previously not known to be involved in this process. Finally, we show that proper endocytosis of the G protein is needed for sustained cellular morphogenesis and mating in response to pheromone stimulation. We conclude that a cascade of ubiquitin-binding proteins serves to deliver the G protein to its final destination within the cell. In this instance and in contrast to the previously characterized visual system, endocytosis from the plasma membrane is needed for proper signal transduction rather than for signal desensitization. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.
Heart-type fatty acid-binding protein in cardiovascular disease: A systemic review.

PubMed

Otaki, Yoichiro; Watanabe, Tetsu; Kubota, Isao

2017-11-01

Fatty acid-binding proteins, whose clinical applications have been studied, are a family of proteins that reflect tissue injury. Heart-type fatty acid-binding protein (H-FABP) is a marker of ongoing myocardial damage and useful for early diagnosis of acute myocardial infarction (AMI). In the past decade, compared to other cardiac enzymes, H-FABP has shown more promise as an early detection marker for AMI. However, the role of H-FABP is being re-examined due to recent refinement in the search for newer biomarkers, and greater understanding of the role of high-sensitivity troponin. We discuss the current role of H-FABP as an early marker for AMI in the era of high sensitive troponin. H-FABP is highlighted as a prognostic marker for a broad spectrum of fatal diseases, viz., AMI, heart failure, arrhythmia, and pulmonary embolism that could be associated with poor clinical outcomes. Because the cut-off value of what constitutes an abnormal H-FABP potentially differs for each cardiovascular event and depends on the clinical setting, an optimal cut-off value has not been clearly established. Of note, several factors such as age, gender, and cardiovascular risk factors, which affect H-FABP levels need to be considered in this context. In this review, we discuss the clinical applications of H-FABP as a prognostic marker in various clinical settings. Copyright © 2017 Elsevier B.V. All rights reserved.
Quantum annealing versus classical machine learning applied to a simplified computational biology problem

NASA Astrophysics Data System (ADS)

Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

2018-03-01

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to classify and rank binding affinities. Using simplified data sets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified data sets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems.
Interactions between Hofmeister anions and the binding pocket of a protein.

PubMed

Fox, Jerome M; Kang, Kyungtae; Sherman, Woody; Héroux, Annie; Sastry, G Madhavi; Baghbanzadeh, Mostafa; Lockett, Matthew R; Whitesides, George M

2015-03-25

This paper uses the binding pocket of human carbonic anhydrase II (HCAII, EC 4.2.1.1) as a tool to examine the properties of Hofmeister anions that determine (i) where, and how strongly, they associate with concavities on the surfaces of proteins and (ii) how, upon binding, they alter the structure of water within those concavities. Results from X-ray crystallography and isothermal titration calorimetry show that most anions associate with the binding pocket of HCAII by forming inner-sphere ion pairs with the Zn(2+) cofactor. In these ion pairs, the free energy of anion-Zn(2+) association is inversely proportional to the free energetic cost of anion dehydration; this relationship is consistent with the mechanism of ion pair formation suggested by the "law of matching water affinities". Iodide and bromide anions also associate with a hydrophobic declivity in the wall of the binding pocket. Molecular dynamics simulations suggest that anions, upon associating with Zn(2+), trigger rearrangements of water that extend up to 8 Å away from their surfaces. These findings expand the range of interactions previously thought to occur between ions and proteins by suggesting that (i) weakly hydrated anions can bind complementarily shaped hydrophobic declivities, and that (ii) ion-induced rearrangements of water within protein concavities can (in contrast with similar rearrangements in bulk water) extend well beyond the first hydration shells of the ions that trigger them. This study paints a picture of Hofmeister anions as a set of structurally varied ligands that differ in size, shape, and affinity for water and, thus, in their ability to bind to—and to alter the charge and hydration structure of—polar, nonpolar, and topographically complex concavities on the surfaces of proteins.
Recognizing metal and acid radical ion-binding sites by integrating ab initio modeling with template-based transferals.

PubMed

Hu, Xiuzhen; Dong, Qiwen; Yang, Jianyi; Zhang, Yang

2016-11-01

More than half of proteins require binding of metal and acid radical ions for their structure and function. Identification of the ion-binding locations is important for understanding the biological functions of proteins. Due to the small size and high versatility of the metal and acid radical ions, however, computational prediction of their binding sites remains difficult. We proposed a new ligand-specific approach devoted to the binding site prediction of 13 metal ions (Zn 2+ , Cu 2+ , Fe 2+ , Fe 3+ , Ca 2+ , Mg 2+ , Mn 2+ , Na + , K + ) and acid radical ion ligands (CO3 2- , NO2 - , SO4 2- , PO4 3- ) that are most frequently seen in protein databases. A sequence-based ab initio model is first trained on sequence profiles, where a modified AdaBoost algorithm is extended to balance binding and non-binding residue samples. A composite method IonCom is then developed to combine the ab initio model with multiple threading alignments for further improving the robustness of the binding site predictions. The pipeline was tested using 5-fold cross validations on a comprehensive set of 2,100 non-redundant proteins bound with 3,075 small ion ligands. Significant advantage was demonstrated compared with the state of the art ligand-binding methods including COACH and TargetS for high-accuracy ion-binding site identification. Detailed data analyses show that the major advantage of IonCom lies at the integration of complementary ab initio and template-based components. Ion-specific feature design and binding library selection also contribute to the improvement of small ion ligand binding predictions. http://zhanglab.ccmb.med.umich.edu/IonCom CONTACT: hxz@imut.edu.cn or zhng@umich.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
The methyltransferase NSD3 has chromatin-binding motifs, PHD5-C5HCH, that are distinct from other NSD (nuclear receptor SET domain) family members in their histone H3 recognition.

PubMed

He, Chao; Li, Fudong; Zhang, Jiahai; Wu, Jihui; Shi, Yunyu

2013-02-15

The NSD (nuclear receptor SET domain-containing) family members, consisting of NSD1, NSD2 (MMSET/WHSC1), and NSD3 (WHSC1L1), are SET domain-containing methyltransferases and aberrant expression of each member has been implicated in multiple diseases. They have specific mono- and dimethylase activities for H3K36, whereas play nonredundant roles during development. Aside from the well characterized catalytic SET domain, NSD proteins have multiple potential chromatin-binding motifs that are clinically relevant, including the fifth plant homeodomain (PHD5) and the adjacent Cys-His-rich domain (C5HCH) located at the C terminus. Herein, we report the crystal structures of the PHD5-C5HCH module of NSD3, in the free state and in complex with H3(1-7) (H3 residues 1-7), H3(1-15) (H3 residues 1-15), and H3(1-15)K9me3 (H3 residues 1-15 with trimethylation on K9) peptides. These structures reveal that the PHD5 and C5HCH domains fold into a novel integrated PHD-PHD-like structural module with H3 peptide bound only on the surface of PHD5 and provide the molecular basis for the recognition of unmodified H3K4 and trimethylated H3K9 by NSD3 PHD5. Structural studies and binding assays show that differences exist in histone binding specificity of the PHD5 domain between three members of the NSD family. For NSD2, the PHD5-C5HCH:H3 N terminus interaction is largely conserved, although with a stronger preference for unmethylated H3K9 (H3K9me0) than trimethylated H3K9 (H3K9me3), and NSD1 PHD5-C5HCH does not bind to H3 peptides. Our results shed light on how NSD proteins that mediate H3K36 methylation are localized to specific genomic sites and provide implications for the mechanism of functional diversity of NSD proteins.
QSAR modeling of β-lactam binding to human serum proteins

NASA Astrophysics Data System (ADS)

Hall, L. Mark; Hall, Lowell H.; Kier, Lemont B.

2003-02-01

The binding of beta-lactams to human serum proteins was modeled with topological descriptors of molecular structure. Experimental data was the concentration of protein-bound drug expressed as a percent of the total plasma concentration (percent fraction bound, PFB) for 87 penicillins and for 115 β-lactams. The electrotopological state indices (E-State) and the molecular connectivity chi indices were found to be the basis of two satisfactory models. A data set of 74 penicillins from a drug design series was successfully modeled with statistics: r2=0.80, s = 12.1, q2=0.76, spress=13.4. This model was then used to predict protein binding (PFB) for 13 commercial penicillins, resulting in a very good mean absolute error, MAE = 12.7 and correlation coefficient, q2=0.84. A group of 28 cephalosporins were combined with the penicillin data to create a dataset of 115 beta-lactams that was successfully modeled: r2=0.82, s = 12.7, q2=0.78, spress=13.7. A ten-fold 10% leave-group-out (LGO) cross-validation procedure was implemented, leading to very good statistics: MAE = 10.9, spress=14.0, q2 (or r2 press)=0.78. The models indicate a combination of general and specific structure features that are important for estimating protein binding in this class of antibiotics. For the β-lactams, significant factors that increase binding are presence and electron accessibility of aromatic rings, halogens, methylene groups, and =N- atoms. Significant negative influence on binding comes from amine groups and carbonyl oxygen atoms.
Developmental roles of 21 Drosophila transcription factors are determined by quantitative differences in binding to an overlapping set of thousands of genomic regions

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacArthur, Stewart; Li, Xiao-Yong; Li, Jingyi

2009-05-15

BACKGROUND: We previously established that six sequence-specific transcription factors that initiate anterior/posterior patterning in Drosophila bind to overlapping sets of thousands of genomic regions in blastoderm embryos. While regions bound at high levels include known and probable functional targets, more poorly bound regions are preferentially associated with housekeeping genes and/or genes not transcribed in the blastoderm, and are frequently found in protein coding sequences or in less conserved non-coding DNA, suggesting that many are likely non-functional. RESULTS: Here we show that an additional 15 transcription factors that regulate other aspects of embryo patterning show a similar quantitative continuum of functionmore » and binding to thousands of genomic regions in vivo. Collectively, the 21 regulators show a surprisingly high overlap in the regions they bind given that they belong to 11 DNA binding domain families, specify distinct developmental fates, and can act via different cis-regulatory modules. We demonstrate, however, that quantitative differences in relative levels of binding to shared targets correlate with the known biological and transcriptional regulatory specificities of these factors. CONCLUSIONS: It is likely that the overlap in binding of biochemically and functionally unrelated transcription factors arises from the high concentrations of these proteins in nuclei, which, coupled with their broad DNA binding specificities, directs them to regions of open chromatin. We suggest that most animal transcription factors will be found to show a similar broad overlapping pattern of binding in vivo, with specificity achieved by modulating the amount, rather than the identity, of bound factor.« less
Discovery of a new chemical series of BRD4(1) inhibitors using protein-ligand docking and structure-guided design.

PubMed

Duffy, Bryan C; Liu, Shuang; Martin, Gregory S; Wang, Ruifang; Hsia, Ming Min; Zhao, He; Guo, Cheng; Ellis, Michael; Quinn, John F; Kharenko, Olesya A; Norek, Karen; Gesner, Emily M; Young, Peter R; McLure, Kevin G; Wagner, Gregory S; Lakshminarasimhan, Damodharan; White, Andre; Suto, Robert K; Hansen, Henrik C; Kitchen, Douglas B

2015-07-15

Bromodomains are key transcriptional regulators that are thought to be druggable epigenetic targets for cancer, inflammation, diabetes and cardiovascular therapeutics. Of particular importance is the first of two bromodomains in bromodomain containing 4 protein (BRD4(1)). Protein-ligand docking in BRD4(1) was used to purchase a small, focused screening set of compounds possessing a large variety of core structures. Within this set, a small number of weak hits each contained a dihydroquinoxalinone ring system. We purchased other analogs with this ring system and further validated the new hit series and obtained improvement in binding inhibition. Limited exploration by new analog synthesis showed that the binding inhibition in a FRET assay could be improved to the low μM level making this new core a potential hit-to-lead series. Additionally, the predicted geometries of the initial hit and an improved analog were confirmed by X-ray co-crystallography with BRD4(1). Copyright © 2015 Elsevier Ltd. All rights reserved.
Identification of regions of rabbit muscle pyruvate kinase important for allosteric regulation by phenylalanine, detected by H/D exchange mass spectrometry†

PubMed Central

Prasannan, Charulata B.; Villar, Maria T.; Artigues, Antonio; Fenton, Aron W.

2013-01-01

Mass spectrometry has been used to determine the number of exchangeable backbone amide protons and the associated rate constants that are altered when rabbit muscle pyruvate kinase (rM1-PYK) binds either the allosteric inhibitor (phenylalanine) or a non-allosteric analogue of the inhibitor. Alanine is used as the non-allosteric analogue since it binds competitively with phenylalanine, but elicits a negligible allosteric inhibition, i.e. a negligible reduction of the affinity of rM1-PYK for the substrate, phosphoenolpyruvate (PEP). This experimental design is expected to distinguish changes in the protein caused by effector binding (i.e. those changes common upon the addition of alanine vs. phenylalanine) from changes associated with allosteric regulation (i.e. those elicited by the addition of phenylalanine binding, but not alanine binding). High quality peptic fragments covering 98% of the protein were identified. Changes in both the number of exchangeable protons per peptide and in the rate constant associated with exchange highlight regions of the protein with allosteric roles. The set of allosterically relevant peptides identified by this technique include residues previously identified by mutagenesis to have roles in the allosteric regulation by phenylalanine. PMID:23418858
Interaction of Colloidal Gold Nanoparticles with Model Serum Proteins: The Nanoparticle-Protein 'Corona' from a PhysicoChemical Viewpoint

NASA Astrophysics Data System (ADS)

Dominguez Medina, Sergio

When nanoparticles come in contact with biological fluids they become coated with a mixture of proteins present in the media, forming what is known as the nanoparticle-protein 'corona'. This corona changes the nanoparticles' original surface properties and plays a central role in how these get screened by cellular receptors. In the context of biomedical research, this presents a bottleneck for the transition of nanoparticles from research laboratories to clinical settings. It is therefore fundamental to probe these nanoparticle-protein interactions in order to understand the different physico-chemical mechanisms involved. This thesis is aimed to investigate the exposure of colloidal gold nanoparticles to model serum proteins, particularly serum albumin, the main transporter of molecular compounds in the bloodstream of mammals. A set of experimental tools based on optical microscopy and spectroscopy were developed in order to probe these interactions in situ. First, the intrinsic photoluminescence and elastic scattering of individual gold nanoparticles were investigated in order to understand its physical origin. These optical signals were then used to measure the size of the nanoparticles while in Brownian diffusion using fluctuation correlation spectroscopy. This spectroscopic tool was then applied to detect the binding of serum albumin onto the nanoparticle surface, increasing its hydrodynamic size. By performing a binding isotherm as a function of protein concentration, it was determined that serum albumin follows an anti-cooperative binding mechanism on negatively charged gold nanoparticles. This protein monolayer substantially enhanced the stability of the colloid, preventing their aggregation in saline solutions with ionic strength higher than biological media. Cationic gold nanoparticles in contrast, aggregated when serum albumin was present at a low protein-to-nanoparticle ratio, but prevented aggregation if exposed in excess. Single-molecule fluorescence microscopy revealed that under low protein-to-nanoparticle binding ratios, serum albumin irreversibly unfolds upon adsorption and spreads across the available nanoparticle surface area. Unfolded proteins then interact with one another, triggering nanoparticle aggregation. Fibrinogen and globulin also triggered aggregation when exposed to cationic nanoparticles. In an effort to relate these physico-chemical observations to relevant biological parameters, the uptake of protein coated gold nanoparticles by a model cancer cell line was investigated under different incubation conditions. Those nanoparticles pre-incubated with bovine serum albumin before fetal bovine serum were found to be uptaken three times more than those only incubated in serum.
Exploring the potential of a structural alphabet-based tool for mining multiple target conformations and target flexibility insight

PubMed Central

Chéron, Jean-Baptiste; Triki, Dhoha; Senac, Caroline; Flatters, Delphine; Camproux, Anne-Claude

2017-01-01

Protein flexibility is often implied in binding with different partners and is essential for protein function. The growing number of macromolecular structures in the Protein Data Bank entries and their redundancy has become a major source of structural knowledge of the protein universe. The analysis of structural variability through available redundant structures of a target, called multiple target conformations (MTC), obtained using experimental or modeling methods and under different biological conditions or different sources is one way to explore protein flexibility. This analysis is essential to improve the understanding of various mechanisms associated with protein target function and flexibility. In this study, we explored structural variability of three biological targets by analyzing different MTC sets associated with these targets. To facilitate the study of these MTC sets, we have developed an efficient tool, SA-conf, dedicated to capturing and linking the amino acid and local structure variability and analyzing the target structural variability space. The advantage of SA-conf is that it could be applied to divers sets composed of MTCs available in the PDB obtained using NMR and crystallography or homology models. This tool could also be applied to analyze MTC sets obtained by dynamics approaches. Our results showed that SA-conf tool is effective to quantify the structural variability of a MTC set and to localize the structural variable positions and regions of the target. By selecting adapted MTC subsets and comparing their variability detected by SA-conf, we highlighted different sources of target flexibility such as induced by binding partner, by mutation and intrinsic flexibility. Our results support the interest to mine available structures associated with a target using to offer valuable insight into target flexibility and interaction mechanisms. The SA-conf executable script, with a set of pre-compiled binaries are available at http://www.mti.univ-paris-diderot.fr/recherche/plateformes/logiciels. PMID:28817602
Exploring the potential of a structural alphabet-based tool for mining multiple target conformations and target flexibility insight.

PubMed

Regad, Leslie; Chéron, Jean-Baptiste; Triki, Dhoha; Senac, Caroline; Flatters, Delphine; Camproux, Anne-Claude

2017-01-01

Protein flexibility is often implied in binding with different partners and is essential for protein function. The growing number of macromolecular structures in the Protein Data Bank entries and their redundancy has become a major source of structural knowledge of the protein universe. The analysis of structural variability through available redundant structures of a target, called multiple target conformations (MTC), obtained using experimental or modeling methods and under different biological conditions or different sources is one way to explore protein flexibility. This analysis is essential to improve the understanding of various mechanisms associated with protein target function and flexibility. In this study, we explored structural variability of three biological targets by analyzing different MTC sets associated with these targets. To facilitate the study of these MTC sets, we have developed an efficient tool, SA-conf, dedicated to capturing and linking the amino acid and local structure variability and analyzing the target structural variability space. The advantage of SA-conf is that it could be applied to divers sets composed of MTCs available in the PDB obtained using NMR and crystallography or homology models. This tool could also be applied to analyze MTC sets obtained by dynamics approaches. Our results showed that SA-conf tool is effective to quantify the structural variability of a MTC set and to localize the structural variable positions and regions of the target. By selecting adapted MTC subsets and comparing their variability detected by SA-conf, we highlighted different sources of target flexibility such as induced by binding partner, by mutation and intrinsic flexibility. Our results support the interest to mine available structures associated with a target using to offer valuable insight into target flexibility and interaction mechanisms. The SA-conf executable script, with a set of pre-compiled binaries are available at http://www.mti.univ-paris-diderot.fr/recherche/plateformes/logiciels.
Nano-functionalization of protein microspheres

NASA Astrophysics Data System (ADS)

Yoon, Sungkwon; Nichols, William T.

2014-08-01

Protein microspheres are promising building blocks for the assembly of complex functional materials. Here we demonstrate a set of three techniques that add functionality to the surface of protein microspheres. In the first technique, a positive surface charge on the protein spheres is deposited by electrostatic adsorption. Negatively charged silica and gold nanoparticle colloids can then electrostatically bind reversibly to the microsphere surface. In the second technique, nanoparticles are covalently anchored to the protein shell using a simple one-pot process. The strong covalent bond between sulfur groups in cysteine in the protein shell irreversibly binds to the gold nanoparticles. In the third technique, surface morphology of the protein microsphere is tuned through hydrodynamic instability at the water-oil interface. This is accomplished through the degree of solubility of the oil phase in water. Taken together these three techniques form a platform to create nano-functionalized protein microspheres, which can then be used as building blocks for the assembly of more complex macroscopic materials.
An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge.

PubMed

Nassif, Houssam; Al-Ali, Hassan; Khuri, Sawsan; Keirouz, Walid; Page, David

2010-01-01

Hexoses are simple sugars that play a key role in many cellular pathways, and in the regulation of development and disease mechanisms. Current protein-sugar computational models are based, at least partially, on prior biochemical findings and knowledge. They incorporate different parts of these findings in predictive black-box models. We investigate the empirical support for biochemical findings by comparing Inductive Logic Programming (ILP) induced rules to actual biochemical results. We mine the Protein Data Bank for a representative data set of hexose binding sites, non-hexose binding sites and surface grooves. We build an ILP model of hexose-binding sites and evaluate our results against several baseline machine learning classifiers. Our method achieves an accuracy similar to that of other black-box classifiers while providing insight into the discriminating process. In addition, it confirms wet-lab findings and reveals a previously unreported Trp-Glu amino acids dependency.
Structures of Human Pumilio with Noncognate RNAs Reveal Molecular Mechanisms for Binding Promiscuity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gupta,Y.; Nair, D.; Wharton, R.

2008-01-01

Pumilio is a founder member of the evolutionarily conserved Puf family of RNA-binding proteins that control a number of physiological processes in eukaryotes. A structure of human Pumilio (hPum) Puf domain bound to a Drosophila regulatory sequence showed that each Puf repeat recognizes a single nucleotide. Puf domains in general bind promiscuously to a large set of degenerate sequences, but the structural basis for this promiscuity has been unclear. Here, we describe the structures of hPum Puf domain complexed to two noncognate RNAs, CycBreverse and Puf5. In each complex, one of the nucleotides is ejected from the binding surface, inmore » effect, acting as a 'spacer.' The complexes also reveal the plasticity of several Puf repeats, which recognize noncanonical nucleotides. Together, these complexes provide a molecular basis for recognition of degenerate binding sites, which significantly increases the number of mRNAs targeted for regulation by Puf proteins in vivo.« less
Cavity Versus Ligand Shape Descriptors: Application to Urokinase Binding Pockets.

PubMed

Cerisier, Natacha; Regad, Leslie; Triki, Dhoha; Camproux, Anne-Claude; Petitjean, Michel

2017-11-01

We analyzed 78 binding pockets of the human urokinase plasminogen activator (uPA) catalytic domain extracted from a data set of crystallized uPA-ligand complexes. These binding pockets were computed with an original geometric method that does NOT involve any arbitrary parameter, such as cutoff distances, angles, and so on. We measured the deviation from convexity of each pocket shape with the pocket convexity index (PCI). We defined a new pocket descriptor called distributional sphericity coefficient (DISC), which indicates to which extent the protein atoms of a given pocket lie on the surface of a sphere. The DISC values were computed with the freeware PCI. The pocket descriptors and their high correspondences with ligand descriptors are crucial for polypharmacology prediction. We found that the protein heavy atoms lining the urokinases binding pockets are either located on the surface of their convex hull or lie close to this surface. We also found that the radii of the urokinases binding pockets and the radii of their ligands are highly correlated (r = 0.9).

Dual-Color Luciferase Complementation for Chemokine Receptor Signaling.

PubMed

Luker, Kathryn E; Luker, Gary D

2016-01-01

Chemokine receptors may share common ligands, setting up potential competition for ligand binding, and association of activated receptors with downstream signaling molecules such as β-arrestin. Determining the "winner" of competition for shared effector molecules is essential for understanding integrated functions of chemokine receptor signaling in normal physiology, disease, and response to therapy. We describe a dual-color click beetle luciferase complementation assay for cell-based analysis of interactions of two different chemokine receptors, CXCR4 and ACKR3, with the intracellular scaffolding protein β-arrestin 2. This assay provides real-time quantification of receptor activation and signaling in response to chemokine CXCL12. More broadly, this general imaging strategy can be applied to quantify interactions of any set of two proteins that interact with a common binding partner. © 2016 Elsevier Inc. All rights reserved.
APBSmem: A Graphical Interface for Electrostatic Calculations at the Membrane

PubMed Central

Callenberg, Keith M.; Choudhary, Om P.; de Forest, Gabriel L.; Gohara, David W.; Baker, Nathan A.; Grabe, Michael

2010-01-01

Electrostatic forces are one of the primary determinants of molecular interactions. They help guide the folding of proteins, increase the binding of one protein to another and facilitate protein-DNA and protein-ligand binding. A popular method for computing the electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation, and there are several easy-to-use software packages available that solve the PB equation for soluble proteins. Here we present a freely available program, called APBSmem, for carrying out these calculations in the presence of a membrane. The Adaptive Poisson-Boltzmann Solver (APBS) is used as a back-end for solving the PB equation, and a Java-based graphical user interface (GUI) coordinates a set of routines that introduce the influence of the membrane, determine its placement relative to the protein, and set the membrane potential. The software Jmol is embedded in the GUI to visualize the protein inserted in the membrane before the calculation and the electrostatic potential after completing the computation. We expect that the ease with which the GUI allows one to carry out these calculations will make this software a useful resource for experimenters and computational researchers alike. Three examples of membrane protein electrostatic calculations are carried out to illustrate how to use APBSmem and to highlight the different quantities of interest that can be calculated. PMID:20949122
APBSmem: a graphical interface for electrostatic calculations at the membrane.

PubMed

Callenberg, Keith M; Choudhary, Om P; de Forest, Gabriel L; Gohara, David W; Baker, Nathan A; Grabe, Michael

2010-09-29

Electrostatic forces are one of the primary determinants of molecular interactions. They help guide the folding of proteins, increase the binding of one protein to another and facilitate protein-DNA and protein-ligand binding. A popular method for computing the electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation, and there are several easy-to-use software packages available that solve the PB equation for soluble proteins. Here we present a freely available program, called APBSmem, for carrying out these calculations in the presence of a membrane. The Adaptive Poisson-Boltzmann Solver (APBS) is used as a back-end for solving the PB equation, and a Java-based graphical user interface (GUI) coordinates a set of routines that introduce the influence of the membrane, determine its placement relative to the protein, and set the membrane potential. The software Jmol is embedded in the GUI to visualize the protein inserted in the membrane before the calculation and the electrostatic potential after completing the computation. We expect that the ease with which the GUI allows one to carry out these calculations will make this software a useful resource for experimenters and computational researchers alike. Three examples of membrane protein electrostatic calculations are carried out to illustrate how to use APBSmem and to highlight the different quantities of interest that can be calculated.
Dissecting the protein architecture of DNA-binding transcription factors in bacteria and archaea.

PubMed

Rivera-Gómez, Nancy; Martínez-Núñez, Mario Alberto; Pastor, Nina; Rodriguez-Vazquez, Katya; Perez-Rueda, Ernesto

2017-08-01

Gene regulation at the transcriptional level is a central process in all organisms where DNA-binding transcription factors play a fundamental role. This class of proteins binds specifically at DNA sequences, activating or repressing gene expression as a function of the cell's metabolic status, operator context and ligand-binding status, among other factors, through the DNA-binding domain (DBD). In addition, TFs may contain partner domains (PaDos), which are involved in ligand binding and protein-protein interactions. In this work, we systematically evaluated the distribution, abundance and domain organization of DNA-binding TFs in 799 non-redundant bacterial and archaeal genomes. We found that the distributions of the DBDs and their corresponding PaDos correlated with the size of the genome. We also identified specific combinations between the DBDs and their corresponding PaDos. Within each class of DBDs there are differences in the actual angle formed at the dimerization interface, responding to the presence/absence of ligands and/or crystallization conditions, setting the orientation of the resulting helices and wings facing the DNA. Our results highlight the importance of PaDos as central elements that enhance the diversity of regulatory functions in all bacterial and archaeal organisms, and our results also demonstrate the role of PaDos in sensing diverse signal compounds. The highly specific interactions between DBDs and PaDos observed in this work, together with our structural analysis highlighting the difficulty in predicting both inter-domain geometry and quaternary structure, suggest that these systems appeared once and evolved with diverse duplication events in all the analysed organisms.
Virus-producing cells determine the host protein profiles of HIV-1 virion cores

PubMed Central

2012-01-01

Background Upon HIV entry into target cells, viral cores are released and rearranged into reverse transcription complexes (RTCs), which support reverse transcription and also protect and transport viral cDNA to the site of integration. RTCs are composed of viral and cellular proteins that originate from both target and producer cells, the latter entering the target cell within the viral core. However, the proteome of HIV-1 viral cores in the context of the type of producer cells has not yet been characterized. Results We examined the proteomic profiles of the cores purified from HIV-1 NL4-3 virions assembled in Sup-T1 cells (T lymphocytes), PMA and vitamin D3 activated THP1 (model of macrophages, mMΦ), and non-activated THP1 cells (model of monocytes, mMN) and assessed potential involvement of identified proteins in the early stages of infection using gene ontology information and data from genome-wide screens on proteins important for HIV-1 replication. We identified 202 cellular proteins incorporated in the viral cores (T cells: 125, mMΦ: 110, mMN: 90) with the overlap between these sets limited to 42 proteins. The groups of RNA binding (29), DNA binding (17), cytoskeleton (15), cytoskeleton regulation (21), chaperone (18), vesicular trafficking-associated (12) and ubiquitin-proteasome pathway-associated proteins (9) were most numerous. Cores of the virions from SupT1 cells contained twice as many RNA binding proteins as cores of THP1-derived virus, whereas cores of virions from mMΦ and mMN were enriched in components of cytoskeleton and vesicular transport machinery, most probably due to differences in virion assembly pathways between these cells. Spectra of chaperones, cytoskeletal proteins and ubiquitin-proteasome pathway components were similar between viral cores from different cell types, whereas DNA-binding and especially RNA-binding proteins were highly diverse. Western blot analysis showed that within the group of overlapping proteins, the level of incorporation of some RNA binding (RHA and HELIC2) and DNA binding proteins (MCM5 and Ku80) in the viral cores from T cells was higher than in the cores from both mMΦ and mMN and did not correlate with the abundance of these proteins in virus producing cells. Conclusions Profiles of host proteins packaged in the cores of HIV-1 virions depend on the type of virus producing cell. The pool of proteins present in the cores of all virions is likely to contain factors important for viral functions. Incorporation ratio of certain RNA- and DNA-binding proteins suggests their more efficient, non-random packaging into virions in T cells than in mMΦ and mMN. PMID:22889230
Convergence and Sampling in Determining Free Energy Landscapes for Membrane Protein Association.

PubMed

Domański, Jan; Hedger, George; Best, Robert B; Stansfeld, Phillip J; Sansom, Mark S P

2017-04-20

Potential of mean force (PMF) calculations are used to characterize the free energy landscape of protein-lipid and protein-protein association within membranes. Coarse-grained simulations allow binding free energies to be determined with reasonable statistical error. This accuracy relies on defining a good collective variable to describe the binding and unbinding transitions, and upon criteria for assessing the convergence of the simulation toward representative equilibrium sampling. As examples, we calculate protein-lipid binding PMFs for ANT/cardiolipin and Kir2.2/PIP 2 , using umbrella sampling on a distance coordinate. These highlight the importance of replica exchange between windows for convergence. The use of two independent sets of simulations, initiated from bound and unbound states, provide strong evidence for simulation convergence. For a model protein-protein interaction within a membrane, center-of-mass distance is shown to be a poor collective variable for describing transmembrane helix-helix dimerization. Instead, we employ an alternative intermolecular distance matrix RMS (D RMS ) coordinate to obtain converged PMFs for the association of the glycophorin transmembrane domain. While the coarse-grained force field gives a reasonable K d for dimerization, the majority of the bound population is revealed to be in a near-native conformation. Thus, the combination of a refined reaction coordinate with improved sampling reveals previously unnoticed complexities of the dimerization free energy landscape. We propose the use of replica-exchange umbrella sampling starting from different initial conditions as a robust approach for calculation of the binding energies in membrane simulations.
High glucose disrupts oligosaccharide recognition function via competitive inhibition: a potential mechanism for immune dysregulation in diabetes mellitus.

PubMed

Ilyas, Rebecca; Wallis, Russell; Soilleux, Elizabeth J; Townsend, Paul; Zehnder, Daniel; Tan, Bee K; Sim, Robert B; Lehnert, Hendrik; Randeva, Harpal S; Mitchell, Daniel A

2011-01-01

Diabetic complications include infection and cardiovascular disease. Within the immune system, host-pathogen and regulatory host-host interactions operate through binding of oligosaccharides by C-type lectin. A number of C-type lectins recognise oligosaccharides rich in mannose and fucose - sugars with similar structures to glucose. This raises the possibility that high glucose conditions in diabetes affect protein-oligosaccharide interactions via competitive inhibition. Mannose-binding lectin, soluble DC-SIGN and DC-SIGNR, and surfactant protein D, were tested for carbohydrate binding in the presence of glucose concentrations typical of diabetes, via surface plasmon resonance and affinity chromatography. Complement activation assays were performed in high glucose. DC-SIGN and DC-SIGNR expression in adipose tissues was examined via immunohistochemistry. High glucose inhibited C-type lectin binding to high-mannose glycoprotein and binding of DC-SIGN to fucosylated ligand (blood group B) was abrogated in high glucose. Complement activation via the lectin pathway was inhibited in high glucose and also in high trehalose - a nonreducing sugar with glucoside stereochemistry. DC-SIGN staining was seen on cells with DC morphology within omental and subcutaneous adipose tissues. We conclude that high glucose disrupts C-type lectin function, potentially illuminating new perspectives on susceptibility to infectious and inflammatory disease in diabetes. Mechanisms involve competitive inhibition of carbohydrate binding within sets of defined proteins, in contrast to broadly indiscriminate, irreversible glycation of proteins. Copyright © 2010 Elsevier GmbH. All rights reserved.
Engineered Escherichia coli Silver-Binding Periplasmic Protein That Promotes Silver Tolerance

PubMed Central

Hall Sedlak, Ruth; Hnilova, Marketa; Grosh, Carolynn; Fong, Hanson; Baneyx, Francois; Schwartz, Dan; Sarikaya, Mehmet; Tamerler, Candan

2012-01-01

Silver toxicity is a problem that microorganisms face in medical and environmental settings. Through exposure to silver compounds, some bacteria have adapted to growth in high concentrations of silver ions. Such adapted microbes may be dangerous as pathogens but, alternatively, could be potentially useful in nanomaterial-manufacturing applications. While naturally adapted isolates typically utilize efflux pumps to achieve metal resistance, we have engineered a silver-tolerant Escherichia coli strain by the use of a simple silver-binding peptide motif. A silver-binding peptide, AgBP2, was identified from a combinatorial display library and fused to the C terminus of the E. coli maltose-binding protein (MBP) to yield a silver-binding protein exhibiting nanomolar affinity for the metal. Growth experiments performed in the presence of silver nitrate showed that cells secreting MBP-AgBP2 into the periplasm exhibited silver tolerance in a batch culture, while those expressing a cytoplasmic version of the fusion protein or MBP alone did not. Transmission electron microscopy analysis of silver-tolerant cells revealed the presence of electron-dense silver nanoparticles. This is the first report of a specifically engineered metal-binding peptide exhibiting a strong in vivo phenotype, pointing toward a novel ability to manipulate bacterial interactions with heavy metals by the use of short and simple peptide motifs. Engineered metal-ion-tolerant microorganisms such as this E. coli strain could potentially be used in applications ranging from remediation to interrogation of biomolecule-metal interactions in vivo. PMID:22286990
AutoSite: an automated approach for pseudo-ligands prediction—from ligand-binding sites identification to predicting key ligand atoms

PubMed Central

Ravindranath, Pradeep Anand; Sanner, Michel F.

2016-01-01

Motivation: The identification of ligand-binding sites from a protein structure facilitates computational drug design and optimization, and protein function assignment. We introduce AutoSite: an efficient software tool for identifying ligand-binding sites and predicting pseudo ligand corresponding to each binding site identified. Binding sites are reported as clusters of 3D points called fills in which every point is labelled as hydrophobic or as hydrogen bond donor or acceptor. From these fills AutoSite derives feature points: a set of putative positions of hydrophobic-, and hydrogen-bond forming ligand atoms. Results: We show that AutoSite identifies ligand-binding sites with higher accuracy than other leading methods, and produces fills that better matches the ligand shape and properties, than the fills obtained with a software program with similar capabilities, AutoLigand. In addition, we demonstrate that for the Astex Diverse Set, the feature points identify 79% of hydrophobic ligand atoms, and 81% and 62% of the hydrogen acceptor and donor hydrogen ligand atoms interacting with the receptor, and predict 81.2% of water molecules mediating interactions between ligand and receptor. Finally, we illustrate potential uses of the predicted feature points in the context of lead optimization in drug discovery projects. Availability and Implementation: http://adfr.scripps.edu/AutoDockFR/autosite.html Contact: sanner@scripps.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27354702
Binding site and affinity prediction of general anesthetics to protein targets using docking.

PubMed

Liu, Renyu; Perez-Aguilar, Jose Manuel; Liang, David; Saven, Jeffery G

2012-05-01

The protein targets for general anesthetics remain unclear. A tool to predict anesthetic binding for potential binding targets is needed. In this study, we explored whether a computational method, AutoDock, could serve as such a tool. High-resolution crystal data of water-soluble proteins (cytochrome C, apoferritin, and human serum albumin), and a membrane protein (a pentameric ligand-gated ion channel from Gloeobacter violaceus [GLIC]) were used. Isothermal titration calorimetry (ITC) experiments were performed to determine anesthetic affinity in solution conditions for apoferritin. Docking calculations were performed using DockingServer with the Lamarckian genetic algorithm and the Solis and Wets local search method (http://www.dockingserver.com/web). Twenty general anesthetics were docked into apoferritin. The predicted binding constants were compared with those obtained from ITC experiments for potential correlations. In the case of apoferritin, details of the binding site and their interactions were compared with recent cocrystallization data. Docking calculations for 6 general anesthetics currently used in clinical settings (isoflurane, sevoflurane, desflurane, halothane, propofol, and etomidate) with known 50% effective concentration (EC(50)) values were also performed in all tested proteins. The binding constants derived from docking experiments were compared with known EC(50) values and octanol/water partition coefficients for the 6 general anesthetics. All 20 general anesthetics docked unambiguously into the anesthetic binding site identified in the crystal structure of apoferritin. The binding constants for 20 anesthetics obtained from the docking calculations correlate significantly with those obtained from ITC experiments (P = 0.04). In the case of GLIC, the identified anesthetic binding sites in the crystal structure are among the docking predicted binding sites, but not the top ranked site. Docking calculations suggest a most probable binding site located in the extracellular domain of GLIC. The predicted affinities correlated significantly with the known EC(50) values for the 6 frequently used anesthetics in GLIC for the site identified in the experimental crystal data (P = 0.006). However, predicted affinities in apoferritin, human serum albumin, and cytochrome C did not correlate with these 6 anesthetics' known experimental EC(50) values. A weak correlation between the predicted affinities and the octanol/water partition coefficients was observed for the sites in GLIC. We demonstrated that anesthetic binding sites and relative affinities can be predicted using docking calculations in an automatic docking server (AutoDock) for both water-soluble and membrane proteins. Correlation of predicted affinity and EC(50) for 6 frequently used general anesthetics was only observed in GLIC, a member of a protein family relevant to anesthetic mechanism.
Binding Site and Affinity Prediction of General Anesthetics to Protein Targets Using Docking

PubMed Central

Liu, Renyu; Perez-Aguilar, Jose Manuel; Liang, David; Saven, Jeffery G.

2012-01-01

Background The protein targets for general anesthetics remain unclear. A tool to predict anesthetic binding for potential binding targets is needed. In this study, we explore whether a computational method, AutoDock, could serve as such a tool. Methods High-resolution crystal data of water soluble proteins (cytochrome C, apoferritin and human serum albumin), and a membrane protein (a pentameric ligand-gated ion channel from Gloeobacter violaceus, GLIC) were used. Isothermal titration calorimetry (ITC) experiments were performed to determine anesthetic affinity in solution conditions for apoferritin. Docking calculations were performed using DockingServer with the Lamarckian genetic algorithm and the Solis and Wets local search method (https://www.dockingserver.com/web). Twenty general anesthetics were docked into apoferritin. The predicted binding constants are compared with those obtained from ITC experiments for potential correlations. In the case of apoferritin, details of the binding site and their interactions were compared with recent co-crystallization data. Docking calculations for six general anesthetics currently used in clinical settings (isoflurane, sevoflurane, desflurane, halothane, propofol, and etomidate) with known EC50 were also performed in all tested proteins. The binding constants derived from docking experiments were compared with known EC50s and octanol/water partition coefficients for the six general anesthetics. Results All 20 general anesthetics docked unambiguously into the anesthetic binding site identified in the crystal structure of apoferritin. The binding constants for 20 anesthetics obtained from the docking calculations correlate significantly with those obtained from ITC experiments (p=0.04). In the case of GLIC, the identified anesthetic binding sites in the crystal structure are among the docking predicted binding sites, but not the top ranked site. Docking calculations suggest a most probable binding site located in the extracellular domain of GLIC. The predicted affinities correlated significantly with the known EC50s for the six commonly used anesthetics in GLIC for the site identified in the experimental crystal data (p=0.006). However, predicted affinities in apoferritin, human serum albumin, and cytochrome C did not correlate with these six anesthetics’ known experimental EC50s. A weak correlation between the predicted affinities and the octanol/water partition coefficients was observed for the sites in GLIC. Conclusion We demonstrated that anesthetic binding sites and relative affinities can be predicted using docking calculations in an automatic docking server (Autodock) for both water soluble and membrane proteins. Correlation of predicted affinity and EC50 for six commonly used general anesthetics was only observed in GLIC, a member of a protein family relevant to anesthetic mechanism. PMID:22392968
Rapid and accurate prediction and scoring of water molecules in protein binding sites.

PubMed

Ross, Gregory A; Morris, Garrett M; Biggin, Philip C

2012-01-01

Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.
Tumor-promoting function and prognostic significance of the RNA-binding protein T-cell intracellular antigen-1 in esophageal squamous cell carcinoma

PubMed Central

Fujita, Yuji; Naruto, Takuya; Kohmoto, Tomohiro; Miyakami, Yuko; Watanabe, Miki; Kudo, Yasusei; Fujiwara, Hitoshi; Ichikawa, Daisuke; Otsuji, Eigo; Imoto, Issei

2016-01-01

T-cell intracellular antigen-1 (TIA1) is an RNA-binding protein involved in many regulatory aspects of mRNA metabolism. Here, we report previously unknown tumor-promoting activity of TIA1, which seems to be associated with its isoform-specific molecular distribution and regulation of a set of cancer-related transcripts, in esophageal squamous cell carcinoma (ESCC). Immunohistochemical overexpression of TIA1 ectopically localized in the cytoplasm of tumor cells was an independent prognosticator for worse overall survival in a cohort of 143 ESCC patients. Knockdown of TIA1 inhibited proliferation of ESCC cells. By exogenously introducing each of two major isoforms, TIA1a and TIA1b, only TIA1a, which was localized to both the nucleus and cytoplasm, promoted anchorage-dependent and anchorage-independent ESCC cell proliferation. Ribonucleoprotein immunoprecipitation, followed by microarray analysis or massive-parallel sequencing, identified a set of TIA1-binding mRNAs, including SKP2 and CCNA2. TIA1 increased SKP2 and CCNA2 protein levels through the suppression of mRNA decay and translational induction, respectively. Our findings uncover a novel oncogenic function of TIA1 in esophageal tumorigenesis, and implicate its use as a marker for prognostic evaluation and as a therapeutic target in ESCC. PMID:26958940
Tumor-promoting function and prognostic significance of the RNA-binding protein T-cell intracellular antigen-1 in esophageal squamous cell carcinoma.

PubMed

Hamada, Junichi; Shoda, Katsutoshi; Masuda, Kiyoshi; Fujita, Yuji; Naruto, Takuya; Kohmoto, Tomohiro; Miyakami, Yuko; Watanabe, Miki; Kudo, Yasusei; Fujiwara, Hitoshi; Ichikawa, Daisuke; Otsuji, Eigo; Imoto, Issei

2016-03-29

T-cell intracellular antigen-1 (TIA1) is an RNA-binding protein involved in many regulatory aspects of mRNA metabolism. Here, we report previously unknown tumor-promoting activity of TIA1, which seems to be associated with its isoform-specific molecular distribution and regulation of a set of cancer-related transcripts, in esophageal squamous cell carcinoma (ESCC). Immunohistochemical overexpression of TIA1 ectopically localized in the cytoplasm of tumor cells was an independent prognosticator for worse overall survival in a cohort of 143 ESCC patients. Knockdown of TIA1 inhibited proliferation of ESCC cells. By exogenously introducing each of two major isoforms, TIA1a and TIA1b, only TIA1a, which was localized to both the nucleus and cytoplasm, promoted anchorage-dependent and anchorage-independent ESCC cell proliferation. Ribonucleoprotein immunoprecipitation, followed by microarray analysis or massive-parallel sequencing, identified a set of TIA1-binding mRNAs, including SKP2 and CCNA2. TIA1 increased SKP2 and CCNA2 protein levels through the suppression of mRNA decay and translational induction, respectively. Our findings uncover a novel oncogenic function of TIA1 in esophageal tumorigenesis, and implicate its use as a marker for prognostic evaluation and as a therapeutic target in ESCC.
CPI motif interaction is necessary for capping protein function in cells

PubMed Central

Edwards, Marc; McConnell, Patrick; Schafer, Dorothy A.; Cooper, John A.

2015-01-01

Capping protein (CP) has critical roles in actin assembly in vivo and in vitro. CP binds with high affinity to the barbed end of actin filaments, blocking the addition and loss of actin subunits. Heretofore, models for actin assembly in cells generally assumed that CP is constitutively active, diffusing freely to find and cap barbed ends. However, CP can be regulated by binding of the ‘capping protein interaction' (CPI) motif, found in a diverse and otherwise unrelated set of proteins that decreases, but does not abolish, the actin-capping activity of CP and promotes uncapping in biochemical experiments. Here, we report that CP localization and the ability of CP to function in cells requires interaction with a CPI-motif-containing protein. Our discovery shows that cells target and/or modulate the capping activity of CP via CPI motif interactions in order for CP to localize and function in cells. PMID:26412145
RCK: accurate and efficient inference of sequence- and structure-based protein-RNA binding models from RNAcompete data.

PubMed

Orenstein, Yaron; Wang, Yuhao; Berger, Bonnie

2016-06-15

Protein-RNA interactions, which play vital roles in many processes, are mediated through both RNA sequence and structure. CLIP-based methods, which measure protein-RNA binding in vivo, suffer from experimental noise and systematic biases, whereas in vitro experiments capture a clearer signal of protein RNA-binding. Among them, RNAcompete provides binding affinities of a specific protein to more than 240 000 unstructured RNA probes in one experiment. The computational challenge is to infer RNA structure- and sequence-based binding models from these data. The state-of-the-art in sequence models, Deepbind, does not model structural preferences. RNAcontext models both sequence and structure preferences, but is outperformed by GraphProt. Unfortunately, GraphProt cannot detect structural preferences from RNAcompete data due to the unstructured nature of the data, as noted by its developers, nor can it be tractably run on the full RNACompete dataset. We develop RCK, an efficient, scalable algorithm that infers both sequence and structure preferences based on a new k-mer based model. Remarkably, even though RNAcompete data is designed to be unstructured, RCK can still learn structural preferences from it. RCK significantly outperforms both RNAcontext and Deepbind in in vitro binding prediction for 244 RNAcompete experiments. Moreover, RCK is also faster and uses less memory, which enables scalability. While currently on par with existing methods in in vivo binding prediction on a small scale test, we demonstrate that RCK will increasingly benefit from experimentally measured RNA structure profiles as compared to computationally predicted ones. By running RCK on the entire RNAcompete dataset, we generate and provide as a resource a set of protein-RNA structure-based models on an unprecedented scale. Software and models are freely available at http://rck.csail.mit.edu/ bab@mit.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.
A Point Mutation in the Exon Junction Complex Factor Y14 Disrupts Its Function in mRNA Cap Binding and Translation Enhancement.

PubMed

Chuang, Tzu-Wei; Lee, Kuo-Ming; Lou, Yuan-Chao; Lu, Chia-Chen; Tarn, Woan-Yuh

2016-04-15

Eukaryotic mRNA biogenesis involves a series of interconnected steps mediated by RNA-binding proteins. The exon junction complex core protein Y14 is required for nonsense-mediated mRNA decay (NMD) and promotes translation. Moreover, Y14 binds the cap structure of mRNAs and inhibits the activity of the decapping enzyme Dcp2. In this report, we show that an evolutionarily conserved tryptophan residue (Trp-73) of Y14 is critical for its binding to the mRNA cap structure. A Trp-73 mutant (W73V) bound weakly to mRNAs and failed to protect them from degradation. However, this mutant could still interact with the NMD and mRNA degradation factors and retained partial NMD activity. In addition, we found that the W73V mutant could not interact with translation initiation factors. Overexpression of W73V suppressed reporter mRNA translation in vitro and in vivo and reduced the level of a set of nascent proteins. These results reveal a residue of Y14 that confers cap-binding activity and is essential for Y14-mediated enhancement of translation. Finally, we demonstrated that Y14 may selectively and differentially modulate protein biosynthesis. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
A Surface Energy Transfer Nanoruler for Measuring Binding Site Distances on Live Cell Surfaces

PubMed Central

Chen, Yan; O’Donoghue, Meghan B.; Huang, Yu-Fen; Kang, Huaizhi; Phillips, Joseph A.; Chen, Xiaolan; Estevez, M.-Carmen; Tan, Weihong

2010-01-01

Measuring distances at molecular length scales in living systems is a significant challenge. Methods like FRET have limitations due to short detection distances and strict orientations. Recently, surface energy transfer (SET) has been used in bulk solutions; however, it cannot be applied to living systems. Here, we have developed an SET nanoruler, using aptamer-gold-nanoparticle conjugates with different diameters, to monitor the distance between binding sites of a receptor on living cells. The nanoruler can measure separation distances well beyond the detection limit of FRET. Thus, for the first time, we have developed an effective SET nanoruler for live cells with long distance, easy construction, fast detection and low background. This is also the first time that the distance between the aptamer and antibody binding sites in the membrane protein PTK7 was measured accurately. The SET nanoruler represents the next leap forward to monitor structural components within living cell membranes. PMID:21038856
Splice-mediated Variants of Proteins (SpliVaP) - data and characterization of changes in signatures among protein isoforms due to alternative splicing.

PubMed

Floris, Matteo; Orsini, Massimiliano; Thanaraj, Thangavel Alphonse

2008-10-02

It is often the case that mammalian genes are alternatively spliced; the resulting alternate transcripts often encode protein isoforms that differ in amino acid sequences. Changes among the protein isoforms can alter the cellular properties of proteins. The effect can range from a subtle modulation to a complete loss of function. (i) We examined human splice-mediated protein isoforms (as extracted from a manually curated data set, and from a computationally predicted data set) for differences in the annotation for protein signatures (Pfam domains and PRINTS fingerprints) and we characterized the differences & their effects on protein functionalities. An important question addressed relates to the extent of protein isoforms that may lack any known function in the cell. (ii) We present a database that reports differences in protein signatures among human splice-mediated protein isoform sequences. (i) Characterization: The work points to distinct sets of alternatively spliced genes with varying degrees of annotation for the splice-mediated protein isoforms. Protein molecular functions seen to be often affected are those that relate to: binding, catalytic, transcription regulation, structural molecule, transporter, motor, and antioxidant; and the processes that are often affected are nucleic acid binding, signal transduction, and protein-protein interactions. Signatures are often included/excluded and truncated in length among protein isoforms; truncation is seen as the predominant type of change. Analysis points to the following novel aspects: (a) Analysis using data from the manually curated Vega indicates that one in 8.9 genes can lead to a protein isoform of no "known" function; and one in 18 expressed protein isoforms can be such an "orphan" isoform; the corresponding numbers as seen with computationally predicted ASD data set are: one in 4.9 genes and one in 9.8 isoforms. (b) When swapping of signatures occurs, it is often between those of same functional classifications. (c) Pfam domains can occur in varying lengths, and PRINTS fingerprints can occur with varying number of constituent motifs among isoforms - since such a variation is seen in large number of genes, it could be a general mechanism to modulate protein function. (ii) The reported resource (at http://www.bioinformatica.crs4.org/tools/dbs/splivap/) provides the community ability to access data on splice-mediated protein isoforms (with value-added annotation such as association with diseases) through changes in protein signatures.
BIPAD: A web server for modeling bipartite sequence elements

PubMed Central

Bi, Chengpeng; Rogan, Peter K

2006-01-01

Background Many dimeric protein complexes bind cooperatively to families of bipartite nucleic acid sequence elements, which consist of pairs of conserved half-site sequences separated by intervening distances that vary among individual sites. Results We introduce the Bipad Server [1], a web interface to predict sequence elements embedded within unaligned sequences. Either a bipartite model, consisting of a pair of one-block position weight matrices (PWM's) with a gap distribution, or a single PWM matrix for contiguous single block motifs may be produced. The Bipad program performs multiple local alignment by entropy minimization and cyclic refinement using a stochastic greedy search strategy. The best models are refined by maximizing incremental information contents among a set of potential models with varying half site and gap lengths. Conclusion The web service generates information positional weight matrices, identifies binding site motifs, graphically represents the set of discovered elements as a sequence logo, and depicts the gap distribution as a histogram. Server performance was evaluated by generating a collection of bipartite models for distinct DNA binding proteins. PMID:16503993

Identification of Conserved Water Sites in Protein Structures for Drug Design.

PubMed

Jukič, Marko; Konc, Janez; Gobec, Stanislav; Janežič, Dušanka

2017-12-26

Identification of conserved waters in protein structures is a challenging task with applications in molecular docking and protein stability prediction. As an alternative to computationally demanding simulations of proteins in water, experimental cocrystallized waters in the Protein Data Bank (PDB) in combination with a local structure alignment algorithm can be used for reliable prediction of conserved water sites. We developed the ProBiS H2O approach based on the previously developed ProBiS algorithm, which enables identification of conserved water sites in proteins using experimental protein structures from the PDB or a set of custom protein structures available to the user. With a protein structure, a binding site, or an individual water molecule as a query, ProBiS H2O collects similar proteins from the PDB and performs local or binding site-specific superimpositions of the query structure with similar proteins using the ProBiS algorithm. It collects the experimental water molecules from the similar proteins and transposes them to the query protein. Transposed waters are clustered by their mutual proximity, which enables identification of discrete sites in the query protein with high water conservation. ProBiS H2O is a robust and fast new approach that uses existing experimental structural data to identify conserved water sites on the interfaces of protein complexes, for example protein-small molecule interfaces, and elsewhere on the protein structures. It has been successfully validated in several reported proteins in which conserved water molecules were found to play an important role in ligand binding with applications in drug design.
PHOENIX: a scoring function for affinity prediction derived using high-resolution crystal structures and calorimetry measurements.

PubMed

Tang, Yat T; Marshall, Garland R

2011-02-28

Binding affinity prediction is one of the most critical components to computer-aided structure-based drug design. Despite advances in first-principle methods for predicting binding affinity, empirical scoring functions that are fast and only relatively accurate are still widely used in structure-based drug design. With the increasing availability of X-ray crystallographic structures in the Protein Data Bank and continuing application of biophysical methods such as isothermal titration calorimetry to measure thermodynamic parameters contributing to binding free energy, sufficient experimental data exists that scoring functions can now be derived by separating enthalpic (ΔH) and entropic (TΔS) contributions to binding free energy (ΔG). PHOENIX, a scoring function to predict binding affinities of protein-ligand complexes, utilizes the increasing availability of experimental data to improve binding affinity predictions by the following: model training and testing using high-resolution crystallographic data to minimize structural noise, independent models of enthalpic and entropic contributions fitted to thermodynamic parameters assumed to be thermodynamically biased to calculate binding free energy, use of shape and volume descriptors to better capture entropic contributions. A set of 42 descriptors and 112 protein-ligand complexes were used to derive functions using partial least-squares for change of enthalpy (ΔH) and change of entropy (TΔS) to calculate change of binding free energy (ΔG), resulting in a predictive r2 (r(pred)2) of 0.55 and a standard error (SE) of 1.34 kcal/mol. External validation using the 2009 version of the PDBbind "refined set" (n = 1612) resulted in a Pearson correlation coefficient (R(p)) of 0.575 and a mean error (ME) of 1.41 pK(d). Enthalpy and entropy predictions were of limited accuracy individually. However, their difference resulted in a relatively accurate binding free energy. While the development of an accurate and applicable scoring function was an objective of this study, the main focus was evaluation of the use of high-resolution X-ray crystal structures with high-quality thermodynamic parameters from isothermal titration calorimetry for scoring function development. With the increasing application of structure-based methods in molecular design, this study suggests that using high-resolution crystal structures, separating enthalpy and entropy contributions to binding free energy, and including descriptors to better capture entropic contributions may prove to be effective strategies toward rapid and accurate calculation of binding affinity.
A binary plasmid system for shuffling combinatorial antibody libraries.

PubMed

Collet, T A; Roben, P; O'Kennedy, R; Barbas, C F; Burton, D R; Lerner, R A

1992-11-01

We have used a binary system of replicon-compatible plasmids to test the potential for promiscuous recombination of heavy and light chains within sets of human Fab fragments isolated from combinatorial antibody libraries. Antibody molecules showed a surprising amount of promiscuity in that a particular heavy chain could recombine with multiple light chains with retention of binding to a protein antigen. The degree to which a given heavy chain productively paired with any light chain to bind antigen varied from 43% to 100% and depended strongly on the heavy-chain sequence. Such productive crosses resulted in a set of Fab fragments of similar apparent binding constants, which seemed to differ mainly in the amount of active Fab fragment produced in the bacterial cell. The dominance of the heavy chain in the antibody-antigen interaction was further explored in a set of directed crosses, in which heavy and light chains derived from antigen-specific clones were crossed with nonrelated heavy and light chains. In these crosses, an Fab fragment retained antigen binding only if it contained a heavy chain from an antigen-specific clone. In no case did the light chain confer detectable affinity when paired with indifferent heavy chains. The surprising promiscuity of heavy chains has ramifications for the evaluation of the diversity of combinatorial libraries made against protein antigens and should allow the combination of one such promiscuous heavy chain with an engineered light chain to form an Fab fragment carrying synthetic cofactors to assist in antibody catalysis.
A binary plasmid system for shuffling combinatorial antibody libraries.

PubMed Central

Collet, T A; Roben, P; O'Kennedy, R; Barbas, C F; Burton, D R; Lerner, R A

1992-01-01

We have used a binary system of replicon-compatible plasmids to test the potential for promiscuous recombination of heavy and light chains within sets of human Fab fragments isolated from combinatorial antibody libraries. Antibody molecules showed a surprising amount of promiscuity in that a particular heavy chain could recombine with multiple light chains with retention of binding to a protein antigen. The degree to which a given heavy chain productively paired with any light chain to bind antigen varied from 43% to 100% and depended strongly on the heavy-chain sequence. Such productive crosses resulted in a set of Fab fragments of similar apparent binding constants, which seemed to differ mainly in the amount of active Fab fragment produced in the bacterial cell. The dominance of the heavy chain in the antibody-antigen interaction was further explored in a set of directed crosses, in which heavy and light chains derived from antigen-specific clones were crossed with nonrelated heavy and light chains. In these crosses, an Fab fragment retained antigen binding only if it contained a heavy chain from an antigen-specific clone. In no case did the light chain confer detectable affinity when paired with indifferent heavy chains. The surprising promiscuity of heavy chains has ramifications for the evaluation of the diversity of combinatorial libraries made against protein antigens and should allow the combination of one such promiscuous heavy chain with an engineered light chain to form an Fab fragment carrying synthetic cofactors to assist in antibody catalysis. Images PMID:1438192
Macroscopic modeling and simulations of supercoiled DNA with bound proteins

NASA Astrophysics Data System (ADS)

Huang, Jing; Schlick, Tamar

2002-11-01

General methods are presented for modeling and simulating DNA molecules with bound proteins on the macromolecular level. These new approaches are motivated by the need for accurate and affordable methods to simulate slow processes (on the millisecond time scale) in DNA/protein systems, such as the large-scale motions involved in the Hin-mediated inversion process. Our approaches, based on the wormlike chain model of long DNA molecules, introduce inhomogeneous potentials for DNA/protein complexes based on available atomic-level structures. Electrostatically, treat those DNA/protein complexes as sets of effective charges, optimized by our discrete surface charge optimization package, in which the charges are distributed on an excluded-volume surface that represents the macromolecular complex. We also introduce directional bending potentials as well as non-identical bead hydrodynamics algorithm to further mimic the inhomogeneous effects caused by protein binding. These models thus account for basic elements of protein binding effects on DNA local structure but remain computational tractable. To validate these models and methods, we reproduce various properties measured by both Monte Carlo methods and experiments. We then apply the developed models to study the Hin-mediated inversion system in long DNA. By simulating supercoiled, circular DNA with or without bound proteins, we observe significant effects of protein binding on global conformations and long-time dynamics of the DNA on the kilo basepair length.
Metals in proteins: correlation between the metal-ion type, coordination number and the amino-acid residues involved in the coordination.

PubMed

Dokmanić, Ivan; Sikić, Mile; Tomić, Sanja

2008-03-01

Metal ions are constituents of many metalloproteins, in which they have either catalytic (metalloenzymes) or structural functions. In this work, the characteristics of various metals were studied (Cu, Zn, Mg, Mn, Fe, Co, Ni, Cd and Ca in proteins with known crystal structure) as well as the specificity of their environments. The analysis was performed on two data sets: the set of protein structures in the Protein Data Bank (PDB) determined with resolution <1.5 A and the set of nonredundant protein structures from the PDB. The former was used to determine the distances between each metal ion and its electron donors and the latter was used to assess the preferred coordination numbers and common combinations of amino-acid residues in the neighbourhood of each metal. Although the metal ions considered predominantly had a valence of two, their preferred coordination number and the type of amino-acid residues that participate in the coordination differed significantly from one metal ion to the next. This study concentrates on finding the specificities of a metal-ion environment, namely the distribution of coordination numbers and the amino-acid residue types that frequently take part in coordination. Furthermore, the correlation between the coordination number and the occurrence of certain amino-acid residues (quartets and triplets) in a metal-ion coordination sphere was analysed. The results obtained are of particular value for the identification and modelling of metal-binding sites in protein structures derived by homology modelling. Knowledge of the geometry and characteristics of the metal-binding sites in metalloproteins of known function can help to more closely determine the biological activity of proteins of unknown function and to aid in design of proteins with specific affinity for certain metals.
The poly(rC)-binding protein αCP2 is a noncanonical factor in X. laevis cytoplasmic polyadenylation

PubMed Central

Vishnu, Melanie R.; Sumaroka, Marina; Klein, Peter S.; Liebhaber, Stephen A.

2011-01-01

Post-transcriptional control of mRNA stability and translation is central to multiple developmental pathways. This control can be linked to cytoplasmic polyadenylation in certain settings. In maturing Xenopus oocytes, specific mRNAs are targeted for polyadenylation via recruitment of the Cytoplasmic Polyadenylation Element (CPE) binding protein (CPEB) to CPE(s) within the 3′ UTR. Cytoplasmic polyadenylation is also critical to early embryonic events, although corresponding determinants are less defined. Here, we demonstrate that the Xenopus ortholog of the poly(rC) binding protein αCP2 can recruit cytoplasmic poly(A) polymerase activity to mRNAs in Xenopus post-fertilization embryos, and that this recruitment relies on cis sequences recognized by αCP2. We find that the hα-globin 3′ UTR, a validated mammalian αCP2 target, constitutes an effective target for cytoplasmic polyadenylation in Xenopus embryos, but not during Xenopus oocyte maturation. We further demonstrate that the cytoplasmic polyadenylation activity is dependent on the action of the C-rich αCP-binding site in conjunction with the adjacent AAUAAA. Consistent with its ability to target mRNA for poly(A) addition, we find that XαCP2 associates with core components of the Xenopus cytoplasmic polyadenylation complex, including the cytoplasmic poly(A) polymerase XGLD2. Furthermore, we observe that the C-rich αCP-binding site can robustly enhance the activity of a weak canonical oocyte maturation CPE in early embryos, possibly via a direct interaction between XαCP2 and CPEB1. These studies establish XαCP2 as a novel cytoplasmic polyadenylation trans factor, indicate that C-rich sequences can function as noncanonical cytoplasmic polyadenylation elements, and expand our understanding of the complexities underlying cytoplasmic polyadenylation in specific developmental settings. PMID:21444632
Zona pellucida-binding protein 2 (ZPBP2) and several proteins containing BX7B motifs in human sperm may have hyaluronic acid binding or recognition properties.

PubMed

Torabi, F; Bogle, O A; Estanyol, J M; Oliva, R; Miller, D

2017-12-01

Are there novel hyaladherins in human sperm? Zona pellucida-binding protein 2 (ZPBP2), containing a Link-like hyaluronic acid (HA)-binding domain, and several other proteins containing BX7B motifs, such as ADAM32 and Midkine, may be novel hyaladherins with HA-binding properties. HA-binding proteins (hyaladherins), which can bind HA surrounding the cumulus-oophorus complex, are distinct from hyases such as PH 20 (SPAM1) and are expressed by mature spermatozoa. Although HABP1 and CD44 are reasonably well characterized hyaladherins and the former has been implicated in sperm-oocyte interactions, the overall significance of sperm hyaladherins for male fertility is still poorly understood. This was a laboratory-based investigation into human sperm hyaladherins undertaken as part of a three year PhD programme sponsored by the EU Marie Curie Training network, Reprotrain. Protein homogenates of sperm obtained from young men of unknown fertility (N = 4) were partitioned into HA-binding and non-binding fractions by a protein affinity 'panning' method; their subsequent characterization was by liquid chromatography-tandem mass spectrometry (LC-MS-MS) and partitioning behaviour was confirmed by western blotting. Sequences of proteins from both fractions were submitted to PDBsum to look for orthologous entries (PDB codes) and all returned codes were queried against the matching protein using SAS (Sequences Annotated by Structure) looking for structural similarities between them. A systematic search for other common features of hyaladherins was also undertaken. The presence of BX7B sequence motifs found in several well-described hyaladherins including RHAMM was used to assess efficacy of potential hyaladherin partitioning by the HA substrate. The data showed that 50% (14/28) and 34.5% (28/81) of proteins in the bound and unbound fractions, respectively, contained these motifs (one-tailed Z-score = 1.45; P = 0.074), indicating weak discrimination by the substrate. Querying PDBsum with sequences for all bound proteins returned several PDB codes matching ZPBP2 with the HA-binding Link domain of the hyaladherin, CD44. Western blot analysis confirmed the affinity partitioning of proteins indicated by the LC-MS/MS results, with ADAM32 (containing two BX7B motifs) and ZPBP2 (containing a Link-like HA-binding domain) present only in the binding fraction. There remains the possibility that the putative hyaladherins uncovered by this study were coincidentally enriched by HA-binding. The full proteomics data set is available on request. The protein extraction methods or the HA substrate used to pan them in this study were probably not ideal, as hyaladherins expected to be present in sperm homogenates (such as CD44 and RHAMM) were not detected. The results provide evidence that ZPBP2, found only in the bound fraction, may have hyaladherin-like properties, which could reflect the evolutionary background context of contemporary sperm-oocyte interaction mechanisms. An EU Marie Curie Sklodowska Initial Training Network Scholarship, supporting Ms Torabi, is gratefully acknowledged. This project was also supported and funded by the Efficacy and Mechanism Evaluation Programme, a UK MRC and NIHR partnership (Grant No 11/14/ 34). There is no conflict of interest in relation to this work. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Human Alveolar Macrophages May Not Be Susceptible to Direct Infection by a Human Influenza Virus.

PubMed

Ettensohn, David B; Frampton, Mark W; Nichols, Joan E; Roberts, Norbert J

2016-12-01

The current studies were undertaken to determine the susceptibility of human alveolar macrophages (AMs) to influenza A virus (IAV) infection in comparison with autologous peripheral blood-derived monocytes-macrophages (PBMs). AMs and PBMs were exposed to IAV in vitro and examined for their ability to bind and internalize IAV, and synthesize viral proteins and RNA. PBMs but not AMs demonstrated binding and internalization of the virus, synthesizing viral proteins and RNA. Exposure of AMs in the presence of a sialidase inhibitor or anti-IAV antibody resulted in viral protein synthesis by the cells. Exposure of AMs to fluorescein isothiocyanate-labeled IAV in the presence of anti-fluorescein isothiocyanate antibody also resulted in viral protein synthesis. Thus, human AMs are apparently not susceptible to direct infection by a human IAV but are likely to be infected indirectly in the setting of exposure in the presence of antibody that binds the challenging strain of IAV. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.
Identification of distant drug off-targets by direct superposition of binding pocket surfaces.

PubMed

Schumann, Marcel; Armen, Roger S

2013-01-01

Correctly predicting off-targets for a given molecular structure, which would have the ability to bind a large range of ligands, is both particularly difficult and important if they share no significant sequence or fold similarity with the respective molecular target ("distant off-targets"). A novel approach for identification of off-targets by direct superposition of protein binding pocket surfaces is presented and applied to a set of well-studied and highly relevant drug targets, including representative kinases and nuclear hormone receptors. The entire Protein Data Bank is searched for similar binding pockets and convincing distant off-target candidates were identified that share no significant sequence or fold similarity with the respective target structure. These putative target off-target pairs are further supported by the existence of compounds that bind strongly to both with high topological similarity, and in some cases, literature examples of individual compounds that bind to both. Also, our results clearly show that it is possible for binding pockets to exhibit a striking surface similarity, while the respective off-target shares neither significant sequence nor significant fold similarity with the respective molecular target ("distant off-target").
Identification of Distant Drug Off-Targets by Direct Superposition of Binding Pocket Surfaces

PubMed Central

Schumann, Marcel; Armen, Roger S.

2013-01-01

Correctly predicting off-targets for a given molecular structure, which would have the ability to bind a large range of ligands, is both particularly difficult and important if they share no significant sequence or fold similarity with the respective molecular target (“distant off-targets”). A novel approach for identification of off-targets by direct superposition of protein binding pocket surfaces is presented and applied to a set of well-studied and highly relevant drug targets, including representative kinases and nuclear hormone receptors. The entire Protein Data Bank is searched for similar binding pockets and convincing distant off-target candidates were identified that share no significant sequence or fold similarity with the respective target structure. These putative target off-target pairs are further supported by the existence of compounds that bind strongly to both with high topological similarity, and in some cases, literature examples of individual compounds that bind to both. Also, our results clearly show that it is possible for binding pockets to exhibit a striking surface similarity, while the respective off-target shares neither significant sequence nor significant fold similarity with the respective molecular target (“distant off-target”). PMID:24391782
Structural Basis for the Recognition of Tyrosine-based Sorting Signals by the μ3A Subunit of the AP-3 Adaptor Complex*

PubMed Central

Mardones, Gonzalo A.; Burgos, Patricia V.; Lin, Yimo; Kloer, Daniel P.; Magadán, Javier G.; Hurley, James H.; Bonifacino, Juan S.

2013-01-01

Tyrosine-based signals fitting the YXXØ motif mediate sorting of transmembrane proteins to endosomes, lysosomes, the basolateral plasma membrane of polarized epithelial cells, and the somatodendritic domain of neurons through interactions with the homologous μ1, μ2, μ3, and μ4 subunits of the corresponding AP-1, AP-2, AP-3, and AP-4 complexes. Previous x-ray crystallographic analyses identified distinct binding sites for YXXØ signals on μ2 and μ4, which were located on opposite faces of the proteins. To elucidate the mode of recognition of YXXØ signals by other members of the μ family, we solved the crystal structure at 1.85 Å resolution of the C-terminal domain of the μ3 subunit of AP-3 (isoform A) in complex with a peptide encoding a YXXØ signal (SDYQRL) from the trans-Golgi network protein TGN38. The μ3A C-terminal domain consists of an immunoglobulin-like β-sandwich organized into two subdomains, A and B. The YXXØ signal binds in an extended conformation to a site on μ3A subdomain A, at a location similar to the YXXØ-binding site on μ2 but not μ4. The binding sites on μ3A and μ2 exhibit similarities and differences that account for the ability of both proteins to bind distinct sets of YXXØ signals. Biochemical analyses confirm the identification of the μ3A site and show that this protein binds YXXØ signals with 14–19 μm affinity. The surface electrostatic potential of μ3A is less basic than that of μ2, in part explaining the association of AP-3 with intracellular membranes having less acidic phosphoinositides. PMID:23404500
Structural basis for the recognition of tyrosine-based sorting signals by the μ3A subunit of the AP-3 adaptor complex.

PubMed

Mardones, Gonzalo A; Burgos, Patricia V; Lin, Yimo; Kloer, Daniel P; Magadán, Javier G; Hurley, James H; Bonifacino, Juan S

2013-03-29

Tyrosine-based signals fitting the YXXØ motif mediate sorting of transmembrane proteins to endosomes, lysosomes, the basolateral plasma membrane of polarized epithelial cells, and the somatodendritic domain of neurons through interactions with the homologous μ1, μ2, μ3, and μ4 subunits of the corresponding AP-1, AP-2, AP-3, and AP-4 complexes. Previous x-ray crystallographic analyses identified distinct binding sites for YXXØ signals on μ2 and μ4, which were located on opposite faces of the proteins. To elucidate the mode of recognition of YXXØ signals by other members of the μ family, we solved the crystal structure at 1.85 Å resolution of the C-terminal domain of the μ3 subunit of AP-3 (isoform A) in complex with a peptide encoding a YXXØ signal (SDYQRL) from the trans-Golgi network protein TGN38. The μ3A C-terminal domain consists of an immunoglobulin-like β-sandwich organized into two subdomains, A and B. The YXXØ signal binds in an extended conformation to a site on μ3A subdomain A, at a location similar to the YXXØ-binding site on μ2 but not μ4. The binding sites on μ3A and μ2 exhibit similarities and differences that account for the ability of both proteins to bind distinct sets of YXXØ signals. Biochemical analyses confirm the identification of the μ3A site and show that this protein binds YXXØ signals with 14-19 μm affinity. The surface electrostatic potential of μ3A is less basic than that of μ2, in part explaining the association of AP-3 with intracellular membranes having less acidic phosphoinositides.
Novel Family of Insect Salivary Inhibitors Blocks Contact Pathway Activation by Binding to Polyphosphate, Heparin, and Dextran Sulfate

PubMed Central

Alvarenga, Patricia H.; Xu, Xueqing; Oliveira, Fabiano; Chagas, Andrezza C.; Nascimento, Clarissa R.; Francischetti, Ivo M.B.; Juliano, Maria A.; Juliano, Luiz; Scharfstein, Julio; Valenzuela, Jesus G.; Ribeiro, José M.C.; Andersen, John F.

2014-01-01

Objective Polyphosphate and heparin are anionic polymers released by activated mast cells and platelets that are known to stimulate the contact pathway of coagulation. These polymers promote both the autoactivation of factor XII and the assembly of complexes containing factor XI, prekallikrein, and high-molecular-weight kininogen. We are searching for salivary proteins from blood-feeding insects that counteract the effect of procoagulant and proinflammatory factors in the host, including elements of the contact pathway. Approach and Results Here, we evaluate the ability of the sand fly salivary proteins, PdSP15a and PdSP15b, to inhibit the contact pathway by disrupting binding of its components to anionic polymers. We attempt to demonstrate binding of the proteins to polyphosphate, heparin, and dextran sulfate. We also evaluate the effect of this binding on contact pathway reactions. We also set out to determine the x-ray crystal structure of PdSP15b and examine the determinants of relevant molecular interactions. Both proteins bind polyphosphate, heparin, and dextran sulfate with high affinity. Through this mechanism they inhibit the autoactivation of factor XII and factor XI, the reciprocal activation of factor XII and prekallikrein, the activation of factor XI by thrombin and factor XIIa, the cleavage of high-molecular-weight kininogen in plasma, and plasma extravasation induced by polyphosphate. The crystal structure of PdSP15b contains an amphipathic helix studded with basic side chains that forms the likely interaction surface. Conclusions The results of these studies indicate that the binding of anionic polymers by salivary proteins is used by blood feeders as an antihemostatic/anti-inflammatory mechanism. PMID:24092749
Impact of mutations on the allosteric conformational equilibrium

PubMed Central

Weinkam, Patrick; Chen, Yao Chi; Pons, Jaume; Sali, Andrej

2012-01-01

Allostery in a protein involves effector binding at an allosteric site that changes the structure and/or dynamics at a distant, functional site. In addition to the chemical equilibrium of ligand binding, allostery involves a conformational equilibrium between one protein substate that binds the effector and a second substate that less strongly binds the effector. We run molecular dynamics simulations using simple, smooth energy landscapes to sample specific ligand-induced conformational transitions, as defined by the effector-bound and unbound protein structures. These simulations can be performed using our web server: http://salilab.org/allosmod/. We then develop a set of features to analyze the simulations and capture the relevant thermodynamic properties of the allosteric conformational equilibrium. These features are based on molecular mechanics energy functions, stereochemical effects, and structural/dynamic coupling between sites. Using a machine-learning algorithm on a dataset of 10 proteins and 179 mutations, we predict both the magnitude and sign of the allosteric conformational equilibrium shift by the mutation; the impact of a large identifiable fraction of the mutations can be predicted with an average unsigned error of 1 kBT. With similar accuracy, we predict the mutation effects for an 11th protein that was omitted from the initial training and testing of the machine-learning algorithm. We also assess which calculated thermodynamic properties contribute most to the accuracy of the prediction. PMID:23228330
Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL): adapting the Partial Phylogenetic Profiling algorithm to scan sequences for signatures that predict protein function

PubMed Central

2010-01-01

Background Comparative genomics methods such as phylogenetic profiling can mine powerful inferences from inherently noisy biological data sets. We introduce Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL), a method that applies the Partial Phylogenetic Profiling (PPP) approach locally within a protein sequence to discover short sequence signatures associated with functional sites. The approach is based on the basic scoring mechanism employed by PPP, namely the use of binomial distribution statistics to optimize sequence similarity cutoffs during searches of partitioned training sets. Results Here we illustrate and validate the ability of the SIMBAL method to find functionally relevant short sequence signatures by application to two well-characterized protein families. In the first example, we partitioned a family of ABC permeases using a metabolic background property (urea utilization). Thus, the TRUE set for this family comprised members whose genome of origin encoded a urea utilization system. By moving a sliding window across the sequence of a permease, and searching each subsequence in turn against the full set of partitioned proteins, the method found which local sequence signatures best correlated with the urea utilization trait. Mapping of SIMBAL "hot spots" onto crystal structures of homologous permeases reveals that the significant sites are gating determinants on the cytosolic face rather than, say, docking sites for the substrate-binding protein on the extracellular face. In the second example, we partitioned a protein methyltransferase family using gene proximity as a criterion. In this case, the TRUE set comprised those methyltransferases encoded near the gene for the substrate RF-1. SIMBAL identifies sequence regions that map onto the substrate-binding interface while ignoring regions involved in the methyltransferase reaction mechanism in general. Neither method for training set construction requires any prior experimental characterization. Conclusions SIMBAL shows that, in functionally divergent protein families, selected short sequences often significantly outperform their full-length parent sequence for making functional predictions by sequence similarity, suggesting avenues for improved functional classifiers. When combined with structural data, SIMBAL affords the ability to localize and model functional sites. PMID:20102603
Isolation and characterization of major histocompatibility complex class IIB genes from the nurse shark.

PubMed

Bartl, S; Weissman, I L

1994-01-04

The major histocompatibility complex (MHC) contains a set of linked genes which encode cell surface proteins involved in the binding of small peptide antigens for their subsequent recognition by T lymphocytes. MHC proteins share structural features and the presence and location of polymorphic residues which play a role in the binding of antigens. In order to compare the structure of these molecules and gain insights into their evolution, we have isolated two MHC class IIB genes from the nurse shark, Ginglymostoma cirratum. Two clones, most probably alleles, encode proteins which differ by 13 amino acids located in the putative antigen-binding cleft. The protein structure and the location of polymorphic residues are similar to their mammalian counterparts. Although these genes appear to encode a typical MHC protein, no T-cell-mediated responses have been demonstrated in cartilaginous fish. The nurse shark represents the most phylogenetically primitive organism in which both class IIA [Kasahara, M., Vazquez, M., Sato, K., McKinney, E.C. & Flajnik, M.F. (1992) Proc. Natl. Acad. Sci USA 89, 6688-6692] and class IIB genes, presumably encoding the alpha/beta heterodimer, have been isolated.
Multi-omics Reveal Specific Targets of the RNA-Binding Protein Puf3p and Its Orchestration of Mitochondrial Biogenesis.

PubMed

Lapointe, Christopher P; Stefely, Jonathan A; Jochem, Adam; Hutchins, Paul D; Wilson, Gary M; Kwiecien, Nicholas W; Coon, Joshua J; Wickens, Marvin; Pagliarini, David J

2018-01-24

Coenzyme Q (CoQ) is a redox-active lipid required for mitochondrial oxidative phosphorylation (OxPhos). How CoQ biosynthesis is coordinated with the biogenesis of OxPhos protein complexes is unclear. Here, we show that the Saccharomyces cerevisiae RNA-binding protein (RBP) Puf3p regulates CoQ biosynthesis. To establish the mechanism for this regulation, we employed a multi-omic strategy to identify mRNAs that not only bind Puf3p but also are regulated by Puf3p in vivo. The CoQ biosynthesis enzyme Coq5p is a critical Puf3p target: Puf3p regulates the abundance of Coq5p and prevents its detrimental hyperaccumulation, thereby enabling efficient CoQ production. More broadly, Puf3p represses a specific set of proteins involved in mitochondrial protein import, translation, and OxPhos complex assembly (pathways essential to prime mitochondrial biogenesis). Our data reveal a mechanism for post-transcriptionally coordinating CoQ production with OxPhos biogenesis, and they demonstrate the power of multi-omics for defining genuine targets of RBPs. Copyright © 2017 Elsevier Inc. All rights reserved.
Finding Inspiration in the Protein Data Bank to Chemically Antagonize Readers of the Histone Code.

PubMed

Campagna-Slater, Valérie; Schapira, Matthieu

2010-04-12

Members of the Royal family of proteins are readers of the histone code that contain aromatic cages capable of recognizing specific sequences and lysine methylation states on histone tails. These binding modules play a key role in epigenetic signalling, and are part of a larger group of epigenetic targets that are becoming increasingly attractive for drug discovery. In the current study, pharmacophore representations of the aromatic cages forming the methyl-lysine (Me-Lys) recognition site were used to search the Protein Data Bank (PDB) for ligand binding pockets possessing similar chemical and geometrical features in unrelated proteins. The small molecules bound to these sites were then extracted from the PDB, and clustered based on fragments binding to the aromatic cages. The compounds collected are numerous and structurally diverse, but point to a limited set of preferred chemotypes; these include quaternary ammonium, sulfonium, and primary, secondary and tertiary amine moieties, as well as aromatic, aliphatic or orthogonal rings, and bicyclic systems. The chemical tool-kit identified can be used to design antagonists of the Royal family and related proteins. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
The sterol-binding activity of PATHOGENESIS-RELATED PROTEIN 1 reveals the mode of action of an antimicrobial protein.

PubMed

Gamir, Jordi; Darwiche, Rabih; Van't Hof, Pieter; Choudhary, Vineet; Stumpe, Michael; Schneiter, Roger; Mauch, Felix

2017-02-01

Pathogenesis-related proteins played a pioneering role 50 years ago in the discovery of plant innate immunity as a set of proteins that accumulated upon pathogen challenge. The most abundant of these proteins, PATHOGENESIS-RELATED 1 (PR-1) encodes a small antimicrobial protein that has become, as a marker of plant immune signaling, one of the most referred to plant proteins. The biochemical activity and mode of action of PR-1 proteins has remained elusive, however. Here, we provide genetic and biochemical evidence for the capacity of PR-1 proteins to bind sterols, and demonstrate that the inhibitory effect on pathogen growth is caused by the sequestration of sterol from pathogens. In support of our findings, sterol-auxotroph pathogens such as the oomycete Phytophthora are particularly sensitive to PR-1, whereas sterol-prototroph fungal pathogens become highly sensitive only when sterol biosynthesis is compromised. Our results are in line with previous findings showing that plants with enhanced PR-1 expression are particularly well protected against oomycete pathogens. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

A dominant role for the methyl-CpG-binding protein Mbd2 in controlling Th2 induction by dendritic cells.

PubMed

Cook, Peter C; Owen, Heather; Deaton, Aimée M; Borger, Jessica G; Brown, Sheila L; Clouaire, Thomas; Jones, Gareth-Rhys; Jones, Lucy H; Lundie, Rachel J; Marley, Angela K; Morrison, Vicky L; Phythian-Adams, Alexander T; Wachter, Elisabeth; Webb, Lauren M; Sutherland, Tara E; Thomas, Graham D; Grainger, John R; Selfridge, Jim; McKenzie, Andrew N J; Allen, Judith E; Fagerholm, Susanna C; Maizels, Rick M; Ivens, Alasdair C; Bird, Adrian; MacDonald, Andrew S

2015-04-24

Dendritic cells (DCs) direct CD4(+) T-cell differentiation into diverse helper (Th) subsets that are required for protection against varied infections. However, the mechanisms used by DCs to promote Th2 responses, which are important both for immunity to helminth infection and in allergic disease, are currently poorly understood. We demonstrate a key role for the protein methyl-CpG-binding domain-2 (Mbd2), which links DNA methylation to repressive chromatin structure, in regulating expression of a range of genes that are associated with optimal DC activation and function. In the absence of Mbd2, DCs display reduced phenotypic activation and a markedly impaired capacity to initiate Th2 immunity against helminths or allergens. These data identify an epigenetic mechanism that is central to the activation of CD4(+) T-cell responses by DCs, particularly in Th2 settings, and reveal methyl-CpG-binding proteins and the genes under their control as possible therapeutic targets for type-2 inflammation.
Identification of Phosphorylation Codes for Arrestin Recruitment by G Protein-Coupled Receptors.

PubMed

Zhou, X Edward; He, Yuanzheng; de Waal, Parker W; Gao, Xiang; Kang, Yanyong; Van Eps, Ned; Yin, Yanting; Pal, Kuntal; Goswami, Devrishi; White, Thomas A; Barty, Anton; Latorraca, Naomi R; Chapman, Henry N; Hubbell, Wayne L; Dror, Ron O; Stevens, Raymond C; Cherezov, Vadim; Gurevich, Vsevolod V; Griffin, Patrick R; Ernst, Oliver P; Melcher, Karsten; Xu, H Eric

2017-07-27

G protein-coupled receptors (GPCRs) mediate diverse signaling in part through interaction with arrestins, whose binding promotes receptor internalization and signaling through G protein-independent pathways. High-affinity arrestin binding requires receptor phosphorylation, often at the receptor's C-terminal tail. Here, we report an X-ray free electron laser (XFEL) crystal structure of the rhodopsin-arrestin complex, in which the phosphorylated C terminus of rhodopsin forms an extended intermolecular β sheet with the N-terminal β strands of arrestin. Phosphorylation was detected at rhodopsin C-terminal tail residues T336 and S338. These two phospho-residues, together with E341, form an extensive network of electrostatic interactions with three positively charged pockets in arrestin in a mode that resembles binding of the phosphorylated vasopressin-2 receptor tail to β-arrestin-1. Based on these observations, we derived and validated a set of phosphorylation codes that serve as a common mechanism for phosphorylation-dependent recruitment of arrestins by GPCRs. Copyright © 2017 Elsevier Inc. All rights reserved.
Sequence, Structure, and Context Preferences of Human RNA Binding Proteins.

PubMed

Dominguez, Daniel; Freese, Peter; Alexis, Maria S; Su, Amanda; Hochman, Myles; Palden, Tsultrim; Bazile, Cassandra; Lambert, Nicole J; Van Nostrand, Eric L; Pratt, Gabriel A; Yeo, Gene W; Graveley, Brenton R; Burge, Christopher B

2018-06-07

RNA binding proteins (RBPs) orchestrate the production, processing, and function of mRNAs. Here, we present the affinity landscapes of 78 human RBPs using an unbiased assay that determines the sequence, structure, and context preferences of these proteins in vitro by deep sequencing of bound RNAs. These data enable construction of "RNA maps" of RBP activity without requiring crosslinking-based assays. We found an unexpectedly low diversity of RNA motifs, implying frequent convergence of binding specificity toward a relatively small set of RNA motifs, many with low compositional complexity. Offsetting this trend, however, we observed extensive preferences for contextual features distinct from short linear RNA motifs, including spaced "bipartite" motifs, biased flanking nucleotide composition, and bias away from or toward RNA structure. Our results emphasize the importance of contextual features in RNA recognition, which likely enable targeting of distinct subsets of transcripts by different RBPs that recognize the same linear motif. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
A Global Map of Lipid-Binding Proteins and Their Ligandability in Cells.

PubMed

Niphakis, Micah J; Lum, Kenneth M; Cognetta, Armand B; Correia, Bruno E; Ichu, Taka-Aki; Olucha, Jose; Brown, Steven J; Kundu, Soumajit; Piscitelli, Fabiana; Rosen, Hugh; Cravatt, Benjamin F

2015-06-18

Lipids play central roles in physiology and disease, where their structural, metabolic, and signaling functions often arise from interactions with proteins. Here, we describe a set of lipid-based chemical proteomic probes and their global interaction map in mammalian cells. These interactions involve hundreds of proteins from diverse functional classes and frequently occur at sites of drug action. We determine the target profiles for several drugs across the lipid-interaction proteome, revealing that its ligandable content extends far beyond traditionally defined categories of druggable proteins. In further support of this finding, we describe a selective ligand for the lipid-binding protein nucleobindin-1 (NUCB1) and show that this compound perturbs the hydrolytic and oxidative metabolism of endocannabinoids in cells. The described chemical proteomic platform thus provides an integrated path to both discover and pharmacologically characterize a wide range of proteins that participate in lipid pathways in cells. Copyright © 2015 Elsevier Inc. All rights reserved.
Sequence and structure insights of kazal type thrombin inhibitor protein: Studied with phylogeny, homology modeling and dynamic MM/GBSA studies.

PubMed

Jadhav, Aparna; Dash, RadhaCharan; Hirwani, Raj; Abdin, Malik

2018-03-01

Despite the wide medical importance of serine protease inhibitors, many of kazal type proteins are still to be explored. These thrombin inhibiting proteins are found in the digestive system of hematophagous organisms mainly Arthropods. We studied one of such protein i.e. Kazal type-1 protein from sand-fly Phlebotomus papatasi as its structure and interaction with thrombin is unclear. Initially, Dipetalin a kazal-follistasin domain protein was run through PSI-BLAST to retrieve related sequences. Using this set of sequence a phylogenetic tree was constructed, which identified a distantly related kazal type-1 protein. A three-dimensional structure was predicted for this protein and was aligned with Rhodniin for further evaluation. To have a comparative understanding of it's binding at the thrombin active site, the aligned kazal model-thrombin and rhodniin-thrombin complexes were subjected to molecular dynamics simulations. Dynamics analysis with reference to main chain RMSD, H-chain residue RMSF and total energy showed rhodniin-thrombin complex as a more stable system. Further, the MM/GBSA method was applied that calculated the binding free energy (ΔG binding ) for rhodniin and kazal model as -220.32kcal/Mol and -90.70kcal/Mol, respectively. Thus, it shows that kazal model has weaker bonding with thrombin, unlike rhodniin. Copyright © 2017 Elsevier B.V. All rights reserved.
Brain tumor is a sequence-specific RNA-binding protein that directs maternal mRNA clearance during the Drosophila maternal-to-zygotic transition.

PubMed

Laver, John D; Li, Xiao; Ray, Debashish; Cook, Kate B; Hahn, Noah A; Nabeel-Shah, Syed; Kekis, Mariana; Luo, Hua; Marsolais, Alexander J; Fung, Karen Yy; Hughes, Timothy R; Westwood, J Timothy; Sidhu, Sachdev S; Morris, Quaid; Lipshitz, Howard D; Smibert, Craig A

2015-05-12

Brain tumor (BRAT) is a Drosophila member of the TRIM-NHL protein family. This family is conserved among metazoans and its members function as post-transcriptional regulators. BRAT was thought to be recruited to mRNAs indirectly through interaction with the RNA-binding protein Pumilio (PUM). However, it has recently been demonstrated that BRAT directly binds to RNA. The precise sequence recognized by BRAT, the extent of BRAT-mediated regulation, and the exact roles of PUM and BRAT in post-transcriptional regulation are unknown. Genome-wide identification of transcripts associated with BRAT or with PUM in Drosophila embryos shows that they bind largely non-overlapping sets of mRNAs. BRAT binds mRNAs that encode proteins associated with a variety of functions, many of which are distinct from those implemented by PUM-associated transcripts. Computational analysis of in vitro and in vivo data identified a novel RNA motif recognized by BRAT that confers BRAT-mediated regulation in tissue culture cells. The regulatory status of BRAT-associated mRNAs suggests a prominent role for BRAT in post-transcriptional regulation, including a previously unidentified role in transcript degradation. Transcriptomic analysis of embryos lacking functional BRAT reveals an important role in mediating the decay of hundreds of maternal mRNAs during the maternal-to-zygotic transition. Our results represent the first genome-wide analysis of the mRNAs associated with a TRIM-NHL protein and the first identification of an RNA motif bound by this protein family. BRAT is a prominent post-transcriptional regulator in the early embryo through mechanisms that are largely independent of PUM.
Target Highlights in CASP9: Experimental Target Structures for the Critical Assessment of Techniques for Protein Structure Prediction

PubMed Central

Kryshtafovych, Andriy; Moult, John; Bartual, Sergio G.; Bazan, J. Fernando; Berman, Helen; Casteel, Darren E.; Christodoulou, Evangelos; Everett, John K.; Hausmann, Jens; Heidebrecht, Tatjana; Hills, Tanya; Hui, Raymond; Hunt, John F.; Jayaraman, Seetharaman; Joachimiak, Andrzej; Kennedy, Michael A.; Kim, Choel; Lingel, Andreas; Michalska, Karolina; Montelione, Gaetano T.; Otero, José M.; Perrakis, Anastassis; Pizarro, Juan C.; van Raaij, Mark J.; Ramelot, Theresa A.; Rousseau, Francois; Tong, Liang; Wernimont, Amy K.; Young, Jasmine; Schwede, Torsten

2011-01-01

One goal of the CASP Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction is to identify the current state of the art in protein structure prediction and modeling. A fundamental principle of CASP is blind prediction on a set of relevant protein targets, i.e. the participating computational methods are tested on a common set of experimental target proteins, for which the experimental structures are not known at the time of modeling. Therefore, the CASP experiment would not have been possible without broad support of the experimental protein structural biology community. In this manuscript, several experimental groups discuss the structures of the proteins which they provided as prediction targets for CASP9, highlighting structural and functional peculiarities of these structures: the long tail fibre protein gp37 from bacteriophage T4, the cyclic GMP-dependent protein kinase Iβ (PKGIβ) dimerization/docking domain, the ectodomain of the JTB (Jumping Translocation Breakpoint) transmembrane receptor, Autotaxin (ATX) in complex with an inhibitor, the DNA-Binding J-Binding Protein 1 (JBP1) domain essential for biosynthesis and maintenance of DNA base-J (β-D-glucosyl-hydroxymethyluracil) in Trypanosoma and Leishmania, an so far uncharacterized 73 residue domain from Ruminococcus gnavus with a fold typical for PDZ-like domains, a domain from the Phycobilisome (PBS) core-membrane linker (LCM) phycobiliprotein ApcE from Synechocystis, the Heat shock protein 90 (Hsp90) activators PFC0360w and PFC0270w from Plasmodium falciparum, and 2-oxo-3-deoxygalactonate kinase from Klebsiella pneumoniae. PMID:22020785
A Role for Weak Electrostatic Interactions in Peripheral Membrane Protein Binding

PubMed Central

Khan, Hanif M.; He, Tao; Fuglebakk, Edvin; Grauffel, Cédric; Yang, Boqian; Roberts, Mary F.; Gershenson, Anne; Reuter, Nathalie

2016-01-01

Bacillus thuringiensis phosphatidylinositol-specific phospholipase C (BtPI-PLC) is a secreted virulence factor that binds specifically to phosphatidylcholine (PC) bilayers containing negatively charged phospholipids. BtPI-PLC carries a negative net charge and its interfacial binding site has no obvious cluster of basic residues. Continuum electrostatic calculations show that, as expected, nonspecific electrostatic interactions between BtPI-PLC and membranes vary as a function of the fraction of anionic lipids present in the bilayers. Yet they are strikingly weak, with a calculated ΔGel below 1 kcal/mol, largely due to a single lysine (K44). When K44 is mutated to alanine, the equilibrium dissociation constant for small unilamellar vesicles increases more than 50 times (∼2.4 kcal/mol), suggesting that interactions between K44 and lipids are not merely electrostatic. Comparisons of molecular-dynamics simulations performed using different lipid compositions reveal that the bilayer composition does not affect either hydrogen bonds or hydrophobic contacts between the protein interfacial binding site and bilayers. However, the occupancies of cation-π interactions between PC choline headgroups and protein tyrosines vary as a function of PC content. The overall contribution of basic residues to binding affinity is also context dependent and cannot be approximated by a rule-of-thumb value because these residues can contribute to both nonspecific electrostatic and short-range protein-lipid interactions. Additionally, statistics on the distribution of basic amino acids in a data set of membrane-binding domains reveal that weak electrostatics, as observed for BtPI-PLC, might be a less unusual mechanism for peripheral membrane binding than is generally thought. PMID:27028646
Crystallization and preliminary X-ray diffraction analysis of the Bacillus subtilis replication termination protein in complex with the 37-base-pair TerI-binding site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vivian, J. P.; Porter, C.; Wilce, J. A.

2006-11-01

A preparation of replication terminator protein (RTP) of B. subtilis and a 37-base-pair TerI sequence (comprising two binding sites for RTP) has been purified and crystallized. The replication terminator protein (RTP) of Bacillus subtilis binds to specific DNA sequences that halt the progression of the replisome in a polar manner. These terminator complexes flank a defined region of the chromosome into which they allow replication forks to enter but not exit. Forcing the fusion of replication forks in a specific zone is thought to allow the coordination of post-replicative processes. The functional terminator complex comprises two homodimers each of 29more » kDa bound to overlapping binding sites. A preparation of RTP and a 37-base-pair TerI sequence (comprising two binding sites for RTP) has been purified and crystallized. A data set to 3.9 Å resolution with 97.0% completeness and an R{sub sym} of 12% was collected from a single flash-cooled crystal using synchrotron radiation. The diffraction data are consistent with space group P622, with unit-cell parameters a = b = 118.8, c = 142.6 Å.« less
Crystal Structure of Mycobacterium tuberculosis H37Rv AldR (Rv2779c), a Regulator of the ald Gene

PubMed Central

Dey, Abhishek; Shree, Sonal; Pandey, Sarvesh Kumar; Tripathi, Rama Pati; Ramachandran, Ravishankar

2016-01-01

Here we report the crystal structure of M. tuberculosis AldR (Rv2779c) showing that the N-terminal DNA-binding domains are swapped, forming a dimer, and four dimers are assembled into an octamer through crystal symmetry. The C-terminal domain is involved in oligomeric interactions that stabilize the oligomer, and it contains the effector-binding sites. The latter sites are 30–60% larger compared with homologs like MtbFFRP (Rv3291c) and can consequently accommodate larger molecules. MtbAldR binds to the region upstream to the ald gene that is highly up-regulated in nutrient-starved tuberculosis models and codes for l-alanine dehydrogenase (MtbAld; Rv2780). Further, the MtbAldR-DNA complex is inhibited upon binding of Ala, Tyr, Trp and Asp to the protein. Studies involving a ligand-binding site G131T mutant show that the mutant forms a DNA complex that cannot be inhibited by adding the amino acids. Comparative studies suggest that binding of the amino acids changes the relative spatial disposition of the DNA-binding domains and thereby disrupt the protein-DNA complex. Finally, we identified small molecules, including a tetrahydroquinoline carbonitrile derivative (S010-0261), that inhibit the MtbAldR-DNA complex. The latter molecules represent the very first inhibitors of a feast/famine regulatory protein from any source and set the stage for exploring MtbAldR as a potential anti-tuberculosis target. PMID:27006398
The zinc fingers of the Small Optic Lobes (SOL) calpain bind polyubiquitin.

PubMed

Hastings, Margaret H; Qiu, Alvin; Zha, Congyao; Farah, Carole A; Mahdid, Yacine; Ferguson, Larissa; Sossin, Wayne S

2018-05-28

The Small Optic Lobes (SOL) calpain is a highly conserved member of the calpain family expressed in the nervous system. A dominant negative form of the SOL calpain inhibited consolidation of one form of synaptic plasticity, non-associative facilitation, in sensory-motor neuronal cultures in Aplysia, presumably by inhibiting cleavage of protein kinase Cs (PKCs) into constitutively active protein kinase Ms (PKMs) (Hu et al, 2017a). SOL calpains have a conserved set of 5-6 N-terminal zinc fingers. Bioinformatic analysis suggests that these zinc fingers could bind to ubiquitin. In this study, we show that both the Aplysia and mouse SOL calpain (also known as Calpain 15) zinc fingers bind ubiquitinated proteins, and we confirm that Aplysia SOL binds poly- but not mono or di-ubiquitin. No specific zinc finger is required for polyubiquitin binding. Neither polyubiquitin nor calcium was sufficient to induce purified Aplysia SOL calpain to autolyse or to cleave the atypical PKC to PKM in vitro. In Aplysia, overexpression of the atypical PKC in sensory neurons leads to an activity-dependent cleavage event and an increase in nuclear ubiquitin staining. Activity-dependent cleavage is partially blocked by a dominant negative SOL calpain, but not by a dominant negative classical calpain. The cleaved PKM was stabilized by the dominant negative classical calpain and destabilized by a dominant negative form of the PKM stabilizing proteinKIdney/BRAin protein(KIBRA). These studies provide new insight into SOL calpain's function and regulation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Carbon-Binding Designer Proteins that Discriminate between sp2- and sp3-Hybridized Carbon Surfaces

PubMed Central

Coyle, Brandon L.; Rolandi, Marco; Baneyx, François

2013-01-01

Robust and simple strategies to directly functionalize graphene- and diamond-based nanostructures with proteins are of considerable interest for biologically driven manufacturing, biosensing and bioimaging. Here, we identify a new set of carbon binding peptides that vary in overall hydrophobicity and charge, and engineer two of these sequences (Car9 and Car15) within the framework of E. coli Thioredoxin 1 (TrxA). We develop purification schemes to recover the resulting TrxA derivatives in a soluble form and conduct a detailed analysis of the mechanisms that underpin the interaction of the fusion proteins with carbonaceous surfaces. Although equilibrium quartz crystal microbalance measurements show that TrxA∷Car9 and TrxA∷Car15 have similar affinity for sp2-hybridized graphitic carbon (Kd = 50 and 90 nM, respectively), only the latter protein is capable of dispersing carbon nanotubes. Further investigation by surface plasmon resonance and atomic force microscopy reveals that TrxA∷Car15 interacts with sp2-bonded carbon through a combination of hydrophobic and π-π interactions but that TrxA∷Car9 exhibits a cooperative mode of binding which relies on a combination of electrostatics and weaker π-stacking. Consequently, we find that TrxA∷Car9 binds equally well to sp2- and sp3-bonded (diamond-like) carbon particles, while TrxA∷Car15 is capable of discriminating between the two carbon allotropes. Our results emphasize the importance of understanding both bulk and molecular recognition events when exploiting the adhesive properties of solid-binding peptides and proteins in technological applications. PMID:23510486
Structural analyses of the CRISPR protein Csc2 reveal the RNA-binding interface of the type I-D Cas7 family.

PubMed

Hrle, Ajla; Maier, Lisa-Katharina; Sharma, Kundan; Ebert, Judith; Basquin, Claire; Urlaub, Henning; Marchfelder, Anita; Conti, Elena

2014-01-01

Upon pathogen invasion, bacteria and archaea activate an RNA-interference-like mechanism termed CRISPR (clustered regularly interspaced short palindromic repeats). A large family of Cas (CRISPR-associated) proteins mediates the different stages of this sophisticated immune response. Bioinformatic studies have classified the Cas proteins into families, according to their sequences and respective functions. These range from the insertion of the foreign genetic elements into the host genome to the activation of the interference machinery as well as target degradation upon attack. Cas7 family proteins are central to the type I and type III interference machineries as they constitute the backbone of the large interference complexes. Here we report the crystal structure of Thermofilum pendens Csc2, a Cas7 family protein of type I-D. We found that Csc2 forms a core RRM-like domain, flanked by three peripheral insertion domains: a lid domain, a Zinc-binding domain and a helical domain. Comparison with other Cas7 family proteins reveals a set of similar structural features both in the core and in the peripheral domains, despite the absence of significant sequence similarity. T. pendens Csc2 binds single-stranded RNA in vitro in a sequence-independent manner. Using a crosslinking - mass-spectrometry approach, we mapped the RNA-binding surface to a positively charged surface patch on T. pendens Csc2. Thus our analysis of the key structural and functional features of T. pendens Csc2 highlights recurring themes and evolutionary relationships in type I and type III Cas proteins.
Characterization of UO2(2+) binding to osteopontin, a highly phosphorylated protein: insights into potential mechanisms of uranyl accumulation in bones.

PubMed

Qi, Lei; Basset, Christian; Averseng, Olivier; Quéméneur, Eric; Hagège, Agnès; Vidaud, Claude

2014-01-01

Bones are one of the few organs in which uranyl (UO2(2+)) accumulates. This large dioxo-cation displays affinity for carboxylates, phenolates and phosphorylated functional groups in proteins. The noncollagenous protein osteopontin (OPN) plays an important role in bone homeostasis. It is mainly found in the extracellular matrix of mineralized tissues but also in body fluids such as milk, blood and urine. Furthermore, OPN is an intrinsically disordered protein, which, like other proteins of the SIBLING family, contains a polyaspartic acid sequence and numerous patterns of alternating acidic and phosphorylated residues. All these properties led to the hypothesis that this protein could be prone to UO2(2+) binding. In this work, a simple purification procedure enabling highly purified bovine (bOPN) and human OPN (hOPN) to be obtained was developed. Various biophysical approaches were set up to study the impact of phosphorylations on the affinity of OPN for UO2(2+) as well as the formation of stable complexes originating from structural changes induced by the binding of this metal cation. The results obtained suggest a new mechanism of the interaction of UO2(2+) with bone metabolism and a new role for OPN as a metal transporter.
Arpeggio: harmonic compression of ChIP-seq data reveals protein-chromatin interaction signatures.

PubMed

Stanton, Kelly Patrick; Parisi, Fabio; Strino, Francesco; Rabin, Neta; Asp, Patrik; Kluger, Yuval

2013-09-01

Researchers generating new genome-wide data in an exploratory sequencing study can gain biological insights by comparing their data with well-annotated data sets possessing similar genomic patterns. Data compression techniques are needed for efficient comparisons of a new genomic experiment with large repositories of publicly available profiles. Furthermore, data representations that allow comparisons of genomic signals from different platforms and across species enhance our ability to leverage these large repositories. Here, we present a signal processing approach that characterizes protein-chromatin interaction patterns at length scales of several kilobases. This allows us to efficiently compare numerous chromatin-immunoprecipitation sequencing (ChIP-seq) data sets consisting of many types of DNA-binding proteins collected from a variety of cells, conditions and organisms. Importantly, these interaction patterns broadly reflect the biological properties of the binding events. To generate these profiles, termed Arpeggio profiles, we applied harmonic deconvolution techniques to the autocorrelation profiles of the ChIP-seq signals. We used 806 publicly available ChIP-seq experiments and showed that Arpeggio profiles with similar spectral densities shared biological properties. Arpeggio profiles of ChIP-seq data sets revealed characteristics that are not easily detected by standard peak finders. They also allowed us to relate sequencing data sets from different genomes, experimental platforms and protocols. Arpeggio is freely available at http://sourceforge.net/p/arpeggio/wiki/Home/.
A comparison of successful and failed protein interface designs highlights the challenges of designing buried hydrogen bonds.

PubMed

Stranges, P Benjamin; Kuhlman, Brian

2013-01-01

The accurate design of new protein-protein interactions is a longstanding goal of computational protein design. However, most computationally designed interfaces fail to form experimentally. This investigation compares five previously described successful de novo interface designs with 158 failures. Both sets of proteins were designed with the molecular modeling program Rosetta. Designs were considered a success if a high-resolution crystal structure of the complex closely matched the design model and the equilibrium dissociation constant for binding was less than 10 μM. The successes and failures represent a wide variety of interface types and design goals including heterodimers, homodimers, peptide-protein interactions, one-sided designs (i.e., where only one of the proteins was mutated) and two-sided designs. The most striking feature of the successful designs is that they have fewer polar atoms at their interfaces than many of the failed designs. Designs that attempted to create extensive sets of interface-spanning hydrogen bonds resulted in no detectable binding. In contrast, polar atoms make up more than 40% of the interface area of many natural dimers, and native interfaces often contain extensive hydrogen bonding networks. These results suggest that Rosetta may not be accurately balancing hydrogen bonding and electrostatic energies against desolvation penalties and that design processes may not include sufficient sampling to identify side chains in preordered conformations that can fully satisfy the hydrogen bonding potential of the interface. Copyright © 2012 The Protein Society.
Recommendations for evaluation of computational methods

NASA Astrophysics Data System (ADS)

Jain, Ajay N.; Nicholls, Anthony

2008-03-01

The field of computational chemistry, particularly as applied to drug design, has become increasingly important in terms of the practical application of predictive modeling to pharmaceutical research and development. Tools for exploiting protein structures or sets of ligands known to bind particular targets can be used for binding-mode prediction, virtual screening, and prediction of activity. A serious weakness within the field is a lack of standards with respect to quantitative evaluation of methods, data set preparation, and data set sharing. Our goal should be to report new methods or comparative evaluations of methods in a manner that supports decision making for practical applications. Here we propose a modest beginning, with recommendations for requirements on statistical reporting, requirements for data sharing, and best practices for benchmark preparation and usage.
Crystal Structure of Mycobacterium tuberculosis H37Rv AldR (Rv2779c), a Regulator of the ald Gene: DNA BINDING AND IDENTIFICATION OF SMALL MOLECULE INHIBITORS.

PubMed

Dey, Abhishek; Shree, Sonal; Pandey, Sarvesh Kumar; Tripathi, Rama Pati; Ramachandran, Ravishankar

2016-06-03

Here we report the crystal structure of M. tuberculosis AldR (Rv2779c) showing that the N-terminal DNA-binding domains are swapped, forming a dimer, and four dimers are assembled into an octamer through crystal symmetry. The C-terminal domain is involved in oligomeric interactions that stabilize the oligomer, and it contains the effector-binding sites. The latter sites are 30-60% larger compared with homologs like MtbFFRP (Rv3291c) and can consequently accommodate larger molecules. MtbAldR binds to the region upstream to the ald gene that is highly up-regulated in nutrient-starved tuberculosis models and codes for l-alanine dehydrogenase (MtbAld; Rv2780). Further, the MtbAldR-DNA complex is inhibited upon binding of Ala, Tyr, Trp and Asp to the protein. Studies involving a ligand-binding site G131T mutant show that the mutant forms a DNA complex that cannot be inhibited by adding the amino acids. Comparative studies suggest that binding of the amino acids changes the relative spatial disposition of the DNA-binding domains and thereby disrupt the protein-DNA complex. Finally, we identified small molecules, including a tetrahydroquinoline carbonitrile derivative (S010-0261), that inhibit the MtbAldR-DNA complex. The latter molecules represent the very first inhibitors of a feast/famine regulatory protein from any source and set the stage for exploring MtbAldR as a potential anti-tuberculosis target. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding.

PubMed

Ma, Wenxiu; Yang, Lin; Rohs, Remo; Noble, William Stafford

2017-10-01

Transcription factors (TFs) bind to specific DNA sequence motifs. Several lines of evidence suggest that TF-DNA binding is mediated in part by properties of the local DNA shape: the width of the minor groove, the relative orientations of adjacent base pairs, etc. Several methods have been developed to jointly account for DNA sequence and shape properties in predicting TF binding affinity. However, a limitation of these methods is that they typically require a training set of aligned TF binding sites. We describe a sequence + shape kernel that leverages DNA sequence and shape information to better understand protein-DNA binding preference and affinity. This kernel extends an existing class of k-mer based sequence kernels, based on the recently described di-mismatch kernel. Using three in vitro benchmark datasets, derived from universal protein binding microarrays (uPBMs), genomic context PBMs (gcPBMs) and SELEX-seq data, we demonstrate that incorporating DNA shape information improves our ability to predict protein-DNA binding affinity. In particular, we observe that (i) the k-spectrum + shape model performs better than the classical k-spectrum kernel, particularly for small k values; (ii) the di-mismatch kernel performs better than the k-mer kernel, for larger k; and (iii) the di-mismatch + shape kernel performs better than the di-mismatch kernel for intermediate k values. The software is available at https://bitbucket.org/wenxiu/sequence-shape.git. rohs@usc.edu or william-noble@uw.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
SP transcription factor paralogs and DNA-binding sites coevolve and adaptively converge in mammals and birds.

PubMed

Yokoyama, Ken Daigoro; Pollock, David D

2012-01-01

Functional modification of regulatory proteins can affect hundreds of genes throughout the genome, and is therefore thought to be almost universally deleterious. This belief, however, has recently been challenged. A potential example comes from transcription factor SP1, for which statistical evidence indicates that motif preferences were altered in eutherian mammals. Here, we set out to discover possible structural and theoretical explanations, evaluate the role of selection in SP1 evolution, and discover effects on coregulatory proteins. We show that SP1 motif preferences were convergently altered in birds as well as mammals, inducing coevolutionary changes in over 800 regulatory regions. Structural and phylogenic evidence implicates a single causative amino acid replacement at the same SP1 position along both lineages. Furthermore, paralogs SP3 and SP4, which coregulate SP1 target genes through competitive binding to the same sites, have accumulated convergent replacements at the homologous position multiple times during eutherian and bird evolution, presumably to preserve competitive binding. To determine plausibility, we developed and implemented a simple model of transcription factor and binding site coevolution. This model predicts that, in contrast to prevailing beliefs, even small selective benefits per locus can drive concurrent fixation of transcription factor and binding site mutants under a broad range of conditions. Novel binding sites tend to arise de novo, rather than by mutation from ancestral sites, a prediction substantiated by SP1-binding site alignments. Thus, multiple lines of evidence indicate that selection has driven convergent evolution of transcription factors along with their binding sites and coregulatory proteins.

SP Transcription Factor Paralogs and DNA-Binding Sites Coevolve and Adaptively Converge in Mammals and Birds

PubMed Central

Yokoyama, Ken Daigoro; Pollock, David D.

2012-01-01

Functional modification of regulatory proteins can affect hundreds of genes throughout the genome, and is therefore thought to be almost universally deleterious. This belief, however, has recently been challenged. A potential example comes from transcription factor SP1, for which statistical evidence indicates that motif preferences were altered in eutherian mammals. Here, we set out to discover possible structural and theoretical explanations, evaluate the role of selection in SP1 evolution, and discover effects on coregulatory proteins. We show that SP1 motif preferences were convergently altered in birds as well as mammals, inducing coevolutionary changes in over 800 regulatory regions. Structural and phylogenic evidence implicates a single causative amino acid replacement at the same SP1 position along both lineages. Furthermore, paralogs SP3 and SP4, which coregulate SP1 target genes through competitive binding to the same sites, have accumulated convergent replacements at the homologous position multiple times during eutherian and bird evolution, presumably to preserve competitive binding. To determine plausibility, we developed and implemented a simple model of transcription factor and binding site coevolution. This model predicts that, in contrast to prevailing beliefs, even small selective benefits per locus can drive concurrent fixation of transcription factor and binding site mutants under a broad range of conditions. Novel binding sites tend to arise de novo, rather than by mutation from ancestral sites, a prediction substantiated by SP1-binding site alignments. Thus, multiple lines of evidence indicate that selection has driven convergent evolution of transcription factors along with their binding sites and coregulatory proteins. PMID:23019068
Novel Computational Approaches to Drug Discovery

NASA Astrophysics Data System (ADS)

Skolnick, Jeffrey; Brylinski, Michal

2010-01-01

New approaches to protein functional inference based on protein structure and evolution are described. First, FINDSITE, a threading based approach to protein function prediction, is summarized. Then, the results of large scale benchmarking of ligand binding site prediction, ligand screening, including applications to HIV protease, and GO molecular functional inference are presented. A key advantage of FINDSITE is its ability to use low resolution, predicted structures as well as high resolution experimental structures. Then, an extension of FINDSITE to ligand screening in GPCRs using predicted GPCR structures, FINDSITE/QDOCKX, is presented. This is a particularly difficult case as there are few experimentally solved GPCR structures. Thus, we first train on a subset of known binding ligands for a set of GPCRs; this is then followed by benchmarking against a large ligand library. For the virtual ligand screening of a number of Dopamine receptors, encouraging results are seen, with significant enrichment in identified ligands over those found in the training set. Thus, FINDSITE and its extensions represent a powerful approach to the successful prediction of a variety of molecular functions.
DBAC: A simple prediction method for protein binding hot spots based on burial levels and deeply buried atomic contacts

PubMed Central

2011-01-01

Background A protein binding hot spot is a cluster of residues in the interface that are energetically important for the binding of the protein with its interaction partner. Identifying protein binding hot spots can give useful information to protein engineering and drug design, and can also deepen our understanding of protein-protein interaction. These residues are usually buried inside the interface with very low solvent accessible surface area (SASA). Thus SASA is widely used as an outstanding feature in hot spot prediction by many computational methods. However, SASA is not capable of distinguishing slightly buried residues, of which most are non hot spots, and deeply buried ones that are usually inside a hot spot. Results We propose a new descriptor called “burial level” for characterizing residues, atoms and atomic contacts. Specifically, burial level captures the depth the residues are buried. We identify different kinds of deeply buried atomic contacts (DBAC) at different burial levels that are directly broken in alanine substitution. We use their numbers as input for SVM to classify between hot spot or non hot spot residues. We achieve F measure of 0.6237 under the leave-one-out cross-validation on a data set containing 258 mutations. This performance is better than other computational methods. Conclusions Our results show that hot spot residues tend to be deeply buried in the interface, not just having a low SASA value. This indicates that a high burial level is not only a necessary but also a more sufficient condition than a low SASA for a residue to be a hot spot residue. We find that those deeply buried atoms become increasingly more important when their burial levels rise up. This work also confirms the contribution of deeply buried interfacial atomic contacts to the energy of protein binding hot spot. PMID:21689480
DOCLASP - Docking ligands to target proteins using spatial and electrostatic congruence extracted from a known holoenzyme and applying simple geometrical transformations.

PubMed

Chakraborty, Sandeep

2014-01-01

The ability to accurately and effectively predict the interaction between proteins and small drug-like compounds has long intrigued researchers for pedagogic, humanitarian and economic reasons. Protein docking methods (AutoDock, GOLD, DOCK, FlexX and Glide to name a few) rank a large number of possible conformations of protein-ligand complexes using fast algorithms. Previously, it has been shown that structural congruence leading to the same enzymatic function necessitates the congruence of electrostatic properties (CLASP). The current work presents a methodology for docking a ligand into a target protein, provided that there is at least one known holoenzyme with ligand bound - DOCLASP (Docking using CLASP). The contact points of the ligand in the holoenzyme defines a motif, which is used to query the target enzyme using CLASP. If there are significant matches, the holoenzyme and the target protein are superimposed based on congruent atoms. The same linear and rotational transformations are also applied to the ligand, thus creating a unified coordinate framework having the holoenzyme, the ligand and the target enzyme. In the current work, the dipeptidyl peptidase-IV inhibitor vildagliptin was docked to the PI-PLC structure complexed with myo-inositol using DOCLASP. Also, corroboration of the docking of phenylthiourea to the modelled structure of polyphenol oxidase (JrPPO1) from walnut is provided based on the subsequently solved structure of JrPPO1 (PDBid:5CE9). Analysis of the binding of the antitrypanosomial drug suramin to nine non-homologous proteins in the PDB database shows a diverse set of binding motifs, and multiple binding sites in the phospholipase A2-likeproteins from the Bothrops genus of pitvipers. The conformational changes in the suramin molecule on binding highlights the challenges in docking flexible ligands into an already 'plastic' binding site. Thus, DOCLASP presents a method for 'soft docking' ligands to proteins with low computational requirements.
Continuous desalting of refolded protein solution improves capturing in ion exchange chromatography: A seamless process.

PubMed

Walch, Nicole; Jungbauer, Alois

2017-06-01

Truly continuous biomanufacturing processes enable an uninterrupted feed stream throughout the whole production without the need for holding tanks. We have utilized microporous anion and cation exchangers into which only salts, but not proteins, can penetrate into the pores for desalting of protein solutions, while diafiltration or dilution is usually employed for feed adjustments. Anion exchange and cation exchange chromatography columns were connected in series to remove both anions and cations. To increase operation performance, a continuous process was developed comprised of four columns. Continuous mode was achieved by staggered cycle operation, where one set of columns, consisting of one anion exchange and one cation exchange column, was loaded during the regeneration of the second set. Refolding, desalting and subsequent ion exchange capturing with a scFv as the model protein was demonstrated. The refolding solution was successfully desalted resulting in a consistent conductivity below 0.5 mS/cm from initial values of 10 to 11 mS/cm. With continuous operation process time could be reduced by 39% while productivity was increased to 163% compared to batch operation. Desalting of the protein solution resulted in up to 7-fold higher binding capacities in the subsequent ion exchange capture step with conventional protein binding resins. © 2017 The Authors. Biotechnology Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Structural Isosteres of Phosphate Groups in the Protein Data Bank.

PubMed

Zhang, Yuezhou; Borrel, Alexandre; Ghemtio, Leo; Regad, Leslie; Boije Af Gennäs, Gustav; Camproux, Anne-Claude; Yli-Kauhaluoma, Jari; Xhaard, Henri

2017-03-27

We developed a computational workflow to mine the Protein Data Bank for isosteric replacements that exist in different binding site environments but have not necessarily been identified and exploited in compound design. Taking phosphate groups as examples, the workflow was used to construct 157 data sets, each composed of a reference protein complexed with AMP, ADP, ATP, or pyrophosphate as well other ligands. Phosphate binding sites appear to have a high hydration content and large size, resulting in U-shaped bioactive conformations recurrently found across unrelated protein families. A total of 16 413 replacements were extracted, filtered for a significant structural overlap on phosphate groups, and sorted according to their SMILES codes. In addition to the classical isosteres of phosphate, such as carboxylate, sulfone, or sulfonamide, unexpected replacements that do not conserve charge or polarity, such as aryl, aliphatic, or positively charged groups, were found.
Patchwork structure-function analysis of the Sendai virus matrix protein.

PubMed

Mottet-Osman, Geneviève; Miazza, Vincent; Vidalain, Pierre-Olivier; Roux, Laurent

2014-09-01

Paramyxoviruses contain a bi-lipidic envelope decorated by two transmembrane glycoproteins and carpeted on the inner surface with a layer of matrix proteins (M), thought to bridge the glycoproteins with the viral nucleocapsids. To characterize M structure-function features, a set of M domains were mutated or deleted. The genes encoding these modified M were incorporated into recombinant Sendai viruses and expressed as supplemental proteins. Using a method of integrated suppression complementation system (ISCS), the functions of these M mutants were analyzed in the context of the infection. Cellular membrane association, localization at the cell periphery, nucleocapsid binding, cellular protein interactions and promotion of viral particle formation were characterized in relation with the mutations. At the end, lack of nucleocapsid binding go together with lack of cell surface localization and both features definitely correlate with loss of M global function estimated by viral particle production. Copyright © 2014 Elsevier Inc. All rights reserved.
BindML/BindML+: Detecting Protein-Protein Interaction Interface Propensity from Amino Acid Substitution Patterns.

PubMed

Wei, Qing; La, David; Kihara, Daisuke

2017-01-01

Prediction of protein-protein interaction sites in a protein structure provides important information for elucidating the mechanism of protein function and can also be useful in guiding a modeling or design procedures of protein complex structures. Since prediction methods essentially assess the propensity of amino acids that are likely to be part of a protein docking interface, they can help in designing protein-protein interactions. Here, we introduce BindML and BindML+ protein-protein interaction sites prediction methods. BindML predicts protein-protein interaction sites by identifying mutation patterns found in known protein-protein complexes using phylogenetic substitution models. BindML+ is an extension of BindML for distinguishing permanent and transient types of protein-protein interaction sites. We developed an interactive web-server that provides a convenient interface to assist in structural visualization of protein-protein interactions site predictions. The input data for the web-server are a tertiary structure of interest. BindML and BindML+ are available at http://kiharalab.org/bindml/ and http://kiharalab.org/bindml/plus/ .
Cavity Versus Ligand Shape Descriptors: Application to Urokinase Binding Pockets

PubMed Central

Cerisier, Natacha; Regad, Leslie; Triki, Dhoha; Camproux, Anne-Claude

2017-01-01

Abstract We analyzed 78 binding pockets of the human urokinase plasminogen activator (uPA) catalytic domain extracted from a data set of crystallized uPA–ligand complexes. These binding pockets were computed with an original geometric method that does NOT involve any arbitrary parameter, such as cutoff distances, angles, and so on. We measured the deviation from convexity of each pocket shape with the pocket convexity index (PCI). We defined a new pocket descriptor called distributional sphericity coefficient (DISC), which indicates to which extent the protein atoms of a given pocket lie on the surface of a sphere. The DISC values were computed with the freeware PCI. The pocket descriptors and their high correspondences with ligand descriptors are crucial for polypharmacology prediction. We found that the protein heavy atoms lining the urokinases binding pockets are either located on the surface of their convex hull or lie close to this surface. We also found that the radii of the urokinases binding pockets and the radii of their ligands are highly correlated (r = 0.9). PMID:28570103
Predicting binding modes of reversible peptide-based inhibitors of falcipain-2 consistent with structure-activity relationships.

PubMed

Hernández González, Jorge Enrique; Hernández Alvarez, Lilian; Pascutti, Pedro Geraldo; Valiente, Pedro A

2017-09-01

Falcipain-2 (FP-2) is a major hemoglobinase of Plasmodium falciparum, considered an important drug target for the development of antimalarials. A previous study reported a novel series of 20 reversible peptide-based inhibitors of FP-2. However, the lack of tridimensional structures of the complexes hinders further optimization strategies to enhance the inhibitory activity of the compounds. Here we report the prediction of the binding modes of the aforementioned inhibitors to FP-2. A computational approach combining previous knowledge on the determinants of binding to the enzyme, docking, and postdocking refinement steps, is employed. The latter steps comprise molecular dynamics simulations and free energy calculations. Remarkably, this approach leads to the identification of near-native ligand conformations when applied to a validation set of protein-ligand structures. Overall, we proposed substrate-like binding modes of the studied compounds fulfilling the structural requirements for FP-2 binding and yielding free energy values that correlated well with the experimental data. Proteins 2017; 85:1666-1683. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Developing a Dynamic Pharmacophore Model for HIV-1 Integrase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlson, Heather A.; Masukawa, Keven M.; Rubins, Kathleen

2000-05-11

We present the first receptor-based pharmacophore model for HIV-1 integrase. The development of ''dynamic'' pharmacophore models is a new method that accounts for the inherent flexibility of the active site and aims to reduce the entropic penalties associated with binding a ligand. Furthermore, this new drug discovery method overcomes the limitation of an incomplete crystal structure of the target protein. A molecular dynamics (MD) simulation describes the flexibility of the uncomplexed protein. Many conformational models of the protein are saved from the MD simulations and used in a series of multi-unit search for interacting conformers (MUSIC) simulations. MUSIC is amore » multiple-copy minimization method, available in the BOSS program; it is used to determine binding regions for probe molecules containing functional groups that complement the active site. All protein conformations from the MD are overlaid, and conserved binding regions for the probe molecules are identified. Those conserved binding regions define the dynamic pharmacophore model. Here, the dynamic model is compared to known inhibitors of the integrase as well as a three-point, ligand-based pharmacophore model from the literature. Also, a ''static'' pharmacophore model was determined in the standard fashion, using a single crystal structure. Inhibitors thought to bind in the active site of HIV-1 integrase fit the dynamic model but not the static model. Finally, we have identified a set of compounds from the Available Chemicals Directory that fit the dynamic pharmacophore model, and experimental testing of the compounds has confirmed several new inhibitors.« less
Imparting albumin-binding affinity to a human protein by mimicking the contact surface of a bacterial binding protein.

PubMed

Oshiro, Satoshi; Honda, Shinya

2014-04-18

Attachment of a bacterial albumin-binding protein module is an attractive strategy for extending the plasma residence time of protein therapeutics. However, a protein fused with such a bacterial module could induce unfavorable immune reactions. To address this, we designed an alternative binding protein by imparting albumin-binding affinity to a human protein using molecular surface grafting. The result was a series of human-derived 6 helix-bundle proteins, one of which specifically binds to human serum albumin (HSA) with adequate affinity (KD = 100 nM). The proteins were designed by transferring key binding residues of a bacterial albumin-binding module, Finegoldia magna protein G-related albumin-binding domain (GA) module, onto the human protein scaffold. Despite 13-15 mutations, the designed proteins maintain the original secondary structure by virtue of careful grafting based on structural informatics. Competitive binding assays and thermodynamic analyses of the best binders show that the binding mode resembles that of the GA module, suggesting that the contacting surface of the GA module is mimicked well on the designed protein. These results indicate that the designed protein may act as an alternative low-risk binding module to HSA. Furthermore, molecular surface grafting in combination with structural informatics is an effective approach for avoiding deleterious mutations on a target protein and for imparting the binding function of one protein onto another.
The basic tilted helix bundle domain of the prolyl isomerase FKBP25 is a novel double-stranded RNA binding module

PubMed Central

Dilworth, David; Bonnafous, Pierre; Edoo, Amiirah Bibi; Bourbigot, Sarah; Pesek-Jardim, Francy; Gudavicius, Geoff; Serpa, Jason J.; Petrotchenko, Evgeniy V.; Borchers, Christoph H.

2017-01-01

Abstract Prolyl isomerases are defined by a catalytic domain that facilitates the cis–trans interconversion of proline residues. In most cases, additional domains in these enzymes add important biological function, including recruitment to a set of protein substrates. Here, we report that the N-terminal basic tilted helix bundle (BTHB) domain of the human prolyl isomerase FKBP25 confers specific binding to double-stranded RNA (dsRNA). This binding is selective over DNA as well as single-stranded oligonucleotides. We find that FKBP25 RNA-association is required for its nucleolar localization and for the vast majority of its protein interactions, including those with 60S pre-ribosome and early ribosome biogenesis factors. An independent mobility of the BTHB and FKBP catalytic domains supports a model by which the N-terminus of FKBP25 is anchored to regions of dsRNA, whereas the FKBP domain is free to interact with neighboring proteins. Apart from the identification of the BTHB as a new dsRNA-binding module, this domain adds to the growing list of auxiliary functions used by prolyl isomerases to define their primary cellular targets. PMID:29036638
Identifying mRNA sequence elements for target recognition by human Argonaute proteins

PubMed Central

Li, Jingjing; Kim, TaeHyung; Nutiu, Razvan; Ray, Debashish; Hughes, Timothy R.; Zhang, Zhaolei

2014-01-01

It is commonly known that mammalian microRNAs (miRNAs) guide the RNA-induced silencing complex (RISC) to target mRNAs through the seed-pairing rule. However, recent experiments that coimmunoprecipitate the Argonaute proteins (AGOs), the central catalytic component of RISC, have consistently revealed extensive AGO-associated mRNAs that lack seed complementarity with miRNAs. We herein test the hypothesis that AGO has its own binding preference within target mRNAs, independent of guide miRNAs. By systematically analyzing the data from in vivo cross-linking experiments with human AGOs, we have identified a structurally accessible and evolutionarily conserved region (∼10 nucleotides in length) that alone can accurately predict AGO–mRNA associations, independent of the presence of miRNA binding sites. Within this region, we further identified an enriched motif that was replicable on independent AGO-immunoprecipitation data sets. We used RNAcompete to enumerate the RNA-binding preference of human AGO2 to all possible 7-mer RNA sequences and validated the AGO motif in vitro. These findings reveal a novel function of AGOs as sequence-specific RNA-binding proteins, which may aid miRNAs in recognizing their targets with high specificity. PMID:24663241
Sperm Lysozyme-Like Protein 1 (SLLP1), an intra-acrosomal oolemmal-binding sperm protein, reveals filamentous organization in protein crystal form

PubMed Central

Zheng, Heping; Mandal, Arabinda; Shumilin, Igor A.; Chordia, Mahendra D.; Panneerdoss, Subbarayalu; Herr, John C.; Minor, Wladek

2016-01-01

Sperm Lysozyme-Like Protein 1 (SLLP1) is one of the lysozyme-like proteins predominantly expressed in mammalian testes that lacks bacteriolytic activity, localizes in the sperm acrosome, and exhibits high affinity for an oolemmal receptor, SAS1B. The crystal structure of mouse SLLP1 (mSLLP1) was determined at 2.15Å resolution. mSLLP1 monomer adopts a structural fold similar to that of chicken/mouse lysozymes retaining all four canonical disulfide bonds. mSLLP1 is distinct from c-lysozyme by substituting two essential catalytic residues (E35T/D52N), exhibiting different surface charge distribution, and by forming helical filaments approximately 75Å in diameter with a 25Å central pore comprised of six monomers per helix turn repeating every 33Å. Cross-species alignment of all reported SLLP1 sequences revealed a set of invariant surface regions comprising a characteristic fingerprint uniquely identifying SLLP1 from other c-lysozyme family members. The fingerprint surface regions reside around the lips of the putative glycan binding groove including three polar residues (Y33/E46/H113). A flexible salt bridge (E46-R61) was observed covering the glycan binding groove. The conservation of these regions may be linked to their involvement in oolemmal protein binding. Interaction between SLLP1 monomer and its oolemmal receptor SAS1B was modeled using protein-protein docking algorithms, utilizing the SLLP1 fingerprint regions along with the SAS1B conserved surface regions. This computational model revealed complementarity between the conserved SLLP1/SAS1B interacting surfaces supporting the experimentally-observed SLLP1/SAS1B interaction involved in fertilization. PMID:26198801
Measuring binding of protein to gel-bound ligands using magnetic levitation.

PubMed

Shapiro, Nathan D; Mirica, Katherine A; Soh, Siowling; Phillips, Scott T; Taran, Olga; Mace, Charles R; Shevkoplyas, Sergey S; Whitesides, George M

2012-03-28

This paper describes the use of magnetic levitation (MagLev) to measure the association of proteins and ligands. The method starts with diamagnetic gel beads that are functionalized covalently with small molecules (putative ligands). Binding of protein to the ligands within the bead causes a change in the density of the bead. When these beads are suspended in a paramagnetic aqueous buffer and placed between the poles of two NbFeB magnets with like poles facing, the changes in the density of the bead on binding of protein result in changes in the levitation height of the bead that can be used to quantify the amount of protein bound. This paper uses a reaction-diffusion model to examine the physical principles that determine the values of rate and equilibrium constants measured by this system, using the well-defined model system of carbonic anhydrase and aryl sulfonamides. By tuning the experimental protocol, the method is capable of quantifying either the concentration of protein in a solution, or the binding affinities of a protein to several resin-bound small molecules simultaneously. Since this method requires no electricity and only a single piece of inexpensive equipment, it may find use in situations where portability and low cost are important, such as in bioanalysis in resource-limited settings, point-of-care diagnosis, veterinary medicine, and plant pathology. It still has several practical disadvantages. Most notably, the method requires relatively long assay times and cannot be applied to large proteins (>70 kDa), including antibodies. The design and synthesis of beads with improved characteristics (e.g., larger pore size) has the potential to resolve these problems.
Measuring Binding of Protein to Gel-Bound Ligands Using Magnetic Levitation

PubMed Central

Shapiro, Nathan D.; Mirica, Katherine A.; Soh, Siowling; Phillips, Scott T.; Taran, Olga; Mace, Charles R.; Shevkoplyas, Sergey S.; Whitesides, George M.

2012-01-01

This paper describes the use of magnetic levitation (MagLev) to measure the association of proteins and ligands. The method starts with diamagnetic gel beads that are functionalized covalently with small molecules (putative ligands). Binding of protein to the ligands within the bead causes a change in the density of the bead. When these beads are suspended in a paramagnetic aqueous buffer and placed between the poles of two NbFeB magnets with like poles facing, the changes in the density of the bead on binding of protein result in changes in the levitation height of the bead that can be used to quantify the amount of protein bound. This paper uses a reaction-diffusion model to examine the physical principles that determine the values of rate and equilibrium constants measured by this system, using the well-defined model system of carbonic anhydrase and aryl sulfonamides. By tuning the experimental protocol, the method is capable of quantifying either the concentration of protein in a solution, or the binding affinities of a protein to several resin-bound small molecules simultaneously. Since this method requires no electricity and only a single piece of inexpensive equipment, it may find use in situations where portability and low cost are important, such as in bioanalysis in resource-limited settings, point-of-care diagnosis, veterinary medicine, and plant pathology. It still has several practical disadvantages. Most notably, the method requires relatively long assay times and cannot be applied to large proteins (> 70 kDa), including antibodies. The design and synthesis of beads with improved characteristics (e.g., larger pore size) has the potential to resolve these problems. PMID:22364170
Sperm Lysozyme-Like Protein 1 (SLLP1), an intra-acrosomal oolemmal-binding sperm protein, reveals filamentous organization in protein crystal form.

PubMed

Zheng, H; Mandal, A; Shumilin, I A; Chordia, M D; Panneerdoss, S; Herr, J C; Minor, W

2015-07-01

Sperm lysozyme-like protein 1 (SLLP1) is one of the lysozyme-like proteins predominantly expressed in mammalian testes that lacks bacteriolytic activity, localizes in the sperm acrosome, and exhibits high affinity for an oolemmal receptor, SAS1B. The crystal structure of mouse SLLP1 (mSLLP1) was determined at 2.15 Å resolution. mSLLP1 monomer adopts a structural fold similar to that of chicken/mouse lysozymes retaining all four canonical disulfide bonds. mSLLP1 is distinct from c-lysozyme by substituting two essential catalytic residues (E35T/D52N), exhibiting different surface charge distribution, and by forming helical filaments approximately 75 Å in diameter with a 25 Å central pore comprised of six monomers per helix turn repeating every 33 Å. Cross-species alignment of all reported SLLP1 sequences revealed a set of invariant surface regions comprising a characteristic fingerprint uniquely identifying SLLP1 from other c-lysozyme family members. The fingerprint surface regions reside around the lips of the putative glycan-binding groove including three polar residues (Y33/E46/H113). A flexible salt bridge (E46-R61) was observed covering the glycan-binding groove. The conservation of these regions may be linked to their involvement in oolemmal protein binding. Interaction between SLLP1 monomer and its oolemmal receptor SAS1B was modeled using protein-protein docking algorithms, utilizing the SLLP1 fingerprint regions along with the SAS1B conserved surface regions. This computational model revealed complementarity between the conserved SLLP1/SAS1B interacting surfaces supporting the experimentally observed SLLP1/SAS1B interaction involved in fertilization. © 2015 American Society of Andrology and European Academy of Andrology.
Functional assignment to JEV proteins using SVM.

PubMed

Sahoo, Ganesh Chandra; Dikhit, Manas Ranjan; Das, Pradeep

2008-01-01

Identification of different protein functions facilitates a mechanistic understanding of Japanese encephalitis virus (JEV) infection and opens novel means for drug development. Support vector machines (SVM), useful for predicting the functional class of distantly related proteins, is employed to ascribe a possible functional class to Japanese encephalitis virus protein. Our study from SVMProt and available JE virus sequences suggests that structural and nonstructural proteins of JEV genome possibly belong to diverse protein functions, are expected to occur in the life cycle of JE virus. Protein functions common to both structural and non-structural proteins are iron-binding, metal-binding, lipid-binding, copper-binding, transmembrane, outer membrane, channels/Pores - Pore-forming toxins (proteins and peptides) group of proteins. Non-structural proteins perform functions like actin binding, zinc-binding, calcium-binding, hydrolases, Carbon-Oxygen Lyases, P-type ATPase, proteins belonging to major facilitator family (MFS), secreting main terminal branch (MTB) family, phosphotransfer-driven group translocators and ATP-binding cassette (ABC) family group of proteins. Whereas structural proteins besides belonging to same structural group of proteins (capsid, structural, envelope), they also perform functions like nuclear receptor, antibiotic resistance, RNA-binding, DNA-binding, magnesium-binding, isomerase (intra-molecular), oxidoreductase and participate in type II (general) secretory pathway (IISP).
Functional assignment to JEV proteins using SVM

PubMed Central

Sahoo, Ganesh Chandra; Dikhit, Manas Ranjan; Das, Pradeep

2008-01-01

Identification of different protein functions facilitates a mechanistic understanding of Japanese encephalitis virus (JEV) infection and opens novel means for drug development. Support vector machines (SVM), useful for predicting the functional class of distantly related proteins, is employed to ascribe a possible functional class to Japanese encephalitis virus protein. Our study from SVMProt and available JE virus sequences suggests that structural and nonstructural proteins of JEV genome possibly belong to diverse protein functions, are expected to occur in the life cycle of JE virus. Protein functions common to both structural and non-structural proteins are iron-binding, metal-binding, lipid-binding, copper-binding, transmembrane, outer membrane, channels/Pores - Pore-forming toxins (proteins and peptides) group of proteins. Non-structural proteins perform functions like actin binding, zinc-binding, calcium-binding, hydrolases, Carbon-Oxygen Lyases, P-type ATPase, proteins belonging to major facilitator family (MFS), secreting main terminal branch (MTB) family, phosphotransfer-driven group translocators and ATP-binding cassette (ABC) family group of proteins. Whereas structural proteins besides belonging to same structural group of proteins (capsid, structural, envelope), they also perform functions like nuclear receptor, antibiotic resistance, RNA-binding, DNA-binding, magnesium-binding, isomerase (intra-molecular), oxidoreductase and participate in type II (general) secretory pathway (IISP). PMID:19052658

Computational assessment of the cooperativity between RNA binding proteins and MicroRNAs in Transcript Decay.

PubMed

Jiang, Peng; Singh, Mona; Coller, Hilary A

2013-01-01

Transcript degradation is a widespread and important mechanism for regulating protein abundance. Two major regulators of transcript degradation are RNA Binding Proteins (RBPs) and microRNAs (miRNAs). We computationally explored whether RBPs and miRNAs cooperate to promote transcript decay. We defined five RBP motifs based on the evolutionary conservation of their recognition sites in 3'UTRs as the binding motifs for Pumilio (PUM), U1A, Fox-1, Nova, and UAUUUAU. Recognition sites for some of these RBPs tended to localize at the end of long 3'UTRs. A specific group of miRNA recognition sites were enriched within 50 nts from the RBP recognition sites for PUM and UAUUUAU. The presence of both a PUM recognition site and a recognition site for preferentially co-occurring miRNAs was associated with faster decay of the associated transcripts. For PUM and its co-occurring miRNAs, binding of the RBP to its recognition sites was predicted to release nearby miRNA recognition sites from RNA secondary structures. The mammalian miRNAs that preferentially co-occur with PUM binding sites have recognition seeds that are reverse complements to the PUM recognition motif. Their binding sites have the potential to form hairpin secondary structures with proximal PUM binding sites that would normally limit RISC accessibility, but would be more accessible to miRNAs in response to the binding of PUM. In sum, our computational analyses suggest that a specific set of RBPs and miRNAs work together to affect transcript decay, with the rescue of miRNA recognition sites via RBP binding as one possible mechanism of cooperativity.
BFEE: A User-Friendly Graphical Interface Facilitating Absolute Binding Free-Energy Calculations.

PubMed

Fu, Haohao; Gumbart, James C; Chen, Haochuan; Shao, Xueguang; Cai, Wensheng; Chipot, Christophe

2018-03-26

Quantifying protein-ligand binding has attracted the attention of both theorists and experimentalists for decades. Many methods for estimating binding free energies in silico have been reported in recent years. Proper use of the proposed strategies requires, however, adequate knowledge of the protein-ligand complex, the mathematical background for deriving the underlying theory, and time for setting up the simulations, bookkeeping, and postprocessing. Here, to minimize human intervention, we propose a toolkit aimed at facilitating the accurate estimation of standard binding free energies using a geometrical route, coined the binding free-energy estimator (BFEE), and introduced it as a plug-in of the popular visualization program VMD. Benefitting from recent developments in new collective variables, BFEE can be used to generate the simulation input files, based solely on the structure of the complex. Once the simulations are completed, BFEE can also be utilized to perform the post-treatment of the free-energy calculations, allowing the absolute binding free energy to be estimated directly from the one-dimensional potentials of mean force in simulation outputs. The minimal amount of human intervention required during the whole process combined with the ergonomic graphical interface makes BFEE a very effective and practical tool for the end-user.
High-throughput analysis of peptide binding modules

PubMed Central

Liu, Bernard A.; Engelmann, Brett; Nash, Piers D.

2014-01-01

Modular protein interaction domains that recognize linear peptide motifs are found in hundreds of proteins within the human genome. Some protein interaction domains such as SH2, 14-3-3, Chromo and Bromo domains serve to recognize post-translational modification of amino acids (such as phosphorylation, acetylation, methylation etc.) and translate these into discrete cellular responses. Other modules such as SH3 and PDZ domains recognize linear peptide epitopes and serve to organize protein complexes based on localization and regions of elevated concentration. In both cases, the ability to nucleate specific signaling complexes is in large part dependent on the selectivity of a given protein module for its cognate peptide ligand. High throughput analysis of peptide-binding domains by peptide or protein arrays, phage display, mass spectrometry or other HTP techniques provides new insight into the potential protein-protein interactions prescribed by individual or even whole families of modules. Systems level analyses have also promoted a deeper understanding of the underlying principles that govern selective protein-protein interactions and how selectivity evolves. Lastly, there is a growing appreciation for the limitations and potential pitfalls of high-throughput analysis of protein-peptide interactomes. This review will examine some of the common approaches utilized for large-scale studies of protein interaction domains and suggest a set of standards for the analysis and validation of datasets from large-scale studies of peptide-binding modules. We will also highlight how data from large-scale studies of modular interaction domain families can provide insight into systems level properties such as the linguistics of selective interactions. PMID:22610655
Identifying the binding mode of a molecular scaffold

NASA Astrophysics Data System (ADS)

Chema, Doron; Eren, Doron; Yayon, Avner; Goldblum, Amiram; Zaliani, Andrea

2004-01-01

We describe a method for docking of a scaffold-based series and present its advantages over docking of individual ligands, for determining the binding mode of a molecular scaffold in a binding site. The method has been applied to eight different scaffolds of protein kinase inhibitors (PKI). A single analog of each of these eight scaffolds was previously crystallized with different protein kinases. We have used FlexX to dock a set of molecules that share the same scaffold, rather than docking a single molecule. The main mode of binding is determined by the mode of binding of the largest cluster among the docked molecules that share a scaffold. Clustering is based on our `nearest single neighbor' method [J. Chem. Inf. Comput. Sci., 43 (2003) 208-217]. Additional criteria are applied in those cases in which more than one significant binding mode is found. Using the proposed method, most of the crystallographic binding modes of these scaffolds were reconstructed. Alternative modes, that have not been detected yet by experiments, could also be identified. The method was applied to predict the binding mode of an additional molecular scaffold that was not yet reported and the predicted binding mode has been found to be very similar to experimental results for a closely related scaffold. We suggest that this approach be used as a virtual screening tool for scaffold-based design processes.
Representation of Ion–Protein Interactions Using the Drude Polarizable Force-Field

PubMed Central

2016-01-01

Small metal ions play critical roles in numerous biological processes. Of particular interest is how metalloenzymes are allosterically regulated by the binding of specific ions. Understanding how ion binding affects these biological processes requires atomic models that accurately treat the microscopic interactions with the protein ligands. Theoretical approaches at different levels of sophistication can contribute to a deeper understanding of these systems, although computational models must strike a balance between accuracy and efficiency in order to enable long molecular dynamics simulations. In this study, we present a systematic effort to optimize the parameters of a polarizable force field based on classical Drude oscillators to accurately represent the interactions between ions (K+, Na+, Ca2+, and Cl–) and coordinating amino-acid residues for a set of 30 biologically important proteins. By combining ab initio calculations and experimental thermodynamic data, we derive a polarizable force field that is consistent with a wide range of properties, including the geometries and interaction energies of gas-phase ion/protein-like model compound clusters, and the experimental solvation free-energies of the cations in liquids. The resulting models display significant improvements relative to the fixed-atomic-charge additive CHARMM C36 force field, particularly in their ability to reproduce the many-body electrostatic nonadditivity effects estimated from ab initio calculations. The analysis clarifies the fundamental limitations of the pairwise additivity assumption inherent in classical fixed-charge force fields, and shows its dramatic failures in the case of Ca2+ binding sites. These optimized polarizable models, amenable to computationally efficient large-scale MD simulations, set a firm foundation and offer a powerful avenue to study the roles of the ions in soluble and membrane transport proteins. PMID:25578354
21 CFR 866.5765 - Retinol-binding protein immunological test system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Retinol-binding protein immunological test system....5765 Retinol-binding protein immunological test system. (a) Identification. A retinol-binding protein... the retinol-binding protein that binds and transports vitamin A in serum and urine. Measurement of...
21 CFR 866.5765 - Retinol-binding protein immunological test system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Retinol-binding protein immunological test system....5765 Retinol-binding protein immunological test system. (a) Identification. A retinol-binding protein... the retinol-binding protein that binds and transports vitamin A in serum and urine. Measurement of...
21 CFR 866.5765 - Retinol-binding protein immunological test system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Retinol-binding protein immunological test system....5765 Retinol-binding protein immunological test system. (a) Identification. A retinol-binding protein... the retinol-binding protein that binds and transports vitamin A in serum and urine. Measurement of...
21 CFR 866.5765 - Retinol-binding protein immunological test system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Retinol-binding protein immunological test system....5765 Retinol-binding protein immunological test system. (a) Identification. A retinol-binding protein... the retinol-binding protein that binds and transports vitamin A in serum and urine. Measurement of...
How many atoms are required to characterize accurately trajectory fluctuations of a protein?

NASA Astrophysics Data System (ADS)

Cukier, Robert I.

2010-06-01

Large molecules, whose thermal fluctuations sample a complex energy landscape, exhibit motions on an extended range of space and time scales. Principal component analysis (PCA) is often used to extract dominant motions that in proteins are typically domain motions. These motions are captured in the large eigenvalue (leading) principal components. There is also information in the small eigenvalues, arising from approximate linear dependencies among the coordinates. These linear dependencies suggest that instead of using all the atom coordinates to represent a trajectory, it should be possible to use a reduced set of coordinates with little loss in the information captured by the large eigenvalue principal components. In this work, methods that can monitor the correlation (overlap) between a reduced set of atoms and any number of retained principal components are introduced. For application to trajectory data generated by simulations, where the overall translational and rotational motion needs to be eliminated before PCA is carried out, some difficulties with the overlap measures arise and methods are developed to overcome them. The overlap measures are evaluated for a trajectory generated by molecular dynamics for the protein adenylate kinase, which consists of a stable, core domain, and two more mobile domains, referred to as the LID domain and the AMP-binding domain. The use of reduced sets corresponding, for the smallest set, to one-eighth of the alpha carbon (CA) atoms relative to using all the CA atoms is shown to predict the dominant motions of adenylate kinase. The overlap between using all the CA atoms and all the backbone atoms is essentially unity for a sum over PCA modes that effectively capture the exact trajectory. A reduction to a few atoms (three in the LID and three in the AMP-binding domain) shows that at least the first principal component, characterizing a large part of the LID-binding and AMP-binding motion, is well described. Based on these results, the overlap criterion should be applicable as a guide to postulating and validating coarse-grained descriptions of generic biomolecular assemblies.
Biofilm Matrix Proteins.

PubMed

Fong, Jiunn N C; Yildiz, Fitnat H

2015-04-01

Proteinaceous components of the biofilm matrix include secreted extracellular proteins, cell surface adhesins, and protein subunits of cell appendages such as flagella and pili. Biofilm matrix proteins play diverse roles in biofilm formation and dissolution. They are involved in attaching cells to surfaces, stabilizing the biofilm matrix via interactions with exopolysaccharide and nucleic acid components, developing three-dimensional biofilm architectures, and dissolving biofilm matrix via enzymatic degradation of polysaccharides, proteins, and nucleic acids. In this article, we will review functions of matrix proteins in a selected set of microorganisms, studies of the matrix proteomes of Vibrio cholerae and Pseudomonas aeruginosa, and roles of outer membrane vesicles and of nucleoid-binding proteins in biofilm formation.
Acceleration of Binding Site Comparisons by Graph Partitioning.

PubMed

Krotzky, Timo; Klebe, Gerhard

2015-08-01

The comparison of protein binding sites is a prominent task in computational chemistry and has been studied in many different ways. For the automatic detection and comparison of putative binding cavities the Cavbase system has been developed which uses a coarse-grained set of pseudocenters to represent the physicochemical properties of a binding site and employs a graph-based procedure to calculate similarities between two binding sites. However, the comparison of two graphs is computationally quite demanding which makes large-scale studies such as the rapid screening of entire databases hardly feasible. In a recent work, we proposed the method Local Cliques (LC) for the efficient comparison of Cavbase binding sites. It employs a clique heuristic to detect the maximum common subgraph of two binding sites and an extended graph model to additionally compare the shape of individual surface patches. In this study, we present an alternative to further accelerate the LC method by partitioning the binding-site graphs into disjoint components prior to their comparisons. The pseudocenter sets are split with regard to their assigned phyiscochemical type, which leads to seven much smaller graphs than the original one. Applying this approach on the same test scenarios as in the former comprehensive way results in a significant speed-up without sacrificing accuracy. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Application of oxime-diversification to optimize ligand interactions within a cryptic pocket of the polo-like kinase 1 polo-box domain.

PubMed

Zhao, Xue Zhi; Hymel, David; Burke, Terrence R

2016-10-15

By a process involving initial screening of a set of 87 aldehydes using an oxime ligation-based strategy, we were able to achieve a several-fold affinity enhancement over one of the most potent previously known polo-like kinase 1 (Plk1) polo-box domain (PBD) binding inhibitors. This improved binding may result by accessing a newly identified auxiliary region proximal to a key hydrophobic cryptic pocket on the surface of the protein. Our findings could have general applicability to the design of PBD-binding antagonists. Published by Elsevier Ltd.
A Strategy Based on Protein-Protein Interface Motifs May Help in Identifying Drug Off-Targets

PubMed Central

Engin, H. Billur; Keskin, Ozlem; Nussinov, Ruth; Gursoy, Attila

2014-01-01

Networks are increasingly used to study the impact of drugs at the systems level. From the algorithmic standpoint, a drug can ‘attack’ nodes or edges of a protein-protein interaction network. In this work, we propose a new network strategy, “The Interface Attack”, based on protein-protein interfaces. Similar interface architectures can occur between unrelated proteins. Consequently, in principle, a drug that binds to one has a certain probability of binding others. The interface attack strategy simultaneously removes from the network all interactions that consist of similar interface motifs. This strategy is inspired by network pharmacology and allows inferring potential off-targets. We introduce a network model which we call “Protein Interface and Interaction Network (P2IN)”, which is the integration of protein-protein interface structures and protein interaction networks. This interface-based network organization clarifies which protein pairs have structurally similar interfaces, and which proteins may compete to bind the same surface region. We built the P2IN of p53 signaling network and performed network robustness analysis. We show that (1) ‘hitting’ frequent interfaces (a set of edges distributed around the network) might be as destructive as eleminating high degree proteins (hub nodes); (2) frequent interfaces are not always topologically critical elements in the network; and (3) interface attack may reveal functional changes in the system better than attack of single proteins. In the off-target detection case study, we found that drugs blocking the interface between CDK6 and CDKN2D may also affect the interaction between CDK4 and CDKN2D. PMID:22817115
Combinatorial interactions of two amino acids with a single base pair define target site specificity in plant dimeric homeodomain proteins

PubMed Central

Tron, Adriana E.; Bertoncini, Carlos W.; Palena, Claudia M.; Chan, Raquel L.; Gonzalez, Daniel H.

2001-01-01

Four groups of plant homeodomain proteins contain a dimerization motif closely linked to the homeodomain. We here show that two sunflower homeodomain proteins, Hahb-4 and HAHR1, which belong to the Hd-Zip I and GL2/Hd-Zip IV groups, respectively, show different binding preferences at a defined position of a pseudopalindromic DNA-binding site used as a target. HAHR1 shows a preference for the sequence 5′-CATT(A/T)AATG-3′, rather than 5′-CAAT(A/T)ATTG-3′, recognized by Hahb-4. To analyze the molecular basis of this behavior, we have constructed a set of mutants with exchanged residues (Phe→Ile and Ile→Phe) at position 47 of the homeodomain, together with chimeric proteins between HAHR1 and Hahb-4. The results obtained indicate that Phe47, but not Ile47, allows binding to 5′-CATT(A/T)AATG-3′. However, the preference for this sequence is determined, in addition, by amino acids located C-terminal to residue 53 of the HAHR1 homeodomain. A double mutant of Hahb-4 (Ile47→Phe/Ala54→Thr) shows the same binding behavior as HAHR1, suggesting that combinatorial interactions of amino acid residues at positions 47 and 54 of the homeodomain are involved in establishing the affinity and selectivity of plant dimeric homeodomain proteins with different DNA target sequences. PMID:11726696
Human sex hormone-binding globulin binding affinities of 125 structurally diverse chemicals and comparison with their binding to androgen receptor, estrogen receptor, and α-fetoprotein.

PubMed

Hong, Huixiao; Branham, William S; Ng, Hui Wen; Moland, Carrie L; Dial, Stacey L; Fang, Hong; Perkins, Roger; Sheehan, Daniel; Tong, Weida

2015-02-01

One endocrine disruption mechanism is through binding to nuclear receptors such as the androgen receptor (AR) and estrogen receptor (ER) in target cells. The concentration of a chemical in serum is important for its entry into the target cells to bind the receptors, which is regulated by the serum proteins. Human sex hormone-binding globulin (SHBG) is the major transport protein in serum that can bind androgens and estrogens and thus change a chemical's availability to enter the target cells. Sequestration of an androgen or estrogen in the serum can alter the chemical elicited AR- and ER-mediated responses. To better understand the chemical-induced endocrine activity, we developed a competitive binding assay using human pregnancy plasma and measured the binding to the human SHBG for 125 structurally diverse chemicals, most of which were known to bind AR and ER. Eighty seven chemicals were able to bind the human SHBG in the assay, whereas 38 chemicals were nonbinders. Binding data for human SHBG are compared with that for rat α-fetoprotein, ER and AR. Knowing the binding profiles between serum and nuclear receptors will improve assessment of a chemical's potential for endocrine disruption. The SHBG binding data reported here represent the largest data set of structurally diverse chemicals tested for human SHBG binding. Utilization of the SHBG binding data with AR and ER binding data could enable better evaluation of endocrine disrupting potential of chemicals through AR- and ER-mediated responses since sequestration in serum could be considered. Published by Oxford University Press on behalf of the Society of Toxicology 2014. This work is written by US Government employees and is in the public domain in the US.
Heterodimer Binding Scaffolds Recognition via the Analysis of Kinetically Hot Residues.

PubMed

Perišić, Ognjen

2018-03-16

Physical interactions between proteins are often difficult to decipher. The aim of this paper is to present an algorithm that is designed to recognize binding patches and supporting structural scaffolds of interacting heterodimer proteins using the Gaussian Network Model (GNM). The recognition is based on the (self) adjustable identification of kinetically hot residues and their connection to possible binding scaffolds. The kinetically hot residues are residues with the lowest entropy, i.e., the highest contribution to the weighted sum of the fastest modes per chain extracted via GNM. The algorithm adjusts the number of fast modes in the GNM's weighted sum calculation using the ratio of predicted and expected numbers of target residues (contact and the neighboring first-layer residues). This approach produces very good results when applied to dimers with high protein sequence length ratios. The protocol's ability to recognize near native decoys was compared to the ability of the residue-level statistical potential of Lu and Skolnick using the Sternberg and Vakser decoy dimers sets. The statistical potential produced better overall results, but in a number of cases its predicting ability was comparable, or even inferior, to the prediction ability of the adjustable GNM approach. The results presented in this paper suggest that in heterodimers at least one protein has interacting scaffold determined by the immovable, kinetically hot residues. In many cases, interacting proteins (especially if being of noticeably different sizes) either behave as a rigid lock and key or, presumably, exhibit the opposite dynamic behavior. While the binding surface of one protein is rigid and stable, its partner's interacting scaffold is more flexible and adaptable.
Thioredoxin binding protein (TBP)-2/Txnip and α-arrestin proteins in cancer and diabetes mellitus.

PubMed

Masutani, Hiroshi; Yoshihara, Eiji; Masaki, So; Chen, Zhe; Yodoi, Junji

2012-01-01

Thioredoxin binding protein -2/ thioredoxin interacting protein is an α-arrestin protein that has attracted much attention as a multifunctional regulator. Thioredoxin binding protein -2 expression is downregulated in tumor cells and the level of thioredoxin binding protein is correlated with clinical stage of cancer. Mice with mutations or knockout of the thioredoxin binding protein -2 gene are much more susceptible to carcinogenesis than wild-type mice, indicating a role for thioredoxin binding protein -2 in cancer suppression. Studies have also revealed roles for thioredoxin binding protein -2 in metabolic control. Enhancement of thioredoxin binding protein -2 expression causes impairment of insulin sensitivity and glucose-induced insulin secretion, and β-cell apoptosis. These changes are important characteristics of type 2 diabetes mellitus. Thioredoxin binding protein -2 regulates transcription of metabolic regulating genes. Thioredoxin binding protein -2-like inducible membrane protein/ arrestin domain containing 3 regulates endocytosis of receptors such as the β(2)-adrenergic receptor. The α-arrestin family possesses PPXY motifs and may function as an adaptor/scaffold for NEDD family ubiquitin ligases. Elucidation of the molecular mechanisms of α-arrestin proteins would provide a new pharmacological basis for developing approaches against cancer and type 2 diabetes mellitus.
A Single Rainbow Trout Cobalamin-binding Protein Stands in for Three Human Binders

PubMed Central

Greibe, Eva; Fedosov, Sergey; Sorensen, Boe S.; Højrup, Peter; Poulsen, Steen S.; Nexo, Ebba

2012-01-01

Cobalamin uptake and transport in mammals are mediated by three cobalamin-binding proteins: haptocorrin, intrinsic factor, and transcobalamin. The nature of cobalamin-binding proteins in lower vertebrates remains to be elucidated. The aim of this study was to characterize the cobalamin-binding proteins of the rainbow trout (Oncorhynchus mykiss) and to compare their properties with those of the three human cobalamin-binding proteins. High cobalamin-binding capacity was found in trout stomach (210 pmol/g), roe (400 pmol/g), roe fluid (390 nmol/liter), and plasma (2500 nmol/liter). In all cases, it appeared to be the same protein based on analysis of partial sequences and immunological responses. The trout cobalamin-binding protein was purified from roe fluid, sequenced, and further characterized. Like haptocorrin, the trout cobalamin-binding protein was stable at low pH and had a high binding affinity for the cobalamin analog cobinamide. Like haptocorrin and transcobalamin, the trout cobalamin-binding protein was present in plasma and recognized ligands with altered nucleotide moiety. Like intrinsic factors, the trout cobalamin-binding protein was present in the stomach and resisted degradation by trypsin and chymotrypsin. It also resembled intrinsic factor in the composition of conserved residues in the primary cobalamin-binding site in the C terminus. The trout cobalamin-binding protein was glycosylated and displayed spectral properties comparable with those of haptocorrin and intrinsic factor. In conclusion, only one soluble cobalamin-binding protein was identified in the rainbow trout, a protein that structurally behaves like an intermediate between the three human cobalamin-binding proteins. PMID:22872637
A systems biology analysis of the changes in gene expression via silencing of HPV-18 E1 expression in HeLa cells.

PubMed

Castillo, Andres; Wang, Lu; Koriyama, Chihaya; Eizuru, Yoshito; Jordan, King; Akiba, Suminori

2014-10-01

Previous studies have reported the detection of a truncated E1 mRNA generated from HPV-18 in HeLa cells. Although it is unclear whether a truncated E1 protein could function as a replicative helicase for viral replication, it would still retain binding sites for potential interactions with different host cell proteins. Furthermore, in this study, we found evidence in support of expression of full-length HPV-18 E1 mRNA in HeLa cells. To determine whether interactions between E1 and cellular proteins play an important role in cellular processes other than viral replication, genome-wide expression profiles of HPV-18 positive HeLa cells were compared before and after the siRNA knockdown of E1 expression. Differential expression and gene set enrichment analysis uncovered four functionally related sets of genes implicated in host defence mechanisms against viral infection. These included the toll-like receptor, interferon and apoptosis pathways, along with the antiviral interferon-stimulated gene set. In addition, we found that the transcriptional coactivator E1A-binding protein p300 (EP300) was downregulated, which is interesting given that EP300 is thought to be required for the transcription of HPV-18 genes in HeLa cells. The observed changes in gene expression produced via the silencing of HPV-18 E1 expression in HeLa cells indicate that in addition to its well-known role in viral replication, the E1 protein may also play an important role in mitigating the host's ability to defend against viral infection.

PTPRT regulates the interaction of Syntaxin-binding protein 1 with Syntaxin 1 through dephosphorylation of specific tyrosine residue

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lim, So-Hee; Moon, Jeonghee; Lee, Myungkyu

2013-09-13

Highlights: •PTPRT is a brain-specific, expressed, protein tyrosine phosphatase. •PTPRT regulated the interaction of Syntaxin-binding protein 1 with Syntaxin 1. •PTPRT dephosphorylated the specific tyrosine residue of Syntaxin-binding protein 1. •Dephosphorylation of Syntaxin-binding protein 1 enhanced the interaction with Syntaxin 1. •PTPRT appears to regulate the fusion of synaptic vesicle through dephosphorylation. -- Abstract: PTPRT (protein tyrosine phosphatase receptor T), a brain-specific tyrosine phosphatase, has been found to regulate synaptic formation and development of hippocampal neurons, but its regulation mechanism is not yet fully understood. Here, Syntaxin-binding protein 1, a key component of synaptic vesicle fusion machinery, was identified asmore » a possible interaction partner and an endogenous substrate of PTPRT. PTPRT interacted with Syntaxin-binding protein 1 in rat synaptosome, and co-localized with Syntaxin-binding protein 1 in cultured hippocampal neurons. PTPRT dephosphorylated tyrosine 145 located around the linker between domain 1 and 2 of Syntaxin-binding protein 1. Syntaxin-binding protein 1 directly binds to Syntaxin 1, a t-SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) protein, and plays a role as catalysts of SNARE complex formation. Syntaxin-binding protein 1 mutant mimicking non-phosphorylation (Y145F) enhanced the interaction with Syntaxin 1 compared to wild type, and therefore, dephosphorylation of Syntaxin-binding protein 1 appeared to be important for SNARE-complex formation. In conclusion, PTPRT could regulate the interaction of Syntaxin-binding protein 1 with Syntaxin 1, and as a result, the synaptic vesicle fusion appeared to be controlled through dephosphorylation of Syntaxin-binding protein 1.« less
Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins.

PubMed

Ashtawy, Hossam M; Mahapatra, Nihar R

2015-01-01

Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex.
Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins

PubMed Central

2015-01-01

Background Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. Results and conclusion We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex. PMID:25916860
Lessons in molecular recognition: the effects of ligand and protein flexibility on molecular docking accuracy.

PubMed

Erickson, Jon A; Jalaie, Mehran; Robertson, Daniel H; Lewis, Richard A; Vieth, Michal

2004-01-01

The key to success for computational tools used in structure-based drug design is the ability to accurately place or "dock" a ligand in the binding pocket of the target of interest. In this report we examine the effect of several factors on docking accuracy, including ligand and protein flexibility. To examine ligand flexibility in an unbiased fashion, a test set of 41 ligand-protein cocomplex X-ray structures were assembled that represent a diversity of size, flexibility, and polarity with respect to the ligands. Four docking algorithms, DOCK, FlexX, GOLD, and CDOCKER, were applied to the test set, and the results were examined in terms of the ability to reproduce X-ray ligand positions within 2.0A heavy atom root-mean-square deviation. Overall, each method performed well (>50% accuracy) but for all methods it was found that docking accuracy decreased substantially for ligands with eight or more rotatable bonds. Only CDOCKER was able to accurately dock most of those ligands with eight or more rotatable bonds (71% accuracy rate). A second test set of structures was gathered to examine how protein flexibility influences docking accuracy. CDOCKER was applied to X-ray structures of trypsin, thrombin, and HIV-1-protease, using protein structures bound to several ligands and also the unbound (apo) form. Docking experiments of each ligand to one "average" structure and to the apo form were carried out, and the results were compared to docking each ligand back to its originating structure. The results show that docking accuracy falls off dramatically if one uses an average or apo structure. In fact, it is shown that the drop in docking accuracy mirrors the degree to which the protein moves upon ligand binding.
Eye patches: Protein assembly of index-gradient squid lenses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, J.; Townsend, J. P.; Dodson, T. C.

A parabolic relationship between lens radius and refractive index allows spherical lenses to avoid spherical aberration. We show that in squid, patchy colloidal physics resulted from an evolutionary radiation of globular S-crystallin proteins. Small-angle x-ray scattering experiments on lens tissue show colloidal gels of S-crystallins at all radial positions. Sparse lens materials form via low-valence linkages between disordered loops protruding from the protein surface. The loops are polydisperse and bind via a set of hydrogen bonds between disordered side chains. Peripheral lens regions with low particle valence form stable, volume-spanning gels at low density, whereas central regions with higher averagemore » valence gel at higher densities. The proteins demonstrate an evolved set of linkers for self-assembly of nanoparticles into volumetric materials.« less
Ligand Binding Site Detection by Local Structure Alignment and Its Performance Complementarity

PubMed Central

Lee, Hui Sun; Im, Wonpil

2013-01-01

Accurate determination of potential ligand binding sites (BS) is a key step for protein function characterization and structure-based drug design. Despite promising results of template-based BS prediction methods using global structure alignment (GSA), there is a room to improve the performance by properly incorporating local structure alignment (LSA) because BS are local structures and often similar for proteins with dissimilar global folds. We present a template-based ligand BS prediction method using G-LoSA, our LSA tool. A large benchmark set validation shows that G-LoSA predicts drug-like ligands’ positions in single-chain protein targets more precisely than TM-align, a GSA-based method, while the overall success rate of TM-align is better. G-LoSA is particularly efficient for accurate detection of local structures conserved across proteins with diverse global topologies. Recognizing the performance complementarity of G-LoSA to TM-align and a non-template geometry-based method, fpocket, a robust consensus scoring method, CMCS-BSP (Complementary Methods and Consensus Scoring for ligand Binding Site Prediction), is developed and shows improvement on prediction accuracy. The G-LoSA source code is freely available at http://im.bioinformatics.ku.edu/GLoSA. PMID:23957286
A combinatorial approach to synthetic transcription factor-promoter combinations for yeast strain engineering

DOE PAGES

Dossani, Zain Y.; Reider Apel, Amanda; Szmidt-Middleton, Heather; ...

2017-10-30

Despite the need for inducible promoters in strain development efforts, the majority of engineering in Saccharomyces cerevisiae continues to rely on a few constitutively active or inducible promoters. Building on advances that use the modular nature of both transcription factors and promoter regions, we have built a library of hybrid promoters that are regulated by a synthetic transcription factor. The hybrid promoters consist of native S. cerevisiae promoters, in which the operator regions have been replaced with sequences that are recognized by the bacterial LexA DNA binding protein. Correspondingly, the synthetic transcription factor (TF) consists of the DNA binding domainmore » of the LexA protein, fused with the human estrogen binding domain and the viral activator domain, VP16. The resulting system with a bacterial DNA binding domain avoids the transcription of native S. cerevisiae genes, and the hybrid promoters can be induced using estradiol, a compound with no detectable impact on S. cerevisiae physiology. Using combinations of one, two or three operator sequence repeats and a set of native S. cerevisiae promoters, we obtained a series of hybrid promoters that can be induced to different levels, using the same synthetic TF and a given estradiol. Finally, this set of promoters, in combination with our synthetic TF, has the potential to regulate numerous genes or pathways simultaneously, to multiple desired levels, in a single strain.« less
A combinatorial approach to synthetic transcription factor‐promoter combinations for yeast strain engineering

PubMed Central

Dossani, Zain Y.; Reider Apel, Amanda; Szmidt‐Middleton, Heather; Hillson, Nathan J.; Deutsch, Samuel; Keasling, Jay D.

2017-01-01

Abstract Despite the need for inducible promoters in strain development efforts, the majority of engineering in Saccharomyces cerevisiae continues to rely on a few constitutively active or inducible promoters. Building on advances that use the modular nature of both transcription factors and promoter regions, we have built a library of hybrid promoters that are regulated by a synthetic transcription factor. The hybrid promoters consist of native S. cerevisiae promoters, in which the operator regions have been replaced with sequences that are recognized by the bacterial LexA DNA binding protein. Correspondingly, the synthetic transcription factor (TF) consists of the DNA binding domain of the LexA protein, fused with the human estrogen binding domain and the viral activator domain, VP16. The resulting system with a bacterial DNA binding domain avoids the transcription of native S. cerevisiae genes, and the hybrid promoters can be induced using estradiol, a compound with no detectable impact on S. cerevisiae physiology. Using combinations of one, two or three operator sequence repeats and a set of native S. cerevisiae promoters, we obtained a series of hybrid promoters that can be induced to different levels, using the same synthetic TF and a given estradiol. This set of promoters, in combination with our synthetic TF, has the potential to regulate numerous genes or pathways simultaneously, to multiple desired levels, in a single strain. PMID:29084380
A combinatorial approach to synthetic transcription factor-promoter combinations for yeast strain engineering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dossani, Zain Y.; Reider Apel, Amanda; Szmidt-Middleton, Heather

Despite the need for inducible promoters in strain development efforts, the majority of engineering in Saccharomyces cerevisiae continues to rely on a few constitutively active or inducible promoters. Building on advances that use the modular nature of both transcription factors and promoter regions, we have built a library of hybrid promoters that are regulated by a synthetic transcription factor. The hybrid promoters consist of native S. cerevisiae promoters, in which the operator regions have been replaced with sequences that are recognized by the bacterial LexA DNA binding protein. Correspondingly, the synthetic transcription factor (TF) consists of the DNA binding domainmore » of the LexA protein, fused with the human estrogen binding domain and the viral activator domain, VP16. The resulting system with a bacterial DNA binding domain avoids the transcription of native S. cerevisiae genes, and the hybrid promoters can be induced using estradiol, a compound with no detectable impact on S. cerevisiae physiology. Using combinations of one, two or three operator sequence repeats and a set of native S. cerevisiae promoters, we obtained a series of hybrid promoters that can be induced to different levels, using the same synthetic TF and a given estradiol. Finally, this set of promoters, in combination with our synthetic TF, has the potential to regulate numerous genes or pathways simultaneously, to multiple desired levels, in a single strain.« less
Monoclonal antibodies to human vitamin D-binding protein.

PubMed Central

Pierce, E A; Dame, M C; Bouillon, R; Van Baelen, H; DeLuca, H F

1985-01-01

Monoclonal antibodies to vitamin D-binding protein isolated from human serum have been produced. The antibodies obtained have been shown to be specific for human vitamin D-binding protein by three independent assays. The antibodies recognize human vitamin D-binding protein specifically in an enzyme-linked immunosorbent assay. Human vitamin D-binding protein is detected specifically in both pure and crude samples by a radiometric immunosorbent assay (RISA) and by an immunoprecipitation assay. The anti-human vitamin D-binding protein antibodies cross-react with monkey and pig vitamin D-binding protein, but not with vitamin D-binding protein from rat, mouse, or chicken, as determined by the RISA and immunoprecipitation assays. Images PMID:3936035
Predicting the tolerated sequences for proteins and protein interfaces using RosettaBackrub flexible backbone design.

PubMed

Smith, Colin A; Kortemme, Tanja

2011-01-01

Predicting the set of sequences that are tolerated by a protein or protein interface, while maintaining a desired function, is useful for characterizing protein interaction specificity and for computationally designing sequence libraries to engineer proteins with new functions. Here we provide a general method, a detailed set of protocols, and several benchmarks and analyses for estimating tolerated sequences using flexible backbone protein design implemented in the Rosetta molecular modeling software suite. The input to the method is at least one experimentally determined three-dimensional protein structure or high-quality model. The starting structure(s) are expanded or refined into a conformational ensemble using Monte Carlo simulations consisting of backrub backbone and side chain moves in Rosetta. The method then uses a combination of simulated annealing and genetic algorithm optimization methods to enrich for low-energy sequences for the individual members of the ensemble. To emphasize certain functional requirements (e.g. forming a binding interface), interactions between and within parts of the structure (e.g. domains) can be reweighted in the scoring function. Results from each backbone structure are merged together to create a single estimate for the tolerated sequence space. We provide an extensive description of the protocol and its parameters, all source code, example analysis scripts and three tests applying this method to finding sequences predicted to stabilize proteins or protein interfaces. The generality of this method makes many other applications possible, for example stabilizing interactions with small molecules, DNA, or RNA. Through the use of within-domain reweighting and/or multistate design, it may also be possible to use this method to find sequences that stabilize particular protein conformations or binding interactions over others.
Water-Soluble Chlorophyll Protein (WSCP) Stably Binds Two or Four Chlorophylls.

PubMed

Palm, Daniel M; Agostini, Alessandro; Tenzer, Stefan; Gloeckle, Barbara M; Werwie, Mara; Carbonera, Donatella; Paulsen, Harald

2017-03-28

Water-soluble chlorophyll proteins (WSCPs) of class IIa from Brassicaceae form tetrameric complexes containing one chlorophyll (Chl) per apoprotein but no carotenoids. The complexes are remarkably stable toward dissociation and protein denaturation even at 100 °C and extreme pH values, and the Chls are partially protected against photooxidation. There are several hypotheses that explain the biological role of WSCPs, one of them proposing that they function as a scavenger of Chls set free upon plant senescence or pathogen attack. The biochemical properties of WSCP described in this paper are consistent with the protein acting as an efficient and flexible Chl scavenger. At limiting Chl concentrations, the recombinant WSCP apoprotein binds substoichiometric amounts of Chl (two Chls per tetramer) to form complexes that are as stable toward thermal dissociation, denaturation, and photodamage as the fully pigmented ones. If more Chl is added, these two-Chl complexes can bind another two Chls to reach the fully pigmented state. The protection of WSCP Chls against photodamage has been attributed to the apoprotein serving as a diffusion barrier for oxygen, preventing its access to triplet excited Chls and, thus, the formation of singlet oxygen. By contrast, the sequential binding of Chls by WSCP suggests a partially open or at least flexible structure, raising the question of how WSCP photoprotects its Chls without the help of carotenoids.
Predicted RNA Binding Proteins Pes4 and Mip6 Regulate mRNA Levels, Translation, and Localization during Sporulation in Budding Yeast.

PubMed

Jin, Liang; Zhang, Kai; Sternglanz, Rolf; Neiman, Aaron M

2017-05-01

In response to starvation, diploid cells of Saccharomyces cerevisiae undergo meiosis and form haploid spores, a process collectively referred to as sporulation. The differentiation into spores requires extensive changes in gene expression. The transcriptional activator Ndt80 is a central regulator of this process, which controls many genes essential for sporulation. Ndt80 induces ∼300 genes coordinately during meiotic prophase, but different mRNAs within the NDT80 regulon are translated at different times during sporulation. The protein kinase Ime2 and RNA binding protein Rim4 are general regulators of meiotic translational delay, but how differential timing of individual transcripts is achieved was not known. This report describes the characterization of two related NDT80 -induced genes, PES4 and MIP6 , encoding predicted RNA binding proteins. These genes are necessary to regulate the steady-state expression, translational timing, and localization of a set of mRNAs that are transcribed by NDT80 but not translated until the end of meiosis II. Mutations in the predicted RNA binding domains within PES4 alter the stability of target mRNAs. PES4 and MIP6 affect only a small portion of the NDT80 regulon, indicating that they act as modulators of the general Ime2/Rim4 pathway for specific transcripts. Copyright © 2017 American Society for Microbiology.
Molecular docking based screening of compounds against VP40 from Ebola virus.

PubMed

M Alam El-Din, Hanaa; A Loutfy, Samah; Fathy, Nasra; H Elberry, Mostafa; M Mayla, Ahmed; Kassem, Sara; Naqvi, Asif

2016-01-01

Ebola virus causes severe and often fatal hemorrhagic fevers in humans. The 2014 Ebola epidemic affected multiple countries. The virus matrix protein (VP40) plays a central role in virus assembly and budding. Since there is no FDA-approved vaccine or medicine against Ebola viral infection, discovering new compounds with different binding patterns against it is required. Therefore, we aim to identify small molecules that target the Arg 134 RNA binding and active site of VP40 protein. 1800 molecules were retrieved from PubChem compound database based on Structure Similarity and Conformers of pyrimidine-2, 4-dione. Molecular docking approach using Lamarckian Genetic Algorithm was carried out to find the potent inhibitors for VP40 based on calculated ligand-protein pairwise interaction energies. The grid maps representing the protein were calculated using auto grid and grid size was set to 60*60*60 points with grid spacing of 0.375 Ǻ. Ten independent docking runs were carried out for each ligand and results were clustered according to the 1.0 Ǻ RMSD criteria. The post-docking analysis showed that binding energies ranged from -8.87 to 0.6 Kcal/mol. We report 7 molecules, which showed promising ADMET results, LD-50, as well as H-bond interaction in the binding pocket. The small molecules discovered could act as potential inhibitors for VP40 and could interfere with virus assembly and budding process.
Molecular docking based screening of compounds against VP40 from Ebola virus

PubMed Central

M Alam El-Din, Hanaa; A. Loutfy, Samah; Fathy, Nasra; H Elberry, Mostafa; M Mayla, Ahmed; Kassem, Sara; Naqvi, Asif

2016-01-01

Ebola virus causes severe and often fatal hemorrhagic fevers in humans. The 2014 Ebola epidemic affected multiple countries. The virus matrix protein (VP40) plays a central role in virus assembly and budding. Since there is no FDA-approved vaccine or medicine against Ebola viral infection, discovering new compounds with different binding patterns against it is required. Therefore, we aim to identify small molecules that target the Arg 134 RNA binding and active site of VP40 protein. 1800 molecules were retrieved from PubChem compound database based on Structure Similarity and Conformers of pyrimidine-2, 4-dione. Molecular docking approach using Lamarckian Genetic Algorithm was carried out to find the potent inhibitors for VP40 based on calculated ligand-protein pairwise interaction energies. The grid maps representing the protein were calculated using auto grid and grid size was set to 60*60*60 points with grid spacing of 0.375 Ǻ. Ten independent docking runs were carried out for each ligand and results were clustered according to the 1.0 Ǻ RMSD criteria. The post-docking analysis showed that binding energies ranged from -8.87 to 0.6 Kcal/mol. We report 7 molecules, which showed promising ADMET results, LD-50, as well as H-bond interaction in the binding pocket. The small molecules discovered could act as potential inhibitors for VP40 and could interfere with virus assembly and budding process. PMID:28149054
Investigation of the inhibitors of histone-lysine N-methyltransferase SETD2 for acute lymphoblastic leukaemia from traditional Chinese medicine.

PubMed

Chang, Y-L; Chen, H-Y; Chen, K-B; Chen, K-C; Chang, K-L; Chang, P-C; Chang, T-T; Chen, Y-C

2016-07-01

Leukaemia is the leading cause of childhood malignancies. Recent research indicates that the SETD2 gene is associated with acute lymphoblastic leukaemia. This study aims to identify potential lead compounds from traditional Chinese medicine (TCM) using virtual screening for SET domain containing 2 (SETD2) protein against acute lymphoblastic leukaemia. Docking simulation was performed to determine potential candidates which obtain suitable docking poses in the binding domain of the SETD2 protein. We also performed molecular dynamics (MD) simulation to investigate the stability of docking poses of SETD2 protein complexes with the top three TCM candidates and a control. According to the results of docking and MD simulation, coniselin and coniferyl ferulate have high binding affinity and stable interactions with the SETD2 protein. Coniselin is isolated from the alcoholic extract of Comiselinum vaginatum Thell. Coniferyl ferulate can be isolated from Angelica sinensis, Poria cocos (Schw.) Wolf, and Notopterygium forbesii. Although S-adenosyl-L-homocysteine has more stable interactions with key residues in the binding domain than coniselin and coniferyl ferulate during MD simulation, the TCM compounds coniselin and coniferyl ferulate are still potential candidates as lead compounds for further study in the drug development process with the SETD2 protein against acute lymphoblastic leukaemia.
Selective activators of protein phosphatase 5 target the auto-inhibitory mechanism.

PubMed

Haslbeck, Veronika; Drazic, Adrian; Eckl, Julia M; Alte, Ferdinand; Helmuth, Martin; Popowicz, Grzegorz; Schmidt, Werner; Braun, Frank; Weiwad, Matthias; Fischer, Gunter; Gemmecker, Gerd; Sattler, Michael; Striggow, Frank; Groll, Michael; Richter, Klaus

2015-04-20

Protein phosphatase 5 (PP5) is an evolutionary conserved serine/threonine phosphatase. Its dephosphorylation activity modulates a diverse set of cellular factors including protein kinases and the microtubule-associated tau protein involved in neurodegenerative disorders. It is auto-regulated by its heat-shock protein (Hsp90)-interacting tetratricopeptide repeat (TPR) domain and its C-terminal α-helix. In the present study, we report the identification of five specific PP5 activators [PP5 small-molecule activators (P5SAs)] that enhance the phosphatase activity up to 8-fold. The compounds are allosteric modulators accelerating efficiently the turnover rate of PP5, but do barely affect substrate binding or the interaction between PP5 and the chaperone Hsp90. Enzymatic studies imply that the compounds bind to the phosphatase domain of PP5. For the most promising compound crystallographic comparisons of the apo PP5 and the PP5-P5SA-2 complex indicate a relaxation of the auto-inhibited state of PP5. Residual electron density and mutation analyses in PP5 suggest activator binding to a pocket in the phosphatase/TPR domain interface, which may exert regulatory functions. These compounds thus may expose regulatory mechanisms in the PP5 enzyme and serve to develop optimized activators based on these scaffolds. © 2015 Authors.
Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs.

PubMed

Le, Nguyen-Quoc-Khanh; Ou, Yu-Yen

2016-07-30

Cellular respiration is a catabolic pathway for producing adenosine triphosphate (ATP) and is the most efficient process through which cells harvest energy from consumed food. When cells undergo cellular respiration, they require a pathway to keep and transfer electrons (i.e., the electron transport chain). Due to oxidation-reduction reactions, the electron transport chain produces a transmembrane proton electrochemical gradient. In case protons flow back through this membrane, this mechanical energy is converted into chemical energy by ATP synthase. The convert process is involved in producing ATP which provides energy in a lot of cellular processes. In the electron transport chain process, flavin adenine dinucleotide (FAD) is one of the most vital molecules for carrying and transferring electrons. Therefore, predicting FAD binding sites in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. We used an independent data set to evaluate the performance of the proposed method, which had an accuracy of 69.84 %. We compared the performance of the proposed method in analyzing two newly discovered electron transport protein sequences with that of the general FAD binding predictor presented by Mishra and Raghava and determined that the accuracy of the proposed method improved by 9-45 % and its Matthew's correlation coefficient was 0.14-0.5. Furthermore, the proposed method enabled reducing the number of false positives significantly and can provide useful information for biologists. We developed a method that is based on PSSM profiles and SAAPs for identifying FAD binding sites in newly discovered electron transport protein sequences. This approach achieved a significant improvement after we added SAAPs to PSSM features to analyze FAD binding proteins in the electron transport chain. The proposed method can serve as an effective tool for predicting FAD binding sites in electron transport proteins and can help biologists understand the functions of the electron transport chain, particularly those of FAD binding sites. We also developed a web server which identifies FAD binding sites in electron transporters available for academics.
Virtual screening using molecular simulations.

PubMed

Yang, Tianyi; Wu, Johnny C; Yan, Chunli; Wang, Yuanfeng; Luo, Ray; Gonzales, Michael B; Dalby, Kevin N; Ren, Pengyu

2011-06-01

Effective virtual screening relies on our ability to make accurate prediction of protein-ligand binding, which remains a great challenge. In this work, utilizing the molecular-mechanics Poisson-Boltzmann (or Generalized Born) surface area approach, we have evaluated the binding affinity of a set of 156 ligands to seven families of proteins, trypsin β, thrombin α, cyclin-dependent kinase (CDK), cAMP-dependent kinase (PKA), urokinase-type plasminogen activator, β-glucosidase A, and coagulation factor Xa. The effect of protein dielectric constant in the implicit-solvent model on the binding free energy calculation is shown to be important. The statistical correlations between the binding energy calculated from the implicit-solvent approach and experimental free energy are in the range of 0.56-0.79 across all the families. This performance is better than that of typical docking programs especially given that the latter is directly trained using known binding data whereas the molecular mechanics is based on general physical parameters. Estimation of entropic contribution remains the barrier to accurate free energy calculation. We show that the traditional rigid rotor harmonic oscillator approximation is unable to improve the binding free energy prediction. Inclusion of conformational restriction seems to be promising but requires further investigation. On the other hand, our preliminary study suggests that implicit-solvent based alchemical perturbation, which offers explicit sampling of configuration entropy, can be a viable approach to significantly improve the prediction of binding free energy. Overall, the molecular mechanics approach has the potential for medium to high-throughput computational drug discovery. Copyright © 2011 Wiley-Liss, Inc.
A high ratio of insulin-like growth factor II/insulin-like growth factor binding protein 2 messenger RNA as a marker for anaplasia in meningiomas.

PubMed

Nordqvist, A C; Peyrard, M; Pettersson, H; Mathiesen, T; Collins, V P; Dumanski, J P; Schalling, M

1997-07-01

Insulin-like growth factors (IGFs) I and II have been implicated as autocrine or paracrine growth promoters. These growth factors bind to specific receptors, and the response is modulated by interaction with IGF-binding proteins (IGFBPs). We observed a strong correlation between anaplastic/atypical histopathology and a high IGF-II/IGFBP-2 mRNA ratio in a set of 68 sporadic meningiomas. A strong correlation was also found between clinical outcome and IGF-II/IGFBP-2 ratio, whereas previously used histochemical markers were less correlated to outcome. We suggest that a high IGF-II/IGFBP-2 mRNA ratio may be a sign of biologically aggressive behavior in meningiomas that can influence treatment strategies. We propose that low IGFBP-2 levels in combination with increased levels of IGF-II would result in more free IGF-II and consequently greater stimulation of proliferation.

Phosphatidic acid binding proteins display differential binding as a function of membrane curvature stress and chemical properties.

PubMed

Putta, Priya; Rankenberg, Johanna; Korver, Ruud A; van Wijk, Ringo; Munnik, Teun; Testerink, Christa; Kooijman, Edgar E

2016-11-01

Phosphatidic acid (PA) is a crucial membrane phospholipid involved in de novo lipid synthesis and numerous intracellular signaling cascades. The signaling function of PA is mediated by peripheral membrane proteins that specifically recognize PA. While numerous PA-binding proteins are known, much less is known about what drives specificity of PA-protein binding. Previously, we have described the ionization properties of PA, summarized in the electrostatic-hydrogen bond switch, as one aspect that drives the specific binding of PA by PA-binding proteins. Here we focus on membrane curvature stress induced by phosphatidylethanolamine and show that many PA-binding proteins display enhanced binding as a function of negative curvature stress. This result is corroborated by the observation that positive curvature stress, induced by lyso phosphatidylcholine, abolishes PA binding of target proteins. We show, for the first time, that a novel plant PA-binding protein, Arabidopsis Epsin-like Clathrin Adaptor 1 (ECA1) displays curvature-dependence in its binding to PA. Other established PA targets examined in this study include, the plant proteins TGD2, and PDK1, the yeast proteins Opi1 and Spo20, and, the mammalian protein Raf-1 kinase and the C2 domain of the mammalian phosphatidylserine binding protein Lact as control. Based on our observations, we propose that liposome binding assays are the preferred method to investigate lipid binding compared to the popular lipid overlay assays where membrane environment is lost. The use of complex lipid mixtures is important to elucidate further aspects of PA binding proteins. Copyright © 2016. Published by Elsevier B.V.
Specific and Non-Specific Protein Association in Solution: Computation of Solvent Effects and Prediction of First-Encounter Modes for Efficient Configurational Bias Monte Carlo Simulations

PubMed Central

Cardone, Antonio; Pant, Harish; Hassan, Sergio A.

2013-01-01

Weak and ultra-weak protein-protein association play a role in molecular recognition, and can drive spontaneous self-assembly and aggregation. Such interactions are difficult to detect experimentally, and are a challenge to the force field and sampling technique. A method is proposed to identify low-population protein-protein binding modes in aqueous solution. The method is designed to identify preferential first-encounter complexes from which the final complex(es) at equilibrium evolves. A continuum model is used to represent the effects of the solvent, which accounts for short- and long-range effects of water exclusion and for liquid-structure forces at protein/liquid interfaces. These effects control the behavior of proteins in close proximity and are optimized based on binding enthalpy data and simulations. An algorithm is described to construct a biasing function for self-adaptive configurational-bias Monte Carlo of a set of interacting proteins. The function allows mixing large and local changes in the spatial distribution of proteins, thereby enhancing sampling of relevant microstates. The method is applied to three binary systems. Generalization to multiprotein complexes is discussed. PMID:24044772
Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning

NASA Astrophysics Data System (ADS)

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-04-01

Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.
Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning.

PubMed

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-04-18

Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.
In Silico Prediction and Validation of Novel RNA Binding Proteins and Residues in the Human Proteome.

PubMed

Chowdhury, Shomeek; Zhang, Jian; Kurgan, Lukasz

2018-05-28

Deciphering a complete landscape of protein-RNA interactions in the human proteome remains an elusive challenge. We computationally elucidate RNA binding proteins (RBPs) using an approach that complements previous efforts. We employ two modern complementary sequence-based methods that provide accurate predictions from the structured and the intrinsically disordered sequences, even in the absence of sequence similarity to the known RBPs. We generate and analyze putative RNA binding residues on the whole proteome scale. Using a conservative setting that ensures low, 5% false positive rate, we identify 1511 putative RBPs that include 281 known RBPs and 166 RBPs that were previously predicted. We empirically demonstrate that these overlaps are statistically significant. We also validate the putative RBPs based on two major hallmarks of their RNA binding residues: high levels of evolutionary conservation and enrichment in charged amino acids. Moreover, we show that the novel RBPs are significantly under-annotated functionally which coincides with the fact that they were not yet found to interact with RNAs. We provide two examples of our novel putative RBPs for which there is recent evidence of their interactions with RNAs. The dataset of novel putative RBPs and RNA binding residues for the future hypothesis generation is provided in the Supporting Information. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Computational biology of RNA interactions.

PubMed

Dieterich, Christoph; Stadler, Peter F

2013-01-01

The biodiversity of the RNA world has been underestimated for decades. RNA molecules are key building blocks, sensors, and regulators of modern cells. The biological function of RNA molecules cannot be separated from their ability to bind to and interact with a wide space of chemical species, including small molecules, nucleic acids, and proteins. Computational chemists, physicists, and biologists have developed a rich tool set for modeling and predicting RNA interactions. These interactions are to some extent determined by the binding conformation of the RNA molecule. RNA binding conformations are approximated with often acceptable accuracy by sequence and secondary structure motifs. Secondary structure ensembles of a given RNA molecule can be efficiently computed in many relevant situations by employing a standard energy model for base pair interactions and dynamic programming techniques. The case of bi-molecular RNA-RNA interactions can be seen as an extension of this approach. However, unbiased transcriptome-wide scans for local RNA-RNA interactions are computationally challenging yet become efficient if the binding motif/mode is known and other external information can be used to confine the search space. Computational methods are less developed for proteins and small molecules, which bind to RNA with very high specificity. Binding descriptors of proteins are usually determined by in vitro high-throughput assays (e.g., microarrays or sequencing). Intriguingly, recent experimental advances, which are mostly based on light-induced cross-linking of binding partners, render in vivo binding patterns accessible yet require new computational methods for careful data interpretation. The grand challenge is to model the in vivo situation where a complex interplay of RNA binders competes for the same target RNA molecule. Evidently, bioinformaticians are just catching up with the impressive pace of these developments. Copyright © 2012 John Wiley & Sons, Ltd.
Autoimmune Regulator (AIRE) Is Expressed in Spermatogenic Cells, and It Altered the Expression of Several Nucleic-Acid-Binding and Cytoskeletal Proteins in Germ Cell 1 Spermatogonial (GC1-spg) Cells.

PubMed

Radhakrishnan, Karthika; Bhagya, Kongattu P; Kumar, Anil Tr; Devi, Anandavalli N; Sengottaiyan, Jeeva; Kumar, Pradeep G

2016-08-01

Autoimmune regulator (AIRE) is a gene associated with autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED). AIRE is expressed heavily in the thymic epithelial cells and is involved in maintaining self-tolerance through regulating the expression of tissue-specific antigens. The testes are the most predominant extrathymic location where a heavy expression of AIRE is reported. Homozygous Aire-deficient male mice were infertile, possibly due to impaired spermatogenesis, deregulated germ cell apoptosis, or autoimmunity. We report that AIRE is expressed in the testes of neonatal, adolescent, and adult mice. AIRE expression was detected in glial cell derived neurotrophic factor receptor alpha (GFRα)(+) (spermatogonia), GFRα(-)/synaptonemal complex protein (SCP3)(+) (meiotic), and GFRα(-)/Phosphoglycerate kinase 2 (PGK2)(+) (postmeiotic) germ cells in mouse testes. GC1-spg, a germ-cell-derived cell line, did not express AIRE. Retinoic acid induced AIRE expression in GC1-spg cells. Ectopic expression of AIRE in GC1-spg cells using label-free LC-MS/MS identified a total of 371 proteins that were differentially expressed. 100 proteins were up-regulated, and 271 proteins were down-regulated. Data are available via ProteomeXchange with identifier PXD002511. Functional analysis of the differentially expressed proteins showed increased levels of various nucleic-acid-binding proteins and transcription factors and a decreased level of various cytoskeletal and structural proteins in the AIRE overexpressing cells as compared with the empty vector-transfected controls. The transcripts of a select set of the up-regulated proteins were also elevated. However, there was no corresponding decrease in the mRNA levels of the down-regulated set of proteins. Molecular function network analysis indicated that AIRE influenced gene expression in GC1-spg cells by acting at multiple levels, including transcription, translation, RNA processing, protein transport, protein localization, and protein degradation, thus setting the foundation in understanding the functional role of AIRE in germ cell biology. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
NPIDB: Nucleic acid-Protein Interaction DataBase.

PubMed

Kirsanov, Dmitry D; Zanegina, Olga N; Aksianov, Evgeniy A; Spirin, Sergei A; Karyagina, Anna S; Alexeevski, Andrei V

2013-01-01

The Nucleic acid-Protein Interaction DataBase (http://npidb.belozersky.msu.ru/) contains information derived from structures of DNA-protein and RNA-protein complexes extracted from the Protein Data Bank (3846 complexes in October 2012). It provides a web interface and a set of tools for extracting biologically meaningful characteristics of nucleoprotein complexes. The content of the database is updated weekly. The current version of the Nucleic acid-Protein Interaction DataBase is an upgrade of the version published in 2007. The improvements include a new web interface, new tools for calculation of intermolecular interactions, a classification of SCOP families that contains DNA-binding protein domains and data on conserved water molecules on the DNA-protein interface.
A computational analysis of the binding model of MDM2 with inhibitors

NASA Astrophysics Data System (ADS)

Hu, Guodong; Wang, Dunyou; Liu, Xinguo; Zhang, Qinggang

2010-08-01

It is a new and promising strategy for anticancer drug design to block the MDM2-p53 interaction using a non-peptide small-molecule inhibitor. We carry out molecular dynamics simulations to study the binding of a set of six non-peptide small-molecule inhibitors with the MDM2. The relative binding free energies calculated using molecular mechanics Poisson-Boltzmann surface area method produce a good correlation with experimentally determined results. The study shows that the van der Waals energies are the largest component of the binding free energy for each complex, which indicates that the affinities of these inhibitors for MDM2 are dominated by shape complementarity. The A-ligands and the B-ligands are the same except for the conformation of 2,2-dimethylbutane group. The quantum mechanics and the binding free energies calculation also show the B-ligands are the more possible conformation of ligands. Detailed binding free energies between inhibitors and individual protein residues are calculated to provide insights into the inhibitor-protein binding model through interpretation of the structural and energetic results from the simulations. The study shows that G1, G2 and G3 group mimic the Phe19, Trp23 and Leu26 residues in p53 and their interactions with MDM2, but the binding model of G4 group differs from the original design strategy to mimic Leu22 residue in p53.
Engineered protein scaffolds as next-generation antibody therapeutics.

PubMed

Gebauer, Michaela; Skerra, Arne

2009-06-01

Antibodies have been the paradigm of binding proteins with desired specificities for more than one century and during the past decade their recombinant or humanized versions have entered clinical application with remarkable success. Meanwhile, a new generation of receptor proteins was born, which is derived from small and robust non-immunoglobulin "scaffolds" that can be equipped with prescribed binding functions using the methods of combinatorial protein design. Their ongoing development does not only provide valuable insights into the principles of molecular recognition and protein structure-function relationships but also yields novel reagents for medical use. This technology goes hand in hand with our expanding knowledge about the molecular pathologies of cancer, immunological, and infectious diseases. Currently, questions regarding the choice of suitable medically relevant targets with regard to a certain protein scaffold, the methodology for engineering high affinity, arming with effector functions, routes of administration, plasma half-life, and immunogenicity are in the focus. While many protein scaffolds have been proposed during the past years, the technology shows a trend toward consolidation with a smaller set of systems that are being applied against multiple targets and in different settings, with emphasis on the development of drug candidates for therapy or in vivo diagnostics: Adnectins, Affibodies, Anticalins, DARPins, and engineered Kunitz-type inhibitors, among others. Only few data from early clinical studies are available yet, but many more are likely to come in the near future, thus providing a growing basis for assessing the therapeutic potential--but possibly also some limitations--of this exciting new class of protein drugs.
Regulation of adeno-associated virus DNA replication by the cellular TAF-I/set complex.

PubMed

Pegoraro, Gianluca; Marcello, Alessandro; Myers, Michael P; Giacca, Mauro

2006-07-01

The Rep proteins of the adeno-associated virus (AAV) are required for viral replication in the presence of adenovirus helper functions and as yet poorly characterized cellular factors. In an attempt to identify such factors, we purified Flag-Rep68-interacting proteins from human cell lysates. Several polypeptides were identified by mass spectrometry, among which was ANP32B, a member of the acidic nuclear protein 32 family which takes part in the formation of the template-activating factor I/Set oncoprotein (TAF-I/Set) complex. The N terminus of Rep was found to specifically bind the acidic domain of ANP32B; through this interaction, Rep was also able to recruit other members of the TAF-I/Set complex, including the ANP32A protein and the histone chaperone TAF-I/Set. Further experiments revealed that silencing of ANP32A and ANP32B inhibited AAV replication, while overexpression of all of the components of the TAF-I/Set complex increased de novo AAV DNA synthesis in permissive cells. Besides being the first indication that the TAF-I/Set complex participates in wild-type AAV replication, these findings have important implications for the generation of recombinant AAV vectors since overexpression of the TAF-I/Set components was found to markedly increase viral vector production.
Thioredoxin binding protein (TBP)-2/Txnip and α-arrestin proteins in cancer and diabetes mellitus

PubMed Central

Masutani, Hiroshi; Yoshihara, Eiji; Masaki, So; Chen, Zhe; Yodoi, Junji

2012-01-01

Thioredoxin binding protein −2/ thioredoxin interacting protein is an α-arrestin protein that has attracted much attention as a multifunctional regulator. Thioredoxin binding protein −2 expression is downregulated in tumor cells and the level of thioredoxin binding protein is correlated with clinical stage of cancer. Mice with mutations or knockout of the thioredoxin binding protein −2 gene are much more susceptible to carcinogenesis than wild-type mice, indicating a role for thioredoxin binding protein −2 in cancer suppression. Studies have also revealed roles for thioredoxin binding protein −2 in metabolic control. Enhancement of thioredoxin binding protein −2 expression causes impairment of insulin sensitivity and glucose-induced insulin secretion, and β-cell apoptosis. These changes are important characteristics of type 2 diabetes mellitus. Thioredoxin binding protein −2 regulates transcription of metabolic regulating genes. Thioredoxin binding protein −2-like inducible membrane protein/ arrestin domain containing 3 regulates endocytosis of receptors such as the β2-adrenergic receptor. The α-arrestin family possesses PPXY motifs and may function as an adaptor/scaffold for NEDD family ubiquitin ligases. Elucidation of the molecular mechanisms of α-arrestin proteins would provide a new pharmacological basis for developing approaches against cancer and type 2 diabetes mellitus. PMID:22247597
Sequence Discrimination by Alternatively Spliced Isoforms of a DNA Binding Zinc Finger Domain

NASA Astrophysics Data System (ADS)

Gogos, Joseph A.; Hsu, Tien; Bolton, Jesse; Kafatos, Fotis C.

1992-09-01

Two major developmentally regulated isoforms of the Drosophila chorion transcription factor CF2 differ by an extra zinc finger within the DNA binding domain. The preferred DNA binding sites were determined and are distinguished by an internal duplication of TAT in the site recognized by the isoform with the extra finger. The results are consistent with modular interactions between zinc fingers and trinucleotides and also suggest rules for recognition of AT-rich DNA sites by zinc finger proteins. The results show how modular finger interactions with trinucleotides can be used, in conjunction with alternative splicing, to alter the binding specificity and increase the spectrum of sites recognized by a DNA binding domain. Thus, CF2 may potentially regulate distinct sets of target genes during development.
Discovery of binding proteins for a protein target using protein-protein docking-based virtual screening.

PubMed

Zhang, Changsheng; Tang, Bo; Wang, Qian; Lai, Luhua

2014-10-01

Target structure-based virtual screening, which employs protein-small molecule docking to identify potential ligands, has been widely used in small-molecule drug discovery. In the present study, we used a protein-protein docking program to identify proteins that bind to a specific target protein. In the testing phase, an all-to-all protein-protein docking run on a large dataset was performed. The three-dimensional rigid docking program SDOCK was used to examine protein-protein docking on all protein pairs in the dataset. Both the binding affinity and features of the binding energy landscape were considered in the scoring function in order to distinguish positive binding pairs from negative binding pairs. Thus, the lowest docking score, the average Z-score, and convergency of the low-score solutions were incorporated in the analysis. The hybrid scoring function was optimized in the all-to-all docking test. The docking method and the hybrid scoring function were then used to screen for proteins that bind to tumor necrosis factor-α (TNFα), which is a well-known therapeutic target for rheumatoid arthritis and other autoimmune diseases. A protein library containing 677 proteins was used for the screen. Proteins with scores among the top 20% were further examined. Sixteen proteins from the top-ranking 67 proteins were selected for experimental study. Two of these proteins showed significant binding to TNFα in an in vitro binding study. The results of the present study demonstrate the power and potential application of protein-protein docking for the discovery of novel binding proteins for specific protein targets. © 2014 Wiley Periodicals, Inc.
A Screen for Novel Phosphoinositide 3-kinase Effector Proteins*

PubMed Central

Dixon, Miles J.; Gray, Alexander; Boisvert, François-Michel; Agacan, Mark; Morrice, Nicholas A.; Gourlay, Robert; Leslie, Nicholas R.; Downes, C. Peter; Batty, Ian H.

2011-01-01

Class I phosphoinositide 3-kinases exert important cellular effects through their two primary lipid products, phosphatidylinositol 3,4,5-trisphosphate and phosphatidylinositol 3,4-bisphosphate (PtdIns(3,4)P2). As few molecular targets for PtdIns(3,4)P2 have yet been identified, a screen for PI 3-kinase-responsive proteins that is selective for these is described. This features a tertiary approach incorporating a unique, primary recruitment of target proteins in intact cells to membranes selectively enriched in PtdIns(3,4)P2. A secondary purification of these proteins, optimized using tandem pleckstrin homology domain containing protein-1 (TAPP-1), an established PtdIns(3,4)P2 selective ligand, yields a fraction enriched in proteins of potentially similar lipid binding character that are identified by liquid chromatography-tandem MS. Thirdly, this approach is coupled to stable isotope labeling with amino acids in cell culture using differential isotope labeling of cells stimulated in the absence and presence of the PI 3-kinase inhibitor wortmannin. This provides a ratio-metric readout that distinguishes authentically responsive components from copurifying background proteins. Enriched fractions thus obtained from astrocytoma cells revealed a subset of proteins that exhibited ratios indicative of their initial, cellular responsiveness to PI 3-kinase activation. The inclusion among these of tandem pleckstrin homology domain containing protein-1, three isoforms of Akt, switch associated protein-70, early endosome antigen-1 and of additional proteins expressing recognized lipid binding domains demonstrates the utility of this strategy and lends credibility to the novel candidate proteins identified. The latter encompass a broad set of proteins that include the gene product of TBC1D2A, a putative Rab guanine nucleotide triphosphatase activating protein (GAP) and IQ motif containing GAP1, a potential tumor promoter. A sequence comparison of the former protein indicates the presence of a pleckstrin homology domain whose lipid binding character remains to be established. IQ motif containing GAP1 lacks known lipid interacting components and a preliminary analysis here indicates that this may exemplify a novel class of atypical phosphoinositide (aPI) binding domain. PMID:21263009
Molecular Docking Studies of Flavonoids Derivatives on the Flavonoid 3- O-Glucosyltransferase.

PubMed

Harsa, Alexandra M; Harsa, Teodora E; Diudea, Mircea V; Janezic, Dusanka

2015-01-01

A study of 30 flavonoid derivatives, taken from PubChem database and docked on flavonoid 3-O-glucosyltransferase 3HBF, next submitted to a QSAR study, performed within a hypermolecule frame, to model their LD50 values, is reported. The initial set of molecules was split into a training set and the test set (taken from the best scored molecules in the docking test); the predicted LD50 values, computed on similarity clusters, built up for each of the molecules of the test set, surpassed in accuracy the best model. The binding energies to 3HBF protein, provided by the docking step, are not related to the LD50 of these flavonoids, more protein targets are to be investigated in this respect. However, the docking step was useful in choosing the test set of molecules.
Novel, customizable scoring functions, parameterized using N-PLS, for structure-based drug discovery.

PubMed

Catana, Cornel; Stouten, Pieter F W

2007-01-01

The ability to accurately predict biological affinity on the basis of in silico docking to a protein target remains a challenging goal in the CADD arena. Typically, "standard" scoring functions have been employed that use the calculated docking result and a set of empirical parameters to calculate a predicted binding affinity. To improve on this, we are exploring novel strategies for rapidly developing and tuning "customized" scoring functions tailored to a specific need. In the present work, three such customized scoring functions were developed using a set of 129 high-resolution protein-ligand crystal structures with measured Ki values. The functions were parametrized using N-PLS (N-way partial least squares), a multivariate technique well-known in the 3D quantitative structure-activity relationship field. A modest correlation between observed and calculated pKi values using a standard scoring function (r2 = 0.5) could be improved to 0.8 when a customized scoring function was applied. To mimic a more realistic scenario, a second scoring function was developed, not based on crystal structures but exclusively on several binding poses generated with the Flo+ docking program. Finally, a validation study was conducted by generating a third scoring function with 99 randomly selected complexes from the 129 as a training set and predicting pKi values for a test set that comprised the remaining 30 complexes. Training and test set r2 values were 0.77 and 0.78, respectively. These results indicate that, even without direct structural information, predictive customized scoring functions can be developed using N-PLS, and this approach holds significant potential as a general procedure for predicting binding affinity on the basis of in silico docking.
Characterization of Sodium Mobility and Binding by 23 Na NMR Spectroscopy in a Model Lipoproteic Emulsion Gel for Sodium Reduction.

PubMed

Okada, Kyle S; Lee, Youngsoo

2017-07-01

The effects of formulation and processing parameters on sodium availability in a model lipid/protein-based emulsion gel were studied for purposes of sodium reduction. Heat-set model gels were prepared with varying levels of protein, lipid, and NaCl contents and high pressure homogenization treatments. Single quantum and double quantum-filtered 23 Na NMR spectroscopy experiments were used to characterize sodium mobility, structural order around "bound" (restricted mobility) sodium, and sodium binding, which have been correlated to saltiness perception in food systems previously. Total sodium mobility was lower in gels with higher protein or fat content, and was not affected by changes in homogenization pressure. The gels with increased protein, fat, or homogenization pressure had increased structure surrounding "bound" sodium and more relative "bound" sodium due to increased interfacial protein interactions. The data obtained in this study provide information on factors affecting sodium availability, which can be applied towards sodium reduction in lipid/protein-based foods. © 2017 Institute of Food Technologists®.
The mammalian RNA-binding protein Staufen2 links nuclear and cytoplasmic RNA processing pathways in neurons.

PubMed

Monshausen, Michaela; Gehring, Niels H; Kosik, Kenneth S

2004-01-01

Members of the Staufen family of RNA-binding proteins are highly conserved cytoplasmic RNA transporters associated with RNA granules. staufen2 is specifically expressed in neurons where the delivery of RNA to dendrites is thought to have a role in plasticity. We found that Staufen2 interacts with the nuclear pore protein p62, with the RNA export protein Tap and with the exon-exon junction complex (EJC) proteins Y14-Mago. The interaction of Staufen2 with the Y14-Mago heterodimer seems to represent a highly conserved complex as the same proteins are involved in the Staufen-mediated localization of oskar mRNA in Drosophila oocytes. A pool of Staufen2 is present in neuronal nuclei and colocalizes to a large degree with p62 and partly with Tap, Y14, and Mago. We suggest a model whereby a set of conserved genes in the oskar mRNA export pathway may be recruited to direct a dendritic destination for mRNAs originating as a Staufen2 nuclear complex.
Deriving an explicit hepatic clearance equation accounting for plasma protein binding and hepatocellular uptake.

PubMed

Yoon, Miyoung; Clewell, Harvey J; Andersen, Melvin E

2013-02-01

High throughput in vitro biochemical and cell-based assays have the promise to provide more mechanism-based assessments of the adverse effects of large numbers of chemicals. One of the most challenging hurdles for interpreting in vitro toxicity findings is the need for reverse dosimetry tools that estimate the exposures that will give concentrations in vivo similar to the active concentrations in vitro. Recent experience using IVIVE approaches to estimate in vivo pharmacokinetics (Wetmore et al., 2012) identified the need to develop a hepatic clearance equation that explicitly accounted for a broader set of protein binding and membrane transport processes and did not depend on a well-mixed description of the liver compartment. Here we derive an explicit steady-state hepatic clearance equation that includes these factors. In addition to the derivation, we provide simple computer code to calculate steady-state extraction for any combination of blood flow, membrane transport processes and plasma protein-chemical binding rates. This expanded equation provides a tool to estimate hepatic clearance for a more diverse array of compounds. Copyright © 2012 Elsevier Ltd. All rights reserved.

Sequence-Specific Recognition of DNA by Proteins: Binding Motifs Discovered Using a Novel Statistical/Computational Analysis

PubMed Central

Jakubec, David; Laskowski, Roman A.; Vondrasek, Jiri

2016-01-01

Decades of intensive experimental studies of the recognition of DNA sequences by proteins have provided us with a view of a diverse and complicated world in which few to no features are shared between individual DNA-binding protein families. The originally conceived direct readout of DNA residue sequences by amino acid side chains offers very limited capacity for sequence recognition, while the effects of the dynamic properties of the interacting partners remain difficult to quantify and almost impossible to generalise. In this work we investigated the energetic characteristics of all DNA residue—amino acid side chain combinations in the conformations found at the interaction interface in a very large set of protein—DNA complexes by the means of empirical potential-based calculations. General specificity-defining criteria were derived and utilised to look beyond the binding motifs considered in previous studies. Linking energetic favourability to the observed geometrical preferences, our approach reveals several additional amino acid motifs which can distinguish between individual DNA bases. Our results remained valid in environments with various dielectric properties. PMID:27384774
Food proteins and maturation of small intestinal microvillus membranes (MVM). I. Binding characteristics of cow's milk proteins and concanavalin A to MVM from newborn and adult rats.

PubMed

Stern, M; Gellermann, B

1988-01-01

To study maturational changes of food protein and lectin binding to rat small intestinal microvillus membranes (MVM), MVM were prepared from newborn and adult animals by a modified CaCl2 precipitation technique. Radiolabeled cow's milk proteins [alpha-lactalbumin, alpha-casein, beta-lactoglobulin, bovine serum albumin (BSA)] and the lectin concanavalin A (Con A) were used for incubations. Binding assays were done using miniature ultracentrifugation for separation of unbound material. Binding of Con A to MVM from newborn and adult rats was strong, specific, and saturable. Binding of Con A was inhibited by cold Con A and by the sugar ligand polymer mannan. Adult MVM bound more Con A than newborn preparations. Unlike Con A, binding of cow's milk proteins by MVM was weak, nonspecific, and noninhibitable. Newborn MVM bound more cow's milk proteins than adult controls. This was true for all the proteins tested (p less than 0.001). Binding rose with decreased molecular weight of cow's milk proteins, but molecular weight was not the only determining factor for binding. Trypsin treatment of MVM caused a marked increase of BSA binding in adult but not in newborn preparations. This finding indicated the importance of protein components of MVM for cow's milk protein binding. Maturational changes in protein-lipid interactions and membrane fluidity possibly influence nonspecific cow's milk protein binding to MVM. Differences in binding between newborns and adults were not directly related to maturational shifts in membrane glycosylation that are indicated by differential Con A binding. Increased cow's milk protein binding in newborn individuals might increase the potential risk to develop an adverse reaction to food proteins.
Probing the Energetics of Dynactin Filament Assembly and the Binding of Cargo Adaptor Proteins Using Molecular Dynamics Simulation and Electrostatics-Based Structural Modeling.

PubMed

Zheng, Wenjun

2017-01-10

Dynactin, a large multiprotein complex, binds with the cytoplasmic dynein-1 motor and various adaptor proteins to allow recruitment and transportation of cellular cargoes toward the minus end of microtubules. The structure of the dynactin complex is built around an actin-like minifilament with a defined length, which has been visualized in a high-resolution structure of the dynactin filament determined by cryo-electron microscopy (cryo-EM). To understand the energetic basis of dynactin filament assembly, we used molecular dynamics simulation to probe the intersubunit interactions among the actin-like proteins, various capping proteins, and four extended regions of the dynactin shoulder. Our simulations revealed stronger intersubunit interactions at the barbed and pointed ends of the filament and involving the extended regions (compared with the interactions within the filament), which may energetically drive filament termination by the capping proteins and recruitment of the actin-like proteins by the extended regions, two key features of the dynactin filament assembly process. Next, we modeled the unknown binding configuration among dynactin, dynein tails, and a number of coiled-coil adaptor proteins (including several Bicaudal-D and related proteins and three HOOK proteins), and predicted a key set of charged residues involved in their electrostatic interactions. Our modeling is consistent with previous findings of conserved regions, functional sites, and disease mutations in the adaptor proteins and will provide a structural framework for future functional and mutational studies of these adaptor proteins. In sum, this study yielded rich structural and energetic information about dynactin and associated adaptor proteins that cannot be directly obtained from the cryo-EM structures with limited resolutions.
Mechanism of the G-protein mimetic nanobody binding to a muscarinic G-protein-coupled receptor.

PubMed

Miao, Yinglong; McCammon, J Andrew

2018-03-20

Protein-protein binding is key in cellular signaling processes. Molecular dynamics (MD) simulations of protein-protein binding, however, are challenging due to limited timescales. In particular, binding of the medically important G-protein-coupled receptors (GPCRs) with intracellular signaling proteins has not been simulated with MD to date. Here, we report a successful simulation of the binding of a G-protein mimetic nanobody to the M 2 muscarinic GPCR using the robust Gaussian accelerated MD (GaMD) method. Through long-timescale GaMD simulations over 4,500 ns, the nanobody was observed to bind the receptor intracellular G-protein-coupling site, with a minimum rmsd of 2.48 Å in the nanobody core domain compared with the X-ray structure. Binding of the nanobody allosterically closed the orthosteric ligand-binding pocket, being consistent with the recent experimental finding. In the absence of nanobody binding, the receptor orthosteric pocket sampled open and fully open conformations. The GaMD simulations revealed two low-energy intermediate states during nanobody binding to the M 2 receptor. The flexible receptor intracellular loops contribute remarkable electrostatic, polar, and hydrophobic residue interactions in recognition and binding of the nanobody. These simulations provided important insights into the mechanism of GPCR-nanobody binding and demonstrated the applicability of GaMD in modeling dynamic protein-protein interactions.
A comparison of successful and failed protein interface designs highlights the challenges of designing buried hydrogen bonds

PubMed Central

Stranges, P Benjamin; Kuhlman, Brian

2013-01-01

The accurate design of new protein–protein interactions is a longstanding goal of computational protein design. However, most computationally designed interfaces fail to form experimentally. This investigation compares five previously described successful de novo interface designs with 158 failures. Both sets of proteins were designed with the molecular modeling program Rosetta. Designs were considered a success if a high-resolution crystal structure of the complex closely matched the design model and the equilibrium dissociation constant for binding was less than 10 μM. The successes and failures represent a wide variety of interface types and design goals including heterodimers, homodimers, peptide-protein interactions, one-sided designs (i.e., where only one of the proteins was mutated) and two-sided designs. The most striking feature of the successful designs is that they have fewer polar atoms at their interfaces than many of the failed designs. Designs that attempted to create extensive sets of interface-spanning hydrogen bonds resulted in no detectable binding. In contrast, polar atoms make up more than 40% of the interface area of many natural dimers, and native interfaces often contain extensive hydrogen bonding networks. These results suggest that Rosetta may not be accurately balancing hydrogen bonding and electrostatic energies against desolvation penalties and that design processes may not include sufficient sampling to identify side chains in preordered conformations that can fully satisfy the hydrogen bonding potential of the interface. PMID:23139141
Interaction between phloretin and the red blood cell membrane

PubMed Central

1976-01-01

Phloretin binding to red blood cell components has been characterized at pH6, where binding and inhibitory potency are maximal. Binding to intact red cells and to purified hemoglobin are nonsaturated processes approximately equal in magnitude, which strongly suggests that most of the red cell binding may be ascribed to hemoglobin. This conclusion is supported by the fact that homoglobin-free red cell ghosts can bind only 10% as much phloretin as an equivalent number of red cells. The permeability of the red cell membrane to phloretin has been determined by a direct measurement at the time-course of the phloretin uptake. At a 2% hematocrit, the half time for phloretin uptake is 8.7s, corresponding to a permeability coefficient of 2 x 10(-4) cm/s. The concentration dependence of the binding to ghosts reveals two saturable components. Phloretin binds with high affinity (K diss = 1.5 muM) to about 2.5 x 10(6) sites per cell; it also binds with lower affinity (Kdiss = 54 muM) to a second (5.5 x 10(7) per cell) set of sites. In sonicated total lipid extracts of red cell ghosts, phloretin binding consists of a single, saturable component. Its affinity and total number of sites are not significantly different from those of the low affinity binding process in ghosts. No high affinity binding of phloretin is exhibited by the red cell lipid extracts. Therefore, the high affinity phloretin binding sites are related to membrane proteins, and the low affinity sites result from phloretin binding to lipid. The identification of these two types of binding sites allows phloretin effects on protein-mediated transport processes to be distinguished from effects on the lipid region of the membrane. PMID:5575
Interaction entropy for protein-protein binding

NASA Astrophysics Data System (ADS)

Sun, Zhaoxi; Yan, Yu N.; Yang, Maoyou; Zhang, John Z. H.

2017-03-01

Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interaction entropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interaction entropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.
Interaction entropy for protein-protein binding.

PubMed

Sun, Zhaoxi; Yan, Yu N; Yang, Maoyou; Zhang, John Z H

2017-03-28

Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interactionentropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interactionentropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.
Paxillin associates with poly(A)-binding protein 1 at the dense endoplasmic reticulum and the leading edge of migrating cells.

PubMed

Woods, Alison J; Roberts, Marnie S; Choudhary, Jyoti; Barry, Simon T; Mazaki, Yuichi; Sabe, Hisataka; Morley, Simon J; Critchley, David R; Norman, Jim C

2002-02-22

Using mass spectrometry we have identified proteins which co-immunoprecipitate with paxillin, an adaptor protein implicated in the integrin-mediated signaling pathways of cell motility. A major component of paxillin immunoprecipitates was poly(A)-binding protein 1, a 70-kDa mRNA-binding protein. Poly(A)-binding protein 1 associated with both the alpha and beta isoforms of paxillin, and this was unaffected by RNase treatment consistent with a protein-protein interaction. The NH(2)-terminal region of paxillin (residues 54-313) associated directly with poly(A)-binding protein 1 in cell lysates, and with His-poly(A)-binding protein 1 immobilized in microtiter wells. Binding was specific, saturable and of high affinity (K(d) of approximately 10 nm). Cell fractionation studies showed that at steady state, the bulk of paxillin and poly(A)-binding protein 1 was present in the "dense" polyribosome-associated endoplasmic reticulum. However, inhibition of nuclear export with leptomycin B caused paxillin and poly(A)-binding protein 1 to accumulate in the nucleus, indicating that they shuttle between the nuclear and cytoplasmic compartments. When cells migrate, poly(A)-binding protein 1 colocalized with paxillin-beta at the tips of lamellipodia. Our results suggest a new mechanism whereby a paxillin x poly(A)-binding protein 1 complex facilitates transport of mRNA from the nucleus to sites of protein synthesis at the endoplasmic reticulum and the leading lamella during cell migration.
Modeling backbone flexibility to achieve sequence diversity: The design of novel alpha-helical ligands for Bcl-xL

PubMed Central

Fu, Xiaoran; Apgar, James R.; Keating, Amy E.

2007-01-01

Computational protein design can be used to select sequences that are compatible with a fixed-backbone template. This strategy has been used in numerous instances to engineer novel proteins. However, the fixed-backbone assumption severely restricts the sequence space that is accessible via design. For challenging problems, such as the design of functional proteins, this may not be acceptable. In this paper, we present a method for introducing backbone flexibility into protein design calculations and apply it to the design of diverse helical BH3 ligands that bind to the anti-apoptotic protein Bcl-xL, a member of the Bcl-2 protein family. We demonstrate how normal mode analysis can be used to sample different BH3 backbones, and show that this leads to a larger and more diverse set of low-energy solutions than can be achieved using a native high-resolution Bcl-xL complex crystal structure as a template. We tested several of the designed solutions experimentally and found that this approach worked well when normal mode calculations were used to deform a native BH3 helix structure, but less well when they were used to deform an idealized helix. A subsequent round of design and testing identified a likely source of the problem as inadequate sampling of the helix pitch. In all, we tested seventeen designed BH3 peptide sequences, including several point mutants. Of these, eight bound well to Bcl-xL and four others showed weak but detectable binding. The successful designs showed a diversity of sequences that would have been difficult or impossible to achieve using only a fixed backbone. Thus, introducing backbone flexibility via normal mode analysis effectively broadened the set of sequences identified by computational design, and provided insight into positions important for binding Bcl-xL. PMID:17597151
Comparison of the Folding Mechanism of Highly Homologous Proteins in the Lipid-binding Protein Family

EPA Science Inventory

The folding mechanism of two closely related proteins in the intracellular lipid binding protein family, human bile acid binding protein (hBABP) and rat bile acid binding protein (rBABP) were examined. These proteins are 77% identical (93% similar) in sequence Both of these singl...
Effects of salts on protein-surface interactions: applications for column chromatography.

PubMed

Tsumoto, Kouhei; Ejima, Daisuke; Senczuk, Anna M; Kita, Yoshiko; Arakawa, Tsutomu

2007-07-01

Development of protein pharmaceuticals depends on the availability of high quality proteins. Various column chromatographies are used to purify proteins and characterize the purity and properties of the proteins. Most column chromatographies require salts, whether inorganic or organic, for binding, elution or simply better recovery and resolution. The salts modulate affinity of the proteins for particular columns and nonspecific protein-protein or protein-surface interactions, depending on the type and concentration of the salts, in both specific and nonspecific manners. Salts also affect the binding capacity of the column, which determines the size of the column to be used. Binding capacity, whether equilibrium or dynamic (under an approximation of a slow flow rate), depends on the binding constant, protein concentration and the number of the binding site on the column as well as nonspecific binding. This review attempts to summarize the mechanism of the salt effects on binding affinity and capacity for various column chromatographies and on nonspecific protein-protein or protein-surface interactions. Understanding such salt effects should also be useful in preventing nonspecific protein binding to various containers. Copyright 2007 Wiley-Liss, Inc.
Molecular modelling study of changes induced by netropsin binding to nucleosome core particles.

PubMed Central

Pérez, J J; Portugal, J

1990-01-01

It is well known that certain sequence-dependent modulators in structure appear to determine the rotational positioning of DNA on the nucleosome core particle. That preference is rather weak and could be modified by some ligands as netropsin, a minor-groove binding antibiotic. We have undertaken a molecular modelling approach to calculate the relative energy of interaction between a DNA molecule and the protein core particle. The histones particle is considered as a distribution of positive charges on the protein surface that interacts with the DNA molecule. The molecular electrostatic potentials for the DNA, simulated as a discontinuous cylinder, were calculated using the values for all the base pairs. Computing these parameters, we calculated the relative energy of interaction and the more stable rotational setting of DNA. The binding of four molecules of netropsin to this model showed that a new minimum of energy is obtained when the DNA turns toward the protein surface by about 180 degrees, so a new energetically favoured structure appears where netropsin binding sites are located facing toward the histones surface. The effect of netropsin could be explained in terms of an induced change in the phasing of DNA on the core particle. The induced rotation is considered to optimize non-bonded contacts between the netropsin molecules and the DNA backbone. PMID:2165249
Predicting Protein–protein Association Rates using Coarse-grained Simulation and Machine Learning

PubMed Central

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-01-01

Protein–protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate. PMID:28418043
Functional interactions of nucleocapsid protein of feline immunodeficiency virus and cellular prion protein with the viral RNA.

PubMed

Moscardini, Mila; Pistello, Mauro; Bendinelli, M; Ficheux, Damien; Miller, Jennifer T; Gabus, Caroline; Le Grice, Stuart F J; Surewicz, Witold K; Darlix, Jean-Luc

2002-04-19

All lentiviruses and oncoretroviruses examined so far encode a major nucleic-acid binding protein (nucleocapsid or NC* protein), approximately 2500 molecules of which coat the dimeric RNA genome. Studies on HIV-1 and MoMuLV using in vitro model systems and in vivo have shown that NC protein is required to chaperone viral RNA dimerization and packaging during virus assembly, and proviral DNA synthesis by reverse transcriptase (RT) during infection. The human cellular prion protein (PrP), thought to be the major component of the agent causing transmissible spongiform encephalopathies (TSE), was recently found to possess a strong affinity for nucleic acids and to exhibit chaperone properties very similar to HIV-1 NC protein in the HIV-1 context in vitro. Tight binding of PrP to nucleic acids is proposed to participate directly in the prion disease process. To extend our understanding of lentiviruses and of the unexpected nucleic acid chaperone properties of the human prion protein, we set up an in vitro system to investigate replication of the feline immunodeficiency virus (FIV), which is functionally and phylogenetically distant from HIV-1. The results show that in the FIV model system, NC protein chaperones viral RNA dimerization, primer tRNA(Lys,3) annealing to the genomic primer-binding site (PBS) and minus strand DNA synthesis by the homologous FIV RT. FIV NC protein is able to trigger specific viral DNA synthesis by inhibiting self-priming of reverse transcription. The human prion protein was found to mimic the properties of FIV NC with respect to primer tRNA annealing to the viral RNA and chaperoning minus strand DNA synthesis. Copyright 2002 Elsevier Science Ltd.
Wide screening of phage-displayed libraries identifies immune targets in planta.

PubMed

Rioja, Cristina; Van Wees, Saskia C; Charlton, Keith A; Pieterse, Corné M J; Lorenzo, Oscar; García-Sánchez, Susana

2013-01-01

Microbe-Associated Molecular Patterns and virulence effectors are recognized by plants as a first step to mount a defence response against potential pathogens. This recognition involves a large family of extracellular membrane receptors and other immune proteins located in different sub-cellular compartments. We have used phage-display technology to express and select for Arabidopsis proteins able to bind bacterial pathogens. To rapidly identify microbe-bound phage, we developed a monitoring method based on microarrays. This combined strategy allowed for a genome-wide screening of plant proteins involved in pathogen perception. Two phage libraries for high-throughput selection were constructed from cDNA of plants infected with Pseudomonas aeruginosa PA14, or from combined samples of the virulent isolate DC3000 of Pseudomonas syringae pv. tomato and its avirulent variant avrRpt2. These three pathosystems represent different degrees in the specificity of plant-microbe interactions. Libraries cover up to 2 × 10(7) different plant transcripts that can be displayed as functional proteins on the surface of T7 bacteriophage. A number of these were selected in a bio-panning assay for binding to Pseudomonas cells. Among the selected clones we isolated the ethylene response factor ATERF-1, which was able to bind the three bacterial strains in competition assays. ATERF-1 was rapidly exported from the nucleus upon infiltration of either alive or heat-killed Pseudomonas. Moreover, aterf-1 mutants exhibited enhanced susceptibility to infection. These findings suggest that ATERF-1 contains a microbe-recognition domain with a role in plant defence. To identify other putative pathogen-binding proteins on a genome-wide scale, the copy number of selected-vs.-total clones was compared by hybridizing phage cDNAs with Arabidopsis microarrays. Microarray analysis revealed a set of 472 candidates with significant fold change. Within this set defence-related genes, including well-known targets of bacterial effectors, are over-represented. Other genes non-previously related to defence can be associated through this study with general or strain-specific recognition of Pseudomonas.
Selective enrichment of metal-binding proteins based on magnetic core/shell microspheres functionalized with metal cations.

PubMed

Fang, Caiyun; Zhang, Lei; Zhang, Xiaoqin; Lu, Haojie

2015-06-21

Metal binding proteins play many important roles in a broad range of biological processes. Characterization of metal binding proteins is important for understanding their structure and biological functions, thus leading to a clear understanding of metal associated diseases. The present study is the first to investigate the effectiveness of magnetic microspheres functionalized with metal cations (Ca(2+), Cu(2+), Zn(2+) and Fe(3+)) as the absorbent matrix in IMAC technology to enrich metal containing/binding proteins. The putative metal binding proteins in rat liver were then globally characterized by using this strategy which is very easy to handle and can capture a number of metal binding proteins effectively. In total, 185 putative metal binding proteins were identified from rat liver including some known less abundant and membrane-bound metal binding proteins such as Plcg1, Acsl5, etc. The identified proteins are involved in many important processes including binding, catalytic activity, translation elongation factor activity, electron carrier activity, and so on.
Informing the Human Plasma Protein Binding of ...

EPA Pesticide Factsheets

The free fraction of a xenobiotic in plasma (Fub) is an important determinant of chemical adsorption, distribution, metabolism, elimination, and toxicity, yet experimental plasma protein binding data is scarce for environmentally relevant chemicals. The presented work explores the merit of utilizing available pharmaceutical data to predict Fub for environmentally relevant chemicals via machine learning techniques. Quantitative structure-activity relationship (QSAR) models were constructed with k nearest neighbors (kNN), support vector machines (SVM), and random forest (RF) machine learning algorithms from a training set of 1045 pharmaceuticals. The models were then evaluated with independent test sets of pharmaceuticals (200 compounds) and environmentally relevant ToxCast chemicals (406 total, in two groups of 238 and 168 compounds). The selection of a minimal feature set of 10-15 2D molecular descriptors allowed for both informative feature interpretation and practical applicability domain assessment via a bounded box of descriptor ranges and principal component analysis. The diverse pharmaceutical and environmental chemical sets exhibit similarities in terms of chemical space (99-82% overlap), as well as comparable bias and variance in constructed learning curves. All the models exhibit significant predictability with mean absolute errors (MAE) in the range of 0.10-0.18 Fub. The models performed best for highly bound chemicals (MAE 0.07-0.12), neutrals (MAE 0
Tighter Ligand Binding Can Compensate for Impaired Stability of an RNA-Binding Protein.

PubMed

Wallis, Christopher P; Richman, Tara R; Filipovska, Aleksandra; Rackham, Oliver

2018-06-15

It has been widely shown that ligand-binding residues, by virtue of their orientation, charge, and solvent exposure, often have a net destabilizing effect on proteins that is offset by stability conferring residues elsewhere in the protein. This structure-function trade-off can constrain possible adaptive evolutionary changes of function and may hamper protein engineering efforts to design proteins with new functions. Here, we present evidence from a large randomized mutant library screen that, in the case of PUF RNA-binding proteins, this structural relationship may be inverted and that active-site mutations that increase protein activity are also able to compensate for impaired stability. We show that certain mutations in RNA-protein binding residues are not necessarily destabilizing and that increased ligand-binding can rescue an insoluble, unstable PUF protein. We hypothesize that these mutations restabilize the protein via thermodynamic coupling of protein folding and RNA binding.
Heterodimer Binding Scaffolds Recognition via the Analysis of Kinetically Hot Residues

PubMed Central

Perišić, Ognjen

2018-01-01

Physical interactions between proteins are often difficult to decipher. The aim of this paper is to present an algorithm that is designed to recognize binding patches and supporting structural scaffolds of interacting heterodimer proteins using the Gaussian Network Model (GNM). The recognition is based on the (self) adjustable identification of kinetically hot residues and their connection to possible binding scaffolds. The kinetically hot residues are residues with the lowest entropy, i.e., the highest contribution to the weighted sum of the fastest modes per chain extracted via GNM. The algorithm adjusts the number of fast modes in the GNM’s weighted sum calculation using the ratio of predicted and expected numbers of target residues (contact and the neighboring first-layer residues). This approach produces very good results when applied to dimers with high protein sequence length ratios. The protocol’s ability to recognize near native decoys was compared to the ability of the residue-level statistical potential of Lu and Skolnick using the Sternberg and Vakser decoy dimers sets. The statistical potential produced better overall results, but in a number of cases its predicting ability was comparable, or even inferior, to the prediction ability of the adjustable GNM approach. The results presented in this paper suggest that in heterodimers at least one protein has interacting scaffold determined by the immovable, kinetically hot residues. In many cases, interacting proteins (especially if being of noticeably different sizes) either behave as a rigid lock and key or, presumably, exhibit the opposite dynamic behavior. While the binding surface of one protein is rigid and stable, its partner’s interacting scaffold is more flexible and adaptable. PMID:29547506

Motion Tree Delineates Hierarchical Structure of Protein Dynamics Observed in Molecular Dynamics Simulation

PubMed Central

Moritsugu, Kei; Koike, Ryotaro; Yamada, Kouki; Kato, Hiroaki; Kidera, Akinori

2015-01-01

Molecular dynamics (MD) simulations of proteins provide important information to understand their functional mechanisms, which are, however, likely to be hidden behind their complicated motions with a wide range of spatial and temporal scales. A straightforward and intuitive analysis of protein dynamics observed in MD simulation trajectories is therefore of growing significance with the large increase in both the simulation time and system size. In this study, we propose a novel description of protein motions based on the hierarchical clustering of fluctuations in the inter-atomic distances calculated from an MD trajectory, which constructs a single tree diagram, named a “Motion Tree”, to determine a set of rigid-domain pairs hierarchically along with associated inter-domain fluctuations. The method was first applied to the MD trajectory of substrate-free adenylate kinase to clarify the usefulness of the Motion Tree, which illustrated a clear-cut dynamics picture of the inter-domain motions involving the ATP/AMP lid and the core domain together with the associated amplitudes and correlations. The comparison of two Motion Trees calculated from MD simulations of ligand-free and -bound glutamine binding proteins clarified changes in inherent dynamics upon ligand binding appeared in both large domains and a small loop that stabilized ligand molecule. Another application to a huge protein, a multidrug ATP binding cassette (ABC) transporter, captured significant increases of fluctuations upon binding a drug molecule observed in both large scale inter-subunit motions and a motion localized at a transmembrane helix, which may be a trigger to the subsequent structural change from inward-open to outward-open states to transport the drug molecule. These applications demonstrated the capabilities of Motion Trees to provide an at-a-glance view of various sizes of functional motions inherent in the complicated MD trajectory. PMID:26148295
Molecular Dynamics Simulations and Structural Analysis of Giardia duodenalis 14-3-3 Protein-Protein Interactions.

PubMed

Cau, Ylenia; Fiorillo, Annarita; Mori, Mattia; Ilari, Andrea; Botta, Maurizo; Lalle, Marco

2015-12-28

Giardiasis is a gastrointestinal diarrheal illness caused by the protozoan parasite Giardia duodenalis, which affects annually over 200 million people worldwide. The limited antigiardial drug arsenal and the emergence of clinical cases refractory to standard treatments dictate the need for new chemotherapeutics. The 14-3-3 family of regulatory proteins, extensively involved in protein-protein interactions (PPIs) with pSer/pThr clients, represents a highly promising target. Despite homology with human counterparts, the single 14-3-3 of G. duodenalis (g14-3-3) is characterized by a constitutive phosphorylation in a region critical for target binding, thus affecting the function and the conformation of g14-3-3/clients interaction. However, to approach the design of specific small molecule modulators of g14-3-3 PPIs, structural elucidations are required. Here, we present a detailed computational and crystallographic study exploring the implications of g14-3-3 phosphorylation on protein structure and target binding. Self-Guided Langevin Dynamics and classical molecular dynamics simulations show that phosphorylation affects locally and globally g14-3-3 conformation, inducing a structural rearrangement more suitable for target binding. Profitable features for g14-3-3/clients interaction were highlighted using a hydrophobicity-based descriptor to characterize g14-3-3 client peptides. Finally, the X-ray structure of g14-3-3 in complex with a mode-1 prototype phosphopeptide was solved and combined with structure-based simulations to identify molecular features relevant for clients binding to g14-3-3. The data presented herein provide a further and structural understanding of g14-3-3 features and set the basis for drug design studies.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Morgan, Rhodri M. L.; Pal, Mohinder; Roe, S. Mark

A helix swap involving the fifth helix between two adjacently bound Tah1 molecules restores the normal binding environment of the conserved MEEVD peptide of Hsp90. Dimerization also explains how other monomeric TPR-domain proteins are excluded from forming inappropriate mixed co-chaperone complexes with Hsp90 and Tah1. Specific co-chaperone adaptors facilitate the recruitment of client proteins to the Hsp90 system. Tah1 binds the C-terminal conserved MEEVD motif of Hsp90, thus linking an eclectic set of client proteins to the R2TP complex for their assembly and regulation by Hsp90. Rather than the normal complement of seven α-helices seen in other tetratricopeptide repeat (TPR)more » domains, Tah1 unusually consists of the first five only. Consequently, the methionine of the MEEVD peptide remains exposed to solvent when bound by Tah1. In solution Tah1 appears to be predominantly monomeric, and recent structures have failed to explain how Tah1 appears to prevent the formation of mixed TPR domain-containing complexes such as Cpr6–(Hsp90){sub 2}–Tah1. To understand this further, the crystal structure of Tah1 in complex with the MEEVD peptide of Hsp90 was determined, which shows a helix swap involving the fifth α-helix between two adjacently bound Tah1 molecules. Dimerization of Tah1 restores the normal binding environment of the bound Hsp90 methionine residue by reconstituting a TPR binding site similar to that in seven-helix-containing TPR domain proteins. Dimerization also explains how other monomeric TPR-domain proteins are excluded from forming inappropriate mixed co-chaperone complexes.« less
TgrC1 mediates cell-cell adhesion by interacting with TgrB1 via mutual IPT/TIG domains during development of Dictyostelium discoideum.

PubMed

Chen, Gong; Wang, Jun; Xu, Xiaoqun; Wu, Xiangfu; Piao, Ruihan; Siu, Chi-Hung

2013-06-01

Cell-cell adhesion plays crucial roles in cell differentiation and morphogenesis during development of Dictyostelium discoideum. The heterophilic adhesion protein TgrC1 (Tgr is transmembrane, IPT, IG, E-set, repeat protein) is expressed during cell aggregation, and disruption of the tgrC1 gene results in the arrest of development at the loose aggregate stage. We have used far-Western blotting coupled with MS to identify TgrB1 as the heterophilic binding partner of TgrC1. Co-immunoprecipitation and pull-down studies showed that TgrB1 and TgrC1 are capable of binding with each other in solution. TgrB1 and TgrC1 are encoded by a pair of adjacent genes which share a common promoter. Both TgrB1 and TgrC1 are type I transmembrane proteins, which contain three extracellular IPT/TIG (immunoglobulin, plexin, transcription factor-like/transcription factor immunoglobulin) domains. Antibodies raised against TgrB1 inhibit cell reassociation at the post-aggregation stage of development and block fruiting body formation. Ectopic expression of TgrB1 and TgrC1 driven by the actin15 promoter leads to heterotypic cell aggregation of vegetative cells. Using recombinant proteins that cover different portions of TgrB1 and TgrC1 in binding assays, we have mapped the cell-binding regions in these two proteins to Lys(537)-Ala(783) in TgrB1 and Ile(336)-Val(360) in TgrC1, corresponding to their respective TIG3 and TIG2 domain.
Prediction of binding hot spot residues by using structural and evolutionary parameters.

PubMed

Higa, Roberto Hiroshi; Tozzi, Clésio Luis

2009-07-01

In this work, we present a method for predicting hot spot residues by using a set of structural and evolutionary parameters. Unlike previous studies, we use a set of parameters which do not depend on the structure of the protein in complex, so that the predictor can also be used when the interface region is unknown. Despite the fact that no information concerning proteins in complex is used for prediction, the application of the method to a compiled dataset described in the literature achieved a performance of 60.4%, as measured by F-Measure, corresponding to a recall of 78.1% and a precision of 49.5%. This result is higher than those reported by previous studies using the same data set.
Structural determinants of arrestin functions.

PubMed

Gurevich, Vsevolod V; Gurevich, Eugenia V

2013-01-01

Arrestins are a small protein family with only four members in mammals. Arrestins demonstrate an amazing versatility, interacting with hundreds of different G protein-coupled receptor (GPCR) subtypes, numerous nonreceptor signaling proteins, and components of the internalization machinery, as well as cytoskeletal elements, including regular microtubules and centrosomes. Here, we focus on the structural determinants that mediate various arrestin functions. The receptor-binding elements in arrestins were mapped fairly comprehensively, which set the stage for the construction of mutants targeting particular GPCRs. The elements engaged by other binding partners are only now being elucidated and in most cases we have more questions than answers. Interestingly, even very limited and imprecise identification of structural requirements for the interaction with very few other proteins has enabled the development of signaling-biased arrestin mutants. More comprehensive understanding of the structural underpinning of different arrestin functions will pave the way for the construction of arrestins that can link the receptor we want to the signaling pathway of our choosing. Copyright © 2013 Elsevier Inc. All rights reserved.
Structural Determinants of Arrestin Functions

PubMed Central

Gurevich, Vsevolod V.; Gurevich, Eugenia V.

2015-01-01

Arrestins are a small protein family with only four members in mammals. Arrestins demonstrate an amazing versatility, interacting with hundreds of different G protein-coupled receptor (GPCR) subtypes, numerous nonreceptor signaling proteins, and components of the internalization machinery, as well as cytoskeletal elements, including regular microtubules and centrosomes. Here, we focus on the structural determinants that mediate various arrestin functions. The receptor-binding elements in arrestins were mapped fairly comprehensively, which set the stage for the construction of mutants targeting particular GPCRs. The elements engaged by other binding partners are only now being elucidated and in most cases we have more questions than answers. Interestingly, even very limited and imprecise identification of structural requirements for the interaction with very few other proteins has enabled the development of signaling-biased arrestin mutants. More comprehensive understanding of the structural underpinning of different arrestin functions will pave the way for the construction of arrestins that can link the receptor we want to the signaling pathway of our choosing. PMID:23764050
Joining the dots - protein-RNA interactions mediating local mRNA translation in neurons.

PubMed

Gallagher, Christopher; Ramos, Andres

2018-06-01

Establishing and maintaining the complex network of connections required for neuronal communication requires the transport and in situ translation of large groups of mRNAs to create local proteomes. In this Review, we discuss the regulation of local mRNA translation in neurons and the RNA-binding proteins that recognise RNA zipcode elements and connect the mRNAs to the cellular transport networks, as well as regulate their translation control. However, mRNA recognition by the regulatory proteins is mediated by the combinatorial action of multiple RNA-binding domains. This increases the specificity and affinity of the interaction, while allowing the protein to recognise a diverse set of targets and mediate a range of mechanisms for translational regulation. The structural and molecular understanding of the interactions can be used together with novel microscopy and transcriptome-wide data to build a mechanistic framework for the regulation of local mRNA translation. © 2018 Federation of European Biochemical Societies.
Large scale free energy calculations for blind predictions of protein-ligand binding: the D3R Grand Challenge 2015.

PubMed

Deng, Nanjie; Flynn, William F; Xia, Junchao; Vijayan, R S K; Zhang, Baofeng; He, Peng; Mentes, Ahmet; Gallicchio, Emilio; Levy, Ronald M

2016-09-01

We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein-ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.
Large scale free energy calculations for blind predictions of protein-ligand binding: the D3R Grand Challenge 2015

NASA Astrophysics Data System (ADS)

Deng, Nanjie; Flynn, William F.; Xia, Junchao; Vijayan, R. S. K.; Zhang, Baofeng; He, Peng; Mentes, Ahmet; Gallicchio, Emilio; Levy, Ronald M.

2016-09-01

We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein-ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.
Designed Proteins as Optimized Oxygen Carriers for Artificial Blood

DTIC Science & Technology

2013-02-01

to the lower energy for electron transfer when coupled to a proton transfer from water (3). Thus we set out to compare the rate of solvent...binding affinities and reduction potentials are the sole result of differences in internal electric fields in these proteins wrought by the surface...serving as the source of potential energy for the hexa- to penta-coordinate conformational change, and one in which the b-position glutamates from
Identification of Nuclear Phosphatidylinositol 4,5-Bisphosphate-Interacting Proteins by Neomycin Extraction*

PubMed Central

Lewis, Aurélia E.; Sommer, Lilly; Arntzen, Magnus Ø.; Strahm, Yvan; Morrice, Nicholas A.; Divecha, Nullin; D'Santos, Clive S.

2011-01-01

Considerable insight into phosphoinositide-regulated cytoplasmic functions has been gained by identifying phosphoinositide-effector proteins. Phosphoinositide-regulated nuclear functions however are fewer and less clear. To address this, we established a proteomic method based on neomycin extraction of intact nuclei to enrich for nuclear phosphoinositide-effector proteins. We identified 168 proteins harboring phosphoinositide-binding domains. Although the vast majority of these contained lysine/arginine-rich patches with the following motif, K/R-(Xn = 3–7)-K-X-K/R-K/R, we also identified a smaller subset of known phosphoinositide-binding proteins containing pleckstrin homology or plant homeodomain modules. Proteins with no prior history of phosphoinositide interaction were identified, some of which have functional roles in RNA splicing and processing and chromatin assembly. The remaining proteins represent potentially other novel nuclear phosphoinositide-effector proteins and as such strengthen our appreciation of phosphoinositide-regulated nuclear functions. DNA topology was exemplar among these: Biochemical assays validated our proteomic data supporting a direct interaction between phosphatidylinositol 4,5-bisphosphate and DNA Topoisomerase IIα. In addition, a subset of neomycin extracted proteins were further validated as phosphatidyl 4,5-bisphosphate-interacting proteins by quantitative lipid pull downs. In summary, data sets such as this serve as a resource for a global view of phosphoinositide-regulated nuclear functions. PMID:21048195
Methylation of transcription factor YY2 regulates its transcriptional activity and cell proliferation

PubMed Central

Wu, Xiao-nan; Shi, Tao-tao; He, Yao-hui; Wang, Fei-fei; Sang, Rui; Ding, Jian-cheng; Zhang, Wen-juan; Shu, Xing-yi; Shen, Hai-feng; Yi, Jia; Gao, Xiang; Liu, Wen

2017-01-01

Yin Yang 1 (YY1) is a multifunctional DNA-binding transcription factor shown to be critical in a variety of biological processes, and its activity and function have been shown to be regulated by multitude of mechanisms, which include but are not limited to post-translational modifications (PTMs), its associated proteins and cellular localization. YY2, the paralog of YY1 in mouse and human, has been proposed to function redundantly or oppositely in a context-specific manner compared with YY1. Despite its functional importance, how YY2’s DNA-binding activity and function are regulated, particularly by PTMs, remains completely unknown. Here we report the first PTM with functional characterization on YY2, namely lysine 247 monomethylation (K247me1), which was found to be dynamically regulated by SET7/9 and LSD1 both in vitro and in cultured cells. Functional study revealed that SET7/9-mediated YY2 methylation regulated its DNA-binding activity in vitro and in association with chromatin examined by chromatin immunoprecipitation coupled with sequencing (ChIP-seq) in cultured cells. Knockout of YY2, SET7/9 or LSD1 by CRISPR (clustered, regularly interspaced, short palindromic repeats)/Cas9-mediated gene editing followed by RNA sequencing (RNA-seq) revealed that a subset of genes was positively regulated by YY2 and SET7/9, but negatively regulated by LSD1, which were enriched with genes involved in cell proliferation regulation. Importantly, YY2-regulated gene transcription, cell proliferation and tumor growth were dependent, at least partially, on YY2 K247 methylation. Finally, somatic mutations on YY2 found in cancer, which are in close proximity to K247, altered its methylation, DNA-binding activity and gene transcription it controls. Our findings revealed the first PTM with functional implications imposed on YY2 protein, and linked YY2 methylation with its biological functions. PMID:29098080
Structure-based multiscale approach for identification of interaction partners of PDZ domains.

PubMed

Tiwari, Garima; Mohanty, Debasisa

2014-04-28

PDZ domains are peptide recognition modules which mediate specific protein-protein interactions and are known to have a complex specificity landscape. We have developed a novel structure-based multiscale approach which identifies crucial specificity determining residues (SDRs) of PDZ domains from explicit solvent molecular dynamics (MD) simulations on PDZ-peptide complexes and uses these SDRs in combination with knowledge-based scoring functions for proteomewide identification of their interaction partners. Multiple explicit solvent simulations ranging from 5 to 50 ns duration have been carried out on 28 PDZ-peptide complexes with known binding affinities. MM/PBSA binding energy values calculated from these simulations show a correlation coefficient of 0.755 with the experimental binding affinities. On the basis of the SDRs of PDZ domains identified by MD simulations, we have developed a simple scoring scheme for evaluating binding energies for PDZ-peptide complexes using residue based statistical pair potentials. This multiscale approach has been benchmarked on a mouse PDZ proteome array data set by calculating the binding energies for 217 different substrate peptides in binding pockets of 64 different mouse PDZ domains. Receiver operating characteristic (ROC) curve analysis indicates that, the area under curve (AUC) values for binder vs nonbinder classification by our structure based method is 0.780. Our structure based method does not require experimental PDZ-peptide binding data for training.
Sequence-Based Prediction of RNA-Binding Residues in Proteins.

PubMed

Walia, Rasna R; El-Manzalawy, Yasser; Honavar, Vasant G; Dobbs, Drena

2017-01-01

Identifying individual residues in the interfaces of protein-RNA complexes is important for understanding the molecular determinants of protein-RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein-RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein-RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner.
SECRET domain of variola virus CrmB protein can be a member of poxviral type II chemokine-binding proteins family

PubMed Central

2010-01-01

Background Variola virus (VARV) the causative agent of smallpox, eradicated in 1980, have wide spectrum of immunomodulatory proteins to evade host immunity. Recently additional biological activity was discovered for VARV CrmB protein, known to bind and inhibit tumour necrosis factor (TNF) through its N-terminal domain homologous to cellular TNF receptors. Besides binding TNF, this protein was also shown to bind with high affinity several chemokines which recruit B- and T-lymphocytes and dendritic cells to sites of viral entry and replication. Ability to bind chemokines was shown to be associated with unique C-terminal domain of CrmB protein. This domain named SECRET (Smallpox virus-Encoded Chemokine Receptor) is unrelated to the host proteins and lacks significant homology with other known viral chemokine-binding proteins or any other known protein. Findings De novo modelling of VARV-CrmB SECRET domain spatial structure revealed its apparent structural homology with cowpox virus CC-chemokine binding protein (vCCI) and vaccinia virus A41 protein, despite low sequence identity between these three proteins. Potential ligand-binding surface of modelled VARV-CrmB SECRET domain was also predicted to bear prominent electronegative charge which is characteristic to known orthopoxviral chemokine-binding proteins. Conclusions Our results suggest that SECRET should be included into the family of poxviral type II chemokine-binding proteins and that it might have been evolved from the vCCI-like predecessor protein. PMID:20979600
SECRET domain of variola virus CrmB protein can be a member of poxviral type II chemokine-binding proteins family.

PubMed

Antonets, Denis V; Nepomnyashchikh, Tatyana S; Shchelkunov, Sergei N

2010-10-27

Variola virus (VARV) the causative agent of smallpox, eradicated in 1980, have wide spectrum of immunomodulatory proteins to evade host immunity. Recently additional biological activity was discovered for VARV CrmB protein, known to bind and inhibit tumour necrosis factor (TNF) through its N-terminal domain homologous to cellular TNF receptors. Besides binding TNF, this protein was also shown to bind with high affinity several chemokines which recruit B- and T-lymphocytes and dendritic cells to sites of viral entry and replication. Ability to bind chemokines was shown to be associated with unique C-terminal domain of CrmB protein. This domain named SECRET (Smallpox virus-Encoded Chemokine Receptor) is unrelated to the host proteins and lacks significant homology with other known viral chemokine-binding proteins or any other known protein. De novo modelling of VARV-CrmB SECRET domain spatial structure revealed its apparent structural homology with cowpox virus CC-chemokine binding protein (vCCI) and vaccinia virus A41 protein, despite low sequence identity between these three proteins. Potential ligand-binding surface of modelled VARV-CrmB SECRET domain was also predicted to bear prominent electronegative charge which is characteristic to known orthopoxviral chemokine-binding proteins. Our results suggest that SECRET should be included into the family of poxviral type II chemokine-binding proteins and that it might have been evolved from the vCCI-like predecessor protein.
Determining Membrane Protein-Lipid Binding Thermodynamics Using Native Mass Spectrometry.

PubMed

Cong, Xiao; Liu, Yang; Liu, Wen; Liang, Xiaowen; Russell, David H; Laganowsky, Arthur

2016-04-06

Membrane proteins are embedded in the biological membrane where the chemically diverse lipid environment can modulate their structure and function. However, the thermodynamics governing the molecular recognition and interaction of lipids with membrane proteins is poorly understood. Here, we report a method using native mass spectrometry (MS), to determine thermodynamics of individual ligand binding events to proteins. Unlike conventional methods, native MS can resolve individual ligand binding events and, coupled with an apparatus to control the temperature, determine binding thermodynamic parameters, such as for protein-lipid interactions. We validated our approach using three soluble protein-ligand systems (maltose binding protein, lysozyme, and nitrogen regulatory protein) and obtained similar results to those using isothermal titration calorimetry and surface plasmon resonance. We also determined for the first time the thermodynamics of individual lipid binding to the ammonia channel (AmtB), an integral membrane protein from Escherichia coli. Remarkably, we observed distinct thermodynamic signatures for the binding of different lipids and entropy-enthalpy compensation for binding lipids of variable chain length. Additionally, using a mutant form of AmtB that abolishes a specific phosphatidylglycerol (PG) binding site, we observed distinct changes in the thermodynamic signatures for binding PG, implying these signatures can identify key residues involved in specific lipid binding and potentially differentiate between specific lipid binding sites.
Direct regulation of E-cadherin by targeted histone methylation of TALE-SET fusion protein in cancer cells.

PubMed

Cho, Hyun-Soo; Kang, Jeong Gu; Lee, Jae-Hye; Lee, Jeong-Ju; Jeon, Seong Kook; Ko, Jeong-Heon; Kim, Dae-Soo; Park, Kun-Hyang; Kim, Yong-Sam; Kim, Nam-Soon

2015-09-15

TALE-nuclease chimeras (TALENs) can bind to and cleave specific genomic loci and, are used to engineer gene knockouts and additions. Recently, instead of using the FokI domain, epigenetically active domains, such as TET1 and LSD1, have been combined with TAL effector domains to regulate targeted gene expression via DNA and histone demethylation. However, studies of histone methylation in the TALE system have not been performed. Therefore, in this study, we established a novel targeted regulation system with a TAL effector domain and a histone methylation domain. To construct a TALE-methylation fusion protein, we combined a TAL effector domain containing an E-Box region to act as a Snail binding site and the SET domain of EHMT 2 to allow for histone methylation. The constructed TALE-SET module (TSET) repressed the expression of E-cadherin via by increasing H3K9 dimethylation. Moreover, the cells that overexpressed TSET showed increased cell migration and invasion. This is the first phenotype-based study of targeted histone methylation by the TALE module, and this new system can be applied in new cancer therapies to reduce side effects.
A role for surface hydrophobicity in protein-protein recognition.

PubMed Central

Young, L.; Jernigan, R. L.; Covell, D. G.

1994-01-01

The role of hydrophobicity as a determinant of protein-protein interactions is examined. Surfaces of apo-protein targets comprising 9 classes of enzymes, 7 antibody fragments, hirudin, growth hormone, and retinol-binding protein, and their associated ligands with available X-ray structures for their complexed forms, are scanned to determine clusters of surface-accessible amino acids. Clusters of surface residues are ranked on the basis of the hydrophobicity of their constituent amino acids. The results indicate that the location of the co-crystallized ligand is commonly found to correspond with one of the strongest hydrophobic clusters on the surface of the target molecule. In 25 of 38 cases, the correspondence is exact, with the position of the most hydrophobic cluster coinciding with more than one-third of the surface buried by the bound ligand. The remaining 13 cases demonstrate this correspondence within the top 6 hydrophobic clusters. These results suggest that surface hydrophobicity can be used to identify regions of a protein's surface most likely to interact with a binding ligand. This fast and simple procedure may be useful for identifying small sets of well-defined loci for possible ligand attachment. PMID:8061602

Amyotrophic lateral sclerosis mutant vesicle-associated membrane protein-associated protein-B transgenic mice develop TAR-DNA-binding protein-43 pathology.

PubMed

Tudor, E L; Galtrey, C M; Perkinton, M S; Lau, K-F; De Vos, K J; Mitchell, J C; Ackerley, S; Hortobágyi, T; Vámos, E; Leigh, P N; Klasen, C; McLoughlin, D M; Shaw, C E; Miller, C C J

2010-05-19

Cytoplasmic ubiquitin-positive inclusions containing TAR-DNA-binding protein-43 (TDP-43) within motor neurons are the hallmark pathology of sporadic amyotrophic lateral sclerosis (ALS). TDP-43 is a nuclear protein and the mechanisms by which it becomes mislocalized and aggregated in ALS are not properly understood. A mutation in the vesicle-associated membrane protein-associated protein-B (VAPB) involving a proline to serine substitution at position 56 (VAPBP56S) is the cause of familial ALS type-8. To gain insight into the molecular mechanisms by which VAPBP56S induces disease, we created transgenic mice that express either wild-type VAPB (VAPBwt) or VAPBP56S in the nervous system. Analyses of both sets of mice revealed no overt motor phenotype nor alterations in survival. However, VAPBP56S but not VAPBwt transgenic mice develop cytoplasmic TDP-43 accumulations within spinal cord motor neurons that were first detected at 18 months of age. Our results suggest a link between abnormal VAPBP56S function and TDP-43 mislocalization. Copyright 2010 IBRO. Published by Elsevier Ltd. All rights reserved.
Proteome-wide Identification of Novel Ceramide-binding Proteins by Yeast Surface cDNA Display and Deep Sequencing.

PubMed

Bidlingmaier, Scott; Ha, Kevin; Lee, Nam-Kyung; Su, Yang; Liu, Bin

2016-04-01

Although the bioactive sphingolipid ceramide is an important cell signaling molecule, relatively few direct ceramide-interacting proteins are known. We used an approach combining yeast surface cDNA display and deep sequencing technology to identify novel proteins binding directly to ceramide. We identified 234 candidate ceramide-binding protein fragments and validated binding for 20. Most (17) bound selectively to ceramide, although a few (3) bound to other lipids as well. Several novel ceramide-binding domains were discovered, including the EF-hand calcium-binding motif, the heat shock chaperonin-binding motif STI1, the SCP2 sterol-binding domain, and the tetratricopeptide repeat region motif. Interestingly, four of the verified ceramide-binding proteins (HPCA, HPCAL1, NCS1, and VSNL1) and an additional three candidate ceramide-binding proteins (NCALD, HPCAL4, and KCNIP3) belong to the neuronal calcium sensor family of EF hand-containing proteins. We used mutagenesis to map the ceramide-binding site in HPCA and to create a mutant HPCA that does not bind to ceramide. We demonstrated selective binding to ceramide by mammalian cell-produced wild type but not mutant HPCA. Intriguingly, we also identified a fragment from prostaglandin D2synthase that binds preferentially to ceramide 1-phosphate. The wide variety of proteins and domains capable of binding to ceramide suggests that many of the signaling functions of ceramide may be regulated by direct binding to these proteins. Based on the deep sequencing data, we estimate that our yeast surface cDNA display library covers ∼60% of the human proteome and our selection/deep sequencing protocol can identify target-interacting protein fragments that are present at extremely low frequency in the starting library. Thus, the yeast surface cDNA display/deep sequencing approach is a rapid, comprehensive, and flexible method for the analysis of protein-ligand interactions, particularly for the study of non-protein ligands. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
[Determination of plasma protein binding rate of arctiin and arctigenin with ultrafiltration].

PubMed

Han, Xue-Ying; Wang, Wei; Tan, Ri-Qiu; Dou, De-Qiang

2013-02-01

To determine the plasma protein binding rate of arctiin and arctigenin. The ultrafiltration combined with HPLC was employed to determine the plasma protein binding rate of arctiin and arctigenin as well as rat plasma and healthy human plasma proteins. The plasma protein binding rate of arctiin with rat plasma at the concentrations of 64. 29, 32.14, 16.07 mg x L(-1) were (71.2 +/- 2.0)%, (73.4 +/- 0.61)%, (78.2 +/- 1.9)%, respectively; while the plasma protein binding rate of arctiin with healthy human plasma at the above concentrations were (64.8 +/- 3.1)%, (64.5 +/- 2.5)%, (77.5 +/- 1.7)%, respectively. The plasma protein binding rate of arctigenin with rat plasma at the concentrations of 77.42, 38.71, 19.36 mg x L(-1) were (96.7 +/- 0.41)%, (96.8 +/- 1.6)%, (97.3 +/- 0.46)%, respectively; while the plasma protein binding rate of arctigenin with normal human plasma at the above concentrations were (94.7 +/- 3.1)%, (96.8 +/- 1.6)%, (97.9 +/- 1.3)%, respectively. The binding rate of arctiin with rat plasma protein was moderate, which is slightly higher than the binding rate of arctiin with healthy human plasma protein. The plasma protein binding rates of arctigenin with both rat plasma and healthy human plasma are very high.
Mechanical coupling in myosin V: a simulation study

PubMed Central

Ovchinnikov, Victor; Trout, Bernhardt L.

2009-01-01

Myosin motor function depends on the interaction between different domains that transmit information from one part of the molecule to another. The inter-domain coupling in myosin V is studied with Restrained Targeted Molecular Dynamics (RTMD) using an all-atom representation in explicit solvent. To elucidate the origin of the conformational change due to the binding of ATP, targeting forces are applied to small sets of atoms (the forcing sets, FS) in the direction of their displacement from the rigor conformation, which has a closed actin-binding cleft, to the post-rigor conformation, in which the cleft is open. The ‘minimal’ FS that results in extensive structural changes in the overall myosin conformation is comprised of the ATP, Switch 1, and the nearby HF, HG and HH helices. Addition of switch 2 to the forcing set is required to achieve a complete opening of the actin-binding cleft. The RTMD simulations reveal the mechanical coupling pathways between (i) the nucleotide-binding pocket (NBP) and the actin-binding cleft, (ii) the NBP and the converter, and (iii) the actin-binding cleft and the converter. Closing of the NBP due to ATP binding is tightly coupled to the opening of the cleft, and leads to the rupture of a key hydrogen bond (F441N/A684O) between switch 2 and the SH1 helix. The actin-binding cleft may mediate the rupture of this bond via a connection between the HW helix, the Relay helix, and Switch 2. The findings are consistent with experimental studies and a recent normal mode analysis. The present method is expected to be useful more generally in studies of inter-domain coupling in proteins. PMID:19853615
A Quantitative Measure of Conformational Changes in Apo, Holo and Ligand-Bound Forms of Enzymes.

PubMed

Singh, Satendra; Singh, Atul Kumar; Wadhwa, Gulshan; Singh, Dev Bukhsh; Dwivedi, Seema; Gautam, Budhayash; Ramteke, Pramod W

2016-06-01

Determination of the native geometry of the enzymes and ligand complexes is a key step in the process of structure-based drug designing. Enzymes and ligands show flexibility in structural behavior as they come in contact with each other. When ligand binds with active site of the enzyme, in the presence of cofactor some structural changes are expected to occur in the active site. Motivation behind this study is to determine the nature of conformational changes as well as regions where such changes are more pronounced. To measure the structural changes due to cofactor and ligand complex, enzyme in apo, holo and ligand-bound forms is selected. Enzyme data set was retrieved from protein data bank. Fifteen triplet groups were selected for the analysis of structural changes based on selection criteria. Structural features for selected enzymes were compared at the global as well as local region. Accessible surface area for the enzymes in entire triplet set was calculated, which describes the change in accessible surface area upon binding of cofactor and ligand with the enzyme. It was observed that some structural changes take place during binding of ligand in the presence of cofactor. This study will helps in understanding the level of flexibility in protein-ligand interaction for computer-aided drug designing.
Molecular Determinants of Epidermal Growth Factor Binding: A Molecular Dynamics Study

PubMed Central

Sanders, Jeffrey M.; Wampole, Matthew E.; Thakur, Mathew L.; Wickstrom, Eric

2013-01-01

The epidermal growth factor receptor (EGFR) is a member of the receptor tyrosine kinase family that plays a role in multiple cellular processes. Activation of EGFR requires binding of a ligand on the extracellular domain to promote conformational changes leading to dimerization and transphosphorylation of intracellular kinase domains. Seven ligands are known to bind EGFR with affinities ranging from sub-nanomolar to near micromolar dissociation constants. In the case of EGFR, distinct conformational states assumed upon binding a ligand is thought to be a determining factor in activation of a downstream signaling network. Previous biochemical studies suggest the existence of both low affinity and high affinity EGFR ligands. While these studies have identified functional effects of ligand binding, high-resolution structural data are lacking. To gain a better understanding of the molecular basis of EGFR binding affinities, we docked each EGFR ligand to the putative active state extracellular domain dimer and 25.0 ns molecular dynamics simulations were performed. MM-PBSA/GBSA are efficient computational approaches to approximate free energies of protein-protein interactions and decompose the free energy at the amino acid level. We applied these methods to the last 6.0 ns of each ligand-receptor simulation. MM-PBSA calculations were able to successfully rank all seven of the EGFR ligands based on the two affinity classes: EGF>HB-EGF>TGF-α>BTC>EPR>EPG>AR. Results from energy decomposition identified several interactions that are common among binding ligands. These findings reveal that while several residues are conserved among the EGFR ligand family, no single set of residues determines the affinity class. Instead we found heterogeneous sets of interactions that were driven primarily by electrostatic and Van der Waals forces. These results not only illustrate the complexity of EGFR dynamics but also pave the way for structure-based design of therapeutics targeting EGF ligands or the receptor itself. PMID:23382875
DOE Office of Scientific and Technical Information (OSTI.GOV)

Caberoy, Nora B.; Zhou, Yixiong; Alvarado, Gabriela

To efficiently elucidate the biological roles of phosphatidylserine (PS), we developed open-reading-frame (ORF) phage display to identify PS-binding proteins. The procedure of phage panning was optimized with a phage clone expressing MFG-E8, a well-known PS-binding protein. Three rounds of phage panning with ORF phage display cDNA library resulted in {approx}300-fold enrichment in PS-binding activity. A total of 17 PS-binding phage clones were identified. Unlike phage display with conventional cDNA libraries, all 17 PS-binding clones were ORFs encoding 13 real proteins. Sequence analysis revealed that all identified PS-specific phage clones had dimeric basic amino acid residues. GST fusion proteins were expressedmore » for 3 PS-binding proteins and verified for their binding activity to PS liposomes, but not phosphatidylcholine liposomes. These results elucidated previously unknown PS-binding proteins and demonstrated that ORF phage display is a versatile technology capable of efficiently identifying binding proteins for non-protein molecules like PS.« less
Structural comparison of cytochromes P450 2A6, 2A13, and 2E1 with pilocarpine

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeVore, Natasha M.; Meneely, Kathleen M.; Bart, Aaron G.

2013-11-20

Human xenobiotic-metabolizing cytochrome P450 (CYP) enzymes can each bind and monooxygenate a diverse set of substrates, including drugs, often producing a variety of metabolites. Additionally, a single ligand can interact with multiple CYP enzymes, but often the protein structural similarities and differences that mediate such overlapping selectivity are not well understood. Even though the CYP superfamily has a highly canonical global protein fold, there are large variations in the active site size, topology, and conformational flexibility. We have determined how a related set of three human CYP enzymes bind and interact with a common inhibitor, the muscarinic receptor agonist drugmore » pilocarpine. Pilocarpine binds and inhibits the hepatic CYP2A6 and respiratory CYP2A13 enzymes much more efficiently than the hepatic CYP2E1 enzyme. To elucidate key residues involved in pilocarpine binding, crystal structures of CYP2A6 (2.4 {angstrom}), CYP2A13 (3.0 {angstrom}), CYP2E1 (2.35 {angstrom}), and the CYP2A6 mutant enzyme, CYP2A6 I208S/I300F/G301A/S369G (2.1 {angstrom}) have been determined with pilocarpine in the active site. In all four structures, pilocarpine coordinates to the heme iron, but comparisons reveal how individual residues lining the active sites of these three distinct human enzymes interact differently with the inhibitor pilocarpine.« less
Isolation and characterizations of oxalate-binding proteins in the kidney

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roop-ngam, Piyachat; Chaiyarit, Sakdithep; Pongsakul, Nutkridta

Highlights: Black-Right-Pointing-Pointer The first large-scale characterizations of oxalate-binding kidney proteins. Black-Right-Pointing-Pointer The recently developed oxalate-conjugated EAH Sepharose 4B beads were applied. Black-Right-Pointing-Pointer 38 forms of 26 unique oxalate-binding kidney proteins were identified. Black-Right-Pointing-Pointer 25/26 (96%) of identified proteins had 'L-x(3,5)-R-x(2)-[AGILPV]' domain. -- Abstract: Oxalate-binding proteins are thought to serve as potential modulators of kidney stone formation. However, only few oxalate-binding proteins have been identified from previous studies. Our present study, therefore, aimed for large-scale identification of oxalate-binding proteins in porcine kidney using an oxalate-affinity column containing oxalate-conjugated EAH Sepharose 4B beads for purification followed by two-dimensional gel electrophoresis (2-DE) tomore » resolve the recovered proteins. Comparing with those obtained from the controlled column containing uncoupled EAH-Sepharose 4B (to subtract the background of non-specific bindings), a total of 38 protein spots were defined as oxalate-binding proteins. These protein spots were successfully identified by quadrupole time-of-flight mass spectrometry (MS) and/or tandem MS (MS/MS) as 26 unique proteins, including several nuclear proteins, mitochondrial proteins, oxidative stress regulatory proteins, metabolic enzymes and others. Identification of oxalate-binding domain using the PRATT tool revealed 'L-x(3,5)-R-x(2)-[AGILPV]' as a functional domain responsible for oxalate-binding in 25 of 26 (96%) unique identified proteins. We report herein, for the first time, large-scale identification and characterizations of oxalate-binding proteins in the kidney. The presence of positively charged arginine residue in the middle of this functional domain suggested its significance for binding to the negatively charged oxalate. These data will enhance future stone research, particularly on stone modulators.« less
Iron loading site on the Fe-S cluster assembly scaffold protein is distinct from the active site.

PubMed

Rodrigues, Andria V; Kandegedara, Ashoka; Rotondo, John A; Dancis, Andrew; Stemmler, Timothy L

2015-06-01

Iron-sulfur (Fe-S) cluster containing proteins are utilized in almost every biochemical pathway. The unique redox and coordination chemistry associated with the cofactor allows these proteins to participate in a diverse set of reactions, including electron transfer, enzyme catalysis, DNA synthesis and signaling within several pathways. Due to the high reactivity of the metal, it is not surprising that biological Fe-S cluster assembly is tightly regulated within cells. In yeast, the major assembly pathway for Fe-S clusters is the mitochondrial ISC pathway. Yeast Fe-S cluster assembly is accomplished using the scaffold protein (Isu1) as the molecular foundation, with assistance from the cysteine desulfurase (Nfs1) to provide sulfur, the accessory protein (Isd11) to regulate Nfs1 activity, the yeast frataxin homologue (Yfh1) to regulate Nfs1 activity and participate in Isu1 Fe loading possibly as a chaperone, and the ferredoxin (Yah1) to provide reducing equivalents for assembly. In this report, we utilize calorimetric and spectroscopic methods to provide molecular insight into how wt-Isu1 from S. cerevisiae becomes loaded with iron. Isothermal titration calorimetry and an iron competition binding assay were developed to characterize the energetics of protein Fe(II) binding. Differential scanning calorimetry was used to identify thermodynamic characteristics of the protein in the apo state or under iron loaded conditions. Finally, X-ray absorption spectroscopy was used to characterize the electronic and structural properties of Fe(II) bound to Isu1. Current data are compared to our previous characterization of the D37A Isu1 mutant, and these suggest that when Isu1 binds Fe(II) in a manner not perturbed by the D37A substitution, and that metal binding occurs at a site distinct from the cysteine rich active site in the protein.
Structural Analysis of Semi-specific Oligosaccharide Recognition by a Cellulose-binding Protein of Thermotoga maritima Reveals Adaptations for Functional Diversification of the Oligopeptide Periplasmic Binding Protein Fold

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cuneo, Matthew J.; Beese, Lorena S.; Hellinga, Homme W.

Periplasmic binding proteins (PBPs) constitute a protein superfamily that binds a wide variety of ligands. In prokaryotes, PBPs function as receptors for ATP-binding cassette or tripartite ATP-independent transporters and chemotaxis systems. In many instances, PBPs bind their cognate ligands with exquisite specificity, distinguishing, for example, between sugar epimers or structurally similar anions. By contrast, oligopeptide-binding proteins bind their ligands through interactions with the peptide backbone but do not distinguish between different side chains. The extremophile Thermotoga maritima possesses a remarkable array of carbohydrate-processing metabolic systems, including the hydrolysis of cellulosic polymers. Here, we present the crystal structure of a T.more » maritima cellobiose-binding protein (tm0031) that is homologous to oligopeptide-binding proteins. T. maritima cellobiose-binding protein binds a variety of lengths of {beta}(1 {yields} 4)-linked glucose oligomers, ranging from two rings (cellobiose) to five (cellopentaose). The structure reveals that binding is semi-specific. The disaccharide at the nonreducing end binds specifically; the other rings are located in a large solvent-filled groove, where the reducing end makes several contacts with the protein, thereby imposing an upper limit of the oligosaccharides that are recognized. Semi-specific recognition, in which a molecular class rather than individual species is selected, provides an efficient solution for the uptake of complex mixtures.« less
Application of NMR Methods to Identify Detection Reagents for Use in the Development of Robust Nanosensors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cosman, M; Krishnan, V V; Balhorn, R

2004-04-29

Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful technique for studying bi-molecular interactions at the atomic scale. Our NMR lab is involved in the identification of small molecules, or ligands that bind to target protein receptors, such as tetanus (TeNT) and botulinum (BoNT) neurotoxins, anthrax proteins and HLA-DR10 receptors on non-Hodgkin's lymphoma cancer cells. Once low affinity binders are identified, they can be linked together to produce multidentate synthetic high affinity ligands (SHALs) that have very high specificity for their target protein receptors. An important nanotechnology application for SHALs is their use in the development of robust chemical sensors ormore » biochips for the detection of pathogen proteins in environmental samples or body fluids. Here, we describe a recently developed NMR competition assay based on transferred nuclear Overhauser effect spectroscopy (trNOESY) that enables the identification of sets of ligands that bind to the same site, or a different site, on the surface of TeNT fragment C (TetC) than a known ''marker'' ligand, doxorubicin. Using this assay, we can identify the optimal pairs of ligands to be linked together for creating detection reagents, as well as estimate the relative binding constants for ligands competing for the same site.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)

Selezneva, Anna I.; Cavigiolio, Giorgio; Theil, Elizabeth C.

Iron regulatory protein 1 (IRP1) is a bifunctional protein with activity as an RNA-binding protein or as a cytoplasmic aconitase. Interconversion of IRP1 between these mutually exclusive states is central to cellular iron regulation and is accomplished through iron-responsive assembly and disassembly of a [4Fe-4S] cluster. When in its apo form, IRP1 binds to iron responsive elements (IREs) found in mRNAs encoding proteins of iron storage and transport and either prevents translation or degradation of the bound mRNA. Excess cellular iron stimulates the assembly of a [4Fe-4S] cluster in IRP1, inhibiting its IRE-binding ability and converting it to an aconitase.more » The three-dimensional structure of IRP1 in its different active forms will provide details of the interconversion process and clarify the selective recognition of mRNA, Fe-S sites and catalytic activity. To this end, the apo form of IRP1 bound to a ferritin IRE was crystallized. Crystals belong to the monoclinic space group P21, with unit-cell parameters a = 109.6, b = 80.9, c = 142.9 {angstrom}, = 92.0{sup o}. Native data sets have been collected from several crystals with resolution extending to 2.8 {angstrom} and the structure has been solved by molecular replacement.« less
Staufen recruitment into stress granules does not affect early mRNA transport in oligodendrocytes.

PubMed

Thomas, María G; Martinez Tosar, Leandro J; Loschi, Mariela; Pasquini, Juana M; Correale, Jorge; Kindler, Stefan; Boccaccio, Graciela L

2005-01-01

Staufen is a conserved double-stranded RNA-binding protein required for mRNA localization in Drosophila oocytes and embryos. The mammalian homologues Staufen 1 and Staufen 2 have been implicated in dendritic RNA targeting in neurons. Here we show that in rodent oligodendrocytes, these two proteins are present in two independent sets of RNA granules located at the distal myelinating processes. A third kind of RNA granules lacks Staufen and contains major myelin mRNAs. Myelin Staufen granules associate with microfilaments and microtubules, and their subcellular distribution is affected by polysome-disrupting drugs. Under oxidative stress, both Staufen 1 and Staufen 2 are recruited into stress granules (SGs), which are stress-induced organelles containing transiently silenced messengers. Staufen SGs contain the poly(A)-binding protein (PABP), the RNA-binding proteins HuR and TIAR, and small but not large ribosomal subunits. Staufen recruitment into perinuclear SGs is paralleled by a similar change in the overall localization of polyadenylated RNA. Under the same conditions, the distribution of recently transcribed and exported mRNAs is not affected. Our results indicate that Staufen 1 and Staufen 2 are novel and ubiquitous SG components and suggest that Staufen RNPs are involved in repositioning of most polysomal mRNAs, but not of recently synthesized transcripts, during the stress response.
ATtRACT-a database of RNA-binding proteins and associated motifs.

PubMed

Giudice, Girolamo; Sánchez-Cabo, Fátima; Torroja, Carlos; Lara-Pezzi, Enrique

2016-01-01

RNA-binding proteins (RBPs) play a crucial role in key cellular processes, including RNA transport, splicing, polyadenylation and stability. Understanding the interaction between RBPs and RNA is key to improve our knowledge of RNA processing, localization and regulation in a global manner. Despite advances in recent years, a unified non-redundant resource that includes information on experimentally validated motifs, RBPs and integrated tools to exploit this information is lacking. Here, we developed a database named ATtRACT (available athttp://attract.cnic.es) that compiles information on 370 RBPs and 1583 RBP consensus binding motifs, 192 of which are not present in any other database. To populate ATtRACT we (i) extracted and hand-curated experimentally validated data from CISBP-RNA, SpliceAid-F, RBPDB databases, (ii) integrated and updated the unavailable ASD database and (iii) extracted information from Protein-RNA complexes present in Protein Data Bank database through computational analyses. ATtRACT provides also efficient algorithms to search a specific motif and scan one or more RNA sequences at a time. It also allows discoveringde novomotifs enriched in a set of related sequences and compare them with the motifs included in the database.Database URL:http:// attract. cnic. es. © The Author(s) 2016. Published by Oxford University Press.
Mapping of the immunophilin-immunosuppressant site of interaction on calcineurin.

PubMed

Husi, H; Luyten, M A; Zurini, M G

1994-05-13

The interaction of the immunosuppressive complexes cyclosporin A-cyclophilin A and FK506 binding protein-FK506 with the Ca(2+)- and calmodulin-dependent protein phosphatase calcineurin has been investigated by means of photoaffinity labeling and chemical cross-linking. Photolabeling of purified bovine brain calcineurin with the affinity label [O-[4-[4-(1-diazo-2,2,2-trifluoroethyl)benzoyl]aminobutanoyl]-D- serine8]cyclosporin in the presence of cyclophilin A results, in addition to the labeling of cyclophilin itself, in the transfer of some of the chemical probe to both the catalytic subunit A and the regulatory subunit B of calcineurin. Chemical cross-linking studies with disuccinimidyl suberate in the presence of either cyclophilin A, B, or C in complex with cyclosporin A or FK506 binding protein-FK506 result on the other hand in the apparently exclusive and strictly immunosuppressant-dependent formation of covalent immunophilin-calcineurin B subunit products. Cross-linking of immunophilins to calcineurin B subunit requires the presence of subunit A. In the present study, using a set of recombinant maltose-binding protein fusion products representing different stretches of the catalytic subunit A, we were able to map the minimal calcineurin A sequence necessary for immunophilin-ligand-calcineurin B interaction to occur.
Mass Spectrometry of Human Leukocyte Antigen Class I Peptidomes Reveals Strong Effects of Protein Abundance and Turnover on Antigen Presentation*

PubMed Central

Bassani-Sternberg, Michal; Pletscher-Frankild, Sune; Jensen, Lars Juhl; Mann, Matthias

2015-01-01

HLA class I molecules reflect the health state of cells to cytotoxic T cells by presenting a repertoire of endogenously derived peptides. However, the extent to which the proteome shapes the peptidome is still largely unknown. Here we present a high-throughput mass-spectrometry-based workflow that allows stringent and accurate identification of thousands of such peptides and direct determination of binding motifs. Applying the workflow to seven cancer cell lines and primary cells, yielded more than 22,000 unique HLA peptides across different allelic binding specificities. By computing a score representing the HLA-I sampling density, we show a strong link between protein abundance and HLA-presentation (p < 0.0001). When analyzing overpresented proteins – those with at least fivefold higher density score than expected for their abundance – we noticed that they are degraded almost 3 h faster than similar but nonpresented proteins (top 20% abundance class; median half-life 20.8h versus 23.6h, p < 0.0001). This validates protein degradation as an important factor for HLA presentation. Ribosomal, mitochondrial respiratory chain, and nucleosomal proteins are particularly well presented. Taking a set of proteins associated with cancer, we compared the predicted immunogenicity of previously validated T-cell epitopes with other peptides from these proteins in our data set. The validated epitopes indeed tend to have higher immunogenic scores than the other detected HLA peptides. Remarkably, we identified five mutated peptides from a human colon cancer cell line, which have very recently been predicted to be HLA-I binders. Altogether, we demonstrate the usefulness of combining MS-analysis with immunogenesis prediction for identifying, ranking, and selecting peptides for therapeutic use. PMID:25576301
SONAR Discovers RNA-Binding Proteins from Analysis of Large-Scale Protein-Protein Interactomes.

PubMed

Brannan, Kristopher W; Jin, Wenhao; Huelga, Stephanie C; Banks, Charles A S; Gilmore, Joshua M; Florens, Laurence; Washburn, Michael P; Van Nostrand, Eric L; Pratt, Gabriel A; Schwinn, Marie K; Daniels, Danette L; Yeo, Gene W

2016-10-20

RNA metabolism is controlled by an expanding, yet incomplete, catalog of RNA-binding proteins (RBPs), many of which lack characterized RNA binding domains. Approaches to expand the RBP repertoire to discover non-canonical RBPs are currently needed. Here, HaloTag fusion pull down of 12 nuclear and cytoplasmic RBPs followed by quantitative mass spectrometry (MS) demonstrates that proteins interacting with multiple RBPs in an RNA-dependent manner are enriched for RBPs. This motivated SONAR, a computational approach that predicts RNA binding activity by analyzing large-scale affinity precipitation-MS protein-protein interactomes. Without relying on sequence or structure information, SONAR identifies 1,923 human, 489 fly, and 745 yeast RBPs, including over 100 human candidate RBPs that contain zinc finger domains. Enhanced CLIP confirms RNA binding activity and identifies transcriptome-wide RNA binding sites for SONAR-predicted RBPs, revealing unexpected RNA binding activity for disease-relevant proteins and DNA binding proteins. Copyright © 2016 Elsevier Inc. All rights reserved.
Calculations of binding affinity between C8-substituted GTP analogs and the bacterial cell-division protein FtsZ

PubMed Central

Hritz, Jozef; Läppchen, Tilman

2010-01-01

The FtsZ protein is a self-polymerizing GTPase that plays a central role in bacterial cell division. Several C8-substituted GTP analogs are known to inhibit the polymerization of FtsZ by competing for the same binding site as its endogenous activating ligand GTP. Free energy calculations of the relative binding affinities to FtsZ for a set of five C8-substituted GTP analogs were performed. The calculated values agree well with the available experimental data, and the main contribution to the free energy differences is determined to be the conformational restriction of the ligands. The dihedral angle distributions around the glycosidic bond of these compounds in water are known to vary considerably depending on the physicochemical properties of the substituent at C8. However, within the FtsZ protein, this substitution has a negligible influence on the dihedral angle distributions, which fall within the narrow range of −140° to −90° for all investigated compounds. The corresponding ensemble average of the coupling constants 3J(C4,H1′) is calculated to be 2.95 ± 0.1 Hz. The contribution of the conformational selection of the GTP analogs upon binding was quantified from the corresponding populations. The obtained restraining free energy values follow the same trend as the relative binding affinities to FtsZ, indicating their dominant contribution. PMID:20559630
Mechanisms of inverse agonist action at D2 dopamine receptors

PubMed Central

Roberts, David J; Strange, Philip G

2005-01-01

Mechanisms of inverse agonist action at the D2(short) dopamine receptor have been examined. Discrimination of G-protein-coupled and -uncoupled forms of the receptor by inverse agonists was examined in competition ligand-binding studies versus the agonist [3H]NPA at a concentration labelling both G-protein-coupled and -uncoupled receptors. Competition of inverse agonists versus [3H]NPA gave data that were fitted best by a two-binding site model in the absence of GTP but by a one-binding site model in the presence of GTP. Ki values were derived from the competition data for binding of the inverse agonists to G-protein-uncoupled and -coupled receptors. Kcoupled and Kuncoupled were statistically different for the set of compounds tested (ANOVA) but the individual values were different in a post hoc test only for (+)-butaclamol. These observations were supported by simulations of these competition experiments according to the extended ternary complex model. Inverse agonist efficacy of the ligands was assessed from their ability to reduce agonist-independent [35S]GTPγS binding to varying degrees in concentration–response curves. Inverse agonism by (+)-butaclamol and spiperone occurred at higher potency when GDP was added to assays, whereas the potency of (−)-sulpiride was unaffected. These data show that some inverse agonists ((+)-butaclamol, spiperone) achieve inverse agonism by stabilising the uncoupled form of the receptor at the expense of the coupled form. For other compounds tested, we were unable to define the mechanism. PMID:15735658

Electrostatically Accelerated Coupled Binding and Folding of Intrinsically Disordered Proteins

PubMed Central

Ganguly, Debabani; Otieno, Steve; Waddell, Brett; Iconaru, Luigi; Kriwacki, Richard W.; Chen, Jianhan

2012-01-01

Intrinsically disordered proteins (IDPs) are now recognized to be prevalent in biology, and many potential functional benefits have been discussed. However, the frequent requirement of peptide folding in specific interactions of IDPs could impose a kinetic bottleneck, which could be overcome only by efficient folding upon encounter. Intriguingly, existing kinetic data suggest that specific binding of IDPs is generally no slower than that of globular proteins. Here, we exploited the cell cycle regulator p27Kip1 (p27) as a model system to understand how IDPs might achieve efficient folding upon encounter for facile recognition. Combining experiments and coarse-grained modeling, we demonstrate that long-range electrostatic interactions between enriched charges on p27 and near its binding site on cyclin A not only enhance the encounter rate (i.e., electrostatic steering), but also promote folding-competent topologies in the encounter complexes, allowing rapid subsequent formation of short-range native interactions en route to the specific complex. In contrast, nonspecific hydrophobic interactions, while hardly affecting the encounter rate, can significantly reduce the efficiency of folding upon encounter and lead to slower binding kinetics. Further analysis of charge distributions in a set of known IDP complexes reveals that, although IDP binding sites tend to be more hydrophobic compared to the rest of the target surface, their vicinities are frequently enriched with charges to complement those on IDPs. This observation suggests that electrostatically accelerated encounter and induced folding might represent a prevalent mechanism for promoting facile IDP recognition. PMID:22721951
Developmental regulation of collagenase-3 mRNA in normal, differentiating osteoblasts through the activator protein-1 and the runt domain binding sites

NASA Technical Reports Server (NTRS)

Winchester, S. K.; Selvamurugan, N.; D'Alonzo, R. C.; Partridge, N. C.

2000-01-01

Collagenase-3 mRNA is initially detectable when osteoblasts cease proliferation, increasing during differentiation and mineralization. We showed that this developmental expression is due to an increase in collagenase-3 gene transcription. Mutation of either the activator protein-1 or the runt domain binding site decreased collagenase-3 promoter activity, demonstrating that these sites are responsible for collagenase-3 gene transcription. The activator protein-1 and runt domain binding sites bind members of the activator protein-1 and core-binding factor family of transcription factors, respectively. We identified core-binding factor a1 binding to the runt domain binding site and JunD in addition to a Fos-related antigen binding to the activator protein-1 site. Overexpression of both c-Fos and c-Jun in osteoblasts or core-binding factor a1 increased collagenase-3 promoter activity. Furthermore, overexpression of c-Fos, c-Jun, and core-binding factor a1 synergistically increased collagenase-3 promoter activity. Mutation of either the activator protein-1 or the runt domain binding site resulted in the inability of c-Fos and c-Jun or core-binding factor a1 to increase collagenase-3 promoter activity, suggesting that there is cooperative interaction between the sites and the proteins. Overexpression of Fra-2 and JunD repressed core-binding factor a1-induced collagenase-3 promoter activity. Our results suggest that members of the activator protein-1 and core-binding factor families, binding to the activator protein-1 and runt domain binding sites are responsible for the developmental regulation of collagenase-3 gene expression in osteoblasts.
Develop and Test a Solvent Accessible Surface Area-Based Model in Conformational Entropy Calculations

PubMed Central

Wang, Junmei; Hou, Tingjun

2012-01-01

It is of great interest in modern drug design to accurately calculate the free energies of protein-ligand or nucleic acid-ligand binding. MM-PBSA (Molecular Mechanics-Poisson Boltzmann Surface Area) and MM-GBSA (Molecular Mechanics-Generalized Born Surface Area) have gained popularity in this field. For both methods, the conformational entropy, which is usually calculated through normal mode analysis (NMA), is needed to calculate the absolute binding free energies. Unfortunately, NMA is computationally demanding and becomes a bottleneck of the MM-PB/GBSA-NMA methods. In this work, we have developed a fast approach to estimate the conformational entropy based upon solvent accessible surface area calculations. In our approach, the conformational entropy of a molecule, S, can be obtained by summing up the contributions of all atoms, no matter they are buried or exposed. Each atom has two types of surface areas, solvent accessible surface area (SAS) and buried SAS (BSAS). The two types of surface areas are weighted to estimate the contribution of an atom to S. Atoms having the same atom type share the same weight and a general parameter k is applied to balance the contributions of the two types of surface areas. This entropy model was parameterized using a large set of small molecules for which their conformational entropies were calculated at the B3LYP/6-31G* level taking the solvent effect into account. The weighted solvent accessible surface area (WSAS) model was extensively evaluated in three tests. For the convenience, TS, the product of temperature T and conformational entropy S, were calculated in those tests. T was always set to 298.15 K through the text. First of all, good correlations were achieved between WSAS TS and NMA TS for 44 protein or nucleic acid systems sampled with molecular dynamics simulations (10 snapshots were collected for post-entropy calculations): the mean correlation coefficient squares (R2) was 0.56. As to the 20 complexes, the TS changes upon binding, TΔS, were also calculated and the mean R2 was 0.67 between NMA and WSAS. In the second test, TS were calculated for 12 proteins decoy sets (each set has 31 conformations) generated by the Rosetta software package. Again, good correlations were achieved for all decoy sets: the mean, maximum, minimum of R2 were 0.73, 0.89 and 0.55, respectively. Finally, binding free energies were calculated for 6 protein systems (the numbers of inhibitors range from 4 to 18) using four scoring functions. Compared to the measured binding free energies, the mean R2 of the six protein systems were 0.51, 0.47, 0.40 and 0.43 for MM-GBSA-WSAS, MM-GBSA-NMA, MM-PBSA-WSAS and MM-PBSA-NMA, respectively. The mean RMS errors of prediction were 1.19, 1.24, 1.41, 1.29 kcal/mol for the four scoring functions, correspondingly. Therefore, the two scoring functions employing WSAS achieved a comparable prediction performance to that of the scoring functions using NMA. It should be emphasized that no minimization was performed prior to the WSAS calculation in the last test. Although WSAS is not as rigorous as physical models such as quasi-harmonic analysis and thermodynamic integration (TI), it is computationally very efficient as only surface area calculation is involved and no structural minimization is required. Moreover, WSAS has achieved a comparable performance to normal mode analysis. We expect that this model could find its applications in the fields like high throughput screening (HTS), molecular docking and rational protein design. In those fields, efficiency is crucial since there are a large number of compounds, docking poses or protein models to be evaluated. A list of acronyms and abbreviations used in this work is provided for quick reference. PMID:22497310
Grain setting defect1, Encoding a Remorin Protein, Affects the Grain Setting in Rice through Regulating Plasmodesmatal Conductance1[W

PubMed Central

Gui, Jinshan; Liu, Chang; Shen, Junhui; Li, Laigeng

2014-01-01

Effective grain filling is one of the key determinants of grain setting in rice (Oryza sativa). Grain setting defect1 (GSD1), which encodes a putative remorin protein, was found to affect grain setting in rice. Investigation of the phenotype of a transfer DNA insertion mutant (gsd1-Dominant) with enhanced GSD1 expression revealed abnormalities including a reduced grain setting rate, accumulation of carbohydrates in leaves, and lower soluble sugar content in the phloem exudates. GSD1 was found to be specifically expressed in the plasma membrane and plasmodesmata (PD) of phloem companion cells. Experimental evidence suggests that the phenotype of the gsd1-Dominant mutant is caused by defects in the grain-filling process as a result of the impaired transport of carbohydrates from the photosynthetic site to the phloem. GSD1 functioned in affecting PD conductance by interacting with rice ACTIN1 in association with the PD callose binding protein1. Together, our results suggest that GSD1 may play a role in regulating photoassimilate translocation through the symplastic pathway to impact grain setting in rice. PMID:25253885
Identification of AOSC-binding proteins in neurons

NASA Astrophysics Data System (ADS)

Liu, Ming; Nie, Qin; Xin, Xianliang; Geng, Meiyu

2008-11-01

Acidic oligosaccharide sugar chain (AOSC), a D-mannuronic acid oligosaccharide, derived from brown algae polysaccharide, has been completed Phase I clinical trial in China as an anti-Alzheimer’s Disease (AD) drug candidate. The identification of AOSC-binding protein(s) in neurons is very important for understanding its action mechanism. To determine the binding protein(s) of AOSC in neurons mediating its anti-AD activities, confocal microscopy, affinity chromatography, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis were used. Confocal microscopy analysis shows that AOSC binds to SH-SY5Y cells in concentration-, time-, and temperature-dependent fashions. The AOSC binding proteins were purified by affinity chromatography and identified by LC-MS/MS analysis. The results showed that there are 349 proteins binding AOSC, including clathrin, adaptor protein-2 (AP-2) and amyloid precursor protein (APP). These results suggest that the binding/entrance of AOSC to neurons is probably responsible for anti-AD activities.
Alchemical Free Energy Calculations for Nucleotide Mutations in Protein-DNA Complexes.

PubMed

Gapsys, Vytautas; de Groot, Bert L

2017-12-12

Nucleotide-sequence-dependent interactions between proteins and DNA are responsible for a wide range of gene regulatory functions. Accurate and generalizable methods to evaluate the strength of protein-DNA binding have long been sought. While numerous computational approaches have been developed, most of them require fitting parameters to experimental data to a certain degree, e.g., machine learning algorithms or knowledge-based statistical potentials. Molecular-dynamics-based free energy calculations offer a robust, system-independent, first-principles-based method to calculate free energy differences upon nucleotide mutation. We present an automated procedure to set up alchemical MD-based calculations to evaluate free energy changes occurring as the result of a nucleotide mutation in DNA. We used these methods to perform a large-scale mutation scan comprising 397 nucleotide mutation cases in 16 protein-DNA complexes. The obtained prediction accuracy reaches 5.6 kJ/mol average unsigned deviation from experiment with a correlation coefficient of 0.57 with respect to the experimentally measured free energies. Overall, the first-principles-based approach performed on par with the molecular modeling approaches Rosetta and FoldX. Subsequently, we utilized the MD-based free energy calculations to construct protein-DNA binding profiles for the zinc finger protein Zif268. The calculation results compare remarkably well with the experimentally determined binding profiles. The software automating the structure and topology setup for alchemical calculations is a part of the pmx package; the utilities have also been made available online at http://pmx.mpibpc.mpg.de/dna_webserver.html .
[Supercomputer investigation of the protein-ligand system low-energy minima].

PubMed

Oferkin, I V; Sulimov, A V; Katkova, E V; Kutov, D K; Grigoriev, F V; Kondakova, O A; Sulimov, V B

2015-01-01

The accuracy of the protein-ligand binding energy calculations and ligand positioning is strongly influenced by the choice of the docking target function. This work demonstrates the evaluation of the five different target functions used in docking: functions based on MMFF94 force field and functions based on PM7 quantum-chemical method accounting or without accounting the implicit solvent model (PCM, COSMO or SGB). For these purposes the ligand positions corresponding to the minima of the target function and the experimentally known ligand positions in the protein active site (crystal ligand positions) were compared. Each function was examined on the same test-set of 16 protein-ligand complexes. The new parallelized docking program FLM based on Monte Carlo search algorithm was developed to perform the comprehensive low-energy minima search and to calculate the protein-ligand binding energy. This study demonstrates that the docking target function based on the MMFF94 force field can be used to detect the crystal or near crystal positions of the ligand by the finding the low-energy local minima spectrum of the target function. The importance of solvent accounting in the docking process for the accurate ligand positioning is also shown. The accuracy of the ligand positioning as well as the correlation between the calculated and experimentally determined protein-ligand binding energies are improved when the MMFF94 force field is substituted by the new PM7 method with implicit solvent accounting.
Facile manipulation of protein localization in fission yeast through binding of GFP-binding protein to GFP.

PubMed

Chen, Ying-Hui; Wang, Gao-Yuan; Hao, Hao-Chao; Chao, Chun-Jiang; Wang, Yamei; Jin, Quan-Wen

2017-03-01

GFP-binding protein (or GBP) has been recently developed in various systems and organisms as an efficient tool to purify GFP-fusion proteins. Due to the high affinity between GBP and GFP or GFP variants, this GBP-based approach is also ideally suited to alter the localization of functional proteins in live cells. In order to facilitate the wide use of the GBP-targeting approach in the fission yeast Schizosaccharomyces pombe , we developed a set of pFA6a-, pJK148- and pUC119-based vectors containing GBP- or GBP-mCherry-coding sequences and variants of inducible nmt1 or constitutive adh1 promoters that result in different levels of expression. The GBP or GBP-mCherry fragments can serve as cassettes for N- or C-terminal genomic tagging of genes of interest. We illustrated the application of these vectors in the construction of yeast strains with Dma1 or Cdc7 tagged with GBP-mCherry and efficient targeting of Dma1- or Cdc7-GBP-mCherry to the spindle pole body by Sid4-GFP. This series of vectors should help to facilitate the application of the GBP-targeting approach in manipulating protein localization and the analysis of gene function in fission yeast, at the level of single genes, as well as at a systematic scale. © 2017. Published by The Company of Biologists Ltd.
Investigation of protein selectivity in multimodal chromatography using in silico designed Fab fragment variants.

PubMed

Karkov, Hanne Sophie; Krogh, Berit Olsen; Woo, James; Parimal, Siddharth; Ahmadian, Haleh; Cramer, Steven M

2015-11-01

In this study, a unique set of antibody Fab fragments was designed in silico and produced to examine the relationship between protein surface properties and selectivity in multimodal chromatographic systems. We hypothesized that multimodal ligands containing both hydrophobic and charged moieties would interact strongly with protein surface regions where charged groups and hydrophobic patches were in close spatial proximity. Protein surface property characterization tools were employed to identify the potential multimodal ligand binding regions on the Fab fragment of a humanized antibody and to evaluate the impact of mutations on surface charge and hydrophobicity. Twenty Fab variants were generated by site-directed mutagenesis, recombinant expression, and affinity purification. Column gradient experiments were carried out with the Fab variants in multimodal, cation-exchange, and hydrophobic interaction chromatographic systems. The results clearly indicated that selectivity in the multimodal system was different from the other chromatographic modes examined. Column retention data for the reduced charge Fab variants identified a binding site comprising light chain CDR1 as the main electrostatic interaction site for the multimodal and cation-exchange ligands. Furthermore, the multimodal ligand binding was enhanced by additional hydrophobic contributions as evident from the results obtained with hydrophobic Fab variants. The use of in silico protein surface property analyses combined with molecular biology techniques, protein expression, and chromatographic evaluations represents a previously undescribed and powerful approach for investigating multimodal selectivity with complex biomolecules. © 2015 Wiley Periodicals, Inc.
Protein promiscuity: drug resistance and native functions--HIV-1 case.

PubMed

Fernández, Ariel; Tawfik, Dan S; Berkhout, Ben; Sanders, Rogier; Kloczkowski, Andrzej; Sen, Taner; Jernigan, Bob

2005-06-01

The association of a drug with its target protein has the effect of blocking the protein activity and is termed a promiscuous function to distinguish from the protein's native function (Tawfik and associates, Nat. Genet. 37, 73-6, 2005). Obviously, a protein has not evolved naturally for drug association or drug resistance. Promiscuous protein functions exhibit unique traits of evolutionary adaptability, or evolvability, which is dependent on the induction of novel phenotypic traits by a small number of mutations. These mutations might have small effects on native functions, but large effects on promiscuous function; for example, an evolving protein could become increasingly drug resistant while maintaining its original function. Ariel Fernandez, in his opinion piece, notes that drug-binding "promiscuity" can hardly be dissociated from native functions; a dominant approach to drug discovery is the protein-native-substrate transition-state mimetic strategy. Thus, man-made ligands (e.g. drugs) have been successfully crafted to restrain enzymatic activity by focusing on the very same structural features that determine the native function. Using the successful inhibition of HIV-1 protease as an example, Fernandez illustrates how drug designers have employed naturally evolved features of the protein to suppress its activity. Based on these arguments, he dismisses the notion that drug binding is quintessentially promiscuous, even though in principle, proteins did not evolve to associate with man made ligands. In short, Fernandez argues that there may not be separate protein domains that one could term promiscuous domains. While acknowledging that drugs may bind promiscuously or in a native-like manner a la Fernandez, Tawfik maintains the role of evolutionary adaptation, even when a drug binds native-like. In the case of HIV-1 protease, drugs bind natively, and the initial onset of mutations results in drug resistance in addition to a dramatic decline in enzymatic activity and fitness of the virus. A chain of compensatory mutations follows this, and then the virus becomes fully fit and drug resistant. Ben Berkhout and Rogier Sanders subscribe to the evolution of new protein functions through gene duplication. With two identical protein domains, one domain can be released from a constraint imposed by the original function and it is thus free to move in sequence space toward a new function without loss of the original function. They emphasize that the forced evolution of drug-resistance differs significantly from the spontaneous evolution of an additional protein function. For instance, the latter process could proceed gradually on an evolutionary time scale, whereas the acquisition of drug-resistance is an all or nothing process for a virus, leading to the failure or success of therapy. They find no evidence to the thesis that resistance-mutations appear more rapidly in promiscuous domains than native domains. Berkhout and Sanders illustrate the genetic plasticity of HIV-1 by citing examples in which well-conserved amino acid residues of catalytic domains are forced to mutate under drug-pressure. HIV drug resistance biology is very complex. Instead of a viral protein, a drug can be targeted at a cellular protein. For example, Berkhout and Sanders claim, a drug targeted at the cellular protein CCR5 inhibits the binding of the viral envelope glycoprotein (Env) to CCR5. However, Env mutates so that it binds to the CCR5-drug complex and develops drug resistance. Interestingly, CCR5 has not evolved to bind to Env, but to a series of chemokines. Andrzej Kloczkowski, Taner Sen, and Bob Jernigan point out the importance of protein motions for binding. They believe it is likely that different ligands can bind to the diverse protein conformations sampled in the course of normal protein conformational fluctuations. They have been applying simple elastic network models to extract the motions as normal modes, which yield relatively small numbers of conformations that are useful for developing protein mechanisms; while these are typically small motions, for some proteins they can be quite large in scale. One of the major advantages of the approach is that only relatively small numbers of modes are important contributors to the overall motion -- so the approach provides a way to systematically map out a protein's motions. These models successfully represent the conformational fluctuations manifested in the crystallographic B-factors, and often suggest motions related to protein functional behaviors, such as those observed for reverse transcriptase, where two dominant hinges clearly relate to the processing steps -- one showing anti-correlation between the polymerase and ribonuclease H sites related to the translation and positioning of the nucleic acid chain, and another for opening and closing the polymerase site. Disordered proteins represent a more extreme case where the set of accessible conformations is much larger; thus they could offer up a broader range of possible binding forms. Whether evolution controls the functional motions for proteins remains little studied. Intriguingly, buried in the existing databases of protein-protein interactions may be information that can shed light on the extent of promiscuous binding among proteins themselves. Within these data there are cases where large numbers of diverse proteins have been shown to interact with a single protein; some of these could represent promiscuous protein-protein binding. Uncovering these promiscuous behaviors could be important for comprehending the details of how proteins can bind promiscuously to one another, and can exhibit even greater promiscuity in their binding to small molecules. The evolutionary routes, the dynamics of the target protein, and the many other aspects that need to be addressed while designing a drug that may dodge drug resistance, indicate the complexity and multi-disciplinary nature of the issue of drug resistance.
Exploring DNA-binding Proteins with In Vivo Chemical Cross-linking and Mass Spectrometry

PubMed Central

Qiu, Haibo; Wang, Yinsheng

2009-01-01

DNA-binding proteins are very important constituents of proteomes of all species and play crucial roles in transcription, DNA replication, recombination, repair and other activities associated with DNA. Although a number of DNA-binding proteins have been identified, many proteins involved in gene regulation and DNA repair are likely still unknown because of their dynamic and/or weak interactions with DNA. In this report, we described an approach for the comprehensive identification of DNA-binding proteins with in vivo formaldehyde cross-linking and LC-MS/MS. DNA-binding proteins could be purified via the isolation of DNA-protein complexes and released from the complexes by reversing the cross-linking. By using this method, we were able to identify more than one hundred DNA-binding proteins, such as proteins involved in transcription, gene regulation, DNA replication and repair, and a large number of proteins which are potentially associated with DNA and DNA-binding proteins. This method should be generally applicable to the investigation of other nucleic acid-binding proteins, and hold great potential in the comprehensive study of gene regulation, DNA damage response and repair, as well as many other critical biological processes at proteomic level. PMID:19714816
Adrenocortical nuclear progesterone-binding protein: Identification by photoaffinity labeling and evidence for deoxyribonucleic acid binding and stimulation by adrenocorticotropin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Demura, T.; Driscoll, W.J.; Lee, Y.C.

1991-01-01

Nuclei of the guinea pig adrenal cortex contain a protein that specifically binds progesterone and that, biochemically, is clearly distinct from the classical progesterone receptor. The adrenocortical nuclear progesterone-binding protein has now been purified more than 2000-fold by steroid-affinity chromatography with a 75% yield. The purified protein preparation demonstrated three major bands on sodium dodecyl sulfate-polyacrylamide gel of 79K, 74K, and 50K. To determine which of the three might represent the progesterone-binding protein, steroid photoaffinity labeling was performed which resulted in the specific and exclusive labeling of a 50K band. Thus, the adrenocortical nuclear progesterone-binding protein appears to be distinctmore » from the classical progesterone receptor not only biochemically, but also on the basis of molecular size. To test whether the adrenocortical nuclear progesterone-binding protein can be hormonally stimulated, guinea pigs were treated with ACTH. The chronic administration of ACTH caused a 4- to 6-fold increase in the specific progesterone binding capacity without a change in the binding affinity. There appeared to be no significant difference in nuclear progesterone binding between the zona fasciculata and zona reticularis. This finding suggests a mediating role for the progesterone-binding protein in ACTH action. In addition, the nuclear progesterone-binding protein bound to nonspecific DNA sequences, further suggesting a possible transcriptional regulatory role.« less
Fibroblast growth factor regulates insulin-like growth factor-binding protein production by vascular smooth muscle cells.

PubMed

Ververis, J; Ku, L; Delafontaine, P

1994-02-01

Insulin-like growth factor I is an important mitogen for vascular smooth muscle cells, and its effects are regulated by several binding proteins. Western ligand blotting of conditioned medium from rat aortic smooth muscle cells detected a 24 kDa binding protein and a 28 kDa glycosylated variant of this protein, consistent with insulin-like growth factor binding protein-4 by size. Low amounts of a glycosylated 38 to 42 kDa doublet (consistent with binding protein-3) and a 31 kDa non-glycosylated protein also were present. Basic fibroblast growth factor markedly increased secretion of the 24 kDa binding protein and its 28 kDa glycosylated variant. This effect was dose- and time-dependent and was inhibited by co-incubation with cycloheximide. Crosslinking of [125I]-insulin-like growth factor I to cell monolayers revealed no surface-associated binding proteins, either basally or after agonist treatment. Induction of binding protein production by fibroblast growth factor at sites of vascular injury may be important in vascular proliferative responses in vivo.
Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.

PubMed

Li, Yang; Yang, Jianyi

2017-04-24

The prediction of protein-ligand binding affinity has recently been improved remarkably by machine-learning-based scoring functions. For example, using a set of simple descriptors representing the atomic distance counts, the RF-Score improves the Pearson correlation coefficient to about 0.8 on the core set of the PDBbind 2007 database, which is significantly higher than the performance of any conventional scoring function on the same benchmark. A few studies have been made to discuss the performance of machine-learning-based methods, but the reason for this improvement remains unclear. In this study, by systemically controlling the structural and sequence similarity between the training and test proteins of the PDBbind benchmark, we demonstrate that protein structural and sequence similarity makes a significant impact on machine-learning-based methods. After removal of training proteins that are highly similar to the test proteins identified by structure alignment and sequence alignment, machine-learning-based methods trained on the new training sets do not outperform the conventional scoring functions any more. On the contrary, the performance of conventional functions like X-Score is relatively stable no matter what training data are used to fit the weights of its energy terms.
Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis

PubMed Central

2018-01-01

Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that ‘leftover’ proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module allows cells to tune where endocytosis occurs, providing sensitive control over cargo uptake via clathrin-coated vesicles. PMID:29518071
Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis.

PubMed

Holland, David O; Johnson, Margaret E

2018-03-01

Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that 'leftover' proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module allows cells to tune where endocytosis occurs, providing sensitive control over cargo uptake via clathrin-coated vesicles.
Specificity in substrate binding by protein folding catalysts: tyrosine and tryptophan residues are the recognition motifs for the binding of peptides to the pancreas-specific protein disulfide isomerase PDIp.

PubMed Central

Ruddock, L. W.; Freedman, R. B.; Klappa, P.

2000-01-01

Using a cross-linking approach, we recently demonstrated that radiolabeled peptides or misfolded proteins specifically interact in vitro with two luminal proteins in crude extracts from pancreas microsomes. The proteins were the folding catalysts protein disulfide isomerase (PDI) and PDIp, a glycosylated, PDI-related protein, expressed exclusively in the pancreas. In this study, we explore the specificity of these proteins in binding peptides and related ligands and show that tyrosine and tryptophan residues in peptides are the recognition motifs for their binding by PDIp. This peptide-binding specificity may reflect the selectivity of PDIp in binding regions of unfolded polypeptide during catalysis of protein folding. PMID:10794419
Dominant Alcohol-Protein Interaction via Hydration-Enabled Enthalpy-Driven Binding Mechanism

PubMed Central

Chong, Yuan; Kleinhammes, Alfred; Tang, Pei; Xu, Yan; Wu, Yue

2015-01-01

Water plays an important role in weak associations of small drug molecules with proteins. Intense focus has been on binding-induced structural changes in the water network surrounding protein binding sites, especially their contributions to binding thermodynamics. However, water is also tightly coupled to protein conformations and dynamics, and so far little is known about the influence of water-protein interactions on ligand binding. Alcohols are a type of low-affinity drugs, and it remains unclear how water affects alcohol-protein interactions. Here, we present alcohol adsorption isotherms under controlled protein hydration using in-situ NMR detection. As functions of hydration level, Gibbs free energy, enthalpy, and entropy of binding were determined from the temperature dependence of isotherms. Two types of alcohol binding were found. The dominant type is low-affinity nonspecific binding, which is strongly dependent on temperature and the level of hydration. At low hydration levels, this nonspecific binding only occurs above a threshold of alcohol vapor pressure. An increased hydration level reduces this threshold, with it finally disappearing at a hydration level of h~0.2 (g water/g protein), gradually shifting alcohol binding from an entropy-driven to an enthalpy-driven process. Water at charged and polar groups on the protein surface was found to be particularly important in enabling this binding. Although further increase in hydration has smaller effects on the changes of binding enthalpy and entropy, it results in significant negative change in Gibbs free energy due to unmatched enthalpy-entropy compensation. These results show the crucial role of water-protein interplay in alcohol binding. PMID:25856773
Evaluation of Cu(i) binding to the E2 domain of the amyloid precursor protein - a lesson in quantification of metal binding to proteins via ligand competition.

PubMed

Young, Tessa R; Wedd, Anthony G; Xiao, Zhiguang

2018-01-24

The extracellular domain E2 of the amyloid precursor protein (APP) features a His-rich metal-binding site (denoted as the M1 site). In conjunction with surrounding basic residues, the site participates in interactions with components of the extracellular matrix including heparins, a class of negatively charged polysaccharide molecules of varying length. This work studied the chemistry of Cu(i) binding to APP E2 with the probe ligands Bcs, Bca, Fz and Fs. APP E2 forms a stable Cu(i)-mediated ternary complex with each of these anionic ligands. The complex with Bca was selected for isolation and characterization and was demonstrated, by native ESI-MS analysis, to have the stoichiometry E2 : Cu(i) : Bca = 1 : 1 : 1. Formation of these ternary complexes is specific for the APP E2 domain and requires Cu(i) coordination to the M1 site. Mutation of the M1 site was consistent with the His ligands being part of the E2 ligand set. It is likely that interactions between the negatively charged probe ligands and a positively charged patch on the surface of APP E2 are one aspect of the generation of the stable ternary complexes. Their formation prevented meaningful quantification of the affinity of Cu(i) binding to the M1 site with these probe ligands. However, the ternary complexes are disrupted by heparin, allowing reliable determination of a picomolar Cu(i) affinity for the E2/heparin complex with the Fz or Bca probe ligands. This is the first documented example of the formation of stable ternary complexes between a Cu(i) binding protein and a probe ligand. The ready disruption of the complexes by heparin identified clear 'tell-tale' signs for diagnosis of ternary complex formation and allowed a systematic review of conditions and criteria for reliable determination of affinities for metal binding via ligand competition. This study also provides new insights into a potential correlation of APP functions regulated by copper binding and heparin interaction.
Factor H binds to the hypervariable region of many Streptococcus pyogenes M proteins but does not promote phagocytosis resistance or acute virulence.

PubMed

Gustafsson, Mattias C U; Lannergård, Jonas; Nilsson, O Rickard; Kristensen, Bodil M; Olsen, John E; Harris, Claire L; Ufret-Vincenty, Rafael L; Stålhammar-Carlemalm, Margaretha; Lindahl, Gunnar

2013-01-01

Many pathogens express a surface protein that binds the human complement regulator factor H (FH), as first described for Streptococcus pyogenes and the antiphagocytic M6 protein. It is commonly assumed that FH recruited to an M protein enhances virulence by protecting the bacteria against complement deposition and phagocytosis, but the role of FH-binding in S. pyogenes pathogenesis has remained unclear and controversial. Here, we studied seven purified M proteins for ability to bind FH and found that FH binds to the M5, M6 and M18 proteins but not the M1, M3, M4 and M22 proteins. Extensive immunochemical analysis indicated that FH binds solely to the hypervariable region (HVR) of an M protein, suggesting that selection has favored the ability of certain HVRs to bind FH. These FH-binding HVRs could be studied as isolated polypeptides that retain ability to bind FH, implying that an FH-binding HVR represents a distinct ligand-binding domain. The isolated HVRs specifically interacted with FH among all human serum proteins, interacted with the same region in FH and showed species specificity, but exhibited little or no antigenic cross-reactivity. Although these findings suggested that FH recruited to an M protein promotes virulence, studies in transgenic mice did not demonstrate a role for bound FH during acute infection. Moreover, phagocytosis tests indicated that ability to bind FH is neither sufficient nor necessary for S. pyogenes to resist killing in whole human blood. While these data shed new light on the HVR of M proteins, they suggest that FH-binding may affect S. pyogenes virulence by mechanisms not assessed in currently used model systems.

Factor H Binds to the Hypervariable Region of Many Streptococcus pyogenes M Proteins but Does Not Promote Phagocytosis Resistance or Acute Virulence

PubMed Central

Kristensen, Bodil M.; Olsen, John E.; Harris, Claire L.; Ufret-Vincenty, Rafael L.; Stålhammar-Carlemalm, Margaretha; Lindahl, Gunnar

2013-01-01

Many pathogens express a surface protein that binds the human complement regulator factor H (FH), as first described for Streptococcus pyogenes and the antiphagocytic M6 protein. It is commonly assumed that FH recruited to an M protein enhances virulence by protecting the bacteria against complement deposition and phagocytosis, but the role of FH-binding in S. pyogenes pathogenesis has remained unclear and controversial. Here, we studied seven purified M proteins for ability to bind FH and found that FH binds to the M5, M6 and M18 proteins but not the M1, M3, M4 and M22 proteins. Extensive immunochemical analysis indicated that FH binds solely to the hypervariable region (HVR) of an M protein, suggesting that selection has favored the ability of certain HVRs to bind FH. These FH-binding HVRs could be studied as isolated polypeptides that retain ability to bind FH, implying that an FH-binding HVR represents a distinct ligand-binding domain. The isolated HVRs specifically interacted with FH among all human serum proteins, interacted with the same region in FH and showed species specificity, but exhibited little or no antigenic cross-reactivity. Although these findings suggested that FH recruited to an M protein promotes virulence, studies in transgenic mice did not demonstrate a role for bound FH during acute infection. Moreover, phagocytosis tests indicated that ability to bind FH is neither sufficient nor necessary for S. pyogenes to resist killing in whole human blood. While these data shed new light on the HVR of M proteins, they suggest that FH-binding may affect S. pyogenes virulence by mechanisms not assessed in currently used model systems. PMID:23637608
Interaction energies for the purine inhibitor roscovitine with cyclin-dependent kinase 2: correlated ab initio quantum-chemical, DFT and empirical calculations.

PubMed

Dobes, Petr; Otyepka, Michal; Strnad, Miroslav; Hobza, Pavel

2006-05-24

The interaction between roscovitine and cyclin-dependent kinase 2 (cdk2) was investigated by performing correlated ab initio quantum-chemical calculations. The whole protein was fragmented into smaller systems consisting of one or a few amino acids, and the interaction energies of these fragments with roscovitine were determined by using the MP2 method with the extended aug-cc-pVDZ basis set. For selected complexes, the complete basis set limit MP2 interaction energies, as well as the coupled-cluster corrections with inclusion of single, double and noninteractive triples contributions [CCSD(T)], were also evaluated. The energies of interaction between roscovitine and small fragments and between roscovitine and substantial sections of protein (722 atoms) were also computed by using density-functional tight-binding methods covering dispersion energy (DFTB-D) and the Cornell empirical potential. Total stabilisation energy originates predominantly from dispersion energy and methods that do not account for the dispersion energy cannot, therefore, be recommended for the study of protein-inhibitor interactions. The Cornell empirical potential describes reasonably well the interaction between roscovitine and protein; therefore, this method can be applied in future thermodynamic calculations. A limited number of amino acid residues contribute significantly to the binding of roscovitine and cdk2, whereas a rather large number of amino acids make a negligible contribution.
MM-ISMSA: An Ultrafast and Accurate Scoring Function for Protein-Protein Docking.

PubMed

Klett, Javier; Núñez-Salgado, Alfonso; Dos Santos, Helena G; Cortés-Cabrera, Álvaro; Perona, Almudena; Gil-Redondo, Rubén; Abia, David; Gago, Federico; Morreale, Antonio

2012-09-11

An ultrafast and accurate scoring function for protein-protein docking is presented. It includes (1) a molecular mechanics (MM) part based on a 12-6 Lennard-Jones potential; (2) an electrostatic component based on an implicit solvent model (ISM) with individual desolvation penalties for each partner in the protein-protein complex plus a hydrogen bonding term; and (3) a surface area (SA) contribution to account for the loss of water contacts upon protein-protein complex formation. The accuracy and performance of the scoring function, termed MM-ISMSA, have been assessed by (1) comparing the total binding energies, the electrostatic term, and its components (charge-charge and individual desolvation energies), as well as the per residue contributions, to results obtained with well-established methods such as APBSA or MM-PB(GB)SA for a set of 1242 decoy protein-protein complexes and (2) testing its ability to recognize the docking solution closest to the experimental structure as that providing the most favorable total binding energy. For this purpose, a test set consisting of 15 protein-protein complexes with known 3D structure mixed with 10 decoys for each complex was used. The correlation between the values afforded by MM-ISMSA and those from the other methods is quite remarkable (r(2) ∼ 0.9), and only 0.2-5.0 s (depending on the number of residues) are spent on a single calculation including an all vs all pairwise energy decomposition. On the other hand, MM-ISMSA correctly identifies the best docking solution as that closest to the experimental structure in 80% of the cases. Finally, MM-ISMSA can process molecular dynamics trajectories and reports the results as averaged values with their standard deviations. MM-ISMSA has been implemented as a plugin to the widely used molecular graphics program PyMOL, although it can also be executed in command-line mode. MM-ISMSA is distributed free of charge to nonprofit organizations.
Molecular requirements for actin-based lamella formation in Drosophila S2 cells

PubMed Central

Rogers, Stephen L.; Wiedemann, Ursula; Stuurman, Nico; Vale, Ronald D.

2003-01-01

Cell migration occurs through the protrusion of the actin-enriched lamella. Here, we investigated the effects of RNAi depletion of ∼90 proteins implicated in actin function on lamella formation in Drosophila S2 cells. Similar to in vitro reconstitution studies of actin-based Listeria movement, we find that lamellae formation requires a relatively small set of proteins that participate in actin nucleation (Arp2/3 and SCAR), barbed end capping (capping protein), filament depolymerization (cofilin and Aip1), and actin monomer binding (profilin and cyclase-associated protein). Lamellae are initiated by parallel and partially redundant signaling pathways involving Rac GTPases and the adaptor protein Nck, which stimulate SCAR, an Arp2/3 activator. We also show that RNAi of three proteins (kette, Abi, and Sra-1) known to copurify with and inhibit SCAR in vitro leads to SCAR degradation, revealing a novel function of this protein complex in SCAR stability. Our results have identified an essential set of proteins involved in actin dynamics during lamella formation in Drosophila S2 cells. PMID:12975351
[Glutamate-binding membrane proteins from human platelets].

PubMed

Gurevich, V S; Popov, Iu G; Gorodinskiĭ, A I; Dambinova, S A

1991-09-01

Solubilization of the total membrane fraction of human platelets in a 2% solution of sodium deoxycholate and subsequent affinity chromatography on glutamate agarose resulted in two protein fractions possessing a glutamate-binding activity. As can be evidenced from radioligand binding data, the first fraction contains two types of binding sites (Kd1 = 1 microM, Bmax 1 = 100 pmol/mg of protein; Kd2 = 9.3 microMm Bmax2 = 395 pmol/mg of protein). The second fraction has only one type of binding sites (Kd = 1 microM, Bmax = = 110 pmol/mg of protein). SDS-PAAG electrophoresis revealed the presence in the first fraction of proteins with Mr of 14, 24, 56 and 155 kDa, whereas the second fraction was found to contain 14, 46, 71 and 155 kDa proteins. Solid phase immunoenzymatic analysis using poly- and monoclonal specific antibodies against mammalian brain glutamate-binding proteins revealed a marked immunochemical similarity of the isolated protein fractions with human brain synaptic membrane glutamate-binding proteins.
Crystallographic study of FABP5 as an intracellular endocannabinoid transporter

PubMed Central

Sanson, Benoît; Wang, Tao; Sun, Jing; Wang, Liqun; Kaczocha, Martin; Ojima, Iwao; Deutsch, Dale; Li, Huilin

2014-01-01

In addition to binding intracellular fatty acids, fatty-acid-binding proteins (FABPs) have recently been reported to also transport the endocannabinoids anandamide (AEA) and 2-arachidonoylglycerol (2-AG), arachidonic acid derivatives that function as neurotransmitters and mediate a diverse set of physiological and psychological processes. To understand how the endocannabinoids bind to FABPs, the crystal structures of FABP5 in complex with AEA, 2-AG and the inhibitor BMS-309403 were determined. These ligands are shown to interact primarily with the substrate-binding pocket via hydrophobic interactions as well as a common hydrogen bond to the Tyr131 residue. This work advances our understanding of FABP5–endocannabinoid interactions and may be useful for future efforts in the development of small-molecule inhibitors to raise endocannabinoid levels. PMID:24531463
Structural Context of Disease-Associated Mutations and Putative Mechanism of Autoinhibition Revealed by X-Ray Crystallographic Analysis of the EZH2-SET Domain

PubMed Central

Antonysamy, Stephen; Condon, Bradley; Druzina, Zhanna; Bonanno, Jeffrey B.; Gheyi, Tarun; Zhang, Feiyu; MacEwan, Iain; Zhang, Aiping; Ashok, Sheela; Rodgers, Logan; Russell, Marijane; Gately Luz, John

2013-01-01

The enhancer-of-zeste homolog 2 (EZH2) gene product is an 87 kDa polycomb group (PcG) protein containing a C-terminal methyltransferase SET domain. EZH2, along with binding partners, i.e., EED and SUZ12, upon which it is dependent for activity forms the core of the polycomb repressive complex 2 (PRC2). PRC2 regulates gene silencing by catalyzing the methylation of histone H3 at lysine 27. Both overexpression and mutation of EZH2 are associated with the incidence and aggressiveness of various cancers. The novel crystal structure of the SET domain was determined in order to understand disease-associated EZH2 mutations and derive an explanation for its inactivity independent of complex formation. The 2.00 Å crystal structure reveals that, in its uncomplexed form, the EZH2 C-terminus folds back into the active site blocking engagement with substrate. Furthermore, the S-adenosyl-L-methionine (SAM) binding pocket observed in the crystal structure of homologous SET domains is notably absent. This suggests that a conformational change in the EZH2 SET domain, dependent upon complex formation, must take place for cofactor and substrate binding activities to be recapitulated. In addition, the data provide a structural context for clinically significant mutations found in the EZH2 SET domain. PMID:24367637
Hyperdiversity of Genes Encoding Integral Light-Harvesting Proteins in the Dinoflagellate Symbiodinium sp

PubMed Central

Boldt, Lynda; Yellowlees, David; Leggat, William

2012-01-01

The superfamily of light-harvesting complex (LHC) proteins is comprised of proteins with diverse functions in light-harvesting and photoprotection. LHC proteins bind chlorophyll (Chl) and carotenoids and include a family of LHCs that bind Chl a and c. Dinophytes (dinoflagellates) are predominantly Chl c binding algal taxa, bind peridinin or fucoxanthin as the primary carotenoid, and can possess a number of LHC subfamilies. Here we report 11 LHC sequences for the chlorophyll a-chlorophyll c 2-peridinin protein complex (acpPC) subfamily isolated from Symbiodinium sp. C3, an ecologically important peridinin binding dinoflagellate taxa. Phylogenetic analysis of these proteins suggests the acpPC subfamily forms at least three clades within the Chl a/c binding LHC family; Clade 1 clusters with rhodophyte, cryptophyte and peridinin binding dinoflagellate sequences, Clade 2 with peridinin binding dinoflagellate sequences only and Clades 3 with heterokontophytes, fucoxanthin and peridinin binding dinoflagellate sequences. PMID:23112815
Protein Binding: Do We Ever Learn?▿

PubMed Central

Zeitlinger, Markus A.; Derendorf, Hartmut; Mouton, Johan W.; Cars, Otto; Craig, William A.; Andes, David; Theuretzbacher, Ursula

2011-01-01

Although the influence of protein binding (PB) on antibacterial activity has been reported for many antibiotics and over many years, there is currently no standardization for pharmacodynamic models that account for the impact of protein binding of antimicrobial agents in vitro. This might explain the somewhat contradictory results obtained from different studies. Simple in vitro models which compare the MIC obtained in protein-free standard medium versus a protein-rich medium are prone to methodological pitfalls and may lead to flawed conclusions. Within in vitro test systems, a range of test conditions, including source of protein, concentration of the tested antibiotic, temperature, pH, electrolytes, and supplements may influence the impact of protein binding. As new antibiotics with a high degree of protein binding are in clinical development, attention and action directed toward the optimization and standardization of testing the impact of protein binding on the activity of antibiotics in vitro become even more urgent. In addition, the quantitative relationship between the effects of protein binding in vitro and in vivo needs to be established, since the physiological conditions differ. General recommendations for testing the impact of protein binding in vitro are suggested. PMID:21537013
Functional importance of short-range binding and long-range solvent interactions in helical antifreeze peptides.

PubMed

Ebbinghaus, Simon; Meister, Konrad; Prigozhin, Maxim B; Devries, Arthur L; Havenith, Martina; Dzubiella, Joachim; Gruebele, Martin

2012-07-18

Short-range ice binding and long-range solvent perturbation both have been implicated in the activity of antifreeze proteins and antifreeze glycoproteins. We study these two mechanisms for activity of winter flounder antifreeze peptide. Four mutants are characterized by freezing point hysteresis (activity), circular dichroism (secondary structure), Förster resonance energy transfer (end-to-end rigidity), molecular dynamics simulation (structure), and terahertz spectroscopy (long-range solvent perturbation). Our results show that the short-range model is sufficient to explain the activity of our mutants, but the long-range model provides a necessary condition for activity: the most active peptides in our data set all have an extended dynamical hydration shell. It appears that antifreeze proteins and antifreeze glycoproteins have reached different evolutionary solutions to the antifreeze problem, utilizing either a few precisely positioned OH groups or a large quantity of OH groups for ice binding, assisted by long-range solvent perturbation. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.
The mRNA-bound proteome of the early fly embryo

PubMed Central

Wessels, Hans-Hermann; Imami, Koshi; Baltz, Alexander G.; Kolinski, Marcin; Beldovskaya, Anastasia; Selbach, Matthias; Small, Stephen; Ohler, Uwe; Landthaler, Markus

2016-01-01

Early embryogenesis is characterized by the maternal to zygotic transition (MZT), in which maternally deposited messenger RNAs are degraded while zygotic transcription begins. Before the MZT, post-transcriptional gene regulation by RNA-binding proteins (RBPs) is the dominant force in embryo patterning. We used two mRNA interactome capture methods to identify RBPs bound to polyadenylated transcripts within the first 2 h of Drosophila melanogaster embryogenesis. We identified a high-confidence set of 476 putative RBPs and confirmed RNA-binding activities for most of 24 tested candidates. Most proteins in the interactome are known RBPs or harbor canonical RBP features, but 99 exhibited previously uncharacterized RNA-binding activity. mRNA-bound RBPs and TFs exhibit distinct expression dynamics, in which the newly identified RBPs dominate the first 2 h of embryonic development. Integrating our resource with in situ hybridization data from existing databases showed that mRNAs encoding RBPs are enriched in posterior regions of the early embryo, suggesting their general importance in posterior patterning and germ cell maturation. PMID:27197210
Successive gain of insulator proteins in arthropod evolution.

PubMed

Heger, Peter; George, Rebecca; Wiehe, Thomas

2013-10-01

Alteration of regulatory DNA elements or their binding proteins may have drastic consequences for morphological evolution. Chromatin insulators are one example of such proteins and play a fundamental role in organizing gene expression. While a single insulator protein, CTCF (CCCTC-binding factor), is known in vertebrates, Drosophila melanogaster utilizes six additional factors. We studied the evolution of these proteins and show here that-in contrast to the bilaterian-wide distribution of CTCF-all other D. melanogaster insulators are restricted to arthropods. The full set is present exclusively in the genus Drosophila whereas only two insulators, Su(Hw) and CTCF, existed at the base of the arthropod clade and all additional factors have been acquired successively at later stages. Secondary loss of factors in some lineages further led to the presence of different insulator subsets in arthropods. Thus, the evolution of insulator proteins within arthropods is an ongoing and dynamic process that reshapes and supplements the ancient CTCF-based system common to bilaterians. Expansion of insulator systems may therefore be a general strategy to increase an organism's gene regulatory repertoire and its potential for morphological plasticity. © 2013 The Authors. Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.
Single Molecule Spectroscopy of Amino Acids and Peptides by Recognition Tunneling

PubMed Central

Zhao, Yanan; Ashcroft, Brian; Zhang, Peiming; Liu, Hao; Sen, Suman; Song, Weisi; Im, JongOne; Gyarfas, Brett; Manna, Saikat; Biswas, Sovan; Borges, Chad; Lindsay, Stuart

2014-01-01

The human proteome has millions of protein variants due to alternative RNA splicing and post-translational modifications, and variants that are related to diseases are frequently present in minute concentrations. For DNA and RNA, low concentrations can be amplified using the polymerase chain reaction, but there is no such reaction for proteins. Therefore, the development of single molecule protein sequencing is a critical step in the search for protein biomarkers. Here we show that single amino acids can be identified by trapping the molecules between two electrodes that are coated with a layer of recognition molecules and measuring the electron tunneling current across the junction. A given molecule can bind in more than one way in the junction, and we therefore use a machine-learning algorithm to distinguish between the sets of electronic ‘fingerprints’ associated with each binding motif. With this recognition tunneling technique, we are able to identify D, L enantiomers, a methylated amino acid, isobaric isomers, and short peptides. The results suggest that direct electronic sequencing of single proteins could be possible by sequentially measuring the products of processive exopeptidase digestion, or by using a molecular motor to pull proteins through a tunnel junction integrated with a nanopore. PMID:24705512
Protein-Protein Interactions in a Crowded Environment: An Analysis via Cross-Docking Simulations and Evolutionary Information

PubMed Central

Lopes, Anne; Sacquin-Mora, Sophie; Dimitrova, Viktoriya; Laine, Elodie; Ponty, Yann; Carbone, Alessandra

2013-01-01

Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information showing that the combination of the two improves partner identification. On the other hand, since protein interactions usually occur in crowded environments with several competing partners, we realized a thorough analysis of the interactions of proteins with true partners but also with non-partners to evaluate whether proteins in the environment, competing with the true partner, affect its identification. We found three populations of proteins: strongly competing, never competing, and interacting with different levels of strength. Populations and levels of strength are numerically characterized and provide a signature for the behavior of a protein in the crowded environment. We showed that partner identification, to some extent, does not depend on the competing partners present in the environment, that certain biochemical classes of proteins are intrinsically easier to analyze than others, and that small proteins are not more promiscuous than large ones. Our approach brings to light that the knowledge of the binding site can be used to reduce the high computational cost of docking simulations with no consequence in the quality of the results, demonstrating the possibility to apply coarse-grain docking to datasets made of thousands of proteins. Comparison with all available large-scale analyses aimed to partner predictions is realized. We release the complete decoys set issued by coarse-grain docking simulations of both true and false interacting partners, and their evolutionary sequence analysis leading to binding site predictions. Download site: http://www.lgm.upmc.fr/CCDMintseris/ PMID:24339765
Interaction of Tenebrio Molitor Antifreeze Protein with Ice Crystal: Insights from Molecular Dynamics Simulations.

PubMed

Ramya, L; Ramakrishnan, Vigneshwar

2016-07-01

Antifreeze proteins (AFP) observed in cold-adapting organisms bind to ice crystals and prevent further ice growth. However, the molecular mechanism of AFP-ice binding and AFP-inhibited ice growth remains unclear. Here we report the interaction of the insect antifreeze protein (Tenebrio molitor, TmAFP) with ice crystal by molecular dynamics simulation studies. Two sets of simulations were carried out at 263 K by placing the protein near the primary prism plane (PP) and basal plane (BL) of the ice crystal. To delineate the effect of temperatures, both the PP and BL simulations were carried out at 253 K as well. The analyses revealed that the protein interacts strongly with the ice crystal in BL simulation than in PP simulation both at 263 K and 253 K. Further, it was observed that the interactions are primarily mediated through the interface waters. We also observed that as the temperature decreases, the interaction between the protein and the ice increases which can be attributed to the decreased flexibility and the increased structuring of the protein at low temperature. In essence, our study has shed light on the interaction mechanism between the TmAFP antifreeze protein and the ice crystal. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Principal component analysis on molecular descriptors as an alternative point of view in the search of new Hsp90 inhibitors.

PubMed

Lauria, Antonino; Ippolito, Mario; Almerico, Anna Maria

2009-10-01

Inhibiting a protein that regulates multiple signal transduction pathways in cancer cells is an attractive goal for cancer therapy. Heat shock protein 90 (Hsp90) is one of the most promising molecular targets for such an approach. In fact, Hsp90 is a ubiquitous molecular chaperone protein that is involved in folding, activating and assembling of many key mediators of signal transduction, cellular growth, differentiation, stress-response and apoptothic pathways. With the aim to analyze which molecular descriptors have the higher importance in the binding interactions of these classes, we first performed molecular docking experiments on the 187 Hsp90 inhibitors included in the BindingDB, a public database of measured binding affinities. Further, for each frozen conformation obtained from the docking, a set of 250 molecular descriptors was calculated, and the resulting Structure/Descriptors matrix was submitted to Principal Component Analysis. From the factor scores it emerged a good clusterization among similar compounds both in terms of structural class and activity spectrum, while examination of the loadings of the first two factors also allowed to study the classes of descriptors which mainly contribute to each one.
Fully Flexible Docking of Medium Sized Ligand Libraries with RosettaLigand

PubMed Central

DeLuca, Samuel; Khar, Karen; Meiler, Jens

2015-01-01

RosettaLigand has been successfully used to predict binding poses in protein-small molecule complexes. However, the RosettaLigand docking protocol is comparatively slow in identifying an initial starting pose for the small molecule (ligand) making it unfeasible for use in virtual High Throughput Screening (vHTS). To overcome this limitation, we developed a new sampling approach for placing the ligand in the protein binding site during the initial ‘low-resolution’ docking step. It combines the translational and rotational adjustments to the ligand pose in a single transformation step. The new algorithm is both more accurate and more time-efficient. The docking success rate is improved by 10–15% in a benchmark set of 43 protein/ligand complexes, reducing the number of models that typically need to be generated from 1000 to 150. The average time to generate a model is reduced from 50 seconds to 10 seconds. As a result we observe an effective 30-fold speed increase, making RosettaLigand appropriate for docking medium sized ligand libraries. We demonstrate that this improved initial placement of the ligand is critical for successful prediction of an accurate binding position in the ‘high-resolution’ full atom refinement step. PMID:26207742
Protein binding hot spots prediction from sequence only by a new ensemble learning method.

PubMed

Hu, Shan-Shan; Chen, Peng; Wang, Bing; Li, Jinyan

2017-10-01

Hot spots are interfacial core areas of binding proteins, which have been applied as targets in drug design. Experimental methods are costly in both time and expense to locate hot spot areas. Recently, in-silicon computational methods have been widely used for hot spot prediction through sequence or structure characterization. As the structural information of proteins is not always solved, and thus hot spot identification from amino acid sequences only is more useful for real-life applications. This work proposes a new sequence-based model that combines physicochemical features with the relative accessible surface area of amino acid sequences for hot spot prediction. The model consists of 83 classifiers involving the IBk (Instance-based k means) algorithm, where instances are encoded by important properties extracted from a total of 544 properties in the AAindex1 (Amino Acid Index) database. Then top-performance classifiers are selected to form an ensemble by a majority voting technique. The ensemble classifier outperforms the state-of-the-art computational methods, yielding an F1 score of 0.80 on the benchmark binding interface database (BID) test set. http://www2.ahu.edu.cn/pchen/web/HotspotEC.htm .
Consensus Induced Fit Docking (cIFD): methodology, validation, and application to the discovery of novel Crm1 inhibitors

NASA Astrophysics Data System (ADS)

Kalid, Ori; Toledo Warshaviak, Dora; Shechter, Sharon; Sherman, Woody; Shacham, Sharon

2012-11-01

We present the Consensus Induced Fit Docking (cIFD) approach for adapting a protein binding site to accommodate multiple diverse ligands for virtual screening. This novel approach results in a single binding site structure that can bind diverse chemotypes and is thus highly useful for efficient structure-based virtual screening. We first describe the cIFD method and its validation on three targets that were previously shown to be challenging for docking programs (COX-2, estrogen receptor, and HIV reverse transcriptase). We then demonstrate the application of cIFD to the challenging discovery of irreversible Crm1 inhibitors. We report the identification of 33 novel Crm1 inhibitors, which resulted from the testing of 402 purchased compounds selected from a screening set containing 261,680 compounds. This corresponds to a hit rate of 8.2 %. The novel Crm1 inhibitors reveal diverse chemical structures, validating the utility of the cIFD method in a real-world drug discovery project. This approach offers a pragmatic way to implicitly account for protein flexibility without the additional computational costs of ensemble docking or including full protein flexibility during virtual screening.
Like-charged protein-polyelectrolyte complexation driven by charge patches

NASA Astrophysics Data System (ADS)

Yigit, Cemil; Heyda, Jan; Ballauff, Matthias; Dzubiella, Joachim

2015-08-01

We study the pair complexation of a single, highly charged polyelectrolyte (PE) chain (of 25 or 50 monomers) with like-charged patchy protein models (CPPMs) by means of implicit-solvent, explicit-salt Langevin dynamics computer simulations. Our previously introduced set of CPPMs embraces well-defined zero-, one-, and two-patched spherical globules each of the same net charge and (nanometer) size with mono- and multipole moments comparable to those of globular proteins with similar size. We observe large binding affinities between the CPPM and the like-charged PE in the tens of the thermal energy, kBT, that are favored by decreasing salt concentration and increasing charge of the patch(es). Our systematic analysis shows a clear correlation between the distance-resolved potentials of mean force, the number of ions released from the PE, and CPPM orientation effects. In particular, we find a novel two-site binding behavior for PEs in the case of two-patched CPPMs, where intermediate metastable complex structures are formed. In order to describe the salt-dependence of the binding affinity for mainly dipolar (one-patched) CPPMs, we introduce a combined counterion-release/Debye-Hückel model that quantitatively captures the essential physics of electrostatic complexation in our systems.

An introduction to best practices in free energy calculations.

PubMed

Shirts, Michael R; Mobley, David L

2013-01-01

Free energy calculations are extremely useful for investigating small-molecule biophysical properties such as protein-ligand binding affinities and partition coefficients. However, these calculations are also notoriously difficult to implement correctly. In this chapter, we review standard methods for computing free energy via simulation, discussing current best practices and examining potential pitfalls for computational researchers performing them for the first time. We include a variety of examples and tips for how to set up and conduct these calculations, including applications to relative binding affinities and small-molecule solvation free energies.
Ion-binding properties of Calnuc, Ca2+ versus Mg2+--Calnuc adopts additional and unusual Ca2+-binding sites upon interaction with G-protein.

PubMed

Kanuru, Madhavi; Samuel, Jebakumar J; Balivada, Lavanya M; Aradhyam, Gopala K

2009-05-01

Calnuc is a novel, highly modular, EF-hand containing, Ca(2+)-binding, Golgi resident protein whose functions are not clear. Using amino acid sequences, we demonstrate that Calnuc is a highly conserved protein among various organisms, from Ciona intestinalis to humans. Maximum homology among all sequences is found in the region that binds to G-proteins. In humans, it is known to be expressed in a variety of tissues, and it interacts with several important protein partners. Among other proteins, Calnuc is known to interact with heterotrimeric G-proteins, specifically with the alpha-subunit. Herein, we report the structural implications of Ca(2+) and Mg(2+) binding, and illustrate that Calnuc functions as a downstream effector for G-protein alpha-subunit. Our results show that Ca(2+) binds with an affinity of 7 mum and causes structural changes. Although Mg(2+) binds to Calnuc with very weak affinity, the structural changes that it causes are further enhanced by Ca(2+) binding. Furthermore, isothermal titration calorimetry results show that Calnuc and the G-protein bind with an affinity of 13 nm. We also predict a probable function for Calnuc, that of maintaining Ca(2+) homeostasis in the cell. Using Stains-all and terbium as Ca(2+) mimic probes, we demonstrate that the Ca(2+)-binding ability of Calnuc is governed by the activity-based conformational state of the G-protein. We propose that Calnuc adopts structural sites similar to the ones seen in proteins such as annexins, c2 domains or chromogrannin A, and therefore binds more calcium ions upon binding to Gialpha. With the number of organelle-targeted G-protein-coupled receptors increasing, intracellular communication mediated by G-proteins could become a new paradigm. In this regard, we propose that Calnuc could be involved in the downstream signaling of G-proteins.
Prediction of binding hot spot residues by using structural and evolutionary parameters

PubMed Central

2009-01-01

In this work, we present a method for predicting hot spot residues by using a set of structural and evolutionary parameters. Unlike previous studies, we use a set of parameters which do not depend on the structure of the protein in complex, so that the predictor can also be used when the interface region is unknown. Despite the fact that no information concerning proteins in complex is used for prediction, the application of the method to a compiled dataset described in the literature achieved a performance of 60.4%, as measured by F-Measure, corresponding to a recall of 78.1% and a precision of 49.5%. This result is higher than those reported by previous studies using the same data set. PMID:21637529
In Situ Protein Binding Assay Using Fc-Fusion Proteins.

PubMed

Padmanabhan, Nirmala; Siddiqui, Tabrez J

2017-01-01

This protocol describes an in situ protein-protein interaction assay between tagged recombinant proteins and cell-surface expressed synaptic proteins. The assay is arguably more sensitive than other traditional protein binding assays such as co-immunoprecipitation and pull-downs and provides a visual readout for binding. This assay has been widely used to determine the dissociation constant of binding of trans-synaptic adhesion proteins. The step-wise description in the protocol should facilitate the adoption of this method in other laboratories.
Fc-Binding Ligands of Immunoglobulin G: An Overview of High Affinity Proteins and Peptides

PubMed Central

Choe, Weonu; Durgannavar, Trishaladevi A.; Chung, Sang J.

2016-01-01

The rapidly increasing application of antibodies has inspired the development of several novel methods to isolate and target antibodies using smart biomaterials that mimic the binding of Fc-receptors to antibodies. The Fc-binding domain of antibodies is the primary binding site for e.g., effector proteins and secondary antibodies, whereas antigens bind to the Fab region. Protein A, G, and L, surface proteins expressed by pathogenic bacteria, are well known to bind immunoglobulin and have been widely exploited in antibody purification strategies. Several difficulties are encountered when bacterial proteins are used in antibody research and application. One of the major obstacles hampering the use of bacterial proteins is sample contamination with trace amounts of these proteins, which can invoke an immune response in the host. Many research groups actively develop synthetic ligands that are able to selectively and strongly bind to antibodies. Among the reported ligands, peptides that bind to the Fc-domain of antibodies are attractive tools in antibody research. Besides their use as high affinity ligands in antibody purification chromatography, Fc-binding peptides are applied e.g., to localize antibodies on nanomaterials and to increase the half-life of proteins in serum. In this review, recent developments of Fc-binding peptides are presented and their binding characteristics and diverse applications are discussed. PMID:28774114
21 CFR 866.5765 - Retinol-binding protein immunological test system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... SERVICES (CONTINUED) MEDICAL DEVICES IMMUNOLOGY AND MICROBIOLOGY DEVICES Immunological Test Systems § 866.5765 Retinol-binding protein immunological test system. (a) Identification. A retinol-binding protein... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Retinol-binding protein immunological test system...
GMXPBSA 2.1: A GROMACS tool to perform MM/PBSA and computational alanine scanning

NASA Astrophysics Data System (ADS)

Paissoni, C.; Spiliotopoulos, D.; Musco, G.; Spitaleri, A.

2015-01-01

GMXPBSA 2.1 is a user-friendly suite of Bash/Perl scripts for streamlining MM/PBSA calculations on structural ensembles derived from GROMACS trajectories, to automatically calculate binding free energies for protein-protein or ligand-protein complexes [R.T. Bradshaw et al., Protein Eng. Des. Sel. 24 (2011) 197-207]. GMXPBSA 2.1 is flexible and can easily be customized to specific needs and it is an improvement of the previous GMXPBSA 2.0 [C. Paissoni et al., Comput. Phys. Commun. (2014), 185, 2920-2929]. Additionally, it performs computational alanine scanning (CAS) to study the effects of ligand and/or receptor alanine mutations on the free energy of binding. Calculations require only for protein-protein or protein-ligand MD simulations. GMXPBSA 2.1 performs different comparative analyses, including a posteriori generation of alanine mutants of the wild-type complex, calculation of the binding free energy values of the mutant complexes and comparison of the results with the wild-type system. Moreover, it compares the binding free energy of different complex trajectories, allowing the study of the effects of non-alanine mutations, post-translational modifications or unnatural amino acids on the binding free energy of the system under investigation. Finally, it can calculate and rank relative affinity to the same receptor utilizing MD simulations of proteins in complex with different ligands. In order to dissect the different MM/PBSA energy contributions, including molecular mechanic (MM), electrostatic contribution to solvation (PB) and nonpolar contribution to solvation (SA), the tool combines two freely available programs: the MD simulations software GROMACS [S. Pronk et al., Bioinformatics 29 (2013) 845-854] and the Poisson-Boltzmann equation solver APBS [N.A. Baker et al., Proc. Natl. Acad. Sci. U.S.A 98 (2001) 10037-10041]. All the calculations can be performed in single or distributed automatic fashion on a cluster facility in order to increase the calculation by dividing frames across the available processors. This new version with respect to our previously published GMXPBSA 2.0 fixes some problem and allows additional kind of calculations, such as CAS on single protein in order to individuate the hot-spots, more custom options to perform APBS calculations, improvements of speed calculation of APBS (precF set to 0), possibility to work with multichain systems (see Summary of revisions for more details). The program is freely available under the GPL license.
Lipid-binding proteins modulate ligand-dependent trans-activation by peroxisome proliferator-activated receptors and localize to the nucleus as well as the cytoplasm.

PubMed

Helledie, T; Antonius, M; Sorensen, R V; Hertzel, A V; Bernlohr, D A; Kølvraa, S; Kristiansen, K; Mandrup, S

2000-11-01

Peroxisome proliferator-activated receptors (PPARs) are activated by a variety of fatty acids, eicosanoids, and hypolipidemic and insulin-sensitizing drugs. Many of these compounds bind avidly to members of a family of small lipid-binding proteins, the fatty acid-binding proteins (FABPs). Fatty acids are activated to CoA esters, which bind with high affinity to the acyl-CoA-binding protein (ACBP). Thus, the availability of known and potential PPAR ligands may be regulated by lipid-binding proteins. In this report we show by transient transfection of CV-1 cells that coexpression of ACBP and adipocyte lipid-binding protein (ALBP) exerts a ligand- and PPAR subtype-specific attenuation of PPAR-mediated trans-activation, suggesting that lipid-binding proteins, when expressed at high levels, may function as negative regulators of PPAR activation by certain ligands. Expression of ACBP, ALBP, and keratinocyte lipid-binding protein (KLBP) is induced during adipocyte differentiation, a process during which PPARgamma plays a prominent role. We present evidence that endogenous ACBP, ALBP, and KLBP not only localize to the cytoplasm but also exhibit a prominent nuclear localization in 3T3-L1 adipocytes. In addition, forced expression of ACBP, ALBP, and KLBP in CV-1 cells resulted in a substantial accumulation of all three proteins in the nucleus. These results suggest that lipid-binding proteins, contrary to the general assumption, may exert their action in the nucleus as well as in the cytoplasm.
Unconventional RNA-binding proteins: an uncharted zone in RNA biology.

PubMed

Albihlal, Waleed S; Gerber, André P

2018-06-16

RNA-binding proteins play essential roles in the post-transcriptional regulation of gene expression. While hundreds of RNA-binding proteins can be predicted computationally, the recent introduction of proteome-wide approaches has dramatically expanded the repertoire of proteins interacting with RNA. Besides canonical RNA-binding proteins that contain characteristic RNA-binding domains, many proteins that lack such domains but have other well-characterised cellular functions were identified; including metabolic enzymes, heat shock proteins, kinases, as well as transcription factors and chromatin-associated proteins. In the context of these recently published RNA-protein interactome datasets obtained from yeast, nematodes, flies, plants and mammalian cells, we discuss examples for seemingly evolutionary conserved "unconventional" RNA-binding proteins that act in central carbon metabolism, stress response or regulation of transcription. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
The hepta-beta-glucoside elicitor-binding proteins from legumes represent a putative receptor family.

PubMed

Mithöfer, A; Fliegmann, J; Neuhaus-Url, G; Schwarz, H; Ebel, J

2000-08-01

The ability of legumes to recognize and respond to beta-glucan elicitors by synthesizing phytoalexins is consistent with the existence of a membrane-bound beta-glucan-binding site. Related proteins of approximately 75 kDa and the corresponding mRNAs were detected in various species of legumes which respond to beta-glucans. The cDNAs for the beta-glucan-binding proteins of bean and soybean were cloned. The deduced 75-kDa proteins are predominantly hydrophilic and constitute a unique class of glucan-binding proteins with no currently recognizable functional domains. Heterologous expression of the soybean beta-glucan-binding protein in tomato cells resulted in the generation of a high-affinity binding site for the elicitor-active hepta-beta-glucoside conjugate (Kd = 4.5 nM). Ligand competition experiments with the recombinant binding sites demonstrated similar ligand specificities when compared with soybean. In both soybean and transgenic tomato, membrane-bound, active forms of the glucan-binding proteins coexist with immunologically detectable, soluble but inactive forms of the proteins. Reconstitution of a soluble protein fraction into lipid vesicles regained beta-glucoside-binding activity but with lower affinity (Kd = 130 nM). We conclude that the beta-glucan elicitor receptors of legumes are composed of the 75 kDa glucan-binding proteins as the critical components for ligand-recognition, and of an as yet unknown membrane anchor constituting the plasma membrane-associated receptor complex.
Isolation from genomic DNA of sequences binding specific regulatory proteins by the acceleration of protein electrophoretic mobility upon DNA binding.

PubMed

Subrahmanyam, S; Cronan, J E

1999-01-21

We report an efficient and flexible in vitro method for the isolation of genomic DNA sequences that are the binding targets of a given DNA binding protein. This method takes advantage of the fact that binding of a protein to a DNA molecule generally increases the rate of migration of the protein in nondenaturing gel electrophoresis. By the use of a radioactively labeled DNA-binding protein and nonradioactive DNA coupled with PCR amplification from gel slices, we show that specific binding sites can be isolated from Escherichia coli genomic DNA. We have applied this method to isolate a binding site for FadR, a global regulator of fatty acid metabolism in E. coli. We have also isolated a second binding site for BirA, the biotin operon repressor/biotin ligase, from the E. coli genome that has a very low binding efficiency compared with the bio operator region.
Engineered proteins as specific binding reagents.

PubMed

Binz, H Kaspar; Plückthun, Andreas

2005-08-01

Over the past 30 years, monoclonal antibodies have become the standard binding proteins and currently find applications in research, diagnostics and therapy. Yet, monoclonal antibodies now face strong competition from synthetic antibody libraries in combination with powerful library selection technologies. More recently, an increased understanding of other natural binding proteins together with advances in protein engineering, selection and evolution technologies has also triggered the exploration of numerous other protein architectures for the generation of designed binding molecules. Valuable protein-binding scaffolds have been obtained and represent promising alternatives to antibodies for biotechnological and, potentially, clinical applications.
The DEAD-Box Protein CYT-19 Uses Arginine Residues in Its C-Tail To Tether RNA Substrates.

PubMed

Busa, Veronica F; Rector, Maxwell J; Russell, Rick

2017-07-18

DEAD-box proteins are nonprocessive RNA helicases that play diverse roles in cellular processes. The Neurospora crassa DEAD-box protein CYT-19 promotes mitochondrial group I intron splicing and functions as a general RNA chaperone. CYT-19 includes a disordered, arginine-rich "C-tail" that binds RNA, positioning the helicase core to capture and unwind nearby RNA helices. Here we probed the C-tail further by varying the number and positions of arginines within it. We found that removing sets of as few as four of the 11 arginines reduced RNA unwinding activity (k cat /K M ) to a degree equivalent to that seen upon removal of the C-tail, suggesting that a minimum or "threshold" number of arginines is required. In addition, a mutant with 16 arginines displayed RNA unwinding activity greater than that of wild-type CYT-19. The C-tail modifications impacted unwinding only of RNA helices within constructs that included an adjacent helix or structured RNA element that would allow C-tail binding, indicating that the helicase core remained active in the mutants. In addition, changes in RNA unwinding efficiency of the mutants were mirrored by changes in functional RNA affinity, as determined from the RNA concentration dependence of ATPase activity, suggesting that the C-tail functions primarily to increase RNA affinity. Interestingly, the salt concentration dependence of RNA unwinding activity is unaffected by C-tail composition, suggesting that the C-tail uses primarily hydrogen bonding, not electrostatic interactions, to bind double-stranded RNA. Our results provide insights into how an unstructured C-tail contributes to DEAD-box protein activity and suggest parallels with other families of RNA- and DNA-binding proteins.
Nuclease-resistant c-di-AMP derivatives that differentially recognize RNA and protein receptors

PubMed Central

Meehan, Robert E.; Torgerson, Chad D.; Gaffney, Barbara L.; Jones, Roger A.; Strobel, Scott A.

2016-01-01

The ability of bacteria to sense environmental cues and adapt is essential for their survival. The use of second-messenger signaling molecules to translate these cues into a physiological response is a common mechanism employed by bacteria. The second messenger 3’-5’-cyclic diadenosine monophosphate (c-di-AMP) has been linked to a diverse set of biological processes involved in maintaining cell viability and homeostasis, as well as pathogenicity. A complex network of both protein and RNA receptors inside the cell activate specific pathways and mediate phenotypic outputs in response to c-di-AMP. Structural analysis of these RNA and protein receptors has revealed the different recognition elements employed by these effectors to bind the same small molecule. Herein, using a series of c-di-AMP analogs, we probed the interactions made with a riboswitch and a phosphodiesterase protein to identify the features important for c-di-AMP binding and recognition. We found that the ydaO riboswitch binds c-di-AMP in two discrete sites with near identical affinity and a Hill coefficient of 1.6. The ydaO riboswitch distinguishes between c-di-AMP and structurally related second messengers by discriminating against an amine at the C2 position, more than a carbonyl at the C6 position. We also identified phosphate-modified analogs that bind both the ydaO RNA and GdpP protein with high affinity, while symmetrically-modified ribose analogs exhibited a substantial decrease in ydaO affinity, but retained high affinity for GdpP. These ligand modifications resulted in increased resistance to enzyme-catalyzed hydrolysis by the GdpP enzyme. Together, these data suggest that these c-di-AMP analogs could be useful as chemical tools to specifically target subsections of the second-messenger signaling pathways. PMID:26789423
The Impact of Protein Structure and Sequence Similarity on the Accuracy of Machine-Learning Scoring Functions for Binding Affinity Prediction

PubMed Central

Peng, Jiangjun; Leung, Yee; Leung, Kwong-Sak; Wong, Man-Hon; Lu, Gang; Ballester, Pedro J.

2018-01-01

It has recently been claimed that the outstanding performance of machine-learning scoring functions (SFs) is exclusively due to the presence of training complexes with highly similar proteins to those in the test set. Here, we revisit this question using 24 similarity-based training sets, a widely used test set, and four SFs. Three of these SFs employ machine learning instead of the classical linear regression approach of the fourth SF (X-Score which has the best test set performance out of 16 classical SFs). We have found that random forest (RF)-based RF-Score-v3 outperforms X-Score even when 68% of the most similar proteins are removed from the training set. In addition, unlike X-Score, RF-Score-v3 is able to keep learning with an increasing training set size, becoming substantially more predictive than X-Score when the full 1105 complexes are used for training. These results show that machine-learning SFs owe a substantial part of their performance to training on complexes with dissimilar proteins to those in the test set, against what has been previously concluded using the same data. Given that a growing amount of structural and interaction data will be available from academic and industrial sources, this performance gap between machine-learning SFs and classical SFs is expected to enlarge in the future. PMID:29538331
The Impact of Protein Structure and Sequence Similarity on the Accuracy of Machine-Learning Scoring Functions for Binding Affinity Prediction.

PubMed

Li, Hongjian; Peng, Jiangjun; Leung, Yee; Leung, Kwong-Sak; Wong, Man-Hon; Lu, Gang; Ballester, Pedro J

2018-03-14

It has recently been claimed that the outstanding performance of machine-learning scoring functions (SFs) is exclusively due to the presence of training complexes with highly similar proteins to those in the test set. Here, we revisit this question using 24 similarity-based training sets, a widely used test set, and four SFs. Three of these SFs employ machine learning instead of the classical linear regression approach of the fourth SF (X-Score which has the best test set performance out of 16 classical SFs). We have found that random forest (RF)-based RF-Score-v3 outperforms X-Score even when 68% of the most similar proteins are removed from the training set. In addition, unlike X-Score, RF-Score-v3 is able to keep learning with an increasing training set size, becoming substantially more predictive than X-Score when the full 1105 complexes are used for training. These results show that machine-learning SFs owe a substantial part of their performance to training on complexes with dissimilar proteins to those in the test set, against what has been previously concluded using the same data. Given that a growing amount of structural and interaction data will be available from academic and industrial sources, this performance gap between machine-learning SFs and classical SFs is expected to enlarge in the future.
Odorant-binding proteins from a primitive termite.

PubMed

Ishida, Yuko; Chiang, Vicky P; Haverty, Michael I; Leal, Walter S

2002-09-01

Hitherto, odorant-binding proteins (OBPs) have been identified from insects belonging to more highly evolved insect orders (Lepidoptera, Coleoptera, Diptera, Hymenoptera, and Hemiptera), whereas only chemosensory proteins have been identified from more primitive species, such as orthopteran and phasmid species. Here, we report for the first time the isolation and cloning of odorant-binding proteins from a primitive termite species, the dampwood termite. Zootermopsis nevadensis nevadensis (Isoptera: Termopsidae). A major antennae-specific protein was detected by native PAGE along with four other minor proteins, which were also absent in the extract from control tissues (hindlegs). Multiple cDNA cloning led to the full characterization of the major antennae-specific protein (ZnevOBP1) and to the identification of two other antennae-specific cDNAs, encoding putative odorant-binding proteins (ZnevOBP2 and ZnevOBP3). N-terminal amino acid sequencing of the minor antennal bands and cDNA cloning showed that olfaction in Z. n. nevadensis may involve multiple odorant-binding proteins. Database searches suggest that the OBPs from this primitive termite are homologues of the pheromone-binding proteins from scarab beetles and antennal-binding proteins from moths.
Roles of Copper-Binding Proteins in Breast Cancer.

PubMed

Blockhuys, Stéphanie; Wittung-Stafshede, Pernilla

2017-04-20

Copper ions are needed in several steps of cancer progression. However, the underlying mechanisms, and involved copper-binding proteins, are mainly elusive. Since most copper ions in the body (in and outside cells) are protein-bound, it is important to investigate what copper-binding proteins participate and, for these, how they are loaded with copper by copper transport proteins. Mechanistic information for how some copper-binding proteins, such as extracellular lysyl oxidase (LOX), play roles in cancer have been elucidated but there is still much to learn from a biophysical molecular viewpoint. Here we provide a summary of copper-binding proteins and discuss ones reported to have roles in cancer. We specifically focus on how copper-binding proteins such as mediator of cell motility 1 (MEMO1), LOX, LOX-like proteins, and secreted protein acidic and rich in cysteine (SPARC) modulate breast cancer from molecular and clinical aspects. Because of the importance of copper for invasion/migration processes, which are key components of cancer metastasis, further insights into the actions of copper-binding proteins may provide new targets to combat cancer.
SH2 Domains Recognize Contextual Peptide Sequence Information to Determine Selectivity*

PubMed Central

Liu, Bernard A.; Jablonowski, Karl; Shah, Eshana E.; Engelmann, Brett W.; Jones, Richard B.; Nash, Piers D.

2010-01-01

Selective ligand recognition by modular protein interaction domains is a primary determinant of specificity in signaling pathways. Src homology 2 (SH2) domains fulfill this capacity immediately downstream of tyrosine kinases, acting to recruit their host polypeptides to ligand proteins harboring phosphorylated tyrosine residues. The degree to which SH2 domains are selective and the mechanisms underlying selectivity are fundamental to understanding phosphotyrosine signaling networks. An examination of interactions between 50 SH2 domains and a set of 192 phosphotyrosine peptides corresponding to physiological motifs within FGF, insulin, and IGF-1 receptor pathways indicates that individual SH2 domains have distinct recognition properties and exhibit a remarkable degree of selectivity beyond that predicted by previously described binding motifs. The underlying basis for such selectivity is the ability of SH2 domains to recognize both permissive amino acid residues that enhance binding and non-permissive amino acid residues that oppose binding in the vicinity of the essential phosphotyrosine. Neighboring positions affect one another so local sequence context matters to SH2 domains. This complex linguistics allows SH2 domains to distinguish subtle differences in peptide ligands. This newly appreciated contextual dependence substantially increases the accessible information content embedded in the peptide ligands that can be effectively integrated to determine binding. This concept may serve more broadly as a paradigm for subtle recognition of physiological ligands by protein interaction domains. PMID:20627867
Special AT-rich sequence binding protein 1 promotes tumor growth and metastasis of esophageal squamous cell carcinoma.

PubMed

Ma, Jun; Wu, Kaiming; Zhao, Zhenxian; Miao, Rong; Xu, Zhe

2017-03-01

Esophageal squamous cell carcinoma is one of the most aggressive malignancies worldwide. Special AT-rich sequence binding protein 1 is a nuclear matrix attachment region binding protein which participates in higher order chromatin organization and tissue-specific gene expression. However, the role of special AT-rich sequence binding protein 1 in esophageal squamous cell carcinoma remains unknown. In this study, western blot and quantitative real-time polymerase chain reaction analysis were performed to identify differentially expressed special AT-rich sequence binding protein 1 in a series of esophageal squamous cell carcinoma tissue samples. The effects of special AT-rich sequence binding protein 1 silencing by two short-hairpin RNAs on cell proliferation, migration, and invasion were assessed by the CCK-8 assay and transwell assays in esophageal squamous cell carcinoma in vitro. Special AT-rich sequence binding protein 1 was significantly upregulated in esophageal squamous cell carcinoma tissue samples and cell lines. Silencing of special AT-rich sequence binding protein 1 inhibited the proliferation of KYSE450 and EC9706 cells which have a relatively high level of special AT-rich sequence binding protein 1, and the ability of migration and invasion of KYSE450 and EC9706 cells was distinctly suppressed. Special AT-rich sequence binding protein 1 could be a potential target for the treatment of esophageal squamous cell carcinoma and inhibition of special AT-rich sequence binding protein 1 may provide a new strategy for the prevention of esophageal squamous cell carcinoma invasion and metastasis.

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