Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms

PubMed Central

Jian, Jhih-Wei; Elumalai, Pavadai; Pitti, Thejkiran; Wu, Chih Yuan; Tsai, Keng-Chang; Chang, Jeng-Yih; Peng, Hung-Pin; Yang, An-Suei

2016-01-01

Predicting ligand binding sites (LBSs) on protein structures, which are obtained either from experimental or computational methods, is a useful first step in functional annotation or structure-based drug design for the protein structures. In this work, the structure-based machine learning algorithm ISMBLab-LIG was developed to predict LBSs on protein surfaces with input attributes derived from the three-dimensional probability density maps of interacting atoms, which were reconstructed on the query protein surfaces and were relatively insensitive to local conformational variations of the tentative ligand binding sites. The prediction accuracy of the ISMBLab-LIG predictors is comparable to that of the best LBS predictors benchmarked on several well-established testing datasets. More importantly, the ISMBLab-LIG algorithm has substantial tolerance to the prediction uncertainties of computationally derived protein structure models. As such, the method is particularly useful for predicting LBSs not only on experimental protein structures without known LBS templates in the database but also on computationally predicted model protein structures with structural uncertainties in the tentative ligand binding sites. PMID:27513851

Kinetics of heavy metal adsorption and desorption in soil: Developing a unified model based on chemical speciation

NASA Astrophysics Data System (ADS)

Peng, Lanfang; Liu, Paiyu; Feng, Xionghan; Wang, Zimeng; Cheng, Tao; Liang, Yuzhen; Lin, Zhang; Shi, Zhenqing

2018-03-01

Predicting the kinetics of heavy metal adsorption and desorption in soil requires consideration of multiple heterogeneous soil binding sites and variations of reaction chemistry conditions. Although chemical speciation models have been developed for predicting the equilibrium of metal adsorption on soil organic matter (SOM) and important mineral phases (e.g. Fe and Al (hydr)oxides), there is still a lack of modeling tools for predicting the kinetics of metal adsorption and desorption reactions in soil. In this study, we developed a unified model for the kinetics of heavy metal adsorption and desorption in soil based on the equilibrium models WHAM 7 and CD-MUSIC, which specifically consider metal kinetic reactions with multiple binding sites of SOM and soil minerals simultaneously. For each specific binding site, metal adsorption and desorption rate coefficients were constrained by the local equilibrium partition coefficients predicted by WHAM 7 or CD-MUSIC, and, for each metal, the desorption rate coefficients of various binding sites were constrained by their metal binding constants with those sites. The model had only one fitting parameter for each soil binding phase, and all other parameters were derived from WHAM 7 and CD-MUSIC. A stirred-flow method was used to study the kinetics of Cd, Cu, Ni, Pb, and Zn adsorption and desorption in multiple soils under various pH and metal concentrations, and the model successfully reproduced most of the kinetic data. We quantitatively elucidated the significance of different soil components and important soil binding sites during the adsorption and desorption kinetic processes. Our model has provided a theoretical framework to predict metal adsorption and desorption kinetics, which can be further used to predict the dynamic behavior of heavy metals in soil under various natural conditions by coupling other important soil processes.

Predicting protein-binding RNA nucleotides with consideration of binding partners.

PubMed

Tuvshinjargal, Narankhuu; Lee, Wook; Park, Byungkyu; Han, Kyungsook

2015-06-01

In recent years several computational methods have been developed to predict RNA-binding sites in protein. Most of these methods do not consider interacting partners of a protein, so they predict the same RNA-binding sites for a given protein sequence even if the protein binds to different RNAs. Unlike the problem of predicting RNA-binding sites in protein, the problem of predicting protein-binding sites in RNA has received little attention mainly because it is much more difficult and shows a lower accuracy on average. In our previous study, we developed a method that predicts protein-binding nucleotides from an RNA sequence. In an effort to improve the prediction accuracy and usefulness of the previous method, we developed a new method that uses both RNA and protein sequence data. In this study, we identified effective features of RNA and protein molecules and developed a new support vector machine (SVM) model to predict protein-binding nucleotides from RNA and protein sequence data. The new model that used both protein and RNA sequence data achieved a sensitivity of 86.5%, a specificity of 86.2%, a positive predictive value (PPV) of 72.6%, a negative predictive value (NPV) of 93.8% and Matthews correlation coefficient (MCC) of 0.69 in a 10-fold cross validation; it achieved a sensitivity of 58.8%, a specificity of 87.4%, a PPV of 65.1%, a NPV of 84.2% and MCC of 0.48 in independent testing. For comparative purpose, we built another prediction model that used RNA sequence data alone and ran it on the same dataset. In a 10 fold-cross validation it achieved a sensitivity of 85.7%, a specificity of 80.5%, a PPV of 67.7%, a NPV of 92.2% and MCC of 0.63; in independent testing it achieved a sensitivity of 67.7%, a specificity of 78.8%, a PPV of 57.6%, a NPV of 85.2% and MCC of 0.45. In both cross-validations and independent testing, the new model that used both RNA and protein sequences showed a better performance than the model that used RNA sequence data alone in most performance measures. To the best of our knowledge, this is the first sequence-based prediction of protein-binding nucleotides in RNA which considers the binding partner of RNA. The new model will provide valuable information for designing biochemical experiments to find putative protein-binding sites in RNA with unknown structure. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Analysis of Factors Influencing Hydration Site Prediction Based on Molecular Dynamics Simulations

PubMed Central

2015-01-01

Water contributes significantly to the binding of small molecules to proteins in biochemical systems. Molecular dynamics (MD) simulation based programs such as WaterMap and WATsite have been used to probe the locations and thermodynamic properties of hydration sites at the surface or in the binding site of proteins generating important information for structure-based drug design. However, questions associated with the influence of the simulation protocol on hydration site analysis remain. In this study, we use WATsite to investigate the influence of factors such as simulation length and variations in initial protein conformations on hydration site prediction. We find that 4 ns MD simulation is appropriate to obtain a reliable prediction of the locations and thermodynamic properties of hydration sites. In addition, hydration site prediction can be largely affected by the initial protein conformations used for MD simulations. Here, we provide a first quantification of this effect and further indicate that similar conformations of binding site residues (RMSD < 0.5 Å) are required to obtain consistent hydration site predictions. PMID:25252619

Prediction of the binding sites of huperzine A in acetylcholinesterase by docking studies

NASA Astrophysics Data System (ADS)

Pang, Yuan-Ping; Kozikowski, Alan P.

1994-12-01

We have performed docking studies with the SYSDOC program on acetylcholinesterase (AChE) to predict the binding sites in AChE of huperzine A (HA), which is a potent and selective, reversible inhibitor of AChE. The unique aspects of our docking studies include the following: (i) Molecular flexibility of the guest and the host is taken into account, which permits both to change their conformations upon binding. (ii) The binding energy is evaluated by a sum of energies of steric, electrostatic and hydrogen bonding interactions. In the energy calculation no grid approximation is used, and all hydrogen atoms of the system are treated explicitly. (iii) The energy of cation-π interactions between the guest and the host, which is important in the binding of AChE, is included in the calculated binding energy. (iv) Docking is performed in all regions of the host's binding cavity. Based on our docking studies and the pharmacological results reported for HA and its analogs, we predict that HA binds to the bottom of the binding cavity of AChE (the gorge) with its ammonium group interacting with Trp84, Phe330, Glu199 and Asp72 (catalytic site). At the the opening of the gorge with its ammonium group partially interacting with Trp279 (peripheral site). At the catalytic site, three partially overlapping subsites of HA were identified which might provide a dynamic view of binding of HA to the catalytic site.

Binding Leverage as a Molecular Basis for Allosteric Regulation

PubMed Central

Mitternacht, Simon; Berezovsky, Igor N.

2011-01-01

Allosteric regulation involves conformational transitions or fluctuations between a few closely related states, caused by the binding of effector molecules. We introduce a quantity called binding leverage that measures the ability of a binding site to couple to the intrinsic motions of a protein. We use Monte Carlo simulations to generate potential binding sites and either normal modes or pairs of crystal structures to describe relevant motions. We analyze single catalytic domains and multimeric allosteric enzymes with complex regulation. For the majority of the analyzed proteins, we find that both catalytic and allosteric sites have high binding leverage. Furthermore, our analysis of the catabolite activator protein, which is allosteric without conformational change, shows that its regulation involves other types of motion than those modulated at sites with high binding leverage. Our results point to the importance of incorporating dynamic information when predicting functional sites. Because it is possible to calculate binding leverage from a single crystal structure it can be used for characterizing proteins of unknown function and predicting latent allosteric sites in any protein, with implications for drug design. PMID:21935347

PRISM offers a comprehensive genomic approach to transcription factor function prediction

PubMed Central

Wenger, Aaron M.; Clarke, Shoa L.; Guturu, Harendra; Chen, Jenny; Schaar, Bruce T.; McLean, Cory Y.; Bejerano, Gill

2013-01-01

The human genome encodes 1500–2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells. PMID:23382538

Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods.

PubMed

Roche, Daniel Barry; Brackenridge, Danielle Allison; McGuffin, Liam James

2015-12-15

Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein-ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein-ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein-ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

Analysis of functional importance of binding sites in the Drosophila gap gene network model.

PubMed

Kozlov, Konstantin; Gursky, Vitaly V; Kulakovskiy, Ivan V; Dymova, Arina; Samsonova, Maria

2015-01-01

The statistical thermodynamics based approach provides a promising framework for construction of the genotype-phenotype map in many biological systems. Among important aspects of a good model connecting the DNA sequence information with that of a molecular phenotype (gene expression) is the selection of regulatory interactions and relevant transcription factor bindings sites. As the model may predict different levels of the functional importance of specific binding sites in different genomic and regulatory contexts, it is essential to formulate and study such models under different modeling assumptions. We elaborate a two-layer model for the Drosophila gap gene network and include in the model a combined set of transcription factor binding sites and concentration dependent regulatory interaction between gap genes hunchback and Kruppel. We show that the new variants of the model are more consistent in terms of gene expression predictions for various genetic constructs in comparison to previous work. We quantify the functional importance of binding sites by calculating their impact on gene expression in the model and calculate how these impacts correlate across all sites under different modeling assumptions. The assumption about the dual interaction between hb and Kr leads to the most consistent modeling results, but, on the other hand, may obscure existence of indirect interactions between binding sites in regulatory regions of distinct genes. The analysis confirms the previously formulated regulation concept of many weak binding sites working in concert. The model predicts a more or less uniform distribution of functionally important binding sites over the sets of experimentally characterized regulatory modules and other open chromatin domains.

A Large-Scale Assessment of Nucleic Acids Binding Site Prediction Programs

PubMed Central

Miao, Zhichao; Westhof, Eric

2015-01-01

Computational prediction of nucleic acid binding sites in proteins are necessary to disentangle functional mechanisms in most biological processes and to explore the binding mechanisms. Several strategies have been proposed, but the state-of-the-art approaches display a great diversity in i) the definition of nucleic acid binding sites; ii) the training and test datasets; iii) the algorithmic methods for the prediction strategies; iv) the performance measures and v) the distribution and availability of the prediction programs. Here we report a large-scale assessment of 19 web servers and 3 stand-alone programs on 41 datasets including more than 5000 proteins derived from 3D structures of protein-nucleic acid complexes. Well-defined binary assessment criteria (specificity, sensitivity, precision, accuracy…) are applied. We found that i) the tools have been greatly improved over the years; ii) some of the approaches suffer from theoretical defects and there is still room for sorting out the essential mechanisms of binding; iii) RNA binding and DNA binding appear to follow similar driving forces and iv) dataset bias may exist in some methods. PMID:26681179

Computational identification of developmental enhancers:conservation and function of transcription factor binding-site clustersin drosophila melanogaster and drosophila psedoobscura

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

Berman, Benjamin P.; Pfeiffer, Barret D.; Laverty, Todd R.

2004-08-06

The identification of sequences that control transcription in metazoans is a major goal of genome analysis. In a previous study, we demonstrated that searching for clusters of predicted transcription factor binding sites could discover active regulatory sequences, and identified 37 regions of the Drosophila melanogaster genome with high densities of predicted binding sites for five transcription factors involved in anterior-posterior embryonic patterning. Nine of these clusters overlapped known enhancers. Here, we report the results of in vivo functional analysis of 27 remaining clusters. We generated transgenic flies carrying each cluster attached to a basal promoter and reporter gene, and assayedmore » embryos for reporter gene expression. Six clusters are enhancers of adjacent genes: giant, fushi tarazu, odd-skipped, nubbin, squeeze and pdm2; three drive expression in patterns unrelated to those of neighboring genes; the remaining 18 do not appear to have enhancer activity. We used the Drosophila pseudoobscura genome to compare patterns of evolution in and around the 15 positive and 18 false-positive predictions. Although conservation of primary sequence cannot distinguish true from false positives, conservation of binding-site clustering accurately discriminates functional binding-site clusters from those with no function. We incorporated conservation of binding-site clustering into a new genome-wide enhancer screen, and predict several hundred new regulatory sequences, including 85 adjacent to genes with embryonic patterns. Measuring conservation of sequence features closely linked to function--such as binding-site clustering--makes better use of comparative sequence data than commonly used methods that examine only sequence identity.« less

Discovery and validation of information theory-based transcription factor and cofactor binding site motifs.

PubMed

Lu, Ruipeng; Mucaki, Eliseos J; Rogan, Peter K

2017-03-17

Data from ChIP-seq experiments can derive the genome-wide binding specificities of transcription factors (TFs) and other regulatory proteins. We analyzed 765 ENCODE ChIP-seq peak datasets of 207 human TFs with a novel motif discovery pipeline based on recursive, thresholded entropy minimization. This approach, while obviating the need to compensate for skewed nucleotide composition, distinguishes true binding motifs from noise, quantifies the strengths of individual binding sites based on computed affinity and detects adjacent cofactor binding sites that coordinate with the targets of primary, immunoprecipitated TFs. We obtained contiguous and bipartite information theory-based position weight matrices (iPWMs) for 93 sequence-specific TFs, discovered 23 cofactor motifs for 127 TFs and revealed six high-confidence novel motifs. The reliability and accuracy of these iPWMs were determined via four independent validation methods, including the detection of experimentally proven binding sites, explanation of effects of characterized SNPs, comparison with previously published motifs and statistical analyses. We also predict previously unreported TF coregulatory interactions (e.g. TF complexes). These iPWMs constitute a powerful tool for predicting the effects of sequence variants in known binding sites, performing mutation analysis on regulatory SNPs and predicting previously unrecognized binding sites and target genes. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Biological and functional relevance of CASP predictions.

PubMed

Liu, Tianyun; Ish-Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D; Altman, Russ B

2018-03-01

Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo-sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo-sites), and Ten sites containing important motifs, loops, or key residues with important disease-associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best-ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand-binding sites, most prediction methods have higher performance on apo-sites than holo-sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein-protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein-protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. © 2017 The Authors Proteins: Structure, Function and Bioinformatics Published by Wiley Periodicals, Inc.

Combining solvent thermodynamic profiles with functionality maps of the Hsp90 binding site to predict the displacement of water molecules.

PubMed

Haider, Kamran; Huggins, David J

2013-10-28

Intermolecular interactions in the aqueous phase must compete with the interactions between the two binding partners and their solvating water molecules. In biological systems, water molecules in protein binding sites cluster at well-defined hydration sites and can form strong hydrogen-bonding interactions with backbone and side-chain atoms. Displacement of such water molecules is only favorable when the ligand can form strong compensating hydrogen bonds. Conversely, water molecules in hydrophobic regions of protein binding sites make only weak interactions, and the requirements for favorable displacement are less stringent. The propensity of water molecules for displacement can be identified using inhomogeneous fluid solvation theory (IFST), a statistical mechanical method that decomposes the solvation free energy of a solute into the contributions from different spatial regions and identifies potential binding hotspots. In this study, we employed IFST to study the displacement of water molecules from the ATP binding site of Hsp90, using a test set of 103 ligands. The predicted contribution of a hydration site to the hydration free energy was found to correlate well with the observed displacement. Additionally, we investigated if this correlation could be improved by using the energetic scores of favorable probe groups binding at the location of hydration sites, derived from a multiple copy simultaneous search (MCSS) method. The probe binding scores were not highly predictive of the observed displacement and did not improve the predictivity when used in combination with IFST-based hydration free energies. The results show that IFST alone can be used to reliably predict the observed displacement of water molecules in Hsp90. However, MCSS can augment IFST calculations by suggesting which functional groups should be used to replace highly displaceable water molecules. Such an approach could be very useful in improving the hit-to-lead process for new drug targets.

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.

OnTheFly: a database of Drosophila melanogaster transcription factors and their binding sites.

PubMed

Shazman, Shula; Lee, Hunjoong; Socol, Yakov; Mann, Richard S; Honig, Barry

2014-01-01

We present OnTheFly (http://bhapp.c2b2.columbia.edu/OnTheFly/index.php), a database comprising a systematic collection of transcription factors (TFs) of Drosophila melanogaster and their DNA-binding sites. TFs predicted in the Drosophila melanogaster genome are annotated and classified and their structures, obtained via experiment or homology models, are provided. All known preferred TF DNA-binding sites obtained from the B1H, DNase I and SELEX methodologies are presented. DNA shape parameters predicted for these sites are obtained from a high throughput server or from crystal structures of protein-DNA complexes where available. An important feature of the database is that all DNA-binding domains and their binding sites are fully annotated in a eukaryote using structural criteria and evolutionary homology. OnTheFly thus provides a comprehensive view of TFs and their binding sites that will be a valuable resource for deciphering non-coding regulatory DNA.

Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes

PubMed Central

Kuang, Zheng; Ji, Zhicheng

2018-01-01

Abstract Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes. PMID:29325176

Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction

PubMed Central

Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K.; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G.; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H.

2017-01-01

The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. PMID:27899623

Identification of Candidate Transcription Factor Binding Sites in the Cattle Genome

PubMed Central

Bickhart, Derek M.; Liu, George E.

2013-01-01

A resource that provides candidate transcription factor binding sites (TFBSs) does not currently exist for cattle. Such data is necessary, as predicted sites may serve as excellent starting locations for future omics studies to develop transcriptional regulation hypotheses. In order to generate this resource, we employed a phylogenetic footprinting approach—using sequence conservation across cattle, human and dog—and position-specific scoring matrices to identify 379,333 putative TFBSs upstream of nearly 8000 Mammalian Gene Collection (MGC) annotated genes within the cattle genome. Comparisons of our predictions to known binding site loci within the PCK1, ACTA1 and G6PC promoter regions revealed 75% sensitivity for our method of discovery. Additionally, we intersected our predictions with known cattle SNP variants in dbSNP and on the Illumina BovineHD 770k and Bos 1 SNP chips, finding 7534, 444 and 346 overlaps, respectively. Due to our stringent filtering criteria, these results represent high quality predictions of putative TFBSs within the cattle genome. All binding site predictions are freely available at http://bfgl.anri.barc.usda.gov/BovineTFBS/ or http://199.133.54.77/BovineTFBS. PMID:23433959

Computational identification of developmental enhancers:conservation and function of transcription factor binding-site clustersin drosophila melanogaster and drosophila psedoobscura

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

Berman, Benjamin P.; Pfeiffer, Barret D.; Laverty, Todd R.

2004-08-06

Background The identification of sequences that control transcription in metazoans is a major goal of genome analysis. In a previous study, we demonstrated that searching for clusters of predicted transcription factor binding sites could discover active regulatory sequences, and identified 37 regions of the Drosophila melanogaster genome with high densities of predicted binding sites for five transcription factors involved in anterior-posterior embryonic patterning. Nine of these clusters overlapped known enhancers. Here, we report the results of in vivo functional analysis of 27 remaining clusters. Results We generated transgenic flies carrying each cluster attached to a basal promoter and reporter gene,more » and assayed embryos for reporter gene expression. Six clusters are enhancers of adjacent genes: giant, fushi tarazu, odd-skipped, nubbin, squeeze and pdm2; three drive expression in patterns unrelated to those of neighboring genes; the remaining 18 do not appear to have enhancer activity. We used the Drosophila pseudoobscura genome to compare patterns of evolution in and around the 15 positive and 18 false-positive predictions. Although conservation of primary sequence cannot distinguish true from false positives, conservation of binding-site clustering accurately discriminates functional binding-site clusters from those with no function. We incorporated conservation of binding-site clustering into a new genome-wide enhancer screen, and predict several hundred new regulatory sequences, including 85 adjacent to genes with embryonic patterns. Conclusions Measuring conservation of sequence features closely linked to function - such as binding-site clustering - makes better use of comparative sequence data than commonly used methods that examine only sequence identity.« less

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

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.

Understanding Transcription Factor Regulation by Integrating Gene Expression and DNase I Hypersensitive Sites.

PubMed

Wang, Guohua; Wang, Fang; Huang, Qian; Li, Yu; Liu, Yunlong; Wang, Yadong

2015-01-01

Transcription factors are proteins that bind to DNA sequences to regulate gene transcription. The transcription factor binding sites are short DNA sequences (5-20 bp long) specifically bound by one or more transcription factors. The identification of transcription factor binding sites and prediction of their function continue to be challenging problems in computational biology. In this study, by integrating the DNase I hypersensitive sites with known position weight matrices in the TRANSFAC database, the transcription factor binding sites in gene regulatory region are identified. Based on the global gene expression patterns in cervical cancer HeLaS3 cell and HelaS3-ifnα4h cell (interferon treatment on HeLaS3 cell for 4 hours), we present a model-based computational approach to predict a set of transcription factors that potentially cause such differential gene expression. Significantly, 6 out 10 predicted functional factors, including IRF, IRF-2, IRF-9, IRF-1 and IRF-3, ICSBP, belong to interferon regulatory factor family and upregulate the gene expression levels responding to the interferon treatment. Another factor, ISGF-3, is also a transcriptional activator induced by interferon alpha. Using the different transcription factor binding sites selected criteria, the prediction result of our model is consistent. Our model demonstrated the potential to computationally identify the functional transcription factors in gene regulation.

aPPRove: An HMM-Based Method for Accurate Prediction of RNA-Pentatricopeptide Repeat Protein Binding Events

PubMed Central

Harrison, Thomas; Ruiz, Jaime; Sloan, Daniel B.; Ben-Hur, Asa; Boucher, Christina

2016-01-01

Pentatricopeptide repeat containing proteins (PPRs) bind to RNA transcripts originating from mitochondria and plastids. There are two classes of PPR proteins. The P class contains tandem P-type motif sequences, and the PLS class contains alternating P, L and S type sequences. In this paper, we describe a novel tool that predicts PPR-RNA interaction; specifically, our method, which we call aPPRove, determines where and how a PLS-class PPR protein will bind to RNA when given a PPR and one or more RNA transcripts by using a combinatorial binding code for site specificity proposed by Barkan et al. Our results demonstrate that aPPRove successfully locates how and where a PPR protein belonging to the PLS class can bind to RNA. For each binding event it outputs the binding site, the amino-acid-nucleotide interaction, and its statistical significance. Furthermore, we show that our method can be used to predict binding events for PLS-class proteins using a known edit site and the statistical significance of aligning the PPR protein to that site. In particular, we use our method to make a conjecture regarding an interaction between CLB19 and the second intronic region of ycf3. The aPPRove web server can be found at www.cs.colostate.edu/~approve. PMID:27560805

Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes.

PubMed

Kuang, Zheng; Ji, Zhicheng; Boeke, Jef D; Ji, Hongkai

2018-01-09

Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Predicting conformational ensembles and genome-wide transcription factor binding sites from DNA sequences.

PubMed

Andrabi, Munazah; Hutchins, Andrew Paul; Miranda-Saavedra, Diego; Kono, Hidetoshi; Nussinov, Ruth; Mizuguchi, Kenji; Ahmad, Shandar

2017-06-22

DNA shape is emerging as an important determinant of transcription factor binding beyond just the DNA sequence. The only tool for large scale DNA shape estimates, DNAshape was derived from Monte-Carlo simulations and predicts four broad and static DNA shape features, Propeller twist, Helical twist, Minor groove width and Roll. The contributions of other shape features e.g. Shift, Slide and Opening cannot be evaluated using DNAshape. Here, we report a novel method DynaSeq, which predicts molecular dynamics-derived ensembles of a more exhaustive set of DNA shape features. We compared the DNAshape and DynaSeq predictions for the common features and applied both to predict the genome-wide binding sites of 1312 TFs available from protein interaction quantification (PIQ) data. The results indicate a good agreement between the two methods for the common shape features and point to advantages in using DynaSeq. Predictive models employing ensembles from individual conformational parameters revealed that base-pair opening - known to be important in strand separation - was the best predictor of transcription factor-binding sites (TFBS) followed by features employed by DNAshape. Of note, TFBS could be predicted not only from the features at the target motif sites, but also from those as far as 200 nucleotides away from the motif.

Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction.

PubMed

Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H

2017-01-09

The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Role of Electrostatics in Protein-RNA Binding: The Global vs the Local Energy Landscape.

PubMed

Ghaemi, Zhaleh; Guzman, Irisbel; Gnutt, David; Luthey-Schulten, Zaida; Gruebele, Martin

2017-09-14

U1A protein-stem loop 2 RNA association is a basic step in the assembly of the spliceosomal U1 small nuclear ribonucleoprotein. Long-range electrostatic interactions due to the positive charge of U1A are thought to provide high binding affinity for the negatively charged RNA. Short range interactions, such as hydrogen bonds and contacts between RNA bases and protein side chains, favor a specific binding site. Here, we propose that electrostatic interactions are as important as local contacts in biasing the protein-RNA energy landscape toward a specific binding site. We show by using molecular dynamics simulations that deletion of two long-range electrostatic interactions (K22Q and K50Q) leads to mutant-specific alternative RNA bound states. One of these states preserves short-range interactions with aromatic residues in the original binding site, while the other one does not. We test the computational prediction with experimental temperature-jump kinetics using a tryptophan probe in the U1A-RNA binding site. The two mutants show the distinct predicted kinetic behaviors. Thus, the stem loop 2 RNA has multiple binding sites on a rough RNA-protein binding landscape. We speculate that the rough protein-RNA binding landscape, when biased to different local minima by electrostatics, could be one way that protein-RNA interactions evolve toward new binding sites and novel function.

Active sites prediction and binding analysis E1-E2 protein human papillomavirus with biphenylsulfonacetic acid

NASA Astrophysics Data System (ADS)

Iryani, I.; Amelia, F.; Iswendi, I.

2018-04-01

Cervix cancer triggered by Human papillomavirus infection is the second cause to woman death in worldwide. The binding site of E1-E2 protein of HPV 16 is not known from a 3-D structure yet, so in this study we address this issue to study the structure of E1-E2 protein from Human papillomavirus type 16 and to find its potential binding sites using biphenylsulfonacetic acid as inhibitor. Swiss model was used for 3D structure prediction and PDB: 2V9P (E1 protein) and 2NNU (E2 protein) having 52.32% and 100% identity respectively was selected as a template. The 3D model structure developed of E1 and E2 in the core and allowed regions were 99.2% and 99.5%. The ligand binding sites were predicted using online server meta pocket 2.0 and MOE 2009.10 was used for docking. E1-and E2 protein of HPV-16 has three potential binding site that can interact with the inhibitors. The Docking biphenylsulfonacetic acid using these binding sites shows that ligand interact with the protein through hydrogen bonds on Lys 403, Arg 410, His 551 in the first pocket, on Tyr 32, Leu 99 in the second pocket, and Lys 558m Lys 517 in the third pocket.

Real-Time Ligand Binding Pocket Database Search Using Local Surface Descriptors

PubMed Central

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-01-01

Due to the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of a particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two dimensional pseudo-Zernike moments or the 3D Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark study employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed. PMID:20455259

Real-time ligand binding pocket database search using local surface descriptors.

PubMed

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-07-01

Because of the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two-dimensional pseudo-Zernike moments or the three-dimensional Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark studies employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed.

iCLIP Predicts the Dual Splicing Effects of TIA-RNA Interactions

PubMed Central

Briese, Michael; Zarnack, Kathi; Luscombe, Nicholas M.; Rot, Gregor; Zupan, Blaž; Curk, Tomaž; Ule, Jernej

2010-01-01

The regulation of alternative splicing involves interactions between RNA-binding proteins and pre-mRNA positions close to the splice sites. T-cell intracellular antigen 1 (TIA1) and TIA1-like 1 (TIAL1) locally enhance exon inclusion by recruiting U1 snRNP to 5′ splice sites. However, effects of TIA proteins on splicing of distal exons have not yet been explored. We used UV-crosslinking and immunoprecipitation (iCLIP) to find that TIA1 and TIAL1 bind at the same positions on human RNAs. Binding downstream of 5′ splice sites was used to predict the effects of TIA proteins in enhancing inclusion of proximal exons and silencing inclusion of distal exons. The predictions were validated in an unbiased manner using splice-junction microarrays, RT-PCR, and minigene constructs, which showed that TIA proteins maintain splicing fidelity and regulate alternative splicing by binding exclusively downstream of 5′ splice sites. Surprisingly, TIA binding at 5′ splice sites silenced distal cassette and variable-length exons without binding in proximity to the regulated alternative 3′ splice sites. Using transcriptome-wide high-resolution mapping of TIA-RNA interactions we evaluated the distal splicing effects of TIA proteins. These data are consistent with a model where TIA proteins shorten the time available for definition of an alternative exon by enhancing recognition of the preceding 5′ splice site. Thus, our findings indicate that changes in splicing kinetics could mediate the distal regulation of alternative splicing. PMID:21048981

Characterization of Conserved Tandem Donor Sites and Intronic Motifs Required for Alternative Splicing in Corticosteroid Receptor Genes

PubMed Central

Qian, Xiaoxiao; Matthews, Laura; Lightman, Stafford; Ray, David; Norman, Michael

2015-01-01

Alternative splicing events from tandem donor sites result in mRNA variants coding for additional amino acids in the DNA binding domain of both the glucocorticoid (GR) and mineralocorticoid (MR) receptors. We now show that expression of both splice variants is extensively conserved in mammalian species, providing strong evidence for their functional significance. An exception to the conservation of the MR tandem splice site (an A at position +5 of the MR+12 donor site in the mouse) was predicted to decrease U1 small nuclear RNA binding. In accord with this prediction, we were unable to detect the MR+12 variant in this species. The one exception to the conservation of the GR tandem splice site, an A at position +3 of the platypus GRγ donor site that was predicted to enhance binding of U1 snRNA, was unexpectedly associated with decreased expression of the variant from the endogenous gene as well as a minigene. An intronic pyrimidine motif present in both GR and MR genes was found to be critical for usage of the downstream donor site, and overexpression of TIA1/TIAL1 RNA binding proteins, which are known to bind such motifs, led to a marked increase in the proportion of GRγ and MR+12. These results provide striking evidence for conservation of a complex splicing mechanism that involves processes other than stochastic spliceosome binding and identify a mechanism that would allow regulation of variant expression. PMID:19819975

GenProBiS: web server for mapping of sequence variants to protein binding sites.

PubMed

Konc, Janez; Skrlj, Blaz; Erzen, Nika; Kunej, Tanja; Janezic, Dusanka

2017-07-03

Discovery of potentially deleterious sequence variants is important and has wide implications for research and generation of new hypotheses in human and veterinary medicine, and drug discovery. The GenProBiS web server maps sequence variants to protein structures from the Protein Data Bank (PDB), and further to protein-protein, protein-nucleic acid, protein-compound, and protein-metal ion binding sites. The concept of a protein-compound binding site is understood in the broadest sense, which includes glycosylation and other post-translational modification sites. Binding sites were defined by local structural comparisons of whole protein structures using the Protein Binding Sites (ProBiS) algorithm and transposition of ligands from the similar binding sites found to the query protein using the ProBiS-ligands approach with new improvements introduced in GenProBiS. Binding site surfaces were generated as three-dimensional grids encompassing the space occupied by predicted ligands. The server allows intuitive visual exploration of comprehensively mapped variants, such as human somatic mis-sense mutations related to cancer and non-synonymous single nucleotide polymorphisms from 21 species, within the predicted binding sites regions for about 80 000 PDB protein structures using fast WebGL graphics. The GenProBiS web server is open and free to all users at http://genprobis.insilab.org. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

ProBiS-CHARMMing: Web Interface for Prediction and Optimization of Ligands in Protein Binding Sites.

PubMed

Konc, Janez; Miller, Benjamin T; Štular, Tanja; Lešnik, Samo; Woodcock, H Lee; Brooks, Bernard R; Janežič, Dušanka

2015-11-23

Proteins often exist only as apo structures (unligated) in the Protein Data Bank, with their corresponding holo structures (with ligands) unavailable. However, apoproteins may not represent the amino-acid residue arrangement upon ligand binding well, which is especially problematic for molecular docking. We developed the ProBiS-CHARMMing web interface by connecting the ProBiS ( http://probis.cmm.ki.si ) and CHARMMing ( http://www.charmming.org ) web servers into one functional unit that enables prediction of protein-ligand complexes and allows for their geometry optimization and interaction energy calculation. The ProBiS web server predicts ligands (small compounds, proteins, nucleic acids, and single-atom ligands) that may bind to a query protein. This is achieved by comparing its surface structure against a nonredundant database of protein structures and finding those that have binding sites similar to that of the query protein. Existing ligands found in the similar binding sites are then transposed to the query according to predictions from ProBiS. The CHARMMing web server enables, among other things, minimization and potential energy calculation for a wide variety of biomolecular systems, and it is used here to optimize the geometry of the predicted protein-ligand complex structures using the CHARMM force field and to calculate their interaction energies with the corresponding query proteins. We show how ProBiS-CHARMMing can be used to predict ligands and their poses for a particular binding site, and minimize the predicted protein-ligand complexes to obtain representations of holoproteins. The ProBiS-CHARMMing web interface is freely available for academic users at http://probis.nih.gov.

Text Mining Improves Prediction of Protein Functional Sites

PubMed Central

Cohn, Judith D.; Ravikumar, Komandur E.

2012-01-01

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

Protein-protein docking with binding site patch prediction and network-based terms enhanced combinatorial scoring.

PubMed

Gong, Xinqi; Wang, Panwen; Yang, Feng; Chang, Shan; Liu, Bin; He, Hongqiu; Cao, Libin; Xu, Xianjin; Li, Chunhua; Chen, Weizu; Wang, Cunxin

2010-11-15

Protein-protein docking has made much progress in recent years, but challenges still exist. Here we present the application of our docking approach HoDock in CAPRI. In this approach, a binding site prediction is implemented to reduce docking sampling space and filter out unreasonable docked structures, and a network-based enhanced combinatorial scoring function HPNCscore is used to evaluate the decoys. The experimental information was combined with the predicted binding site to pick out the most likely key binding site residues. We applied the HoDock method in the recent rounds of the CAPRI experiments, and got good results as predictors on targets 39, 40, and 41. We also got good results as scorers on targets 35, 37, 40, and 41. This indicates that our docking approach can contribute to the progress of protein-protein docking methods and to the understanding of the mechanism of protein-protein interactions. © 2010 Wiley-Liss, Inc.

Characterization of Protein Tyrosine Phosphatase 1B Inhibition by Chlorogenic Acid and Cichoric Acid.

PubMed

Lipchock, James M; Hendrickson, Heidi P; Douglas, Bonnie B; Bird, Kelly E; Ginther, Patrick S; Rivalta, Ivan; Ten, Nicholas S; Batista, Victor S; Loria, J Patrick

2017-01-10

Protein tyrosine phosphatase 1B (PTP1B) is a known regulator of the insulin and leptin signaling pathways and is an active target for the design of inhibitors for the treatment of type II diabetes and obesity. Recently, cichoric acid (CHA) and chlorogenic acid (CGA) were predicted by docking methods to be allosteric inhibitors that bind distal to the active site. However, using a combination of steady-state inhibition kinetics, solution nuclear magnetic resonance experiments, and molecular dynamics simulations, we show that CHA is a competitive inhibitor that binds in the active site of PTP1B. CGA, while a noncompetitive inhibitor, binds in the second aryl phosphate binding site, rather than the predicted benzfuran binding pocket. The molecular dynamics simulations of the apo enzyme and cysteine-phosphoryl intermediate states with and without bound CGA suggest CGA binding inhibits PTP1B by altering hydrogen bonding patterns at the active site. This study provides a mechanistic understanding of the allosteric inhibition of PTP1B.

Prediction of consensus binding mode geometries for related chemical series of positive allosteric modulators of adenosine and muscarinic acetylcholine receptors.

PubMed

Sakkal, Leon A; Rajkowski, Kyle Z; Armen, Roger S

2017-06-05

Following insights from recent crystal structures of the muscarinic acetylcholine receptor, binding modes of Positive Allosteric Modulators (PAMs) were predicted under the assumption that PAMs should bind to the extracellular surface of the active state. A series of well-characterized PAMs for adenosine (A 1 R, A 2A R, A 3 R) and muscarinic acetylcholine (M 1 R, M 5 R) receptors were modeled using both rigid and flexible receptor CHARMM-based molecular docking. Studies of adenosine receptors investigated the molecular basis of the probe-dependence of PAM activity by modeling in complex with specific agonist radioligands. Consensus binding modes map common pharmacophore features of several chemical series to specific binding interactions. These models provide a rationalization of how PAM binding slows agonist radioligand dissociation kinetics. M 1 R PAMs were predicted to bind in the analogous M 2 R PAM LY2119620 binding site. The M 5 R NAM (ML-375) was predicted to bind in the PAM (ML-380) binding site with a unique induced-fit receptor conformation. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

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.

Sequence-Based Prediction of RNA-Binding Residues in Proteins

PubMed Central

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. PMID:27787829

Molecular cloning and analysis of Schizosaccharomyces pombe Reb1p: sequence-specific recognition of two sites in the far upstream rDNA intergenic spacer.

PubMed Central

Zhao, A; Guo, A; Liu, Z; Pape, L

1997-01-01

The coding sequences for a Schizosaccharomyces pombe sequence-specific DNA binding protein, Reb1p, have been cloned. The predicted S. pombe Reb1p is 24-29% identical to mouse TTF-1 (transcription termination factor-1) and Saccharomyces cerevisiae REB1 protein, both of which direct termination of RNA polymerase I catalyzed transcripts. The S.pombe Reb1 cDNA encodes a predicted polypeptide of 504 amino acids with a predicted molecular weight of 58.4 kDa. The S. pombe Reb1p is unusual in that the bipartite DNA binding motif identified originally in S.cerevisiae and Klyveromyces lactis REB1 proteins is uninterrupted and thus S.pombe Reb1p may contain the smallest natural REB1 homologous DNA binding domain. Its genomic coding sequences were shown to be interrupted by two introns. A recombinant histidine-tagged Reb1 protein bearing the rDNA binding domain has two homologous, sequence-specific binding sites in the S. pomber DNA intergenic spacer, located between 289 and 480 nt downstream of the end of the approximately 25S rRNA coding sequences. Each binding site is 13-14 bp downstream of two of the three proposed in vivo termination sites. The core of this 17 bp site, AGGTAAGGGTAATGCAC, is specifically protected by Reb1p in footprinting analysis. PMID:9016645

Core Binding Site of a Thioflavin-T-Derived Imaging Probe on Amyloid β Fibrils Predicted by Computational Methods.

PubMed

Kawai, Ryoko; Araki, Mitsugu; Yoshimura, Masashi; Kamiya, Narutoshi; Ono, Masahiro; Saji, Hideo; Okuno, Yasushi

2018-05-16

Development of new diagnostic imaging probes for Alzheimer's disease, such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) probes, has been strongly desired. In this study, we investigated the most accessible amyloid β (Aβ) binding site of [ 123 I]IMPY, a Thioflavin-T-derived SPECT probe, using experimental and computational methods. First, we performed a competitive inhibition assay with Orange-G, which recognizes the KLVFFA region in Aβ fibrils, suggesting that IMPY and Orange-G bind to different sites in Aβ fibrils. Next, we precisely predicted the IMPY binding site on a multiple-protofilament Aβ fibril model using computational approaches, consisting of molecular dynamics and docking simulations. We generated possible IMPY-binding structures using docking simulations to identify candidates for probe-binding sites. The binding free energy of IMPY with the Aβ fibril was calculated by a free energy simulation method, MP-CAFEE. These computational results suggest that IMPY preferentially binds to an interfacial pocket located between two protofilaments and is stabilized mainly through hydrophobic interactions. Finally, our computational approach was validated by comparing it with the experimental results. The present study demonstrates the possibility of computational approaches to screen new PET/SPECT probes for Aβ imaging.

Evaluation of a novel virtual screening strategy using receptor decoy binding sites.

PubMed

Patel, Hershna; Kukol, Andreas

2016-08-23

Virtual screening is used in biomedical research to predict the binding affinity of a large set of small organic molecules to protein receptor targets. This report shows the development and evaluation of a novel yet straightforward attempt to improve this ranking in receptor-based molecular docking using a receptor-decoy strategy. This strategy includes defining a decoy binding site on the receptor and adjusting the ranking of the true binding-site virtual screen based on the decoy-site screen. The results show that by docking against a receptor-decoy site with Autodock Vina, improved Receiver Operator Characteristic Enrichment (ROCE) was achieved for 5 out of fifteen receptor targets investigated, when up to 15 % of a decoy site rank list was considered. No improved enrichment was seen for 7 targets, while for 3 targets the ROCE was reduced. The extent to which this strategy can effectively improve ligand prediction is dependent on the target receptor investigated.

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

Nucleotide Interdependency in Transcription Factor Binding Sites in the Drosophila Genome.

PubMed

Dresch, Jacqueline M; Zellers, Rowan G; Bork, Daniel K; Drewell, Robert A

2016-01-01

A long-standing objective in modern biology is to characterize the molecular components that drive the development of an organism. At the heart of eukaryotic development lies gene regulation. On the molecular level, much of the research in this field has focused on the binding of transcription factors (TFs) to regulatory regions in the genome known as cis-regulatory modules (CRMs). However, relatively little is known about the sequence-specific binding preferences of many TFs, especially with respect to the possible interdependencies between the nucleotides that make up binding sites. A particular limitation of many existing algorithms that aim to predict binding site sequences is that they do not allow for dependencies between nonadjacent nucleotides. In this study, we use a recently developed computational algorithm, MARZ, to compare binding site sequences using 32 distinct models in a systematic and unbiased approach to explore nucleotide dependencies within binding sites for 15 distinct TFs known to be critical to Drosophila development. Our results indicate that many of these proteins have varying levels of nucleotide interdependencies within their DNA recognition sequences, and that, in some cases, models that account for these dependencies greatly outperform traditional models that are used to predict binding sites. We also directly compare the ability of different models to identify the known KRUPPEL TF binding sites in CRMs and demonstrate that a more complex model that accounts for nucleotide interdependencies performs better when compared with simple models. This ability to identify TFs with critical nucleotide interdependencies in their binding sites will lead to a deeper understanding of how these molecular characteristics contribute to the architecture of CRMs and the precise regulation of transcription during organismal development.

Nucleotide Interdependency in Transcription Factor Binding Sites in the Drosophila Genome

PubMed Central

Dresch, Jacqueline M.; Zellers, Rowan G.; Bork, Daniel K.; Drewell, Robert A.

2016-01-01

A long-standing objective in modern biology is to characterize the molecular components that drive the development of an organism. At the heart of eukaryotic development lies gene regulation. On the molecular level, much of the research in this field has focused on the binding of transcription factors (TFs) to regulatory regions in the genome known as cis-regulatory modules (CRMs). However, relatively little is known about the sequence-specific binding preferences of many TFs, especially with respect to the possible interdependencies between the nucleotides that make up binding sites. A particular limitation of many existing algorithms that aim to predict binding site sequences is that they do not allow for dependencies between nonadjacent nucleotides. In this study, we use a recently developed computational algorithm, MARZ, to compare binding site sequences using 32 distinct models in a systematic and unbiased approach to explore nucleotide dependencies within binding sites for 15 distinct TFs known to be critical to Drosophila development. Our results indicate that many of these proteins have varying levels of nucleotide interdependencies within their DNA recognition sequences, and that, in some cases, models that account for these dependencies greatly outperform traditional models that are used to predict binding sites. We also directly compare the ability of different models to identify the known KRUPPEL TF binding sites in CRMs and demonstrate that a more complex model that accounts for nucleotide interdependencies performs better when compared with simple models. This ability to identify TFs with critical nucleotide interdependencies in their binding sites will lead to a deeper understanding of how these molecular characteristics contribute to the architecture of CRMs and the precise regulation of transcription during organismal development. PMID:27330274

Position specific variation in the rate of evolution in transcription factor binding sites

PubMed Central

Moses, Alan M; Chiang, Derek Y; Kellis, Manolis; Lander, Eric S; Eisen, Michael B

2003-01-01

Background The binding sites of sequence specific transcription factors are an important and relatively well-understood class of functional non-coding DNAs. Although a wide variety of experimental and computational methods have been developed to characterize transcription factor binding sites, they remain difficult to identify. Comparison of non-coding DNA from related species has shown considerable promise in identifying these functional non-coding sequences, even though relatively little is known about their evolution. Results Here we analyse the genome sequences of the budding yeasts Saccharomyces cerevisiae, S. bayanus, S. paradoxus and S. mikatae to study the evolution of transcription factor binding sites. As expected, we find that both experimentally characterized and computationally predicted binding sites evolve slower than surrounding sequence, consistent with the hypothesis that they are under purifying selection. We also observe position-specific variation in the rate of evolution within binding sites. We find that the position-specific rate of evolution is positively correlated with degeneracy among binding sites within S. cerevisiae. We test theoretical predictions for the rate of evolution at positions where the base frequencies deviate from background due to purifying selection and find reasonable agreement with the observed rates of evolution. Finally, we show how the evolutionary characteristics of real binding motifs can be used to distinguish them from artefacts of computational motif finding algorithms. Conclusion As has been observed for protein sequences, the rate of evolution in transcription factor binding sites varies with position, suggesting that some regions are under stronger functional constraint than others. This variation likely reflects the varying importance of different positions in the formation of the protein-DNA complex. The characterization of the pattern of evolution in known binding sites will likely contribute to the effective use of comparative sequence data in the identification of transcription factor binding sites and is an important step toward understanding the evolution of functional non-coding DNA. PMID:12946282

ProBiS tools (algorithm, database, and web servers) for predicting and modeling of biologically interesting proteins.

PubMed

Konc, Janez; Janežič, Dušanka

2017-09-01

ProBiS (Protein Binding Sites) Tools consist of algorithm, database, and web servers for prediction of binding sites and protein ligands based on the detection of structurally similar binding sites in the Protein Data Bank. In this article, we review the operations that ProBiS Tools perform, provide comments on the evolution of the tools, and give some implementation details. We review some of its applications to biologically interesting proteins. ProBiS Tools are freely available at http://probis.cmm.ki.si and http://probis.nih.gov. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites.

PubMed

Vukovic, Sinisa; Brennan, Paul E; Huggins, David J

2016-09-01

The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.

Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites

NASA Astrophysics Data System (ADS)

Vukovic, Sinisa; Brennan, Paul E.; Huggins, David J.

2016-09-01

The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.

Discovery and information-theoretic characterization of transcription factor binding sites that act cooperatively.

PubMed

Clifford, Jacob; Adami, Christoph

2015-09-02

Transcription factor binding to the surface of DNA regulatory regions is one of the primary causes of regulating gene expression levels. A probabilistic approach to model protein-DNA interactions at the sequence level is through position weight matrices (PWMs) that estimate the joint probability of a DNA binding site sequence by assuming positional independence within the DNA sequence. Here we construct conditional PWMs that depend on the motif signatures in the flanking DNA sequence, by conditioning known binding site loci on the presence or absence of additional binding sites in the flanking sequence of each site's locus. Pooling known sites with similar flanking sequence patterns allows for the estimation of the conditional distribution function over the binding site sequences. We apply our model to the Dorsal transcription factor binding sites active in patterning the Dorsal-Ventral axis of Drosophila development. We find that those binding sites that cooperate with nearby Twist sites on average contain about 0.5 bits of information about the presence of Twist transcription factor binding sites in the flanking sequence. We also find that Dorsal binding site detectors conditioned on flanking sequence information make better predictions about what is a Dorsal site relative to background DNA than detection without information about flanking sequence features.

Identification of candidate transcription factor binding sites in the cattle genome

USDA-ARS?s Scientific Manuscript database

A resource that provides candidate transcription factor binding sites does not currently exist for cattle. Such data is necessary, as predicted sites may serve as excellent starting locations for future 'omics studies to develop transcriptional regulation hypotheses. In order to generate this resour...

Hot-spot identification on a broad class of proteins and RNA suggest unifying principles of molecular recognition

PubMed Central

Kulp, John L.; Cloudsdale, Ian S.; Kulp, John L.

2017-01-01

Chemically diverse fragments tend to collectively bind at localized sites on proteins, which is a cornerstone of fragment-based techniques. A central question is how general are these strategies for predicting a wide variety of molecular interactions such as small molecule-protein, protein-protein and protein-nucleic acid for both experimental and computational methods. To address this issue, we recently proposed three governing principles, (1) accurate prediction of fragment-macromolecule binding free energy, (2) accurate prediction of water-macromolecule binding free energy, and (3) locating sites on a macromolecule that have high affinity for a diversity of fragments and low affinity for water. To test the generality of these concepts we used the computational technique of Simulated Annealing of Chemical Potential to design one small fragment to break the RecA-RecA protein-protein interaction and three fragments that inhibit peptide-deformylase via water-mediated multi-body interactions. Experiments confirm the predictions that 6-hydroxydopamine potently inhibits RecA and that PDF inhibition quantitatively tracks the water-mediated binding predictions. Additionally, the principles correctly predict the essential bound waters in HIV Protease, the surprisingly extensive binding site of elastase, the pinpoint location of electron transfer in dihydrofolate reductase, the HIV TAT-TAR protein-RNA interactions, and the MDM2-MDM4 differential binding to p53. The experimental confirmations of highly non-obvious predictions combined with the precise characterization of a broad range of known phenomena lend strong support to the generality of fragment-based methods for characterizing molecular recognition. PMID:28837642

Hot-spot identification on a broad class of proteins and RNA suggest unifying principles of molecular recognition.

PubMed

Kulp, John L; Cloudsdale, Ian S; Kulp, John L; Guarnieri, Frank

2017-01-01

Chemically diverse fragments tend to collectively bind at localized sites on proteins, which is a cornerstone of fragment-based techniques. A central question is how general are these strategies for predicting a wide variety of molecular interactions such as small molecule-protein, protein-protein and protein-nucleic acid for both experimental and computational methods. To address this issue, we recently proposed three governing principles, (1) accurate prediction of fragment-macromolecule binding free energy, (2) accurate prediction of water-macromolecule binding free energy, and (3) locating sites on a macromolecule that have high affinity for a diversity of fragments and low affinity for water. To test the generality of these concepts we used the computational technique of Simulated Annealing of Chemical Potential to design one small fragment to break the RecA-RecA protein-protein interaction and three fragments that inhibit peptide-deformylase via water-mediated multi-body interactions. Experiments confirm the predictions that 6-hydroxydopamine potently inhibits RecA and that PDF inhibition quantitatively tracks the water-mediated binding predictions. Additionally, the principles correctly predict the essential bound waters in HIV Protease, the surprisingly extensive binding site of elastase, the pinpoint location of electron transfer in dihydrofolate reductase, the HIV TAT-TAR protein-RNA interactions, and the MDM2-MDM4 differential binding to p53. The experimental confirmations of highly non-obvious predictions combined with the precise characterization of a broad range of known phenomena lend strong support to the generality of fragment-based methods for characterizing molecular recognition.

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

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.

Protein protein interactions: organization, cooperativity and mapping in a bottom-up Systems Biology approach

NASA Astrophysics Data System (ADS)

Keskin, Ozlem; Ma, Buyong; Rogale, Kristina; Gunasekaran, K.; Nussinov, Ruth

2005-06-01

Understanding and ultimately predicting protein associations is immensely important for functional genomics and drug design. Here, we propose that binding sites have preferred organizations. First, the hot spots cluster within densely packed 'hot regions'. Within these regions, they form networks of interactions. Thus, hot spots located within a hot region contribute cooperatively to the stability of the complex. However, the contributions of separate, independent hot regions are additive. Moreover, hot spots are often already pre-organized in the unbound (free) protein states. Describing a binding site through independent local hot regions has implications for binding site definition, design and parametrization for prediction. The compactness and cooperativity emphasize the similarity between binding and folding. This proposition is grounded in computation and experiment. It explains why summation of the interactions may over-estimate the stability of the complex. Furthermore, statistically, charge-charge coupling of the hot spots is disfavored. However, since within the highly packed regions the solvent is screened, the electrostatic contributions are strengthened. Thus, we propose a new description of protein binding sites: a site consists of (one or a few) self-contained cooperative regions. Since the residue hot spots are those conserved by evolution, proteins binding multiple partners at the same sites are expected to use all or some combination of these regions.

Global Mapping of Transcription Factor Binding Sites by Sequencing Chromatin Surrogates: a Perspective on Experimental Design, Data Analysis, and Open Problems.

PubMed

Wei, Yingying; Wu, George; Ji, Hongkai

2013-05-01

Mapping genome-wide binding sites of all transcription factors (TFs) in all biological contexts is a critical step toward understanding gene regulation. The state-of-the-art technologies for mapping transcription factor binding sites (TFBSs) couple chromatin immunoprecipitation (ChIP) with high-throughput sequencing (ChIP-seq) or tiling array hybridization (ChIP-chip). These technologies have limitations: they are low-throughput with respect to surveying many TFs. Recent advances in genome-wide chromatin profiling, including development of technologies such as DNase-seq, FAIRE-seq and ChIP-seq for histone modifications, make it possible to predict in vivo TFBSs by analyzing chromatin features at computationally determined DNA motif sites. This promising new approach may allow researchers to monitor the genome-wide binding sites of many TFs simultaneously. In this article, we discuss various experimental design and data analysis issues that arise when applying this approach. Through a systematic analysis of the data from the Encyclopedia Of DNA Elements (ENCODE) project, we compare the predictive power of individual and combinations of chromatin marks using supervised and unsupervised learning methods, and evaluate the value of integrating information from public ChIP and gene expression data. We also highlight the challenges and opportunities for developing novel analytical methods, such as resolving the one-motif-multiple-TF ambiguity and distinguishing functional and non-functional TF binding targets from the predicted binding sites. The online version of this article (doi:10.1007/s12561-012-9066-5) contains supplementary material, which is available to authorized users.

Sequence-based prediction of protein-binding sites in DNA: comparative study of two SVM models.

PubMed

Park, Byungkyu; Im, Jinyong; Tuvshinjargal, Narankhuu; Lee, Wook; Han, Kyungsook

2014-11-01

As many structures of protein-DNA complexes have been known in the past years, several computational methods have been developed to predict DNA-binding sites in proteins. However, its inverse problem (i.e., predicting protein-binding sites in DNA) has received much less attention. One of the reasons is that the differences between the interaction propensities of nucleotides are much smaller than those between amino acids. Another reason is that DNA exhibits less diverse sequence patterns than protein. Therefore, predicting protein-binding DNA nucleotides is much harder than predicting DNA-binding amino acids. We computed the interaction propensity (IP) of nucleotide triplets with amino acids using an extensive dataset of protein-DNA complexes, and developed two support vector machine (SVM) models that predict protein-binding nucleotides from sequence data alone. One SVM model predicts protein-binding nucleotides using DNA sequence data alone, and the other SVM model predicts protein-binding nucleotides using both DNA and protein sequences. In a 10-fold cross-validation with 1519 DNA sequences, the SVM model that uses DNA sequence data only predicted protein-binding nucleotides with an accuracy of 67.0%, an F-measure of 67.1%, and a Matthews correlation coefficient (MCC) of 0.340. With an independent dataset of 181 DNAs that were not used in training, it achieved an accuracy of 66.2%, an F-measure 66.3% and a MCC of 0.324. Another SVM model that uses both DNA and protein sequences achieved an accuracy of 69.6%, an F-measure of 69.6%, and a MCC of 0.383 in a 10-fold cross-validation with 1519 DNA sequences and 859 protein sequences. With an independent dataset of 181 DNAs and 143 proteins, it showed an accuracy of 67.3%, an F-measure of 66.5% and a MCC of 0.329. Both in cross-validation and independent testing, the second SVM model that used both DNA and protein sequence data showed better performance than the first model that used DNA sequence data. To the best of our knowledge, this is the first attempt to predict protein-binding nucleotides in a given DNA sequence from the sequence data alone. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Combining fragment homology modeling with molecular dynamics aims at prediction of Ca2+ binding sites in CaBPs

NASA Astrophysics Data System (ADS)

Pang, ChunLi; Cao, TianGuang; Li, JunWei; Jia, MengWen; Zhang, SuHua; Ren, ShuXi; An, HaiLong; Zhan, Yong

2013-08-01

The family of calcium-binding proteins (CaBPs) consists of dozens of members and contributes to all aspects of the cell's function, from homeostasis to learning and memory. However, the Ca2+-binding mechanism is still unclear for most of CaBPs. To identify the Ca2+-binding sites of CaBPs, this study presented a computational approach which combined the fragment homology modeling with molecular dynamics simulation. For validation, we performed a two-step strategy as follows: first, the approach is used to identify the Ca2+-binding sites of CaBPs, which have the EF-hand Ca2+-binding site and the detailed binding mechanism. To accomplish this, eighteen crystal structures of CaBPs with 49 Ca2+-binding sites are selected to be analyzed including calmodulin. The computational method identified 43 from 49 Ca2+-binding sites. Second, we performed the approach to large-conductance Ca2+-activated K+ (BK) channels which don't have clear Ca2+-binding mechanism. The simulated results are consistent with the experimental data. The computational approach may shed some light on the identification of Ca2+-binding sites in CaBPs.

Computational Predictions Provide Insights into the Biology of TAL Effector Target Sites

PubMed Central

Grau, Jan; Wolf, Annett; Reschke, Maik; Bonas, Ulla; Posch, Stefan; Boch, Jens

2013-01-01

Transcription activator-like (TAL) effectors are injected into host plant cells by Xanthomonas bacteria to function as transcriptional activators for the benefit of the pathogen. The DNA binding domain of TAL effectors is composed of conserved amino acid repeat structures containing repeat-variable diresidues (RVDs) that determine DNA binding specificity. In this paper, we present TALgetter, a new approach for predicting TAL effector target sites based on a statistical model. In contrast to previous approaches, the parameters of TALgetter are estimated from training data computationally. We demonstrate that TALgetter successfully predicts known TAL effector target sites and often yields a greater number of predictions that are consistent with up-regulation in gene expression microarrays than an existing approach, Target Finder of the TALE-NT suite. We study the binding specificities estimated by TALgetter and approve that different RVDs are differently important for transcriptional activation. In subsequent studies, the predictions of TALgetter indicate a previously unreported positional preference of TAL effector target sites relative to the transcription start site. In addition, several TAL effectors are predicted to bind to the TATA-box, which might constitute one general mode of transcriptional activation by TAL effectors. Scrutinizing the predicted target sites of TALgetter, we propose several novel TAL effector virulence targets in rice and sweet orange. TAL-mediated induction of the candidates is supported by gene expression microarrays. Validity of these targets is also supported by functional analogy to known TAL effector targets, by an over-representation of TAL effector targets with similar function, or by a biological function related to pathogen infection. Hence, these predicted TAL effector virulence targets are promising candidates for studying the virulence function of TAL effectors. TALgetter is implemented as part of the open-source Java library Jstacs, and is freely available as a web-application and a command line program. PMID:23526890

Prediction of the binding site of 1-benzyl-4-[(5,6-dimethoxy-1-indanon-2-yl)methyl]piperidine in acetylcholinesterase by docking studies with the SYSDOC program

NASA Astrophysics Data System (ADS)

Pang, Yuan-Ping; Kozikowski, Alan P.

1994-12-01

In the preceding paper we reported on a docking study with the SYSDOC program for predicting the binding sites of huperzine A in acetylcholinesterase (AChE) [Pang, Y.-P. and Kozikowski, A.P., J. Comput.-Aided Mol. Design, 8 (1994) 669]. Here we present a prediction of the binding sites of 1-benzyl-4-[(5,6-dimethoxy-1-indanon-2-yl)methyl]piperidine (E2020) in AChE by the same method. E2020 is one of the most potent and selective reversible inhibitors of AChE, and this molecule has puzzled researchers, partly due to its flexible structure, in understanding how it binds to AChE. Based on the results of docking 1320 different conformers of E2020 into 69 different conformers of AChE and on the pharmacological data reported for E2020 and its analogs, we predict that both the R- and the S-isomer of E2020 span the whole binding cavity of AChE, with the ammonium group interacting mainly with Trp84, Phe330 and Asp72, the phenyl group interacting mainly with Trp84 and Phe330, and the indanone moiety interacting mainly with Tyr70 and Trp279. The topography of the calculated E2020 binding sites provides insights into understanding the high potency of E2020 in the inhibition of AChE and provides hints as to possible structural modifications for identifying improved AChE inhibitors as potential therapeutics for the palliative treatment of Alzheimer's disease.

Incorporating evolution of transcription factor binding sites into annotated alignments.

PubMed

Bais, Abha S; Grossmann, Stefen; Vingron, Martin

2007-08-01

Identifying transcription factor binding sites (TFBSs) is essential to elucidate putative regulatory mechanisms. A common strategy is to combine cross-species conservation with single sequence TFBS annotation to yield "conserved TFBSs". Most current methods in this field adopt a multi-step approach that segregates the two aspects. Again, it is widely accepted that the evolutionary dynamics of binding sites differ from those of the surrounding sequence. Hence, it is desirable to have an approach that explicitly takes this factor into account. Although a plethora of approaches have been proposed for the prediction of conserved TFBSs, very few explicitly model TFBS evolutionary properties, while additionally being multi-step. Recently, we introduced a novel approach to simultaneously align and annotate conserved TFBSs in a pair of sequences. Building upon the standard Smith-Waterman algorithm for local alignments, SimAnn introduces additional states for profiles to output extended alignments or annotated alignments. That is, alignments with parts annotated as gaplessly aligned TFBSs (pair-profile hits)are generated. Moreover,the pair- profile related parameters are derived in a sound statistical framework. In this article, we extend this approach to explicitly incorporate evolution of binding sites in the SimAnn framework. We demonstrate the extension in the theoretical derivations through two position-specific evolutionary models, previously used for modelling TFBS evolution. In a simulated setting, we provide a proof of concept that the approach works given the underlying assumptions,as compared to the original work. Finally, using a real dataset of experimentally verified binding sites in human-mouse sequence pairs,we compare the new approach (eSimAnn) to an existing multi-step tool that also considers TFBS evolution. Although it is widely accepted that binding sites evolve differently from the surrounding sequences, most comparative TFBS identification methods do not explicitly consider this.Additionally, prediction of conserved binding sites is carried out in a multi-step approach that segregates alignment from TFBS annotation. In this paper, we demonstrate how the simultaneous alignment and annotation approach of SimAnn can be further extended to incorporate TFBS evolutionary relationships. We study how alignments and binding site predictions interplay at varying evolutionary distances and for various profile qualities.

eF-seek: prediction of the functional sites of proteins by searching for similar electrostatic potential and molecular surface shape.

PubMed

Kinoshita, Kengo; Murakami, Yoichi; Nakamura, Haruki

2007-07-01

We have developed a method to predict ligand-binding sites in a new protein structure by searching for similar binding sites in the Protein Data Bank (PDB). The similarities are measured according to the shapes of the molecular surfaces and their electrostatic potentials. A new web server, eF-seek, provides an interface to our search method. It simply requires a coordinate file in the PDB format, and generates a prediction result as a virtual complex structure, with the putative ligands in a PDB format file as the output. In addition, the predicted interacting interface is displayed to facilitate the examination of the virtual complex structure on our own applet viewer with the web browser (URL: http://eF-site.hgc.jp/eF-seek).

Prediction of allosteric sites on protein surfaces with an elastic-network-model-based thermodynamic method.

PubMed

Su, Ji Guo; Qi, Li Sheng; Li, Chun Hua; Zhu, Yan Ying; Du, Hui Jing; Hou, Yan Xue; Hao, Rui; Wang, Ji Hua

2014-08-01

Allostery is a rapid and efficient way in many biological processes to regulate protein functions, where binding of an effector at the allosteric site alters the activity and function at a distant active site. Allosteric regulation of protein biological functions provides a promising strategy for novel drug design. However, how to effectively identify the allosteric sites remains one of the major challenges for allosteric drug design. In the present work, a thermodynamic method based on the elastic network model was proposed to predict the allosteric sites on the protein surface. In our method, the thermodynamic coupling between the allosteric and active sites was considered, and then the allosteric sites were identified as those where the binding of an effector molecule induces a large change in the binding free energy of the protein with its ligand. Using the proposed method, two proteins, i.e., the 70 kD heat shock protein (Hsp70) and GluA2 alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor, were studied and the allosteric sites on the protein surface were successfully identified. The predicted results are consistent with the available experimental data, which indicates that our method is a simple yet effective approach for the identification of allosteric sites on proteins.

Prediction of allosteric sites on protein surfaces with an elastic-network-model-based thermodynamic method

NASA Astrophysics Data System (ADS)

Su, Ji Guo; Qi, Li Sheng; Li, Chun Hua; Zhu, Yan Ying; Du, Hui Jing; Hou, Yan Xue; Hao, Rui; Wang, Ji Hua

2014-08-01

Allostery is a rapid and efficient way in many biological processes to regulate protein functions, where binding of an effector at the allosteric site alters the activity and function at a distant active site. Allosteric regulation of protein biological functions provides a promising strategy for novel drug design. However, how to effectively identify the allosteric sites remains one of the major challenges for allosteric drug design. In the present work, a thermodynamic method based on the elastic network model was proposed to predict the allosteric sites on the protein surface. In our method, the thermodynamic coupling between the allosteric and active sites was considered, and then the allosteric sites were identified as those where the binding of an effector molecule induces a large change in the binding free energy of the protein with its ligand. Using the proposed method, two proteins, i.e., the 70 kD heat shock protein (Hsp70) and GluA2 alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor, were studied and the allosteric sites on the protein surface were successfully identified. The predicted results are consistent with the available experimental data, which indicates that our method is a simple yet effective approach for the identification of allosteric sites on proteins.

Binding Pathway of Opiates to μ-Opioid Receptors Revealed by Machine Learning

NASA Astrophysics Data System (ADS)

Barati Farimani, Amir; Feinberg, Evan; Pande, Vijay

2018-02-01

Many important analgesics relieve pain by binding to the $\\mu$-Opioid Receptor ($\\mu$OR), which makes the $\\mu$OR among the most clinically relevant proteins of the G Protein Coupled Receptor (GPCR) family. Despite previous studies on the activation pathways of the GPCRs, the mechanism of opiate binding and the selectivity of $\\mu$OR are largely unknown. We performed extensive molecular dynamics (MD) simulation and analysis to find the selective allosteric binding sites of the $\\mu$OR and the path opiates take to bind to the orthosteric site. In this study, we predicted that the allosteric site is responsible for the attraction and selection of opiates. Using Markov state models and machine learning, we traced the pathway of opiates in binding to the orthosteric site, the main binding pocket. Our results have important implications in designing novel analgesics.

Probing binding hot spots at protein-RNA recognition sites.

PubMed

Barik, Amita; Nithin, Chandran; Karampudi, Naga Bhushana Rao; Mukherjee, Sunandan; Bahadur, Ranjit Prasad

2016-01-29

We use evolutionary conservation derived from structure alignment of polypeptide sequences along with structural and physicochemical attributes of protein-RNA interfaces to probe the binding hot spots at protein-RNA recognition sites. We find that the degree of conservation varies across the RNA binding proteins; some evolve rapidly compared to others. Additionally, irrespective of the structural class of the complexes, residues at the RNA binding sites are evolutionary better conserved than those at the solvent exposed surfaces. For recognitions involving duplex RNA, residues interacting with the major groove are better conserved than those interacting with the minor groove. We identify multi-interface residues participating simultaneously in protein-protein and protein-RNA interfaces in complexes where more than one polypeptide is involved in RNA recognition, and show that they are better conserved compared to any other RNA binding residues. We find that the residues at water preservation site are better conserved than those at hydrated or at dehydrated sites. Finally, we develop a Random Forests model using structural and physicochemical attributes for predicting binding hot spots. The model accurately predicts 80% of the instances of experimental ΔΔG values in a particular class, and provides a stepping-stone towards the engineering of protein-RNA recognition sites with desired affinity. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

TmiRUSite and TmiROSite scripts: searching for mRNA fragments with miRNA binding sites with encoded amino acid residues.

PubMed

Berillo, Olga; Régnier, Mireille; Ivashchenko, Anatoly

2014-01-01

microRNAs are small RNA molecules that inhibit the translation of target genes. microRNA binding sites are located in the untranslated regions as well as in the coding domains. We describe TmiRUSite and TmiROSite scripts developed using python as tools for the extraction of nucleotide sequences for miRNA binding sites with their encoded amino acid residue sequences. The scripts allow for retrieving a set of additional sequences at left and at right from the binding site. The scripts presents all received data in table formats that are easy to analyse further. The predicted data finds utility in molecular and evolutionary biology studies. They find use in studying miRNA binding sites in animals and plants. TmiRUSite and TmiROSite scripts are available for free from authors upon request and at https: //sites.google.com/site/malaheenee/downloads for download.

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.

Improve the prediction of RNA-binding residues using structural neighbours.

PubMed

Li, Quan; Cao, Zanxia; Liu, Haiyan

2010-03-01

The interactions between RNA-binding proteins (RBPs) with RNA play key roles in managing some of the cell's basic functions. The identification and prediction of RNA binding sites is important for understanding the RNA-binding mechanism. Computational approaches are being developed to predict RNA-binding residues based on the sequence- or structure-derived features. To achieve higher prediction accuracy, improvements on current prediction methods are necessary. We identified that the structural neighbors of RNA-binding and non-RNA-binding residues have different amino acid compositions. Combining this structure-derived feature with evolutionary (PSSM) and other structural information (secondary structure and solvent accessibility) significantly improves the predictions over existing methods. Using a multiple linear regression approach and 6-fold cross validation, our best model can achieve an overall correct rate of 87.8% and MCC of 0.47, with a specificity of 93.4%, correctly predict 52.4% of the RNA-binding residues for a dataset containing 107 non-homologous RNA-binding proteins. Compared with existing methods, including the amino acid compositions of structure neighbors lead to clearly improvement. A web server was developed for predicting RNA binding residues in a protein sequence (or structure),which is available at http://mcgill.3322.org/RNA/.

Druggable pockets and binding site centric chemical space: a paradigm shift in drug discovery.

PubMed

Pérot, Stéphanie; Sperandio, Olivier; Miteva, Maria A; Camproux, Anne-Claude; Villoutreix, Bruno O

2010-08-01

Detection, comparison and analyses of binding pockets are pivotal to structure-based drug design endeavors, from hit identification, screening of exosites and de-orphanization of protein functions to the anticipation of specific and non-specific binding to off- and anti-targets. Here, we analyze protein-ligand complexes and discuss methods that assist binding site identification, prediction of druggability and binding site comparison. The full potential of pockets is yet to be harnessed, and we envision that better understanding of the pocket space will have far-reaching implications in the field of drug discovery, such as the design of pocket-specific compound libraries and scoring functions.

G-LoSA for Prediction of Protein-Ligand Binding Sites and Structures.

PubMed

Lee, Hui Sun; Im, Wonpil

2017-01-01

Recent advances in high-throughput structure determination and computational protein structure prediction have significantly enriched the universe of protein structure. However, there is still a large gap between the number of available protein structures and that of proteins with annotated function in high accuracy. Computational structure-based protein function prediction has emerged to reduce this knowledge gap. The identification of a ligand binding site and its structure is critical to the determination of a protein's molecular function. We present a computational methodology for predicting small molecule ligand binding site and ligand structure using G-LoSA, our protein local structure alignment and similarity measurement tool. All the computational procedures described here can be easily implemented using G-LoSA Toolkit, a package of standalone software programs and preprocessed PDB structure libraries. G-LoSA and G-LoSA Toolkit are freely available to academic users at http://compbio.lehigh.edu/GLoSA . We also illustrate a case study to show the potential of our template-based approach harnessing G-LoSA for protein function prediction.

Nature of the Active Sites for CO Reduction on Copper Nanoparticles; Suggestions for Optimizing Performance.

PubMed

Cheng, Tao; Xiao, Hai; Goddard, William A

2017-08-30

Recent experiments show that the grain boundaries (GBs) of copper nanoparticles (NPs) lead to an outstanding performance in reducing CO 2 and CO to alcohol products. We report here multiscale simulations that simulate experimental synthesis conditions to predict the structure of a 10 nm Cu NP (158 555 atoms). To identify active sites, we first predict the CO binding at a large number of sites and select four exhibiting CO binding stronger than the (211) step surface. Then, we predict the formation energy of the *OCCOH intermediate as a descriptor for C-C coupling, identifying two active sites, both of which have an under-coordinated surface square site adjacent to a subsurface stacking fault. We then propose a periodic Cu surface (4 by 4 supercell) with a similar site that substantially decreases the formation energy of *OCCOH, by 0.14 eV.

First Principles Predictions of the Structure and Function of G-Protein-Coupled Receptors: Validation for Bovine Rhodopsin

PubMed Central

Trabanino, Rene J.; Hall, Spencer E.; Vaidehi, Nagarajan; Floriano, Wely B.; Kam, Victor W. T.; Goddard, William A.

2004-01-01

G-protein-coupled receptors (GPCRs) are involved in cell communication processes and with mediating such senses as vision, smell, taste, and pain. They constitute a prominent superfamily of drug targets, but an atomic-level structure is available for only one GPCR, bovine rhodopsin, making it difficult to use structure-based methods to design receptor-specific drugs. We have developed the MembStruk first principles computational method for predicting the three-dimensional structure of GPCRs. In this article we validate the MembStruk procedure by comparing its predictions with the high-resolution crystal structure of bovine rhodopsin. The crystal structure of bovine rhodopsin has the second extracellular (EC-II) loop closed over the transmembrane regions by making a disulfide linkage between Cys-110 and Cys-187, but we speculate that opening this loop may play a role in the activation process of the receptor through the cysteine linkage with helix 3. Consequently we predicted two structures for bovine rhodopsin from the primary sequence (with no input from the crystal structure)—one with the EC-II loop closed as in the crystal structure, and the other with the EC-II loop open. The MembStruk-predicted structure of bovine rhodopsin with the closed EC-II loop deviates from the crystal by 2.84 Å coordinate root mean-square (CRMS) in the transmembrane region main-chain atoms. The predicted three-dimensional structures for other GPCRs can be validated only by predicting binding sites and energies for various ligands. For such predictions we developed the HierDock first principles computational method. We validate HierDock by predicting the binding site of 11-cis-retinal in the crystal structure of bovine rhodopsin. Scanning the whole protein without using any prior knowledge of the binding site, we find that the best scoring conformation in rhodopsin is 1.1 Å CRMS from the crystal structure for the ligand atoms. This predicted conformation has the carbonyl O only 2.82 Å from the N of Lys-296. Making this Schiff base bond and minimizing leads to a final conformation only 0.62 Å CRMS from the crystal structure. We also used HierDock to predict the binding site of 11-cis-retinal in the MembStruk-predicted structure of bovine rhodopsin (closed loop). Scanning the whole protein structure leads to a structure in which the carbonyl O is only 2.85 Å from the N of Lys-296. Making this Schiff base bond and minimizing leads to a final conformation only 2.92 Å CRMS from the crystal structure. The good agreement of the ab initio-predicted protein structures and ligand binding site with experiment validates the use of the MembStruk and HierDock first principles' methods. Since these methods are generic and applicable to any GPCR, they should be useful in predicting the structures of other GPCRs and the binding site of ligands to these proteins. PMID:15041637

Mapping structural landmarks, ligand binding sites and missense mutations to the collagen IV heterotrimers predicts major functional domains, novel interactions and variation in phenotypes in inherited diseases affecting basement membranes

PubMed Central

Des Parkin, J.; San Antonio, James D.; Pedchenko, Vadim; Hudson, Billy; Jensen, Shane T.; Savige, Judy

2016-01-01

Collagen IV is the major protein found in basement membranes. It comprises 3 heterotrimers (α1α1α2, α3α4α5, and α5α5α6) that form distinct networks, and are responsible for membrane strength and integrity. We constructed linear maps of the collagen IV heterotrimers (‘interactomes’) that indicated major structural landmarks, known and predicted ligand-binding sites, and missense mutations, in order to identify functional and disease-associated domains, potential interactions between ligands, and genotype-phenotype relationships. The maps documented more than 30 known ligand-binding sites as well as motifs for integrins, heparin, von Willebrand factor (VWF), decorin and bone morphogenetic protein (BMP). They predicted functional domains for angiogenesis and haemostasis, and disease domains for autoimmunity, tumor growth and inhibition, infection and glycation. Cooperative ligand interactions were indicated by binding site proximity, for example, between integrins, matrix metalloproteinases and heparin. The maps indicated that mutations affecting major ligand-binding sites, for example for Von Hippel Lindau (VHL) protein in the α1 chain or integrins in the α5 chain, resulted in distinctive phenotypes (Hereditary Angiopathy, Nephropathy, Aneurysms and muscle Cramps (HANAC) syndrome, and early onset Alport syndrome respectively). These maps further our understanding of basement membrane biology and disease, and suggest novel membrane interactions, functions, and therapeutic targets. PMID:21280145

Prediction of Ordered Water Molecules in Protein Binding Sites from Molecular Dynamics Simulations: The Impact of Ligand Binding on Hydration Networks.

PubMed

Rudling, Axel; Orro, Adolfo; Carlsson, Jens

2018-02-26

Water plays a major role in ligand binding and is attracting increasing attention in structure-based drug design. Water molecules can make large contributions to binding affinity by bridging protein-ligand interactions or by being displaced upon complex formation, but these phenomena are challenging to model at the molecular level. Herein, networks of ordered water molecules in protein binding sites were analyzed by clustering of molecular dynamics (MD) simulation trajectories. Locations of ordered waters (hydration sites) were first identified from simulations of high resolution crystal structures of 13 protein-ligand complexes. The MD-derived hydration sites reproduced 73% of the binding site water molecules observed in the crystal structures. If the simulations were repeated without the cocrystallized ligands, a majority (58%) of the crystal waters in the binding sites were still predicted. In addition, comparison of the hydration sites obtained from simulations carried out in the absence of ligands to those identified for the complexes revealed that the networks of ordered water molecules were preserved to a large extent, suggesting that the locations of waters in a protein-ligand interface are mainly dictated by the protein. Analysis of >1000 crystal structures showed that hydration sites bridged protein-ligand interactions in complexes with different ligands, and those with high MD-derived occupancies were more likely to correspond to experimentally observed ordered water molecules. The results demonstrate that ordered water molecules relevant for modeling of protein-ligand complexes can be identified from MD simulations. Our findings could contribute to development of improved methods for structure-based virtual screening and lead optimization.

Predicting RNA-protein binding sites and motifs through combining local and global deep convolutional neural networks.

PubMed

Pan, Xiaoyong; Shen, Hong-Bin

2018-05-02

RNA-binding proteins (RBPs) take over 5∼10% of the eukaryotic proteome and play key roles in many biological processes, e.g. gene regulation. Experimental detection of RBP binding sites is still time-intensive and high-costly. Instead, computational prediction of the RBP binding sites using pattern learned from existing annotation knowledge is a fast approach. From the biological point of view, the local structure context derived from local sequences will be recognized by specific RBPs. However, in computational modeling using deep learning, to our best knowledge, only global representations of entire RNA sequences are employed. So far, the local sequence information is ignored in the deep model construction process. In this study, we present a computational method iDeepE to predict RNA-protein binding sites from RNA sequences by combining global and local convolutional neural networks (CNNs). For the global CNN, we pad the RNA sequences into the same length. For the local CNN, we split a RNA sequence into multiple overlapping fixed-length subsequences, where each subsequence is a signal channel of the whole sequence. Next, we train deep CNNs for multiple subsequences and the padded sequences to learn high-level features, respectively. Finally, the outputs from local and global CNNs are combined to improve the prediction. iDeepE demonstrates a better performance over state-of-the-art methods on two large-scale datasets derived from CLIP-seq. We also find that the local CNN run 1.8 times faster than the global CNN with comparable performance when using GPUs. Our results show that iDeepE has captured experimentally verified binding motifs. https://github.com/xypan1232/iDeepE. xypan172436@gmail.com or hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online.

Three-dimensional (3D) structure prediction and function analysis of the chitin-binding domain 3 protein HD73_3189 from Bacillus thuringiensis HD73.

PubMed

Zhan, Yiling; Guo, Shuyuan

2015-01-01

Bacillus thuringiensis (Bt) is capable of producing a chitin-binding protein believed to be functionally important to bacteria during the stationary phase of its growth cycle. In this paper, the chitin-binding domain 3 protein HD73_3189 from B. thuringiensis has been analyzed by computer technology. Primary and secondary structural analyses demonstrated that HD73_3189 is negatively charged and contains several α-helices, aperiodical coils and β-strands. Domain and motif analyses revealed that HD73_3189 contains a signal peptide, an N-terminal chitin binding 3 domains, two copies of a fibronectin-like domain 3 and a C-terminal carbohydrate binding domain classified as CBM_5_12. Moreover, analysis predicted the protein's associated localization site to be the cell wall. Ligand site prediction determined that amino acid residues GLU-312, TRP-334, ILE-341 and VAL-382 exposed on the surface of the target protein exhibit polar interactions with the substrate.

Development of a sugar-binding residue prediction system from protein sequences using support vector machine.

PubMed

Banno, Masaki; Komiyama, Yusuke; Cao, Wei; Oku, Yuya; Ueki, Kokoro; Sumikoshi, Kazuya; Nakamura, Shugo; Terada, Tohru; Shimizu, Kentaro

2017-02-01

Several methods have been proposed for protein-sugar binding site prediction using machine learning algorithms. However, they are not effective to learn various properties of binding site residues caused by various interactions between proteins and sugars. In this study, we classified sugars into acidic and nonacidic sugars and showed that their binding sites have different amino acid occurrence frequencies. By using this result, we developed sugar-binding residue predictors dedicated to the two classes of sugars: an acid sugar binding predictor and a nonacidic sugar binding predictor. We also developed a combination predictor which combines the results of the two predictors. We showed that when a sugar is known to be an acidic sugar, the acidic sugar binding predictor achieves the best performance, and showed that when a sugar is known to be a nonacidic sugar or is not known to be either of the two classes, the combination predictor achieves the best performance. Our method uses only amino acid sequences for prediction. Support vector machine was used as a machine learning algorithm and the position-specific scoring matrix created by the position-specific iterative basic local alignment search tool was used as the feature vector. We evaluated the performance of the predictors using five-fold cross-validation. We have launched our system, as an open source freeware tool on the GitHub repository (https://doi.org/10.5281/zenodo.61513). Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

footprintDB: a database of transcription factors with annotated cis elements and binding interfaces.

PubMed

Sebastian, Alvaro; Contreras-Moreira, Bruno

2014-01-15

Traditional and high-throughput techniques for determining transcription factor (TF) binding specificities are generating large volumes of data of uneven quality, which are scattered across individual databases. FootprintDB integrates some of the most comprehensive freely available libraries of curated DNA binding sites and systematically annotates the binding interfaces of the corresponding TFs. The first release contains 2422 unique TF sequences, 10 112 DNA binding sites and 3662 DNA motifs. A survey of the included data sources, organisms and TF families was performed together with proprietary database TRANSFAC, finding that footprintDB has a similar coverage of multicellular organisms, while also containing bacterial regulatory data. A search engine has been designed that drives the prediction of DNA motifs for input TFs, or conversely of TF sequences that might recognize input regulatory sequences, by comparison with database entries. Such predictions can also be extended to a single proteome chosen by the user, and results are ranked in terms of interface similarity. Benchmark experiments with bacterial, plant and human data were performed to measure the predictive power of footprintDB searches, which were able to correctly recover 10, 55 and 90% of the tested sequences, respectively. Correctly predicted TFs had a higher interface similarity than the average, confirming its diagnostic value. Web site implemented in PHP,Perl, MySQL and Apache. Freely available from http://floresta.eead.csic.es/footprintdb.

JET2 Viewer: a database of predicted multiple, possibly overlapping, protein-protein interaction sites for PDB structures.

PubMed

Ripoche, Hugues; Laine, Elodie; Ceres, Nicoletta; Carbone, Alessandra

2017-01-04

The database JET2 Viewer, openly accessible at http://www.jet2viewer.upmc.fr/, reports putative protein binding sites for all three-dimensional (3D) structures available in the Protein Data Bank (PDB). This knowledge base was generated by applying the computational method JET 2 at large-scale on more than 20 000 chains. JET 2 strategy yields very precise predictions of interacting surfaces and unravels their evolutionary process and complexity. JET2 Viewer provides an online intelligent display, including interactive 3D visualization of the binding sites mapped onto PDB structures and suitable files recording JET 2 analyses. Predictions were evaluated on more than 15 000 experimentally characterized protein interfaces. This is, to our knowledge, the largest evaluation of a protein binding site prediction method. The overall performance of JET 2 on all interfaces are: Sen = 52.52, PPV = 51.24, Spe = 80.05, Acc = 75.89. The data can be used to foster new strategies for protein-protein interactions modulation and interaction surface redesign. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Automated docking of ligands to an artificial active site: augmenting crystallographic analysis with computer modeling

NASA Astrophysics Data System (ADS)

Rosenfeld, Robin J.; Goodsell, David S.; Musah, Rabi A.; Morris, Garrett M.; Goodin, David B.; Olson, Arthur J.

2003-08-01

The W191G cavity of cytochrome c peroxidase is useful as a model system for introducing small molecule oxidation in an artificially created cavity. A set of small, cyclic, organic cations was previously shown to bind in the buried, solvent-filled pocket created by the W191G mutation. We docked these ligands and a set of non-binders in the W191G cavity using AutoDock 3.0. For the ligands, we compared docking predictions with experimentally determined binding energies and X-ray crystal structure complexes. For the ligands, predicted binding energies differed from measured values by ± 0.8 kcal/mol. For most ligands, the docking simulation clearly predicted a single binding mode that matched the crystallographic binding mode within 1.0 Å RMSD. For 2 ligands, where the docking procedure yielded an ambiguous result, solutions matching the crystallographic result could be obtained by including an additional crystallographically observed water molecule in the protein model. For the remaining 2 ligands, docking indicated multiple binding modes, consistent with the original electron density, suggesting disordered binding of these ligands. Visual inspection of the atomic affinity grid maps used in docking calculations revealed two patches of high affinity for hydrogen bond donating groups. Multiple solutions are predicted as these two sites compete for polar hydrogens in the ligand during the docking simulation. Ligands could be distinguished, to some extent, from non-binders using a combination of two trends: predicted binding energy and level of clustering. In summary, AutoDock 3.0 appears to be useful in predicting key structural and energetic features of ligand binding in the W191G cavity.

CisMiner: Genome-Wide In-Silico Cis-Regulatory Module Prediction by Fuzzy Itemset Mining

PubMed Central

Navarro, Carmen; Lopez, Francisco J.; Cano, Carlos; Garcia-Alcalde, Fernando; Blanco, Armando

2014-01-01

Eukaryotic gene control regions are known to be spread throughout non-coding DNA sequences which may appear distant from the gene promoter. Transcription factors are proteins that coordinately bind to these regions at transcription factor binding sites to regulate gene expression. Several tools allow to detect significant co-occurrences of closely located binding sites (cis-regulatory modules, CRMs). However, these tools present at least one of the following limitations: 1) scope limited to promoter or conserved regions of the genome; 2) do not allow to identify combinations involving more than two motifs; 3) require prior information about target motifs. In this work we present CisMiner, a novel methodology to detect putative CRMs by means of a fuzzy itemset mining approach able to operate at genome-wide scale. CisMiner allows to perform a blind search of CRMs without any prior information about target CRMs nor limitation in the number of motifs. CisMiner tackles the combinatorial complexity of genome-wide cis-regulatory module extraction using a natural representation of motif combinations as itemsets and applying the Top-Down Fuzzy Frequent- Pattern Tree algorithm to identify significant itemsets. Fuzzy technology allows CisMiner to better handle the imprecision and noise inherent to regulatory processes. Results obtained for a set of well-known binding sites in the S. cerevisiae genome show that our method yields highly reliable predictions. Furthermore, CisMiner was also applied to putative in-silico predicted transcription factor binding sites to identify significant combinations in S. cerevisiae and D. melanogaster, proving that our approach can be further applied genome-wide to more complex genomes. CisMiner is freely accesible at: http://genome2.ugr.es/cisminer. CisMiner can be queried for the results presented in this work and can also perform a customized cis-regulatory module prediction on a query set of transcription factor binding sites provided by the user. PMID:25268582

Mechanism of human antibody-mediated neutralization of Marburg virus.

PubMed

Flyak, Andrew I; Ilinykh, Philipp A; Murin, Charles D; Garron, Tania; Shen, Xiaoli; Fusco, Marnie L; Hashiguchi, Takao; Bornholdt, Zachary A; Slaughter, James C; Sapparapu, Gopal; Klages, Curtis; Ksiazek, Thomas G; Ward, Andrew B; Saphire, Erica Ollmann; Bukreyev, Alexander; Crowe, James E

2015-02-26

The mechanisms by which neutralizing antibodies inhibit Marburg virus (MARV) are not known. We isolated a panel of neutralizing antibodies from a human MARV survivor that bind to MARV glycoprotein (GP) and compete for binding to a single major antigenic site. Remarkably, several of the antibodies also bind to Ebola virus (EBOV) GP. Single-particle EM structures of antibody-GP complexes reveal that all of the neutralizing antibodies bind to MARV GP at or near the predicted region of the receptor-binding site. The presence of the glycan cap or mucin-like domain blocks binding of neutralizing antibodies to EBOV GP, but not to MARV GP. The data suggest that MARV-neutralizing antibodies inhibit virus by binding to infectious virions at the exposed MARV receptor-binding site, revealing a mechanism of filovirus inhibition. Copyright © 2015 Elsevier Inc. All rights reserved.

Using RSAT to scan genome sequences for transcription factor binding sites and cis-regulatory modules.

PubMed

Turatsinze, Jean-Valery; Thomas-Chollier, Morgane; Defrance, Matthieu; van Helden, Jacques

2008-01-01

This protocol shows how to detect putative cis-regulatory elements and regions enriched in such elements with the regulatory sequence analysis tools (RSAT) web server (http://rsat.ulb.ac.be/rsat/). The approach applies to known transcription factors, whose binding specificity is represented by position-specific scoring matrices, using the program matrix-scan. The detection of individual binding sites is known to return many false predictions. However, results can be strongly improved by estimating P value, and by searching for combinations of sites (homotypic and heterotypic models). We illustrate the detection of sites and enriched regions with a study case, the upstream sequence of the Drosophila melanogaster gene even-skipped. This protocol is also tested on random control sequences to evaluate the reliability of the predictions. Each task requires a few minutes of computation time on the server. The complete protocol can be executed in about one hour.

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.

Theory on the mechanism of site-specific DNA-protein interactions in the presence of traps

NASA Astrophysics Data System (ADS)

Niranjani, G.; Murugan, R.

2016-08-01

The speed of site-specific binding of transcription factor (TFs) proteins with genomic DNA seems to be strongly retarded by the randomly occurring sequence traps. Traps are those DNA sequences sharing significant similarity with the original specific binding sites (SBSs). It is an intriguing question how the naturally occurring TFs and their SBSs are designed to manage the retarding effects of such randomly occurring traps. We develop a simple random walk model on the site-specific binding of TFs with genomic DNA in the presence of sequence traps. Our dynamical model predicts that (a) the retarding effects of traps will be minimum when the traps are arranged around the SBS such that there is a negative correlation between the binding strength of TFs with traps and the distance of traps from the SBS and (b) the retarding effects of sequence traps can be appeased by the condensed conformational state of DNA. Our computational analysis results on the distribution of sequence traps around the putative binding sites of various TFs in mouse and human genome clearly agree well the theoretical predictions. We propose that the distribution of traps can be used as an additional metric to efficiently identify the SBSs of TFs on genomic DNA.

Modeling the evolution of regulatory elements by simultaneous detection and alignment with phylogenetic pair HMMs.

PubMed

Majoros, William H; Ohler, Uwe

2010-12-16

The computational detection of regulatory elements in DNA is a difficult but important problem impacting our progress in understanding the complex nature of eukaryotic gene regulation. Attempts to utilize cross-species conservation for this task have been hampered both by evolutionary changes of functional sites and poor performance of general-purpose alignment programs when applied to non-coding sequence. We describe a new and flexible framework for modeling binding site evolution in multiple related genomes, based on phylogenetic pair hidden Markov models which explicitly model the gain and loss of binding sites along a phylogeny. We demonstrate the value of this framework for both the alignment of regulatory regions and the inference of precise binding-site locations within those regions. As the underlying formalism is a stochastic, generative model, it can also be used to simulate the evolution of regulatory elements. Our implementation is scalable in terms of numbers of species and sequence lengths and can produce alignments and binding-site predictions with accuracy rivaling or exceeding current systems that specialize in only alignment or only binding-site prediction. We demonstrate the validity and power of various model components on extensive simulations of realistic sequence data and apply a specific model to study Drosophila enhancers in as many as ten related genomes and in the presence of gain and loss of binding sites. Different models and modeling assumptions can be easily specified, thus providing an invaluable tool for the exploration of biological hypotheses that can drive improvements in our understanding of the mechanisms and evolution of gene regulation.

Comprehensive human transcription factor binding site map for combinatory binding motifs discovery.

PubMed

Müller-Molina, Arnoldo J; Schöler, Hans R; Araúzo-Bravo, Marcos J

2012-01-01

To know the map between transcription factors (TFs) and their binding sites is essential to reverse engineer the regulation process. Only about 10%-20% of the transcription factor binding motifs (TFBMs) have been reported. This lack of data hinders understanding gene regulation. To address this drawback, we propose a computational method that exploits never used TF properties to discover the missing TFBMs and their sites in all human gene promoters. The method starts by predicting a dictionary of regulatory "DNA words." From this dictionary, it distills 4098 novel predictions. To disclose the crosstalk between motifs, an additional algorithm extracts TF combinatorial binding patterns creating a collection of TF regulatory syntactic rules. Using these rules, we narrowed down a list of 504 novel motifs that appear frequently in syntax patterns. We tested the predictions against 509 known motifs confirming that our system can reliably predict ab initio motifs with an accuracy of 81%-far higher than previous approaches. We found that on average, 90% of the discovered combinatorial binding patterns target at least 10 genes, suggesting that to control in an independent manner smaller gene sets, supplementary regulatory mechanisms are required. Additionally, we discovered that the new TFBMs and their combinatorial patterns convey biological meaning, targeting TFs and genes related to developmental functions. Thus, among all the possible available targets in the genome, the TFs tend to regulate other TFs and genes involved in developmental functions. We provide a comprehensive resource for regulation analysis that includes a dictionary of "DNA words," newly predicted motifs and their corresponding combinatorial patterns. Combinatorial patterns are a useful filter to discover TFBMs that play a major role in orchestrating other factors and thus, are likely to lock/unlock cellular functional clusters.

Comprehensive Human Transcription Factor Binding Site Map for Combinatory Binding Motifs Discovery

PubMed Central

Müller-Molina, Arnoldo J.; Schöler, Hans R.; Araúzo-Bravo, Marcos J.

2012-01-01

To know the map between transcription factors (TFs) and their binding sites is essential to reverse engineer the regulation process. Only about 10%–20% of the transcription factor binding motifs (TFBMs) have been reported. This lack of data hinders understanding gene regulation. To address this drawback, we propose a computational method that exploits never used TF properties to discover the missing TFBMs and their sites in all human gene promoters. The method starts by predicting a dictionary of regulatory “DNA words.” From this dictionary, it distills 4098 novel predictions. To disclose the crosstalk between motifs, an additional algorithm extracts TF combinatorial binding patterns creating a collection of TF regulatory syntactic rules. Using these rules, we narrowed down a list of 504 novel motifs that appear frequently in syntax patterns. We tested the predictions against 509 known motifs confirming that our system can reliably predict ab initio motifs with an accuracy of 81%—far higher than previous approaches. We found that on average, 90% of the discovered combinatorial binding patterns target at least 10 genes, suggesting that to control in an independent manner smaller gene sets, supplementary regulatory mechanisms are required. Additionally, we discovered that the new TFBMs and their combinatorial patterns convey biological meaning, targeting TFs and genes related to developmental functions. Thus, among all the possible available targets in the genome, the TFs tend to regulate other TFs and genes involved in developmental functions. We provide a comprehensive resource for regulation analysis that includes a dictionary of “DNA words,” newly predicted motifs and their corresponding combinatorial patterns. Combinatorial patterns are a useful filter to discover TFBMs that play a major role in orchestrating other factors and thus, are likely to lock/unlock cellular functional clusters. PMID:23209563

Elimination of a ligand gating site generates a supersensitive olfactory receptor.

PubMed

Sharma, Kanika; Ahuja, Gaurav; Hussain, Ashiq; Balfanz, Sabine; Baumann, Arnd; Korsching, Sigrun I

2016-06-21

Olfaction poses one of the most complex ligand-receptor matching problems in biology due to the unparalleled multitude of odor molecules facing a large number of cognate olfactory receptors. We have recently deorphanized an olfactory receptor, TAAR13c, as a specific receptor for the death-associated odor cadaverine. Here we have modeled the cadaverine/TAAR13c interaction, exchanged predicted binding residues by site-directed mutagenesis, and measured the activity of the mutant receptors. Unexpectedly we observed a binding site for cadaverine at the external surface of the receptor, in addition to an internal binding site, whose mutation resulted in complete loss of activity. In stark contrast, elimination of the external binding site generated supersensitive receptors. Modeling suggests this site to act as a gate, limiting access of the ligand to the internal binding site and thereby downregulating the affinity of the native receptor. This constitutes a novel mechanism to fine-tune physiological sensitivity to socially relevant odors.

Elimination of a ligand gating site generates a supersensitive olfactory receptor

PubMed Central

Sharma, Kanika; Ahuja, Gaurav; Hussain, Ashiq; Balfanz, Sabine; Baumann, Arnd; Korsching, Sigrun I.

2016-01-01

Olfaction poses one of the most complex ligand-receptor matching problems in biology due to the unparalleled multitude of odor molecules facing a large number of cognate olfactory receptors. We have recently deorphanized an olfactory receptor, TAAR13c, as a specific receptor for the death-associated odor cadaverine. Here we have modeled the cadaverine/TAAR13c interaction, exchanged predicted binding residues by site-directed mutagenesis, and measured the activity of the mutant receptors. Unexpectedly we observed a binding site for cadaverine at the external surface of the receptor, in addition to an internal binding site, whose mutation resulted in complete loss of activity. In stark contrast, elimination of the external binding site generated supersensitive receptors. Modeling suggests this site to act as a gate, limiting access of the ligand to the internal binding site and thereby downregulating the affinity of the native receptor. This constitutes a novel mechanism to fine-tune physiological sensitivity to socially relevant odors. PMID:27323929

Synergistic use of compound properties and docking scores in neural network modeling of CYP2D6 binding: predicting affinity and conformational sampling.

PubMed

Bazeley, Peter S; Prithivi, Sridevi; Struble, Craig A; Povinelli, Richard J; Sem, Daniel S

2006-01-01

Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known active site. Docking scores for the active site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85+/-6% is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound's formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12% improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23% above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding.

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.

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.

Selection of the simplest RNA that binds isoleucine

PubMed Central

LOZUPONE, CATHERINE; CHANGAYIL, SHANKAR; MAJERFELD, IRENE; YARUS, MICHAEL

2003-01-01

We have identified the simplest RNA binding site for isoleucine using selection-amplification (SELEX), by shrinking the size of the randomized region until affinity selection is extinguished. Such a protocol can be useful because selection does not necessarily make the simplest active motif most prominent, as is often assumed. We find an isoleucine binding site that behaves exactly as predicted for the site that requires fewest nucleotides. This UAUU motif (16 highly conserved positions; 27 total), is also the most abundant site in successful selections on short random tracts. The UAUU site, now isolated independently at least 63 times, is a small asymmetric internal loop. Conserved loop sequences include isoleucine codon and anticodon triplets, whose nucleotides are required for amino acid binding. This reproducible association between isoleucine and its coding sequences supports the idea that the genetic code is, at least in part, a stereochemical residue of the most easily isolated RNA–amino acid binding structures. PMID:14561881

SVM prediction of ligand-binding sites in bacterial lipoproteins employing shape and physio-chemical descriptors.

PubMed

Kadam, Kiran; Prabhakar, Prashant; Jayaraman, V K

2012-11-01

Bacterial lipoproteins play critical roles in various physiological processes including the maintenance of pathogenicity and numbers of them are being considered as potential candidates for generating novel vaccines. In this work, we put forth an algorithm to identify and predict ligand-binding sites in bacterial lipoproteins. The method uses three types of pocket descriptors, namely fpocket descriptors, 3D Zernike descriptors and shell descriptors, and combines them with Support Vector Machine (SVM) method for the classification. The three types of descriptors represent shape-based properties of the pocket as well as its local physio-chemical features. All three types of descriptors, along with their hybrid combinations are evaluated with SVM and to improve classification performance, WEKA-InfoGain feature selection is applied. Results obtained in the study show that the classifier successfully differentiates between ligand-binding and non-binding pockets. For the combination of three types of descriptors, 10 fold cross-validation accuracy of 86.83% is obtained for training while the selected model achieved test Matthews Correlation Coefficient (MCC) of 0.534. Individually or in combination with new and existing methods, our model can be a very useful tool for the prediction of potential ligand-binding sites in bacterial lipoproteins.

Informative priors based on transcription factor structural class improve de novo motif discovery.

PubMed

Narlikar, Leelavati; Gordân, Raluca; Ohler, Uwe; Hartemink, Alexander J

2006-07-15

An important problem in molecular biology is to identify the locations at which a transcription factor (TF) binds to DNA, given a set of DNA sequences believed to be bound by that TF. In previous work, we showed that information in the DNA sequence of a binding site is sufficient to predict the structural class of the TF that binds it. In particular, this suggests that we can predict which locations in any DNA sequence are more likely to be bound by certain classes of TFs than others. Here, we argue that traditional methods for de novo motif finding can be significantly improved by adopting an informative prior probability that a TF binding site occurs at each sequence location. To demonstrate the utility of such an approach, we present priority, a powerful new de novo motif finding algorithm. Using data from TRANSFAC, we train three classifiers to recognize binding sites of basic leucine zipper, forkhead, and basic helix loop helix TFs. These classifiers are used to equip priority with three class-specific priors, in addition to a default prior to handle TFs of other classes. We apply priority and a number of popular motif finding programs to sets of yeast intergenic regions that are reported by ChIP-chip to be bound by particular TFs. priority identifies motifs the other methods fail to identify, and correctly predicts the structural class of the TF recognizing the identified binding sites. Supplementary material and code can be found at http://www.cs.duke.edu/~amink/.

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

Predicting Nonspecific Ion Binding Using DelPhi

PubMed Central

Petukh, Marharyta; Zhenirovskyy, Maxim; Li, Chuan; Li, Lin; Wang, Lin; Alexov, Emil

2012-01-01

Ions are an important component of the cell and affect the corresponding biological macromolecules either via direct binding or as a screening ion cloud. Although some ion binding is highly specific and frequently associated with the function of the macromolecule, other ions bind to the protein surface nonspecifically, presumably because the electrostatic attraction is strong enough to immobilize them. Here, we test such a scenario and demonstrate that experimentally identified surface-bound ions are located at a potential that facilitates binding, which indicates that the major driving force is the electrostatics. Without taking into consideration geometrical factors and structural fluctuations, we show that ions tend to be bound onto the protein surface at positions with strong potential but with polarity opposite to that of the ion. This observation is used to develop a method that uses a DelPhi-calculated potential map in conjunction with an in-house-developed clustering algorithm to predict nonspecific ion-binding sites. Although this approach distinguishes only the polarity of the ions, and not their chemical nature, it can predict nonspecific binding of positively or negatively charged ions with acceptable accuracy. One can use the predictions in the Poisson-Boltzmann approach by placing explicit ions in the predicted positions, which in turn will reduce the magnitude of the local potential and extend the limits of the Poisson-Boltzmann equation. In addition, one can use this approach to place the desired number of ions before conducting molecular-dynamics simulations to neutralize the net charge of the protein, because it was shown to perform better than standard screened Coulomb canned routines, or to predict ion-binding sites in proteins. This latter is especially true for proteins that are involved in ion transport, because such ions are loosely bound and very difficult to detect experimentally. PMID:22735539

CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction.

PubMed

Xu, Youjun; Wang, Shiwei; Hu, Qiwan; Gao, Shuaishi; Ma, Xiaomin; Zhang, Weilin; Shen, Yihang; Chen, Fangjin; Lai, Luhua; Pei, Jianfeng

2018-05-10

CavityPlus is a web server that offers protein cavity detection and various functional analyses. Using protein three-dimensional structural information as the input, CavityPlus applies CAVITY to detect potential binding sites on the surface of a given protein structure and rank them based on ligandability and druggability scores. These potential binding sites can be further analysed using three submodules, CavPharmer, CorrSite, and CovCys. CavPharmer uses a receptor-based pharmacophore modelling program, Pocket, to automatically extract pharmacophore features within cavities. CorrSite identifies potential allosteric ligand-binding sites based on motion correlation analyses between cavities. CovCys automatically detects druggable cysteine residues, which is especially useful to identify novel binding sites for designing covalent allosteric ligands. Overall, CavityPlus provides an integrated platform for analysing comprehensive properties of protein binding cavities. Such analyses are useful for many aspects of drug design and discovery, including target selection and identification, virtual screening, de novo drug design, and allosteric and covalent-binding drug design. The CavityPlus web server is freely available at http://repharma.pku.edu.cn/cavityplus or http://www.pkumdl.cn/cavityplus.

Systematic optimization model and algorithm for binding sequence selection in computational enzyme design

PubMed Central

Huang, Xiaoqiang; Han, Kehang; Zhu, Yushan

2013-01-01

A systematic optimization model for binding sequence selection in computational enzyme design was developed based on the transition state theory of enzyme catalysis and graph-theoretical modeling. The saddle point on the free energy surface of the reaction system was represented by catalytic geometrical constraints, and the binding energy between the active site and transition state was minimized to reduce the activation energy barrier. The resulting hyperscale combinatorial optimization problem was tackled using a novel heuristic global optimization algorithm, which was inspired and tested by the protein core sequence selection problem. The sequence recapitulation tests on native active sites for two enzyme catalyzed hydrolytic reactions were applied to evaluate the predictive power of the design methodology. The results of the calculation show that most of the native binding sites can be successfully identified if the catalytic geometrical constraints and the structural motifs of the substrate are taken into account. Reliably predicting active site sequences may have significant implications for the creation of novel enzymes that are capable of catalyzing targeted chemical reactions. PMID:23649589

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

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.

Target-mediated drug disposition model for drugs with two binding sites that bind to a target with one binding site.

PubMed

Gibiansky, Leonid; Gibiansky, Ekaterina

2017-10-01

The paper extended the TMDD model to drugs with two identical binding sites (2-1 TMDD). The quasi-steady-state (2-1 QSS), quasi-equilibrium (2-1 QE), irreversible binding (2-1 IB), and Michaelis-Menten (2-1 MM) approximations of the model were derived. Using simulations, the 2-1 QSS approximation was compared with the full 2-1 TMDD model. As expected and similarly to the standard TMDD for monoclonal antibodies (mAb), 2-1 QSS predictions were nearly identical to 2-1 TMDD predictions, except for times of fast changes following initiation of dosing, when equilibrium has not yet been reached. To illustrate properties of new equations and approximations, several variations of population PK data for mAbs with soluble (slow elimination of the complex) or membrane-bound (fast elimination of the complex) targets were simulated from a full 2-1 TMDD model and fitted to 2-1 TMDD models, to its approximations, and to the standard (1-1) QSS model. For a mAb with a soluble target, it was demonstrated that the 2-1 QSS model provided nearly identical description of the observed (simulated) free drug and total target concentrations, although there was some minor bias in predictions of unobserved free target concentrations. The standard QSS approximation also provided a good description of the observed data, but was not able to distinguish between free drug concentrations (with no target attached and both binding site free) and partially bound drug concentrations (with one of the binding sites occupied by the target). For a mAb with a membrane-bound target, the 2-1 MM approximation adequately described the data. The 2-1 QSS approximation converged 10 times faster than the full 2-1 TMDD, and its run time was comparable with the standard QSS model.

The epitope of monoclonal antibodies blocking erythrocyte invasion by Plasmodium falciparum map to the dimerization and receptor glycan binding sites of EBA-175.

PubMed

Ambroggio, Xavier; Jiang, Lubin; Aebig, Joan; Obiakor, Harold; Lukszo, Jan; Narum, David L

2013-01-01

The malaria parasite, Plasmodium falciparum, and related parasites use a variety of proteins with Duffy-Binding Like (DBL) domains to bind glycoproteins on the surface of host cells. Among these proteins, the 175 kDa erythrocyte binding antigen, EBA-175, specifically binds to glycophorin A on the surface of human erythrocytes during the process of merozoite invasion. The domain responsible for glycophorin A binding was identified as region II (RII) which contains two DBL domains, F1 and F2. The crystal structure of this region revealed a dimer that is presumed to represent the glycophorin A binding conformation as sialic acid binding sites and large cavities are observed at the dimer interface. The dimer interface is largely composed of two loops from within each monomer, identified as the F1 and F2 β-fingers that contact depressions in the opposing monomers in a similar manner. Previous studies have identified a panel of five monoclonal antibodies (mAbs) termed R215 to R218 and R256 that bind to RII and inhibit invasion of erythrocytes to varying extents. In this study, we predict the F2 β-finger region as the conformational epitope for mAbs, R215, R217, and R256, and confirm binding for the most effective blocking mAb R217 and R215 to a synthetic peptide mimic of the F2 β-finger. Localization of the epitope to the dimerization and glycan binding sites of EBA-175 RII and site-directed mutagenesis within the predicted epitope are consistent with R215 and R217 blocking erythrocyte invasion by Plasmodium falciparum by preventing formation of the EBA-175- glycophorin A complex.

Prediction and Dissection of Protein-RNA Interactions by Molecular Descriptors.

PubMed

Liu, Zhi-Ping; Chen, Luonan

2016-01-01

Protein-RNA interactions play crucial roles in numerous biological processes. However, detecting the interactions and binding sites between protein and RNA by traditional experiments is still time consuming and labor costing. Thus, it is of importance to develop bioinformatics methods for predicting protein-RNA interactions and binding sites. Accurate prediction of protein-RNA interactions and recognitions will highly benefit to decipher the interaction mechanisms between protein and RNA, as well as to improve the RNA-related protein engineering and drug design. In this work, we summarize the current bioinformatics strategies of predicting protein-RNA interactions and dissecting protein-RNA interaction mechanisms from local structure binding motifs. In particular, we focus on the feature-based machine learning methods, in which the molecular descriptors of protein and RNA are extracted and integrated as feature vectors of representing the interaction events and recognition residues. In addition, the available methods are classified and compared comprehensively. The molecular descriptors are expected to elucidate the binding mechanisms of protein-RNA interaction and reveal the functional implications from structural complementary perspective.

An efficient method to transcription factor binding sites imputation via simultaneous completion of multiple matrices with positional consistency.

PubMed

Guo, Wei-Li; Huang, De-Shuang

2017-08-22

Transcription factors (TFs) are DNA-binding proteins that have a central role in regulating gene expression. Identification of DNA-binding sites of TFs is a key task in understanding transcriptional regulation, cellular processes and disease. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) enables genome-wide identification of in vivo TF binding sites. However, it is still difficult to map every TF in every cell line owing to cost and biological material availability, which poses an enormous obstacle for integrated analysis of gene regulation. To address this problem, we propose a novel computational approach, TFBSImpute, for predicting additional TF binding profiles by leveraging information from available ChIP-seq TF binding data. TFBSImpute fuses the dataset to a 3-mode tensor and imputes missing TF binding signals via simultaneous completion of multiple TF binding matrices with positional consistency. We show that signals predicted by our method achieve overall similarity with experimental data and that TFBSImpute significantly outperforms baseline approaches, by assessing the performance of imputation methods against observed ChIP-seq TF binding profiles. Besides, motif analysis shows that TFBSImpute preforms better in capturing binding motifs enriched in observed data compared with baselines, indicating that the higher performance of TFBSImpute is not simply due to averaging related samples. We anticipate that our approach will constitute a useful complement to experimental mapping of TF binding, which is beneficial for further study of regulation mechanisms and disease.

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

Electrostatic Interactions Mediate Binding of Obscurin to Small Ankyrin 1: Biochemical and Molecular Modeling Studies

PubMed Central

Busby, Ben; Oashi, Taiji; Willis, Chris D.; Ackermann, Maegen A.; Kontrogianni-Konstantopoulos, Aikaterini; MacKerell, Alexander D.; Bloch, Robert J.

2012-01-01

Small ankyrin 1 (sAnk1; also Ank1.5) is an integral protein of the sarcoplasmic reticulum in skeletal and cardiac muscle cells, where it is thought to bind to the C-terminal region of obscurin, a large modular protein that surrounds the contractile apparatus. Using fusion proteins in vitro, in combination with site directed mutagenesis and surface plasmon resonance measurements, we previously showed that the binding site on sAnk1 for obscurin consists in part of six lysine and arginine residues. Here we show that four charged residues in the high affinity binding site on obscurin for sAnk1, between residues 6316-6345, consisting of three glutamates and a lysine, are necessary, but not sufficient, for this site on obscurin to bind with high affinity to sAnk1. We also identify specific complementary mutations in sAnk1 that can partially or completely compensate for the changes in binding caused by charge-switching mutations in obscurin. We used molecular modeling to develop structural models of residues 6322-6339 of obscurin bound to sAnk1. The models, based on a combination of Brownian and molecular dynamics simulations, predict that the binding site on sAnk1 for obscurin is organized as two ankyrin-like repeats, with the last α-helical segment oriented at an angle to the nearby helices, allowing lysine-6338 of obscurin to form an ionic interaction with aspartate-111 of sAnk1. This prediction was validated by double mutant cycle experiments. Our results are consistent with a model in which electrostatic interactions between specific pairs of side chains on obscurin and sAnk1 promote binding and complex formation. PMID:21333652

Structural insights into conserved L-arabinose metabolic enzymes reveal the substrate binding site of a thermophilic L-arabinose isomerase.

PubMed

Lee, Yong-Jik; Lee, Sang-Jae; Kim, Seong-Bo; Lee, Sang Jun; Lee, Sung Haeng; Lee, Dong-Woo

2014-03-18

Structural genomics demonstrates that despite low levels of structural similarity of proteins comprising a metabolic pathway, their substrate binding regions are likely to be conserved. Herein based on the 3D-structures of the α/β-fold proteins involved in the ara operon, we attempted to predict the substrate binding residues of thermophilic Geobacillus stearothermophilus L-arabinose isomerase (GSAI) with no 3D-structure available. Comparison of the structures of L-arabinose catabolic enzymes revealed a conserved feature to form the substrate-binding modules, which can be extended to predict the substrate binding site of GSAI (i.e., D195, E261 and E333). Moreover, these data implicated that proteins in the l-arabinose metabolic pathway might retain their substrate binding niches as the modular structure through conserved molecular evolution even with totally different structural scaffolds. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

De-novo discovery of differentially abundant transcription factor binding sites including their positional preference.

PubMed

Keilwagen, Jens; Grau, Jan; Paponov, Ivan A; Posch, Stefan; Strickert, Marc; Grosse, Ivo

2011-02-10

Transcription factors are a main component of gene regulation as they activate or repress gene expression by binding to specific binding sites in promoters. The de-novo discovery of transcription factor binding sites in target regions obtained by wet-lab experiments is a challenging problem in computational biology, which has not been fully solved yet. Here, we present a de-novo motif discovery tool called Dispom for finding differentially abundant transcription factor binding sites that models existing positional preferences of binding sites and adjusts the length of the motif in the learning process. Evaluating Dispom, we find that its prediction performance is superior to existing tools for de-novo motif discovery for 18 benchmark data sets with planted binding sites, and for a metazoan compendium based on experimental data from micro-array, ChIP-chip, ChIP-DSL, and DamID as well as Gene Ontology data. Finally, we apply Dispom to find binding sites differentially abundant in promoters of auxin-responsive genes extracted from Arabidopsis thaliana microarray data, and we find a motif that can be interpreted as a refined auxin responsive element predominately positioned in the 250-bp region upstream of the transcription start site. Using an independent data set of auxin-responsive genes, we find in genome-wide predictions that the refined motif is more specific for auxin-responsive genes than the canonical auxin-responsive element. In general, Dispom can be used to find differentially abundant motifs in sequences of any origin. However, the positional distribution learned by Dispom is especially beneficial if all sequences are aligned to some anchor point like the transcription start site in case of promoter sequences. We demonstrate that the combination of searching for differentially abundant motifs and inferring a position distribution from the data is beneficial for de-novo motif discovery. Hence, we make the tool freely available as a component of the open-source Java framework Jstacs and as a stand-alone application at http://www.jstacs.de/index.php/Dispom.

Computational analysis of EBNA1 ``druggability'' suggests novel insights for Epstein-Barr virus inhibitor design

NASA Astrophysics Data System (ADS)

Gianti, Eleonora; Messick, Troy E.; Lieberman, Paul M.; Zauhar, Randy J.

2016-04-01

The Epstein-Barr Nuclear Antigen 1 (EBNA1) is a critical protein encoded by the Epstein-Barr Virus (EBV). During latent infection, EBNA1 is essential for DNA replication and transcription initiation of viral and cellular genes and is necessary to immortalize primary B-lymphocytes. Nonetheless, the concept of EBNA1 as drug target is novel. Two EBNA1 crystal structures are publicly available and the first small-molecule EBNA1 inhibitors were recently discovered. However, no systematic studies have been reported on the structural details of EBNA1 "druggable" binding sites. We conducted computational identification and structural characterization of EBNA1 binding pockets, likely to accommodate ligand molecules (i.e. "druggable" binding sites). Then, we validated our predictions by docking against a set of compounds previously tested in vitro for EBNA1 inhibition (PubChem AID-2381). Finally, we supported assessments of pocket druggability by performing induced fit docking and molecular dynamics simulations paired with binding affinity predictions by Molecular Mechanics Generalized Born Surface Area calculations for a number of hits belonging to druggable binding sites. Our results establish EBNA1 as a target for drug discovery, and provide the computational evidence that active AID-2381 hits disrupt EBNA1:DNA binding upon interacting at individual sites. Lastly, structural properties of top scoring hits are proposed to support the rational design of the next generation of EBNA1 inhibitors.

The Role of miRNAs in the Progression of Prostate Cancer from Androgen-Dependent to Androgen-Independent Stages

DTIC Science & Technology

2012-09-01

regulated by miR-99a/let7c/125b-2 cluster. Using bioinformatic prediction algorithm TargetScan, we identified 7 genes that are commonly targeted by miR-99a...HPeak, a Hidden Markov Model (HMM)-based peak identifying algorithm (http://www.sph.umich.edu/csg/qin/HPeak/). Seven AR binding sites were reported by...and ARBS2 by ALGGEN- PROMO, a matrix algorithm for predicting transcription factor binding sites based on TRANSFAC (http://alggen.lsi.upc.es/cgi- bin

DNA breathing dynamics distinguish binding from nonbinding consensus sites for transcription factor YY1 in cells.

PubMed

Alexandrov, Boian S; Fukuyo, Yayoi; Lange, Martin; Horikoshi, Nobuo; Gelev, Vladimir; Rasmussen, Kim Ø; Bishop, Alan R; Usheva, Anny

2012-11-01

The genome-wide mapping of the major gene expression regulators, the transcription factors (TFs) and their DNA binding sites, is of great importance for describing cellular behavior and phenotypic diversity. Presently, the methods for prediction of genomic TF binding produce a large number of false positives, most likely due to insufficient description of the physiochemical mechanisms of protein-DNA binding. Growing evidence suggests that, in the cell, the double-stranded DNA (dsDNA) is subject to local transient strands separations (breathing) that contribute to genomic functions. By using site-specific chromatin immunopecipitations, gel shifts, BIOBASE data, and our model that accurately describes the melting behavior and breathing dynamics of dsDNA we report a specific DNA breathing profile found at YY1 binding sites in cells. We find that the genomic flanking sequence variations and SNPs, may exert long-range effects on DNA dynamics and predetermine YY1 binding. The ubiquitous TF YY1 has a fundamental role in essential biological processes by activating, initiating or repressing transcription depending upon the sequence context it binds. We anticipate that consensus binding sequences together with the related DNA dynamics profile may significantly improve the accuracy of genomic TF binding sites and TF binding-related functional SNPs.

Homology modeling, binding site identification and docking study of human angiotensin II type I (Ang II-AT1) receptor.

PubMed

Vyas, Vivek K; Ghate, Manjunath; Patel, Kinjal; Qureshi, Gulamnizami; Shah, Surmil

2015-08-01

Ang II-AT1 receptors play an important role in mediating virtually all of the physiological actions of Ang II. Several drugs (SARTANs) are available, which can block the AT1 receptor effectively and lower the blood pressure in the patients with hypertension. Currently, there is no experimental Ang II-AT1 structure available; therefore, in this study we modeled Ang II-AT1 receptor structure using homology modeling followed by identification and characterization of binding sites and thereby assessing druggability of the receptor. Homology models were constructed using MODELLER and I-TASSER server, refined and validated using PROCHECK in which 96.9% of 318 residues were present in the favoured regions of the Ramachandran plots. Various Ang II-AT1 receptor antagonist drugs are available in the market as antihypertensive drug, so we have performed docking study with the binding site prediction algorithms to predict different binding pockets on the modeled proteins. The identification of 3D structures and binding sites for various known drugs will guide us for the structure-based drug design of novel compounds as Ang II-AT1 receptor antagonists for the treatment of hypertension. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Pyrrole-Based Antitubulin Agents: Two Distinct Binding Modalities Are Predicted for C-2 Analogues in the Colchicine Site

PubMed Central

2011-01-01

3,5-Dibromo-4-(3,4-dimethoxyphenyl)-1H-pyrrole-2-carboxylic acid ethyl ester is a promising antitubulin lead agent that targets the colchicine site of tubulin. C-2 analogues were synthesized and tested for microtubule depolymerizing and antiproliferative activity. Molecular modeling studies using both GOLD docking and HINT (Hydropathic INTeraction) scoring revealed two distinct binding modes that explain the structure–activity relationships and are in accord with the structural basis of colchicine binding to tubulin. The binding mode of higher activity compounds is buried deeper in the site and overlaps well with rings A and C of colchicine, while the lower activity binding mode shows fewer critical contacts with tubulin. The model distinguishes highly active compounds from those with weaker activities and provides novel insights into the colchicine site and compound design. PMID:22611477

Pyrrole-Based Antitubulin Agents: Two Distinct Binding Modalities are Predicted for C-2 Analogs in the Colchicine Site.

PubMed

Da, Chenxiao; Telang, Nakul; Barelli, Peter; Jia, Xin; Gupton, John T; Mooberry, Susan L; Kellogg, Glen E

2012-01-12

3,5-dibromo-4-(3,4-dimethoxyphenyl)-1H-pyrrole-2-carboxylic acid ethyl ester is a promising antitubulin lead agent that targets the colchicine site of tubulin. C-2 analogs were synthesized and tested for microtubule depolymerizing and antiproliferative activity. Molecular modeling studies using both GOLD docking and HINT (Hydropathic INTeraction) scoring revealed two distinct binding modes that explain the structural-activity relationships and are in accord with the structural basis of colchicine binding to tubulin. The binding mode of higher activity compounds is buried deeper in the site and overlaps well with rings A and C of colchicine, while the lower activity binding mode shows fewer critical contacts with tubulin. The model distinguishes highly active compounds from those with weaker activities and provides novel insights into the colchicine site and compound design.

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.

The Role of Genome Accessibility in Transcription Factor Binding in Bacteria.

PubMed

Gomes, Antonio L C; Wang, Harris H

2016-04-01

ChIP-seq enables genome-scale identification of regulatory regions that govern gene expression. However, the biological insights generated from ChIP-seq analysis have been limited to predictions of binding sites and cooperative interactions. Furthermore, ChIP-seq data often poorly correlate with in vitro measurements or predicted motifs, highlighting that binding affinity alone is insufficient to explain transcription factor (TF)-binding in vivo. One possibility is that binding sites are not equally accessible across the genome. A more comprehensive biophysical representation of TF-binding is required to improve our ability to understand, predict, and alter gene expression. Here, we show that genome accessibility is a key parameter that impacts TF-binding in bacteria. We developed a thermodynamic model that parameterizes ChIP-seq coverage in terms of genome accessibility and binding affinity. The role of genome accessibility is validated using a large-scale ChIP-seq dataset of the M. tuberculosis regulatory network. We find that accounting for genome accessibility led to a model that explains 63% of the ChIP-seq profile variance, while a model based in motif score alone explains only 35% of the variance. Moreover, our framework enables de novo ChIP-seq peak prediction and is useful for inferring TF-binding peaks in new experimental conditions by reducing the need for additional experiments. We observe that the genome is more accessible in intergenic regions, and that increased accessibility is positively correlated with gene expression and anti-correlated with distance to the origin of replication. Our biophysically motivated model provides a more comprehensive description of TF-binding in vivo from first principles towards a better representation of gene regulation in silico, with promising applications in systems biology.

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

Modeling Shear Induced Von Willebrand Factor Binding to Collagen

NASA Astrophysics Data System (ADS)

Dong, Chuqiao; Wei, Wei; Morabito, Michael; Webb, Edmund; Oztekin, Alparslan; Zhang, Xiaohui; Cheng, Xuanhong

2017-11-01

Von Willebrand factor (vWF) is a blood glycoprotein that binds with platelets and collagen on injured vessel surfaces to form clots. VWF bioactivity is shear flow induced: at low shear, binding between VWF and other biological entities is suppressed; for high shear rate conditions - as are found near arterial injury sites - VWF elongates, activating its binding with platelets and collagen. Based on parameters derived from single molecule force spectroscopy experiments, we developed a coarse-grain molecular model to simulate bond formation probability as a function of shear rate. By introducing a binding criterion that depends on the conformation of a sub-monomer molecular feature of our model, the model predicts shear-induced binding, even for conditions where binding is highly energetically favorable. We further investigate the influence of various model parameters on the ability to predict shear-induced binding (vWF length, collagen site density and distribution, binding energy landscape, and slip/catch bond length) and demonstrate parameter ranges where the model provides good agreement with existing experimental data. Our results may be important for understanding vWF activity and also for achieving targeted drug therapy via biomimetic synthetic molecules. National Science Foundation (NSF),Division of Mathematical Sciences (DMS).

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 .

An improved ChIP-seq peak detection system for simultaneously identifying post-translational modified transcription factors by combinatorial fusion, using SUMOylation as an example.

PubMed

Cheng, Chia-Yang; Chu, Chia-Han; Hsu, Hung-Wei; Hsu, Fang-Rong; Tang, Chung Yi; Wang, Wen-Ching; Kung, Hsing-Jien; Chang, Pei-Ching

2014-01-01

Post-translational modification (PTM) of transcriptional factors and chromatin remodelling proteins is recognized as a major mechanism by which transcriptional regulation occurs. Chromatin immunoprecipitation (ChIP) in combination with high-throughput sequencing (ChIP-seq) is being applied as a gold standard when studying the genome-wide binding sites of transcription factor (TFs). This has greatly improved our understanding of protein-DNA interactions on a genomic-wide scale. However, current ChIP-seq peak calling tools are not sufficiently sensitive and are unable to simultaneously identify post-translational modified TFs based on ChIP-seq analysis; this is largely due to the wide-spread presence of multiple modified TFs. Using SUMO-1 modification as an example; we describe here an improved approach that allows the simultaneous identification of the particular genomic binding regions of all TFs with SUMO-1 modification. Traditional peak calling methods are inadequate when identifying multiple TF binding sites that involve long genomic regions and therefore we designed a ChIP-seq processing pipeline for the detection of peaks via a combinatorial fusion method. Then, we annotate the peaks with known transcription factor binding sites (TFBS) using the Transfac Matrix Database (v7.0), which predicts potential SUMOylated TFs. Next, the peak calling result was further analyzed based on the promoter proximity, TFBS annotation, a literature review, and was validated by ChIP-real-time quantitative PCR (qPCR) and ChIP-reChIP real-time qPCR. The results show clearly that SUMOylated TFs are able to be pinpointed using our pipeline. A methodology is presented that analyzes SUMO-1 ChIP-seq patterns and predicts related TFs. Our analysis uses three peak calling tools. The fusion of these different tools increases the precision of the peak calling results. TFBS annotation method is able to predict potential SUMOylated TFs. Here, we offer a new approach that enhances ChIP-seq data analysis and allows the identification of multiple SUMOylated TF binding sites simultaneously, which can then be utilized for other functional PTM binding site prediction in future.

Genome-wide Expression Profiling, In Vivo DNA Binding Analysis, and Probabilistic Motif Prediction Reveal Novel Abf1 Target Genes during Fermentation, Respiration, and Sporulation in Yeast

PubMed Central

Schlecht, Ulrich; Erb, Ionas; Demougin, Philippe; Robine, Nicolas; Borde, Valérie; van Nimwegen, Erik; Nicolas, Alain

2008-01-01

The autonomously replicating sequence binding factor 1 (Abf1) was initially identified as an essential DNA replication factor and later shown to be a component of the regulatory network controlling mitotic and meiotic cell cycle progression in budding yeast. The protein is thought to exert its functions via specific interaction with its target site as part of distinct protein complexes, but its roles during mitotic growth and meiotic development are only partially understood. Here, we report a comprehensive approach aiming at the identification of direct Abf1-target genes expressed during fermentation, respiration, and sporulation. Computational prediction of the protein's target sites was integrated with a genome-wide DNA binding assay in growing and sporulating cells. The resulting data were combined with the output of expression profiling studies using wild-type versus temperature-sensitive alleles. This work identified 434 protein-coding loci as being transcriptionally dependent on Abf1. More than 60% of their putative promoter regions contained a computationally predicted Abf1 binding site and/or were bound by Abf1 in vivo, identifying them as direct targets. The present study revealed numerous loci previously unknown to be under Abf1 control, and it yielded evidence for the protein's variable DNA binding pattern during mitotic growth and meiotic development. PMID:18305101

The bacterial dicarboxylate transporter, VcINDY, uses a two-domain elevator-type mechanism

PubMed Central

Mulligan, Christopher; Fenollar-Ferrer, Cristina; Fitzgerald, Gabriel A.; Vergara-Jaque, Ariela; Kaufmann, Desirée; Li, Yan; Forrest, Lucy R.; Mindell, Joseph A.

2016-01-01

Secondary transporters use alternating access mechanisms to couple uphill substrate movement to downhill ion flux. Most known transporters utilize a “rocking bundle” motion, where the protein moves around an immobile substrate binding site. However, the glutamate transporter homolog, GltPh, translocates its substrate binding site vertically across the membrane, an “elevator” mechanism. Here, we used the “repeat swap” approach to computationally predict the outward-facing state of the Na+/succinate transporter VcINDY, from Vibrio cholerae. Our model predicts a substantial “elevator”-like movement of vcINDY’s substrate binding site, with a vertical translation of ~15 Å and a rotation of ~43°; multiple disulfide crosslinks which completely inhibit transport provide experimental confirmation and demonstrate that such movement is essential. In contrast, crosslinks across the VcINDY dimer interface preserve transport, revealing an absence of large scale coupling between protomers. PMID:26828963

Structural analysis of peptides that fill sites near the active center of the two different enzyme molecules by artificial intelligence and computer simulations

NASA Astrophysics Data System (ADS)

Nishiyama, Katsuhiko

2018-05-01

Using artificial intelligence, the binding styles of 167 tetrapeptides were predicted in the active site of papain and cathepsin K. Five tetrapeptides (Asn-Leu-Lys-Trp, Asp-Gln-Trp-Gly, Cys-Gln-Leu-Arg, Gln-Leu-Trp-Thr and Arg-Ser-Glu-Arg) were found to bind sites near the active center of both papain and cathepsin K. These five tetrapeptides have the potential to also bind sites of other cysteine proteases, and structural characteristics of these tetrapeptides should aid the design of a common inhibitor of cysteine proteases. Smart application of artificial intelligence should accelerate data mining of important complex systems.

Interaction of E. coli outer-membrane protein A with sugars on the receptors of the brain microvascular endothelial cells.

PubMed

Datta, Deepshikha; Vaidehi, Nagarajan; Floriano, Wely B; Kim, Kwang S; Prasadarao, Nemani V; Goddard, William A

2003-02-01

Esherichia coli, the most common gram-negative bacteria, can penetrate the brain microvascular endothelial cells (BMECs) during the neonatal period to cause meningitis with significant morbidity and mortality. Experimental studies have shown that outer-membrane protein A (OmpA) of E. coli plays a key role in the initial steps of the invasion process by binding to specific sugar moieties present on the glycoproteins of BMEC. These experiments also show that polymers of chitobiose (GlcNAcbeta1-4GlcNAc) block the invasion, while epitopes substituted with the L-fucosyl group do not. We used HierDock computational technique that consists of a hierarchy of coarse grain docking method with molecular dynamics (MD) to predict the binding sites and energies of interactions of GlcNAcbeta1-4GlcNAc and other sugars with OmpA. The results suggest two important binding sites for the interaction of carbohydrate epitopes of BMEC glycoproteins to OmpA. We identify one site as the binding pocket for chitobiose (GlcNAcbeta1-4GlcNAc) in OmpA, while the second region (including loops 1 and 2) may be important for recognition of specific sugars. We find that the site involving loops 1 and 2 has relative binding energies that correlate well with experimental observations. This theoretical study elucidates the interaction sites of chitobiose with OmpA and the binding site predictions made in this article are testable either by mutation studies or invasion assays. These results can be further extended in suggesting possible peptide antagonists and drug design for therapeutic strategies. Copyright 2002 Wiley-Liss, Inc.

miRWalk--database: prediction of possible miRNA binding sites by "walking" the genes of three genomes.

PubMed

Dweep, Harsh; Sticht, Carsten; Pandey, Priyanka; Gretz, Norbert

2011-10-01

MicroRNAs are small, non-coding RNA molecules that can complementarily bind to the mRNA 3'-UTR region to regulate the gene expression by transcriptional repression or induction of mRNA degradation. Increasing evidence suggests a new mechanism by which miRNAs may regulate target gene expression by binding in promoter and amino acid coding regions. Most of the existing databases on miRNAs are restricted to mRNA 3'-UTR region. To address this issue, we present miRWalk, a comprehensive database on miRNAs, which hosts predicted as well as validated miRNA binding sites, information on all known genes of human, mouse and rat. All mRNAs, mitochondrial genes and 10 kb upstream flanking regions of all known genes of human, mouse and rat were analyzed by using a newly developed algorithm named 'miRWalk' as well as with eight already established programs for putative miRNA binding sites. An automated and extensive text-mining search was performed on PubMed database to extract validated information on miRNAs. Combined information was put into a MySQL database. miRWalk presents predicted and validated information on miRNA-target interaction. Such a resource enables researchers to validate new targets of miRNA not only on 3'-UTR, but also on the other regions of all known genes. The 'Validated Target module' is updated every month and the 'Predicted Target module' is updated every 6 months. miRWalk is freely available at http://mirwalk.uni-hd.de/. Copyright © 2011 Elsevier Inc. All rights reserved.

The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

PubMed

Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

2011-07-01

The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

Exploiting three kinds of interface propensities to identify protein binding sites.

PubMed

Liu, Bin; Wang, Xiaolong; Lin, Lei; Dong, Qiwen; Wang, Xuan

2009-08-01

Predicting the binding sites between two interacting proteins provides important clues to the function of a protein. In this study, we present a building block of proteins called order profiles to use the evolutionary information of the protein sequence frequency profiles and apply this building block to produce a class of propensities called order profile interface propensities. For comparisons, we revisit the usage of residue interface propensities and binary profile interface propensities for protein binding site prediction. Each kind of propensities combined with sequence profiles and accessible surface areas are inputted into SVM. When tested on four types of complexes (hetero-permanent complexes, hetero-transient complexes, homo-permanent complexes and homo-transient complexes), experimental results show that the order profile interface propensities are better than residue interface propensities and binary profile interface propensities. Therefore, order profile is a suitable profile-level building block of the protein sequences and can be widely used in many tasks of computational biology, such as the sequence alignment, the prediction of domain boundary, the designation of knowledge-based potentials and the protein remote homology detection.

SNP2TFBS - a database of regulatory SNPs affecting predicted transcription factor binding site affinity.

PubMed

Kumar, Sunil; Ambrosini, Giovanna; Bucher, Philipp

2017-01-04

SNP2TFBS is a computational resource intended to support researchers investigating the molecular mechanisms underlying regulatory variation in the human genome. The database essentially consists of a collection of text files providing specific annotations for human single nucleotide polymorphisms (SNPs), namely whether they are predicted to abolish, create or change the affinity of one or several transcription factor (TF) binding sites. A SNP's effect on TF binding is estimated based on a position weight matrix (PWM) model for the binding specificity of the corresponding factor. These data files are regenerated at regular intervals by an automatic procedure that takes as input a reference genome, a comprehensive SNP catalogue and a collection of PWMs. SNP2TFBS is also accessible over a web interface, enabling users to view the information provided for an individual SNP, to extract SNPs based on various search criteria, to annotate uploaded sets of SNPs or to display statistics about the frequencies of binding sites affected by selected SNPs. Homepage: http://ccg.vital-it.ch/snp2tfbs/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Strong Ligand-Protein Interactions Derived from Diffuse Ligand Interactions with Loose Binding Sites.

PubMed

Marsh, Lorraine

2015-01-01

Many systems in biology rely on binding of ligands to target proteins in a single high-affinity conformation with a favorable ΔG. Alternatively, interactions of ligands with protein regions that allow diffuse binding, distributed over multiple sites and conformations, can exhibit favorable ΔG because of their higher entropy. Diffuse binding may be biologically important for multidrug transporters and carrier proteins. A fine-grained computational method for numerical integration of total binding ΔG arising from diffuse regional interaction of a ligand in multiple conformations using a Markov Chain Monte Carlo (MCMC) approach is presented. This method yields a metric that quantifies the influence on overall ligand affinity of ligand binding to multiple, distinct sites within a protein binding region. This metric is essentially a measure of dispersion in equilibrium ligand binding and depends on both the number of potential sites of interaction and the distribution of their individual predicted affinities. Analysis of test cases indicates that, for some ligand/protein pairs involving transporters and carrier proteins, diffuse binding contributes greatly to total affinity, whereas in other cases the influence is modest. This approach may be useful for studying situations where "nonspecific" interactions contribute to biological function.

In silico assessment of phosphorylation and O-β-GlcNAcylation sites in human NPC1 protein critical for Ebola virus entry.

PubMed

Basharat, Zarrin; Yasmin, Azra

2015-08-01

Ebola is a highly pathogenic enveloped virus responsible for deadly outbreaks of severe hemorrhagic fever. It enters human cells by binding a multifunctional cholesterol transporter Niemann-Pick C1 (NPC1) protein. Post translational modification (PTM) information for NPC1 is crucial to understand Ebola virus (EBOV) entry and action due to changes in phosphorylation or glycosylation at the binding site. It is difficult and costly to experimentally assess this type of interaction, so in silico strategy was employed. Identification of phosphorylation sites, including conserved residues that could be possible targets for 21 predicted kinases was followed by interplay study between phosphorylation and O-β-GlcNAc modification of NPC1. Results revealed that only 4 out of 48 predicted phosphosites exhibited O-β-GlcNAc activity. Predicted outcomes were integrated with residue conservation and 3D structural information. Three Yin Yang sites were located in the α-helix regions and were conserved in studied vertebrate and mammalian species. Only one modification site S425 was found in β-turn region located near the N-terminus of NPC1 and was found to differ in pig, mouse, cobra and humans. The predictions suggest that Yin Yang sites may not be important for virus attachment to NPC1, whereas phosphosite 473 may be important for binding and hence entry of Ebola virus. This information could be useful in addressing further experimental studies and therapeutic strategies targeting PTM events in EBOV entry. Copyright © 2015 Elsevier B.V. All rights reserved.

Binding ligand prediction for proteins using partial matching of local surface patches.

PubMed

Sael, Lee; Kihara, Daisuke

2010-01-01

Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group.

Binding Ligand Prediction for Proteins Using Partial Matching of Local Surface Patches

PubMed Central

Sael, Lee; Kihara, Daisuke

2010-01-01

Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group. PMID:21614188

pUL34 binding near the human cytomegalovirus origin of lytic replication enhances DNA replication and viral growth.

PubMed

Slayton, Mark; Hossain, Tanvir; Biegalke, Bonita J

2018-05-01

The human cytomegalovirus (HCMV) UL34 gene encodes sequence-specific DNA-binding proteins (pUL34) which are required for viral replication. Interactions of pUL34 with DNA binding sites represses transcription of two viral immune evasion genes, US3 and US9. 12 additional predicted pUL34-binding sites are present in the HCMV genome (strain AD169) with three binding sites concentrated near the HCMV origin of lytic replication (oriLyt). We used ChIP-seq analysis of pUL34-DNA interactions to confirm that pUL34 binds to the oriLyt region during infection. Mutagenesis of the UL34-binding sites in an oriLyt-containing plasmid significantly reduced viral-mediated oriLyt-dependent DNA replication. Mutagenesis of these sites in the HCMV genome reduced the replication efficiencies of the resulting viruses. Protein-protein interaction analyses demonstrated that pUL34 interacts with the viral proteins IE2, UL44, and UL84, that are essential for viral DNA replication, suggesting that pUL34-DNA interactions in the oriLyt region are involved in the DNA replication cascade. Copyright © 2018 Elsevier Inc. All rights reserved.

Fold independent structural comparisons of protein-ligand binding sites for exploring functional relationships.

PubMed

Gold, Nicola D; Jackson, Richard M

2006-02-03

The rapid growth in protein structural data and the emergence of structural genomics projects have increased the need for automatic structure analysis and tools for function prediction. Small molecule recognition is critical to the function of many proteins; therefore, determination of ligand binding site similarity is important for understanding ligand interactions and may allow their functional classification. Here, we present a binding sites database (SitesBase) that given a known protein-ligand binding site allows rapid retrieval of other binding sites with similar structure independent of overall sequence or fold similarity. However, each match is also annotated with sequence similarity and fold information to aid interpretation of structure and functional similarity. Similarity in ligand binding sites can indicate common binding modes and recognition of similar molecules, allowing potential inference of function for an uncharacterised protein or providing additional evidence of common function where sequence or fold similarity is already known. Alternatively, the resource can provide valuable information for detailed studies of molecular recognition including structure-based ligand design and in understanding ligand cross-reactivity. Here, we show examples of atomic similarity between superfamily or more distant fold relatives as well as between seemingly unrelated proteins. Assignment of unclassified proteins to structural superfamiles is also undertaken and in most cases substantiates assignments made using sequence similarity. Correct assignment is also possible where sequence similarity fails to find significant matches, illustrating the potential use of binding site comparisons for newly determined proteins.

Non-competitive inhibition by active site binders.

PubMed

Blat, Yuval

2010-06-01

Classical enzymology has been used for generations to understand the interactions of inhibitors with their enzyme targets. Enzymology tools enabled prediction of the biological impact of inhibitors as well as the development of novel, more potent, ones. Experiments designed to examine the competition between the tested inhibitor and the enzyme substrate(s) are the tool of choice to identify inhibitors that bind in the active site. Competition between an inhibitor and a substrate is considered a strong evidence for binding of the inhibitor in the active site, while the lack of competition suggests binding to an alternative site. Nevertheless, exceptions to this notion do exist. Active site-binding inhibitors can display non-competitive inhibition patterns. This unusual behavior has been observed with enzymes utilizing an exosite for substrate binding, isomechanism enzymes, enzymes with multiple substrates and/or products and two-step binding inhibitors. In many of these cases, the mechanisms underlying the lack of competition between the substrate and the inhibitor are well understood. Tools like alternative substrates, testing the enzyme reaction in the reverse direction and monitoring inhibition time dependence can be applied to enable distinction between 'badly behaving' active site binders and true exosite inhibitors.

Inhibition of cytochrome P450 3A by acetoxylated analogues of resveratrol in in vitro and in silico models

NASA Astrophysics Data System (ADS)

Basheer, Loai; Schultz, Keren; Kerem, Zohar

2016-08-01

Many dietary compounds, including resveratrol, are potent inhibitors of CYP3A4. Here we examined the potential to predict inhibition capacity of dietary polyphenolics using an in silico and in vitro approaches and synthetic model compounds. Mono, di, and tri-acetoxy resveratrol were synthesized, a cell line of human intestine origin and microsomes from rat liver served to determine their in vitro inhibition of CYP3A4, and compared to that of resveratrol. Docking simulation served to predict the affinity of the synthetic model compounds to the enzyme. Modelling of the enzyme’s binding site revealed three types of interaction: hydrophobic, electrostatic and H-bonding. The simulation revealed that each of the examined acetylations of resveratrol led to the loss of important interactions of all types. Tri-acetoxy resveratrol was the weakest inhibitor in vitro despite being the more lipophilic and having the highest affinity for the binding site. The simulation demonstrated exclusion of all interactions between tri-acetoxy resveratrol and the heme due to distal binding, highlighting the complexity of the CYP3A4 binding site, which may allow simultaneous accommodation of two molecules. Finally, the use of computational modelling may serve as a quick predictive tool to identify potential harmful interactions between dietary compounds and prescribed drugs.

Non-B-Form DNA Is Enriched at Centromeres

PubMed Central

Henikoff, Steven

2018-01-01

Abstract Animal and plant centromeres are embedded in repetitive “satellite” DNA, but are thought to be epigenetically specified. To define genetic characteristics of centromeres, we surveyed satellite DNA from diverse eukaryotes and identified variation in <10-bp dyad symmetries predicted to adopt non-B-form conformations. Organisms lacking centromeric dyad symmetries had binding sites for sequence-specific DNA-binding proteins with DNA-bending activity. For example, human and mouse centromeres are depleted for dyad symmetries, but are enriched for non-B-form DNA and are associated with binding sites for the conserved DNA-binding protein CENP-B, which is required for artificial centromere function but is paradoxically nonessential. We also detected dyad symmetries and predicted non-B-form DNA structures at neocentromeres, which form at ectopic loci. We propose that centromeres form at non-B-form DNA because of dyad symmetries or are strengthened by sequence-specific DNA binding proteins. This may resolve the CENP-B paradox and provide a general basis for centromere specification. PMID:29365169

Characterization of the ligand-binding site of the transferrin receptor in Trypanosoma brucei demonstrates a structural relationship with the N-terminal domain of the variant surface glycoprotein.

PubMed

Salmon, D; Hanocq-Quertier, J; Paturiaux-Hanocq, F; Pays, A; Tebabi, P; Nolan, D P; Michel, A; Pays, E

1997-12-15

The Trypanosoma brucei transferrin (Tf) receptor is a heterodimer encoded by ESAG7 and ESAG6, two genes contained in the different polycistronic transcription units of the variant surface glycoprotein (VSG) gene. The sequence of ESAG7/6 differs slightly between different units, so that receptors with different affinities for Tf are expressed alternatively following transcriptional switching of VSG expression sites during antigenic variation of the parasite. Based on the sequence homology between pESAG7/6 and the N-terminal domain of VSGs, it can be predicted that the four blocks containing the major sequence differences between pESAG7 and pESAG6 form surface-exposed loops and generate the ligand-binding site. The exchange of a few amino acids in this region between pESAG6s encoded by different VSG units greatly increased the affinity for bovine Tf. Similar changes in other regions were ineffective, while mutations predicted to alter the VSG-like structure abolished the binding. Chimeric proteins containing the N-terminal dimerization domain of VSG and the C-terminal half of either pESAG7 or pESAG6, which contains the ligand-binding domain, can form heterodimers that bind Tf. Taken together, these data provided evidence that the T.brucei Tf receptor is structurally related to the N-terminal domain of the VSG and that the ligand-binding site corresponds to the exposed surface loops of the protein.

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.

Binding free energy prediction in strongly hydrophobic biomolecular systems.

PubMed

Charlier, Landry; Nespoulous, Claude; Fiorucci, Sébastien; Antonczak, Serge; Golebiowski, Jérome

2007-11-21

We present a comparison of various computational approaches aiming at predicting the binding free energy in ligand-protein systems where the ligand is located within a highly hydrophobic cavity. The relative binding free energy between similar ligands is obtained by means of the thermodynamic integration (TI) method and compared to experimental data obtained through isothermal titration calorimetry measurements. The absolute free energy of binding prediction was obtained on a similar system (a pyrazine derivative bound to a lipocalin) by TI, potential of mean force (PMF) and also by means of the MMPBSA protocols. Although the TI protocol performs poorly either with an explicit or an implicit solvation scheme, the PMF calculation using an implicit solvation scheme leads to encouraging results, with a prediction of the binding affinity being 2 kcal mol(-1) lower than the experimental value. The use of an implicit solvation scheme appears to be well suited for the study of such hydrophobic systems, due to the lack of water molecules within the binding site.

Acid-base and copper-binding properties of three organic matter fractions isolated from a forest floor soil solution

NASA Astrophysics Data System (ADS)

van Schaik, Joris W. J.; Kleja, Dan B.; Gustafsson, Jon Petter

2010-02-01

Vast amounts of knowledge about the proton- and metal-binding properties of dissolved organic matter (DOM) in natural waters have been obtained in studies on isolated humic and fulvic (hydrophobic) acids. Although macromolecular hydrophilic acids normally make up about one-third of DOM, their proton- and metal-binding properties are poorly known. Here, we investigated the acid-base and Cu-binding properties of the hydrophobic (fulvic) acid fraction and two hydrophilic fractions isolated from a soil solution. Proton titrations revealed a higher total charge for the hydrophilic acid fractions than for the hydrophobic acid fraction. The most hydrophilic fraction appeared to be dominated by weak acid sites, as evidenced by increased slope of the curve of surface charge versus pH at pH values above 6. The titration curves were poorly predicted by both Stockholm Humic Model (SHM) and NICA-Donnan model calculations using generic parameter values, but could be modelled accurately after optimisation of the proton-binding parameters (pH ⩽ 9). Cu-binding isotherms for the three fractions were determined at pH values of 4, 6 and 9. With the optimised proton-binding parameters, the SHM model predictions for Cu binding improved, whereas the NICA-Donnan predictions deteriorated. After optimisation of Cu-binding parameters, both models described the experimental data satisfactorily. Iron(III) and aluminium competed strongly with Cu for binding sites at both pH 4 and pH 6. The SHM model predicted this competition reasonably well, but the NICA-Donnan model underestimated the effects significantly at pH 6. Overall, the Cu-binding behaviour of the two hydrophilic acid fractions was very similar to that of the hydrophobic acid fraction, despite the differences observed in proton-binding characteristics. These results show that for modelling purposes, it is essential to include the hydrophilic acid fraction in the pool of 'active' humic substances.

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

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.

Rapid evolution of cis-regulatory sequences via local point mutations

NASA Technical Reports Server (NTRS)

Stone, J. R.; Wray, G. A.

2001-01-01

Although the evolution of protein-coding sequences within genomes is well understood, the same cannot be said of the cis-regulatory regions that control transcription. Yet, changes in gene expression are likely to constitute an important component of phenotypic evolution. We simulated the evolution of new transcription factor binding sites via local point mutations. The results indicate that new binding sites appear and become fixed within populations on microevolutionary timescales under an assumption of neutral evolution. Even combinations of two new binding sites evolve very quickly. We predict that local point mutations continually generate considerable genetic variation that is capable of altering gene expression.

Search for Functional Flexible Regions in the G-protein Family: New Reading of the FoldUnfold Program.

PubMed

Galzitskaya, Oxana; Deryusheva, Eugenia; Machulin, Andrey; Nemashkalova, Ekaterina; Glyakina, Anna

2018-06-21

High prediction accuracy of flexible loops in different protein families is a challenge because of the crucial functions associated with these regions. Results of the currently available programs for prediction of loops vary from protein to protein. For prediction of flexible regions in the G-domain for 23 representatives of G-proteins with the known 3D structure we have used eight programs. The results of predictions demonstrate that the FoldUnfold program predicts better loop positions than the PONDR, RОNN, DisEMBL, IUPred, GlobPlot 2, FoldIndex, and MobiDB programs. When classifying the predicted loops (rigid/flexible) according to the Debye-Waller fluctuation factors, our data reveal the existing weak correlation between the B-factors and the average number of closed residues according to the FoldUnfold program; the percentage of overlapping characteristics (residue fold/unfold status) of the protein residues from the two methods is about 60-70%. According to the FoldUnfold program, for G-proteins with the posttranslational modifications, the surrounding binding site residues by disordered-promoting glycine and alanine residues conduces to a more flexible position of the binding sites for fatty acid, while methionine, cysteine and isoleucine residues provide more rigid binding sites. Thus, our research demonstrates additional possibilities of the FoldUnfold program for prediction of flexible regions and characteristics of individual residues in a different protein family. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Great interactions: How binding incorrect partners can teach us about protein recognition and function.

PubMed

Vamparys, Lydie; Laurent, Benoist; Carbone, Alessandra; Sacquin-Mora, Sophie

2016-10-01

Protein-protein interactions play a key part in most biological processes and understanding their mechanism is a fundamental problem leading to numerous practical applications. The prediction of protein binding sites in particular is of paramount importance since proteins now represent a major class of therapeutic targets. Amongst others methods, docking simulations between two proteins known to interact can be a useful tool for the prediction of likely binding patches on a protein surface. From the analysis of the protein interfaces generated by a massive cross-docking experiment using the 168 proteins of the Docking Benchmark 2.0, where all possible protein pairs, and not only experimental ones, have been docked together, we show that it is also possible to predict a protein's binding residues without having any prior knowledge regarding its potential interaction partners. Evaluating the performance of cross-docking predictions using the area under the specificity-sensitivity ROC curve (AUC) leads to an AUC value of 0.77 for the complete benchmark (compared to the 0.5 AUC value obtained for random predictions). Furthermore, a new clustering analysis performed on the binding patches that are scattered on the protein surface show that their distribution and growth will depend on the protein's functional group. Finally, in several cases, the binding-site predictions resulting from the cross-docking simulations will lead to the identification of an alternate interface, which corresponds to the interaction with a biomolecular partner that is not included in the original benchmark. Proteins 2016; 84:1408-1421. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Binding Properties of General Odorant Binding Proteins from the Oriental Fruit Moth, Grapholita molesta (Busck) (Lepidoptera: Tortricidae)

PubMed Central

Li, Guangwei; Chen, Xiulin; Li, Boliao; Zhang, Guohui; Li, Yiping; Wu, Junxiang

2016-01-01

Background The oriental fruit moth Grapholita molesta is a host-switching pest species. The adults highly depend on olfactory cues in locating optimal host plants and oviposition sites. Odorant binding proteins (OBPs) are thought to be responsible for recognizing and transporting hydrophobic odorants across the aqueous sensillum lymph to stimulate the odorant receptors (ORs) within the antennal sensilla and activate the olfactory signal transduction pathway. Exploring the physiological function of these OBPs could facilitate understanding insect chemical communications. Methodology/Principal Finding Two antennae-specific general OBPs (GOBPs) of G. molesta were expressed and purified in vitro. The binding affinities of G. molesta GOBP1 and 2 (GmolGOBP1 and 2) for sex pheromone components and host plant volatiles were measured by fluorescence ligand-binding assays. The distribution of GmolGOBP1 and 2 in the antennal sensillum were defined by whole mount fluorescence immunohistochemistry (WM-FIHC) experiments. The binding sites of GmolGOBP2 were predicted using homology modeling, molecular docking and site-directed mutagenesis. Both GmolGOBP1 and 2 are housing in sensilla basiconica and with no differences in male and female antennae. Recombinant GmolGOBP1 (rGmolGOBP1) exhibited broad binding properties towards host plant volatiles and sex pheromone components; rGmolGOBP2 could not effectively bind host plant volatiles but showed specific binding affinity with a minor sex pheromone component dodecanol. We chose GmolGOBP2 and dodecanol for further homology modeling, molecular docking, and site-directed mutagenesis. Binding affinities of mutants demonstrated that Thr9 was the key binding site and confirmed dodecanol bonding to protein involves a hydrogen bond. Combined with the pH effect on binding affinities of rGmolGOBP2, ligand binding and release of GmolGOBP2 were related to a pH-dependent conformational transition. Conclusion Two rGmolGOBPs exhibit different binding characteristics for tested ligands. rGmolGOBP1 has dual functions in recognition of host plant volatiles and sex pheromone components, while rGmolGOBP2 is mainly involved in minor sex pheromone component dodecanol perception. This study also provides empirical evidence for the predicted functions of key amino acids in recombinant protein ligand-binding characteristics. PMID:27152703

Context influences on TALE–DNA binding revealed by quantitative profiling

PubMed Central

Rogers, Julia M.; Barrera, Luis A.; Reyon, Deepak; Sander, Jeffry D.; Kellis, Manolis; Joung, J Keith; Bulyk, Martha L.

2015-01-01

Transcription activator-like effector (TALE) proteins recognize DNA using a seemingly simple DNA-binding code, which makes them attractive for use in genome engineering technologies that require precise targeting. Although this code is used successfully to design TALEs to target specific sequences, off-target binding has been observed and is difficult to predict. Here we explore TALE–DNA interactions comprehensively by quantitatively assaying the DNA-binding specificities of 21 representative TALEs to ∼5,000–20,000 unique DNA sequences per protein using custom-designed protein-binding microarrays (PBMs). We find that protein context features exert significant influences on binding. Thus, the canonical recognition code does not fully capture the complexity of TALE–DNA binding. We used the PBM data to develop a computational model, Specificity Inference For TAL-Effector Design (SIFTED), to predict the DNA-binding specificity of any TALE. We provide SIFTED as a publicly available web tool that predicts potential genomic off-target sites for improved TALE design. PMID:26067805

Context influences on TALE-DNA binding revealed by quantitative profiling.

PubMed

Rogers, Julia M; Barrera, Luis A; Reyon, Deepak; Sander, Jeffry D; Kellis, Manolis; Joung, J Keith; Bulyk, Martha L

2015-06-11

Transcription activator-like effector (TALE) proteins recognize DNA using a seemingly simple DNA-binding code, which makes them attractive for use in genome engineering technologies that require precise targeting. Although this code is used successfully to design TALEs to target specific sequences, off-target binding has been observed and is difficult to predict. Here we explore TALE-DNA interactions comprehensively by quantitatively assaying the DNA-binding specificities of 21 representative TALEs to ∼5,000-20,000 unique DNA sequences per protein using custom-designed protein-binding microarrays (PBMs). We find that protein context features exert significant influences on binding. Thus, the canonical recognition code does not fully capture the complexity of TALE-DNA binding. We used the PBM data to develop a computational model, Specificity Inference For TAL-Effector Design (SIFTED), to predict the DNA-binding specificity of any TALE. We provide SIFTED as a publicly available web tool that predicts potential genomic off-target sites for improved TALE design.

A flexible docking scheme to explore the binding selectivity of PDZ domains.

PubMed

Gerek, Z Nevin; Ozkan, S Banu

2010-05-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTALIGAND, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 A. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.

A flexible docking scheme to explore the binding selectivity of PDZ domains

PubMed Central

Gerek, Z Nevin; Ozkan, S Banu

2010-01-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using RosettaLigand, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately. PMID:20196074

BiPPred: Combined sequence- and structure-based prediction of peptide binding to the Hsp70 chaperone BiP.

PubMed

Schneider, Markus; Rosam, Mathias; Glaser, Manuel; Patronov, Atanas; Shah, Harpreet; Back, Katrin Christiane; Daake, Marina Angelika; Buchner, Johannes; Antes, Iris

2016-10-01

Substrate binding to Hsp70 chaperones is involved in many biological processes, and the identification of potential substrates is important for a comprehensive understanding of these events. We present a multi-scale pipeline for an accurate, yet efficient prediction of peptides binding to the Hsp70 chaperone BiP by combining sequence-based prediction with molecular docking and MMPBSA calculations. First, we measured the binding of 15mer peptides from known substrate proteins of BiP by peptide array (PA) experiments and performed an accuracy assessment of the PA data by fluorescence anisotropy studies. Several sequence-based prediction models were fitted using this and other peptide binding data. A structure-based position-specific scoring matrix (SB-PSSM) derived solely from structural modeling data forms the core of all models. The matrix elements are based on a combination of binding energy estimations, molecular dynamics simulations, and analysis of the BiP binding site, which led to new insights into the peptide binding specificities of the chaperone. Using this SB-PSSM, peptide binders could be predicted with high selectivity even without training of the model on experimental data. Additional training further increased the prediction accuracies. Subsequent molecular docking (DynaDock) and MMGBSA/MMPBSA-based binding affinity estimations for predicted binders allowed the identification of the correct binding mode of the peptides as well as the calculation of nearly quantitative binding affinities. The general concept behind the developed multi-scale pipeline can readily be applied to other protein-peptide complexes with linearly bound peptides, for which sufficient experimental binding data for the training of classical sequence-based prediction models is not available. Proteins 2016; 84:1390-1407. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

PredictProtein—an open resource for online prediction of protein structural and functional features

PubMed Central

Yachdav, Guy; Kloppmann, Edda; Kajan, Laszlo; Hecht, Maximilian; Goldberg, Tatyana; Hamp, Tobias; Hönigschmid, Peter; Schafferhans, Andrea; Roos, Manfred; Bernhofer, Michael; Richter, Lothar; Ashkenazy, Haim; Punta, Marco; Schlessinger, Avner; Bromberg, Yana; Schneider, Reinhard; Vriend, Gerrit; Sander, Chris; Ben-Tal, Nir; Rost, Burkhard

2014-01-01

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org. PMID:24799431

Structure, Function, and Evolution of Biogenic Amine-binding Proteins in Soft Ticks

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

Mans, Ben J.; Ribeiro, Jose M.C.; Andersen, John F.

2008-08-19

Two highly abundant lipocalins, monomine and monotonin, have been isolated from the salivary gland of the soft tick Argas monolakensis and shown to bind histamine and 5-hydroxytryptamine (5-HT), respectively. The crystal structures of monomine and a paralog of monotonin were determined in the presence of ligands to compare the determinants of ligand binding. Both the structures and binding measurements indicate that the proteins have a single binding site rather than the two sites previously described for the female-specific histamine-binding protein (FS-HBP), the histamine-binding lipocalin of the tick Rhipicephalus appendiculatus. The binding sites of monomine and monotonin are similar to themore » lower, low affinity site of FS-HBP. The interaction of the protein with the aliphatic amine group of the ligand is very similar for the all of the proteins, whereas specificity is determined by interactions with the aromatic portion of the ligand. Interestingly, protein interaction with the imidazole ring of histamine differs significantly between the low affinity binding site of FS-HBP and monomine, suggesting that histamine binding has evolved independently in the two lineages. From the conserved features of these proteins, a tick lipocalin biogenic amine-binding motif could be derived that was used to predict biogenic amine-binding function in other tick lipocalins. Heterologous expression of genes from salivary gland libraries led to the discovery of biogenic amine-binding proteins in soft (Ornithodoros) and hard (Ixodes) tick genera. The data generated were used to reconstruct the most probable evolutionary pathway for the evolution of biogenic amine-binding in tick lipocalins.« less

Anesthetic Binding in a Pentameric Ligand-Gated Ion Channel: GLIC

PubMed Central

Chen, Qiang; Cheng, Mary Hongying; Xu, Yan; Tang, Pei

2010-01-01

Cys-loop receptors are molecular targets of general anesthetics, but the knowledge of anesthetic binding to these proteins remains limited. Here we investigate anesthetic binding to the bacterial Gloeobacter violaceus pentameric ligand-gated ion channel (GLIC), a structural homolog of cys-loop receptors, using an experimental and computational hybrid approach. Tryptophan fluorescence quenching experiments showed halothane and thiopental binding at three tryptophan-associated sites in the extracellular (EC) domain, transmembrane (TM) domain, and EC-TM interface of GLIC. An additional binding site at the EC-TM interface was predicted by docking analysis and validated by quenching experiments on the N200W GLIC mutant. The binding affinities (KD) of 2.3 ± 0.1 mM and 0.10 ± 0.01 mM were derived from the fluorescence quenching data of halothane and thiopental, respectively. Docking these anesthetics to the original GLIC crystal structure and the structures relaxed by molecular dynamics simulations revealed intrasubunit sites for most halothane binding and intersubunit sites for thiopental binding. Tryptophans were within reach of both intra- and intersubunit binding sites. Multiple molecular dynamics simulations on GLIC in the presence of halothane at different sites suggested that anesthetic binding at the EC-TM interface disrupted the critical interactions for channel gating, altered motion of the TM23 linker, and destabilized the open-channel conformation that can lead to inhibition of GLIC channel current. The study has not only provided insights into anesthetic binding in GLIC, but also demonstrated a successful fusion of experiments and computations for understanding anesthetic actions in complex proteins. PMID:20858424

A map of human PRDM9 binding provides evidence for novel behaviors of PRDM9 and other zinc-finger proteins in meiosis

PubMed Central

Noor, Nudrat; Bitoun, Emmanuelle; Tumian, Afidalina; Imbeault, Michael; Chapman, J Ross; Aricescu, A Radu

2017-01-01

PRDM9 binding localizes almost all meiotic recombination sites in humans and mice. However, most PRDM9-bound loci do not become recombination hotspots. To explore factors that affect binding and subsequent recombination outcomes, we mapped human PRDM9 binding sites in a transfected human cell line and measured PRDM9-induced histone modifications. These data reveal varied DNA-binding modalities of PRDM9. We also find that human PRDM9 frequently binds promoters, despite their low recombination rates, and it can activate expression of a small number of genes including CTCFL and VCX. Furthermore, we identify specific sequence motifs that predict consistent, localized meiotic recombination suppression around a subset of PRDM9 binding sites. These motifs strongly associate with KRAB-ZNF protein binding, TRIM28 recruitment, and specific histone modifications. Finally, we demonstrate that, in addition to binding DNA, PRDM9's zinc fingers also mediate its multimerization, and we show that a pair of highly diverged alleles preferentially form homo-multimers. PMID:29072575

Detecting cis-regulatory binding sites for cooperatively binding proteins

PubMed Central

van Oeffelen, Liesbeth; Cornelis, Pierre; Van Delm, Wouter; De Ridder, Fedor; De Moor, Bart; Moreau, Yves

2008-01-01

Several methods are available to predict cis-regulatory modules in DNA based on position weight matrices. However, the performance of these methods generally depends on a number of additional parameters that cannot be derived from sequences and are difficult to estimate because they have no physical meaning. As the best way to detect cis-regulatory modules is the way in which the proteins recognize them, we developed a new scoring method that utilizes the underlying physical binding model. This method requires no additional parameter to account for multiple binding sites; and the only necessary parameters to model homotypic cooperative interactions are the distances between adjacent protein binding sites in basepairs, and the corresponding cooperative binding constants. The heterotypic cooperative binding model requires one more parameter per cooperatively binding protein, which is the concentration multiplied by the partition function of this protein. In a case study on the bacterial ferric uptake regulator, we show that our scoring method for homotypic cooperatively binding proteins significantly outperforms other PWM-based methods where biophysical cooperativity is not taken into account. PMID:18400778

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

Molecular simulations and Markov state modeling reveal the structural diversity and dynamics of a theophylline-binding RNA aptamer in its unbound state

PubMed Central

Warfield, Becka M.

2017-01-01

RNA aptamers are oligonucleotides that bind with high specificity and affinity to target ligands. In the absence of bound ligand, secondary structures of RNA aptamers are generally stable, but single-stranded and loop regions, including ligand binding sites, lack defined structures and exist as ensembles of conformations. For example, the well-characterized theophylline-binding aptamer forms a highly stable binding site when bound to theophylline, but the binding site is unstable and disordered when theophylline is absent. Experimental methods have not revealed at atomic resolution the conformations that the theophylline aptamer explores in its unbound state. Consequently, in the present study we applied 21 microseconds of molecular dynamics simulations to structurally characterize the ensemble of conformations that the aptamer adopts in the absence of theophylline. Moreover, we apply Markov state modeling to predict the kinetics of transitions between unbound conformational states. Our simulation results agree with experimental observations that the theophylline binding site is found in many distinct binding-incompetent states and show that these states lack a binding pocket that can accommodate theophylline. The binding-incompetent states interconvert with binding-competent states through structural rearrangement of the binding site on the nanosecond to microsecond timescale. Moreover, we have simulated the complete theophylline binding pathway. Our binding simulations supplement prior experimental observations of slow theophylline binding kinetics by showing that the binding site must undergo a large conformational rearrangement after the aptamer and theophylline form an initial complex, most notably, a major rearrangement of the C27 base from a buried to solvent-exposed orientation. Theophylline appears to bind by a combination of conformational selection and induced fit mechanisms. Finally, our modeling indicates that when Mg2+ ions are present the population of binding-competent aptamer states increases more than twofold. This population change, rather than direct interactions between Mg2+ and theophylline, accounts for altered theophylline binding kinetics. PMID:28437473

Prediction of enzyme binding: human thrombin inhibition study by quantum chemical and artificial intelligence methods based on X-ray structures.

PubMed

Mlinsek, G; Novic, M; Hodoscek, M; Solmajer, T

2001-01-01

Thrombin is a serine protease which plays important roles in the human body, the key one being the control of thrombus formation. The inhibition of thrombin has become a target for new antithrombotics. The aim of our work was to (i) construct a model which would enable us to predict Ki values for the binding of an inhibitor into the active site of thrombin based on a database of known X-ray structures of inhibitor-enzyme complexes and (ii) to identify the structural and electrostatic characteristics of inhibitor molecules crucially important to their effective binding. To retain as much of the 3D structural information of the bound inhibitor as possible, we implemented the quantum mechanical/molecular mechanical (QM/MM) procedure for calculating the molecular electrostatic potential (MEP) at the van der Waals surfaces of atoms in the protein's active site. The inhibitor was treated quantum mechanically, while the rest of the complex was treated by classical means. The obtained MEP values served as inputs into the counter-propagation artificial neural network (CP-ANN), and a genetic algorithm was subsequently used to search for the combination of atoms that predominantly influences the binding. The constructed CP-ANN model yielded Ki values predictions with a correlation coefficient of 0.96, with Ki values extended over 7 orders of magnitude. Our approach also shows the relative importance of the various amino acid residues present in the active site of the enzyme for inhibitor binding. The list of residues selected by our automatic procedure is in good correlation with the current consensus regarding the importance of certain crucial residues in thrombin's active site.

RBscore&NBench: a high-level web server for nucleic acid binding residues prediction with a large-scale benchmarking database.

PubMed

Miao, Zhichao; Westhof, Eric

2016-07-08

RBscore&NBench combines a web server, RBscore and a database, NBench. RBscore predicts RNA-/DNA-binding residues in proteins and visualizes the prediction scores and features on protein structures. The scoring scheme of RBscore directly links feature values to nucleic acid binding probabilities and illustrates the nucleic acid binding energy funnel on the protein surface. To avoid dataset, binding site definition and assessment metric biases, we compared RBscore with 18 web servers and 3 stand-alone programs on 41 datasets, which demonstrated the high and stable accuracy of RBscore. A comprehensive comparison led us to develop a benchmark database named NBench. The web server is available on: http://ahsoka.u-strasbg.fr/rbscorenbench/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Determinants of RNA binding and translational repression by the Bicaudal-C regulatory protein.

PubMed

Zhang, Yan; Park, Sookhee; Blaser, Susanne; Sheets, Michael D

2014-03-14

Bicaudal-C (Bic-C) RNA binding proteins function as important translational repressors in multiple biological contexts within metazoans. However, their RNA binding sites are unknown. We recently demonstrated that Bic-C functions in spatially regulated translational repression of the xCR1 mRNA during Xenopus development. This repression contributes to normal development by confining the xCR1 protein, a regulator of key signaling pathways, to specific cells of the embryo. In this report, we combined biochemical approaches with in vivo mRNA reporter assays to define the minimal Bic-C target site within the xCR1 mRNA. This 32-nucleotide Bic-C target site is predicted to fold into a stem-loop secondary structure. Mutational analyses provided evidence that this stem-loop structure is important for Bic-C binding. The Bic-C target site was sufficient for Bic-C mediated repression in vivo. Thus, we describe the first RNA binding site for a Bic-C protein. This identification provides an important step toward understanding the mechanisms by which evolutionarily conserved Bic-C proteins control cellular function in metazoans.

DeepSite: protein-binding site predictor using 3D-convolutional neural networks.

PubMed

Jiménez, J; Doerr, S; Martínez-Rosell, G; Rose, A S; De Fabritiis, G

2017-10-01

An important step in structure-based drug design consists in the prediction of druggable binding sites. Several algorithms for detecting binding cavities, those likely to bind to a small drug compound, have been developed over the years by clever exploitation of geometric, chemical and evolutionary features of the protein. Here we present a novel knowledge-based approach that uses state-of-the-art convolutional neural networks, where the algorithm is learned by examples. In total, 7622 proteins from the scPDB database of binding sites have been evaluated using both a distance and a volumetric overlap approach. Our machine-learning based method demonstrates superior performance to two other competitive algorithmic strategies. DeepSite is freely available at www.playmolecule.org. Users can submit either a PDB ID or PDB file for pocket detection to our NVIDIA GPU-equipped servers through a WebGL graphical interface. gianni.defabritiis@upf.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Structure-based CoMFA as a predictive model - CYP2C9 inhibitors as a test case.

PubMed

Yasuo, Kazuya; Yamaotsu, Noriyuki; Gouda, Hiroaki; Tsujishita, Hideki; Hirono, Shuichi

2009-04-01

In this study, we tried to establish a general scheme to create a model that could predict the affinity of small compounds to their target proteins. This scheme consists of a search for ligand-binding sites on a protein, a generation of bound conformations (poses) of ligands in each of the sites by docking, identifications of the correct poses of each ligand by consensus scoring and MM-PBSA analysis, and a construction of a CoMFA model with the obtained poses to predict the affinity of the ligands. By using a crystal structure of CYP 2C9 and the twenty known CYP inhibitors as a test case, we obtained a CoMFA model with a good statistics, which suggested that the classification of the binding sites as well as the predicted bound poses of the ligands should be reasonable enough. The scheme described here would give a method to predict the affinity of small compounds with a reasonable accuracy, which is expected to heighten the value of computational chemistry in the drug design process.

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.

LIBRA-WA: a web application for ligand binding site detection and protein function recognition.

PubMed

Toti, Daniele; Viet Hung, Le; Tortosa, Valentina; Brandi, Valentina; Polticelli, Fabio

2018-03-01

Recently, LIBRA, a tool for active/ligand binding site prediction, was described. LIBRA's effectiveness was comparable to similar state-of-the-art tools; however, its scoring scheme, output presentation, dependence on local resources and overall convenience were amenable to improvements. To solve these issues, LIBRA-WA, a web application based on an improved LIBRA engine, has been developed, featuring a novel scoring scheme consistently improving LIBRA's performance, and a refined algorithm that can identify binding sites hosted at the interface between different subunits. LIBRA-WA also sports additional functionalities like ligand clustering and a completely redesigned interface for an easier analysis of the output. Extensive tests on 373 apoprotein structures indicate that LIBRA-WA is able to identify the biologically relevant ligand/ligand binding site in 357 cases (∼96%), with the correct prediction ranking first in 349 cases (∼98% of the latter, ∼94% of the total). The earlier stand-alone tool has also been updated and dubbed LIBRA+, by integrating LIBRA-WA's improved engine for cross-compatibility purposes. LIBRA-WA and LIBRA+ are available at: http://www.computationalbiology.it/software.html. polticel@uniroma3.it. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

A pseudoreceptor modelling study of the varicella-zoster virus and human thymidine kinase binding sites

NASA Astrophysics Data System (ADS)

Greenidge, Paulette A.; Merz, Alfred; Folkers, Gerd

1995-12-01

A representative range of pyrimidine nucleoside analogues that are known to inhibit herpes simplex virus (HSV) replication have been used to construct receptor binding site models for the varicella-zoster virus (VZV), thymidine kinase (TK) and human TK1. Given a set of interacting ligands, superimposed in such a manner as to define a pharmacophore, the pseudoreceptor modelling technique Yak provides a means of building binding site models of macromolecules for which no three-dimensional experimental structures are available. Once the models have been evaluated by their ability to reproduce experimental binding data [Vedani et al., J. Am. Chem. Soc., 117 (1995) 4987], they can be used for predictive purposes. Calculated and experimental values of relative binding affinity are compared. Our models suggest that the substitution of one residue may be sufficient to determine ligand subtype affinity.

Dynamic Changes in Nucleosome Occupancy Are Not Predictive of Gene Expression Dynamics but Are Linked to Transcription and Chromatin Regulators

PubMed Central

Huebert, Dana J.; Kuan, Pei-Fen; Keleş, Sündüz

2012-01-01

The response to stressful stimuli requires rapid, precise, and dynamic gene expression changes that must be coordinated across the genome. To gain insight into the temporal ordering of genome reorganization, we investigated dynamic relationships between changing nucleosome occupancy, transcription factor binding, and gene expression in Saccharomyces cerevisiae yeast responding to oxidative stress. We applied deep sequencing to nucleosomal DNA at six time points before and after hydrogen peroxide treatment and revealed many distinct dynamic patterns of nucleosome gain and loss. The timing of nucleosome repositioning was not predictive of the dynamics of downstream gene expression change but instead was linked to nucleosome position relative to transcription start sites and specific cis-regulatory elements. We measured genome-wide binding of the stress-activated transcription factor Msn2p over time and found that Msn2p binds different loci with different dynamics. Nucleosome eviction from Msn2p binding sites was common across the genome; however, we show that, contrary to expectation, nucleosome loss occurred after Msn2p binding and in fact required Msn2p. This negates the prevailing model that nucleosomes obscuring Msn2p sites regulate DNA access and must be lost before Msn2p can bind DNA. Together, these results highlight the complexities of stress-dependent chromatin changes and their effects on gene expression. PMID:22354995

Apocalmodulin and Ca2+ calmodulin bind to the same region on the skeletal muscle Ca2+ release channel

NASA Technical Reports Server (NTRS)

Moore, C. P.; Rodney, G.; Zhang, J. Z.; Santacruz-Toloza, L.; Strasburg, G.; Hamilton, S. L.

1999-01-01

The skeletal muscle Ca2+ release channel (RYR1) is regulated by calmodulin in both its Ca2+-free (apocalmodulin) and Ca2+-bound (Ca2+ calmodulin) states. Apocalmodulin is an activator of the channel, and Ca2+ calmodulin is an inhibitor of the channel. Both apocalmodulin and Ca2+ calmodulin binding sites on RYR1 are destroyed by a mild tryptic digestion of the sarcoplasmic reticulum membranes, but calmodulin (either form), bound to RYR1 prior to tryptic digestion, protects both the apocalmodulin and Ca2+ calmodulin sites from tryptic destruction. The protected sites are after arginines 3630 and 3637 on RYR1. These studies suggest that both Ca2+ calmodulin and apocalmodulin bind to the same or overlapping regions on RYR1 and block access of trypsin to sites at amino acids 3630 and 3637. This sequence is part of a predicted Ca2+ CaM binding site of amino acids 3614-3642 [Takeshima, H., et al. (1989) Nature 339, 439-445].

Theory of single-molecule controlled rotation experiments, predictions, tests, and comparison with stalling experiments in F1-ATPase.

PubMed

Volkán-Kacsó, Sándor; Marcus, Rudolph A

2016-10-25

A recently proposed chemomechanical group transfer theory of rotary biomolecular motors is applied to treat single-molecule controlled rotation experiments. In these experiments, single-molecule fluorescence is used to measure the binding and release rate constants of nucleotides by monitoring the occupancy of binding sites. It is shown how missed events of nucleotide binding and release in these experiments can be corrected using theory, with F 1 -ATP synthase as an example. The missed events are significant when the reverse rate is very fast. Using the theory the actual rate constants in the controlled rotation experiments and the corrections are predicted from independent data, including other single-molecule rotation and ensemble biochemical experiments. The effective torsional elastic constant is found to depend on the binding/releasing nucleotide, and it is smaller for ADP than for ATP. There is a good agreement, with no adjustable parameters, between the theoretical and experimental results of controlled rotation experiments and stalling experiments, for the range of angles where the data overlap. This agreement is perhaps all the more surprising because it occurs even though the binding and release of fluorescent nucleotides is monitored at single-site occupancy concentrations, whereas the stalling and free rotation experiments have multiple-site occupancy.

Binding-Site Assessment by Virtual Fragment Screening

PubMed Central

Huang, Niu; Jacobson, Matthew P.

2010-01-01

The accurate prediction of protein druggability (propensity to bind high-affinity drug-like small molecules) would greatly benefit the fields of chemical genomics and drug discovery. We have developed a novel approach to quantitatively assess protein druggability by computationally screening a fragment-like compound library. In analogy to NMR-based fragment screening, we dock ∼11000 fragments against a given binding site and compute a computational hit rate based on the fraction of molecules that exceed an empirically chosen score cutoff. We perform a large-scale evaluation of the approach on four datasets, totaling 152 binding sites. We demonstrate that computed hit rates correlate with hit rates measured experimentally in a previously published NMR-based screening method. Secondly, we show that the in silico fragment screening method can be used to distinguish known druggable and non-druggable targets, including both enzymes and protein-protein interaction sites. Finally, we explore the sensitivity of the results to different receptor conformations, including flexible protein-protein interaction sites. Besides its original aim to assess druggability of different protein targets, this method could be used to identifying druggable conformations of flexible binding site for lead discovery, and suggesting strategies for growing or joining initial fragment hits to obtain more potent inhibitors. PMID:20404926

Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions.

PubMed

Arcon, Juan Pablo; Defelipe, Lucas A; Modenutti, Carlos P; López, Elias D; Alvarez-Garcia, Daniel; Barril, Xavier; Turjanski, Adrián G; Martí, Marcelo A

2017-04-24

One of the most important biological processes at the molecular level is the formation of protein-ligand complexes. Therefore, determining their structure and underlying key interactions is of paramount relevance and has direct applications in drug development. Because of its low cost relative to its experimental sibling, molecular dynamics (MD) simulations in the presence of different solvent probes mimicking specific types of interactions have been increasingly used to analyze protein binding sites and reveal protein-ligand interaction hot spots. However, a systematic comparison of different probes and their real predictive power from a quantitative and thermodynamic point of view is still missing. In the present work, we have performed MD simulations of 18 different proteins in pure water as well as water mixtures of ethanol, acetamide, acetonitrile and methylammonium acetate, leading to a total of 5.4 μs simulation time. For each system, we determined the corresponding solvent sites, defined as space regions adjacent to the protein surface where the probability of finding a probe atom is higher than that in the bulk solvent. Finally, we compared the identified solvent sites with 121 different protein-ligand complexes and used them to perform molecular docking and ligand binding free energy estimates. Our results show that combining solely water and ethanol sites allows sampling over 70% of all possible protein-ligand interactions, especially those that coincide with ligand-based pharmacophoric points. Most important, we also show how the solvent sites can be used to significantly improve ligand docking in terms of both accuracy and precision, and that accurate predictions of ligand binding free energies, along with relative ranking of ligand affinity, can be performed.

Shewregdb: Database and visualization environment for experimental and predicted regulatory information in Shewanella oneidensis mr-1

PubMed Central

Syed, Mustafa H; Karpinets, Tatiana V; Leuze, Michael R; Kora, Guruprasad H; Romine, Margaret R; Uberbacher, Edward C

2009-01-01

Shewanella oneidensis MR-1 is an important model organism for environmental research as it has an exceptional metabolic and respiratory versatility regulated by a complex regulatory network. We have developed a database to collect experimental and computational data relating to regulation of gene and protein expression, and, a visualization environment that enables integration of these data types. The regulatory information in the database includes predictions of DNA regulator binding sites, sigma factor binding sites, transcription units, operons, promoters, and RNA regulators including non-coding RNAs, riboswitches, and different types of terminators. Availability http://shewanella-knowledgebase.org:8080/Shewanella/gbrowserLanding.jsp PMID:20198195

Docking analysis targeted to the whole enzyme: an application to the prediction of inhibition of PTP1B by thiomorpholine and thiazolyl derivatives.

PubMed

Ganou, C A; Eleftheriou, P Th; Theodosis-Nobelos, P; Fesatidou, M; Geronikaki, A A; Lialiaris, T; Rekka, E A

2018-02-01

PTP1b is a protein tyrosine phosphatase involved in the inactivation of insulin receptor. Since inhibition of PTP1b may prolong the action of the receptor, PTP1b has become a drug target for the treatment of type II diabetes. In the present study, prediction of inhibition using docking analysis targeted specifically to the active or allosteric site was performed on 87 compounds structurally belonging to 10 different groups. Two groups, consisting of 15 thiomorpholine and 10 thiazolyl derivatives exhibiting the best prediction results, were selected for in vitro evaluation. All thiomorpholines showed inhibitory action (with IC 50 = 4-45 μΜ, Ki = 2-23 μM), while only three thiazolyl derivatives showed low inhibition (best IC 50 = 18 μΜ, Ki = 9 μΜ). However, free binding energy (E) was in accordance with the IC 50 values only for some compounds. Docking analysis targeted to the whole enzyme revealed that the compounds exhibiting IC 50 values higher than expected could bind to other peripheral sites with lower free energy, E o , than when bound to the active/allosteric site. A prediction factor, E- (Σ Eo × 0.16), which takes into account lower energy binding to peripheral sites, was proposed and was found to correlate well with the IC 50 values following an asymmetrical sigmoidal equation with r 2 = 0.9692.

Inhibition of cytochrome P450 3A by acetoxylated analogues of resveratrol in in vitro and in silico models

PubMed Central

Basheer, Loai; Schultz, Keren; Kerem, Zohar

2016-01-01

Many dietary compounds, including resveratrol, are potent inhibitors of CYP3A4. Here we examined the potential to predict inhibition capacity of dietary polyphenolics using an in silico and in vitro approaches and synthetic model compounds. Mono, di, and tri-acetoxy resveratrol were synthesized, a cell line of human intestine origin and microsomes from rat liver served to determine their in vitro inhibition of CYP3A4, and compared to that of resveratrol. Docking simulation served to predict the affinity of the synthetic model compounds to the enzyme. Modelling of the enzyme’s binding site revealed three types of interaction: hydrophobic, electrostatic and H-bonding. The simulation revealed that each of the examined acetylations of resveratrol led to the loss of important interactions of all types. Tri-acetoxy resveratrol was the weakest inhibitor in vitro despite being the more lipophilic and having the highest affinity for the binding site. The simulation demonstrated exclusion of all interactions between tri-acetoxy resveratrol and the heme due to distal binding, highlighting the complexity of the CYP3A4 binding site, which may allow simultaneous accommodation of two molecules. Finally, the use of computational modelling may serve as a quick predictive tool to identify potential harmful interactions between dietary compounds and prescribed drugs. PMID:27530542

Structure-based prediction of free energy changes of binding of PTP1B inhibitors

NASA Astrophysics Data System (ADS)

Wang, Jing; Ling Chan, Shek; Ramnarayan, Kal

2003-08-01

The goals were (1) to understand the driving forces in the binding of small molecule inhibitors to the active site of PTP1B and (2) to develop a molecular mechanics-based empirical free energy function for compound potency prediction. A set of compounds with known activities was docked onto the active site. The related energy components and molecular surface areas were calculated. The bridging water molecules were identified and their contributions were considered. Linear relationships were explored between the above terms and the binding free energies of compounds derived based on experimental inhibition constants. We found that minimally three terms are required to give rise to a good correlation (0.86) with predictive power in five-group cross-validation test (q2 = 0.70). The dominant terms are the electrostatic energy and non-electrostatic energy stemming from the intra- and intermolecular interactions of solutes and from those of bridging water molecules in complexes.

Structure- and Modeling-based Identification of the Adenovirus E4orf4 Binding Site in the Protein Phosphatase 2A B55α Subunit*

PubMed Central

Horowitz, Ben; Sharf, Rakefet; Avital-Shacham, Meirav; Pechkovsky, Antonina; Kleinberger, Tamar

2013-01-01

The adenovirus E4orf4 protein regulates the progression of viral infection and when expressed outside the context of the virus it induces nonclassical, cancer cell-specific apoptosis. All E4orf4 functions known to date require an interaction between E4orf4 and protein phosphatase 2A (PP2A), which is mediated through PP2A regulatory B subunits. Specifically, an interaction with the B55α subunit is required for induction of cell death by E4orf4. To gain a better insight into the E4orf4-PP2A interaction, mapping of the E4orf4 interaction site in PP2A-B55α has been undertaken. To this end we used a combination of bioinformatics analyses of PP2A-B55α and of E4orf4, which led to the prediction of E4orf4 binding sites on the surface of PP2A-B55α. Mutation analysis, immunoprecipitation, and GST pulldown assays based on the theoretical predictions revealed that the E4orf4 binding site included the α1 and α2 helices described in the B55α structure and involved at least three residues located in these helices facing each other. Loss of E4orf4 binding was accompanied by reduced contribution of the B55α mutants to E4orf4-induced cell death. The identified E4orf4 binding domain lies above the previously described substrate binding site and does not overlap it, although its location could be consistent with direct or indirect effects on substrate binding. This work assigns for the first time a functional significance to the α1,α2 helices of B55α, and we suggest that the binding site defined by these helices could also contribute to interactions between PP2A and some of its cellular regulators. PMID:23530045

Homology modelling of frequent HLA class-II alleles: A perspective to improve prediction of HLA binding peptide and understand the HLA associated disease susceptibility.

PubMed

Kashyap, Manju; Farooq, Umar; Jaiswal, Varun

2016-10-01

Human leukocyte antigen (HLA) plays significant role via the regulation of immune system and contribute in the progression and protection of many diseases. HLA molecules bind and present peptides to T- cell receptors which generate the immune response. HLA peptide interaction and molecular function of HLA molecule is the key to predict peptide binding and understanding its role in different diseases. The availability of accurate three dimensional (3D) structures is the initial step towards this direction. In the present work, homology modelling of important and frequent HLA-DRB1 alleles (07:01, 11:01 and 09:01) was done and acceptable models were generated. These modelled alleles were further refined and cross validated by using several methods including Ramachandran plot, Z-score, ERRAT analysis and root mean square deviation (RMSD) calculations. It is known that numbers of allelic variants are related to the susceptibility or protection of various infectious diseases. Difference in amino acid sequences and structures of alleles were also studied to understand the association of HLA with disease susceptibility and protection. Susceptible alleles showed more amino acid variations than protective alleles in three selected diseases caused by different pathogens. Amino acid variations at binding site were found to be more than other part of alleles. RMSD values were also higher at variable positions within binding site. Higher RMSD values indicate that mutations occurring at peptide binding site alter protein structure more than rest of the protein. Hence, these findings and modelled structures can be used to design HLA-DRB1 binding peptides to overcome low prediction accuracy of HLA class II binding peptides. Furthermore, it may help to understand the allele specific molecular mechanisms involved in susceptibility/resistance against pathogenic diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Volatile anesthetic binding to proteins is influenced by solvent and aliphatic residues.

PubMed

Streiff, John H; Jones, Keith A

2008-10-01

The main objective of this work was to characterize VA binding sites in multiple anesthetic target proteins. A computational algorithm was used to quantify the solvent exclusion and aliphatic character of amphiphilic pockets in the structures of VA binding proteins. VA binding sites in the protein structures were defined as the pockets with solvent exclusion and aliphatic character that exceeded minimum values observed in the VA binding sites of serum albumin, firefly luciferase, and apoferritin. We found that the structures of VA binding proteins are enriched in these pockets and that the predicted binding sites were consistent with experimental determined binding locations in several proteins. Autodock3 was used to dock the simulated molecules of 1,1,1,2,2-pentafluoroethane, difluoromethyl 1,1,1,2-tetrafluoroethyl ether, and sevoflurane and the isomers of halothane and isoflurane into these potential binding sites. We found that the binding of the various VA molecules to the amphiphilic pockets is driven primarily by VDW interactions and to a lesser extent by weak hydrogen bonding and electrostatic interactions. In addition, the trend in Delta G binding values follows the Meyer-Overton rule. These results suggest that VA potencies are related to the VDW interactions between the VA ligand and protein target. It is likely that VA bind to sites with a high degree of solvent exclusion and aliphatic character because aliphatic residues provide favorable VDW contacts and weak hydrogen bond donors. Water molecules occupying these sites maintain pocket integrity, associate with the VA ligand, and diminish the unfavorable solvation enthalpy of the VA. Water molecules displaced into the bulk by the VA ligand may provide an additional favorable enthalpic contribution to VA binding. Anesthesia is a component of many health related procedures, the outcomes of which could be improved with a better understanding of the molecular targets and mechanisms of anesthetic action.

Location dependent coordination chemistry and MRI relaxivity, in de novo designed lanthanide coiled coils† †Electronic supplementary information (ESI) available: Methods, peptide characterization data including mass spectrometry and analytical HPLC, sedimentation equilibrium data, circular dichroism, luminescence, and NMR data. See DOI: 10.1039/c5sc04101e

PubMed Central

Berwick, Matthew R.; Slope, Louise N.; Smith, Caitlin F.; King, Siobhan M.; Newton, Sarah L.; Gillis, Richard B.; Adams, Gary G.; Rowe, Arthur J.; Harding, Stephen E.; Britton, Melanie M.

2016-01-01

Herein, we establish for the first time the design principles for lanthanide coordination within coiled coils, and the important consequences of binding site translation. By interrogating design requirements and by systematically translating binding site residues, one can influence coiled coil stability and more importantly, the lanthanide coordination chemistry. A 10 Å binding site translation along a coiled coil, transforms a coordinatively saturated Tb(Asp)3(Asn)3 site into one in which three exogenous water molecules are coordinated, and in which the Asn layer is no longer essential for binding, Tb(Asp)3(H2O)3. This has a profound impact on the relaxivity of the analogous Gd(iii) coiled coil, with more than a four-fold increase in the transverse relaxivity (21 to 89 mM–1 s–1), by bringing into play, in addition to the outer sphere mechanism present for all Gd(iii) coiled coils, an inner sphere mechanism. Not only do these findings warrant further investigation for possible exploitation as MRI contrast agents, but understanding the impact of binding site translation on coordination chemistry has important repercussions for metal binding site design, taking us an important step closer to the predictable and truly de novo design of metal binding sites, for new functional applications. PMID:29899946

Changes in signal transducer and activator of transcription 3 (STAT3) dynamics induced by complexation with pharmacological inhibitors of Src homology 2 (SH2) domain dimerization.

PubMed

Resetca, Diana; Haftchenary, Sina; Gunning, Patrick T; Wilson, Derek J

2014-11-21

The activity of the transcription factor signal transducer and activator of transcription 3 (STAT3) is dysregulated in a number of hematological and solid malignancies. Development of pharmacological STAT3 Src homology 2 (SH2) domain interaction inhibitors holds great promise for cancer therapy, and a novel class of salicylic acid-based STAT3 dimerization inhibitors that includes orally bioavailable drug candidates has been recently developed. The compounds SF-1-066 and BP-1-102 are predicted to bind to the STAT3 SH2 domain. However, given the highly unstructured and dynamic nature of the SH2 domain, experimental confirmation of this prediction was elusive. We have interrogated the protein-ligand interaction of STAT3 with these small molecule inhibitors by means of time-resolved electrospray ionization hydrogen-deuterium exchange mass spectrometry. Analysis of site-specific evolution of deuterium uptake induced by the complexation of STAT3 with SF-1-066 or BP-1-102 under physiological conditions enabled the mapping of the in silico predicted inhibitor binding site to the STAT3 SH2 domain. The binding of both inhibitors to the SH2 domain resulted in significant local decreases in dynamics, consistent with solvent exclusion at the inhibitor binding site and increased rigidity of the inhibitor-complexed SH2 domain. Interestingly, inhibitor binding induced hot spots of allosteric perturbations outside of the SH2 domain, manifesting mainly as increased deuterium uptake, in regions of STAT3 important for DNA binding and nuclear localization. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

Predicting permanent and transient protein-protein interfaces.

PubMed

La, David; Kong, Misun; Hoffman, William; Choi, Youn Im; Kihara, Daisuke

2013-05-01

Protein-protein interactions (PPIs) are involved in diverse functions in a cell. To optimize functional roles of interactions, proteins interact with a spectrum of binding affinities. Interactions are conventionally classified into permanent and transient, where the former denotes tight binding between proteins that result in strong complexes, whereas the latter compose of relatively weak interactions that can dissociate after binding to regulate functional activity at specific time point. Knowing the type of interactions has significant implications for understanding the nature and function of PPIs. In this study, we constructed amino acid substitution models that capture mutation patterns at permanent and transient type of protein interfaces, which were found to be different with statistical significance. Using the substitution models, we developed a novel computational method that predicts permanent and transient protein binding interfaces (PBIs) in protein surfaces. Without knowledge of the interacting partner, the method uses a single query protein structure and a multiple sequence alignment of the sequence family. Using a large dataset of permanent and transient proteins, we show that our method, BindML+, performs very well in protein interface classification. A very high area under the curve (AUC) value of 0.957 was observed when predicted protein binding sites were classified. Remarkably, near prefect accuracy was achieved with an AUC of 0.991 when actual binding sites were classified. The developed method will be also useful for protein design of permanent and transient PBIs. Copyright © 2013 Wiley Periodicals, Inc.

Discovery of Novel Nonactive Site Inhibitors of the Prothrombinase Enzyme Complex.

PubMed

Kapoor, Karan; McGill, Nicole; Peterson, Cynthia B; Meyers, Harold V; Blackburn, Michael N; Baudry, Jerome

2016-03-28

The risk of serious bleeding is a major liability of anticoagulant drugs that are active-site competitive inhibitors targeting the Factor Xa (FXa) prothrombin (PT) binding site. The present work identifies several new classes of small molecule anticoagulants that can act as nonactive site inhibitors of the prothrombinase (PTase) complex composed of FXa and Factor Va (FVa). These new classes of anticoagulants were identified, using a novel agnostic computational approach to identify previously unrecognized binding pockets at the FXa-FVa interface. From about three million docking calculations of 281,128 compounds in a conformational ensemble of FXa heavy chains identified by molecular dynamics (MD) simulations, 97 compounds and their structural analogues were selected for experimental validation, through a series of inhibition assays. The compound selection was based on their predicted binding affinities to FXa and their ability to successfully bind to multiple protein conformations while showing selectivity for particular binding sites at the FXa/FVa interface. From these, thirty-one (31) compounds were experimentally identified as nonactive site inhibitors. Concentration-based assays further identified 10 compounds represented by four small-molecule families of inhibitors that achieve dose-independent partial inhibition of PTase activity in a nonactive site-dependent and self-limiting mechanism. Several compounds were identified for their ability to bind to protein conformations only seen during MD, highlighting the importance of accounting for protein flexibility in structure-based drug discovery approaches.

Multiple grid arrangement improves ligand docking with unknown binding sites: Application to the inverse docking problem.

PubMed

Ban, Tomohiro; Ohue, Masahito; Akiyama, Yutaka

2018-04-01

The identification of comprehensive drug-target interactions is important in drug discovery. Although numerous computational methods have been developed over the years, a gold standard technique has not been established. Computational ligand docking and structure-based drug design allow researchers to predict the binding affinity between a compound and a target protein, and thus, they are often used to virtually screen compound libraries. In addition, docking techniques have also been applied to the virtual screening of target proteins (inverse docking) to predict target proteins of a drug candidate. Nevertheless, a more accurate docking method is currently required. In this study, we proposed a method in which a predicted ligand-binding site is covered by multiple grids, termed multiple grid arrangement. Notably, multiple grid arrangement facilitates the conformational search for a grid-based ligand docking software and can be applied to the state-of-the-art commercial docking software Glide (Schrödinger, LLC). We validated the proposed method by re-docking with the Astex diverse benchmark dataset and blind binding site situations, which improved the correct prediction rate of the top scoring docking pose from 27.1% to 34.1%; however, only a slight improvement in target prediction accuracy was observed with inverse docking scenarios. These findings highlight the limitations and challenges of current scoring functions and the need for more accurate docking methods. The proposed multiple grid arrangement method was implemented in Glide by modifying a cross-docking script for Glide, xglide.py. The script of our method is freely available online at http://www.bi.cs.titech.ac.jp/mga_glide/. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Virtual screening with AutoDock Vina and the common pharmacophore engine of a low diversity library of fragments and hits against the three allosteric sites of HIV integrase: participation in the SAMPL4 protein-ligand binding challenge

NASA Astrophysics Data System (ADS)

Perryman, Alexander L.; Santiago, Daniel N.; Forli, Stefano; Santos-Martins, Diogo; Olson, Arthur J.

2014-04-01

To rigorously assess the tools and protocols that can be used to understand and predict macromolecular recognition, and to gain more structural insight into three newly discovered allosteric binding sites on a critical drug target involved in the treatment of HIV infections, the Olson and Levy labs collaborated on the SAMPL4 challenge. This computational blind challenge involved predicting protein-ligand binding against the three allosteric sites of HIV integrase (IN), a viral enzyme for which two drugs (that target the active site) have been approved by the FDA. Positive control cross-docking experiments were utilized to select 13 receptor models out of an initial ensemble of 41 different crystal structures of HIV IN. These 13 models of the targets were selected using our new "Rank Difference Ratio" metric. The first stage of SAMPL4 involved using virtual screens to identify 62 active, allosteric IN inhibitors out of a set of 321 compounds. The second stage involved predicting the binding site(s) and crystallographic binding mode(s) for 57 of these inhibitors. Our team submitted four entries for the first stage that utilized: (1) AutoDock Vina (AD Vina) plus visual inspection; (2) a new common pharmacophore engine; (3) BEDAM replica exchange free energy simulations, and a Consensus approach that combined the predictions of all three strategies. Even with the SAMPL4's very challenging compound library that displayed a significantly lower amount of structural diversity than most libraries that are conventionally employed in prospective virtual screens, these approaches produced hit rates of 24, 25, 34, and 27 %, respectively, on a set with 19 % declared binders. Our only entry for the second stage challenge was based on the results of AD Vina plus visual inspection, and it ranked third place overall according to several different metrics provided by the SAMPL4 organizers. The successful results displayed by these approaches highlight the utility of the computational structure-based drug discovery tools and strategies that are being developed to advance the goals of the newly created, multi-institution, NIH-funded center called the "HIV Interaction and Viral Evolution Center".

Virtual screening with AutoDock Vina and the common pharmacophore engine of a low diversity library of fragments and hits against the three allosteric sites of HIV integrase: participation in the SAMPL4 protein-ligand binding challenge.

PubMed

Perryman, Alexander L; Santiago, Daniel N; Forli, Stefano; Martins, Diogo Santos; Olson, Arthur J

2014-04-01

To rigorously assess the tools and protocols that can be used to understand and predict macromolecular recognition, and to gain more structural insight into three newly discovered allosteric binding sites on a critical drug target involved in the treatment of HIV infections, the Olson and Levy labs collaborated on the SAMPL4 challenge. This computational blind challenge involved predicting protein-ligand binding against the three allosteric sites of HIV integrase (IN), a viral enzyme for which two drugs (that target the active site) have been approved by the FDA. Positive control cross-docking experiments were utilized to select 13 receptor models out of an initial ensemble of 41 different crystal structures of HIV IN. These 13 models of the targets were selected using our new "Rank Difference Ratio" metric. The first stage of SAMPL4 involved using virtual screens to identify 62 active, allosteric IN inhibitors out of a set of 321 compounds. The second stage involved predicting the binding site(s) and crystallographic binding mode(s) for 57 of these inhibitors. Our team submitted four entries for the first stage that utilized: (1) AutoDock Vina (AD Vina) plus visual inspection; (2) a new common pharmacophore engine; (3) BEDAM replica exchange free energy simulations, and a Consensus approach that combined the predictions of all three strategies. Even with the SAMPL4's very challenging compound library that displayed a significantly lower amount of structural diversity than most libraries that are conventionally employed in prospective virtual screens, these approaches produced hit rates of 24, 25, 34, and 27 %, respectively, on a set with 19 % declared binders. Our only entry for the second stage challenge was based on the results of AD Vina plus visual inspection, and it ranked third place overall according to several different metrics provided by the SAMPL4 organizers. The successful results displayed by these approaches highlight the utility of the computational structure-based drug discovery tools and strategies that are being developed to advance the goals of the newly created, multi-institution, NIH-funded center called the "HIV Interaction and Viral Evolution Center".

Computational approaches for de novo design and redesign of metal-binding sites on proteins.

PubMed

Akcapinar, Gunseli Bayram; Sezerman, Osman Ugur

2017-04-28

Metal ions play pivotal roles in protein structure, function and stability. The functional and structural diversity of proteins in nature expanded with the incorporation of metal ions or clusters in proteins. Approximately one-third of these proteins in the databases contain metal ions. Many biological and chemical processes in nature involve metal ion-binding proteins, aka metalloproteins. Many cellular reactions that underpin life require metalloproteins. Most of the remarkable, complex chemical transformations are catalysed by metalloenzymes. Realization of the importance of metal-binding sites in a variety of cellular events led to the advancement of various computational methods for their prediction and characterization. Furthermore, as structural and functional knowledgebase about metalloproteins is expanding with advances in computational and experimental fields, the focus of the research is now shifting towards de novo design and redesign of metalloproteins to extend nature's own diversity beyond its limits. In this review, we will focus on the computational toolbox for prediction of metal ion-binding sites, de novo metalloprotein design and redesign. We will also give examples of tailor-made artificial metalloproteins designed with the computational toolbox. © 2017 The Author(s).

Fast and automated functional classification with MED-SuMo: an application on purine-binding proteins.

PubMed

Doppelt-Azeroual, Olivia; Delfaud, François; Moriaud, Fabrice; de Brevern, Alexandre G

2010-04-01

Ligand-protein interactions are essential for biological processes, and precise characterization of protein binding sites is crucial to understand protein functions. MED-SuMo is a powerful technology to localize similar local regions on protein surfaces. Its heuristic is based on a 3D representation of macromolecules using specific surface chemical features associating chemical characteristics with geometrical properties. MED-SMA is an automated and fast method to classify binding sites. It is based on MED-SuMo technology, which builds a similarity graph, and it uses the Markov Clustering algorithm. Purine binding sites are well studied as drug targets. Here, purine binding sites of the Protein DataBank (PDB) are classified. Proteins potentially inhibited or activated through the same mechanism are gathered. Results are analyzed according to PROSITE annotations and to carefully refined functional annotations extracted from the PDB. As expected, binding sites associated with related mechanisms are gathered, for example, the Small GTPases. Nevertheless, protein kinases from different Kinome families are also found together, for example, Aurora-A and CDK2 proteins which are inhibited by the same drugs. Representative examples of different clusters are presented. The effectiveness of the MED-SMA approach is demonstrated as it gathers binding sites of proteins with similar structure-activity relationships. Moreover, an efficient new protocol associates structures absent of cocrystallized ligands to the purine clusters enabling those structures to be associated with a specific binding mechanism. Applications of this classification by binding mode similarity include target-based drug design and prediction of cross-reactivity and therefore potential toxic side effects.

Fast and automated functional classification with MED-SuMo: An application on purine-binding proteins

PubMed Central

Doppelt-Azeroual, Olivia; Delfaud, François; Moriaud, Fabrice; de Brevern, Alexandre G

2010-01-01

Ligand–protein interactions are essential for biological processes, and precise characterization of protein binding sites is crucial to understand protein functions. MED-SuMo is a powerful technology to localize similar local regions on protein surfaces. Its heuristic is based on a 3D representation of macromolecules using specific surface chemical features associating chemical characteristics with geometrical properties. MED-SMA is an automated and fast method to classify binding sites. It is based on MED-SuMo technology, which builds a similarity graph, and it uses the Markov Clustering algorithm. Purine binding sites are well studied as drug targets. Here, purine binding sites of the Protein DataBank (PDB) are classified. Proteins potentially inhibited or activated through the same mechanism are gathered. Results are analyzed according to PROSITE annotations and to carefully refined functional annotations extracted from the PDB. As expected, binding sites associated with related mechanisms are gathered, for example, the Small GTPases. Nevertheless, protein kinases from different Kinome families are also found together, for example, Aurora-A and CDK2 proteins which are inhibited by the same drugs. Representative examples of different clusters are presented. The effectiveness of the MED-SMA approach is demonstrated as it gathers binding sites of proteins with similar structure-activity relationships. Moreover, an efficient new protocol associates structures absent of cocrystallized ligands to the purine clusters enabling those structures to be associated with a specific binding mechanism. Applications of this classification by binding mode similarity include target-based drug design and prediction of cross-reactivity and therefore potential toxic side effects. PMID:20162627

Convection, diffusion and reaction in a surface-based biosensor: modeling of cooperativity and binding site competition on the surface and in the hydrogel.

PubMed

Lebedev, Konstantin; Mafé, Salvador; Stroeve, Pieter

2006-04-15

We study theoretically the transport and kinetic processes underlying the operation of a biosensor (particularly the surface plasmon sensor "Biacore") used to study the surface binding kinetics of biomolecules in solution to immobilized receptors. Unlike previous studies, we concentrate mainly on the modeling of system-specific phenomena rather than on the influence of mass transport limitations on the intrinsic kinetic rate constants determined from binding data. In the first problem, the case of two-site binding where each receptor unit on the surface can accommodate two analyte molecules on two different sites is considered. One analyte molecule always binds first to a specific site. Subsequently, the second analyte molecule can bind to the adjacent unoccupied site. In the second problem, two different analytes compete for one binding site on the same surface receptor. Finally, the third problem considers the case of positive cooperativity among bound molecules in the hydrogel using a simple mean-field approach. The transport in both the flow channel and the hydrogel phases of the biosensor is taken into account in this case (with few exceptions, most previous studies assume a simpler model in which the hydrogel is treated as a planar surface with the receptors). We consider simultaneously diffusion and convection through the flow channel together with diffusion and cooperativity binding on the surface and in the hydrogel. In each case, typical results for the concentration contours of the free and bound molecules in the flow channel and hydrogel regions are presented together with the time-dependent association/dissociation curves and reaction rates. For binding site competition, the analysis predicts overshoot phenomena.

Great interactions: How binding incorrect partners can teach us about protein recognition and function

PubMed Central

Vamparys, Lydie; Laurent, Benoist; Carbone, Alessandra

2016-01-01

ABSTRACT Protein–protein interactions play a key part in most biological processes and understanding their mechanism is a fundamental problem leading to numerous practical applications. The prediction of protein binding sites in particular is of paramount importance since proteins now represent a major class of therapeutic targets. Amongst others methods, docking simulations between two proteins known to interact can be a useful tool for the prediction of likely binding patches on a protein surface. From the analysis of the protein interfaces generated by a massive cross‐docking experiment using the 168 proteins of the Docking Benchmark 2.0, where all possible protein pairs, and not only experimental ones, have been docked together, we show that it is also possible to predict a protein's binding residues without having any prior knowledge regarding its potential interaction partners. Evaluating the performance of cross‐docking predictions using the area under the specificity‐sensitivity ROC curve (AUC) leads to an AUC value of 0.77 for the complete benchmark (compared to the 0.5 AUC value obtained for random predictions). Furthermore, a new clustering analysis performed on the binding patches that are scattered on the protein surface show that their distribution and growth will depend on the protein's functional group. Finally, in several cases, the binding‐site predictions resulting from the cross‐docking simulations will lead to the identification of an alternate interface, which corresponds to the interaction with a biomolecular partner that is not included in the original benchmark. Proteins 2016; 84:1408–1421. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. PMID:27287388

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.

Electrostatically Biased Binding of Kinesin to Microtubules

PubMed Central

Zheng, Wenjun; Alonso, Maria; Huber, Gary; Dlugosz, Maciej; McCammon, J. Andrew; Cross, Robert A.

2011-01-01

The minimum motor domain of kinesin-1 is a single head. Recent evidence suggests that such minimal motor domains generate force by a biased binding mechanism, in which they preferentially select binding sites on the microtubule that lie ahead in the progress direction of the motor. A specific molecular mechanism for biased binding has, however, so far been lacking. Here we use atomistic Brownian dynamics simulations combined with experimental mutagenesis to show that incoming kinesin heads undergo electrostatically guided diffusion-to-capture by microtubules, and that this produces directionally biased binding. Kinesin-1 heads are initially rotated by the electrostatic field so that their tubulin-binding sites face inwards, and then steered towards a plus-endwards binding site. In tethered kinesin dimers, this bias is amplified. A 3-residue sequence (RAK) in kinesin helix alpha-6 is predicted to be important for electrostatic guidance. Real-world mutagenesis of this sequence powerfully influences kinesin-driven microtubule sliding, with one mutant producing a 5-fold acceleration over wild type. We conclude that electrostatic interactions play an important role in the kinesin stepping mechanism, by biasing the diffusional association of kinesin with microtubules. PMID:22140358

Metal binding stoichiometry and isotherm choice in biosorption

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

Schiewer, S.; Wong, M.H.

1999-11-01

Seaweeds that possess a high metal binding capacity may be used as biosorbents for the removal of toxic heavy metals from wastewater. The binding of Cu and Ni by three brown algae (Sargassum, Colpomenia, Petalonia) and one green alga (Ulva) was investigated at pH 4.0 and pH 3.0. The greater binding strength of Cu is reflected in a binding constant that is about 10 times as high as that of Ni. The extent of metal binding followed the order Petalonia {approximately} Sargassum > Colpomenia > Ulva. This was caused by a decreasing number of binding sites and by much lowermore » metal binding constants for Ulva as compared to the brown algae. Three different stoichiometric assumptions are compared for describing the metal binding, which assume either that each metal ion M binds to one binding site B forming a BM complex or that a divalent metal ion M binds to two monovalent sites B forming BM{sub 0.5} or B{sub 2}M complexes, respectively. Stoichiometry plots are proposed as tools to discern the relevant binding stoichiometry. The pH effect in metal binding and the change in proton binding were well predicted for the B{sub 2}M or BM{sub 0.5} stoichiometries with the former being better for Cu and the latter preferable for Ni. Overall, the BM{sub 0.5} model is recommended because it avoids iterations.« less

Unbinding Pathways of an Agonist and an Antagonist from the 5-HT3 Receptor

PubMed Central

Thompson, A. J.; Chau, P.-L.; Chan, S. L.; Lummis, S. C. R.

2006-01-01

The binding sites of 5-HT3 and other Cys-loop receptors have been extensively studied, but there are no data on the entry and exit routes of ligands for these sites. Here we have used molecular dynamics simulations to predict the pathway for agonists and antagonists exiting from the 5-HT3 receptor binding site. The data suggest that the unbinding pathway follows a tunnel at the interface of two subunits, which is ∼8 Å long and terminates ∼20 Å above the membrane. The exit routes for an agonist (5-HT) and an antagonist (granisetron) were similar, with trajectories toward the membrane and outward from the ligand binding site. 5-HT appears to form many hydrogen bonds with residues in the unbinding pathway, and experiments show that mutating these residues significantly affects function. The location of the pathway is also supported by docking studies of granisetron, which show a potential binding site for granisetron on the unbinding route. We propose that leaving the binding pocket along this tunnel places the ligands close to the membrane and prevents their immediate reentry into the binding pocket. We anticipate similar exit pathways for other members of the Cys-loop receptor family. PMID:16387779

Prediction of TF target sites based on atomistic models of protein-DNA complexes

PubMed Central

Angarica, Vladimir Espinosa; Pérez, Abel González; Vasconcelos, Ana T; Collado-Vides, Julio; Contreras-Moreira, Bruno

2008-01-01

Background The specific recognition of genomic cis-regulatory elements by transcription factors (TFs) plays an essential role in the regulation of coordinated gene expression. Studying the mechanisms determining binding specificity in protein-DNA interactions is thus an important goal. Most current approaches for modeling TF specific recognition rely on the knowledge of large sets of cognate target sites and consider only the information contained in their primary sequence. Results Here we describe a structure-based methodology for predicting sequence motifs starting from the coordinates of a TF-DNA complex. Our algorithm combines information regarding the direct and indirect readout of DNA into an atomistic statistical model, which is used to estimate the interaction potential. We first measure the ability of our method to correctly estimate the binding specificities of eight prokaryotic and eukaryotic TFs that belong to different structural superfamilies. Secondly, the method is applied to two homology models, finding that sampling of interface side-chain rotamers remarkably improves the results. Thirdly, the algorithm is compared with a reference structural method based on contact counts, obtaining comparable predictions for the experimental complexes and more accurate sequence motifs for the homology models. Conclusion Our results demonstrate that atomic-detail structural information can be feasibly used to predict TF binding sites. The computational method presented here is universal and might be applied to other systems involving protein-DNA recognition. PMID:18922190

Computational Analysis of the Ligand Binding Site of the Extracellular ATP Receptor, DORN1

DOE PAGES

Nguyen, Cuong The; Tanaka, Kiwamu; Cao, Yangrong; ...

2016-09-01

DORN1 (also known as P2K1) is a plant receptor for extracellular ATP, which belongs to a large gene family of legume-type (L-type) lectin receptor kinases. Extracellular ATP binds to DORN1 with strong affinity through its lectin domain, and the binding triggers a variety of intracellular activities in response to biotic and abiotic stresses. However, information on the tertiary structure of the ligand binding site of DORN1is lacking, which hampers efforts to fully elucidate the mechanism of receptor action. Available data of the crystal structures from more than 50 L-type lectins enable us to perform an in silico study of molecularmore » interaction between DORN1 and ATP. In this study, we employed a computational approach to develop a tertiary structure model of the DORN1 lectin domain. A blind docking analysis demonstrated that ATP binds to a cavity made by four loops (defined as loops A B, C and D) of the DORN1 lectin domain with high affinity. In silico target docking of ATP to the DORN1 binding site predicted interaction with 12 residues, located on the four loops, via hydrogen bonds and hydrophobic interactions. The ATP binding pocket is structurally similar in location to the carbohydrate binding pocket of the canonical L-type lectins. However, four of the residues predicted to interact with ATP are not conserved between DORN1 and the other carbohydrate-binding lectins, suggesting that diversifying selection acting on these key residues may have led to the ATP binding activity of DORN1. Finally, the in silico model was validated by in vitro ATP binding assays using the purified extracellular lectin domain of wild-type DORN1, as well as mutated DORN1 lacking key ATP binding residues.« less

Computational Analysis of the Ligand Binding Site of the Extracellular ATP Receptor, DORN1

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

Nguyen, Cuong The; Tanaka, Kiwamu; Cao, Yangrong

DORN1 (also known as P2K1) is a plant receptor for extracellular ATP, which belongs to a large gene family of legume-type (L-type) lectin receptor kinases. Extracellular ATP binds to DORN1 with strong affinity through its lectin domain, and the binding triggers a variety of intracellular activities in response to biotic and abiotic stresses. However, information on the tertiary structure of the ligand binding site of DORN1is lacking, which hampers efforts to fully elucidate the mechanism of receptor action. Available data of the crystal structures from more than 50 L-type lectins enable us to perform an in silico study of molecularmore » interaction between DORN1 and ATP. In this study, we employed a computational approach to develop a tertiary structure model of the DORN1 lectin domain. A blind docking analysis demonstrated that ATP binds to a cavity made by four loops (defined as loops A B, C and D) of the DORN1 lectin domain with high affinity. In silico target docking of ATP to the DORN1 binding site predicted interaction with 12 residues, located on the four loops, via hydrogen bonds and hydrophobic interactions. The ATP binding pocket is structurally similar in location to the carbohydrate binding pocket of the canonical L-type lectins. However, four of the residues predicted to interact with ATP are not conserved between DORN1 and the other carbohydrate-binding lectins, suggesting that diversifying selection acting on these key residues may have led to the ATP binding activity of DORN1. Finally, the in silico model was validated by in vitro ATP binding assays using the purified extracellular lectin domain of wild-type DORN1, as well as mutated DORN1 lacking key ATP binding residues.« less

Structural basis for collagen recognition by the immune receptor OSCAR.

PubMed

Zhou, Long; Hinerman, Jennifer M; Blaszczyk, Michal; Miller, Jeanette L C; Conrady, Deborah G; Barrow, Alexander D; Chirgadze, Dimitri Y; Bihan, Dominique; Farndale, Richard W; Herr, Andrew B

2016-02-04

The osteoclast-associated receptor (OSCAR) is a collagen-binding immune receptor with important roles in dendritic cell maturation and activation of inflammatory monocytes as well as in osteoclastogenesis. The crystal structure of the OSCAR ectodomain is presented, both free and in complex with a consensus triple-helical peptide (THP). The structures revealed a collagen-binding site in each immunoglobulin-like domain (D1 and D2). The THP binds near a predicted collagen-binding groove in D1, but a more extensive interaction with D2 is facilitated by the unusually wide D1-D2 interdomain angle in OSCAR. Direct binding assays, combined with site-directed mutagenesis, confirm that the primary collagen-binding site in OSCAR resides in D2, in marked contrast to the related collagen receptors, glycoprotein VI (GPVI) and leukocyte-associated immunoglobulin-like receptor-1 (LAIR-1). Monomeric OSCAR D1D2 binds to the consensus THP with a KD of 28 µM measured in solution, but shows a higher affinity (KD 1.5 μM) when binding to a solid-phase THP, most likely due to an avidity effect. These data suggest a 2-stage model for the interaction of OSCAR with a collagen fibril, with transient, low-affinity interactions initiated by the membrane-distal D1, followed by firm adhesion to the primary binding site in D2. © 2016 by The American Society of Hematology.

Molecular Hybridization of Potent and Selective γ-Hydroxybutyric Acid (GHB) Ligands: Design, Synthesis, Binding Studies, and Molecular Modeling of Novel 3-Hydroxycyclopent-1-enecarboxylic Acid (HOCPCA) and trans-γ-Hydroxycrotonic Acid (T-HCA) Analogs.

PubMed

Krall, Jacob; Jensen, Claus Hatt; Bavo, Francesco; Falk-Petersen, Christina Birkedahl; Haugaard, Anne Stæhr; Vogensen, Stine Byskov; Tian, Yongsong; Nittegaard-Nielsen, Mia; Sigurdardóttir, Sara Björk; Kehler, Jan; Kongstad, Kenneth Thermann; Gloriam, David E; Clausen, Rasmus Prætorius; Harpsøe, Kasper; Wellendorph, Petrine; Frølund, Bente

2017-11-09

γ-Hydroxybutyric acid (GHB) is a neuroactive substance with specific high-affinity binding sites. To facilitate target identification and ligand optimization, we herein report a comprehensive structure-affinity relationship study for novel ligands targeting these binding sites. A molecular hybridization strategy was used based on the conformationally restricted 3-hydroxycyclopent-1-enecarboxylic acid (HOCPCA) and the linear GHB analog trans-4-hydroxycrotonic acid (T-HCA). In general, all structural modifications performed on HOCPCA led to reduced affinity. In contrast, introduction of diaromatic substituents into the 4-position of T-HCA led to high-affinity analogs (medium nanomolar K i ) for the GHB high-affinity binding sites as the most high-affinity analogs reported to date. The SAR data formed the basis for a three-dimensional pharmacophore model for GHB ligands, which identified molecular features important for high-affinity binding, with high predictive validity. These findings will be valuable in the further processes of both target characterization and ligand identification for the high-affinity GHB binding sites.

Identification and characterization of the sodium-binding site of activated protein C.

PubMed

He, X; Rezaie, A R

1999-02-19

Activated protein C (APC) requires both Ca2+ and Na+ for its optimal catalytic function. In contrast to the Ca2+-binding sites, the Na+-binding site(s) of APC has not been identified. Based on a recent study with thrombin, the 221-225 loop is predicted to be a potential Na+-binding site in APC. The sequence of this loop is not conserved in trypsin. We engineered a Gla domainless form of protein C (GDPC) in which the 221-225 loop was replaced with the corresponding loop of trypsin. We found that activated GDPC (aGDPC) required Na+ (or other alkali cations) for its amidolytic activity with dissociation constant (Kd(app)) = 44.1 +/- 8.6 mM. In the presence of Ca2+, however, the requirement for Na+ by aGDPC was eliminated, and Na+ stimulated the cleavage rate 5-6-fold with Kd(app) = 2.3 +/- 0.3 mM. Both cations were required for efficient factor Va inactivation by aGDPC. In the presence of Ca2+, the catalytic function of the mutant was independent of Na+. Unlike aGDPC, the mutant did not discriminate among monovalent cations. We conclude that the 221-225 loop is a Na+-binding site in APC and that an allosteric link between the Na+ and Ca2+ binding loops modulates the structure and function of this anticoagulant enzyme.

Quantifying the Effect of DNA Packaging on Gene Expression Level

NASA Astrophysics Data System (ADS)

Kim, Harold

2010-10-01

Gene expression, the process by which the genetic code comes alive in the form of proteins, is one of the most important biological processes in living cells, and begins when transcription factors bind to specific DNA sequences in the promoter region upstream of a gene. The relationship between gene expression output and transcription factor input which is termed the gene regulation function is specific to each promoter, and predicting this gene regulation function from the locations of transcription factor binding sites is one of the challenges in biology. In eukaryotic organisms (for example, animals, plants, fungi etc), DNA is highly compacted into nucleosomes, 147-bp segments of DNA tightly wrapped around histone protein core, and therefore, the accessibility of transcription factor binding sites depends on their locations with respect to nucleosomes - sites inside nucleosomes are less accessible than those outside nucleosomes. To understand how transcription factor binding sites contribute to gene expression in a quantitative manner, we obtain gene regulation functions of promoters with various configurations of transcription factor binding sites by using fluorescent protein reporters to measure transcription factor input and gene expression output in single yeast cells. In this talk, I will show that the affinity of a transcription factor binding site inside and outside the nucleosome controls different aspects of the gene regulation function, and explain this finding based on a mass-action kinetic model that includes competition between nucleosomes and transcription factors.

Rate constants for proteins binding to substrates with multiple binding sites using a generalized forward flux sampling expression

NASA Astrophysics Data System (ADS)

Vijaykumar, Adithya; ten Wolde, Pieter Rein; Bolhuis, Peter G.

2018-03-01

To predict the response of a biochemical system, knowledge of the intrinsic and effective rate constants of proteins is crucial. The experimentally accessible effective rate constant for association can be decomposed in a diffusion-limited rate at which proteins come into contact and an intrinsic association rate at which the proteins in contact truly bind. Reversely, when dissociating, bound proteins first separate into a contact pair with an intrinsic dissociation rate, before moving away by diffusion. While microscopic expressions exist that enable the calculation of the intrinsic and effective rate constants by conducting a single rare event simulation of the protein dissociation reaction, these expressions are only valid when the substrate has just one binding site. If the substrate has multiple binding sites, a bound enzyme can, besides dissociating into the bulk, also hop to another binding site. Calculating transition rate constants between multiple states with forward flux sampling requires a generalized rate expression. We present this expression here and use it to derive explicit expressions for all intrinsic and effective rate constants involving binding to multiple states, including rebinding. We illustrate our approach by computing the intrinsic and effective association, dissociation, and hopping rate constants for a system in which a patchy particle model enzyme binds to a substrate with two binding sites. We find that these rate constants increase as a function of the rotational diffusion constant of the particles. The hopping rate constant decreases as a function of the distance between the binding sites. Finally, we find that blocking one of the binding sites enhances both association and dissociation rate constants. Our approach and results are important for understanding and modeling association reactions in enzyme-substrate systems and other patchy particle systems and open the way for large multiscale simulations of such systems.

Cloud Computing for Protein-Ligand Binding Site Comparison

PubMed Central

2013-01-01

The proteome-wide analysis of protein-ligand binding sites and their interactions with ligands is important in structure-based drug design and in understanding ligand cross reactivity and toxicity. The well-known and commonly used software, SMAP, has been designed for 3D ligand binding site comparison and similarity searching of a structural proteome. SMAP can also predict drug side effects and reassign existing drugs to new indications. However, the computing scale of SMAP is limited. We have developed a high availability, high performance system that expands the comparison scale of SMAP. This cloud computing service, called Cloud-PLBS, combines the SMAP and Hadoop frameworks and is deployed on a virtual cloud computing platform. To handle the vast amount of experimental data on protein-ligand binding site pairs, Cloud-PLBS exploits the MapReduce paradigm as a management and parallelizing tool. Cloud-PLBS provides a web portal and scalability through which biologists can address a wide range of computer-intensive questions in biology and drug discovery. PMID:23762824

Cloud computing for protein-ligand binding site comparison.

PubMed

Hung, Che-Lun; Hua, Guan-Jie

2013-01-01

The proteome-wide analysis of protein-ligand binding sites and their interactions with ligands is important in structure-based drug design and in understanding ligand cross reactivity and toxicity. The well-known and commonly used software, SMAP, has been designed for 3D ligand binding site comparison and similarity searching of a structural proteome. SMAP can also predict drug side effects and reassign existing drugs to new indications. However, the computing scale of SMAP is limited. We have developed a high availability, high performance system that expands the comparison scale of SMAP. This cloud computing service, called Cloud-PLBS, combines the SMAP and Hadoop frameworks and is deployed on a virtual cloud computing platform. To handle the vast amount of experimental data on protein-ligand binding site pairs, Cloud-PLBS exploits the MapReduce paradigm as a management and parallelizing tool. Cloud-PLBS provides a web portal and scalability through which biologists can address a wide range of computer-intensive questions in biology and drug discovery.

Anesthetic sites and allosteric mechanisms of action on Cys-loop ligand-gated ion channels.

PubMed

Forman, Stuart A; Miller, Keith W

2011-02-01

The Cys-loop ligand-gated ion channel superfamily is a major group of neurotransmitter-activated receptors in the central and peripheral nervous system. The superfamily includes inhibitory receptors stimulated by γ-aminobutyric acid (GABA) and glycine and excitatory receptors stimulated by acetylcholine and serotonin. The first part of this review presents current evidence on the location of the anesthetic binding sites on these channels and the mechanism by which binding to these sites alters their function. The second part of the review addresses the basis for this selectivity, and the third part describes the predictive power of a quantitative allosteric model showing the actions of etomidate on γ-aminobutyric acid type A receptors (GABA(A)Rs). General anesthetics at clinical concentrations inhibit the excitatory receptors and enhance the inhibitory receptors. The location of general anesthetic binding sites on these receptors is being defined by photoactivable analogues of general anesthetics. The receptor studied most extensively is the muscle-type nicotinic acetylcholine receptor (nAChR), and progress is now being made with GABA(A)Rs. There are three categories of sites that are all in the transmembrane domain: 1) within a single subunit's four-helix bundle (intrasubunit site; halothane and etomidate on the δ subunit of AChRs); 2) between five subunits in the transmembrane conduction pore (channel lumen sites; etomidate and alcohols on nAChR); and 3) between two subunits (subunit interface sites; etomidate between the α1 and β2/3 subunits of the GABA(A)R). These binding sites function allosterically. Certain conformations of a receptor bind the anesthetic with greater affinity than others. Time-resolved photolabelling of some sites occurs within milliseconds of channel opening on the nAChR but not before. In GABA(A)Rs, electrophysiological data fit an allosteric model in which etomidate binds to and stabilizes the open state, increasing both the fraction of open channels and their lifetime. As predicted by the model, the channel-stabilizing action of etomidate is so strong that higher concentrations open the channel in the absence of agonist. The formal functional paradigm presented for etomidate may apply to other potent general anesthetic drugs. Combining photolabelling with structure-function mutational studies in the context of allosteric mechanisms should lead us to a more detailed understanding of how and where these important drugs act.

TRACTOR_DB: a database of regulatory networks in gamma-proteobacterial genomes

PubMed Central

González, Abel D.; Espinosa, Vladimir; Vasconcelos, Ana T.; Pérez-Rueda, Ernesto; Collado-Vides, Julio

2005-01-01

Experimental data on the Escherichia coli transcriptional regulatory system has been used in the past years to predict new regulatory elements (promoters, transcription factors (TFs), TFs' binding sites and operons) within its genome. As more genomes of gamma-proteobacteria are being sequenced, the prediction of these elements in a growing number of organisms has become more feasible, as a step towards the study of how different bacteria respond to environmental changes at the level of transcriptional regulation. In this work, we present TRACTOR_DB (TRAnscription FaCTORs' predicted binding sites in prokaryotic genomes), a relational database that contains computational predictions of new members of 74 regulons in 17 gamma-proteobacterial genomes. For these predictions we used a comparative genomics approach regarding which several proof-of-principle articles for large regulons have been published. TRACTOR_DB may be currently accessed at http://www.bioinfo.cu/Tractor_DB, http://www.tractor.lncc.br/ or at http://www.cifn.unam.mx/Computational_Genomics/tractorDB. Contact Email id is tractor@cifn.unam.mx. PMID:15608293

Sequence- and Interactome-Based Prediction of Viral Protein Hotspots Targeting Host Proteins: A Case Study for HIV Nef

PubMed Central

Sarmady, Mahdi; Dampier, William; Tozeren, Aydin

2011-01-01

Virus proteins alter protein pathways of the host toward the synthesis of viral particles by breaking and making edges via binding to host proteins. In this study, we developed a computational approach to predict viral sequence hotspots for binding to host proteins based on sequences of viral and host proteins and literature-curated virus-host protein interactome data. We use a motif discovery algorithm repeatedly on collections of sequences of viral proteins and immediate binding partners of their host targets and choose only those motifs that are conserved on viral sequences and highly statistically enriched among binding partners of virus protein targeted host proteins. Our results match experimental data on binding sites of Nef to host proteins such as MAPK1, VAV1, LCK, HCK, HLA-A, CD4, FYN, and GNB2L1 with high statistical significance but is a poor predictor of Nef binding sites on highly flexible, hoop-like regions. Predicted hotspots recapture CD8 cell epitopes of HIV Nef highlighting their importance in modulating virus-host interactions. Host proteins potentially targeted or outcompeted by Nef appear crowding the T cell receptor, natural killer cell mediated cytotoxicity, and neurotrophin signaling pathways. Scanning of HIV Nef motifs on multiple alignments of hepatitis C protein NS5A produces results consistent with literature, indicating the potential value of the hotspot discovery in advancing our understanding of virus-host crosstalk. PMID:21738584

The two-state dimer receptor model: a general model for receptor dimers.

PubMed

Franco, Rafael; Casadó, Vicent; Mallol, Josefa; Ferrada, Carla; Ferré, Sergi; Fuxe, Kjell; Cortés, Antoni; Ciruela, Francisco; Lluis, Carmen; Canela, Enric I

2006-06-01

Nonlinear Scatchard plots are often found for agonist binding to G-protein-coupled receptors. Because there is clear evidence of receptor dimerization, these nonlinear Scatchard plots can reflect cooperativity on agonist binding to the two binding sites in the dimer. According to this, the "two-state dimer receptor model" has been recently derived. In this article, the performance of the model has been analyzed in fitting data of agonist binding to A(1) adenosine receptors, which are an example of receptor displaying concave downward Scatchard plots. Analysis of agonist/antagonist competition data for dopamine D(1) receptors using the two-state dimer receptor model has also been performed. Although fitting to the two-state dimer receptor model was similar to the fitting to the "two-independent-site receptor model", the former is simpler, and a discrimination test selects the two-state dimer receptor model as the best. This model was also very robust in fitting data of estrogen binding to the estrogen receptor, for which Scatchard plots are concave upward. On the one hand, the model would predict the already demonstrated existence of estrogen receptor dimers. On the other hand, the model would predict that concave upward Scatchard plots reflect positive cooperativity, which can be neither predicted nor explained by assuming the existence of two different affinity states. In summary, the two-state dimer receptor model is good for fitting data of binding to dimeric receptors displaying either linear, concave upward, or concave downward Scatchard plots.

Binding and Inhibition of Spermidine Synthase from Plasmodium falciparum and Implications for In Vitro Inhibitor Testing

PubMed Central

Sprenger, Janina; Carey, Jannette; Svensson, Bo; Wengel, Verena

2016-01-01

The aminopropyltransferase spermidine synthase (SpdS) is a promising drug target in cancer and in protozoan diseases including malaria. Plasmodium falciparum SpdS (PfSpdS) transfers the aminopropyl group of decarboxylated S-adenosylmethionine (dcAdoMet) to putrescine or to spermidine to form spermidine or spermine, respectively. In an effort to understand why efficient inhibitors of PfSpdS have been elusive, the present study uses enzyme activity assays and isothermal titration calorimetry with verified or predicted inhibitors of PfSpdS to analyze the relationship between binding affinity as assessed by KD and inhibitory activity as assessed by IC50. The results show that some predicted inhibitors bind to the enzyme with high affinity but are poor inhibitors. Binding studies with PfSpdS substrates and products strongly support an ordered sequential mechanism in which the aminopropyl donor (dcAdoMet) site must be occupied before the aminopropyl acceptor (putrescine) site can be occupied. Analysis of the results also shows that the ordered sequential mechanism adequately accounts for the complex relationship between IC50 and KD and may explain the limited success of previous efforts at structure-based inhibitor design for PfSpdS. Based on PfSpdS active-site occupancy, we suggest a classification of ligands that can help to predict the KD−IC50 relations in future design of new inhibitors. The present findings may be relevant for other drug targets that follow an ordered sequential mechanism. PMID:27661085

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 .

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.

Inference of Expanded Lrp-Like Feast/Famine Transcription Factor Targets in a Non-Model Organism Using Protein Structure-Based Prediction

PubMed Central

Ashworth, Justin; Plaisier, Christopher L.; Lo, Fang Yin; Reiss, David J.; Baliga, Nitin S.

2014-01-01

Widespread microbial genome sequencing presents an opportunity to understand the gene regulatory networks of non-model organisms. This requires knowledge of the binding sites for transcription factors whose DNA-binding properties are unknown or difficult to infer. We adapted a protein structure-based method to predict the specificities and putative regulons of homologous transcription factors across diverse species. As a proof-of-concept we predicted the specificities and transcriptional target genes of divergent archaeal feast/famine regulatory proteins, several of which are encoded in the genome of Halobacterium salinarum. This was validated by comparison to experimentally determined specificities for transcription factors in distantly related extremophiles, chromatin immunoprecipitation experiments, and cis-regulatory sequence conservation across eighteen related species of halobacteria. Through this analysis we were able to infer that Halobacterium salinarum employs a divergent local trans-regulatory strategy to regulate genes (carA and carB) involved in arginine and pyrimidine metabolism, whereas Escherichia coli employs an operon. The prediction of gene regulatory binding sites using structure-based methods is useful for the inference of gene regulatory relationships in new species that are otherwise difficult to infer. PMID:25255272

Inference of expanded Lrp-like feast/famine transcription factor targets in a non-model organism using protein structure-based prediction.

PubMed

Ashworth, Justin; Plaisier, Christopher L; Lo, Fang Yin; Reiss, David J; Baliga, Nitin S

2014-01-01

Widespread microbial genome sequencing presents an opportunity to understand the gene regulatory networks of non-model organisms. This requires knowledge of the binding sites for transcription factors whose DNA-binding properties are unknown or difficult to infer. We adapted a protein structure-based method to predict the specificities and putative regulons of homologous transcription factors across diverse species. As a proof-of-concept we predicted the specificities and transcriptional target genes of divergent archaeal feast/famine regulatory proteins, several of which are encoded in the genome of Halobacterium salinarum. This was validated by comparison to experimentally determined specificities for transcription factors in distantly related extremophiles, chromatin immunoprecipitation experiments, and cis-regulatory sequence conservation across eighteen related species of halobacteria. Through this analysis we were able to infer that Halobacterium salinarum employs a divergent local trans-regulatory strategy to regulate genes (carA and carB) involved in arginine and pyrimidine metabolism, whereas Escherichia coli employs an operon. The prediction of gene regulatory binding sites using structure-based methods is useful for the inference of gene regulatory relationships in new species that are otherwise difficult to infer.

Ligand deconstruction: Why some fragment binding positions are conserved and others are not.

PubMed

Kozakov, Dima; Hall, David R; Jehle, Stefan; Jehle, Sefan; Luo, Lingqi; Ochiana, Stefan O; Jones, Elizabeth V; Pollastri, Michael; Allen, Karen N; Whitty, Adrian; Vajda, Sandor

2015-05-19

Fragment-based drug discovery (FBDD) relies on the premise that the fragment binding mode will be conserved on subsequent expansion to a larger ligand. However, no general condition has been established to explain when fragment binding modes will be conserved. We show that a remarkably simple condition can be developed in terms of how fragments coincide with binding energy hot spots--regions of the protein where interactions with a ligand contribute substantial binding free energy--the locations of which can easily be determined computationally. Because a substantial fraction of the free energy of ligand binding comes from interacting with the residues in the energetically most important hot spot, a ligand moiety that sufficiently overlaps with this region will retain its location even when other parts of the ligand are removed. This hypothesis is supported by eight case studies. The condition helps identify whether a protein is suitable for FBDD, predicts the size of fragments required for screening, and determines whether a fragment hit can be extended into a higher affinity ligand. Our results show that ligand binding sites can usefully be thought of in terms of an anchor site, which is the top-ranked hot spot and dominates the free energy of binding, surrounded by a number of weaker satellite sites that confer improved affinity and selectivity for a particular ligand and that it is the intrinsic binding potential of the protein surface that determines whether it can serve as a robust binding site for a suitably optimized ligand.

Systematic prediction of control proteins and their DNA binding sites

PubMed Central

Sorokin, Valeriy; Severinov, Konstantin; Gelfand, Mikhail S.

2009-01-01

We present here the results of a systematic bioinformatics analysis of control (C) proteins, a class of DNA-binding regulators that control time-delayed transcription of their own genes as well as restriction endonuclease genes in many type II restriction-modification systems. More than 290 C protein homologs were identified and DNA-binding sites for ∼70% of new and previously known C proteins were predicted by a combination of phylogenetic footprinting and motif searches in DNA upstream of C protein genes. Additional analysis revealed that a large proportion of C protein genes are translated from leaderless RNA, which may contribute to time-delayed nature of genetic switches operated by these proteins. Analysis of genetic contexts of newly identified C protein genes revealed that they are not exclusively associated with restriction-modification genes; numerous instances of associations with genes originating from mobile genetic elements were observed. These instances might be vestiges of ancient horizontal transfers and indicate that during evolution ancestral restriction-modification system genes were the sites of mobile elements insertions. PMID:19056824

A Conserved Steroid Binding Site in Cytochrome c Oxidase

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

Qin, Ling; Mills, Denise A.; Buhrow, Leann

2010-09-02

Micromolar concentrations of the bile salt deoxycholate are shown to rescue the activity of an inactive mutant, E101A, in the K proton pathway of Rhodobacter sphaeroides cytochrome c oxidase. A crystal structure of the wild-type enzyme reveals, as predicted, deoxycholate bound with its carboxyl group at the entrance of the K path. Since cholate is a known potent inhibitor of bovine oxidase and is seen in a similar position in the bovine structure, the crystallographically defined, conserved steroid binding site could reveal a regulatory site for steroids or structurally related molecules that act on the essential K proton path.

Genome-wide analysis of AR binding and comparison with transcript expression in primary human fetal prostate fibroblasts and cancer associated fibroblasts.

PubMed

Nash, Claire; Boufaied, Nadia; Mills, Ian G; Franco, Omar E; Hayward, Simon W; Thomson, Axel A

2017-05-05

The androgen receptor (AR) is a transcription factor, and key regulator of prostate development and cancer, which has discrete functions in stromal versus epithelial cells. AR expressed in mesenchyme is necessary and sufficient for prostate development while loss of stromal AR is predictive of prostate cancer progression. Many studies have characterized genome-wide binding of AR in prostate tumour cells but none have used primary mesenchyme or stroma. We applied ChIPseq to identify genomic AR binding sites in primary human fetal prostate fibroblasts and patient derived cancer associated fibroblasts, as well as the WPMY1 cell line overexpressing AR. We identified AR binding sites that were specific to fetal prostate fibroblasts (7534), cancer fibroblasts (629), WPMY1-AR (2561) as well as those common among all (783). Primary fibroblasts had a distinct AR binding profile versus prostate cancer cell lines and tissue, and showed a localisation to gene promoter binding sites 1 kb upstream of the transcriptional start site, as well as non-classical AR binding sequence motifs. We used RNAseq to define transcribed genes associated with AR binding sites and derived cistromes for embryonic and cancer fibroblasts as well as a cistrome common to both. These were compared to several in vivo ChIPseq and transcript expression datasets; which identified subsets of AR targets that were expressed in vivo and regulated by androgens. This analysis enabled us to deconvolute stromal AR targets active in stroma within tumour samples. Taken together, our data suggest that the AR shows significantly different genomic binding site locations in primary prostate fibroblasts compared to that observed in tumour cells. Validation of our AR binding site data with transcript expression in vitro and in vivo suggests that the AR target genes we have identified in primary fibroblasts may contribute to clinically significant and biologically important AR-regulated changes in prostate tissue. Copyright © 2017. Published by Elsevier B.V.

RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach.

PubMed

Pan, Xiaoyong; Shen, Hong-Bin

2017-02-28

RNAs play key roles in cells through the interactions with proteins known as the RNA-binding proteins (RBP) and their binding motifs enable crucial understanding of the post-transcriptional regulation of RNAs. How the RBPs correctly recognize the target RNAs and why they bind specific positions is still far from clear. Machine learning-based algorithms are widely acknowledged to be capable of speeding up this process. Although many automatic tools have been developed to predict the RNA-protein binding sites from the rapidly growing multi-resource data, e.g. sequence, structure, their domain specific features and formats have posed significant computational challenges. One of current difficulties is that the cross-source shared common knowledge is at a higher abstraction level beyond the observed data, resulting in a low efficiency of direct integration of observed data across domains. The other difficulty is how to interpret the prediction results. Existing approaches tend to terminate after outputting the potential discrete binding sites on the sequences, but how to assemble them into the meaningful binding motifs is a topic worth of further investigation. In viewing of these challenges, we propose a deep learning-based framework (iDeep) by using a novel hybrid convolutional neural network and deep belief network to predict the RBP interaction sites and motifs on RNAs. This new protocol is featured by transforming the original observed data into a high-level abstraction feature space using multiple layers of learning blocks, where the shared representations across different domains are integrated. To validate our iDeep method, we performed experiments on 31 large-scale CLIP-seq datasets, and our results show that by integrating multiple sources of data, the average AUC can be improved by 8% compared to the best single-source-based predictor; and through cross-domain knowledge integration at an abstraction level, it outperforms the state-of-the-art predictors by 6%. Besides the overall enhanced prediction performance, the convolutional neural network module embedded in iDeep is also able to automatically capture the interpretable binding motifs for RBPs. Large-scale experiments demonstrate that these mined binding motifs agree well with the experimentally verified results, suggesting iDeep is a promising approach in the real-world applications. The iDeep framework not only can achieve promising performance than the state-of-the-art predictors, but also easily capture interpretable binding motifs. iDeep is available at http://www.csbio.sjtu.edu.cn/bioinf/iDeep.

A simple and efficient method for predicting protein-protein interaction sites.

PubMed

Higa, R H; Tozzi, C L

2008-09-23

Computational methods for predicting protein-protein interaction sites based on structural data are characterized by an accuracy between 70 and 80%. Some experimental studies indicate that only a fraction of the residues, forming clusters in the center of the interaction site, are energetically important for binding. In addition, the analysis of amino acid composition has shown that residues located in the center of the interaction site can be better discriminated from the residues in other parts of the protein surface. In the present study, we implement a simple method to predict interaction site residues exploiting this fact and show that it achieves a very competitive performance compared to other methods using the same dataset and criteria for performance evaluation (success rate of 82.1%).

Prediction of Water Binding to Protein Hydration Sites with a Discrete, Semiexplicit Solvent Model.

PubMed

Setny, Piotr

2015-12-08

Buried water molecules are ubiquitous in protein structures and are found at the interface of most protein-ligand complexes. Determining their distribution and thermodynamic effect is a challenging yet important task, of great of practical value for the modeling of biomolecular structures and their interactions. In this study, we present a novel method aimed at the prediction of buried water molecules in protein structures and estimation of their binding free energies. It is based on a semiexplicit, discrete solvation model, which we previously introduced in the context of small molecule hydration. The method is applicable to all macromolecular structures described by a standard all-atom force field, and predicts complete solvent distribution within a single run with modest computational cost. We demonstrate that it indicates positions of buried hydration sites, including those filled by more than one water molecule, and accurately differentiates them from sterically accessible to water but void regions. The obtained estimates of water binding free energies are in fair agreement with reference results determined with the double decoupling method.

Computational characterization of how the VX nerve agent binds human serum paraoxonase 1.

PubMed

Fairchild, Steven Z; Peterson, Matthew W; Hamza, Adel; Zhan, Chang-Guo; Cerasoli, Douglas M; Chang, Wenling E

2011-01-01

Human serum paraoxonase 1 (HuPON1) is an enzyme that can hydrolyze various chemical warfare nerve agents including VX. A previous study has suggested that increasing HuPON1's VX hydrolysis activity one to two orders of magnitude would make the enzyme an effective countermeasure for in vivo use against VX. This study helps facilitate further engineering of HuPON1 for enhanced VX-hydrolase activity by computationally characterizing HuPON1's tertiary structure and how HuPON1 binds VX. HuPON1's structure is first predicted through two homology modeling procedures. Docking is then performed using four separate methods, and the stability of each bound conformation is analyzed through molecular dynamics and solvated interaction energy calculations. The results show that VX's lone oxygen atom has a strong preference for forming a direct electrostatic interaction with HuPON1's active site calcium ion. Various HuPON1 residues are also detected that are in close proximity to VX and are therefore potential targets for future mutagenesis studies. These include E53, H115, N168, F222, N224, L240, D269, I291, F292, and V346. Additionally, D183 was found to have a predicted pKa near physiological pH. Given D183's location in HuPON1's active site, this residue could potentially act as a proton donor or accepter during hydrolysis. The results from the binding simulations also indicate that steered molecular dynamics can potentially be used to obtain accurate binding predictions even when starting with a closed conformation of a protein's binding or active site.

An Efficient Metadynamics-Based Protocol To Model the Binding Affinity and the Transition State Ensemble of G-Protein-Coupled Receptor Ligands.

PubMed

Saleh, Noureldin; Ibrahim, Passainte; Saladino, Giorgio; Gervasio, Francesco Luigi; Clark, Timothy

2017-05-22

A generally applicable metadynamics scheme for predicting the free energy profile of ligand binding to G-protein-coupled receptors (GPCRs) is described. A common and effective collective variable (CV) has been defined using the ideally placed and highly conserved Trp6.48 as a reference point for ligand-GPCR distance measurement and the common orientation of GPCRs in the cell membrane. Using this single CV together with well-tempered multiple-walker metadynamics with a funnel-like boundary allows an efficient exploration of the entire ligand binding path from the extracellular medium to the orthosteric binding site, including vestibule and intermediate sites. The protocol can be used with X-ray structures or high-quality homology models (based on a high-quality template and after thorough refinement) for the receptor and is universally applicable to agonists, antagonists, and partial and reverse agonists. The root-mean-square error (RMSE) in predicted binding free energies for 12 diverse ligands in five receptors (a total of 23 data points) is surprisingly small (less than 1 kcal mol -1 ). The RMSEs for simulations that use receptor X-ray structures and homology models are very similar.

Degenerate Pax2 and Senseless binding motifs improve detection of low-affinity sites required for enhancer specificity

PubMed Central

Zandvakili, Arya; Campbell, Ian; Weirauch, Matthew T.

2018-01-01

Cells use thousands of regulatory sequences to recruit transcription factors (TFs) and produce specific transcriptional outcomes. Since TFs bind degenerate DNA sequences, discriminating functional TF binding sites (TFBSs) from background sequences represents a significant challenge. Here, we show that a Drosophila regulatory element that activates Epidermal Growth Factor signaling requires overlapping, low-affinity TFBSs for competing TFs (Pax2 and Senseless) to ensure cell- and segment-specific activity. Testing available TF binding models for Pax2 and Senseless, however, revealed variable accuracy in predicting such low-affinity TFBSs. To better define parameters that increase accuracy, we developed a method that systematically selects subsets of TFBSs based on predicted affinity to generate hundreds of position-weight matrices (PWMs). Counterintuitively, we found that degenerate PWMs produced from datasets depleted of high-affinity sequences were more accurate in identifying both low- and high-affinity TFBSs for the Pax2 and Senseless TFs. Taken together, these findings reveal how TFBS arrangement can be constrained by competition rather than cooperativity and that degenerate models of TF binding preferences can improve identification of biologically relevant low affinity TFBSs. PMID:29617378

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/.

CO adsorption on (111) and (100) surfaces of the Pt sub 3 Ti alloy. Evidence for parallel binding and strong activation of CO

NASA Technical Reports Server (NTRS)

Mehandru, S. P.; Anderson, A. B.; Ross, P. N.

1985-01-01

The CO adsorption on a 40 atom cluster model of the (111) surface and a 36 atom cluster model of the (100) surface of the Pt3Ti alloy was studied. Parallel binding to high coordinate sites associated with Ti and low CO bond scission barriers are predicted for both surfaces. The binding of CO to Pt sites occurs in an upright orientation. These orientations are a consequence of the nature of the CO pi donation interactions with the surface. On the Ti sites the orbitals donate to the nearly empty Ti 3d band and the antibonding counterpart orbitals are empty. On the Pt sites, however, they are in the filled Pt 5d region of the alloy band, which causes CO to bond in a vertical orientation by 5 delta donation from the carbon end.

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.

Evaluation of water displacement energetics in protein binding sites with grid cell theory.

PubMed

Gerogiokas, G; Southey, M W Y; Mazanetz, M P; Heifetz, A; Hefeitz, A; Bodkin, M; Law, R J; Michel, J

2015-04-07

Excess free energies, enthalpies and entropies of water in protein binding sites were computed via classical simulations and Grid Cell Theory (GCT) analyses for three pairs of congeneric ligands in complex with the proteins scytalone dehydratase, p38α MAP kinase and EGFR kinase respectively. Comparative analysis is of interest since the binding modes for each ligand pair differ in the displacement of one binding site water molecule, but significant variations in relative binding affinities are observed. Protocols that vary in their use of restraints on protein and ligand atoms were compared to determine the influence of protein-ligand flexibility on computed water structure and energetics, and to assess protocols for routine analyses of protein-ligand complexes. The GCT-derived binding affinities correctly reproduce experimental trends, but the magnitude of the predicted changes in binding affinities is exaggerated with respect to results from a previous Monte Carlo Free Energy Perturbation study. Breakdown of the GCT water free energies into enthalpic and entropic components indicates that enthalpy changes dominate the observed variations in energetics. In EGFR kinase GCT analyses revealed that replacement of a pyrimidine by a cyanopyridine perturbs water energetics up three hydration shells away from the ligand.

In silico modeling of the cryptic E2∼ubiquitin-binding site of E6-associated protein (E6AP)/UBE3A reveals the mechanism of polyubiquitin chain assembly.

PubMed

Ronchi, Virginia P; Kim, Elizabeth D; Summa, Christopher M; Klein, Jennifer M; Haas, Arthur L

2017-11-03

To understand the mechanism for assembly of Lys 48 -linked polyubiquitin degradation signals, we previously demonstrated that the E6AP/UBE3A ligase harbors two functionally distinct E2∼ubiquitin-binding sites: a high-affinity Site 1 required for E6AP Cys 820 ∼ubiquitin thioester formation and a canonical Site 2 responsible for subsequent chain elongation. Ordered binding to Sites 1 and 2 is here revealed by observation of UbcH7∼ubiquitin-dependent substrate inhibition of chain formation at micromolar concentrations. To understand substrate inhibition, we exploited the PatchDock algorithm to model in silico UbcH7∼ubiquitin bound to Site 1, validated by chain assembly kinetics of selected point mutants. The predicted structure buries an extensive solvent-excluded surface bringing the UbcH7∼ubiquitin thioester bond within 6 Å of the Cys 820 nucleophile. Modeling onto the active E6AP trimer suggests that substrate inhibition arises from steric hindrance between Sites 1 and 2 of adjacent subunits. Confirmation that Sites 1 and 2 function in trans was demonstrated by examining the effect of E6APC820A on wild-type activity and single-turnover pulse-chase kinetics. A cyclic proximal indexation model proposes that Sites 1 and 2 function in tandem to assemble thioester-linked polyubiquitin chains from the proximal end attached to Cys 820 before stochastic en bloc transfer to the target protein. Non-reducing SDS-PAGE confirms assembly of the predicted Cys 820 -linked 125 I-polyubiquitin thioester intermediate. Other studies suggest that Glu 550 serves as a general base to generate the Cys 820 thiolate within the low dielectric binding interface and Arg 506 functions to orient Glu 550 and to stabilize the incipient anionic transition state during thioester exchange. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Deactivation of the E. coli pH stress sensor CadC by cadaverine.

PubMed

Haneburger, Ina; Fritz, Georg; Jurkschat, Nicole; Tetsch, Larissa; Eichinger, Andreas; Skerra, Arne; Gerland, Ulrich; Jung, Kirsten

2012-11-23

At acidic pH and in the presence of lysine, the pH sensor CadC activates transcription of the cadBA operon encoding the lysine/cadaverine antiporter CadB and the lysine decarboxylase CadA. In effect, these proteins contribute to acid stress adaptation in Escherichia coli. cadBA expression is feedback inhibited by cadaverine, and a cadaverine binding site is predicted within the central cavity of the periplasmic domain of CadC on the basis of its crystallographic analysis. Our present study demonstrates that this site only partially accounts for the cadaverine response in vivo. Instead, evidence for a second, pivotal binding site was collected, which overlaps with the pH-responsive patch of amino acids located at the dimer interface of the periplasmic domain. The temporal response of the E. coli Cad module upon acid shock was measured and modeled for two CadC variants with mutated cadaverine binding sites. These studies supported a cascade-like binding and deactivation model for the CadC dimer: binding of cadaverine within the pair of central cavities triggers a conformational transition that exposes two further binding sites at the dimer interface, and the occupation of those stabilizes the inactive conformation. Altogether, these data represent a striking example for the deactivation of a pH sensor. Copyright © 2012 Elsevier Ltd. All rights reserved.

The High-Affinity Binding Site for Tricyclic Antidepressants Resides in the Outer Vestibule of the Serotonin TransporterⓈ

PubMed Central

Sarker, Subhodeep; Weissensteiner, René; Steiner, Ilka; Sitte, Harald H.; Ecker, Gerhard F.; Freissmuth, Michael; Sucic, Sonja

2015-01-01

The structure of the bacterial leucine transporter from Aquifex aeolicus (LeuTAa) has been used as a model for mammalian Na+/Cl−-dependent transporters, in particular the serotonin transporter (SERT). The crystal structure of LeuTAa liganded to tricyclic antidepressants predicts simultaneous binding of inhibitor and substrate. This is incompatible with the mutually competitive inhibition of substrates and inhibitors of SERT. We explored the binding modes of tricyclic antidepressants by homology modeling and docking studies. Two approaches were used subsequently to differentiate between three clusters of potential docking poses: 1) a diagnostic SERTY95F mutation, which greatly reduced the affinity for [3H]imipramine but did not affect substrate binding; 2) competition binding experiments in the presence and absence of carbamazepine (i.e., a tricyclic imipramine analog with a short side chain that competes with [3H]imipramine binding to SERT). Binding of releasers (para-chloroamphetamine, methylene-dioxy-methamphetamine/ecstasy) and of carbamazepine were mutually exclusive, but Dixon plots generated in the presence of carbamazepine yielded intersecting lines for serotonin, MPP+, paroxetine, and ibogaine. These observations are consistent with a model, in which 1) the tricyclic ring is docked into the outer vestibule and the dimethyl-aminopropyl side chain points to the substrate binding site; 2) binding of amphetamines creates a structural change in the inner and outer vestibule that precludes docking of the tricyclic ring; 3) simultaneous binding of ibogaine (which binds to the inward-facing conformation) and of carbamazepine is indicative of a second binding site in the inner vestibule, consistent with the pseudosymmetric fold of monoamine transporters. This may be the second low-affinity binding site for antidepressants. PMID:20829432

PhyloGibbs-MP: Module Prediction and Discriminative Motif-Finding by Gibbs Sampling

PubMed Central

Siddharthan, Rahul

2008-01-01

PhyloGibbs, our recent Gibbs-sampling motif-finder, takes phylogeny into account in detecting binding sites for transcription factors in DNA and assigns posterior probabilities to its predictions obtained by sampling the entire configuration space. Here, in an extension called PhyloGibbs-MP, we widen the scope of the program, addressing two major problems in computational regulatory genomics. First, PhyloGibbs-MP can localise predictions to small, undetermined regions of a large input sequence, thus effectively predicting cis-regulatory modules (CRMs) ab initio while simultaneously predicting binding sites in those modules—tasks that are usually done by two separate programs. PhyloGibbs-MP's performance at such ab initio CRM prediction is comparable with or superior to dedicated module-prediction software that use prior knowledge of previously characterised transcription factors. Second, PhyloGibbs-MP can predict motifs that differentiate between two (or more) different groups of regulatory regions, that is, motifs that occur preferentially in one group over the others. While other “discriminative motif-finders” have been published in the literature, PhyloGibbs-MP's implementation has some unique features and flexibility. Benchmarks on synthetic and actual genomic data show that this algorithm is successful at enhancing predictions of differentiating sites and suppressing predictions of common sites and compares with or outperforms other discriminative motif-finders on actual genomic data. Additional enhancements include significant performance and speed improvements, the ability to use “informative priors” on known transcription factors, and the ability to output annotations in a format that can be visualised with the Generic Genome Browser. In stand-alone motif-finding, PhyloGibbs-MP remains competitive, outperforming PhyloGibbs-1.0 and other programs on benchmark data. PMID:18769735

Computational study concerning the effect of some pesticides on the Proteus Mirabilis catalase activity

NASA Astrophysics Data System (ADS)

Isvoran, Adriana

2016-03-01

Assessment of the effects of the herbicides nicosulfuron and chlorsulfuron and the fungicides difenoconazole and drazoxlone upon catalase produced by soil microorganism Proteus mirabilis is performed using the molecular docking technique. The interactions of pesticides with the enzymes are predicted using SwissDock and PatchDock docking tools. There are correlations for predicted binding energy values for enzyme-pesticide complexes obtained using the two docking tools, all the considered pesticides revealing favorable binding to the enzyme, but only the herbicides bind to the catalytic site. These results suggest the inhibitory potential of chlorsulfuron and nicosulfuron on the catalase activity in soil.

Competitive Inhibition Mechanism of Acetylcholinesterase without Catalytic Active Site Interaction: Study on Functionalized C60 Nanoparticles via in Vitro and in Silico Assays.

PubMed

Liu, Yanyan; Yan, Bing; Winkler, David A; Fu, Jianjie; Zhang, Aiqian

2017-06-07

Acetylcholinesterase (AChE) activity regulation by chemical agents or, potentially, nanomaterials is important for both toxicology and pharmacology. Competitive inhibition via direct catalytic active sites (CAS) binding or noncompetitive inhibition through interference with substrate and product entering and exiting has been recognized previously as an AChE-inhibition mechanism for bespoke nanomaterials. The competitive inhibition by peripheral anionic site (PAS) interaction without CAS binding remains unexplored. Here, we proposed and verified the occurrence of a presumed competitive inhibition of AChE without CAS binding for hydrophobically functionalized C 60 nanoparticles (NPs) by employing both experimental and computational methods. The kinetic inhibition analysis distinguished six competitive inhibitors, probably targeting the PAS, from the pristine and hydrophilically modified C 60 NPs. A simple quantitative nanostructure-activity relationship (QNAR) model relating the pocket accessible length of substituent to inhibition capacity was then established to reveal how the geometry of the surface group decides the NP difference in AChE inhibition. Molecular docking identified the PAS as the potential binding site interacting with the NPs via a T-shaped plug-in mode. Specifically, the fullerene core covered the enzyme gorge as a lid through π-π stacking with Tyr72 and Trp286 in the PAS, while the hydrophobic ligands on the fullerene surface inserted into the AChE active site to provide further stability for the complexes. The modeling predicted that inhibition would be severely compromised by Tyr72 and Trp286 deletions, and the subsequent site-directed mutagenesis experiments proved this prediction. Our results demonstrate AChE competitive inhibition of NPs without CAS participation to gain further understanding of both the neurotoxicity and the curative effect of NPs.

Energetic Coupling between Ligand Binding and Dimerization in E. coli Phosphoglycerate Mutase

PubMed Central

Gardner, Nathan W.; Monroe, Lyman K.; Kihara, Daisuke; Park, Chiwook

2016-01-01

Energetic coupling of two molecular events in a protein molecule is ubiquitous in biochemical reactions mediated by proteins, such as catalysis and signal transduction. Here, we investigate energetic coupling between ligand binding and folding of a dimer using a model system that shows three-state equilibrium unfolding in an exceptional quality. The homodimeric E. coli cofactor-dependent phosphoglycerate mutase (dPGM) was found to be stabilized by ATP in a proteome-wide screen, although dPGM does not require or utilize ATP for enzymatic function. We investigated the effect of ATP on the thermodynamic stability of dPGM using equilibrium unfolding. In the absence of ATP, dPGM populates a partially unfolded, monomeric intermediate during equilibrium unfolding. However, addition of 1.0 mM ATP drastically reduces the population of the intermediate by selectively stabilizing the native dimer. Using a computational ligand docking method, we predicted ATP binds to the active site of the enzyme using the triphosphate group. By performing equilibrium unfolding and isothermal titration calorimetry with active-site variants of dPGM, we confirmed that active-site residues are involved in ATP binding. Our findings show that ATP promotes dimerization of the protein by binding to the active site, which is distal from the dimer interface. This cooperativity suggests an energetic coupling between the active-site and the dimer interface. We also propose a structural link to explain how ligand binding to the active site is energetically coupled with dimerization. PMID:26919584

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.

Binding Specificity of Two PBPs in the Yellow Peach Moth Conogethes punctiferalis (Guenée)

PubMed Central

Ge, Xing; Ahmed, Tofael; Zhang, Tiantao; Wang, Zhenying; He, Kanglai; Bai, Shuxiong

2018-01-01

Pheromone binding proteins (PBPs) play an important role in olfaction of insects by transporting sex pheromones across the sensillum lymph to odorant receptors. To obtain a better understanding of the molecular basis between PBPs and semiochemicals, we have cloned, expressed, and purified two PBPs (CpunPBP2 and CpunPBP5) from the antennae of Conogethes punctiferalis. Fluorescence competitive binding assays were used to investigate binding affinities of CpunPBP2 and CpunPBP5 to sex pheromone and volatiles. Results indicate both CpunPBP2 and CpunPBP5 bind sex pheromones E10-16:Ald, Z10-16:Ald and hexadecanal with higher affinities. In addition, CpunPBP2 and CpunPBP5 also could bind some odorants, such as 1-tetradecanol, trans-caryopyllene, farnesene, and β-farnesene. Homology modeling to predict 3D structure and molecular docking to predict key binding sites were used, to better understand interactions of CpunPBP2 and CpunPBP5 with sex pheromones E10-16:Ald and Z10-16:Ald. According to the results, Phe9, Phe33, Ser53, and Phe115 were key binding sites predicted for CpunPBP2, as were Ser9, Phe12, Val115, and Arg120 for CpunPBP5. Binding affinities of four mutants of CpunPBP2 and four mutants of CpunPBP5 with the two sex pheromones were investigated by fluorescence competitive binding assays. Results indicate that single nucleotides mutation may affect interactions between PBPs and sex pheromones. Expression levels of CpunPBP2 and CpunPBP5 in different tissues were evaluated using qPCR. Results show that CpunPBP2 and CpunPBP5 were largely amplified in the antennae, with low expression levels in other tissues. CpunPBP2 was expressed mainly in male antennae, whereas CpunPBP5 was expressed mainly in female antennae. These results provide new insights into understanding the recognition between PBPs and ligands. PMID:29666585

A method for predicting individual residue contributions to enzyme specificity and binding-site energies, and its application to MTH1.

PubMed

Stewart, James J P

2016-11-01

A new method for predicting the energy contributions to substrate binding and to specificity has been developed. Conventional global optimization methods do not permit the subtle effects responsible for these properties to be modeled with sufficient precision to allow confidence to be placed in the results, but by making simple alterations to the model, the precisions of the various energies involved can be improved from about ±2 kcal mol -1 to ±0.1 kcal mol -1 . This technique was applied to the oxidized nucleotide pyrophosphohydrolase enzyme MTH1. MTH1 is unusual in that the binding and reaction sites are well separated-an advantage from a computational chemistry perspective, as it allows the energetics involved in docking to be modeled without the need to consider any issues relating to reaction mechanisms. In this study, two types of energy terms were investigated: the noncovalent interactions between the binding site and the substrate, and those responsible for discriminating between the oxidized nucleotide 8-oxo-dGTP and the normal dGTP. Both of these were investigated using the semiempirical method PM7 in the program MOPAC. The contributions of the individual residues to both the binding energy and the specificity of MTH1 were calculated by simulating the effect of mutations. Where comparisons were possible, all calculated results were in agreement with experimental observations. This technique provides fresh insight into the binding mechanism that enzymes use for discriminating between possible substrates.

Mojo Hand, a TALEN design tool for genome editing applications.

PubMed

Neff, Kevin L; Argue, David P; Ma, Alvin C; Lee, Han B; Clark, Karl J; Ekker, Stephen C

2013-01-16

Recent studies of transcription activator-like (TAL) effector domains fused to nucleases (TALENs) demonstrate enormous potential for genome editing. Effective design of TALENs requires a combination of selecting appropriate genetic features, finding pairs of binding sites based on a consensus sequence, and, in some cases, identifying endogenous restriction sites for downstream molecular genetic applications. We present the web-based program Mojo Hand for designing TAL and TALEN constructs for genome editing applications (http://www.talendesign.org). We describe the algorithm and its implementation. The features of Mojo Hand include (1) automatic download of genomic data from the National Center for Biotechnology Information, (2) analysis of any DNA sequence to reveal pairs of binding sites based on a user-defined template, (3) selection of restriction-enzyme recognition sites in the spacer between the TAL monomer binding sites including options for the selection of restriction enzyme suppliers, and (4) output files designed for subsequent TALEN construction using the Golden Gate assembly method. Mojo Hand enables the rapid identification of TAL binding sites for use in TALEN design. The assembly of TALEN constructs, is also simplified by using the TAL-site prediction program in conjunction with a spreadsheet management aid of reagent concentrations and TALEN formulation. Mojo Hand enables scientists to more rapidly deploy TALENs for genome editing applications.

Discovery of small molecule inhibitors of ubiquitin-like poxvirus proteinase I7L using homology modeling and covalent docking approaches

NASA Astrophysics Data System (ADS)

Katritch, Vsevolod; Byrd, Chelsea M.; Tseitin, Vladimir; Dai, Dongcheng; Raush, Eugene; Totrov, Maxim; Abagyan, Ruben; Jordan, Robert; Hruby, Dennis E.

2007-10-01

Essential for viral replication and highly conserved among poxviridae, the vaccinia virus I7L ubiquitin-like proteinase (ULP) is an attractive target for development of smallpox antiviral drugs. At the same time, the I7L proteinase exemplifies several interesting challenges from the rational drug design perspective. In the absence of a published I7L X-ray structure, we have built a detailed 3D model of the I7L ligand binding site (S2-S2' pocket) based on exceptionally high structural conservation of this site in proteases of the ULP family. The accuracy and limitations of this model were assessed through comparative analysis of available X-ray structures of ULPs, as well as energy based conformational modeling. The 3D model of the I7L ligand binding site was used to perform covalent docking and VLS of a comprehensive library of about 230,000 available ketone and aldehyde compounds. Out of 456 predicted ligands, 97 inhibitors of I7L proteinase activity were confirmed in biochemical assays (˜20% overall hit rate). These experimental results both validate our I7L ligand binding model and provide initial leads for rational optimization of poxvirus I7L proteinase inhibitors. Thus, fragments predicted to bind in the prime portion of the active site can be combined with fragments on non-prime side to yield compounds with improved activity and specificity.

Computational analysis of histidine mutations on the structural stability of human tyrosinases leading to albinism insurgence.

PubMed

Hassan, Mubashir; Abbas, Qamar; Raza, Hussain; Moustafa, Ahmed A; Seo, Sung-Yum

2017-07-25

Misfolding and structural alteration in proteins lead to serious malfunctions and cause various diseases in humans. Mutations at the active binding site in tyrosinase impair structural stability and cause lethal albinism by abolishing copper binding. To evaluate the histidine mutational effect, all mutated structures were built using homology modelling. The protein sequence was retrieved from the UniProt database, and 3D models of original and mutated human tyrosinase sequences were predicted by changing the residual positions within the target sequence separately. Structural and mutational analyses were performed to interpret the significance of mutated residues (N 180 , R 202 , Q 202 , R 211 , Y 363 , R 367 , Y 367 and D 390 ) at the active binding site of tyrosinases. CSpritz analysis depicted that 23.25% residues actively participate in the instability of tyrosinase. The accuracy of predicted models was confirmed through online servers ProSA-web, ERRAT score and VERIFY 3D values. The theoretical pI and GRAVY generated results also showed the accuracy of the predicted models. The CCA negative correlation results depicted that the replacement of mutated residues at His within the active binding site disturbs the structural stability of tyrosinases. The predicted CCA scores of Tyr 367 (-0.079) and Q/R 202 (0.032) revealed that both mutations have more potential to disturb the structural stability. MD simulation analyses of all predicted models justified that Gln 202 , Arg 202 , Tyr 367 and D 390 replacement made the protein structures more susceptible to destabilization. Mutational results showed that the replacement of His with Q/R 202 and Y/R 363 has a lethal effect and may cause melanin associated diseases such as OCA1. Taken together, our computational analysis depicts that the mutated residues such as Q/R 202 and Y/R 363 actively participate in instability and misfolding of tyrosinases, which may govern OCA1 through disturbing the melanin biosynthetic pathway.

A Mechanism-Based Model for the Prediction of the Metabolic Sites of Steroids Mediated by Cytochrome P450 3A4.

PubMed

Dai, Zi-Ru; Ai, Chun-Zhi; Ge, Guang-Bo; He, Yu-Qi; Wu, Jing-Jing; Wang, Jia-Yue; Man, Hui-Zi; Jia, Yan; Yang, Ling

2015-06-30

Early prediction of xenobiotic metabolism is essential for drug discovery and development. As the most important human drug-metabolizing enzyme, cytochrome P450 3A4 has a large active cavity and metabolizes a broad spectrum of substrates. The poor substrate specificity of CYP3A4 makes it a huge challenge to predict the metabolic site(s) on its substrates. This study aimed to develop a mechanism-based prediction model based on two key parameters, including the binding conformation and the reaction activity of ligands, which could reveal the process of real metabolic reaction(s) and the site(s) of modification. The newly established model was applied to predict the metabolic site(s) of steroids; a class of CYP3A4-preferred substrates. 38 steroids and 12 non-steroids were randomly divided into training and test sets. Two major metabolic reactions, including aliphatic hydroxylation and N-dealkylation, were involved in this study. At least one of the top three predicted metabolic sites was validated by the experimental data. The overall accuracy for the training and test were 82.14% and 86.36%, respectively. In summary, a mechanism-based prediction model was established for the first time, which could be used to predict the metabolic site(s) of CYP3A4 on steroids with high predictive accuracy.

Designing and Testing of Novel Taxanes to Probe the Highly Complex Mechanisms by Which Taxanes Bind to Microtubules and Cause Cytotoxicity to Cancer Cells

PubMed Central

St. George, Marc; Ayoub, Ahmed T.; Banerjee, Asok; Churchill, Cassandra D. M.; Winter, Philip; Klobukowski, Mariusz; Cass, Carol E.; Ludueña, Richard F.; Tuszynski, Jack A.; Damaraju, Sambasivarao

2015-01-01

Our previous work identified an intermediate binding site for taxanes in the microtubule nanopore. The goal of this study was to test derivatives of paclitaxel designed to bind to this intermediate site differentially depending on the isotype of β-tubulin. Since β-tubulin isotypes have tissue-dependent expression—specifically, the βIII isotype is very abundant in aggressive tumors and much less common in normal tissues—this is expected to lead to tubulin targeted drugs that are more efficacious and have less side effects. Seven derivatives of paclitaxel were designed and four of these were amenable for synthesis in sufficient purity and yield for further testing in breast cancer model cell lines. None of the derivatives studied were superior to currently used taxanes, however computer simulations provided insights into the activity of the derivatives. Our results suggest that neither binding to the intermediate binding site nor the final binding site is sufficient to explain the activities of the derivative taxanes studied. These findings highlight the need to iteratively improve on the design of taxanes based on their activity in model systems. Knowledge gained on the ability of the engineered drugs to bind to targets and bring about activity in a predictable manner is a step towards personalizing therapies. PMID:26052950

Ligand deconstruction: Why some fragment binding positions are conserved and others are not

PubMed Central

Kozakov, Dima; Hall, David R.; Jehle, Stefan; Luo, Lingqi; Ochiana, Stefan O.; Jones, Elizabeth V.; Pollastri, Michael; Allen, Karen N.; Whitty, Adrian; Vajda, Sandor

2015-01-01

Fragment-based drug discovery (FBDD) relies on the premise that the fragment binding mode will be conserved on subsequent expansion to a larger ligand. However, no general condition has been established to explain when fragment binding modes will be conserved. We show that a remarkably simple condition can be developed in terms of how fragments coincide with binding energy hot spots—regions of the protein where interactions with a ligand contribute substantial binding free energy—the locations of which can easily be determined computationally. Because a substantial fraction of the free energy of ligand binding comes from interacting with the residues in the energetically most important hot spot, a ligand moiety that sufficiently overlaps with this region will retain its location even when other parts of the ligand are removed. This hypothesis is supported by eight case studies. The condition helps identify whether a protein is suitable for FBDD, predicts the size of fragments required for screening, and determines whether a fragment hit can be extended into a higher affinity ligand. Our results show that ligand binding sites can usefully be thought of in terms of an anchor site, which is the top-ranked hot spot and dominates the free energy of binding, surrounded by a number of weaker satellite sites that confer improved affinity and selectivity for a particular ligand and that it is the intrinsic binding potential of the protein surface that determines whether it can serve as a robust binding site for a suitably optimized ligand. PMID:25918377

Structural study of the Fox-1 RRM protein hydration reveals a role for key water molecules in RRM-RNA recognition

PubMed Central

Blatter, Markus; Cléry, Antoine; Damberger, Fred F.

2017-01-01

Abstract The Fox-1 RNA recognition motif (RRM) domain is an important member of the RRM protein family. We report a 1.8 Å X-ray structure of the free Fox-1 containing six distinct monomers. We use this and the nuclear magnetic resonance (NMR) structure of the Fox-1 protein/RNA complex for molecular dynamics (MD) analyses of the structured hydration. The individual monomers of the X-ray structure show diverse hydration patterns, however, MD excellently reproduces the most occupied hydration sites. Simulations of the protein/RNA complex show hydration consistent with the isolated protein complemented by hydration sites specific to the protein/RNA interface. MD predicts intricate hydration sites with water-binding times extending up to hundreds of nanoseconds. We characterize two of them using NMR spectroscopy, RNA binding with switchSENSE and free-energy calculations of mutant proteins. Both hydration sites are experimentally confirmed and their abolishment reduces the binding free-energy. A quantitative agreement between theory and experiment is achieved for the S155A substitution but not for the S122A mutant. The S155 hydration site is evolutionarily conserved within the RRM domains. In conclusion, MD is an effective tool for predicting and interpreting the hydration patterns of protein/RNA complexes. Hydration is not easily detectable in NMR experiments but can affect stability of protein/RNA complexes. PMID:28505313

Tb3+-cleavage assays reveal specific Mg2+ binding sites necessary to pre-fold the btuB riboswitch for AdoCbl binding

NASA Astrophysics Data System (ADS)

Choudhary, Pallavi K.; Gallo, Sofia; Sigel, Roland K. O.

2017-03-01

Riboswitches are RNA elements that bind specific metabolites in order to regulate the gene expression involved in controlling the cellular concentration of the respective molecule or ion. Ligand recognition is mostly facilitated by Mg2+ mediated pre-organization of the riboswitch to an active tertiary fold. To predict these specific Mg2+ induced tertiary interactions of the btuB riboswitch from E. coli, we here report Mg2+ binding pockets in its aptameric part in both, the ligand-free and the ligand-bound form. An ensemble of weak and strong metal ion binding sites distributed over the entire aptamer was detected by terbium(III) cleavage assays, Tb3+ being an established Mg2+ mimic. Interestingly many of the Mn+ (n = 2 or 3) binding sites involve conserved bases within the class of coenzyme B12-binding riboswitches. Comparison with the published crystal structure of the coenzyme B12 riboswitch of S. thermophilum aided in identifying a common set of Mn+ binding sites that might be crucial for tertiary interactions involved in the organization of the aptamer. Our results suggest that Mn+ binding at strategic locations of the btuB riboswitch indeed facilitates the assembly of the binding pocket needed for ligand recognition. Binding of the specific ligand, coenzyme B12 (AdoCbl), to the btuB aptamer does however not lead to drastic alterations of these Mn+ binding cores, indicating the lack of a major rearrangement within the three-dimensional structure of the RNA. This finding is strengthened by Tb3+ mediated footprints of the riboswitch's structure in its ligand-free and ligand-bound state indicating that AdoCbl indeed induces local changes rather than a global structural rearrangement.

Comparison of S. cerevisiae F-BAR domain structures reveals a conserved inositol phosphate binding site

PubMed Central

Moravcevic, Katarina; Alvarado, Diego; Schmitz, Karl R.; Kenniston, Jon A.; Mendrola, Jeannine M.; Ferguson, Kathryn M.; Lemmon, Mark A.

2015-01-01

SUMMARY F-BAR domains control membrane interactions in endocytosis, cytokinesis, and cell signaling. Although generally thought to bind curved membranes containing negatively charged phospholipids, numerous functional studies argue that differences in lipid-binding selectivities of F-BAR domains are functionally important. Here, we compare membrane-binding properties of the S. cerevisiae F-BAR domains in vitro and in vivo. Whereas some F-BAR domains (such as Bzz1p and Hof1p F-BARs) bind equally well to all phospholipids, the F-BAR domain from the RhoGAP Rgd1p preferentially binds phosphoinositides. We determined X-ray crystal structures of F-BAR domains from Hof1p and Rgd1p, the latter bound to an inositol phosphate. The structures explain phospholipid-binding selectivity differences, and reveal an F-BAR phosphoinositide binding site that is fully conserved in a mammalian RhoGAP called Gmip, and is partly retained in certain other F-BAR domains. Our findings reveal previously unappreciated determinants of F-BAR domain lipid-binding specificity, and provide a basis for its prediction from sequence. PMID:25620000

Searching for protein binding sites from Molecular Dynamics simulations and paramagnetic fragment-based NMR studies.

PubMed

Bernini, Andrea; Henrici De Angelis, Lucia; Morandi, Edoardo; Spiga, Ottavia; Santucci, Annalisa; Assfalg, Michael; Molinari, Henriette; Pillozzi, Serena; Arcangeli, Annarosa; Niccolai, Neri

2014-03-01

Hotspot delineation on protein surfaces represents a fundamental step for targeting protein-protein interfaces. Disruptors of protein-protein interactions can be designed provided that the sterical features of binding pockets, including the transient ones, can be defined. Molecular Dynamics, MD, simulations have been used as a reliable framework for identifying transient pocket openings on the protein surface. Accessible surface area and intramolecular H-bond involvement of protein backbone amides are proposed as descriptors for characterizing binding pocket occurrence and evolution along MD trajectories. TEMPOL induced paramagnetic perturbations on (1)H-(15)N HSQC signals of protein backbone amides have been analyzed as a fragment-based search for surface hotspots, in order to validate MD predicted pockets. This procedure has been applied to CXCL12, a small chemokine responsible for tumor progression and proliferation. From combined analysis of MD data and paramagnetic profiles, two CXCL12 sites suitable for the binding of small molecules were identified. One of these sites is the already well characterized CXCL12 region involved in the binding to CXCR4 receptor. The other one is a transient pocket predicted by Molecular Dynamics simulations, which could not be observed from static analysis of CXCL12 PDB structures. The present results indicate how TEMPOL, instrumental in identifying this transient pocket, can be a powerful tool to delineate minor conformations which can be highly relevant in dynamic discovery of antitumoral drugs. Copyright © 2013 Elsevier B.V. All rights reserved.

B 36N 36 fullerene-like nanocages: A novel material for drug delivery

NASA Astrophysics Data System (ADS)

Ganji, M. D.; Yazdani, H.; Mirnejad, A.

2010-07-01

We study interaction between B 36N 36 fullerene-like nanocage and glycine amino acid from the first- principles. Binding energy is calculated and glycine binding to the pure C 60 fullerene is compared. We also analyze the electronic structure and charge Mulliken population for the energetically most favorable complexes. Our results indicate that glycine can form stable bindings with B 36N 36 nanocage via their carbonyl oxygen (O) active site while, the C 60 fullerene might be unable to form stable bindings to glycine amino acid via their active sites, which is consistence with recent experimental and theoretical investigations. Thus, we arrive at the prediction that the B 36N 36 nanocage can be implemented as a novel material for drug delivery applications.

Identification of a 3rd Na+ Binding Site of the Glycine Transporter, GlyT2.

PubMed

Subramanian, Nandhitha; Scopelitti, Amanda J; Carland, Jane E; Ryan, Renae M; O'Mara, Megan L; Vandenberg, Robert J

2016-01-01

The Na+/Cl- dependent glycine transporters GlyT1 and GlyT2 regulate synaptic glycine concentrations. Glycine transport by GlyT2 is coupled to the co-transport of three Na+ ions, whereas transport by GlyT1 is coupled to the co-transport of only two Na+ ions. These differences in ion-flux coupling determine their respective concentrating capacities and have a direct bearing on their functional roles in synaptic transmission. The crystal structures of the closely related bacterial Na+-dependent leucine transporter, LeuTAa, and the Drosophila dopamine transporter, dDAT, have allowed prediction of two Na+ binding sites in GlyT2, but the physical location of the third Na+ site in GlyT2 is unknown. A bacterial betaine transporter, BetP, has also been crystallized and shows structural similarity to LeuTAa. Although betaine transport by BetP is coupled to the co-transport of two Na+ ions, the first Na+ site is not conserved between BetP and LeuTAa, the so called Na1' site. We hypothesized that the third Na+ binding site (Na3 site) of GlyT2 corresponds to the BetP Na1' binding site. To identify the Na3 binding site of GlyT2, we performed molecular dynamics (MD) simulations. Surprisingly, a Na+ placed at the location consistent with the Na1' site of BetP spontaneously dissociated from its initial location and bound instead to a novel Na3 site. Using a combination of MD simulations of a comparative model of GlyT2 together with an analysis of the functional properties of wild type and mutant GlyTs we have identified an electrostatically favorable novel third Na+ binding site in GlyT2 formed by Trp263 and Met276 in TM3, Ala481 in TM6 and Glu648 in TM10.

Identification of a 3rd Na+ Binding Site of the Glycine Transporter, GlyT2

PubMed Central

Subramanian, Nandhitha; Scopelitti, Amanda J.; Carland, Jane E.; Ryan, Renae M.; O’Mara, Megan L.; Vandenberg, Robert J.

2016-01-01

The Na+/Cl- dependent glycine transporters GlyT1 and GlyT2 regulate synaptic glycine concentrations. Glycine transport by GlyT2 is coupled to the co-transport of three Na+ ions, whereas transport by GlyT1 is coupled to the co-transport of only two Na+ ions. These differences in ion-flux coupling determine their respective concentrating capacities and have a direct bearing on their functional roles in synaptic transmission. The crystal structures of the closely related bacterial Na+-dependent leucine transporter, LeuTAa, and the Drosophila dopamine transporter, dDAT, have allowed prediction of two Na+ binding sites in GlyT2, but the physical location of the third Na+ site in GlyT2 is unknown. A bacterial betaine transporter, BetP, has also been crystallized and shows structural similarity to LeuTAa. Although betaine transport by BetP is coupled to the co-transport of two Na+ ions, the first Na+ site is not conserved between BetP and LeuTAa, the so called Na1' site. We hypothesized that the third Na+ binding site (Na3 site) of GlyT2 corresponds to the BetP Na1' binding site. To identify the Na3 binding site of GlyT2, we performed molecular dynamics (MD) simulations. Surprisingly, a Na+ placed at the location consistent with the Na1' site of BetP spontaneously dissociated from its initial location and bound instead to a novel Na3 site. Using a combination of MD simulations of a comparative model of GlyT2 together with an analysis of the functional properties of wild type and mutant GlyTs we have identified an electrostatically favorable novel third Na+ binding site in GlyT2 formed by Trp263 and Met276 in TM3, Ala481 in TM6 and Glu648 in TM10. PMID:27337045

An integrated workflow for analysis of ChIP-chip data.

PubMed

Weigelt, Karin; Moehle, Christoph; Stempfl, Thomas; Weber, Bernhard; Langmann, Thomas

2008-08-01

Although ChIP-chip is a powerful tool for genome-wide discovery of transcription factor target genes, the steps involving raw data analysis, identification of promoters, and correlation with binding sites are still laborious processes. Therefore, we report an integrated workflow for the analysis of promoter tiling arrays with the Genomatix ChipInspector system. We compare this tool with open-source software packages to identify PU.1 regulated genes in mouse macrophages. Our results suggest that ChipInspector data analysis, comparative genomics for binding site prediction, and pathway/network modeling significantly facilitate and enhance whole-genome promoter profiling to reveal in vivo sites of transcription factor-DNA interactions.

Widespread Site-Dependent Buffering of Human Regulatory Polymorphism

PubMed Central

Kutyavin, Tanya; Stamatoyannopoulos, John A.

2012-01-01

The average individual is expected to harbor thousands of variants within non-coding genomic regions involved in gene regulation. However, it is currently not possible to interpret reliably the functional consequences of genetic variation within any given transcription factor recognition sequence. To address this, we comprehensively analyzed heritable genome-wide binding patterns of a major sequence-specific regulator (CTCF) in relation to genetic variability in binding site sequences across a multi-generational pedigree. We localized and quantified CTCF occupancy by ChIP-seq in 12 related and unrelated individuals spanning three generations, followed by comprehensive targeted resequencing of the entire CTCF–binding landscape across all individuals. We identified hundreds of variants with reproducible quantitative effects on CTCF occupancy (both positive and negative). While these effects paralleled protein–DNA recognition energetics when averaged, they were extensively buffered by striking local context dependencies. In the significant majority of cases buffering was complete, resulting in silent variants spanning every position within the DNA recognition interface irrespective of level of binding energy or evolutionary constraint. The prevalence of complex partial or complete buffering effects severely constrained the ability to predict reliably the impact of variation within any given binding site instance. Surprisingly, 40% of variants that increased CTCF occupancy occurred at positions of human–chimp divergence, challenging the expectation that the vast majority of functional regulatory variants should be deleterious. Our results suggest that, even in the presence of “perfect” genetic information afforded by resequencing and parallel studies in multiple related individuals, genomic site-specific prediction of the consequences of individual variation in regulatory DNA will require systematic coupling with empirical functional genomic measurements. PMID:22457641

Computational scheme for the prediction of metal ion binding by a soil fulvic acid

USGS Publications Warehouse

Marinsky, J.A.; Reddy, M.M.; Ephraim, J.H.; Mathuthu, A.S.

1995-01-01

The dissociation and metal ion binding properties of a soil fulvic acid have been characterized. Information thus gained was used to compensate for salt and site heterogeneity effects in metal ion complexation by the fulvic acid. An earlier computational scheme has been modified by incorporating an additional step which improves the accuracy of metal ion speciation estimates. An algorithm is employed for the prediction of metal ion binding by organic acid constituents of natural waters (once the organic acid is characterized in terms of functional group identity and abundance). The approach discussed here, currently used with a spreadsheet program on a personal computer, is conceptually envisaged to be compatible with computer programs available for ion binding by inorganic ligands in natural waters.

Polymorphisms A387P in thrombospondin-4 and N700S in thrombospondin-1 perturb calcium binding sites.

PubMed

Stenina, Olga I; Ustinov, Valentin; Krukovets, Irene; Marinic, Tina; Topol, Eric J; Plow, Edward F

2005-11-01

Recent genetic studies have associated members of the thrombospondin (TSP) gene family with premature cardiovascular disease. The disease-associated polymorphisms lead to single amino acid changes in TSP-4 (A387P) and TSP-1 (N700S). These substitutions reside in adjacent domains of these highly homologous proteins. Secondary structural predictive programs and the homology of the domains harboring these amino acid substitutions to those in other proteins pointed to potential alterations of putative Ca2+ binding sites that reside in close proximity to the polymorphic amino acids. Since Ca2+ binding is critical for the structure and function of TSP family members, direct evidence for differences in Ca2+ binding by the polymorphic forms was sought. Using synthetic peptides and purified recombinant variant fragments bearing the amino acid substitutions, we measured differences in Tb3+ luminescence as an index of Ca2+ binding. The Tb3+ binding constants placed the TSP-1 region affected by N700S polymorphism among other high-affinity Ca2+ binding sites. The affinity of Ca2+ binding was lower for peptides (3.5-fold) and recombinant fragments (10-fold) containing the S700 vs. the N700 form. In TSP-4, the P387 form acquired an additional Ca2+ binding site absent in the A387 form. The results of our study suggest that both substitutions (A387P in TSP-4 and N700S in TSP-1) alter Ca2+ binding properties. Since these substitutions exert the opposite effects on Ca2+ binding, a decrease in TSP-1 and an increase in TSP-4, the two TSP variants are likely to influence cardiovascular functions in distinct but yet pathogenic ways.

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

Hsu, Hao-Chi; Tong, Simon; Zhou, Yuchen

Human FABP5 and FABP7 are intracellular endocannabinoid transporters. SBFI-26 is an α-truxillic acid 1-naphthyl monoester that competitively inhibits the activities of FABP5 and FABP7 and produces antinociceptive and anti-inflammatory effects in mice. The synthesis of SBFI-26 yields several stereoisomers, and it is not known how the inhibitor binds the transporters. Here we report co-crystal structures of SBFI-26 in complex with human FABP5 and FABP7 at 2.2 and 1.9 Å resolution, respectively. We found that only (S)-SBFI-26 was present in the crystal structures. The inhibitor largely mimics the fatty acid binding pattern, but it also has several unique interactions. Notably, themore » FABP7 complex corroborates key aspects of the ligand binding pose at the canonical site previously predicted by virtual screening. In FABP5, SBFI-26 was unexpectedly found to bind at the substrate entry portal region in addition to binding at the canonical ligand-binding pocket. Our structural and binding energy analyses indicate that both R and S forms appear to bind the transporter equally well. We suggest that the S enantiomer observed in the crystal structures may be a result of the crystallization process selectively incorporating the (S)-SBFI-26–FABP complexes into the growing lattice, or that the S enantiomer may bind to the portal site more rapidly than to the canonical site, leading to an increased local concentration of the S enantiomer for binding to the canonical site. Our work reveals two binding poses of SBFI-26 in its target transporters. This knowledge will guide the development of more potent FABP inhibitors based upon the SBFI-26 scaffold.« less

Small Molecule Regulation of Protein Conformation by Binding in the Flap of HIV Protease

PubMed Central

Tiefenbrunn, Theresa; Forli, Stefano; Baksh, Michael M.; Chang, Max W.; Happer, Meaghan; Lin, Ying-Chuan; Perryman, Alexander L.; Rhee, Jin-Kyu; Torbett, Bruce E.; Olson, Arthur J.; Elder, John H.; Finn, M. G.; Stout, C. David

2013-01-01

The fragment indole-6-carboxylic acid (1F1), previously identified as a flap site binder in a fragment-based screen against HIV protease (PR), has been co-crystallized with pepstatin-inhibited PR and with apo-PR. Another fragment, 3-indolepropionic acid (1F1-N), predicted by AutoDock calculations and confirmed in a novel ‘inhibition of nucleation’ crystallization assay, exploits the same interactions in the flap site in two crystal structures. Both 1F1 and 1F1-N bind to the closed form of apo-PR and to pepstatin:PR. In solution, 1F1 and 1F1-N raise the Tm of apo-PR by 3.5–5 °C as assayed by differential scanning fluorimetry (DSF), and show equivalent low-micromolar binding constants to both apo-PR and pepstatin:PR, assayed by backscattering interferometry (BSI). The observed signal intensities in BSI are greater for each fragment upon binding to apo-PR than to pepstatin-bound PR, consistent with greater conformational change in the former binding event. Together, these data indicate that fragment binding in the flap site favors a closed conformation of HIV PR. PMID:23540839

Parkin-phosphoubiquitin complex reveals a cryptic ubiquitin binding site required for RBR ligase activity

PubMed Central

Kumar, Atul; Chaugule, Viduth K; Condos, Tara E C; Barber, Kathryn R; Johnson, Clare; Toth, Rachel; Sundaramoorthy, Ramasubramanian; Knebel, Axel; Shaw, Gary S; Walden, Helen

2017-01-01

RING-BETWEENRING-RING (RBR) E3 ligases are a class of ubiquitin ligases distinct from RING or HECT E3 ligases. An important RBR is Parkin, mutations in which lead to early onset hereditary Parkinsonism. Parkin and other RBRs share a catalytic RBR module, but are usually autoinhibited and activated via distinct mechanisms. Recent insights into Parkin regulation predict large, unknown conformational changes during activation of Parkin. However, current data on active RBRs are in the absence of regulatory domains. Therefore, how individual RBRs are activated, and whether they share a common mechanism remains unclear. We now report the crystal structure of a human Parkin-phosphoubiquitin complex, which shows that phosphoubiquitin binding induces a movement in the IBR domain to reveal a cryptic ubiquitin binding site. Mutation of this site negatively impacts on Parkin’s activity. Furthermore, ubiquitin binding promotes cooperation between Parkin molecules, suggesting a role for interdomain association in RBR ligase mechanism. PMID:28414322

Parkin-phosphoubiquitin complex reveals cryptic ubiquitin-binding site required for RBR ligase activity.

PubMed

Kumar, Atul; Chaugule, Viduth K; Condos, Tara E C; Barber, Kathryn R; Johnson, Clare; Toth, Rachel; Sundaramoorthy, Ramasubramanian; Knebel, Axel; Shaw, Gary S; Walden, Helen

2017-05-01

RING-between-RING (RBR) E3 ligases are a class of ubiquitin ligases distinct from RING or HECT E3 ligases. An important RBR ligase is Parkin, mutations in which lead to early-onset hereditary Parkinsonism. Parkin and other RBR ligases share a catalytic RBR module but are usually autoinhibited and activated via distinct mechanisms. Recent insights into Parkin regulation predict large, unknown conformational changes during Parkin activation. However, current data on active RBR ligases reflect the absence of regulatory domains. Therefore, it remains unclear how individual RBR ligases are activated, and whether they share a common mechanism. We now report the crystal structure of a human Parkin-phosphoubiquitin complex, which shows that phosphoubiquitin binding induces movement in the 'in-between RING' (IBR) domain to reveal a cryptic ubiquitin-binding site. Mutation of this site negatively affects Parkin's activity. Furthermore, ubiquitin binding promotes cooperation between Parkin molecules, which suggests a role for interdomain association in the RBR ligase mechanism.

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.

Uncertainty analysis of the nonideal competitive adsorption-donnan model: effects of dissolved organic matter variability on predicted metal speciation in soil solution.

PubMed

Groenenberg, Jan E; Koopmans, Gerwin F; Comans, Rob N J

2010-02-15

Ion binding models such as the nonideal competitive adsorption-Donnan model (NICA-Donnan) and model VI successfully describe laboratory data of proton and metal binding to purified humic substances (HS). In this study model performance was tested in more complex natural systems. The speciation predicted with the NICA-Donnan model and the associated uncertainty were compared with independent measurements in soil solution extracts, including the free metal ion activity and fulvic (FA) and humic acid (HA) fractions of dissolved organic matter (DOM). Potentially important sources of uncertainty are the DOM composition and the variation in binding properties of HS. HS fractions of DOM in soil solution extracts varied between 14 and 63% and consisted mainly of FA. Moreover, binding parameters optimized for individual FA samples show substantial variation. Monte Carlo simulations show that uncertainties in predicted metal speciation, for metals with a high affinity for FA (Cu, Pb), are largely due to the natural variation in binding properties (i.e., the affinity) of FA. Predictions for metals with a lower affinity (Cd) are more prone to uncertainties in the fraction FA in DOM and the maximum site density (i.e., the capacity) of the FA. Based on these findings, suggestions are provided to reduce uncertainties in model predictions.

Resolving the problem of trapped water in binding cavities: prediction of host-guest binding free energies in the SAMPL5 challenge by funnel metadynamics

NASA Astrophysics Data System (ADS)

Bhakat, Soumendranath; Söderhjelm, Pär

2017-01-01

The funnel metadynamics method enables rigorous calculation of the potential of mean force along an arbitrary binding path and thereby evaluation of the absolute binding free energy. A problem of such physical paths is that the mechanism characterizing the binding process is not always obvious. In particular, it might involve reorganization of the solvent in the binding site, which is not easily captured with a few geometrically defined collective variables that can be used for biasing. In this paper, we propose and test a simple method to resolve this trapped-water problem by dividing the process into an artificial host-desolvation step and an actual binding step. We show that, under certain circumstances, the contribution from the desolvation step can be calculated without introducing further statistical errors. We apply the method to the problem of predicting host-guest binding free energies in the SAMPL5 blind challenge, using two octa-acid hosts and six guest molecules. For one of the hosts, well-converged results are obtained and the prediction of relative binding free energies is the best among all the SAMPL5 submissions. For the other host, which has a narrower binding pocket, the statistical uncertainties are slightly higher; longer simulations would therefore be needed to obtain conclusive results.

Analogs of methyllycaconitine as novel noncompetitive inhibitors of nicotinic receptors: pharmacological characterization, computational modeling, and pharmacophore development.

PubMed

McKay, Dennis B; Chang, Cheng; González-Cestari, Tatiana F; McKay, Susan B; El-Hajj, Raed A; Bryant, Darrell L; Zhu, Michael X; Swaan, Peter W; Arason, Kristjan M; Pulipaka, Aravinda B; Orac, Crina M; Bergmeier, Stephen C

2007-05-01

As a novel approach to drug discovery involving neuronal nicotinic acetylcholine receptors (nAChRs), our laboratory targeted nonagonist binding sites (i.e., noncompetitive binding sites, negative allosteric binding sites) located on nAChRs. Cultured bovine adrenal cells were used as neuronal models to investigate interactions of 67 analogs of methyllycaconitine (MLA) on native alpha3beta4* nAChRs. The availability of large numbers of structurally related molecules presents a unique opportunity for the development of pharmacophore models for noncompetitive binding sites. Our MLA analogs inhibited nicotine-mediated functional activation of both native and recombinant alpha3beta4* nAChRs with a wide range of IC(50) values (0.9-115 microM). These analogs had little or no inhibitory effects on agonist binding to native or recombinant nAChRs, supporting noncompetitive inhibitory activity. Based on these data, two highly predictive 3D quantitative structure-activity relationship (comparative molecular field analysis and comparative molecular similarity index analysis) models were generated. These computational models were successfully validated and provided insights into the molecular interactions of MLA analogs with nAChRs. In addition, a pharmacophore model was constructed to analyze and visualize the binding requirements to the analog binding site. The pharmacophore model was subsequently applied to search structurally diverse molecular databases to prospectively identify novel inhibitors. The rapid identification of eight molecules from database mining and our successful demonstration of in vitro inhibitory activity support the utility of these computational models as novel tools for the efficient retrieval of inhibitors. These results demonstrate the effectiveness of computational modeling and pharmacophore development, which may lead to the identification of new therapeutic drugs that target novel sites on nAChRs.

Binding sites for interaction of peroxiredoxin 6 with surfactant protein A

PubMed Central

Krishnaiah, Saikumari Y; Dodia, Chandra; Sorokina, Elena M; Li, Haitao; Feinstein, Sheldon I; Fisher, Aron B

2016-01-01

Peroxiredoxin 6 (Prdx6) is a bifunctional enzyme with peroxidase and phospholipase A2 (PLA2) activities. This protein participates in the degradation and remodeling of internalized dipalmitoylphosphatidylcholine (DPPC), the major phospholipid component of lung surfactant. We have shown previously that the PLA2 activity of Prdx6 is inhibited by the lung surfactant-associated protein called surfactant protein A (SP-A) through direct protein-protein interaction. Docking of SPA and Prdx6 was modeled using the ZDOCK (zlab.bu.edu) program in order to predict molecular sites for binding of the two proteins. The predicted peptide sequences were evaluated for binding to the opposite protein using isothermal titration calorimetry and circular dichroism measurement followed by determination of the effect of the SP-A peptide on the PLA2 activity of Prdx6. The sequences 195EEEAKKLFPK204.in the Prdx6 helix and 83DEELQTELYEIKHQIL99 in SP-A were identified as the sites for hydrophobic interaction and H+-bonding between the 2 proteins. Treatment of mouse endothelial cells with the SP-A peptide inhibited their recovery from lipid peroxidation associated with oxidative stress indicating inhibition of Prdx6 activity by the peptide in the intact cell. PMID:26723227

Data on master regulators and transcription factor binding sites found by upstream analysis of multi-omics data on methotrexate resistance of colon cancer.

PubMed

Kel, AlexanderE

2017-02-01

Computational analysis of master regulators through the search for transcription factor binding sites followed by analysis of signal transduction networks of a cell is a new approach of causal analysis of multi-omics data. This paper contains results on analysis of multi-omics data that include transcriptomics, proteomics and epigenomics data of methotrexate (MTX) resistant colon cancer cell line. The data were used for analysis of mechanisms of resistance and for prediction of potential drug targets and promising compounds for reverting the MTX resistance of these cancer cells. We present all results of the analysis including the lists of identified transcription factors and their binding sites in genome and the list of predicted master regulators - potential drug targets. This data was generated in the study recently published in the article "Multi-omics "Upstream Analysis" of regulatory genomic regions helps identifying targets against methotrexate resistance of colon cancer" (Kel et al., 2016) [4]. These data are of interest for researchers from the field of multi-omics data analysis and for biologists who are interested in identification of novel drug targets against NTX resistance.

Predicting changes in cardiac myocyte contractility during early drug discovery with in vitro assays

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

Morton, M.J., E-mail: michael.morton@astrazeneca.com; Armstrong, D.; Abi Gerges, N.

2014-09-01

Cardiovascular-related adverse drug effects are a major concern for the pharmaceutical industry. Activity of an investigational drug at the L-type calcium channel could manifest in a number of ways, including changes in cardiac contractility. The aim of this study was to define which of the two assay technologies – radioligand-binding or automated electrophysiology – was most predictive of contractility effects in an in vitro myocyte contractility assay. The activity of reference and proprietary compounds at the L-type calcium channel was measured by radioligand-binding assays, conventional patch-clamp, automated electrophysiology, and by measurement of contractility in canine isolated cardiac myocytes. Activity inmore » the radioligand-binding assay at the L-type Ca channel phenylalkylamine binding site was most predictive of an inotropic effect in the canine cardiac myocyte assay. The sensitivity was 73%, specificity 83% and predictivity 78%. The radioligand-binding assay may be run at a single test concentration and potency estimated. The least predictive assay was automated electrophysiology which showed a significant bias when compared with other assay formats. Given the importance of the L-type calcium channel, not just in cardiac function, but also in other organ systems, a screening strategy emerges whereby single concentration ligand-binding can be performed early in the discovery process with sufficient predictivity, throughput and turnaround time to influence chemical design and address a significant safety-related liability, at relatively low cost. - Highlights: • The L-type calcium channel is a significant safety liability during drug discovery. • Radioligand-binding to the L-type calcium channel can be measured in vitro. • The assay can be run at a single test concentration as part of a screening cascade. • This measurement is highly predictive of changes in cardiac myocyte contractility.« less

Biosorption of trivalent chromium on the brown seaweed biomass.

PubMed

Yun, Y S; Park, D; Park, J M; Volesky, B

2001-11-01

Biosorption has attracted attention as a cost-effective means for the treatment of metal-bearing wastewater. However, the mechanism of metal binding is not clearly understood, and consequently, modeling of the biosorption performance is still raising debates. In this study, the biosorption of trivalent chromium was investigated with protonated brown alga Ecklonia biomass as a model system. Titration of the biomass revealed that it contains at least three types of functional groups. The Fourier transform infrared spectrometry showed that the carboxyl group was the chromium-binding site within the pH range (pH 1-5) used in this study, where chromium does not precipitate. The pK value and the number of carboxyl groups were estimated to be 4.6 +/- 0.1 and 2.2 +/- 0.1 mmol/g, respectively. The equilibrium sorption isotherms determined at different solution pH indicated that the uptake of chromium increased significantly with increasing pH. A model for the description of chromium biosorption was developed incorporating the hydrolysis reactions that chromium undergoes in the aquatic phase. The model was able to predict the equilibrium sorption experimental data at different pH values and chromium concentrations. In addition, the speciation of the binding site as a function of the solution pH was predicted using the model in order to visualize the distribution of chromium ionic species on the binding site.

Osmotic mechanism of the loop extrusion process

NASA Astrophysics Data System (ADS)

Yamamoto, Tetsuya; Schiessel, Helmut

2017-09-01

The loop extrusion theory assumes that protein factors, such as cohesin rings, act as molecular motors that extrude chromatin loops. However, recent single molecule experiments have shown that cohesin does not show motor activity. To predict the physical mechanism involved in loop extrusion, we here theoretically analyze the dynamics of cohesin rings on a loop, where a cohesin loader is in the middle and unloaders at the ends. Cohesin monomers bind to the loader rather frequently and cohesin dimers bind to this site only occasionally. Our theory predicts that a cohesin dimer extrudes loops by the osmotic pressure of cohesin monomers on the chromatin fiber between the two connected rings. With this mechanism, the frequency of the interactions between chromatin segments depends on the loading and unloading rates of dimers at the corresponding sites.

PreCisIon: PREdiction of CIS-regulatory elements improved by gene's positION.

PubMed

Elati, Mohamed; Nicolle, Rémy; Junier, Ivan; Fernández, David; Fekih, Rim; Font, Julio; Képès, François

2013-02-01

Conventional approaches to predict transcriptional regulatory interactions usually rely on the definition of a shared motif sequence on the target genes of a transcription factor (TF). These efforts have been frustrated by the limited availability and accuracy of TF binding site motifs, usually represented as position-specific scoring matrices, which may match large numbers of sites and produce an unreliable list of target genes. To improve the prediction of binding sites, we propose to additionally use the unrelated knowledge of the genome layout. Indeed, it has been shown that co-regulated genes tend to be either neighbors or periodically spaced along the whole chromosome. This study demonstrates that respective gene positioning carries significant information. This novel type of information is combined with traditional sequence information by a machine learning algorithm called PreCisIon. To optimize this combination, PreCisIon builds a strong gene target classifier by adaptively combining weak classifiers based on either local binding sequence or global gene position. This strategy generically paves the way to the optimized incorporation of any future advances in gene target prediction based on local sequence, genome layout or on novel criteria. With the current state of the art, PreCisIon consistently improves methods based on sequence information only. This is shown by implementing a cross-validation analysis of the 20 major TFs from two phylogenetically remote model organisms. For Bacillus subtilis and Escherichia coli, respectively, PreCisIon achieves on average an area under the receiver operating characteristic curve of 70 and 60%, a sensitivity of 80 and 70% and a specificity of 60 and 56%. The newly predicted gene targets are demonstrated to be functionally consistent with previously known targets, as assessed by analysis of Gene Ontology enrichment or of the relevant literature and databases.

The binding sites for benztropines and dopamine in the dopamine transporter overlap

PubMed Central

Bisgaard, Heidi; Larsen, M. Andreas B.; Mazier, Sonia; Beuming, Thijs; Newman, Amy Hauck; Weinstein, Harel; Shi, Lei; Loland, Claus J.; Gether, Ulrik

2013-01-01

Analogues of benztropines (BZTs) are potent inhibitors of the dopamine transporter (DAT) but are less effective than cocaine as behavioral stimulants. As a result, there have been efforts to evaluate these compounds as leads for potential medication for cocaine addiction. Here we use computational modeling together with site-directed mutagenesis to characterize the binding site for BZTs in DAT. Docking into molecular models based on the structure of the bacterial homologue LeuT supported a BZT binding site that overlaps with the substrate binding pocket. In agreement, mutations of residues within the pocket, including Val1523.46* to Ala or Ile, Ser4228.60 to Ala and Asn1573.51 to Cys or Ala, resulted in decreased affinity for BZT and the analog JHW007, as assessed in [3H]dopamine uptake inhibition assays and/or [3H]CFT competition binding assay. A putative polar interaction of one of the phenyl ring fluorine substituents in JHW007 with Asn1573.51 was used as a criterion for determining likely binding poses and establish a structural context for the mutagenesis findings. The analysis positioned the other fluorine substituted phenyl ring of JHW007 in close proximity to Ala47910.51/Ala48010.52 in transmembrane segment (TM) 10. The lack of such an interaction for BZT led to a more tilted orientation, as compared to JHW007, bringing one of the phenyl rings even closer to Ala47910.51/Ala48010.52. Mutation of Ala47910.51 and Ala48010.52 to valines supported these predictions with a larger decrease in the affinity for BZT than for JHW007. Summarized, our data suggest that BZTs display a classical competitive binding mode with binding sites overlapping those of cocaine and dopamine. PMID:20816875

Deconstructing the DGAT1 enzyme: membrane interactions at substrate binding sites.

PubMed

Lopes, Jose L S; Beltramini, Leila M; Wallace, Bonnie A; Araujo, Ana P U

2015-01-01

Diacylglycerol acyltransferase 1 (DGAT1) is a key enzyme in the triacylglyceride synthesis pathway. Bovine DGAT1 is an endoplasmic reticulum membrane-bound protein associated with the regulation of fat content in milk and meat. The aim of this study was to evaluate the interaction of DGAT1 peptides corresponding to putative substrate binding sites with different types of model membranes. Whilst these peptides are predicted to be located in an extramembranous loop of the membrane-bound protein, their hydrophobic substrates are membrane-bound molecules. In this study, peptides corresponding to the binding sites of the two substrates involved in the reaction were examined in the presence of model membranes in order to probe potential interactions between them that might influence the subsequent binding of the substrates. Whilst the conformation of one of the peptides changed upon binding several types of micelles regardless of their surface charge, suggesting binding to hydrophobic domains, the other peptide bound strongly to negatively-charged model membranes. This binding was accompanied by a change in conformation, and produced leakage of the liposome-entrapped dye calcein. The different hydrophobic and electrostatic interactions observed suggest the peptides may be involved in the interactions of the enzyme with membrane surfaces, facilitating access of the catalytic histidine to the triacylglycerol substrates.

Finding the target sites of RNA-binding proteins

PubMed Central

Li, Xiao; Kazan, Hilal; Lipshitz, Howard D; Morris, Quaid D

2014-01-01

RNA–protein interactions differ from DNA–protein interactions because of the central role of RNA secondary structure. Some RNA-binding domains (RBDs) recognize their target sites mainly by their shape and geometry and others are sequence-specific but are sensitive to secondary structure context. A number of small- and large-scale experimental approaches have been developed to measure RNAs associated in vitro and in vivo with RNA-binding proteins (RBPs). Generalizing outside of the experimental conditions tested by these assays requires computational motif finding. Often RBP motif finding is done by adapting DNA motif finding methods; but modeling secondary structure context leads to better recovery of RBP-binding preferences. Genome-wide assessment of mRNA secondary structure has recently become possible, but these data must be combined with computational predictions of secondary structure before they add value in predicting in vivo binding. There are two main approaches to incorporating structural information into motif models: supplementing primary sequence motif models with preferred secondary structure contexts (e.g., MEMERIS and RNAcontext) and directly modeling secondary structure recognized by the RBP using stochastic context-free grammars (e.g., CMfinder and RNApromo). The former better reconstruct known binding preferences for sequence-specific RBPs but are not suitable for modeling RBPs that recognize shape and geometry of RNAs. Future work in RBP motif finding should incorporate interactions between multiple RBDs and multiple RBPs in binding to RNA. WIREs RNA 2014, 5:111–130. doi: 10.1002/wrna.1201 PMID:24217996

PDNAsite: Identification of DNA-binding Site from Protein Sequence by Incorporating Spatial and Sequence Context

PubMed Central

Zhou, Jiyun; Xu, Ruifeng; He, Yulan; Lu, Qin; Wang, Hongpeng; Kong, Bing

2016-01-01

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community. PMID:27282833

An Improved Method for TAL Effectors DNA-Binding Sites Prediction Reveals Functional Convergence in TAL Repertoires of Xanthomonas oryzae Strains

PubMed Central

Pérez-Quintero, Alvaro L.; Rodriguez-R, Luis M.; Dereeper, Alexis; López, Camilo; Koebnik, Ralf; Szurek, Boris; Cunnac, Sebastien

2013-01-01

Transcription Activators-Like Effectors (TALEs) belong to a family of virulence proteins from the Xanthomonas genus of bacterial plant pathogens that are translocated into the plant cell. In the nucleus, TALEs act as transcription factors inducing the expression of susceptibility genes. A code for TALE-DNA binding specificity and high-resolution three-dimensional structures of TALE-DNA complexes were recently reported. Accurate prediction of TAL Effector Binding Elements (EBEs) is essential to elucidate the biological functions of the many sequenced TALEs as well as for robust design of artificial TALE DNA-binding domains in biotechnological applications. In this work a program with improved EBE prediction performances was developed using an updated specificity matrix and a position weight correction function to account for the matching pattern observed in a validation set of TALE-DNA interactions. To gain a systems perspective on the large TALE repertoires from X. oryzae strains, this program was used to predict rice gene targets for 99 sequenced family members. Integrating predictions and available expression data in a TALE-gene network revealed multiple candidate transcriptional targets for many TALEs as well as several possible instances of functional convergence among TALEs. PMID:23869221

Identification of the Catalytic Ubiquinone-binding Site of Vibrio cholerae Sodium-dependent NADH Dehydrogenase

PubMed Central

Tuz, Karina; Li, Chen; Fang, Xuan; Raba, Daniel A.; Liang, Pingdong; Minh, David D. L.; Juárez, Oscar

2017-01-01

The sodium-dependent NADH dehydrogenase (Na+-NQR) is a key component of the respiratory chain of diverse prokaryotic species, including pathogenic bacteria. Na+-NQR uses the energy released by electron transfer between NADH and ubiquinone (UQ) to pump sodium, producing a gradient that sustains many essential homeostatic processes as well as virulence factor secretion and the elimination of drugs. The location of the UQ binding site has been controversial, with two main hypotheses that suggest that this site could be located in the cytosolic subunit A or in the membrane-bound subunit B. In this work, we performed alanine scanning mutagenesis of aromatic residues located in transmembrane helices II, IV, and V of subunit B, near glycine residues 140 and 141. These two critical glycine residues form part of the structures that regulate the site's accessibility. Our results indicate that the elimination of phenylalanine residue 211 or 213 abolishes the UQ-dependent activity, produces a leak of electrons to oxygen, and completely blocks the binding of UQ and the inhibitor HQNO. Molecular docking calculations predict that UQ interacts with phenylalanine 211 and pinpoints the location of the binding site in the interface of subunits B and D. The mutagenesis and structural analysis allow us to propose a novel UQ-binding motif, which is completely different compared with the sites of other respiratory photosynthetic complexes. These results are essential to understanding the electron transfer pathways and mechanism of Na+-NQR catalysis. PMID:28053088

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.

Brachyury, Foxa2 and the cis-Regulatory Origins of the Notochord

PubMed Central

José-Edwards, Diana S.; Oda-Ishii, Izumi; Kugler, Jamie E.; Passamaneck, Yale J.; Katikala, Lavanya; Nibu, Yutaka; Di Gregorio, Anna

2015-01-01

A main challenge of modern biology is to understand how specific constellations of genes are activated to differentiate cells and give rise to distinct tissues. This study focuses on elucidating how gene expression is initiated in the notochord, an axial structure that provides support and patterning signals to embryos of humans and all other chordates. Although numerous notochord genes have been identified, the regulatory DNAs that orchestrate development and propel evolution of this structure by eliciting notochord gene expression remain mostly uncharted, and the information on their configuration and recurrence is still quite fragmentary. Here we used the simple chordate Ciona for a systematic analysis of notochord cis-regulatory modules (CRMs), and investigated their composition, architectural constraints, predictive ability and evolutionary conservation. We found that most Ciona notochord CRMs relied upon variable combinations of binding sites for the transcription factors Brachyury and/or Foxa2, which can act either synergistically or independently from one another. Notably, one of these CRMs contains a Brachyury binding site juxtaposed to an (AC) microsatellite, an unusual arrangement also found in Brachyury-bound regulatory regions in mouse. In contrast, different subsets of CRMs relied upon binding sites for transcription factors of widely diverse families. Surprisingly, we found that neither intra-genomic nor interspecific conservation of binding sites were reliably predictive hallmarks of notochord CRMs. We propose that rather than obeying a rigid sequence-based cis-regulatory code, most notochord CRMs are rather unique. Yet, this study uncovered essential elements recurrently used by divergent chordates as basic building blocks for notochord CRMs. PMID:26684323

Brachyury, Foxa2 and the cis-Regulatory Origins of the Notochord.

PubMed

José-Edwards, Diana S; Oda-Ishii, Izumi; Kugler, Jamie E; Passamaneck, Yale J; Katikala, Lavanya; Nibu, Yutaka; Di Gregorio, Anna

2015-12-01

A main challenge of modern biology is to understand how specific constellations of genes are activated to differentiate cells and give rise to distinct tissues. This study focuses on elucidating how gene expression is initiated in the notochord, an axial structure that provides support and patterning signals to embryos of humans and all other chordates. Although numerous notochord genes have been identified, the regulatory DNAs that orchestrate development and propel evolution of this structure by eliciting notochord gene expression remain mostly uncharted, and the information on their configuration and recurrence is still quite fragmentary. Here we used the simple chordate Ciona for a systematic analysis of notochord cis-regulatory modules (CRMs), and investigated their composition, architectural constraints, predictive ability and evolutionary conservation. We found that most Ciona notochord CRMs relied upon variable combinations of binding sites for the transcription factors Brachyury and/or Foxa2, which can act either synergistically or independently from one another. Notably, one of these CRMs contains a Brachyury binding site juxtaposed to an (AC) microsatellite, an unusual arrangement also found in Brachyury-bound regulatory regions in mouse. In contrast, different subsets of CRMs relied upon binding sites for transcription factors of widely diverse families. Surprisingly, we found that neither intra-genomic nor interspecific conservation of binding sites were reliably predictive hallmarks of notochord CRMs. We propose that rather than obeying a rigid sequence-based cis-regulatory code, most notochord CRMs are rather unique. Yet, this study uncovered essential elements recurrently used by divergent chordates as basic building blocks for notochord CRMs.

Recognition and Detoxification of the Insecticide DDT by Drosophila melanogaster Glutathione S-Transferase D1

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

Low, Wai Yee; Feil, Susanne C.; Ng, Hooi Ling

2010-06-14

GSTD1 is one of several insect glutathione S-transferases capable of metabolizing the insecticide DDT. Here we use crystallography and NMR to elucidate the binding of DDT and glutathione to GSTD1. The crystal structure of Drosophila melanogaster GSTD1 has been determined to 1.1 {angstrom} resolution, which reveals that the enzyme adopts the canonical GST fold but with a partially occluded active site caused by the packing of a C-terminal helix against one wall of the binding site for substrates. This helix would need to unwind or be displaced to enable catalysis. When the C-terminal helix is removed from the model ofmore » the crystal structure, DDT can be computationally docked into the active site in an orientation favoring catalysis. Two-dimensional {sup 1}H,{sup 15}N heteronuclear single-quantum coherence NMR experiments of GSTD1 indicate that conformational changes occur upon glutathione and DDT binding and the residues that broaden upon DDT binding support the predicted binding site. We also show that the ancestral GSTD1 is likely to have possessed DDT dehydrochlorinase activity because both GSTD1 from D. melanogaster and its sibling species, Drosophila simulans, have this activity.« less

Kinetics of Cation and Oxyanion Adsorption and Desorption on Ferrihydrite: Roles of Ferrihydrite Binding Sites and a Unified Model.

PubMed

Tian, Lei; Shi, Zhenqing; Lu, Yang; Dohnalkova, Alice C; Lin, Zhang; Dang, Zhi

2017-09-19

Quantitative understanding the kinetics of toxic ion reactions with various heterogeneous ferrihydrite binding sites is crucial for accurately predicting the dynamic behavior of contaminants in environment. In this study, kinetics of As(V), Cr(VI), Cu(II), and Pb(II) adsorption and desorption on ferrihydrite was studied using a stirred-flow method, which showed that metal adsorption/desorption kinetics was highly dependent on the reaction conditions and varied significantly among four metals. High resolution scanning transmission electron microscopy coupled with energy-dispersive X-ray spectroscopy showed that all four metals were distributed within the ferrihydrite aggregates homogeneously after adsorption reactions. Based on the equilibrium model CD-MUSIC, we developed a novel unified kinetics model applicable for both cation and oxyanion adsorption and desorption on ferrihydrite, which is able to account for the heterogeneity of ferrihydrite binding sites, different binding properties of cations and oxyanions, and variations of solution chemistry. The model described the kinetic results well. We quantitatively elucidated how the equilibrium properties of the cation and oxyanion binding to various ferrihydrite sites and the formation of various surface complexes controlled the adsorption and desorption kinetics at different reaction conditions and time scales. Our study provided a unified modeling method for the kinetics of ion adsorption/desorption on ferrihydrite.

Antibody specific epitope prediction-emergence of a new paradigm.

PubMed

Sela-Culang, Inbal; Ofran, Yanay; Peters, Bjoern

2015-04-01

The development of accurate tools for predicting B-cell epitopes is important but difficult. Traditional methods have examined which regions in an antigen are likely binding sites of an antibody. However, it is becoming increasingly clear that most antigen surface residues will be able to bind one or more of the myriad of possible antibodies. In recent years, new approaches have emerged for predicting an epitope for a specific antibody, utilizing information encoded in antibody sequence or structure. Applying such antibody-specific predictions to groups of antibodies in combination with easily obtainable experimental data improves the performance of epitope predictions. We expect that further advances of such tools will be possible with the integration of immunoglobulin repertoire sequencing data. Copyright © 2015 Elsevier B.V. All rights reserved.

The involvement of coordinative interactions in the binding of dihydrolipoamide dehydrogenase to titanium dioxide-Localization of a putative binding site.

PubMed

Dayan, Avraham; Babin, Gilad; Ganoth, Assaf; Kayouf, Nivin Samir; Nitoker Eliaz, Neta; Mukkala, Srijana; Tsfadia, Yossi; Fleminger, Gideon

2017-08-01

Titanium (Ti) and its alloys are widely used in orthodontic and orthopedic implants by virtue to their high biocompatibility, mechanical strength, and high resistance to corrosion. Biointegration of the implants with the tissue requires strong interactions, which involve biological molecules, proteins in particular, with metal oxide surfaces. An exocellular high-affinity titanium dioxide (TiO 2 )-binding protein (TiBP), purified from Rhodococcus ruber, has been previously studied in our lab. This protein was shown to be homologous with the orthologous cytoplasmic rhodococcal dihydrolipoamide dehydrogenase (rhDLDH). We have found that rhDLDH and its human homolog (hDLDH) share the TiO 2 -binding capabilities with TiBP. Intrigued by the unique TiO 2 -binding properties of hDLDH, we anticipated that it may serve as a molecular bridge between Ti-based medical structures and human tissues. The objective of the current study was to locate the region and the amino acids of the protein that mediate the protein-TiO 2 surface interaction. We demonstrated the role of acidic amino acids in the nonelectrostatic enzyme/dioxide interactions at neutral pH. The observation that the interaction of DLDH with various metal oxides is independent of their isoelectric values strengthens this notion. DLDH does not lose its enzymatic activity upon binding to TiO 2 , indicating that neither the enzyme undergoes major conformational changes nor the TiO 2 binding site is blocked. Docking predictions suggest that both rhDLDH and hDLDH bind TiO 2 through similar regions located far from the active site and the dimerization sites. The putative TiO 2 -binding regions of both the bacterial and human enzymes were found to contain a CHED (Cys, His, Glu, Asp) motif, which has been shown to participate in metal-binding sites in proteins. Copyright © 2017 John Wiley & Sons, Ltd.

Zn(2+) site engineering at the oligomeric interface of the dopamine transporter.

PubMed

Norgaard-Nielsen, Kristine; Norregaard, Lene; Hastrup, Hanne; Javitch, Jonathan A; Gether, Ulrik

2002-07-31

Increasing evidence suggests that Na(+)/Cl(-)-dependent neurotransmitter transporters exist as homo-oligomeric proteins. However, the functional implication of this oligomerization remains unclear. Here we demonstrate the engineering of a Zn(2+) binding site at the predicted dimeric interface of the dopamine transporter (DAT) corresponding to the external end of transmembrane segment 6. Upon binding to this site, which involves a histidine inserted in position 310 (V310H) and the endogenous Cys306 within the same DAT molecule, Zn(2+) potently inhibits [(3)H]dopamine uptake. These data provide indirect evidence that conformational changes critical for the translocation process may occur at the interface between two transporter molecules in the oligomeric structure.

Prediction of biological functions on glycosylation site migrations in human influenza H1N1 viruses.

PubMed

Sun, Shisheng; Wang, Qinzhe; Zhao, Fei; Chen, Wentian; Li, Zheng

2012-01-01

Protein glycosylation alteration is typically employed by various viruses for escaping immune pressures from their hosts. Our previous work had shown that not only the increase of glycosylation sites (glycosites) numbers, but also glycosite migration might be involved in the evolution of human seasonal influenza H1N1 viruses. More importantly, glycosite migration was likely a more effectively alteration way for the host adaption of human influenza H1N1 viruses. In this study, we provided more bioinformatics and statistic evidences for further predicting the significant biological functions of glycosite migration in the host adaptation of human influenza H1N1 viruses, by employing homology modeling and in silico protein glycosylation of representative HA and NA proteins as well as amino acid variability analysis at antigenic sites of HA and NA. The results showed that glycosite migrations in human influenza viruses have at least five possible functions: to more effectively mask the antigenic sites, to more effectively protect the enzymatic cleavage sites of neuraminidase (NA), to stabilize the polymeric structures, to regulate the receptor binding and catalytic activities and to balance the binding activity of hemagglutinin (HA) with the release activity of NA. The information here can provide some constructive suggestions for the function research related to protein glycosylation of influenza viruses, although these predictions still need to be supported by experimental data.

Steroid ligands bind human sex hormone-binding globulin in specific orientations and produce distinct changes in protein conformation.

PubMed

Grishkovskaya, Irina; Avvakumov, George V; Hammond, Geoffrey L; Catalano, Maria G; Muller, Yves A

2002-08-30

The amino-terminal laminin G-like domain of human sex hormone-binding globulin (SHBG) contains a single high affinity steroid-binding site. Crystal structures of this domain in complex with several different steroid ligands have revealed that estradiol occupies the SHBG steroid-binding site in an opposite orientation when compared with 5 alpha-dihydrotestosterone or C19 androgen metabolites (5 alpha-androstan-3 beta,17 beta-diol and 5 alpha-androstan-3 beta,17 alpha-diol) or the synthetic progestin levonorgestrel. Substitution of specific residues within the SHBG steroid-binding site confirmed that Ser(42) plays a key role in determining high affinity interactions by hydrogen bonding to functional groups at C3 of the androstanediols and levonorgestrel and the hydroxyl at C17 of estradiol. Among residues participating in the hydrogen bond network with hydroxy groups at C17 of C19 steroids or C3 of estradiol, Asp(65) appears to be the most important. The different binding mode of estradiol is associated with a difference in the position/orientation of residues (Leu(131) and Lys(134)) in the loop segment (Leu(131)-His(136)) that covers the steroid-binding site as well as others (Leu(171)-Lys(173) and Trp(84)) on the surface of human SHBG and may provide a basis for ligand-dependent interactions between SHBG and other macromolecules. These new crystal structures have also enabled us to construct a simple space-filling model that can be used to predict the characteristics of novel SHBG ligands.

Mathematical description of drug-target interactions: application to biologics that bind to targets with two binding sites.

PubMed

Gibiansky, Leonid; Gibiansky, Ekaterina

2018-02-01

The emerging discipline of mathematical pharmacology occupies the space between advanced pharmacometrics and systems biology. A characteristic feature of the approach is application of advance mathematical methods to study the behavior of biological systems as described by mathematical (most often differential) equations. One of the early application of mathematical pharmacology (that was not called this name at the time) was formulation and investigation of the target-mediated drug disposition (TMDD) model and its approximations. The model was shown to be remarkably successful, not only in describing the observed data for drug-target interactions, but also in advancing the qualitative and quantitative understanding of those interactions and their role in pharmacokinetic and pharmacodynamic properties of biologics. The TMDD model in its original formulation describes the interaction of the drug that has one binding site with the target that also has only one binding site. Following the framework developed earlier for drugs with one-to-one binding, this work aims to describe a rigorous approach for working with similar systems and to apply it to drugs that bind to targets with two binding sites. The quasi-steady-state, quasi-equilibrium, irreversible binding, and Michaelis-Menten approximations of the model are also derived. These equations can be used, in particular, to predict concentrations of the partially bound target (RC). This could be clinically important if RC remains active and has slow internalization rate. In this case, introduction of the drug aimed to suppress target activity may lead to the opposite effect due to RC accumulation.

Isolation of anticancer drug TAXOL from Pestalotiopsis breviseta with apoptosis and B-Cell lymphoma protein docking studies.

PubMed

Kathiravan, G; Sureban, Sripathi M; Sree, Harsha N; Bhuvaneshwari, V; Kramony, Evelin

2012-12-01

Extraction and investigation of TAXOL from Pestalotiopsis breviseta (Sacc.) using protein docking, which is a computational technique that samples conformations of small molecules in protein-binding sites. Scoring functions are used to assess which of these conformations best complements the protein binding site and active site prediction. Coelomycetous fungi P. breviseta (Sacc.) Steyaert was screened for the production of TAXOL, an anticancer drug. TAXOL PRODUCTION WAS CONFIRMED BY THE FOLLOWING METHODS: Ultraviolet (UV) spectroscopic analysis, Infrared analysis, High performance liquid chromatography analysis (HPLC), and Liquid chromatography mass spectrum (LC-MASS). TAXOL produced by the fungi was compared with authentic TAXOL, and protein docking studies were performed. The BCL2 protein of human origin showed a higher affinity toward the compound paclitaxel. It has the binding energy value of -13.0061 (KJ/Mol) with four hydrogen bonds.

Isolation of anticancer drug TAXOL from Pestalotiopsis breviseta with apoptosis and B-Cell lymphoma protein docking studies

PubMed Central

Kathiravan, G.; Sureban, Sripathi M.; Sree, Harsha N.; Bhuvaneshwari, V.; Kramony, Evelin

2012-01-01

Background: Extraction and investigation of TAXOL from Pestalotiopsis breviseta (Sacc.) using protein docking, which is a computational technique that samples conformations of small molecules in protein-binding sites. Scoring functions are used to assess which of these conformations best complements the protein binding site and active site prediction. Materials and Methods: Coelomycetous fungi P. breviseta (Sacc.) Steyaert was screened for the production of TAXOL, an anticancer drug. Results: TAXOL production was confirmed by the following methods: Ultraviolet (UV) spectroscopic analysis, Infrared analysis, High performance liquid chromatography analysis (HPLC), and Liquid chromatography mass spectrum (LC-MASS). TAXOL produced by the fungi was compared with authentic TAXOL, and protein docking studies were performed. Conclusion: The BCL2 protein of human origin showed a higher affinity toward the compound paclitaxel. It has the binding energy value of −13.0061 (KJ/Mol) with four hydrogen bonds. PMID:24808664

Site-Specific Phosphorylation of VEGFR2 Is Mediated by Receptor Trafficking: Insights from a Computational Model

PubMed Central

Clegg, Lindsay Wendel; Mac Gabhann, Feilim

2015-01-01

Matrix-binding isoforms and non-matrix-binding isoforms of vascular endothelial growth factor (VEGF) are both capable of stimulating vascular remodeling, but the resulting blood vessel networks are structurally and functionally different. Here, we develop and validate a computational model of the binding of soluble and immobilized ligands to VEGF receptor 2 (VEGFR2), the endosomal trafficking of VEGFR2, and site-specific VEGFR2 tyrosine phosphorylation to study differences in induced signaling between these VEGF isoforms. In capturing essential features of VEGFR2 signaling and trafficking, our model suggests that VEGFR2 trafficking parameters are largely consistent across multiple endothelial cell lines. Simulations demonstrate distinct localization of VEGFR2 phosphorylated on Y1175 and Y1214. This is the first model to clearly show that differences in site-specific VEGFR2 activation when stimulated with immobilized VEGF compared to soluble VEGF can be accounted for by altered trafficking of VEGFR2 without an intrinsic difference in receptor activation. The model predicts that Neuropilin-1 can induce differences in the surface-to-internal distribution of VEGFR2. Simulations also show that ligated VEGFR2 and phosphorylated VEGFR2 levels diverge over time following stimulation. Using this model, we identify multiple key levers that alter how VEGF binding to VEGFR2 results in different coordinated patterns of multiple downstream signaling pathways. Specifically, simulations predict that VEGF immobilization, interactions with Neuropilin-1, perturbations of VEGFR2 trafficking, and changes in expression or activity of phosphatases acting on VEGFR2 all affect the magnitude, duration, and relative strength of VEGFR2 phosphorylation on tyrosines 1175 and 1214, and they do so predictably within our single consistent model framework. PMID:26067165

Comparison of Saccharomyces cerevisiae F-BAR domain structures reveals a conserved inositol phosphate binding site.

PubMed

Moravcevic, Katarina; Alvarado, Diego; Schmitz, Karl R; Kenniston, Jon A; Mendrola, Jeannine M; Ferguson, Kathryn M; Lemmon, Mark A

2015-02-03

F-BAR domains control membrane interactions in endocytosis, cytokinesis, and cell signaling. Although they are generally thought to bind curved membranes containing negatively charged phospholipids, numerous functional studies argue that differences in lipid-binding selectivities of F-BAR domains are functionally important. Here, we compare membrane-binding properties of the Saccharomyces cerevisiae F-BAR domains in vitro and in vivo. Whereas some F-BAR domains (such as Bzz1p and Hof1p F-BARs) bind equally well to all phospholipids, the F-BAR domain from the RhoGAP Rgd1p preferentially binds phosphoinositides. We determined X-ray crystal structures of F-BAR domains from Hof1p and Rgd1p, the latter bound to an inositol phosphate. The structures explain phospholipid-binding selectivity differences and reveal an F-BAR phosphoinositide binding site that is fully conserved in a mammalian RhoGAP called Gmip and is partly retained in certain other F-BAR domains. Our findings reveal previously unappreciated determinants of F-BAR domain lipid-binding specificity and provide a basis for its prediction from sequence. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparison of Saccharomyces cerevisiae F-BAR Domain Structures Reveals a Conserved Inositol Phosphate Binding Site

DOE PAGES

Moravcevic, Katarina; Alvarado, Diego; Schmitz, Karl R.; ...

2015-01-22

F-BAR domains control membrane interactions in endocytosis, cytokinesis, and cell signaling. Although they are generally thought to bind curved membranes containing negatively charged phospholipids, numerous functional studies argue that differences in lipid-binding selectivities of F-BAR domains are functionally important. Here in this paper, we compare membrane-binding properties of the Saccharomyces cerevisiae F-BAR domains in vitro and in vivo. Whereas some F-BAR domains (such as Bzz1p and Hof1p F-BARs) bind equally well to all phospholipids, the F-BAR domain from the RhoGAP Rgd1p preferentially binds phosphoinositides. We determined X-ray crystal structures of F-BAR domains from Hof1p and Rgd1p, the latter bound tomore » an inositol phosphate. The structures explain phospholipid-binding selectivity differences and reveal an F-BAR phosphoinositide binding site that is fully conserved in a mammalian RhoGAP called Gmip and is partly retained in certain other F-BAR domains. In conclusion, our findings reveal previously unappreciated determinants of F-BAR domain lipid-binding specificity and provide a basis for its prediction from sequence.« less

PdhR, the pyruvate dehydrogenase repressor, does not regulate lipoic acid synthesis.

PubMed

Feng, Youjun; Cronan, John E

2014-01-01

Lipoic acid is a covalently-bound enzyme cofactor required for central metabolism all three domains of life. In the last 20 years the pathway of lipoic acid synthesis and metabolism has been established in Escherichia coli. Expression of the genes of the lipoic acid biosynthesis pathway was believed to be constitutive. However, in 2010 Kaleta and coworkers (BMC Syst. Biol. 4:116) predicted a binding site for the pyruvate dehydrogenase operon repressor, PdhR (referred to lipA site 1) upstream of lipA, the gene encoding lipoic acid synthase and concluded that PdhR regulates lipA transcription. We report in vivo and in vitro evidence that lipA is not controlled by PdhR and that the putative regulatory site deduced by the prior workers is nonfunctional and physiologically irrelevant. E. coli PdhR was purified to homogeneity and used for electrophoretic mobility shift assays. The lipA site 1 of Kaleta and coworkers failed to bind PdhR. The binding detected by these workers is due to another site (lipA site 3) located far upstream of the lipA promoter. Relative to the canonical PdhR binding site lipA site 3 is a half-palindrome and as expected had only weak PdhR binding ability. Manipulation of lipA site 3 to construct a palindrome gave significantly enhanced PdhR binding affinity. The native lipA promoter and the version carrying the artificial lipA3 palindrome were transcriptionally fused to a LacZ reporter gene to directly assay lipA expression. Deletion of pdhR gave no significant change in lipA promoter-driven β-galactosidase activity with either the native or constructed palindrome upstream sequences, indicating that PdhR plays no physiological role in regulation of lipA expression. Copyright © 2014 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Human adenosine A2A receptor binds calmodulin with high affinity in a calcium-dependent manner.

PubMed

Piirainen, Henni; Hellman, Maarit; Tossavainen, Helena; Permi, Perttu; Kursula, Petri; Jaakola, Veli-Pekka

2015-02-17

Understanding how ligands bind to G-protein-coupled receptors and how binding changes receptor structure to affect signaling is critical for developing a complete picture of the signal transduction process. The adenosine A2A receptor (A2AR) is a particularly interesting example, as it has an exceptionally long intracellular carboxyl terminus, which is predicted to be mainly disordered. Experimental data on the structure of the A2AR C-terminus is lacking, because published structures of A2AR do not include the C-terminus. Calmodulin has been reported to bind to the A2AR C-terminus, with a possible binding site on helix 8, next to the membrane. The biological meaning of the interaction as well as its calcium dependence, thermodynamic parameters, and organization of the proteins in the complex are unclear. Here, we characterized the structure of the A2AR C-terminus and the A2AR C-terminus-calmodulin complex using different biophysical methods, including native gel and analytical gel filtration, isothermal titration calorimetry, NMR spectroscopy, and small-angle X-ray scattering. We found that the C-terminus is disordered and flexible, and it binds with high affinity (Kd = 98 nM) to calmodulin without major conformational changes in the domain. Calmodulin binds to helix 8 of the A2AR in a calcium-dependent manner that can displace binding of A2AR to lipid vesicles. We also predicted and classified putative calmodulin-binding sites in a larger group of G-protein-coupled receptors. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

CsrA Represses Translation of sdiA, Which Encodes the N-Acylhomoserine-l-Lactone Receptor of Escherichia coli, by Binding Exclusively within the Coding Region of sdiA mRNA ▿ †

PubMed Central

Yakhnin, Helen; Baker, Carol S.; Berezin, Igor; Evangelista, Michael A.; Rassin, Alisa; Romeo, Tony; Babitzke, Paul

2011-01-01

The RNA binding protein CsrA is the central component of a conserved global regulatory system that activates or represses gene expression posttranscriptionally. In every known example of CsrA-mediated translational control, CsrA binds to the 5′ untranslated region of target transcripts, thereby repressing translation initiation and/or altering the stability of the RNA. Furthermore, with few exceptions, repression by CsrA involves binding directly to the Shine-Dalgarno sequence and blocking ribosome binding. sdiA encodes the quorum-sensing receptor for N-acyl-l-homoserine lactone in Escherichia coli. Because sdiA indirectly stimulates transcription of csrB, which encodes a small RNA (sRNA) antagonist of CsrA, we further explored the relationship between sdiA and the Csr system. Primer extension analysis revealed four putative transcription start sites within 85 nucleotides of the sdiA initiation codon. Potential σ70-dependent promoters were identified for each of these primer extension products. In addition, two CsrA binding sites were predicted in the initially translated region of sdiA. Expression of chromosomally integrated sdiA′-′lacZ translational fusions containing the entire promoter and CsrA binding site regions indicates that CsrA represses sdiA expression. The results from gel shift and footprint studies demonstrate that tight binding of CsrA requires both of these sites. Furthermore, the results from toeprint and in vitro translation experiments indicate that CsrA represses translation of sdiA by directly competing with 30S ribosomal subunit binding. Thus, this represents the first example of CsrA preventing translation by interacting solely within the coding region of an mRNA target. PMID:21908661

Tissue Elasticity Regulated Tumor Gene Expression: Implication for Diagnostic Biomarkers of Primitive Neuroectodermal Tumor

PubMed Central

Vu, Long T.; Keschrumrus, Vic; Zhang, Xi; Zhong, Jiang F.; Su, Qingning; Kabeer, Mustafa H.; Loudon, William G.; Li, Shengwen Calvin

2015-01-01

Background The tumor microenvironment consists of both physical and chemical factors. Tissue elasticity is one physical factor contributing to the microenvironment of tumor cells. To test the importance of tissue elasticity in cell culture, primitive neuroectodermal tumor (PNET) stem cells were cultured on soft polyacrylamide (PAA) hydrogel plates that mimics the elasticity of brain tissue compared with PNET on standard polystyrene (PS) plates. We report the molecular profiles of PNET grown on either PAA or PS. Methodology/Principal Findings A whole-genome microarray profile of transcriptional expression between the two culture conditions was performed as a way to probe effects of substrate on cell behavior in culture. The results showed more genes downregulated on PAA compared to PS. This led us to propose microRNA (miRNA) silencing as a potential mechanism for downregulation. Bioinformatic analysis predicted a greater number of miRNA binding sites from the 3' UTR of downregulated genes and identified as specific miRNA binding sites that were enriched when cells were grown on PAA—this supports the hypothesis that tissue elasticity plays a role in influencing miRNA expression. Thus, Dicer was examined to determine if miRNA processing was affected by tissue elasticity. Dicer genes were downregulated on PAA and had multiple predicted miRNA binding sites in its 3' UTR that matched the miRNA binding sites found enriched on PAA. Many differentially regulated genes were found to be present on PS but downregulated on PAA were mapped onto intron sequences. This suggests expression of alternative polyadenylation sites within intron regions that provide alternative 3' UTRs and alternative miRNA binding sites. This results in tissue specific transcriptional downregulation of mRNA in humans by miRNA. We propose a mechanism, driven by the physical characteristics of the microenvironment by which downregulation of genes occur. We found that tissue elasticity-mediated cytokines (TGFβ2 and TNFα) signaling affect expression of ECM proteins. Conclusions Our results suggest that tissue elasticity plays important roles in miRNA expression, which, in turn, regulate tumor growth or tumorigenicity. PMID:25774514

Activity of N-coordinated multi-metal-atom active site structures for Pt-free oxygen reduction reaction catalysis: Role of *OH ligands

DOE PAGES

Holby, Edward F.; Taylor, Christopher D.

2015-03-19

We report calculated oxygen reduction reaction energy pathways on multi-metal-atom structures that have previously been shown to be thermodynamically favorable. We predict that such sites have the ability to spontaneously cleave the O₂ bond and then will proceed to over-bind reaction intermediates. In particular, the *OH bound state has lower energy than the final 2 H₂O state at positive potentials. Contrary to traditional surface catalysts, this *OH binding does not poison the multi-metal-atom site but acts as a modifying ligand that will spontaneously form in aqueous environments leading to new active sites that have higher catalytic activities. These *OH boundmore » structures have the highest calculated activity to date.« less

The role of the peripheral benzodiazepine receptor in photodynamic activity of certain pyropheophorbide ether photosensitizers: albumin site II as a surrogate marker for activity.

PubMed

Dougherty, Thomas J; Sumlin, Adam B; Greco, William R; Weishaupt, Kenneth R; Vaughan, Lurine A; Pandey, Ravindra K

2002-07-01

A study has been carried out to define the importance of the peripheral benzodiazepine receptor (PBR) as a binding site for a series of chlorin-type photosensitizers, pyropheophorbide-a ethers, the subject of a previous quantitative structure-activity relationship study by us. The effects of the PBR ligand PK11195 on the photodynamic activity have been determined in vivo for certain members of this series of alkyl-substituted ethers: two of the most active derivatives (hexyl and heptyl), the least active derivative (dodecyl [C12]) and one of intermediate activity (octyl [C8]). The photodynamic therapy (PDT) effect was inhibited by PK11195 for both of the most active derivatives, but no effect on PDT activity was found for the less active C12 or C8 ethers. The inhibitory effects of PK11195 were predicted by the binding of only the active derivatives to the benzodiazepine site on albumin, ie. human serum albumin (HSA)-Site II. Thus, as with certain other types of photosensitizers, it has been demonstrated with this series of pyropheophorbide ethers that in vitro binding to HSA-Site II is a predictor of both optimal in vivo activity and binding to the PBR in vivo.

Experimental identification of specificity determinants in the domain linker of a LacI/GalR protein: bioinformatics-based predictions generate true positives and false negatives.

PubMed

Meinhardt, Sarah; Swint-Kruse, Liskin

2008-12-01

In protein families, conserved residues often contribute to a common general function, such as DNA-binding. However, unique attributes for each homolog (e.g. recognition of alternative DNA sequences) must arise from variation in other functionally-important positions. The locations of these "specificity determinant" positions are obscured amongst the background of varied residues that do not make significant contributions to either structure or function. To isolate specificity determinants, a number of bioinformatics algorithms have been developed. When applied to the LacI/GalR family of transcription regulators, several specificity determinants are predicted in the 18 amino acids that link the DNA-binding and regulatory domains. However, results from alternative algorithms are only in partial agreement with each other. Here, we experimentally evaluate these predictions using an engineered repressor comprising the LacI DNA-binding domain, the LacI linker, and the GalR regulatory domain (LLhG). "Wild-type" LLhG has altered DNA specificity and weaker lacO(1) repression compared to LacI or a similar LacI:PurR chimera. Next, predictions of linker specificity determinants were tested, using amino acid substitution and in vivo repression assays to assess functional change. In LLhG, all predicted sites are specificity determinants, as well as three sites not predicted by any algorithm. Strategies are suggested for diminishing the number of false negative predictions. Finally, individual substitutions at LLhG specificity determinants exhibited a broad range of functional changes that are not predicted by bioinformatics algorithms. Results suggest that some variants have altered affinity for DNA, some have altered allosteric response, and some appear to have changed specificity for alternative DNA ligands.

Preferential binding of daunomycin to 5'ATCG and 5'ATGC sequences revealed by footprinting titration experiments.

PubMed

Chaires, J B; Herrera, J E; Waring, M J

1990-07-03

Results from a high-resolution deoxyribonuclease I (DNase I) footprinting titration procedure are described that identify preferred daunomycin binding sites within the 160 bp tyr T DNA fragment. We have obtained single-bond resolution at 65 of the 160 potential binding sites within the tyr T fragment and have examined the effect of 0-3.0 microM total daunomycin concentration on the susceptibility of these sites toward digestion by DNase I. Four types of behavior are observed: (i) protection from DNase I cleavage; (ii) protection, but only after reaching a critical total daunomycin concentration; (iii) enhanced cleavage; (iv) no effect of added drug. Ten sites were identified as the most strongly protected on the basis of the magnitude of the reduction of their digestion product band areas in the presence of daunomycin. These were identified as the preferred daunomycin binding sites. Seven of these 10 sites are found at the end of the triplet sequences 5'ATGC and 5'ATCG, where the notation AT indicates that either A or T may occupy the position. The remaining three strongly protected sites are found at the ends of the triplet sequence 5'ATCAT. Of the preferred daunomycin binding sites we identify in this study, the sequence 5'ATCG is consistent with the specificity predicted by the theoretical studies of Chen et al. [Chen, K.-X., Gresh, N., & Pullman, B. (1985) J. Biomol. Struct. Dyn. 3, 445-466] and is the very sequence to which daunomycin is observed to be bound in two recent X-ray crystallographic studies. Solution studies, theoretical studies, and crystallographic studies have thus converged to provide a consistent and coherent picture of the sequence preference of this important anticancer antibiotic.

CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation.

PubMed

Nikulova, Anna A; Favorov, Alexander V; Sutormin, Roman A; Makeev, Vsevolod J; Mironov, Andrey A

2012-07-01

Identification of transcriptional regulatory regions and tracing their internal organization are important for understanding the eukaryotic cell machinery. Cis-regulatory modules (CRMs) of higher eukaryotes are believed to possess a regulatory 'grammar', or preferred arrangement of binding sites, that is crucial for proper regulation and thus tends to be evolutionarily conserved. Here, we present a method CORECLUST (COnservative REgulatory CLUster STructure) that predicts CRMs based on a set of positional weight matrices. Given regulatory regions of orthologous and/or co-regulated genes, CORECLUST constructs a CRM model by revealing the conserved rules that describe the relative location of binding sites. The constructed model may be consequently used for the genome-wide prediction of similar CRMs, and thus detection of co-regulated genes, and for the investigation of the regulatory grammar of the system. Compared with related methods, CORECLUST shows better performance at identification of CRMs conferring muscle-specific gene expression in vertebrates and early-developmental CRMs in Drosophila.

Analysis of the Binding Sites of Porcine Sialoadhesin Receptor with PRRSV

PubMed Central

Jiang, Yibo; Khan, Faheem Ahmed; Pandupuspitasari, Nuruliarizki Shinta; Kadariya, Ishwari; Cheng, Zhangrui; Ren, Yuwei; Chen, Xing; Zhou, Ao; Yang, Liguo; Kong, Dexin; Zhang, Shujun

2013-01-01

Porcine reproductive and respiratory syndrome virus (PRRSV) can infect pigs and cause enormous economic losses to the pig industry worldwide. Porcine sialoadhesin (pSN) and CD163 have been identified as key viral receptors on porcine alveolar macrophages (PAM), a main target cell infected by PRRSV. In this study, the protein structures of amino acids 1–119 from the pSN and cSN (cattle sialoadhesin) N-termini (excluding the 19-amino acid signal peptide) were modeled via homology modeling based on mSN (mouse sialoadhesin) template structures using bioinformatics tools. Subsequently, pSN and cSN homology structures were superposed onto the mSN protein structure to predict the binding sites of pSN. As a validation experiment, the SN N-terminus (including the wild-type and site-directed-mutant-types of pSN and cSN) was cloned and expressed as a SN-GFP chimera protein. The binding activity between SN and PRRSV was confirmed by WB (Western blotting), FAR-WB (far Western blotting), ELISA (enzyme-linked immunosorbent assay) and immunofluorescence assay. We found that the S107 amino acid residue in the pSN N-terminal played a crucial role in forming a special cavity, as well as a hydrogen bond for enhancing PRRSV binding during PRRSV infection. S107 may be glycosylated during PRRSV infection and may also be involved in forming the cavity for binding PRRSV along with other sites, including W2, Y44, S45, R97, R105, W106 and V109. Additionally, S107 might also be important for pSN binding with PRRSV. However, the function of these binding sites must be confirmed by further studies. PMID:24351868

Designing small molecules to target cryptic pockets yields both positive and negative allosteric modulators

PubMed Central

Moeder, Katelyn E.; Ho, Chris M. W.; Zimmerman, Maxwell I.; Frederick, Thomas E.; Bowman, Gregory R.

2017-01-01

Allosteric drugs, which bind to proteins in regions other than their main ligand-binding or active sites, make it possible to target proteins considered “undruggable” and to develop new therapies that circumvent existing resistance. Despite growing interest in allosteric drug discovery, rational design is limited by a lack of sufficient structural information about alternative binding sites in proteins. Previously, we used Markov State Models (MSMs) to identify such “cryptic pockets,” and here we describe a method for identifying compounds that bind in these cryptic pockets and modulate enzyme activity. Experimental tests validate our approach by revealing both an inhibitor and two activators of TEM β-lactamase (TEM). To identify hits, a library of compounds is first virtually screened against either the crystal structure of a known cryptic pocket or an ensemble of structures containing the same cryptic pocket that is extracted from an MSM. Hit compounds are then screened experimentally and characterized kinetically in individual assays. We identify three hits, one inhibitor and two activators, demonstrating that screening for binding to allosteric sites can result in both positive and negative modulation. The hit compounds have modest effects on TEM activity, but all have higher affinities than previously identified inhibitors, which bind the same cryptic pocket but were found, by chance, via a computational screen targeting the active site. Site-directed mutagenesis of key contact residues predicted by the docking models is used to confirm that the compounds bind in the cryptic pocket as intended. Because hit compounds are identified from docking against both the crystal structure and structures from the MSM, this platform should prove suitable for many proteins, particularly targets whose crystal structures lack obvious druggable pockets, and for identifying both inhibitory and activating small-molecule modulators. PMID:28570708

In Silico Detection of Sequence Variations Modifying Transcriptional Regulation

PubMed Central

Andersen, Malin C; Engström, Pär G; Lithwick, Stuart; Arenillas, David; Eriksson, Per; Lenhard, Boris; Wasserman, Wyeth W; Odeberg, Jacob

2008-01-01

Identification of functional genetic variation associated with increased susceptibility to complex diseases can elucidate genes and underlying biochemical mechanisms linked to disease onset and progression. For genes linked to genetic diseases, most identified causal mutations alter an encoded protein sequence. Technological advances for measuring RNA abundance suggest that a significant number of undiscovered causal mutations may alter the regulation of gene transcription. However, it remains a challenge to separate causal genetic variations from linked neutral variations. Here we present an in silico driven approach to identify possible genetic variation in regulatory sequences. The approach combines phylogenetic footprinting and transcription factor binding site prediction to identify variation in candidate cis-regulatory elements. The bioinformatics approach has been tested on a set of SNPs that are reported to have a regulatory function, as well as background SNPs. In the absence of additional information about an analyzed gene, the poor specificity of binding site prediction is prohibitive to its application. However, when additional data is available that can give guidance on which transcription factor is involved in the regulation of the gene, the in silico binding site prediction improves the selection of candidate regulatory polymorphisms for further analyses. The bioinformatics software generated for the analysis has been implemented as a Web-based application system entitled RAVEN (regulatory analysis of variation in enhancers). The RAVEN system is available at http://www.cisreg.ca for all researchers interested in the detection and characterization of regulatory sequence variation. PMID:18208319

Predicted structure of MIF/CD74 and RTL1000/CD74 complexes.

PubMed

Meza-Romero, Roberto; Benedek, Gil; Leng, Lin; Bucala, Richard; Vandenbark, Arthur A

2016-04-01

Macrophage migration inhibitory factor (MIF) is a key cytokine in autoimmune and inflammatory diseases that attracts and then retains activated immune cells from the periphery to the tissues. MIF exists as a homotrimer and its effects are mediated through its primary receptor, CD74 (the class II invariant chain that exhibits a highly structured trimerization domain), present on class II expressing cells. Although a number of binding residues have been identified between MIF and CD74 trimers, their spatial orientation has not been established. Using a docking program in silico, we have modeled binding interactions between CD74 and MIF as well as CD74 and a competitive MIF inhibitor, RTL1000, a partial MHC class II construct that is currently in clinical trials for multiple sclerosis. These analyses revealed 3 binding sites on the MIF trimer that each were predicted to bind one CD74 trimer through interactions with two distinct 5 amino acid determinants. Surprisingly, predicted binding of one CD74 trimer to a single RTL1000 antagonist utilized the same two 5 residue determinants, providing strong suggestive evidence in support of the MIF binding regions on CD74. Taken together, our structural modeling predicts a new MIF(CD74)3 dodecamer that may provide the basis for increased MIF potency and the requirement for ~3-fold excess RTL1000 to achieve full antagonism.

The Innate Immune Database (IIDB)

PubMed Central

Korb, Martin; Rust, Aistair G; Thorsson, Vesteinn; Battail, Christophe; Li, Bin; Hwang, Daehee; Kennedy, Kathleen A; Roach, Jared C; Rosenberger, Carrie M; Gilchrist, Mark; Zak, Daniel; Johnson, Carrie; Marzolf, Bruz; Aderem, Alan; Shmulevich, Ilya; Bolouri, Hamid

2008-01-01

Background As part of a National Institute of Allergy and Infectious Diseases funded collaborative project, we have performed over 150 microarray experiments measuring the response of C57/BL6 mouse bone marrow macrophages to toll-like receptor stimuli. These microarray expression profiles are available freely from our project web site . Here, we report the development of a database of computationally predicted transcription factor binding sites and related genomic features for a set of over 2000 murine immune genes of interest. Our database, which includes microarray co-expression clusters and a host of web-based query, analysis and visualization facilities, is available freely via the internet. It provides a broad resource to the research community, and a stepping stone towards the delineation of the network of transcriptional regulatory interactions underlying the integrated response of macrophages to pathogens. Description We constructed a database indexed on genes and annotations of the immediate surrounding genomic regions. To facilitate both gene-specific and systems biology oriented research, our database provides the means to analyze individual genes or an entire genomic locus. Although our focus to-date has been on mammalian toll-like receptor signaling pathways, our database structure is not limited to this subject, and is intended to be broadly applicable to immunology. By focusing on selected immune-active genes, we were able to perform computationally intensive expression and sequence analyses that would currently be prohibitive if applied to the entire genome. Using six complementary computational algorithms and methodologies, we identified transcription factor binding sites based on the Position Weight Matrices available in TRANSFAC. For one example transcription factor (ATF3) for which experimental data is available, over 50% of our predicted binding sites coincide with genome-wide chromatin immnuopreciptation (ChIP-chip) results. Our database can be interrogated via a web interface. Genomic annotations and binding site predictions can be automatically viewed with a customized version of the Argo genome browser. Conclusion We present the Innate Immune Database (IIDB) as a community resource for immunologists interested in gene regulatory systems underlying innate responses to pathogens. The database website can be freely accessed at . PMID:18321385

Analysis of molecular determinants of affinity and relative efficacy of a series of R- and S-2-(dipropylamino)tetralins at the 5-HT1A serotonin receptor

PubMed Central

Alder, J Tracy; Hacksell, Uli; Strange, Philip G

2003-01-01

Factors influencing agonist affinity and relative efficacy have been studied for the 5-HT1A serotonin receptor using membranes of CHO cells expressing the human form of the receptor and a series of R-and S-2-(dipropylamino)tetralins (nonhydroxylated and monohydroxylated (5-OH, 6-OH, 7-OH, 8-OH) species). Ligand binding studies were used to determine dissociation constants for agonist binding to the 5-HT1A receptor: Ki values for agonists were determined in competition versus the binding of the agonist [3H]-8-OH DPAT. Competition data were all fitted best by a one-binding site model.Ki values for agonists were also determined in competition versus the binding of the antagonist [3H]-NAD-199. Competition data were all fitted best by a two-binding site model, and agonist affinities for the higher (Kh) and lower affinity (Kl) sites were determined. The ability of the agonists to activate the 5-HT1A receptor was determined using stimulation of [35S]-GTPγS binding. Maximal effects of agonists (Emax) and their potencies (EC50) were determined from concentration/response curves for stimulation of [35S]-GTPγS binding. Kl/Kh determined from ligand binding assays correlated with the relative efficacy (relative Emax) of agonists determined in [35S]-GTPγS binding assays. There was also a correlation between Kl/Kh and Kl/EC50 for agonists determined from ligand binding and [35S]-GTPγS binding assays. Simulations of agonist binding and effect data were performed using the Ternary Complex Model in order to assess the use of Kl/Kh for predicting the relative efficacy of agonists. PMID:12684269

Steric and thermodynamic limits of design for the incorporation of large unnatural amino acids in aminoacyl-tRNA synthetase enzymes.

PubMed

Armen, Roger S; Schiller, Stefan M; Brooks, Charles L

2010-06-01

Orthogonal aminoacyl-tRNA synthetase/tRNA pairs from archaea have been evolved to facilitate site specific in vivo incorporation of unnatural amino acids into proteins in Escherichia coli. Using this approach, unnatural amino acids have been successfully incorporated with high translational efficiency and fidelity. In this study, CHARMM-based molecular docking and free energy calculations were used to evaluate rational design of specific protein-ligand interactions for aminoacyl-tRNA synthetases. A series of novel unnatural amino acid ligands were docked into the p-benzoyl-L-phenylalanine tRNA synthetase, which revealed that the binding pocket of the enzyme does not provide sufficient space for significantly larger ligands. Specific binding site residues were mutated to alanine to create additional space to accommodate larger target ligands, and then mutations were introduced to improve binding free energy. This approach was used to redesign binding sites for several different target ligands, which were then tested against the standard 20 amino acids to verify target specificity. Only the synthetase designed to bind Man-alpha-O-Tyr was predicted to be sufficiently selective for the target ligand and also thermodynamically stable. Our study suggests that extensive redesign of the tRNA synthatase binding pocket for large bulky ligands may be quite thermodynamically unfavorable.

Information analysis of sequences that bind the replication initiator RepA | Center for Cancer Research

Cancer.gov

The tall letters represent the highly conserved bases in DNA binding sites of several prokaryotic repressors and activators. Conservation is strongest where major grooves of the double helical DNA (represented by crests of a cosine wave) face the protein. This shows that conservation analysis alone can be used to predict the face of DNA that contacts the proteins.

Molecular Simulation of Receptor Occupancy and Tumor Penetration of an Antibody and Smaller Scaffolds: Application to Molecular Imaging.

PubMed

Orcutt, Kelly D; Adams, Gregory P; Wu, Anna M; Silva, Matthew D; Harwell, Catey; Hoppin, Jack; Matsumura, Manabu; Kotsuma, Masakatsu; Greenberg, Jonathan; Scott, Andrew M; Beckman, Robert A

2017-10-01

Competitive radiolabeled antibody imaging can determine the unlabeled intact antibody dose that fully blocks target binding but may be confounded by heterogeneous tumor penetration. We evaluated the hypothesis that smaller radiolabeled constructs can be used to more accurately evaluate tumor expressed receptors. The Krogh cylinder distributed model, including bivalent binding and variable intervessel distances, simulated distribution of smaller constructs in the presence of increasing doses of labeled antibody forms. Smaller constructs <25 kDa accessed binding sites more uniformly at large distances from blood vessels compared with larger constructs and intact antibody. These observations were consistent for different affinity and internalization characteristics of constructs. As predicted, a higher dose of unlabeled intact antibody was required to block binding to these distant receptor sites. Small radiolabeled constructs provide more accurate information on total receptor expression in tumors and reveal the need for higher antibody doses for target receptor blockade.

APADB: a database for alternative polyadenylation and microRNA regulation events

PubMed Central

Müller, Sören; Rycak, Lukas; Afonso-Grunz, Fabian; Winter, Peter; Zawada, Adam M.; Damrath, Ewa; Scheider, Jessica; Schmäh, Juliane; Koch, Ina; Kahl, Günter; Rotter, Björn

2014-01-01

Alternative polyadenylation (APA) is a widespread mechanism that contributes to the sophisticated dynamics of gene regulation. Approximately 50% of all protein-coding human genes harbor multiple polyadenylation (PA) sites; their selective and combinatorial use gives rise to transcript variants with differing length of their 3′ untranslated region (3′UTR). Shortened variants escape UTR-mediated regulation by microRNAs (miRNAs), especially in cancer, where global 3′UTR shortening accelerates disease progression, dedifferentiation and proliferation. Here we present APADB, a database of vertebrate PA sites determined by 3′ end sequencing, using massive analysis of complementary DNA ends. APADB provides (A)PA sites for coding and non-coding transcripts of human, mouse and chicken genes. For human and mouse, several tissue types, including different cancer specimens, are available. APADB records the loss of predicted miRNA binding sites and visualizes next-generation sequencing reads that support each PA site in a genome browser. The database tables can either be browsed according to organism and tissue or alternatively searched for a gene of interest. APADB is the largest database of APA in human, chicken and mouse. The stored information provides experimental evidence for thousands of PA sites and APA events. APADB combines 3′ end sequencing data with prediction algorithms of miRNA binding sites, allowing to further improve prediction algorithms. Current databases lack correct information about 3′UTR lengths, especially for chicken, and APADB provides necessary information to close this gap. Database URL: http://tools.genxpro.net/apadb/ PMID:25052703

Physical signals for protein-DNA recognition

NASA Astrophysics Data System (ADS)

Cao, Xiao-Qin; Zeng, Jia; Yan, Hong

2009-09-01

This paper discovers consensus physical signals around eukaryotic splice sites, transcription start sites, and replication origin start and end sites on a genome-wide scale based on their DNA flexibility profiles calculated by three different flexibility models. These salient physical signals are localized highly rigid and flexible DNAs, which may play important roles in protein-DNA recognition by the sliding search mechanism. The found physical signals lead us to a detailed hypothetical view of the search process in which a DNA-binding protein first finds a genomic region close to the target site from an arbitrary starting location by three-dimensional (3D) hopping and intersegment transfer mechanisms for long distances, and subsequently uses the one-dimensional (1D) sliding mechanism facilitated by the localized highly rigid DNAs to accurately locate the target flexible binding site within 30 bp (base pair) short distances. Guided by these physical signals, DNA-binding proteins rapidly search the entire genome to recognize a specific target site from the 3D to 1D pathway. Our findings also show that current promoter prediction programs (PPPs) based on DNA physical properties may suffer from lots of false positives because other functional sites such as splice sites and replication origins have similar physical signals as promoters do.

In silico and in vitro Studies on Begomovirus Induced Andrographolide Biosynthesis Pathway in Andrographis Paniculata for Combating Inflammation and Cancer.

PubMed

Khan, Asifa; Sharma, Pooja; Khan, Feroz; Ajayakumar, P V; Shanker, Karuna; Samad, Abdul

2016-07-01

Andrographolide and neoandrographolide are major bioactive molecules of Andrographis paniculata, a well-known medicinal plant. These molecules exhibited varying degrees of anti-inflammatory and anticancer activities in-vitro and in-vivo. Role of begomovirus protein C2/TrAP in biosynthesis of andrographolide was identified through molecular modeling, docking and predicted results were substantiated by in vitro studies. Homology molecular modeling and molecular docking were performed to study the binding conformations and different bonding behaviors, in order to reveal the possible mechanism of action behind higher accumulation of andrographolide. It was concluded that C2/TrAP inhibit the activation of SNF1-Related Protein Kinase-1 (SnRK1) in terpenoid pathway and removes the negative regulation of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR) by SnRK1, leading to higher accumulation of andrographolide and neoandrographolide in begomovirus infected plants. The binding site residues of SnRK1 docked with C2/TrAP were found to be associated with ATP binding site, substrate binding site and activation loop. Predicted results were also validated by HPTLC. This study provides important insights into understanding the role of viral protein in altering the regulation of biosynthesis of andrographolide and could be used in future research to develop biomimetic methods for increasing the production of such phytometabolites having anti-cancerous and anti-inflammatory properties. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Testing inhomogeneous solvation theory in structure-based ligand discovery.

PubMed

Balius, Trent E; Fischer, Marcus; Stein, Reed M; Adler, Thomas B; Nguyen, Crystal N; Cruz, Anthony; Gilson, Michael K; Kurtzman, Tom; Shoichet, Brian K

2017-08-15

Binding-site water is often displaced upon ligand recognition, but is commonly neglected in structure-based ligand discovery. Inhomogeneous solvation theory (IST) has become popular for treating this effect, but it has not been tested in controlled experiments at atomic resolution. To do so, we turned to a grid-based version of this method, GIST, readily implemented in molecular docking. Whereas the term only improves docking modestly in retrospective ligand enrichment, it could be added without disrupting performance. We thus turned to prospective docking of large libraries to investigate GIST's impact on ligand discovery, geometry, and water structure in a model cavity site well-suited to exploring these terms. Although top-ranked docked molecules with and without the GIST term often overlapped, many ligands were meaningfully prioritized or deprioritized; some of these were selected for testing. Experimentally, 13/14 molecules prioritized by GIST did bind, whereas none of the molecules that it deprioritized were observed to bind. Nine crystal complexes were determined. In six, the ligand geometry corresponded to that predicted by GIST, for one of these the pose without the GIST term was wrong, and three crystallographic poses differed from both predictions. Notably, in one structure, an ordered water molecule with a high GIST displacement penalty was observed to stay in place. Inclusion of this water-displacement term can substantially improve the hit rates and ligand geometries from docking screens, although the magnitude of its effects can be small and its impact in drug binding sites merits further controlled studies.

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.

Binding sites for interaction of peroxiredoxin 6 with surfactant protein A.

PubMed

Krishnaiah, Saikumari Y; Dodia, Chandra; Sorokina, Elena M; Li, Haitao; Feinstein, Sheldon I; Fisher, Aron B

2016-04-01

Peroxiredoxin 6 (Prdx6) is a bifunctional enzyme with peroxidase and phospholipase A2 (PLA2) activities. This protein participates in the degradation and remodeling of internalized dipalmitoylphosphatidylcholine (DPPC), the major phospholipid component of lung surfactant. We have shown previously that the PLA2 activity of Prdx6 is inhibited by the lung surfactant-associated protein called surfactant protein A (SP-A) through direct protein-protein interaction. Docking of SPA and Prdx6 was modeled using the ZDOCK (zlab.bu.edu) program in order to predict molecular sites for binding of the two proteins. The predicted peptide sequences were evaluated for binding to the opposite protein using isothermal titration calorimetry and circular dichroism measurement followed by determination of the effect of the SP-A peptide on the PLA2 activity of Prdx6. The sequences 195EEEAKKLFPK204.in the Prdx6 helix and 83DEELQTELYEIKHQIL99 in SP-A were identified as the sites for hydrophobic interaction and H(+)-bonding between the 2 proteins. Treatment of mouse endothelial cells with the SP-A peptide inhibited their recovery from lipid peroxidation associated with oxidative stress indicating inhibition of Prdx6 activity by the peptide in the intact cell. Copyright © 2015 Elsevier B.V. All rights reserved.

Predicted Structures of the Proton-Bound Membrane-Embedded Rotor Rings of the Saccharomyces cerevisiae and Escherichia coli ATP Synthases.

PubMed

Zhou, Wenchang; Leone, Vanessa; Krah, Alexander; Faraldo-Gómez, José D

2017-04-20

Recent years have witnessed a renewed interest in the ATP synthase as a drug target against human pathogens. Indeed, clinical, biochemical, and structural data indicate that hydrophobic inhibitors targeting the membrane-embedded proton-binding sites of the c-subunit ring could serve as last-resort antibiotics against multidrug resistant strains. However, because inhibition of the mitochondrial ATP synthase in humans is lethal, it is essential that these inhibitors be not only potent but also highly selective for the bacterial enzyme. To this end, a detailed understanding of the structure of this protein target is arguably instrumental. Here, we use computational methods to predict the atomic structures of the proton-binding sites in two prototypical c-rings: that of the ATP synthase from Saccharomyces cerevisiae, which is a model system for mitochondrial enzymes, and that from Escherichia coli, which can be pathogenic for humans. Our study reveals the structure of these binding sites loaded with protons and in the context of the membrane, that is, in the state that would mediate the recognition of a potential inhibitor. Both structures reflect a mode of proton coordination unlike those previously observed in other c-ring structures, whether experimental or modeled.

Role for a region of helically unstable DNA within the Epstein-Barr virus latent cycle origin of DNA replication oriP in origin function

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

Polonskaya, Zhanna; Benham, Craig J.; Hearing, Janet

The minimal replicator of the Epstein-Barr virus (EBV) latent cycle origin of DNA replication oriP is composed of two binding sites for the Epstein-Barr virus nuclear antigen-1 (EBNA-1) and flanking inverted repeats that bind the telomere repeat binding factor TRF2. Although not required for minimal replicator activity, additional binding sites for EBNA-1 and TRF2 and one or more auxiliary elements located to the right of the EBNA-1/TRF2 sites are required for the efficient replication of oriP plasmids. Another region of oriP that is predicted to be destabilized by DNA supercoiling is shown here to be an important functional component ofmore » oriP. The ability of DNA fragments of unrelated sequence and possessing supercoiled-induced DNA duplex destabilized (SIDD) structures, but not fragments characterized by helically stable DNA, to substitute for this component of oriP demonstrates a role for the SIDD region in the initiation of oriP-plasmid DNA replication.« less

Histatin 5 binds to Porphyromonas gingivalis hemagglutinin B (HagB) and alters HagB-induced chemokine responses

NASA Astrophysics Data System (ADS)

Borgwardt, Derek S.; Martin, Aaron D.; van Hemert, Jonathan R.; Yang, Jianyi; Fischer, Carol L.; Recker, Erica N.; Nair, Prashant R.; Vidva, Robinson; Chandrashekaraiah, Shwetha; Progulske-Fox, Ann; Drake, David; Cavanaugh, Joseph E.; Vali, Shireen; Zhang, Yang; Brogden, Kim A.

2014-01-01

Histatins are human salivary gland peptides with anti-microbial and anti-inflammatory activities. In this study, we hypothesized that histatin 5 binds to Porphyromonas gingivalis hemagglutinin B (HagB) and attenuates HagB-induced chemokine responses in human myeloid dendritic cells. Histatin 5 bound to immobilized HagB in a surface plasmon resonance (SPR) spectroscopy-based biosensor system. SPR spectroscopy kinetic and equilibrium analyses, protein microarray studies, and I-TASSER structural modeling studies all demonstrated two histatin 5 binding sites on HagB. One site had a stronger affinity with a KD1 of 1.9 μM and one site had a weaker affinity with a KD2 of 60.0 μM. Binding has biological implications and predictive modeling studies and exposure of dendritic cells both demonstrated that 20.0 μM histatin 5 attenuated (p < 0.05) 0.02 μM HagB-induced CCL3/MIP-1α, CCL4/MIP-1β, and TNFα responses. Thus histatin 5 is capable of attenuating chemokine responses, which may help control oral inflammation.

Onco-Regulon: an integrated database and software suite for site specific targeting of transcription factors of cancer genes

PubMed Central

Tomar, Navneet; Mishra, Akhilesh; Mrinal, Nirotpal; Jayaram, B.

2016-01-01

Transcription factors (TFs) bind at multiple sites in the genome and regulate expression of many genes. Regulating TF binding in a gene specific manner remains a formidable challenge in drug discovery because the same binding motif may be present at multiple locations in the genome. Here, we present Onco-Regulon (http://www.scfbio-iitd.res.in/software/onco/NavSite/index.htm), an integrated database of regulatory motifs of cancer genes clubbed with Unique Sequence-Predictor (USP) a software suite that identifies unique sequences for each of these regulatory DNA motifs at the specified position in the genome. USP works by extending a given DNA motif, in 5′→3′, 3′ →5′ or both directions by adding one nucleotide at each step, and calculates the frequency of each extended motif in the genome by Frequency Counter programme. This step is iterated till the frequency of the extended motif becomes unity in the genome. Thus, for each given motif, we get three possible unique sequences. Closest Sequence Finder program predicts off-target drug binding in the genome. Inclusion of DNA-Protein structural information further makes Onco-Regulon a highly informative repository for gene specific drug development. We believe that Onco-Regulon will help researchers to design drugs which will bind to an exclusive site in the genome with no off-target effects, theoretically. Database URL: http://www.scfbio-iitd.res.in/software/onco/NavSite/index.htm PMID:27515825

In silico approaches to predict the potential of milk protein-derived peptides as dipeptidyl peptidase IV (DPP-IV) inhibitors.

PubMed

Nongonierma, Alice B; Mooney, Catherine; Shields, Denis C; FitzGerald, Richard J

2014-07-01

Molecular docking of a library of all 8000 possible tripeptides to the active site of DPP-IV was used to determine their binding potential. A number of tripeptides were selected for experimental testing, however, there was no direct correlation between the Vina score and their in vitro DPP-IV inhibitory properties. While Trp-Trp-Trp, the peptide with the best docking score, was a moderate DPP-IV inhibitor (IC50 216μM), Lineweaver and Burk analysis revealed its action to be non-competitive. This suggested that it may not bind to the active site of DPP-IV as assumed in the docking prediction. Furthermore, there was no significant link between DPP-IV inhibition and the physicochemical properties of the peptides (molecular mass, hydrophobicity, hydrophobic moment (μH), isoelectric point (pI) and charge). LIGPLOTs indicated that competitive inhibitory peptides were predicted to have both hydrophobic and hydrogen bond interactions with the active site of DPP-IV. DPP-IV inhibitory peptides generally had a hydrophobic or aromatic amino acid at the N-terminus, preferentially a Trp for non-competitive inhibitors and a broader range of residues for competitive inhibitors (Ile, Leu, Val, Phe, Trp or Tyr). Two of the potent DPP-IV inhibitors, Ile-Pro-Ile and Trp-Pro (IC50 values of 3.5 and 44.2μM, respectively), were predicted to be gastrointestinally/intestinally stable. This work highlights the needs to test the assumptions (i.e. competitive binding) of any integrated strategy of computational and experimental screening, in optimizing screening. Future strategies targeting allosteric mechanisms may need to rely more on structure-activity relationship modeling, rather than on docking, in computationally selecting peptides for screening. Copyright © 2014 Elsevier Inc. All rights reserved.

sc-PDB: an annotated database of druggable binding sites from the Protein Data Bank.

PubMed

Kellenberger, Esther; Muller, Pascal; Schalon, Claire; Bret, Guillaume; Foata, Nicolas; Rognan, Didier

2006-01-01

The sc-PDB is a collection of 6 415 three-dimensional structures of binding sites found in the Protein Data Bank (PDB). Binding sites were extracted from all high-resolution crystal structures in which a complex between a protein cavity and a small-molecular-weight ligand could be identified. Importantly, ligands are considered from a pharmacological and not a structural point of view. Therefore, solvents, detergents, and most metal ions are not stored in the sc-PDB. Ligands are classified into four main categories: nucleotides (< 4-mer), peptides (< 9-mer), cofactors, and organic compounds. The corresponding binding site is formed by all protein residues (including amino acids, cofactors, and important metal ions) with at least one atom within 6.5 angstroms of any ligand atom. The database was carefully annotated by browsing several protein databases (PDB, UniProt, and GO) and storing, for every sc-PDB entry, the following features: protein name, function, source, domain and mutations, ligand name, and structure. The repository of ligands has also been archived by diversity analysis of molecular scaffolds, and several chemoinformatics descriptors were computed to better understand the chemical space covered by stored ligands. The sc-PDB may be used for several purposes: (i) screening a collection of binding sites for predicting the most likely target(s) of any ligand, (ii) analyzing the molecular similarity between different cavities, and (iii) deriving rules that describe the relationship between ligand pharmacophoric points and active-site properties. The database is periodically updated and accessible on the web at http://bioinfo-pharma.u-strasbg.fr/scPDB/.

Prediction of the binding mode of N2-phenylguanine derivative inhibitors to herpes simplex virus type 1 thymidine kinase

NASA Astrophysics Data System (ADS)

Gaudio, Anderson Coser; Takahata, Yuji; Richards, William Graham

1998-01-01

The probable binding mode of the herpes simplex virus thymidine kinase (HSV1 TK) N2-[substituted]-phenylguanine inhibitors is proposed. A computational experiment was designed to check some qualitative binding parameters and to calculate the interaction binding energies of alternative binding modes of N2-phenylguanines. The known binding modes of the HSV1 TK natural substrate deoxythymidine and one of its competitive inhibitors ganciclovir were used as templates. Both the qualitative and quantitative parts of the computational experiment indicated that the N2-phenylguanine derivatives bind to the HSV1 TK active site in the deoxythymidine-like binding mode. An experimental observation that N2-phenylguanosine derivatives are not phosphorylated during the interaction with the HSV1 TK gives support to the proposed binding mode.

Empirically Optimized Flow Cytometric Immunoassay Validates Ambient Analyte Theory

PubMed Central

Parpia, Zaheer A.; Kelso, David M.

2010-01-01

Ekins’ ambient analyte theory predicts, counter intuitively, that an immunoassay’s limit of detection can be improved by reducing the amount of capture antibody. In addition, it also anticipates that results should be insensitive to the volume of sample as well as the amount of capture antibody added. The objective of this study is to empirically validate all of the performance characteristics predicted by Ekins’ theory. Flow cytometric analysis was used to detect binding between a fluorescent ligand and capture microparticles since it can directly measure fractional occupancy, the primary response variable in ambient analyte theory. After experimentally determining ambient analyte conditions, comparisons were carried out between ambient and non-ambient assays in terms of their signal strengths, limits of detection, and their sensitivity to variations in reaction volume and number of particles. The critical number of binding sites required for an assay to be in the ambient analyte region was estimated to be 0.1VKd. As predicted, such assays exhibited superior signal/noise levels and limits of detection; and were not affected by variations in sample volume and number of binding sites. When the signal detected measures fractional occupancy, ambient analyte theory is an excellent guide to developing assays with superior performance characteristics. PMID:20152793

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

Structural determinants of species-selective substrate recognition in human and Drosophila serotonin transporters revealed through computational docking studies

PubMed Central

Kaufmann, Kristian W.; Dawson, Eric S.; Henry, L. Keith; Field, Julie R.; Blakely, Randy D.; Meiler, Jens

2009-01-01

To identify potential determinants of substrate selectivity in serotonin (5-HT) transporters (SERT), models of human and Drosophila serotonin transporters (hSERT, dSERT) were built based on the leucine transporter (LeuTAa) structure reported by Yamashita et al. (Nature 2005;437:215–223), PBDID 2A65. Although the overall amino acid identity between SERTs and the LeuTAa is only 17%, it increases to above 50% in the first shell of the putative 5-HT binding site, allowing de novo computational docking of tryptamine derivatives in atomic detail. Comparison of hSERT and dSERT complexed with substrates pinpoints likely structural determinants for substrate binding. Forgoing the use of experimental transport and binding data of tryptamine derivatives for construction of these models enables us to cHitically assess and validate their predictive power: A single 5-HT binding mode was identified that retains the amine placement observed in the LeuTAa structure, matches site-directed mutagenesis and substituted cysteine accessibility method (SCAM) data, complies with support vector machine derived relations activity relations, and predicts computational binding energies for 5-HT analogs with a significant correlation coefficient (R = 0.72). This binding mode places 5-HT deep in the binding pocket of the SERT with the 5-position near residue hSERT A169/dSERT D164 in transmembrane helix 3, the indole nitrogen next to residue Y176/Y171, and the ethylamine tail under residues F335/F327 and S336/S328 within 4 Å of residue D98. Our studies identify a number of potential contacts whose contribution to substrate binding and transport was previously unsuspected. PMID:18704946

SPACER: server for predicting allosteric communication and effects of regulation

PubMed Central

Goncearenco, Alexander; Mitternacht, Simon; Yong, Taipang; Eisenhaber, Birgit; Eisenhaber, Frank; Berezovsky, Igor N.

2013-01-01

The SPACER server provides an interactive framework for exploring allosteric communication in proteins with different sizes, degrees of oligomerization and function. SPACER uses recently developed theoretical concepts based on the thermodynamic view of allostery. It proposes easily tractable and meaningful measures that allow users to analyze the effect of ligand binding on the intrinsic protein dynamics. The server shows potential allosteric sites and allows users to explore communication between the regulatory and functional sites. It is possible to explore, for instance, potential effector binding sites in a given structure as targets for allosteric drugs. As input, the server only requires a single structure. The server is freely available at http://allostery.bii.a-star.edu.sg/. PMID:23737445

Docking modes of BB-3497 into the PDF active site--a comparison of the pure MM and QM/MM based docking strategies.

PubMed

Kumari, Tripti; Issar, Upasana; Kakkar, Rita

2014-01-01

Peptide deformylase (PDF) has emerged as an important antibacterial drug target. Considerable effort is being directed toward developing peptidic and non-peptidic inhibitors for this metalloprotein. In this work, the known peptidic inhibitor BB-3497 and its various ionization and tautomeric states are evaluated for their inhibition efficiency against PDF using a molecular mechanics (MM) approach as well as a mixed quantum mechanics/molecular mechanics (QM/MM) approach, with an aim to understand the interactions in the binding site. The evaluated Gibbs energies of binding with the mixed QM/MM approach are shown to have the best predictive power. The experimental pose is found to have the most negative Gibbs energy of binding, and also the smallest strain energy. A quantum mechanical evaluation of the active site reveals the requirement of strong chelation by the ligand with the metal ion. The investigated ligand chelates the metal ion through the two oxygens of its reverse hydroxamate moiety, particularly the N-O(-) oxygen, forming strong covalent bonds with the metal ion, which is penta-coordinated. In the uninhibited state, the metal ion is tetrahedrally coordinated, and hence chelation with the inhibitor is associated with an increase of the metal ion coordination. Thus, the strong binding of the ligand at the binding site is accounted for.

Local anesthetics QX 572 and benzocaine act at separate sites on the batrachotoxin-activated sodium channel

PubMed Central

1981-01-01

We have studied the effect of local anesthetics QX 572, which is permanently charged, and benzocaine, which is neutral, on batrachotoxin- activated sodium channels in mouse neuroblastoma N18 cells. The dose- response curves for each drug suggest that QX 752 and benzocaine each act on a single class of binding sites. The dissociation constants are 3.15 X 10(-5) M for QX 572 and 2.65 X 10(-4) M for benzocaine. Equilibrium and kinetic experiments indicate that both drugs are competitive inhibitors of batrachotoxin. When benzocaine and QX 572 are present with batrachotoxin, they are much more effective at inhibiting Na+ flux than would be predicted by a one-site model. Our results indicate that QX 572 and benzocaine bind to separate sites, each of which interacts competitively with batrachotoxin. PMID:6267160

Identifying potential selective fluorescent probes for cancer-associated protein carbonic anhydrase IX using a computational approach.

PubMed

Kamstra, Rhiannon L; Floriano, Wely B

2014-11-01

Carbonic anhydrase IX (CAIX) is a biomarker for tumor hypoxia. Fluorescent inhibitors of CAIX have been used to study hypoxic tumor cell lines. However, these inhibitor-based fluorescent probes may have a therapeutic effect that is not appropriate for monitoring treatment efficacy. In the search for novel fluorescent probes that are not based on known inhibitors, a database of 20,860 fluorescent compounds was virtually screened against CAIX using hierarchical virtual ligand screening (HierVLS). The screening database contained 14,862 compounds tagged with the ATTO680 fluorophore plus an additional 5998 intrinsically fluorescent compounds. Overall ranking of compounds to identify hit molecular probe candidates utilized a principal component analysis (PCA) approach. Four potential binding sites, including the catalytic site, were identified within the structure of the protein and targeted for virtual screening. Available sequence information for 23 carbonic anhydrase isoforms was used to prioritize the four sites based on the estimated "uniqueness" of each site in CAIX relative to the other isoforms. A database of 32 known inhibitors and 478 decoy compounds was used to validate the methodology. A receiver-operating characteristic (ROC) analysis using the first principal component (PC1) as predictive score for the validation database yielded an area under the curve (AUC) of 0.92. AUC is interpreted as the probability that a binder will have a better score than a non-binder. The use of first component analysis of binding energies for multiple sites is a novel approach for hit selection. The very high prediction power for this approach increases confidence in the outcome from the fluorescent library screening. Ten of the top scoring candidates for isoform-selective putative binding sites are suggested for future testing as fluorescent molecular probe candidates. Copyright © 2014 Elsevier Inc. All rights reserved.

Towards enhanced and interpretable clustering/classification in integrative genomics

PubMed Central

Lu, Yang Young; Lv, Jinchi; Fuhrman, Jed A.

2017-01-01

Abstract High-throughput technologies have led to large collections of different types of biological data that provide unprecedented opportunities to unravel molecular heterogeneity of biological processes. Nevertheless, how to jointly explore data from multiple sources into a holistic, biologically meaningful interpretation remains challenging. In this work, we propose a scalable and tuning-free preprocessing framework, Heterogeneity Rescaling Pursuit (Hetero-RP), which weighs important features more highly than less important ones in accord with implicitly existing auxiliary knowledge. Finally, we demonstrate effectiveness of Hetero-RP in diverse clustering and classification applications. More importantly, Hetero-RP offers an interpretation of feature importance, shedding light on the driving forces of the underlying biology. In metagenomic contig binning, Hetero-RP automatically weighs abundance and composition profiles according to the varying number of samples, resulting in markedly improved performance of contig binning. In RNA-binding protein (RBP) binding site prediction, Hetero-RP not only improves the prediction performance measured by the area under the receiver operating characteristic curves (AUC), but also uncovers the evidence supported by independent studies, including the distribution of the binding sites of IGF2BP and PUM2, the binding competition between hnRNPC and U2AF2, and the intron–exon boundary of U2AF2 [availability: https://github.com/younglululu/Hetero-RP]. PMID:28977511

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

Theoretical study of the rhenium–alkane interaction in transition metal–alkane σ-complexes

PubMed Central

Cobar, Erika A.; Khaliullin, Rustam Z.; Bergman, Robert G.; Head-Gordon, Martin

2007-01-01

Metal–alkane binding energies have been calculated for [CpRe(CO)2](alkane) and [(CO)2M(C5H4)CC(C5H4)M(CO)2](alkane), where M = Re or Mn. Calculated binding energies were found to increase with the number of metal–alkane interaction sites. In all cases examined, the manganese–alkane binding energies were predicted to be significantly lower than those for the analogous rhenium–alkane complexes. The metal (Mn or Re)–alkane interaction was predicted to be primarily one of charge transfer, both from the alkane to the metal complex (70–80% of total charge transfer) and from the metal complex to the alkane (20–30% of the total charge transfer). PMID:17442751

Systematic characterization of the specificity of the SH2 domains of cytoplasmic tyrosine kinases.

PubMed

Zhao, Bing; Tan, Pauline H; Li, Shawn S C; Pei, Dehua

2013-04-09

Cytoplasmic tyrosine kinases (CTK) generally contain a Src-homology 2 (SH2) domain, whose role in the CTK family is not fully understood. Here we report the determination of the specificity of 25 CTK SH2 domains by screening one-bead-one-compound (OBOC) peptide libraries. Based on the peptide sequences selected by the SH2 domains, we built Support Vector Machine (SVM) models for the prediction of binding ligands for the SH2 domains. These models yielded support for the progressive phosphorylation model for CTKs in which the overlapping specificity of the CTK SH2 and kinase domains has been proposed to facilitate targeting of the CTK substrates with at least two potential phosphotyrosine (pTyr) sites. We curated 93 CTK substrates with at least two pTyr sites catalyzed by the same CTK, and showed that 71% of these substrates had at least two pTyr sites predicted to bind a common CTK SH2 domain. More importantly, we found 34 instances where there was at least one pTyr site predicted to be recognized by the SH2 domain of the same CTK, suggesting that the SH2 and kinase domains of the CTKs may cooperate to achieve progressive phosphorylation of a protein substrate. This article is part of a Special Issue entitled: From protein structures to clinical applications. Copyright © 2012 Elsevier B.V. All rights reserved.

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

Druggability of methyl-lysine binding sites

NASA Astrophysics Data System (ADS)

Santiago, C.; Nguyen, K.; Schapira, M.

2011-12-01

Structural modules that specifically recognize—or read—methylated or acetylated lysine residues on histone peptides are important components of chromatin-mediated signaling and epigenetic regulation of gene expression. Deregulation of epigenetic mechanisms is associated with disease conditions, and antagonists of acetyl-lysine binding bromodomains are efficacious in animal models of cancer and inflammation, but little is known regarding the druggability of methyl-lysine binding modules. We conducted a systematic structural analysis of readers of methyl marks and derived a predictive druggability landscape of methyl-lysine binding modules. We show that these target classes are generally less druggable than bromodomains, but that some proteins stand as notable exceptions.

Application of a continuous distribution model for proton binding by humic acids extracted from acidic lake sediments

NASA Astrophysics Data System (ADS)

Rhea, James R.; Young, Thomas C.

1987-10-01

The proton binding characteristics of humic acids extracted from the sediments of Cranberry Pond, an acidic water body located in the Adirondack Mountain region of New York State, were explored by the application of a multiligand distribution model. The model characterizes a class of proton binding sites by mean log K values and the standard deviations of log K values about the mean. Mean log K values and their relative abundances were determined directly from experimental titration data. The model accurately predicts the binding of protons by the humic acids for pH values in the range 3.5 to 10.0.

Application of a continuous distribution model for proton binding by humic acids extracted from acidic lake sediments

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

Rhea, J.R.; Young, T.C.

1987-01-01

The proton binding characteristics of humic acids extracted from the sediments of Cranberry Pond, an acidic water body located in the Adirondack Mountain region of New York State, were explored by the application of a nultiligand distribution model. The model characterizes a class of proton binding sites by mean log K values and the standard deviations of log K values and the mean. Mean log K values and their relative abundances were determined directly from experimental titration data. The model accurately predicts the binding of protons by the humic acids for pH values in the range 3.5 to 10.0.

DeepMirTar: a deep-learning approach for predicting human miRNA targets.

PubMed

Wen, Ming; Cong, Peisheng; Zhang, Zhimin; Lu, Hongmei; Li, Tonghua

2018-06-01

MicroRNAs (miRNAs) are small noncoding RNAs that function in RNA silencing and post-transcriptional regulation of gene expression by targeting messenger RNAs (mRNAs). Because the underlying mechanisms associated with miRNA binding to mRNA are not fully understood, a major challenge of miRNA studies involves the identification of miRNA-target sites on mRNA. In silico prediction of miRNA-target sites can expedite costly and time-consuming experimental work by providing the most promising miRNA-target-site candidates. In this study, we reported the design and implementation of DeepMirTar, a deep-learning-based approach for accurately predicting human miRNA targets at the site level. The predicted miRNA-target sites are those having canonical or non-canonical seed, and features, including high-level expert-designed, low-level expert-designed, and raw-data-level, were used to represent the miRNA-target site. Comparison with other state-of-the-art machine-learning methods and existing miRNA-target-prediction tools indicated that DeepMirTar improved overall predictive performance. DeepMirTar is freely available at https://github.com/Bjoux2/DeepMirTar_SdA. lith@tongji.edu.cn, hongmeilu@csu.edu.cn. Supplementary data are available at Bioinformatics online.

Identification of Specific DNA Binding Residues in the TCP Family of Transcription Factors in Arabidopsis[W

PubMed Central

Aggarwal, Pooja; Das Gupta, Mainak; Joseph, Agnel Praveen; Chatterjee, Nirmalya; Srinivasan, N.; Nath, Utpal

2010-01-01

The TCP transcription factors control multiple developmental traits in diverse plant species. Members of this family share an ∼60-residue-long TCP domain that binds to DNA. The TCP domain is predicted to form a basic helix-loop-helix (bHLH) structure but shares little sequence similarity with canonical bHLH domain. This classifies the TCP domain as a novel class of DNA binding domain specific to the plant kingdom. Little is known about how the TCP domain interacts with its target DNA. We report biochemical characterization and DNA binding properties of a TCP member in Arabidopsis thaliana, TCP4. We have shown that the 58-residue domain of TCP4 is essential and sufficient for binding to DNA and possesses DNA binding parameters comparable to canonical bHLH proteins. Using a yeast-based random mutagenesis screen and site-directed mutants, we identified the residues important for DNA binding and dimer formation. Mutants defective in binding and dimerization failed to rescue the phenotype of an Arabidopsis line lacking the endogenous TCP4 activity. By combining structure prediction, functional characterization of the mutants, and molecular modeling, we suggest a possible DNA binding mechanism for this class of transcription factors. PMID:20363772

Structural insights into xenobiotic and inhibitor binding to human aldehyde oxidase.

PubMed

Coelho, Catarina; Foti, Alessandro; Hartmann, Tobias; Santos-Silva, Teresa; Leimkühler, Silke; Romão, Maria João

2015-10-01

Aldehyde oxidase (AOX) is a xanthine oxidase (XO)-related enzyme with emerging importance due to its role in the metabolism of drugs and xenobiotics. We report the first crystal structures of human AOX1, substrate free (2.6-Å resolution) and in complex with the substrate phthalazine and the inhibitor thioridazine (2.7-Å resolution). Analysis of the protein active site combined with steady-state kinetic studies highlight the unique features, including binding and substrate orientation at the active site, that characterize human AOX1 as an important drug-metabolizing enzyme. Structural analysis of the complex with the noncompetitive inhibitor thioridazine revealed a new, unexpected and fully occupied inhibitor-binding site that is structurally conserved among mammalian AOXs and XO. The new structural insights into the catalytic and inhibition mechanisms of human AOX that we now report will be of great value for the rational analysis of clinical drug interactions involving inhibition of AOX1 and for the prediction and design of AOX-stable putative drugs.

Structure and Self-Assembly of the Calcium Binding Matrix Protein of Human Metapneumovirus

PubMed Central

Leyrat, Cedric; Renner, Max; Harlos, Karl; Huiskonen, Juha T.; Grimes, Jonathan M.

2014-01-01

Summary The matrix protein (M) of paramyxoviruses plays a key role in determining virion morphology by directing viral assembly and budding. Here, we report the crystal structure of the human metapneumovirus M at 2.8 Å resolution in its native dimeric state. The structure reveals the presence of a high-affinity Ca2+ binding site. Molecular dynamics simulations (MDS) predict a secondary lower-affinity site that correlates well with data from fluorescence-based thermal shift assays. By combining small-angle X-ray scattering with MDS and ensemble analysis, we captured the structure and dynamics of M in solution. Our analysis reveals a large positively charged patch on the protein surface that is involved in membrane interaction. Structural analysis of DOPC-induced polymerization of M into helical filaments using electron microscopy leads to a model of M self-assembly. The conservation of the Ca2+ binding sites suggests a role for calcium in the replication and morphogenesis of pneumoviruses. PMID:24316400

Bioinformatics Identification of Modules of Transcription Factor Binding Sites in Alzheimer's Disease-Related Genes by In Silico Promoter Analysis and Microarrays

PubMed Central

Augustin, Regina; Lichtenthaler, Stefan F.; Greeff, Michael; Hansen, Jens; Wurst, Wolfgang; Trümbach, Dietrich

2011-01-01

The molecular mechanisms and genetic risk factors underlying Alzheimer's disease (AD) pathogenesis are only partly understood. To identify new factors, which may contribute to AD, different approaches are taken including proteomics, genetics, and functional genomics. Here, we used a bioinformatics approach and found that distinct AD-related genes share modules of transcription factor binding sites, suggesting a transcriptional coregulation. To detect additional coregulated genes, which may potentially contribute to AD, we established a new bioinformatics workflow with known multivariate methods like support vector machines, biclustering, and predicted transcription factor binding site modules by using in silico analysis and over 400 expression arrays from human and mouse. Two significant modules are composed of three transcription factor families: CTCF, SP1F, and EGRF/ZBPF, which are conserved between human and mouse APP promoter sequences. The specific combination of in silico promoter and multivariate analysis can identify regulation mechanisms of genes involved in multifactorial diseases. PMID:21559189

Positive and Negative Allosteric Modulation of an α1β3γ2 γ-Aminobutyric Acid Type A (GABAA) Receptor by Binding to a Site in the Transmembrane Domain at the γ+-β− Interface*

PubMed Central

Jayakar, Selwyn S.; Zhou, Xiaojuan; Savechenkov, Pavel Y.; Chiara, David C.; Desai, Rooma; Bruzik, Karol S.; Miller, Keith W.; Cohen, Jonathan B.

2015-01-01

In the process of developing safer general anesthetics, isomers of anesthetic ethers and barbiturates have been discovered that act as convulsants and inhibitors of γ-aminobutyric acid type A receptors (GABAARs) rather than potentiators. It is unknown whether these convulsants act as negative allosteric modulators by binding to the intersubunit anesthetic-binding sites in the GABAAR transmembrane domain (Chiara, D. C., Jayakar, S. S., Zhou, X., Zhang, X., Savechenkov, P. Y., Bruzik, K. S., Miller, K. W., and Cohen, J. B. (2013) J. Biol. Chem. 288, 19343–19357) or to known convulsant sites in the ion channel or extracellular domains. Here, we show that S-1-methyl-5-propyl-5-(m-trifluoromethyl-diazirynylphenyl) barbituric acid (S-mTFD-MPPB), a photoreactive analog of the convulsant barbiturate S-MPPB, inhibits α1β3γ2 but potentiates α1β3 GABAAR responses. In the α1β3γ2 GABAAR, S-mTFD-MPPB binds in the transmembrane domain with high affinity to the γ+-β− subunit interface site with negative energetic coupling to GABA binding in the extracellular domain at the β+-α− subunit interfaces. GABA inhibits S-[3H]mTFD-MPPB photolabeling of γ2Ser-280 (γM2–15′) in this site. In contrast, within the same site GABA enhances photolabeling of β3Met-227 in βM1 by an anesthetic barbiturate, R-[3H]methyl-5-allyl-5-(m-trifluoromethyl-diazirynylphenyl)barbituric acid (mTFD-MPAB), which differs from S-mTFD-MPPB in structure only by chirality and two hydrogens (propyl versus allyl). S-mTFD-MPPB and R-mTFD-MPAB are predicted to bind in different orientations at the γ+-β− site, based upon the distance in GABAAR homology models between γ2Ser-280 and β3Met-227. These results provide an explanation for S-mTFD-MPPB inhibition of α1β3γ2 GABAAR function and provide a first demonstration that an intersubunit-binding site in the GABAAR transmembrane domain binds negative and positive allosteric modulators. PMID:26229099

Docking and 3-D QSAR studies on indolyl aryl sulfones. Binding mode exploration at the HIV-1 reverse transcriptase non-nucleoside binding site and design of highly active N-(2-hydroxyethyl)carboxamide and N-(2-hydroxyethyl)carbohydrazide derivatives.

PubMed

Ragno, Rino; Artico, Marino; De Martino, Gabriella; La Regina, Giuseppe; Coluccia, Antonio; Di Pasquali, Alessandra; Silvestri, Romano

2005-01-13

Three-dimensional quantitative structure-activity relationship (3-D QSAR) studies and docking simulations were developed on indolyl aryl sulfones (IASs), a class of novel HIV-1 non-nucleoside reverse transcriptase (RT) inhibitors (Silvestri, et al. J. Med. Chem. 2003, 46, 2482-2493) highly active against wild type and some clinically relevant resistant strains (Y181C, the double mutant K103N-Y181C, and the K103R-V179D-P225H strain, highly resistant to efavirenz). Predictive 3-D QSAR models using the combination of GRID and GOLPE programs were obtained using a receptor-based alignment by means of docking IASs into the non-nucleoside binding site (NNBS) of RT. The derived 3-D QSAR models showed conventional correlation (r(2)) and cross-validated (q(2)) coefficients values ranging from 0.79 to 0.93 and from 0.59 to 0.84, respectively. All described models were validated by an external test set compiled from previously reported pyrryl aryl sulfones (Artico, et al. J. Med. Chem. 1996, 39, 522-530). The most predictive 3-D QSAR model was then used to predict the activity of novel untested IASs. The synthesis of six designed derivatives (prediction set) allowed disclosure of new IASs endowed with high anti-HIV-1 activities.

Modulation of gene expression via overlapping binding sites exerted by ZNF143, Notch1 and THAP11

PubMed Central

Ngondo-Mbongo, Richard Patryk; Myslinski, Evelyne; Aster, Jon C.; Carbon, Philippe

2013-01-01

ZNF143 is a zinc-finger protein involved in the transcriptional regulation of both coding and non-coding genes from polymerase II and III promoters. Our study deciphers the genome-wide regulatory role of ZNF143 in relation with the two previously unrelated transcription factors Notch1/ICN1 and thanatos-associated protein 11 (THAP11) in several human and murine cells. We show that two distinct motifs, SBS1 and SBS2, are associated to ZNF143-binding events in promoters of >3000 genes. Without co-occupation, these sites are also bound by Notch1/ICN1 in T-lymphoblastic leukaemia cells as well as by THAP11, a factor involved in self-renewal of embryonic stem cells. We present evidence that ICN1 binding overlaps with ZNF143 binding events at the SBS1 and SBS2 motifs, whereas the overlap occurs only at SBS2 for THAP11. We demonstrate that the three factors modulate expression of common target genes through the mutually exclusive occupation of overlapping binding sites. The model we propose predicts that the binding competition between the three factors controls biological processes such as rapid cell growth of both neoplastic and stem cells. Overall, our study establishes a novel relationship between ZNF143, THAP11 and ICN1 and reveals important insights into ZNF143-mediated gene regulation. PMID:23408857

Steric and Thermodynamic Limits of Design for the Incorporation of Large UnNatural Amino Acids in Aminoacyl-tRNA Synthetase Enzymes

PubMed Central

Armen, Roger S.; Schiller, Stefan M.; Brooks, Charles L.

2015-01-01

Orthogonal aminoacyl-tRNA synthetase/tRNA pairs from archaea have been evolved to facilitate site specific in vivo incorporation of unnatural amino acids into proteins in Escherichia coli. Using this approach, unnatural amino acids have been successfully incorporated with high translational efficiency and fidelity. In this study, CHARMM-based molecular docking and free energy calculations were used to evaluate rational design of specific protein-ligand interactions for aminoacyl-tRNA synthetases. A series of novel unnatural amino acid ligands were docked into the p-benzoyl-L-phenylalanine tRNA synthetase, which revealed that the binding pocket of the enzyme does not provide sufficient space for significantly larger ligands. Specific binding site residues were mutated to alanine to create additional space to accommodate larger target ligands, and then mutations were introduced to improve binding free energy. This approach was used to redesign binding sites for several different target ligands, which were then tested against the standard 20 amino acids to verify target specificity. Only the synthetase designed to bind Man-α-O-Tyr was predicted to be sufficiently selective for the target ligand and also thermodynamically stable. Our study suggests that extensive redesign of the tRNA synthatase binding pocket for large bulky ligands may be quite thermodynamically unfavorable. PMID:20310065

Redox process is crucial for inhibitory properties of aurintricarboxylic acid against activity of YopH: virulence factor of Yersinia pestis

PubMed Central

Kuban-Jankowska, Alicja; Gorska, Magdalena; Tuszynski, Jack A; Ossowski, Tadeusz; Wozniak, Michal

2015-01-01

YopH is a bacterial protein tyrosine phosphatase, which is essential for the viability and pathogenic virulence of the plague-causing Yersinia sp. bacteria. Inactivation of YopH activity would lead to the loss of bacterial pathogenicity. We have studied the inhibitory properties of aurintricarboxylic acid (ATA) against YopH phosphatase and found that at nanomolar concentrations ATA reversibly decreases the activity of YopH. Computational docking studies indicated that in all binding poses ATA binds in the YopH active site. Molecular dynamics simulations showed that in the predicted binding pose, ATA binds to the essential Cys403 and Arg409 residues in the active site and has a stronger binding affinity than the natural substrate (pTyr). The cyclic voltammetry experiments suggest that ATA reacts remarkably strongly with molecular oxygen. Additionally, the electrochemical reduction of ATA in the presence of a negative potential from −2.0 to 2.5 V generates a current signal, which is observed for hydrogen peroxide. Here we showed that ATA indicates a unique mechanism of YopH inactivation due to a redox process. We proposed that the potent inhibitory properties of ATA are a result of its strong binding in the YopH active site and in situ generation of hydrogen peroxide near catalytic cysteine residue. PMID:26286963

Insights into RNA binding by the anticancer drug cisplatin from the crystal structure of cisplatin-modified ribosome

PubMed Central

Melnikov, Sergey V.; Söll, Dieter; Steitz, Thomas A.

2016-01-01

Abstract Cisplatin is a widely prescribed anticancer drug, which triggers cell death by covalent binding to a broad range of biological molecules. Among cisplatin targets, cellular RNAs remain the most poorly characterized molecules. Although cisplatin was shown to inactivate essential RNAs, including ribosomal, spliceosomal and telomeric RNAs, cisplatin binding sites in most RNA molecules are unknown, and therefore it remains challenging to study how modifications of RNA by cisplatin contributes to its toxicity. Here we report a 2.6Å-resolution X-ray structure of cisplatin-modified 70S ribosome, which describes cisplatin binding to the ribosome and provides the first nearly atomic model of cisplatin–RNA complex. We observe nine cisplatin molecules bound to the ribosome and reveal consensus structural features of the cisplatin-binding sites. Two of the cisplatin molecules modify conserved functional centers of the ribosome—the mRNA-channel and the GTPase center. In the mRNA-channel, cisplatin intercalates between the ribosome and the messenger RNA, suggesting that the observed inhibition of protein synthesis by cisplatin is caused by impaired mRNA-translocation. Our structure provides an insight into RNA targeting and inhibition by cisplatin, which can help predict cisplatin-binding sites in other cellular RNAs and design studies to elucidate a link between RNA modifications by cisplatin and cisplatin toxicity. PMID:27079977

Ankyrin-binding proteins related to nervous system cell adhesion molecules: candidates to provide transmembrane and intercellular connections in adult brain.

PubMed

Davis, J Q; McLaughlin, T; Bennett, V

1993-04-01

A major class of ankyrin-binding glycoproteins have been identified in adult rat brain of 186, 155, and 140 kD that are alternatively spliced products of the same pre-mRNA. Characterization of cDNAs demonstrated that ankyrin-binding glycoproteins (ABGPs) share 72% amino acid sequence identity with chicken neurofascin, a membrane-spanning neural cell adhesion molecule in the Ig super-family expressed in embryonic brain. ABGP polypeptides have the following features consistent with a role as ankyrin-binding proteins in vitro and in vivo: (a) ABGPs and ankyrin associate as pure proteins in a 1:1 molar stoichiometry; (b) the ankyrin-binding site is located in the COOH-terminal 21 kD of ABGP186 which contains the predicted cytoplasmic domain; (c) ABGP186 is expressed at approximately the same levels as ankyrin (15 pmoles/milligram of membrane protein); and (d) ABGP polypeptides are co-expressed with the adult form of ankyrinB late in postnatal development and are colocalized with ankyrinB by immunofluorescence. Similarity in amino acid sequence and conservation of sites of alternative splicing indicate that genes encoding ABGPs and neurofascin share a common ancestor. However, the major differences in developmental expression reported for neurofascin in embryos versus the late postnatal expression of ABGPs suggest that ABGPs and neurofascin represent products of gene duplication events that have subsequently evolved in parallel with distinct roles. The predicted cytoplasmic domains of rat ABGPs and chicken neurofascin are nearly identical to each other and closely related to a group of nervous system cell adhesion molecules with variable extracellular domains, which includes L1, Nr-CAM, and Ng-CAM of vertebrates, and neuroglian of Drosophila. The ankyrin-binding site of rat ABGPs is localized to the C-terminal 200 residues which encompass the cytoplasmic domain, suggesting the hypothesis that ability to associate with ankyrin may be a shared feature of neurofascin and related nervous system cell adhesion molecules.

In silico analysis of miRNA-mediated gene regulation in OCA and OA genes.

PubMed

Kamaraj, Balu; Gopalakrishnan, Chandrasekhar; Purohit, Rituraj

2014-12-01

Albinism is an autosomal recessive genetic disorder due to low secretion of melanin. The oculocutaneous albinism (OCA) and ocular albinism (OA) genes are responsible for melanin production and also act as a potential targets for miRNAs. The role of miRNA is to inhibit the protein synthesis partially or completely by binding with the 3'UTR of the mRNA thus regulating gene expression. In this analysis, we predicted the genetic variation that occurred in 3'UTR of the transcript which can be a reason for low melanin production thus causing albinism. The single nucleotide polymorphisms (SNPs) in 3'UTR cause more new binding sites for miRNA which binds with mRNA which leads to inhibit the translation process either partially or completely. The SNPs in the mRNA of OCA and OA genes can create new binding sites for miRNA which may control the gene expression and lead to hypopigmentation. We have developed a computational procedure to determine the SNPs in the 3'UTR region of mRNA of OCA (TYR, OCA2, TYRP1 and SLC45A2) and OA (GPR143) genes which will be a potential cause for albinism. We identified 37 SNPs in five genes that are predicted to create 87 new binding sites on mRNA, which may lead to abrogation of the translation process. Expression analysis confirms that these genes are highly expressed in skin and eye regions. It is well supported by enrichment analysis that these genes are mainly involved in eye pigmentation and melanin biosynthesis process. The network analysis also shows how the genes are interacting and expressing in a complex network. This insight provides clue to wet-lab researches to understand the expression pattern of OCA and OA genes and binding phenomenon of mRNA and miRNA upon mutation, which is responsible for inhibition of translation process at genomic levels.

Inter-species chimeras of leukaemia inhibitory factor define a major human receptor-binding determinant.

PubMed Central

Owczarek, C M; Layton, M J; Metcalf, D; Lock, P; Willson, T A; Gough, N M; Nicola, N A

1993-01-01

Human leukaemia inhibitory factor (hLIF) binds to both human and mouse LIF receptors (LIF-R), while mouse LIF (mLIF) binds only to mouse LIF-R. Moreover, hLIF binds with higher affinity to the mLIF-R than does mLIF. In order to define the regions of the hLIF molecule responsible for species-specific interaction with the hLIF-R and for the unusual high-affinity binding to the mLIF-R, a series of 15 mouse/human LIF hybrids has been generated. Perhaps surprisingly, both of these properties mapped to the same region of the hLIF molecule. The predominant contribution was from residues in the loop linking the third and fourth helices, with lesser contributions from residues in the third helix and the loop connecting the second and third helices in the predicted three-dimensional structure. Since all chimeras retained full biological activity and receptor-binding activity on mouse cells, and there was little variation in the specific biological activity of the purified proteins, it can be concluded that the overall secondary and tertiary structures of each chimera were intact. This observation also implied that the primary binding sites on mLIF and hLIF for the mLIF-R were unaltered by inter-species domain swapping. Consequently, the site on the hLIF molecule that confers species-specific binding to the hLIF-R and higher affinity binding to the mLIF-R, must constitute an additional interaction site to that used by both mLIF and hLIF to bind to the mLIF-R. These studies define a maximum of 15 amino acid differences between hLIF and mLIF that are responsible for the different properties of these proteins. Images PMID:8253075

Studies of the mechanism of selectivity of protein tyrosine phosphatase 1B (PTP1B) bidentate inhibitors using molecular dynamics simulations and free energy calculations.

PubMed

Fang, Lei; Zhang, Huai; Cui, Wei; Ji, Mingjun

2008-10-01

Bidentate inhibitors of protein tyrosine phosphatase 1B (PTP1B) are considered as a group of ideal inhibitors with high binding potential and high selectivity in treating type II diabetes. In this paper, the binding models of five bidentate inhibitors to PTP1B, TCPTP, and SHP-2 were investigated and compared by using molecular dynamics (MD) simulations and free energy calculations. The binding free energies were computed using the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) methodology. The calculation results show that the predicted free energies of the complexes are well consistent with the experimental data. The Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) free energy decomposition analysis indicates that the residues ARG24, ARG254, and GLN262 in the second binding site of PTP1B are essential for the high selectivity of inhibitors. Furthermore, the residue PHE182 close to the active site is also important for the selectivity and the binding affinity of the inhibitors. According to our analysis, it can be concluded that in most cases the polarity of the portion of the inhibitor that binds to the second binding site of the protein is positive to the affinity of the inhibitors while negative to the selectivity of the inhibitors. We expect that the information we obtained here can help to develop potential PTP1B inhibitors with more promising specificity.

Computational simulation of formin-mediated actin polymerization predicts homologue-dependent mechanosensitivity.

PubMed

Bryant, Derek; Clemens, Lara; Allard, Jun

2017-01-01

Many actin structures are nucleated and assembled by the barbed-end tracking polymerase formin family, including filopodia, focal adhesions, the cytokinetic ring and cell cortex. These structures respond to forces in distinct ways. Formins typically have profilin-actin binding sites embedded in highly flexible disordered FH1 domains, hypothesized to diffusively explore space to rapidly capture actin monomers for delivery to the barbed end. Recent experiments demonstrate that formin-mediated polymerization accelerates when under tension. The acceleration has been attributed to modifying the state of the FH2 domain of formin. Intriguingly, the same acceleration is reported when tension is applied to the FH1 domains, ostensibly pulling monomers away from the barbed end. Here we develop a mesoscale coarse-grain model of formin-mediated actin polymerization, including monomer capture and delivery by FH1, which sterically interacts with actin along its entire length. The binding of actin monomers to their specific sites on FH1 is entropically disfavored by the high disorder. We find that this penalty is attenuated when force is applied to the FH1 domain by revealing the binding site, increasing monomer capture efficiency. Overall polymerization rates can decrease or increase with increasing force, depending on the length of FH1 domain and location of binding site. Our results suggest that the widely varying FH1 lengths and binding site locations found in known formins could be used to differentially respond to force, depending on the actin structure being assembled. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Design and synthesis of inositolphosphoglycan putative insulin mediators.

PubMed

López-Prados, Javier; Cuevas, Félix; Reichardt, Niels-Christian; de Paz, José-Luis; Morales, Ezequiel Q; Martín-Lomas, Manuel

2005-03-07

The binding modes of a series of molecules, containing the glucosamine (1-->6) myo-inositol structural motif, into the ATP binding site of the catalytic subunit of cAMP-dependent protein kinase (PKA) have been analysed using molecular docking. These calculations predict that the presence of a phosphate group at the non-reducing end in pseudodisaccharide and pseudotrisaccharide structures properly orientate the molecule into the binding site and that pseudotrisaccharide structures present the best shape complementarity. Therefore, pseudodisaccharides and pseudotrisaccharides have been synthesised from common intermediates using effective synthetic strategies. On the basis of this synthetic chemistry, the feasibility of constructing small pseudotrisaccharide libraries on solid-phase using the same intermediates has been explored. The results from the biological evaluation of these molecules provide additional support to an insulin-mediated signalling system which involves the intermediacy of inositolphosphoglycans as putative insulin mediators.

2-(Hetero(aryl)methylene)hydrazine-1-carbothioamides as potent urease inhibitors.

PubMed

Saeed, Aamer; Imran, Aqeel; Channar, Pervaiz A; Shahid, Mohammad; Mahmood, Wajahat; Iqbal, Jamshed

2015-02-01

A small series of 2-(hetero(aryl)methylene) hydrazine-1-carbothioamides including two aryl derivatives was synthesized and tested for their inhibitory activity against urease. Compound (E)-2-(Furan-2-ylmethylene) hydrazine-1-carbothioamide (3f), having a furan ring, was the most potent inhibitor of urease with an IC50 value of 0.58 μM. Molecular modeling was carried out through docking the designed compounds into the urease binding site to predict whether these derivatives have analogous binding mode to the urease inhibitors. The study revealed that all of the tested compounds bind with both metal atoms at the active site of the enzyme. The aromatic ring of the compounds forms ionic interactions with the residues, Ala(440), Asp(494), Ala(636), and Met(637). © 2014 John Wiley & Sons A/S.

Crystal Structure of the Heterotrimeric Integrin-Binding Region of Laminin-111.

PubMed

Pulido, David; Hussain, Sadaf-Ahmahni; Hohenester, Erhard

2017-03-07

Laminins are cell-adhesive glycoproteins that are essential for basement membrane assembly and function. Integrins are important laminin receptors, but their binding site on the heterotrimeric laminins is poorly defined structurally. We report the crystal structure at 2.13 Å resolution of a minimal integrin-binding fragment of mouse laminin-111, consisting of ∼50 residues of α1β1γ1 coiled coil and the first three laminin G-like (LG) domains of the α1 chain. The LG domains adopt a triangular arrangement, with the C terminus of the coiled coil situated between LG1 and LG2. The critical integrin-binding glutamic acid residue in the γ1 chain tail is surface exposed and predicted to bind to the metal ion-dependent adhesion site in the integrin β1 subunit. Additional contacts to the integrin are likely to be made by the LG1 and LG2 surfaces adjacent to the γ1 chain tail, which are notably conserved and free of obstructing glycans. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Prediction of allosteric sites and mediating interactions through bond-to-bond propensities

NASA Astrophysics Data System (ADS)

Amor, B. R. C.; Schaub, M. T.; Yaliraki, S. N.; Barahona, M.

2016-08-01

Allostery is a fundamental mechanism of biological regulation, in which binding of a molecule at a distant location affects the active site of a protein. Allosteric sites provide targets to fine-tune protein activity, yet we lack computational methodologies to predict them. Here we present an efficient graph-theoretical framework to reveal allosteric interactions (atoms and communication pathways strongly coupled to the active site) without a priori information of their location. Using an atomistic graph with energy-weighted covalent and weak bonds, we define a bond-to-bond propensity quantifying the non-local effect of instantaneous bond fluctuations propagating through the protein. Significant interactions are then identified using quantile regression. We exemplify our method with three biologically important proteins: caspase-1, CheY, and h-Ras, correctly predicting key allosteric interactions, whose significance is additionally confirmed against a reference set of 100 proteins. The almost-linear scaling of our method renders it suitable for high-throughput searches for candidate allosteric sites.

Prediction of allosteric sites and mediating interactions through bond-to-bond propensities

PubMed Central

Amor, B. R. C.; Schaub, M. T.; Yaliraki, S. N.; Barahona, M.

2016-01-01

Allostery is a fundamental mechanism of biological regulation, in which binding of a molecule at a distant location affects the active site of a protein. Allosteric sites provide targets to fine-tune protein activity, yet we lack computational methodologies to predict them. Here we present an efficient graph-theoretical framework to reveal allosteric interactions (atoms and communication pathways strongly coupled to the active site) without a priori information of their location. Using an atomistic graph with energy-weighted covalent and weak bonds, we define a bond-to-bond propensity quantifying the non-local effect of instantaneous bond fluctuations propagating through the protein. Significant interactions are then identified using quantile regression. We exemplify our method with three biologically important proteins: caspase-1, CheY, and h-Ras, correctly predicting key allosteric interactions, whose significance is additionally confirmed against a reference set of 100 proteins. The almost-linear scaling of our method renders it suitable for high-throughput searches for candidate allosteric sites. PMID:27561351

Binding Site and Potency Prediction of Teixobactin and other Lipid II Ligands by Statistical Base Scoring of Conformational Space Maps.

PubMed

Lungu, Claudiu N; Diudea, Mircea V

2018-01-01

Lipid II, a peptidoglycan, is a precursor in bacterial cell synthesis. It has both hydrophilic and lipophilic properties. The molecule translocates a bacterial membrane to deliver and incorporate "building blocks" from disaccharide-pentapeptide into the peptidoglican wall. Lipid II is a valid antibiotic target. A receptor binding pocket may be occupied by a ligand in various plausible conformations, among which only few ones are energetically related to a biological activity in the physiological efficiency domain. This paper reports the mapping of the conformational space of Lipid II in its interaction with Teixobactin and other Lipid II ligands. In order to study computationally the complex between Lipid II and ligands, a docking study was first carried on. Docking site was retrieved form literature. After docking, 5 ligand conformations and further 5 complexes (denoted 00 to 04) for each molecule were taken into account. For each structure, conformational studies were performed. Statistical analysis, conformational analysis and molecular dynamics based clustering were used to predict the potency of these compounds. A score for potency prediction was developed. Appling lipid II classification according to Lipid II conformational energy, a conformation of Teixobactin proved to be energetically favorable, followed by Oritravicin, Dalbavycin, Telvanicin, Teicoplamin and Vancomycin, respectively. Scoring of molecules according to cluster band and PCA produced the same result. Molecules classified according to standard deviations showed Dalbavycin as the most favorable conformation, followed by Teicoplamin, Telvanicin, Teixobactin, Oritravicin and Vancomycin, respectively. Total score showing best energetic efficiency of complex formation shows Teixobactin to have the best conformation (a score of 15 points) followed by Dalbavycin (14 points), Oritravicin (12v points), Telvanicin (10 points), Teicoplamin (9 points), Vancomycin (3 points). Statistical analysis of conformations can be used to predict the efficiency of ligand - target interaction and consecutively to find insight regarding ligand potency and postulate about favorable conformation of ligand and binding site. In this study it was shown that Teixobactin is more efficient in binding with Lipid II compared to Vancomycin, results confirmed by experimental data reported in literature. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Zinc-induced modulation of SRSF6 activity alters Bim splicing to promote generation of the most potent apoptotic isoform BimS.

PubMed

Hara, Hirokazu; Takeda, Tatsuya; Yamamoto, Nozomi; Furuya, Keisuke; Hirose, Kazuya; Kamiya, Tetsuro; Adachi, Tetsuo

2013-07-01

Bim is a member of the pro-apoptotic BH3-only Bcl-2 family of proteins. Bim gene undergoes alternative splicing to produce three predominant splicing variants (BimEL, BimL and BimS). The smallest variant BimS is the most potent inducer of apoptosis. Zinc (Zn(2+)) has been reported to stimulate apoptosis in various cell types. In this study, we examined whether Zn(2+) affects the expression of Bim in human neuroblastoma SH-SY5Y cells. Zn(2+) triggered alterations in Bim splicing and induced preferential generation of BimS, but not BimEL and BimL, in a dose- and time-dependent manner. Other metals (cadmium, cobalt and copper) and stresses (oxidative, endoplasmic reticulum and genotoxic stresses) had little or no effect on the expression of BimS. To address the mechanism of Zn(2+)-induced preferential generation of BimS, which lacks exon 4, we developed a Bim mini-gene construct. Deletion analysis using the Bim mini-gene revealed that predicted binding sites of the SR protein SRSF6, also known as SRp55, are located in the intronic region adjacent to exon 4. We also found that mutations in the predicted SRSF6-binding sites abolished generation of BimS mRNA from the mutated Bim mini-gene. In addition, a UV cross-linking assay followed by Western blotting showed that SRSF6 directly bound to the predicted binding site and Zn(2+) suppressed this binding. Moreover, Zn(2+) stimulated SRSF6 hyper-phosphorylation. TG003, a cdc2-like kinase inhibitor, partially prevented Zn(2+)-induced generation of BimS and SRSF6 hyper-phosphorylation. Taken together, our findings suggest that Zn(2+) inhibits the activity of SRSF6 and promotes elimination of exon 4, leading to preferential generation of BimS. © 2013 FEBS.

Exploring molecular insights into the interaction mechanism of cholesterol derivatives with the Mce4A: A combined spectroscopic and molecular dynamic simulation studies.

PubMed

Khan, Shagufta; Khan, Faez Iqbal; Mohammad, Taj; Khan, Parvez; Hasan, Gulam Mustafa; Lobb, Kevin A; Islam, Asimul; Ahmad, Faizan; Imtaiyaz Hassan, Md

2018-05-01

Mammalian cell entry protein (Mce4A) is a member of MCE-family, and is being considered as a potential drug target of Mycobacterium tuberculosis infection because it is required for invasion and latent survival of pathogen by utilizing host's cholesterol. In the present study, we performed molecular docking followed by 100 ns MD simulation studies to understand the mechanism of interaction of Mce4A to the cholesterol derivatives and probucol. The selected ligands, cholesterol, 25-hydroxycholesterol, 5-cholesten-3β-ol-7-one and probucol bind to the predicted active site cavity of Mce4A, and complexes remain stable during entire simulation of 100 ns. In silico studies were further validated by fluorescence-binding studies to calculate actual binding affinity and number of binding site(s). The non-toxicity of all ligands was confirmed on human monocytic cell (THP1) by MTT assay. This work provides a deeper insight into the mechanism of interaction of Mce4A to cholesterol derivatives, which may be further exploited to design potential and specific inhibitors to ameliorate the Mycobacterium pathogenesis. Copyright © 2018 Elsevier B.V. All rights reserved.

Determining ERβ Binding Affinity to Singly Mutant ERE Using Dual Polarization Interferometry

NASA Astrophysics Data System (ADS)

Song, Hong Yan; Su, Xiaodi

In a classic mode of estrogen action, estrogen receptors (ERs) bind to estrogen responsive element (ERE) to activate gene transcription. A perfect ERE contains a 13-base pair sequence of a palindromic repeat separated by a three-base spacer, 5‧-GGTCAnnnTGACC-3‧. In addition to the consensus or wild-type ERE (wtERE), naturally occurring EREs often have one or two base pairs’ alternation. Based on the newly constructed Thermodynamic Modeling of ChIP-seq (TherMos) model, binding energy between ERβ and a series of 34-bp mutant EREs (mutERE) was simulated to predict the binding affinity between ERs and EREs with single base pair deviation at different sites of the 13-bp inverted sequence. Experimentally, dual polarization interferometry (DPI) method was developed to measure ERβ-mutEREs binding affinity. On a biotin-NeutrAvidin (NA)-biotin treated DPI chip, wtERE is immobilized. In a direct binding assay, ERβ-wtERE binding affinity is determined. In a competition assay, ERβ was preincubated with mutant EREs before being added for competitive binding to the immobilized wtERE. This competition strategy provided a successful platform to evaluate the binding affinity variation among large number of ERE with different base mutations. The experimental result correlates well with the mathematically predicted binding energy with a Spearman correlation coefficient of 0.97.

Relative binding affinity prediction of farnesoid X receptor in the D3R Grand Challenge 2 using FEP.

PubMed

Schindler, Christina; Rippmann, Friedrich; Kuhn, Daniel

2018-01-01

Physics-based free energy simulations have increasingly become an important tool for predicting binding affinity and the recent introduction of automated protocols has also paved the way towards a more widespread use in the pharmaceutical industry. The D3R 2016 Grand Challenge 2 provided an opportunity to blindly test the commercial free energy calculation protocol FEP+ and assess its performance relative to other affinity prediction methods. The present D3R free energy prediction challenge was built around two experimental data sets involving inhibitors of farnesoid X receptor (FXR) which is a promising anticancer drug target. The FXR binding site is predominantly hydrophobic with few conserved interaction motifs and strong induced fit effects making it a challenging target for molecular modeling and drug design. For both data sets, we achieved reasonable prediction accuracy (RMSD ≈ 1.4 kcal/mol, rank 3-4 according to RMSD out of 20 submissions) comparable to that of state-of-the-art methods in the field. Our D3R results boosted our confidence in the method and strengthen our desire to expand its applications in future in-house drug design projects.

Relative binding affinity prediction of farnesoid X receptor in the D3R Grand Challenge 2 using FEP+

NASA Astrophysics Data System (ADS)

Schindler, Christina; Rippmann, Friedrich; Kuhn, Daniel

2018-01-01

Physics-based free energy simulations have increasingly become an important tool for predicting binding affinity and the recent introduction of automated protocols has also paved the way towards a more widespread use in the pharmaceutical industry. The D3R 2016 Grand Challenge 2 provided an opportunity to blindly test the commercial free energy calculation protocol FEP+ and assess its performance relative to other affinity prediction methods. The present D3R free energy prediction challenge was built around two experimental data sets involving inhibitors of farnesoid X receptor (FXR) which is a promising anticancer drug target. The FXR binding site is predominantly hydrophobic with few conserved interaction motifs and strong induced fit effects making it a challenging target for molecular modeling and drug design. For both data sets, we achieved reasonable prediction accuracy (RMSD ≈ 1.4 kcal/mol, rank 3-4 according to RMSD out of 20 submissions) comparable to that of state-of-the-art methods in the field. Our D3R results boosted our confidence in the method and strengthen our desire to expand its applications in future in-house drug design projects.

Comparative analysis and molecular characterization of genomic sequences and proteins of FABP4 and FABP5 from the giant panda (Ailuropoda melanoleuca).

PubMed

Song, B; Hou, Y L; Ding, X; Wang, T; Wang, F; Zhong, J C; Xu, T; Zhong, J; Hou, W R; Shuai, S R

2014-02-20

Fatty acid binding proteins (FABPs) are a family of small, highly conserved cytoplasmic proteins that bind long-chain fatty acids and other hydrophobic ligands. In this study, cDNA and genomic sequences of FABP4 and FABP5 were cloned successfully from the giant panda (Ailuropoda melanoleuca) using reverse transcription polymerase chain reaction (RT-PCR) technology and touchdown-PCR. The cDNAs of FABP4 and FABP5 cloned from the giant panda were 400 and 413 bp in length, containing an open reading frame of 399 and 408 bp, encoding 132 and 135 amino acids, respectively. The genomic sequences of FABP4 and FABP5 were 3976 and 3962 bp, respectively, which each contained four exons and three introns. Sequence alignment indicated a high degree of homology with reported FABP sequences of other mammals at both the amino acid and DNA levels. Topology prediction revealed seven protein kinase C phosphorylation sites, two casein kinase II phosphorylation sites, two N-myristoylation sites, and one cytosolic fatty acid-binding protein signature in the FABP4 protein, and three N-glycosylation sites, three protein kinase C phosphorylation sites, one casein kinase II phosphorylation site, one N-myristoylation site, one amidation site, and one cytosolic fatty acid-binding protein signature in the FABP5 protein. The FABP4 and FABP5 genes were overexpressed in Escherichia coli BL21 and they produced the expected 16.8- and 17.0-kDa polypeptides. The results obtained in this study provide information for further in-depth research of this system, which has great value of both theoretical and practical significance.

Separating the Role of Protein Restraints and Local Metal-Site Interaction Chemistry in the Thermodynamics of a Zinc Finger Protein

PubMed Central

Dixit, Purushottam D.; Asthagiri, D.

2011-01-01

We express the effective Hamiltonian of an ion-binding site in a protein as a combination of the Hamiltonian of the ion-bound site in vacuum and the restraints of the protein on the site. The protein restraints are described by the quadratic elastic network model. The Hamiltonian of the ion-bound site in vacuum is approximated as a generalized Hessian around the minimum energy configuration. The resultant of the two quadratic Hamiltonians is cast into a pure quadratic form. In the canonical ensemble, the quadratic nature of the resultant Hamiltonian allows us to express analytically the excess free energy, enthalpy, and entropy of ion binding to the protein. The analytical expressions allow us to separate the roles of the dynamic restraints imposed by the protein on the binding site and the temperature-independent chemical effects in metal-ligand coordination. For the consensus zinc-finger peptide, relative to the aqueous phase, the calculated free energy of exchanging Zn2+ with Fe2+, Co2+, Ni2+, and Cd2+ are in agreement with experiments. The predicted excess enthalpy of ion exchange between Zn2+ and Co2+ also agrees with the available experimental estimate. The free energy of applying the protein restraints reveals that relative to Zn2+, the Co2+, and Cd2+-site clusters are more destabilized by the protein restraints. This leads to an experimentally testable hypothesis that a tetrahedral metal binding site with minimal protein restraints will be less selective for Zn2+ over Co2+ and Cd2+ compared to a zinc finger peptide. No appreciable change is expected for Fe2+ and Ni2+. The framework presented here may prove useful in protein engineering to tune metal selectivity. PMID:21943427

Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints

PubMed Central

Suciu, Maria C.; Telenius, Jelena

2017-01-01

In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k-mer-based analysis of DNase footprints to determine any k-mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome. PMID:28904015

Characterization of Escherichia coli Type 1 Pilus Mutants with Altered Binding Specificities

PubMed Central

Harris, Sandra L.; Spears, Patricia A.; Havell, Edward A.; Hamrick, Terri S.; Horton, John R.; Orndorff, Paul E.

2001-01-01

PCR mutagenesis and a unique enrichment scheme were used to obtain two mutants, each with a single lesion in fimH, the chromosomal gene that encodes the adhesin protein (FimH) of Escherichia coli type 1 pili. These mutants were noteworthy in part because both were altered in the normal range of cell types bound by FimH. One mutation altered an amino acid at a site previously shown to be involved in temperature-dependent binding, and the other altered an amino acid lining the predicted FimH binding pocket. PMID:11395476

Design and Synthesis of a Pan-Janus Kinase Inhibitor Clinical Candidate (PF-06263276) Suitable for Inhaled and Topical Delivery for the Treatment of Inflammatory Diseases of the Lungs and Skin

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

Jones, Peter; Storer, R. Ian; Sabnis, Yogesh A.

By use of a structure-based computational method for identification of structurally novel Janus kinase (JAK) inhibitors predicted to bind beyond the ATP binding site, a potent series of indazoles was identified as selective pan-JAK inhibitors with a type 1.5 binding mode. Optimization of the series for potency and increased duration of action commensurate with inhaled or topical delivery resulted in potent pan-JAK inhibitor 2 (PF-06263276), which was advanced into clinical studies.

Elucidation of Lipid Binding Sites on Lung Surfactant Protein A Using X-ray Crystallography, Mutagenesis, and Molecular Dynamics Simulations.

PubMed

Goh, Boon Chong; Wu, Huixing; Rynkiewicz, Michael J; Schulten, Klaus; Seaton, Barbara A; McCormack, Francis X

2016-07-05

Surfactant protein A (SP-A) is a collagenous C-type lectin (collectin) that is critical for pulmonary defense against inhaled microorganisms. Bifunctional avidity of SP-A for pathogen-associated molecular patterns (PAMPs) such as lipid A and for dipalmitoylphosphatidylcholine (DPPC), the major component of surfactant membranes lining the air-liquid interface of the lung, ensures that the protein is poised for first-line interactions with inhaled pathogens. To improve our understanding of the motifs that are required for interactions with microbes and surfactant structures, we explored the role of the tyrosine-rich binding surface on the carbohydrate recognition domain of SP-A in the interaction with DPPC and lipid A using crystallography, site-directed mutagenesis, and molecular dynamics simulations. Critical binding features for DPPC binding include a three-walled tyrosine cage that binds the choline headgroup through cation-π interactions and a positively charged cluster that binds the phosphoryl group. This basic cluster is also critical for binding of lipid A, a bacterial PAMP and target for SP-A. Molecular dynamics simulations further predict that SP-A binds lipid A more tightly than DPPC. These results suggest that the differential binding properties of SP-A favor transfer of the protein from surfactant DPPC to pathogen membranes containing appropriate lipid PAMPs to effect key host defense functions.

A new method for the construction of a mutant library with a predictable occurrence rate using Poisson distribution.

PubMed

Seong, Ki Moon; Park, Hweon; Kim, Seong Jung; Ha, Hyo Nam; Lee, Jae Yung; Kim, Joon

2007-06-01

A yeast transcriptional activator, Gcn4p, induces the expression of genes that are involved in amino acid and purine biosynthetic pathways under amino acid starvation. Gcn4p has an acidic activation domain in the central region and a bZIP domain in the C-terminus that is divided into the DNA-binding motif and dimerization leucine zipper motif. In order to identify amino acids in the DNA-binding motif of Gcn4p which are involved in transcriptional activation, we constructed mutant libraries in the DNA-binding motif through an innovative application of random mutagenesis. Mutant library made by oligonucleotides which were mutated randomly using the Poisson distribution showed that the actual mutation frequency was in good agreement with expected values. This method could save the time and effort to create a mutant library with a predictable mutation frequency. Based on the studies using the mutant libraries constructed by the new method, the specific residues of the DNA-binding domain in Gcn4p appear to be involved in the transcriptional activities on a conserved binding site.

Functional defect of variants in the adenosine triphosphate-binding sites of ABCB4 and their rescue by the cystic fibrosis transmembrane conductance regulator potentiator, ivacaftor (VX-770).

PubMed

Delaunay, Jean-Louis; Bruneau, Alix; Hoffmann, Brice; Durand-Schneider, Anne-Marie; Barbu, Véronique; Jacquemin, Emmanuel; Maurice, Michèle; Housset, Chantal; Callebaut, Isabelle; Aït-Slimane, Tounsia

2017-02-01

ABCB4 (MDR3) is an adenosine triphosphate (ATP)-binding cassette (ABC) transporter expressed at the canalicular membrane of hepatocytes, where it mediates phosphatidylcholine (PC) secretion. Variations in the ABCB4 gene are responsible for several biliary diseases, including progressive familial intrahepatic cholestasis type 3 (PFIC3), a rare disease that can be lethal in the absence of liver transplantation. In this study, we investigated the effect and potential rescue of ABCB4 missense variations that reside in the highly conserved motifs of ABC transporters, involved in ATP binding. Five disease-causing variations in these motifs have been identified in ABCB4 (G535D, G536R, S1076C, S1176L, and G1178S), three of which are homologous to the gating mutations of cystic fibrosis transmembrane conductance regulator (CFTR or ABCC7; i.e., G551D, S1251N, and G1349D), that were previously shown to be function defective and corrected by ivacaftor (VX-770; Kalydeco), a clinically approved CFTR potentiator. Three-dimensional structural modeling predicted that all five ABCB4 variants would disrupt critical interactions in the binding of ATP and thereby impair ATP-induced nucleotide-binding domain dimerization and ABCB4 function. This prediction was confirmed by expression in cell models, which showed that the ABCB4 mutants were normally processed and targeted to the plasma membrane, whereas their PC secretion activity was dramatically decreased. As also hypothesized on the basis of molecular modeling, PC secretion activity of the mutants was rescued by the CFTR potentiator, ivacaftor (VX-770). Disease-causing variations in the ATP-binding sites of ABCB4 cause defects in PC secretion, which can be rescued by ivacaftor. These results provide the first experimental evidence that ivacaftor is a potential therapy for selected patients who harbor mutations in the ATP-binding sites of ABCB4. (Hepatology 2017;65:560-570). © 2016 by the American Association for the Study of Liver Diseases.

Advancing viral RNA structure prediction: measuring the thermodynamics of pyrimidine-rich internal loops

PubMed Central

Phan, Andy; Mailey, Katherine; Saeki, Jessica; Gu, Xiaobo

2017-01-01

Accurate thermodynamic parameters improve RNA structure predictions and thus accelerate understanding of RNA function and the identification of RNA drug binding sites. Many viral RNA structures, such as internal ribosome entry sites, have internal loops and bulges that are potential drug target sites. Current models used to predict internal loops are biased toward small, symmetric purine loops, and thus poorly predict asymmetric, pyrimidine-rich loops with >6 nucleotides (nt) that occur frequently in viral RNA. This article presents new thermodynamic data for 40 pyrimidine loops, many of which can form UU or protonated CC base pairs. Uracil and protonated cytosine base pairs stabilize asymmetric internal loops. Accurate prediction rules are presented that account for all thermodynamic measurements of RNA asymmetric internal loops. New loop initiation terms for loops with >6 nt are presented that do not follow previous assumptions that increasing asymmetry destabilizes loops. Since the last 2004 update, 126 new loops with asymmetry or sizes greater than 2 × 2 have been measured. These new measurements significantly deepen and diversify the thermodynamic database for RNA. These results will help better predict internal loops that are larger, pyrimidine-rich, and occur within viral structures such as internal ribosome entry sites. PMID:28213527

Modeling the Binding of Neurotransmitter Transporter Inhibitors with Molecular Dynamics and Free Energy Calculations

NASA Astrophysics Data System (ADS)

Jean, Bernandie

The monoamine transporter (MAT) proteins responsible for the reuptake of the neurotransmitter substrates, dopamine, serotonin, and norepinephrine, are drug targets for the treatment of psychiatric disorders including depression, anxiety, and attention deficit hyperactivity disorder. Small molecules that inhibit these proteins can serve as useful therapeutic agents. However, some dopamine transporter (DAT) inhibitors, such as cocaine and methamphetamine, are highly addictive and abusable. Efforts have been made to develop small molecules that will inhibit the transporters and elucidate specific binding site interactions. This work provides knowledge of molecular interactions associated with MAT inhibitors by offering an atomistic perspective that can guide designs of new pharmacotherapeutics with enhanced activity. The work described herein evaluates intermolecular interactions using computational methods to reveal the mechanistic detail of inhibitors binding in the DAT. Because cocaine recognizes the extracellular-facing or outward-facing (OF) DAT conformation and benztropine recognizes the intracellular-facing or inward-facing (IF) conformation, it was postulated that behaviorally "typical" (abusable, locomotor psychostimulant) inhibitors stabilize the OF DAT and "atypical" (little or no abuse potential) inhibitors favor IF DAT. Indeed, behaviorally-atypical cocaine analogs have now been shown to prefer the OF DAT conformation. Specifically, the binding interactions of two cocaine analogs, LX10 and LX11, were studied in the OF DAT using molecular dynamics simulations. LX11 was able to interact with residues of transmembrane helix 8 and bind in a fashion that allowed for hydration of the primary binding site (S1) from the intracellular space, thus impacting the intracellular interaction network capable of regulating conformational transitions in DAT. Additionally, a novel serotonin transporter (SERT) inhibitor previously discovered through virtual screening at the SERT secondary binding site (S2) was studied. Intermolecular interactions between SM11 and SERT have been assessed using binding free energy calculations to predict the ligand-binding site and optimize ligand-binding interactions. Results indicate the addition of atoms to the 4-chlorobenzyl moiety were most energetically favorable. The simulations carried out in DAT and SERT were supported by experimental results. Furthermore, the co-crystal structures of DAT and SERT share similar ligand-binding interactions with the homology models used in this study.

Apigenin shows synergistic anticancer activity with curcumin by binding at different sites of tubulin.

PubMed

Choudhury, Diptiman; Ganguli, Arnab; Dastidar, Debabrata Ghosh; Acharya, Bipul R; Das, Amlan; Chakrabarti, Gopal

2013-06-01

Apigenin, a natural flavone, present in many plants sources, induced apoptosis and cell death in lung epithelium cancer (A549) cells with an IC50 value of 93.7 ± 3.7 μM for 48 h treatment. Target identification investigations using A549 cells and also in cell-free system demonstrated that apigenin depolymerized microtubules and inhibited reassembly of cold depolymerized microtubules of A549 cells. Again apigenin inhibited polymerization of purified tubulin with an IC50 value of 79.8 ± 2.4 μM. It bounds to tubulin in cell-free system and quenched the intrinsic fluorescence of tubulin in a concentration- and time-dependent manner. The interaction was temperature-dependent and kinetics of binding was biphasic in nature with binding rate constants of 11.5 × 10(-7) M(-1) s(-1) and 4.0 × 10(-9) M(-1) s(-1) for fast and slow phases at 37 °C, respectively. The stoichiometry of tubulin-apigenin binding was 1:1 and binding the binding constant (Kd) was 6.08 ± 0.096 μM. Interestingly, apigenin showed synergistic anti-cancer effect with another natural anti-tubulin agent curcumin. Apigenin and curcumin synergistically induced cell death and apoptosis and also blocked cell cycle progression at G2/M phase of A549 cells. The synergistic activity of apigenin and curcumin was also apparent from their strong depolymerizing effects on interphase microtubules and inhibitory effect of reassembly of cold depolymerized microtubules when used in combinations, indicating that these ligands bind to tubulin at different sites. In silico modeling suggested apigenin bounds at the interphase of α-β-subunit of tubulin. The binding site is 19 Å in distance from the previously predicted curcumin binding site. Binding studies with purified protein also showed both apigenin and curcumin can simultaneously bind to purified tubulin. Understanding the mechanism of synergistic effect of apigenin and curcumin could be helped to develop anti-cancer combination drugs from cheap and readily available nutraceuticals. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

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

Free-Energy-Based Protein Design: Re-Engineering Cellular Retinoic Acid Binding Protein II Assisted by the Moveable-Type Approach.

PubMed

Zhong, Haizhen A; Santos, Elizabeth M; Vasileiou, Chrysoula; Zheng, Zheng; Geiger, James H; Borhan, Babak; Merz, Kenneth M

2018-03-14

How to fine-tune the binding free energy of a small-molecule to a receptor site by altering the amino acid residue composition is a key question in protein engineering. Indeed, the ultimate solution to this problem, to chemical accuracy (±1 kcal/mol), will result in profound and wide-ranging applications in protein design. Numerous tools have been developed to address this question using knowledge-based models to more computationally intensive molecular dynamics simulations-based free energy calculations, but while some success has been achieved there remains room for improvement in terms of overall accuracy and in the speed of the methodology. Here we report a fast, knowledge-based movable-type (MT)-based approach to estimate the absolute and relative free energy of binding as influenced by mutations in a small-molecule binding site in a protein. We retrospectively validate our approach using mutagenesis data for retinoic acid binding to the Cellular Retinoic Acid Binding Protein II (CRABPII) system and then make prospective predictions that are borne out experimentally. The overall performance of our approach is supported by its success in identifying mutants that show high or even sub-nano-molar binding affinities of retinoic acid to the CRABPII system.

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

Dai, Han; Shin, Ok-Ho; Machius, Mischa

The neuronal protein synaptotagmin 1 functions as a Ca{sup 2+} sensor in exocytosis via two Ca{sup 2+}-binding C{sub 2} domains. The very similar synaptotagmin 4, which includes all the predicted Ca{sup 2+}-binding residues in the C{sub 2}B domain but not in the C{sub 2}A domain, is also thought to function as a neuronal Ca{sup 2+} sensor. Here we show that, unexpectedly, both C{sub 2} domains of fly synaptotagmin 4 exhibit Ca{sup 2+}-dependent phospholipid binding, whereas neither C{sub 2} domain of rat synaptotagmin 4 binds Ca{sup 2+} or phospholipids efficiently. Crystallography reveals that changes in the orientations of critical Ca{sup 2+}more » ligands, and perhaps their flexibility, render the rat synaptotagmin 4 C{sub 2}B domain unable to form full Ca{sup 2+}-binding sites. These results indicate that synaptotagmin 4 is a Ca{sup 2+} sensor in the fly but not in the rat, that the Ca{sup 2+}-binding properties of C{sub 2} domains cannot be reliably predicted from sequence analyses, and that proteins clearly identified as orthologs may nevertheless have markedly different functional properties.« less

Computational and Biochemical Docking of the Irreversible Cocaine Analog RTI 82 Directly Demonstrates Ligand Positioning in the Dopamine Transporter Central Substrate-binding Site*

PubMed Central

Dahal, Rejwi Acharya; Pramod, Akula Bala; Sharma, Babita; Krout, Danielle; Foster, James D.; Cha, Joo Hwan; Cao, Jianjing; Newman, Amy Hauck; Lever, John R.; Vaughan, Roxanne A.; Henry, L. Keith

2014-01-01

The dopamine transporter (DAT) functions as a key regulator of dopaminergic neurotransmission via re-uptake of synaptic dopamine (DA). Cocaine binding to DAT blocks this activity and elevates extracellular DA, leading to psychomotor stimulation and addiction, but the mechanisms by which cocaine interacts with DAT and inhibits transport remain incompletely understood. Here, we addressed these questions using computational and biochemical methodologies to localize the binding and adduction sites of the photoactivatable irreversible cocaine analog 3β-(p-chlorophenyl)tropane-2β-carboxylic acid, 4′-azido-3′-iodophenylethyl ester ([125I]RTI 82). Comparative modeling and small molecule docking indicated that the tropane pharmacophore of RTI 82 was positioned in the central DA active site with an orientation that juxtaposed the aryliodoazide group for cross-linking to rat DAT Phe-319. This prediction was verified by focused methionine substitution of residues flanking this site followed by cyanogen bromide mapping of the [125I]RTI 82-labeled mutants and by the substituted cysteine accessibility method protection analyses. These findings provide positive functional evidence linking tropane pharmacophore interaction with the core substrate-binding site and support a competitive mechanism for transport inhibition. This synergistic application of computational and biochemical methodologies overcomes many uncertainties inherent in other approaches and furnishes a schematic framework for elucidating the ligand-protein interactions of other classes of DA transport inhibitors. PMID:25179220

Relationship of nonreturn rates of dairy bulls to binding affinity of heparin to sperm

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

Marks, J.L.; Ax, R.L.

1985-08-01

The binding of the glycosaminoglycan (3H) heparin to bull spermatozoa was compared with nonreturn rates of dairy bulls. Semen samples from five bulls above and five below an average 71% nonreturn rate were used. Samples consisted of first and second ejaculates on a single day collected 1 d/wk for up to 5 consecutive wk. Saturation binding assays using (TH) heparin were performed to quantitate the binding characteristics of each sample. Scatchard plot analyses indicated a significant difference in the binding affinity for (TH) heparin between bulls of high and low fertility. Dissociation constants were 69.0 and 119.3 pmol for bullsmore » of high and low fertility, respectively. In contrast, the number of binding sites for (TH) heparin did not differ significantly among bulls. Differences in binding affinity of (TH) heparin to bull sperm might be used to predict relative fertility of dairy bulls.« less

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.

Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets.

PubMed

Feinstein, Wei P; Brylinski, Michal

2015-01-01

Computational approaches have emerged as an instrumental methodology in modern research. For example, virtual screening by molecular docking is routinely used in computer-aided drug discovery. One of the critical parameters for ligand docking is the size of a search space used to identify low-energy binding poses of drug candidates. Currently available docking packages often come with a default protocol for calculating the box size, however, many of these procedures have not been systematically evaluated. In this study, we investigate how the docking accuracy of AutoDock Vina is affected by the selection of a search space. We propose a new procedure for calculating the optimal docking box size that maximizes the accuracy of binding pose prediction against a non-redundant and representative dataset of 3,659 protein-ligand complexes selected from the Protein Data Bank. Subsequently, we use the Directory of Useful Decoys, Enhanced to demonstrate that the optimized docking box size also yields an improved ranking in virtual screening. Binding pockets in both datasets are derived from the experimental complex structures and, additionally, predicted by eFindSite. A systematic analysis of ligand binding poses generated by AutoDock Vina shows that the highest accuracy is achieved when the dimensions of the search space are 2.9 times larger than the radius of gyration of a docking compound. Subsequent virtual screening benchmarks demonstrate that this optimized docking box size also improves compound ranking. For instance, using predicted ligand binding sites, the average enrichment factor calculated for the top 1 % (10 %) of the screening library is 8.20 (3.28) for the optimized protocol, compared to 7.67 (3.19) for the default procedure. Depending on the evaluation metric, the optimal docking box size gives better ranking in virtual screening for about two-thirds of target proteins. This fully automated procedure can be used to optimize docking protocols in order to improve the ranking accuracy in production virtual screening simulations. Importantly, the optimized search space systematically yields better results than the default method not only for experimental pockets, but also for those predicted from protein structures. A script for calculating the optimal docking box size is freely available at www.brylinski.org/content/docking-box-size. Graphical AbstractWe developed a procedure to optimize the box size in molecular docking calculations. Left panel shows the predicted binding pose of NADP (green sticks) compared to the experimental complex structure of human aldose reductase (blue sticks) using a default protocol. Right panel shows the docking accuracy using an optimized box size.

Membrane Topology Mapping of the Na+-Pumping NADH: Quinone Oxidoreductase from Vibrio cholerae by PhoA- Green Fluorescent Protein Fusion Analysis▿

PubMed Central

Duffy, Ellen B.; Barquera, Blanca

2006-01-01

The membrane topologies of the six subunits of Na+-translocating NADH:quinone oxidoreductase (Na+-NQR) from Vibrio cholerae were determined by a combination of topology prediction algorithms and the construction of C-terminal fusions. Fusion expression vectors contained either bacterial alkaline phosphatase (phoA) or green fluorescent protein (gfp) genes as reporters of periplasmic and cytoplasmic localization, respectively. A majority of the topology prediction algorithms did not predict any transmembrane helices for NqrA. A lack of PhoA activity when fused to the C terminus of NqrA and the observed fluorescence of the green fluorescent protein C-terminal fusion confirm that this subunit is localized to the cytoplasmic side of the membrane. Analysis of four PhoA fusions for NqrB indicates that this subunit has nine transmembrane helices and that residue T236, the binding site for flavin mononucleotide (FMN), resides in the cytoplasm. Three fusions confirm that the topology of NqrC consists of two transmembrane helices with the FMN binding site at residue T225 on the cytoplasmic side. Fusion analysis of NqrD and NqrE showed almost mirror image topologies, each consisting of six transmembrane helices; the results for NqrD and NqrE are consistent with the topologies of Escherichia coli homologs YdgQ and YdgL, respectively. The NADH, flavin adenine dinucleotide, and Fe-S center binding sites of NqrF were localized to the cytoplasm. The determination of the topologies of the subunits of Na+-NQR provides valuable insights into the location of cofactors and identifies targets for mutagenesis to characterize this enzyme in more detail. The finding that all the redox cofactors are localized to the cytoplasmic side of the membrane is discussed. PMID:17041063

DNA mimic proteins: functions, structures, and bioinformatic analysis.

PubMed

Wang, Hao-Ching; Ho, Chun-Han; Hsu, Kai-Cheng; Yang, Jinn-Moon; Wang, Andrew H-J

2014-05-13

DNA mimic proteins have DNA-like negative surface charge distributions, and they function by occupying the DNA binding sites of DNA binding proteins to prevent these sites from being accessed by DNA. DNA mimic proteins control the activities of a variety of DNA binding proteins and are involved in a wide range of cellular mechanisms such as chromatin assembly, DNA repair, transcription regulation, and gene recombination. However, the sequences and structures of DNA mimic proteins are diverse, making them difficult to predict by bioinformatic search. To date, only a few DNA mimic proteins have been reported. These DNA mimics were not found by searching for functional motifs in their sequences but were revealed only by structural analysis of their charge distribution. This review highlights the biological roles and structures of 16 reported DNA mimic proteins. We also discuss approaches that might be used to discover new DNA mimic proteins.

Computational characterization of chromatin domain boundary-associated genomic elements

PubMed Central

Hong, Seungpyo

2017-01-01

Abstract Topologically associated domains (TADs) are 3D genomic structures with high internal interactions that play important roles in genome compaction and gene regulation. Their genomic locations and their association with CCCTC-binding factor (CTCF)-binding sites and transcription start sites (TSSs) were recently reported. However, the relationship between TADs and other genomic elements has not been systematically evaluated. This was addressed in the present study, with a focus on the enrichment of these genomic elements and their ability to predict the TAD boundary region. We found that consensus CTCF-binding sites were strongly associated with TAD boundaries as well as with the transcription factors (TFs) Zinc finger protein (ZNF)143 and Yin Yang (YY)1. TAD boundary-associated genomic elements include DNase I-hypersensitive sites, H3K36 trimethylation, TSSs, RNA polymerase II, and TFs such as Specificity protein 1, ZNF274 and SIX homeobox 5. Computational modeling with these genomic elements suggests that they have distinct roles in TAD boundary formation. We propose a structural model of TAD boundaries based on these findings that provides a basis for studying the mechanism of chromatin structure formation and gene regulation. PMID:28977568

Copper binding to soil fulvic and humic acids: NICA-Donnan modeling and conditional affinity spectra.

PubMed

Xu, Jinling; Tan, Wenfeng; Xiong, Juan; Wang, Mingxia; Fang, Linchuan; Koopal, Luuk K

2016-07-01

Binding of Cu(II) to soil fulvic acid (JGFA), soil humic acids (JGHA, JLHA), and lignite-based humic acid (PAHA) was investigated through NICA-Donnan modeling and conditional affinity spectrum (CAS). It is to extend the knowledge of copper binding by soil humic substances (HS) both in respect of enlarging the database of metal ion binding to HS and obtaining a good insight into Cu binding to the functional groups of FA and HA by using the NICA-Donnan model to unravel the intrinsic and conditional affinity spectra. Results showed that Cu binding to HS increased with increasing pH and decreasing ionic strength. The amount of Cu bound to the HAs was larger than the amount bound to JGFA. Milne's generic parameters did not provide satisfactory predictions for the present soil HS samples, while material-specific NICA-Donnan model parameters described and predicted Cu binding to the HS well. Both the 'low' and 'high' concentration fitting procedures indicated a substantial bidentate structure of the Cu complexes with HS. By means of CAS underlying NICA isotherm, which was scarcely used, the nature of the binding at different solution conditions for a given sample and the differences in binding mode were illustrated. It was indicated that carboxylic group played an indispensable role in Cu binding to HS in that the carboxylic CAS had stronger conditional affinity than the phenolic distribution due to its large degree of proton dissociation. The fact was especially true for JGFA and JLHA which contain much larger amount of carboxylic groups, and the occupation of phenolic sites by Cu was negligible. Comparable amounts of carboxylic and phenolic groups on PAHA and JGHA, increased the occupation of phenolic type sites by Cu. The binding strength of PAHA-Cu and JGHA-Cu was stronger than that of JGFA-Cu and JLHA-Cu. The presence of phenolic groups increased the chance of forming more stable complexes, such as the salicylate-Cu or catechol-Cu type structures. Copyright © 2016. Published by Elsevier Inc.

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme

PubMed Central

Leong, Max K.; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-01

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r2 = 0.928–0.988,  = 0.894–0.954, RMSE = 0.002–0.412, s = 0.001–0.214), and the predicted pKi values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r2 = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q2 = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery. PMID:28059133

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme.

PubMed

Leong, Max K; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-06

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r 2  = 0.928-0.988,  = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pK i values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r 2  = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q 2  = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.

Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme

NASA Astrophysics Data System (ADS)

Leong, Max K.; Syu, Ren-Guei; Ding, Yi-Lung; Weng, Ching-Feng

2017-01-01

The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n = 30, r2 = 0.928-0.988,  = 0.894-0.954, RMSE = 0.002-0.412, s = 0.001-0.214), and the predicted pKi values by SVM-Score were found to be in good agreement with the observed values for the training samples (n = 24, r2 = 0.967,  = 0.899, RMSE = 0.295, s = 0.170) and test samples (n = 13, q2 = 0.894, RMSE = 0.437, s = 0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.

A functional SNP catalog of overlapping miRNA-binding sites in genes implicated in prion disease and other neurodegenerative disorders.

PubMed

Saba, Reuben; Medina, Sarah J; Booth, Stephanie A

2014-10-01

The involvement of SNPs in miRNA target sites remains poorly investigated in neurodegenerative disease. In addition to associations with disease risk, such genetic variations can also provide novel insight into mechanistic pathways that may be responsible for disease etiology and/or pathobiology. To identify SNPs associated specifically with degenerating neurons, we restricted our analysis to genes that are dysregulated in CA1 hippocampal neurons of mice during early, preclinical phase of Prion disease. The 125 genes chosen are also implicated in other numerous degenerative and neurological diseases and disorders and are therefore likely to be of fundamental importance. We predicted those SNPs that could increase, decrease, or have neutral effects on miRNA binding. This group of genes was more likely to possess DNA variants than were genes chosen at random. Furthermore, many of the SNPs are common within the human population, and could contribute to the growing awareness that miRNAs and associated SNPs could account for detrimental neurological states. Interestingly, SNPs that overlapped miRNA-binding sites in the 3'-UTR of GABA-receptor subunit coding genes were particularly enriched. Moreover, we demonstrated that SNP rs9291296 would strengthen miR-26a-5p binding to a highly conserved site in the 3'-UTR of gamma-aminobutyric acid receptor subunit alpha-4. © 2014 WILEY PERIODICALS, INC.

Determination of an organic-acid analog of DOC for use in copper toxicity studies on salmonids

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

MacRae, R.K.; Meyer, J.S.; Hansen, J.A.

1995-12-31

Concentrations of dissolved copper in streams draining mine sites often exceed concentrations shown to cause acute and chronic mortality in salmonids. However, toxicity and impaired behaviors may be modified by dissolved organic carbon (DOC) and other inorganic components present in the site water. The effects of DOC on copper speciation, and thus bioavailability and toxicity, were determined by titrating stream waters with copper, using a cupric ion-specific electrode to detect free copper concentrations. Effects of various competing cations (e.g., Ca{sup +2}, Co{sup +2}) on copper-DOC binding were also evaluated. Titration results were evaluated using Scatchard and non-linear regression analyses tomore » quantify the strength and capacity of copper-DOC binding. Inorganic speciation was determined using the geochemical model MINEQL{sup +}. Results of these titrations indicated the presence of two or three distinct copper binding components in site water DOC. Three commercially available organic acids where then chosen to mimic the binding characteristics of natural DOC. This DOC-analog was used successfully in fish toxicity studies to evaluate the influence of DOC on copper bioavailability. Geochemical models were developed to predict copper speciation in both laboratory test waters and site waters, for any typical combination of water chemistry parameters (pH, alkalinity, [DOC], etc.). A combined interpretation of fish toxicity and modeling results indicate that some DOC-bound copper was bioavailable.« less

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

Cloning of an SNF2/SWI2-related protein that binds specifically to the SPH motifs of the SV40 enhancer and to the HIV-1 promoter.

PubMed

Sheridan, P L; Schorpp, M; Voz, M L; Jones, K A

1995-03-03

We have isolated a human cDNA clone encoding HIP116, a protein that binds to the SPH repeats of the SV40 enhancer and to the TATA/inhibitor region of the human immunodeficiency virus (HIV)-1 promoter. The predicted HIP116 protein is related to the yeast SNF2/SWI2 transcription factor and to other members of this extended family and contains seven domains similar to those found in the vaccinia NTP1 ATPase. Interestingly, HIP116 also contains a C3HC4 zinc-binding motif (RING finger) interspersed between the ATPase motifs in an arrangement similar to that found in the yeast RAD5 and RAD16 proteins. The HIP116 amino terminus is unique among the members of this family, and houses a specific DNA-binding domain. Antiserum raised against HIP116 recognizes a 116-kDa nuclear protein in Western blots and specifically supershifts SV40 and HIV-1 protein-DNA complexes in gel shift experiments. The binding site for HIP116 on the SV40 enhancer directly overlaps the site for TEF-1, and like TEF-1, binding of HIP116 to the SV40 enhancer is destroyed by mutations that inhibit SPH enhancer activity in vivo. Purified fractions of HIP116 display strong ATPase activity that is preferentially stimulated by SPH DNA and can be inhibited specifically by antibodies to HIP116. These findings suggest that HIP116 might affect transcription, directly or indirectly, by acting as a DNA binding site-specific ATPase.

Toxicokinetics, including saturable protein binding, of 4-chloro-2-methyl phenoxyacetic acid (MCPA) in patients with acute poisoning

PubMed Central

Roberts, Darren M.; Dawson, Andrew H.; Senarathna, Lalith; Mohamed, Fahim; Cheng, Ron; Eaglesham, Geoffrey; Buckley, Nick A.

2011-01-01

Human data on protein binding and dose-dependent changes in toxicokinetics for MCPA are very limited. 128 blood samples were obtained in 49 patients with acute MCPA poisoning and total and unbound concentrations of MCPA were determined. The Scatchard plot was biphasic suggesting protein binding to two sites. The free MCPA concentration increased when the total concentration exceeded 239 mg/L (95% confidence interval 198–274 mg/L). Nonlinear regression using a two-site binding hyperbola model estimated saturation of the high affinity binding site at 115 mg/L (95%CI 0–304). Further analyses using global fitting of serial data and adjusting for the concentration of albumin predicted similar concentrations for saturable binding (184 mg/L and 167 mg/L, respectively) without narrowing the 95%CI. In 25 patients, the plasma concentration–time curves for both bound and unbound MCPA were approximately log-linear which may suggest first order elimination, although sampling was infrequent so zero order elimination cannot be excluded. Using a cut-off concentration of 200 mg/L, the half-life of MCPA at higher concentrations was 25.5 h (95%CI 15.0–83.0 h; n = 16 patients) compared to 16.8 h (95%CI 13.6–22.2 h; n = 10 patients) at lower concentrations. MCPA is subject to saturable protein binding but the influence on half-life appears marginal. PMID:21256202

Structural Dynamics as a Contributor to Error-prone Replication by an RNA-dependent RNA Polymerase*

PubMed Central

Moustafa, Ibrahim M.; Korboukh, Victoria K.; Arnold, Jamie J.; Smidansky, Eric D.; Marcotte, Laura L.; Gohara, David W.; Yang, Xiaorong; Sánchez-Farrán, María Antonieta; Filman, David; Maranas, Janna K.; Boehr, David D.; Hogle, James M.; Colina, Coray M.; Cameron, Craig E.

2014-01-01

RNA viruses encoding high- or low-fidelity RNA-dependent RNA polymerases (RdRp) are attenuated. The ability to predict residues of the RdRp required for faithful incorporation of nucleotides represents an essential step in any pipeline intended to exploit perturbed fidelity as the basis for rational design of vaccine candidates. We used x-ray crystallography, molecular dynamics simulations, NMR spectroscopy, and pre-steady-state kinetics to compare a mutator (H273R) RdRp from poliovirus to the wild-type (WT) enzyme. We show that the nucleotide-binding site toggles between the nucleotide binding-occluded and nucleotide binding-competent states. The conformational dynamics between these states were enhanced by binding to primed template RNA. For the WT, the occluded conformation was favored; for H273R, the competent conformation was favored. The resonance for Met-187 in our NMR spectra reported on the ability of the enzyme to check the correctness of the bound nucleotide. Kinetic experiments were consistent with the conformational dynamics contributing to the established pre-incorporation conformational change and fidelity checkpoint. For H273R, residues comprising the active site spent more time in the catalytically competent conformation and were more positively correlated than the WT. We propose that by linking the equilibrium between the binding-occluded and binding-competent conformations of the nucleotide-binding pocket and other active-site dynamics to the correctness of the bound nucleotide, faithful nucleotide incorporation is achieved. These studies underscore the need to apply multiple biophysical and biochemical approaches to the elucidation of the physical basis for polymerase fidelity. PMID:25378410

Determination of thermodynamic parameters for complexation of calcium and magnesium with chondroitin sulfate isomers using isothermal titration calorimetry: Implications for calcium kidney-stone research

NASA Astrophysics Data System (ADS)

Rodgers, Allen L.; Jackson, Graham E.

2017-04-01

Chondroitin sulfate (CS) occurs in human urine. It has several potential binding sites for calcium and as such may play an inhibitory role in calcium oxalate and calcium phosphate (kidney stone disease by reducing the supersaturation (SS) and crystallization of these salts. Urinary magnesium is also a role player in determining speciation in stone forming processes. This study was undertaken to determine the thermodynamic parameters for binding of the disaccharide unit of two different CS isomers with calcium and magnesium. These included the binding constant K. Experiments were performed using an isothermal titration calorimeter (ITC) at 3 different pH levels in the physiological range in human urine. Data showed that interactions between the CS isomers and calcium and magnesium occur via one binding site, thought to be sulfate, and that log K values are 1.17-1.93 and 1.77-1.80 for these two metals respectively. Binding was significantly stronger in Mg-CS than in Ca-CS complexes and was found to be dependent on pH in the latter but not in the former. Furthermore, binding in Ca-CS complexes was dependent on the location of the sulfate binding site. This was not the case in the Mg-CS complexes. Interactions were shown to be entropy driven and enthalpy unfavourable. These findings can be used in computational modeling studies to predict the effects of the calcium and magnesium CS complexes on the speciation of calcium and the SS of calcium salts in real urine samples.

Computational analysis of protein-protein interfaces involving an alpha helix: insights for terphenyl-like molecules binding.

PubMed

Isvoran, Adriana; Craciun, Dana; Martiny, Virginie; Sperandio, Olivier; Miteva, Maria A

2013-06-14

Protein-Protein Interactions (PPIs) are key for many cellular processes. The characterization of PPI interfaces and the prediction of putative ligand binding sites and hot spot residues are essential to design efficient small-molecule modulators of PPI. Terphenyl and its derivatives are small organic molecules known to mimic one face of protein-binding alpha-helical peptides. In this work we focus on several PPIs mediated by alpha-helical peptides. We performed computational sequence- and structure-based analyses in order to evaluate several key physicochemical and surface properties of proteins known to interact with alpha-helical peptides and/or terphenyl and its derivatives. Sequence-based analysis revealed low sequence identity between some of the analyzed proteins binding alpha-helical peptides. Structure-based analysis was performed to calculate the volume, the fractal dimension roughness and the hydrophobicity of the binding regions. Besides the overall hydrophobic character of the binding pockets, some specificities were detected. We showed that the hydrophobicity is not uniformly distributed in different alpha-helix binding pockets that can help to identify key hydrophobic hot spots. The presence of hydrophobic cavities at the protein surface with a more complex shape than the entire protein surface seems to be an important property related to the ability of proteins to bind alpha-helical peptides and low molecular weight mimetics. Characterization of similarities and specificities of PPI binding sites can be helpful for further development of small molecules targeting alpha-helix binding proteins.

Structural Basis for Certain Naturally Occurring Bioflavonoids to Function as Reducing Co-Substrates of Cyclooxygenase I and II

PubMed Central

Zhu, Bao Ting

2010-01-01

Background Recent studies showed that some of the dietary bioflavonoids can strongly stimulate the catalytic activity of cyclooxygenase (COX) I and II in vitro and in vivo, presumably by facilitating enzyme re-activation. In this study, we sought to understand the structural basis of COX activation by these dietary compounds. Methodology/Principal Findings A combination of molecular modeling studies, biochemical analysis and site-directed mutagenesis assay was used as research tools. Three-dimensional quantitative structure-activity relationship analysis (QSAR/CoMFA) predicted that the ability of bioflavonoids to activate COX I and II depends heavily on their B-ring structure, a moiety known to be associated with strong antioxidant ability. Using the homology modeling and docking approaches, we identified the peroxidase active site of COX I and II as the binding site for bioflavonoids. Upon binding to this site, bioflavonoid can directly interact with hematin of the COX enzyme and facilitate the electron transfer from bioflavonoid to hematin. The docking results were verified by biochemical analysis, which reveals that when the cyclooxygenase activity of COXs is inhibited by covalent modification, myricetin can still stimulate the conversion of PGG2 to PGE2, a reaction selectively catalyzed by the peroxidase activity. Using the site-directed mutagenesis analysis, we confirmed that Q189 at the peroxidase site of COX II is essential for bioflavonoids to bind and re-activate its catalytic activity. Conclusions/Significance These findings provide the structural basis for bioflavonoids to function as high-affinity reducing co-substrates of COXs through binding to the peroxidase active site, facilitating electron transfer and enzyme re-activation. PMID:20808785

Identification of the hydrophobic strand in the A–B loop of leptin as major binding site III: implications for large-scale preparation of potent recombinant human and ovine leptin antagonists

PubMed Central

Niv-Spector, Leonora; Gonen-Berger, Dana; Gourdou, Isabelle; Biener, Eva; Gussakovsky, Eugene E.; Benomar, Yackir; Ramanujan, Krishnan V.; Taouis, Mohammed; Herman, Brian; Callebaut, Isabelle; Djiane, Jean; Gertler, Arieh

2005-01-01

Interaction of leptin with its receptors resembles that of interleukin-6 and granulocyte colony-stimulating factor, which interact with their receptors through binding sites I–III. Site III plays a pivotal role in receptors' dimerization or tetramerization and subsequent activation. Leptin's site III also mediates the formation of an active multimeric complex through its interaction with the IGD (immunoglobulin-like domain) of LEPRs (leptin receptors). Using a sensitive hydrophobic cluster analysis of leptin's and LEPR's sequences, we identified hydrophobic stretches in leptin's A–B loop (amino acids 39–42) and in the N-terminal end of LEPR's IGD (amino acids 325–328) that are predicted to participate in site III and to interact with each other in a β-sheet-like configuration. To verify this hypothesis, we prepared and purified to homogeneity (as verified by SDS/PAGE, gel filtration and reverse-phase chromatography) several alanine muteins of amino acids 39–42 in human and ovine leptins. CD analyses revealed that those mutations hardly affect the secondary structure. All muteins acted as true antagonists, i.e. they bound LEPR with an affinity similar to the wild-type hormone, had no agonistic activity and specifically inhibited leptin action in several leptin-responsive in vitro bioassays. Alanine mutagenesis of LEPR's IGD (amino acids 325–328) drastically reduced its biological but not binding activity, indicating the importance of this region for interaction with leptin's site III. FRET (fluorescence resonance energy transfer) microscopy experiments have documented that the transient FRET signalling occurring upon exposure to leptin results not from binding of the ligand, but from ligand-induced oligomerization of LEPRs mediated by leptin's site III. PMID:15952938

PoSSuM v.2.0: data update and a new function for investigating ligand analogs and target proteins of small-molecule drugs.

PubMed

Ito, Jun-ichi; Ikeda, Kazuyoshi; Yamada, Kazunori; Mizuguchi, Kenji; Tomii, Kentaro

2015-01-01

PoSSuM (http://possum.cbrc.jp/PoSSuM/) is a database for detecting similar small-molecule binding sites on proteins. Since its initial release in 2011, PoSSuM has grown to provide information related to 49 million pairs of similar binding sites discovered among 5.5 million known and putative binding sites. This enlargement of the database is expected to enhance opportunities for biological and pharmaceutical applications, such as predictions of new functions and drug discovery. In this release, we have provided a new service named PoSSuM drug search (PoSSuMds) at http://possum.cbrc.jp/PoSSuM/drug_search/, in which we selected 194 approved drug compounds retrieved from ChEMBL, and detected their known binding pockets and pockets that are similar to them. Users can access and download all of the search results via a new web interface, which is useful for finding ligand analogs as well as potential target proteins. Furthermore, PoSSuMds enables users to explore the binding pocket universe within PoSSuM. Additionally, we have improved the web interface with new functions, including sortable tables and a viewer for visualizing and downloading superimposed pockets. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

The FTMap family of web servers for determining and characterizing ligand binding hot spots of proteins

PubMed Central

Kozakov, Dima; Grove, Laurie E.; Hall, David R.; Bohnuud, Tanggis; Mottarella, Scott; Luo, Lingqi; Xia, Bing; Beglov, Dmitri; Vajda, Sandor

2016-01-01

FTMap is a computational mapping server that identifies binding hot spots of macromolecules, i.e., regions of the surface with major contributions to the ligand binding free energy. To use FTMap, users submit a protein, DNA, or RNA structure in PDB format. FTMap samples billions of positions of small organic molecules used as probes and scores the probe poses using a detailed energy expression. Regions that bind clusters of multiple probe types identify the binding hot spots, in good agreement with experimental data. FTMap serves as basis for other servers, namely FTSite to predict ligand binding sites, FTFlex to account for side chain flexibility, FTMap/param to parameterize additional probes, and FTDyn to map ensembles of protein structures. Applications include determining druggability of proteins, identifying ligand moieties that are most important for binding, finding the most bound-like conformation in ensembles of unliganded protein structures, and providing input for fragment based drug design. FTMap is more accurate than classical mapping methods such as GRID and MCSS, and is much faster than the more recent approaches to protein mapping based on mixed molecular dynamics. Using 16 probe molecules, the FTMap server finds the hot spots of an average size protein in less than an hour. Since FTFlex performs mapping for all low energy conformers of side chains in the binding site, its completion time is proportionately longer. PMID:25855957

Crystal structure of the S187F variant of human liver alanine: Aminotransferase associated with primary hyperoxaluria type I and its functional implications

PubMed Central

Oppici, Elisa; Fodor, Krisztian; Paiardini, Alessandro; Williams, Chris; Voltattorni, Carla Borri; Wilmanns, Matthias; Cellini, Barbara

2013-01-01

The substitution of Ser187, a residue located far from the active site of human liver peroxisomal alanine:glyoxylate aminotransferase (AGT), by Phe gives rise to a variant associated with primary hyperoxaluria type I. Unexpectedly, previous studies revealed that the recombinant form of S187F exhibits a remarkable loss of catalytic activity, an increased pyridoxal 5′-phosphate (PLP) binding affinity and a different coenzyme binding mode compared with normal AGT. To shed light on the structural elements responsible for these defects, we solved the crystal structure of the variant to a resolution of 2.9 Å. Although the overall conformation of the variant is similar to that of normal AGT, we noticed: (i) a displacement of the PLP-binding Lys209 and Val185, located on the re and si side of PLP, respectively, and (ii) slight conformational changes of other active site residues, in particular Trp108, the base stacking residue with the pyridine cofactor moiety. This active site perturbation results in a mispositioning of the AGT-pyridoxamine 5′-phosphate (PMP) complex and of the external aldimine, as predicted by molecular modeling studies. Taken together, both predicted and observed movements caused by the S187F mutation are consistent with the following functional properties of the variant: (i) a 300- to 500-fold decrease in both the rate constant of L-alanine half-transamination and the kcat of the overall transamination, (ii) a different PMP binding mode and affinity, and (iii) a different microenvironment of the external aldimine. Proposals for the treatment of patients bearing S187F mutation are discussed on the basis of these results. Proteins 2013; 81:1457–1465. © 2013 Wiley Periodicals, Inc. PMID:23589421

Homology-based modeling of the Erwinia amylovora type III secretion chaperone DspF used to identify amino acids required for virulence and interaction with the effector DspE.

PubMed

Triplett, Lindsay R; Wedemeyer, William J; Sundin, George W

2010-09-01

The structure of DspF, a type III secretion system (T3SS) chaperone required for virulence of the fruit tree pathogen Erwinia amylovora, was modeled based on predicted structural homology to characterized T3SS chaperones. This model guided the selection of 11 amino acid residues that were individually mutated to alanine via site-directed mutagenesis. Each mutant was assessed for its effect on virulence complementation, dimerization and interaction with the N-terminal chaperone-binding site of DspE. Four amino acid residues were identified that did not complement the virulence defect of a dspF knockout mutant, and three of these residues were required for interaction with the N-terminus of DspE. This study supports the significance of the predicted beta-sheet helix-binding groove in DspF chaperone function. Copyright 2010 Elsevier Masson SAS. All rights reserved.

Using synthetic bacterial enhancers to reveal a looping-based mechanism for quenching-like repression

PubMed Central

Brunwasser-Meirom, Michal; Pollak, Yaroslav; Goldberg, Sarah; Levy, Lior; Atar, Orna; Amit, Roee

2016-01-01

We explore a model for ‘quenching-like' repression by studying synthetic bacterial enhancers, each characterized by a different binding site architecture. To do so, we take a three-pronged approach: first, we compute the probability that a protein-bound dsDNA molecule will loop. Second, we use hundreds of synthetic enhancers to test the model's predictions in bacteria. Finally, we verify the mechanism bioinformatically in native genomes. Here we show that excluded volume effects generated by DNA-bound proteins can generate substantial quenching. Moreover, the type and extent of the regulatory effect depend strongly on the relative arrangement of the binding sites. The implications of these results are that enhancers should be insensitive to 10–11 bp insertions or deletions (INDELs) and sensitive to 5–6 bp INDELs. We test this prediction on 61 σ54-regulated qrr genes from the Vibrio genus and confirm the tolerance of these enhancers' sequences to the DNA's helical repeat. PMID:26832446

Using synthetic bacterial enhancers to reveal a looping-based mechanism for quenching-like repression.

PubMed

Brunwasser-Meirom, Michal; Pollak, Yaroslav; Goldberg, Sarah; Levy, Lior; Atar, Orna; Amit, Roee

2016-02-02

We explore a model for 'quenching-like' repression by studying synthetic bacterial enhancers, each characterized by a different binding site architecture. To do so, we take a three-pronged approach: first, we compute the probability that a protein-bound dsDNA molecule will loop. Second, we use hundreds of synthetic enhancers to test the model's predictions in bacteria. Finally, we verify the mechanism bioinformatically in native genomes. Here we show that excluded volume effects generated by DNA-bound proteins can generate substantial quenching. Moreover, the type and extent of the regulatory effect depend strongly on the relative arrangement of the binding sites. The implications of these results are that enhancers should be insensitive to 10-11 bp insertions or deletions (INDELs) and sensitive to 5-6 bp INDELs. We test this prediction on 61 σ(54)-regulated qrr genes from the Vibrio genus and confirm the tolerance of these enhancers' sequences to the DNA's helical repeat.

Characterization of the active site properties of CYP4F12.

PubMed

Eksterowicz, John; Rock, Dan A; Rock, Brooke M; Wienkers, Larry C; Foti, Robert S

2014-10-01

Cytochrome P450 4F12 is a drug-metabolizing enzyme that is primarily expressed in the liver, kidney, colon, small intestine, and heart. The properties of CYP4F12 that may impart an increased catalytic selectivity (decreased promiscuity) were explored through in vitro metabolite elucidation, kinetic isotope effect experiments, and computational modeling of the CYP4F12 active site. By using astemizole as a probe substrate for CYP4F12 and CYP3A4, it was observed that although CYP4F12 favored astemizole O-demethylation as the primary route of metabolism, CYP3A4 was capable of metabolizing astemizole at multiple sites on the molecule. Deuteration of astemizole at the site of O-demethylation resulted in an isotope effect of 7.1 as well as an 8.3-fold decrease in the rate of clearance for astemizole by CYP4F12. Conversely, although an isotope effect of 3.8 was observed for the formation of the O-desmethyl metabolite when deuterated astemizole was metabolized by CYP3A4, there was no decrease in the clearance of astemizole. Development of a homology model of CYP4F12 based on the crystal structure of cytochrome P450 BM3 predicted an active site volume for CYP4F12 that was approximately 76% of the active site volume of CYP3A4. As predicted, multiple favorable binding orientations were available for astemizole docked into the active site of CYP3A4, but only a single binding orientation with the site of O-demethylation oriented toward the heme was identified for CYP4F12. Overall, it appears that although CYP4F12 may be capable of binding similar ligands to other cytochrome P450 enzymes such as CYP3A4, the ability to achieve catalytically favorable orientations may be inherently more difficult because of the increased steric constraints of the CYP4F12 active site. Copyright © 2014 by The American Society for Pharmacology and Experimental Therapeutics.

Modeling Fission Product Sorption in Graphite Structures

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

Szlufarska, Izabela; Morgan, Dane; Allen, Todd

2013-04-08

The goal of this project is to determine changes in adsorption and desorption of fission products to/from nuclear-grade graphite in response to a changing chemical environment. First, the project team will employ principle calculations and thermodynamic analysis to predict stability of fission products on graphite in the presence of structural defects commonly observed in very high- temperature reactor (VHTR) graphites. Desorption rates will be determined as a function of partial pressure of oxygen and iodine, relative humidity, and temperature. They will then carry out experimental characterization to determine the statistical distribution of structural features. This structural information will yield distributionsmore » of binding sites to be used as an input for a sorption model. Sorption isotherms calculated under this project will contribute to understanding of the physical bases of the source terms that are used in higher-level codes that model fission product transport and retention in graphite. The project will include the following tasks: Perform structural characterization of the VHTR graphite to determine crystallographic phases, defect structures and their distribution, volume fraction of coke, and amount of sp2 versus sp3 bonding. This information will be used as guidance for ab initio modeling and as input for sorptivity models; Perform ab initio calculations of binding energies to determine stability of fission products on the different sorption sites present in nuclear graphite microstructures. The project will use density functional theory (DFT) methods to calculate binding energies in vacuum and in oxidizing environments. The team will also calculate stability of iodine complexes with fission products on graphite sorption sites; Model graphite sorption isotherms to quantify concentration of fission products in graphite. The binding energies will be combined with a Langmuir isotherm statistical model to predict the sorbed concentration of fission products on each type of graphite site. The model will include multiple simultaneous adsorbing species, which will allow for competitive adsorption effects between different fission product species and O and OH (for modeling accident conditions).« less

Role of Protein Dimeric Interface in Allosteric Inhibition of N-Acetyl-Aspartate Hydrolysis by Human Aspartoacylase.

PubMed

Kots, Ekaterina D; Lushchekina, Sofya V; Varfolomeev, Sergey D; Nemukhin, Alexander V

2017-08-28

The results of molecular modeling suggest a mechanism of allosteric inhibition upon hydrolysis of N-acetyl-aspartate (NAA), one of the most abundant amino acid derivatives in brain, by human aspartoacylase (hAsp). Details of this reaction are important to suggest the practical ways to control the enzyme activity. Search for allosteric sites using the Allosite web server and SiteMap analysis allowed us to identify substrate binding pockets located at the interface between the subunits of the hAsp dimer molecule. Molecular docking of NAA to the pointed areas at the dimer interface predicted a specific site, in which the substrate molecule interacts with the Gly237, Arg233, Glu290, and Lys292 residues. Analysis of multiple long-scaled molecular dynamics trajectories (the total simulation time exceeded 1.5 μs) showed that binding of NAA to the identified allosteric site induced significant rigidity to the protein loops with the amino acid side chains forming gates to the enzyme active site. Application of the protein dynamical network algorithms showed that substantial reorganization of the signal propagation pathways of intersubunit communication in the dimer occurred upon allosteric NAA binding to the remote site. The modeling approaches provide an explanation to the observed decrease of the reaction rate of NAA hydrolysis by hAsp at high substrate concentrations.

HITS-CLIP yields genome-wide insights into brain alternative RNA processing

NASA Astrophysics Data System (ADS)

Licatalosi, Donny D.; Mele, Aldo; Fak, John J.; Ule, Jernej; Kayikci, Melis; Chi, Sung Wook; Clark, Tyson A.; Schweitzer, Anthony C.; Blume, John E.; Wang, Xuning; Darnell, Jennifer C.; Darnell, Robert B.

2008-11-01

Protein-RNA interactions have critical roles in all aspects of gene expression. However, applying biochemical methods to understand such interactions in living tissues has been challenging. Here we develop a genome-wide means of mapping protein-RNA binding sites in vivo, by high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP). HITS-CLIP analysis of the neuron-specific splicing factor Nova revealed extremely reproducible RNA-binding maps in multiple mouse brains. These maps provide genome-wide in vivo biochemical footprints confirming the previous prediction that the position of Nova binding determines the outcome of alternative splicing; moreover, they are sufficiently powerful to predict Nova action de novo. HITS-CLIP revealed a large number of Nova-RNA interactions in 3' untranslated regions, leading to the discovery that Nova regulates alternative polyadenylation in the brain. HITS-CLIP, therefore, provides a robust, unbiased means to identify functional protein-RNA interactions in vivo.

Hydropathic analysis and biological evaluation of stilbene derivatives as colchicine site microtubule inhibitors with anti-leukemic activity

PubMed Central

TRIPATHI, ASHUTOSH; DURRANT, DAVID; LEE, RAY M.; BARUCHELLO, RICCARDO; ROMAGNOLI, ROMEO; SIMONI, DANIELE; KELLOGG, GLEN E.

2009-01-01

The crucial role of the microtubule in the cell division has identified tubulin as a target for the development of therapeutics for cancer; in particular tubulin is a target for antineoplastic agents that act by interfering with the dynamic stability of microtubules. A molecular modeling study was carried out to accurately represent the complex structure and the binding mode of a new class of stilbene-based tubulin inhibitors that bind at the αβ-tubulin colchicine site. Computational docking along with HINT score analysis fitted these inhibitors into the colchicine site and revealed detailed structure-activity information useful for inhibitor design. Quantitative analysis of the results was in good agreement with the in vitro antiproliferative activity of these derivatives (ranging from 3 nM to 100 μM) such that calculated and measured free energies of binding correlate with an r2 of 0.89 (standard error ± 0.85 kcal mol−1). This correlation suggests that the activity of unknown compounds may be predicted. PMID:19912057

Dinitroanilines Bind α-Tubulin to Disrupt Microtubules

PubMed Central

Morrissette, Naomi S.; Mitra, Arpita; Sept, David; Sibley, L. David

2004-01-01

Protozoan parasites are remarkably sensitive to dinitroanilines such as oryzalin, which disrupt plant but not animal microtubules. To explore the basis of dinitroaniline action, we isolated 49 independent resistant Toxoplasma gondii lines after chemical mutagenesis. All 23 of the lines that we examined harbored single point mutations in α-tubulin. These point mutations were sufficient to confer resistance when transfected into wild-type parasites. Several mutations were in the M or N loops, which coordinate protofilament interactions in the microtubule, but most of the mutations were in the core of α-tubulin. Docking studies predict that oryzalin binds with an average affinity of 23 nM to a site located beneath the N loop of Toxoplasma α-tubulin. This binding site included residues that were mutated in several resistant lines. Moreover, parallel analysis of Bos taurus α-tubulin indicated that oryzalin did not interact with this site and had a significantly decreased, nonspecific affinity for vertebrate α-tubulin. We propose that the dinitroanilines act through a novel mechanism, by disrupting M-N loop contacts. These compounds also represent the first class of drugs that act on α-tubulin function. PMID:14742718

Structure and self-assembly of the calcium binding matrix protein of human metapneumovirus.

PubMed

Leyrat, Cedric; Renner, Max; Harlos, Karl; Huiskonen, Juha T; Grimes, Jonathan M

2014-01-07

The matrix protein (M) of paramyxoviruses plays a key role in determining virion morphology by directing viral assembly and budding. Here, we report the crystal structure of the human metapneumovirus M at 2.8 Å resolution in its native dimeric state. The structure reveals the presence of a high-affinity Ca²⁺ binding site. Molecular dynamics simulations (MDS) predict a secondary lower-affinity site that correlates well with data from fluorescence-based thermal shift assays. By combining small-angle X-ray scattering with MDS and ensemble analysis, we captured the structure and dynamics of M in solution. Our analysis reveals a large positively charged patch on the protein surface that is involved in membrane interaction. Structural analysis of DOPC-induced polymerization of M into helical filaments using electron microscopy leads to a model of M self-assembly. The conservation of the Ca²⁺ binding sites suggests a role for calcium in the replication and morphogenesis of pneumoviruses. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

An Augmented Pocketome: Detection and Analysis of Small-Molecule Binding Pockets in Proteins of Known 3D Structure.

PubMed

Bhagavat, Raghu; Sankar, Santhosh; Srinivasan, Narayanaswamy; Chandra, Nagasuma

2018-03-06

Protein-ligand interactions form the basis of most cellular events. Identifying ligand binding pockets in proteins will greatly facilitate rationalizing and predicting protein function. Ligand binding sites are unknown for many proteins of known three-dimensional (3D) structure, creating a gap in our understanding of protein structure-function relationships. To bridge this gap, we detect pockets in proteins of known 3D structures, using computational techniques. This augmented pocketome (PocketDB) consists of 249,096 pockets, which is about seven times larger than what is currently known. We deduce possible ligand associations for about 46% of the newly identified pockets. The augmented pocketome, when subjected to clustering based on similarities among pockets, yielded 2,161 site types, which are associated with 1,037 ligand types, together providing fold-site-type-ligand-type associations. The PocketDB resource facilitates a structure-based function annotation, delineation of the structural basis of ligand recognition, and provides functional clues for domains of unknown functions, allosteric proteins, and druggable pockets. Copyright © 2018 Elsevier Ltd. All rights reserved.

Local Geometry and Evolutionary Conservation of Protein Surfaces Reveal the Multiple Recognition Patches in Protein-Protein Interactions

PubMed Central

Laine, Elodie; Carbone, Alessandra

2015-01-01

Protein-protein interactions (PPIs) are essential to all biological processes and they represent increasingly important therapeutic targets. Here, we present a new method for accurately predicting protein-protein interfaces, understanding their properties, origins and binding to multiple partners. Contrary to machine learning approaches, our method combines in a rational and very straightforward way three sequence- and structure-based descriptors of protein residues: evolutionary conservation, physico-chemical properties and local geometry. The implemented strategy yields very precise predictions for a wide range of protein-protein interfaces and discriminates them from small-molecule binding sites. Beyond its predictive power, the approach permits to dissect interaction surfaces and unravel their complexity. We show how the analysis of the predicted patches can foster new strategies for PPIs modulation and interaction surface redesign. The approach is implemented in JET2, an automated tool based on the Joint Evolutionary Trees (JET) method for sequence-based protein interface prediction. JET2 is freely available at www.lcqb.upmc.fr/JET2. PMID:26690684

From benchmarking HITS-CLIP peak detection programs to a new method for identification of miRNA-binding sites from Ago2-CLIP data.

PubMed

Bottini, Silvia; Hamouda-Tekaya, Nedra; Tanasa, Bogdan; Zaragosi, Laure-Emmanuelle; Grandjean, Valerie; Repetto, Emanuela; Trabucchi, Michele

2017-05-19

Experimental evidence indicates that about 60% of miRNA-binding activity does not follow the canonical rule about the seed matching between miRNA and target mRNAs, but rather a non-canonical miRNA targeting activity outside the seed or with a seed-like motifs. Here, we propose a new unbiased method to identify canonical and non-canonical miRNA-binding sites from peaks identified by Ago2 Cross-Linked ImmunoPrecipitation associated to high-throughput sequencing (CLIP-seq). Since the quality of peaks is of pivotal importance for the final output of the proposed method, we provide a comprehensive benchmarking of four peak detection programs, namely CIMS, PIPE-CLIP, Piranha and Pyicoclip, on four publicly available Ago2-HITS-CLIP datasets and one unpublished in-house Ago2-dataset in stem cells. We measured the sensitivity, the specificity and the position accuracy toward miRNA binding sites identification, and the agreement with TargetScan. Secondly, we developed a new pipeline, called miRBShunter, to identify canonical and non-canonical miRNA-binding sites based on de novo motif identification from Ago2 peaks and prediction of miRNA::RNA heteroduplexes. miRBShunter was tested and experimentally validated on the in-house Ago2-dataset and on an Ago2-PAR-CLIP dataset in human stem cells. Overall, we provide guidelines to choose a suitable peak detection program and a new method for miRNA-target identification. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

From benchmarking HITS-CLIP peak detection programs to a new method for identification of miRNA-binding sites from Ago2-CLIP data

PubMed Central

Bottini, Silvia; Hamouda-Tekaya, Nedra; Tanasa, Bogdan; Zaragosi, Laure-Emmanuelle; Grandjean, Valerie; Repetto, Emanuela

2017-01-01

Abstract Experimental evidence indicates that about 60% of miRNA-binding activity does not follow the canonical rule about the seed matching between miRNA and target mRNAs, but rather a non-canonical miRNA targeting activity outside the seed or with a seed-like motifs. Here, we propose a new unbiased method to identify canonical and non-canonical miRNA-binding sites from peaks identified by Ago2 Cross-Linked ImmunoPrecipitation associated to high-throughput sequencing (CLIP-seq). Since the quality of peaks is of pivotal importance for the final output of the proposed method, we provide a comprehensive benchmarking of four peak detection programs, namely CIMS, PIPE-CLIP, Piranha and Pyicoclip, on four publicly available Ago2-HITS-CLIP datasets and one unpublished in-house Ago2-dataset in stem cells. We measured the sensitivity, the specificity and the position accuracy toward miRNA binding sites identification, and the agreement with TargetScan. Secondly, we developed a new pipeline, called miRBShunter, to identify canonical and non-canonical miRNA-binding sites based on de novo motif identification from Ago2 peaks and prediction of miRNA::RNA heteroduplexes. miRBShunter was tested and experimentally validated on the in-house Ago2-dataset and on an Ago2-PAR-CLIP dataset in human stem cells. Overall, we provide guidelines to choose a suitable peak detection program and a new method for miRNA-target identification. PMID:28108660

Electromobility Shift Assay Reveals Evidence in Favor of Allele-Specific Binding of RUNX1 to the 5' Hypersensitive Site 4-Locus Control Region.

PubMed

Dehghani, Hossein; Ghobakhloo, Sepideh; Neishabury, Maryam

2016-08-01

In our previous studies on the Iranian β-thalassemia (β-thal) patients, we identified an association between the severity of the β-thal phenotype and the polymorphic palindromic site at the 5' hypersensitive site 4-locus control region (5'HS4-LCR) of the β-globin gene cluster. Furthermore, a linkage disequilibrium was observed between this region and XmnI-HBG2 in the patient population. Based on this data, it was suggested that the well-recognized phenotype-ameliorating role assigned to positive XmnI could be associated with its linked elements in the LCR. To investigate the functional significance of polymorphisms at the 5'HS4-LCR, we studied its influence on binding of transcription factors. Web-based predictions of transcription factor binding revealed a binding site for runt-related transcription factor 1 (RUNX1), when the allele at the center of the palindrome (TGGGG(A/G)CCCCA) was A but not when it was G. Furthermore, electromobility shift assay (EMSA) presented evidence in support of allele-specific binding of RUNX1 to 5'HS4. Considering that RUNX1 is a well-known regulator of hematopoiesis, these preliminary data suggest the importance of further studies to confirm this interaction and consequently investigate its functional and phenotypical relevance. These studies could help us to understand the molecular mechanism behind the phenotype modifying role of the 5'HS4-LCR polymorphic palindromic region (rs16912979), which has been observed in previous studies.

SOS response in bacteria: Inhibitory activity of lichen secondary metabolites against Escherichia coli RecA protein.

PubMed

Bellio, Pierangelo; Di Pietro, Letizia; Mancini, Alisia; Piovano, Marisa; Nicoletti, Marcello; Brisdelli, Fabrizia; Tondi, Donatella; Cendron, Laura; Franceschini, Nicola; Amicosante, Gianfranco; Perilli, Mariagrazia; Celenza, Giuseppe

2017-06-15

RecA is a bacterial multifunctional protein essential to genetic recombination, error-prone replicative bypass of DNA damages and regulation of SOS response. The activation of bacterial SOS response is directly related to the development of intrinsic and/or acquired resistance to antimicrobials. Although recent studies directed towards RecA inactivation via ATP binding inhibition described a variety of micromolar affinity ligands, inhibitors of the DNA binding site are still unknown. Twenty-seven secondary metabolites classified as anthraquinones, depsides, depsidones, dibenzofurans, diphenyl-butenolides, paraconic acids, pseudo-depsidones, triterpenes and xanthones, were investigated for their ability to inhibit RecA from Escherichia coli. They were isolated in various Chilean regions from 14 families and 19 genera of lichens. The ATP hydrolytic activity of RecA was quantified detecting the generation of free phosphate in solution. The percentage of inhibition was calculated fixing at 100µM the concentration of the compounds. Deeper investigations were reserved to those compounds showing an inhibition higher than 80%. To clarify the mechanism of inhibition, the semi-log plot of the percentage of inhibition vs. ATP and vs. ssDNA, was evaluated. Only nine compounds showed a percentage of RecA inhibition higher than 80% (divaricatic, perlatolic, alpha-collatolic, lobaric, lichesterinic, protolichesterinic, epiphorellic acids, sphaerophorin and tumidulin). The half-inhibitory concentrations (IC 50 ) calculated for these compounds were ranging from 14.2µM for protolichesterinic acid to 42.6µM for sphaerophorin. Investigations on the mechanism of inhibition showed that all compounds behaved as uncompetitive inhibitors for ATP binding site, with the exception of epiphorellic acid which clearly acted as non-competitive inhibitor of the ATP site. Further investigations demonstrated that epiphorellic acid competitively binds the ssDNA binding site. Kinetic data were confirmed by molecular modelling binding predictions which shows that epiphorellic acid is expected to bind the ssDNA site into the L2 loop of RecA protein. In this paper the first RecA ssDNA binding site ligand is described. Our study sets epiphorellic acid as a promising hit for the development of more effective RecA inhibitors. In our drug discovery approach, natural products in general and lichen in particular, represent a successful source of active ligands and structural diversity. Copyright © 2017 Elsevier GmbH. All rights reserved.

Emerging Computational Methods for the Rational Discovery of Allosteric Drugs

PubMed Central

2016-01-01

Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages. PMID:27074285

Emerging Computational Methods for the Rational Discovery of Allosteric Drugs.

PubMed

Wagner, Jeffrey R; Lee, Christopher T; Durrant, Jacob D; Malmstrom, Robert D; Feher, Victoria A; Amaro, Rommie E

2016-06-08

Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages.

Bioinformatic prediction of gene functions regulated by quorum sensing in the bioleaching bacterium Acidithiobacillus ferrooxidans.

PubMed

Banderas, Alvaro; Guiliani, Nicolas

2013-08-16

The biomining bacterium Acidithiobacillus ferrooxidans oxidizes sulfide ores and promotes metal solubilization. The efficiency of this process depends on the attachment of cells to surfaces, a process regulated by quorum sensing (QS) cell-to-cell signalling in many Gram-negative bacteria. At. ferrooxidans has a functional QS system and the presence of AHLs enhances its attachment to pyrite. However, direct targets of the QS transcription factor AfeR remain unknown. In this study, a bioinformatic approach was used to infer possible AfeR direct targets based on the particular palindromic features of the AfeR binding site. A set of Hidden Markov Models designed to maintain palindromic regions and vary non-palindromic regions was used to screen for putative binding sites. By annotating the context of each predicted binding site (PBS), we classified them according to their positional coherence relative to other putative genomic structures such as start codons, RNA polymerase promoter elements and intergenic regions. We further used the Multiple EM for Motif Elicitation algorithm (MEME) to further filter out low homology PBSs. In summary, 75 target-genes were identified, 34 of which have a higher confidence level. Among the identified genes, we found afeR itself, zwf, genes encoding glycosyltransferase activities, metallo-beta lactamases, and active transport-related proteins. Glycosyltransferases and Zwf (Glucose 6-phosphate-1-dehydrogenase) might be directly involved in polysaccharide biosynthesis and attachment to minerals by At. ferrooxidans cells during the bioleaching process.

Identification and positional distribution analysis of transcription factor binding sites for genes from the wheat fl-cDNA sequences.

PubMed

Chen, Zhen-Yong; Guo, Xiao-Jiang; Chen, Zhong-Xu; Chen, Wei-Ying; Wang, Ji-Rui

2017-06-01

The binding sites of transcription factors (TFs) in upstream DNA regions are called transcription factor binding sites (TFBSs). TFBSs are important elements for regulating gene expression. To date, there have been few studies on the profiles of TFBSs in plants. In total, 4,873 sequences with 5' upstream regions from 8530 wheat fl-cDNA sequences were used to predict TFBSs. We found 4572 TFBSs for the MADS TF family, which was twice as many as for bHLH (1951), B3 (1951), HB superfamily (1914), ERF (1820), and AP2/ERF (1725) TFs, and was approximately four times higher than the remaining TFBS types. The percentage of TFBSs and TF members showed a distinct distribution in different tissues. Overall, the distribution of TFBSs in the upstream regions of wheat fl-cDNA sequences had significant difference. Meanwhile, high frequencies of some types of TFBSs were found in specific regions in the upstream sequences. Both TFs and fl-cDNA with TFBSs predicted in the same tissues exhibited specific distribution preferences for regulating gene expression. The tissue-specific analysis of TFs and fl-cDNA with TFBSs provides useful information for functional research, and can be used to identify relationships between tissue-specific TFs and fl-cDNA with TFBSs. Moreover, the positional distribution of TFBSs indicates that some types of wheat TFBS have different positional distribution preferences in the upstream regions of genes.

Bioinformatic Prediction of Gene Functions Regulated by Quorum Sensing in the Bioleaching Bacterium Acidithiobacillus ferrooxidans

PubMed Central

Banderas, Alvaro; Guiliani, Nicolas

2013-01-01

The biomining bacterium Acidithiobacillus ferrooxidans oxidizes sulfide ores and promotes metal solubilization. The efficiency of this process depends on the attachment of cells to surfaces, a process regulated by quorum sensing (QS) cell-to-cell signalling in many Gram-negative bacteria. At. ferrooxidans has a functional QS system and the presence of AHLs enhances its attachment to pyrite. However, direct targets of the QS transcription factor AfeR remain unknown. In this study, a bioinformatic approach was used to infer possible AfeR direct targets based on the particular palindromic features of the AfeR binding site. A set of Hidden Markov Models designed to maintain palindromic regions and vary non-palindromic regions was used to screen for putative binding sites. By annotating the context of each predicted binding site (PBS), we classified them according to their positional coherence relative to other putative genomic structures such as start codons, RNA polymerase promoter elements and intergenic regions. We further used the Multiple EM for Motif Elicitation algorithm (MEME) to further filter out low homology PBSs. In summary, 75 target-genes were identified, 34 of which have a higher confidence level. Among the identified genes, we found afeR itself, zwf, genes encoding glycosyltransferase activities, metallo-beta lactamases, and active transport-related proteins. Glycosyltransferases and Zwf (Glucose 6-phosphate-1-dehydrogenase) might be directly involved in polysaccharide biosynthesis and attachment to minerals by At. ferrooxidans cells during the bioleaching process. PMID:23959118

Major versus minor groove DNA binding of a bisarginylporphyrin hybrid molecule: A molecular mechanics investigation

NASA Astrophysics Data System (ADS)

Gresh, Nohad; Perrée-fauvet, Martine

1999-03-01

On the basis of theoretical computations, we have recently synthesised [Perrée-Fauvet, M. and Gresh, N., Tetrahedron Lett., 36 (1995) 4227] a bisarginyl conjugate of a tricationic porphyrin (BAP), designed to target, in the major groove of DNA, the d(GGC GCC)2 sequence which is part of the primary binding site of the HIV-1 retrovirus site [Wain-Hobson, S. et al., Cell, 40 (1985) 9]. In the theoretical model, the chromophore intercalates at the central d(CpG)2 step and each of the arginyl arms targets O6/N7belonging to guanine bases flanking the intercalation site. Recent IR and UV-visible spectroscopic studies have confirmed the essential features of these theoretical predictions [Mohammadi, S. et al., Biochemistry, 37 (1998) 6165]. In the present study, we compare the energies of competing intercalation modes of BAP to several double-stranded oligonucleotides, according to whether one, two or three N- methylpyridinium rings project into the major groove. Correspondingly, three minor groove binding modes were considered, the arginyl arms now targeting N3, O2 sites belonging to the purine or pyrimidine bases flanking the intercalation site. This investigation has shown that: (i) in both the major and minor grooves, the best-bound complexes have the three N-methylpyridinium rings in the groove opposite to that of the phenyl group bearing the arginyl arms; (ii) major groove binding is preferred over minor groove binding by a significant energy (29 kcal/mol); and (iii) the best-bound sequence in the major groove is d(GGC GCC)2 with two successive guanines upstream from the intercalation. On the other hand, due to the flexibility of the arginyl arms, other GC-rich sequences have close binding energies, two of them being less stable than it by less than 8 kcal/mol. These results serve as the basis for the design of derivatives of BAP with enhanced sequence selectivities in the major groove.

Gamma-aminobutyric acid-modulated benzodiazepine binding sites in bacteria

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

Lummis, S.C.R.; Johnston, G.A.R.; Nicoletti, G.

1991-01-01

Benzodiazepine binding sites, which were once considered to exist only in higher vertebrates, are here demonstrated in the bacteria E. coli. The bacterial ({sup 3}H)diazepam binding sites are modulated by GABA; the modulation is dose dependent and is reduced at high concentrations. The most potent competitors of E.Coli ({sup 3}H)diazepam binding are those that are active in displacing ({sup 3}H)benzodiazepines from vertebrate peripheral benzodiazepine binding sites. These vertebrate sites are not modulated by GABA, in contrast to vertebrate neuronal benzodiazepine binding sites. The E.coli benzodiazepine binding sites therefore differ from both classes of vertebrate benzodiazepine binding sites; however the ligandmore » spectrum and GABA-modulatory properties of the E.coli sites are similar to those found in insects. This intermediate type of receptor in lower species suggests a precursor for at least one class of vertebrate benzodiazepine binding sites may have existed.« less

Mapping Polymerization and Allostery of Hemoglobin S Using Point Mutations

PubMed Central

Weinkam, Patrick; Sali, Andrej

2014-01-01

Hemoglobin is a complex system that undergoes conformational changes in response to oxygen, allosteric effectors, mutations, and environmental changes. Here, we study allostery and polymerization of hemoglobin and its variants by application of two previously described methods: (i) AllosMod for simulating allostery dynamics given two allosterically related input structures and (ii) a machine-learning method for dynamics- and structure-based prediction of the mutation impact on allostery (Weinkam et al. J. Mol. Biol. 2013), now applicable to systems with multiple coupled binding sites such as hemoglobin. First, we predict the relative stabilities of substates and microstates of hemoglobin, which are determined primarily by entropy within our model. Next, we predict the impact of 866 annotated mutations on hemoglobin’s oxygen binding equilibrium. We then discuss a subset of 30 mutations that occur in the presence of the sickle cell mutation and whose effects on polymerization have been measured. Seven of these HbS mutations occur in three predicted druggable binding pockets that might be exploited to directly inhibit polymerization; one of these binding pockets is not apparent in the crystal structure but only in structures generated by AllosMod. For the 30 mutations, we predict that mutation-induced conformational changes within a single tetramer tend not to significantly impact polymerization; instead, these mutations more likely impact polymerization by directly perturbing a polymerization interface. Finally, our analysis of allostery allows us to hypothesize why hemoglobin evolved to have multiple subunits and a persistent low frequency sickle cell mutation. PMID:23957820

Multiple binding sites for transcriptional repressors can produce regular bursting and enhance noise suppression

NASA Astrophysics Data System (ADS)

Lengyel, Iván M.; Morelli, Luis G.

2017-04-01

Cells may control fluctuations in protein levels by means of negative autoregulation, where transcription factors bind DNA sites to repress their own production. Theoretical studies have assumed a single binding site for the repressor, while in most species it is found that multiple binding sites are arranged in clusters. We study a stochastic description of negative autoregulation with multiple binding sites for the repressor. We find that increasing the number of binding sites induces regular bursting of gene products. By tuning the threshold for repression, we show that multiple binding sites can also suppress fluctuations. Our results highlight possible roles for the presence of multiple binding sites of negative autoregulators.

Characteristics of the isomeric flavonoids apigenin and genistein binding to hemoglobin by spectroscopic methods

NASA Astrophysics Data System (ADS)

Yuan, Jiang-Lan; Liu, Hui; Kang, Xu; Lv, Zhong; Zou, Guo-Lin

2008-11-01

Apigenin (Ap) and genistein (Ge), a couple of isomeric flavonoids with extensive bioactivities, are the most common dietary ingredients. They have been widely investigated due to their potential therapeutic actions for some diseases. In our work, binding characteristics of Ap and Ge to hemoglobin (Hb) were analyzed with fluorescence spectroscopy, circular dichroism (CD) and UV-vis absorption spectroscopy. The results indicated that Ap and Ge caused strong fluorescence quenching of Hb by static quenching mechanism, but their quenching efficiency and mechanisms were different. The binding site n suggested that there was a single binding site in Hb for Ap and Ge. The results of synchronous fluorescence showed that the microenvironment around Tyr residues of Hb had a slight trend of polarity decreasing, but the polarity around Trp residues increased by adding Ap. Results of CD indicated that the Ap and Ge did not changed the secondary structure of Hb. According to the theory of Förster resonance energy transfer, the binding distance r between Trp 37 and Ap/Ge was predicted to be 3.4 nm and 3.32 nm, respectively. The affinity of Ge toward Hb was higher than that of Ap.

MotifMark: Finding regulatory motifs in DNA sequences.

PubMed

Hassanzadeh, Hamid Reza; Kolhe, Pushkar; Isbell, Charles L; Wang, May D

2017-07-01

The interaction between proteins and DNA is a key driving force in a significant number of biological processes such as transcriptional regulation, repair, recombination, splicing, and DNA modification. The identification of DNA-binding sites and the specificity of target proteins in binding to these regions are two important steps in understanding the mechanisms of these biological activities. A number of high-throughput technologies have recently emerged that try to quantify the affinity between proteins and DNA motifs. Despite their success, these technologies have their own limitations and fall short in precise characterization of motifs, and as a result, require further downstream analysis to extract useful and interpretable information from a haystack of noisy and inaccurate data. Here we propose MotifMark, a new algorithm based on graph theory and machine learning, that can find binding sites on candidate probes and rank their specificity in regard to the underlying transcription factor. We developed a pipeline to analyze experimental data derived from compact universal protein binding microarrays and benchmarked it against two of the most accurate motif search methods. Our results indicate that MotifMark can be a viable alternative technique for prediction of motif from protein binding microarrays and possibly other related high-throughput techniques.

Partial Ionic Character beyond the Pauling Paradigm: Metal Nanoparticles

DOE PAGES

Duanmu, Kaining; Truhlar, Donald G.

2014-11-12

A canonical perspective on the chemical bond is the Pauling paradigm: a bond in a molecule containing only identical atoms has no ionic character. However, we show that homonuclear silver clusters have very uneven charge distributions (for example, the C 2v structure of Ag 4 has a larger dipole moment than formaldehyde or acetone), and we show how to predict the charge distribution from coordination numbers and Hirshfeld charges. The new charge model is validated against Kohn–Sham calculations of dipole moments with four approximations for the exchange–correlation functional. We report Kohn–Sham studies of the binding energies of CO on silvermore » monomer and silver clusters containing 2–18 atoms. We also find that an accurate charge model is essential for understanding the site dependence of binding. In particular we find that atoms with more positive charges tend to have higher binding energies, which can be used for guidance in catalyst modeling and design. Furthermore, the nonuniform charge distribution of silver clusters predisposes the site preference of binding of carbon monoxide, and we conclude that nonuniform charge distributions are an important property for understanding binding of metal nanoparticles in general.« less

Mapping the UDP-Glucuronic Acid Binding Site in UDP-Glucuronosyltransferase-1 A10 by Homology-based Modeling: Confirmation with Biochemical Evidence†

PubMed Central

Banerjee, Rajat; Pennington, Matthew W.; Garza, Amanda; Owens, Ida S.

2008-01-01

The UDP-glucuronosyltransferase (UGT) isozyme system is critical for protecting the body against endogenous and exogenous chemicals by linking glucuronic acid donated by UDP-glucuronic acid to a lipophilic acceptor substrate. UGTs convert metabolites, dietary constituents and environmental toxicants to highly excretable glucuronides. Because of difficulties associated with purifying endoplasmic reticulum-bound UGTs for structural studies, we carried out homology-based computer modeling to aid analysis. The search found structural homology in Escherichia coli UDP-galactose 4-epimerase. Consistent with predicted similarities involving the common UDP-moiety in substrates, UDP-glucose and UDP-hexanol amine caused competitive inhibition by Lineweaver-Burk plots. Among predicted binding sites N292, K314, K315 and K404 in UGT1A10, two informative sets of mutants K314R/Q/A/E /G and K404R/E had null activities or 2.7-fold higher/50% less activity, respectively. Scatchard analysis of binding data of affinity-ligand, 5-azido-uridine-[β-32P]-diphosphoglucuronic acid, to purified UGT1A10-His or UGT1A7-His revealed high and low affinity binding sites. 2-Nitro 5-thiocyanobenzoic acid-digested UGT1A10-His bound with radiolabeled affinity-ligand revealed an 11.3- and 14.3-kDa peptide associated with K314 and K404, respectively, in a discontinuous SDS-PAGE system. Similar treatment of 1A10His-K314A bound with the ligand lacked both peptides; 1A10-HisK404R- and 1A10-HisK404E showed 1.3-fold greater- and 50% less-label in the 14.3-kDa peptide, respectively, compared to 1A10-His without affecting the 11.3-kDa peptide. Scatchard analysis of binding data of affinity-ligand to 1A10His-K404R and -K404E showed a 6-fold reduction and a large increase in Kd, respectively. Our results indicate: K314 and K404 are required UDP-glcA binding sites in 1A10, that K404 controls activity and high affinity sites and that K314 and K404 are strictly conserved in 70 aligned UGTs, except for S321--equivalent to K314-- in UGT2B15 and 2B17 and I321 in the inactive UGT8, which suggests UGT2B15 and 2B17 contain suboptimal activity. Hence our data strongly support UDPglcA binding to K314 and K404 in UGT1A10. PMID:18570380

On the molecular interaction between lactoferrin and the dye Red HE-3B. A novel approach for docking a charged and highly flexible molecule to protein surfaces

NASA Astrophysics Data System (ADS)

Grasselli, Mariano; Cascone, Osvaldo; Anspach, F. Birger; Delfino, Jose M.

2002-12-01

Lactoferrin (Lf) is a non-heme, iron binding protein present in many physiological fluids of vertebrates where its main role is the microbicidal activity. It has been isolated by different methods, including dye-affinity chromatography. Red HE-3B is one of the most common triazinic dyes applied in protein purification, but scant knowledge is available on structural details and on the energetics of its interaction with proteins. In this work we present a computational approach useful for identifying possible binding sites for Red HE-3B in apo and holo forms of Lfs from human and bovine source. A new geometrical description of Red HE-3B is introduced which greatly simplifies the conformational analysis. This approach proved to be of particular advantage for addressing conformational ensembles of highly flexible molecules. Predictions from this analysis were correlated with experimentally observed dye-binding sites, as mapped by protection from proteolysis in Red HE-3B/Lf complexes. This method could bear relevance for the screening of possible dye-binding sites in proteins whose structure is known and as a potential tool for the design of engineered protein variants which could be purified by dye-affinity chromatography.

On the molecular interaction between lactoferrin and the dye Red HE-3b. A novel approach for docking a charged and highly flexible molecule to protein surfaces.

PubMed

Grasselli, Mariano; Cascone, Osvaldo; Birger Anspach, F; Delfino, Jose M

2002-12-01

Lactoferrin (Lf) is a non-heme, iron binding protein present in many physiological fluids of vertebrates where its main role is the microbicidal activity. It has been isolated by different methods, including dye-affinity chromatography. Red HE-3B is one of the most common triazinic dyes applied in protein purification, but scant knowledge is available on structural details and on the energetics of its interaction with proteins. In this work we present a computational approach useful for identifying possible binding sites for Red HE-3B in apo and holo forms of Lfs from human and bovine source. A new geometrical description of Red HE-3B is introduced which greatly simplifies the conformational analysis. This approach proved to be of particular advantage for addressing conformational ensembles of highly flexible molecules. Predictions from this analysis were correlated with experimentally observed dye-binding sites, as mapped by protection from proteolysis in Red HE-3B/Lf complexes. This method could bear relevance for the screening of possible dye-binding sites in proteins whose structure is known and as a potential tool for the design of engineered protein variants which could be purified by dye-affinity chromatography.

Thermodynamic analysis of water molecules at the surface of proteins and applications to binding site prediction and characterization.

PubMed

Beuming, Thijs; Che, Ye; Abel, Robert; Kim, Byungchan; Shanmugasundaram, Veerabahu; Sherman, Woody

2012-03-01

Water plays an essential role in determining the structure and function of all biological systems. Recent methodological advances allow for an accurate and efficient estimation of the thermodynamic properties of water molecules at the surface of proteins. In this work, we characterize these thermodynamic properties and relate them to various structural and functional characteristics of the protein. We find that high-energy hydration sites often exist near protein motifs typically characterized as hydrophilic, such as backbone amide groups. We also find that waters around alpha helices and beta sheets tend to be less stable than waters around loops. Furthermore, we find no significant correlation between the hydration site-free energy and the solvent accessible surface area of the site. In addition, we find that the distribution of high-energy hydration sites on the protein surface can be used to identify the location of binding sites and that binding sites of druggable targets tend to have a greater density of thermodynamically unstable hydration sites. Using this information, we characterize the FKBP12 protein and show good agreement between fragment screening hit rates from NMR spectroscopy and hydration site energetics. Finally, we show that water molecules observed in crystal structures are less stable on average than bulk water as a consequence of the high degree of spatial localization, thereby resulting in a significant loss in entropy. These findings should help to better understand the characteristics of waters at the surface of proteins and are expected to lead to insights that can guide structure-based drug design efforts. Copyright © 2011 Wiley Periodicals, Inc.

SpliceRover: Interpretable Convolutional Neural: Networks for Improved Splice Site Prediction.

PubMed

Zuallaert, Jasper; Godin, Fréderic; Kim, Mijung; Soete, Arne; Saeys, Yvan; De Neve, Wesley

2018-06-21

During the last decade, improvements in high-throughput sequencing have generated a wealth of genomic data. Functionally interpreting these sequences and finding the biological signals that are hallmarks of gene function and regulation is currently mostly done using automated genome annotation platforms, which mainly rely on integrated machine learning frameworks to identify different functional sites of interest, including splice sites. Splicing is an essential step in the gene regulation process, and the correct identification of splice sites is a major cornerstone in a genome annotation system. In this paper, we present SpliceRover, a predictive deep learning approach that outperforms the state-of-the-art in splice site prediction. SpliceRover uses convolutional neural networks (CNNs), which have been shown to obtain cutting edge performance on a wide variety of prediction tasks. We adapted this approach to deal with genomic sequence inputs, and show it consistently outperforms already existing approaches, with relative improvements in prediction effectiveness of up to 80.9% when measured in terms of false discovery rate. However, a major criticism of CNNs concerns their "black box" nature, as mechanisms to obtain insight into their reasoning processes are limited. To facilitate interpretability of the SpliceRover models, we introduce an approach to visualize the biologically relevant information learnt. We show that our visualization approach is able to recover features known to be important for splice site prediction (binding motifs around the splice site, presence of polypyrimidine tracts and branch points), as well as reveal new features (e.g., several types of exclusion patterns near splice sites). SpliceRover is available as a web service. The prediction tool and instructions can be found at http://bioit2.irc.ugent.be/splicerover/. Supplementary materials are available at Bioinformatics online.

Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints.

PubMed

Schwessinger, Ron; Suciu, Maria C; McGowan, Simon J; Telenius, Jelena; Taylor, Stephen; Higgs, Doug R; Hughes, Jim R

2017-10-01

In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k -mer-based analysis of DNase footprints to determine any k -mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome. © 2017 Schwessinger et al.; Published by Cold Spring Harbor Laboratory Press.

Engineering the Pseudomonas aeruginosa II lectin: designing mutants with changed affinity and specificity

NASA Astrophysics Data System (ADS)

Kříž, Zdeněk; Adam, Jan; Mrázková, Jana; Zotos, Petros; Chatzipavlou, Thomais; Wimmerová, Michaela; Koča, Jaroslav

2014-09-01

This article focuses on designing mutations of the PA-IIL lectin from Pseudomonas aeruginosa that lead to change in specificity. Following the previous results revealing the importance of the amino acid triad 22-23-24 (so-called specificity-binding loop), saturation in silico mutagenesis was performed, with the intent of finding mutations that increase the lectin's affinity and modify its specificity. For that purpose, a combination of docking, molecular dynamics and binding free energy calculation was used. The combination of methods revealed mutations that changed the performance of the wild-type lectin and its mutants to their preferred partners. The mutation at position 22 resulted in 85 % in inactivation of the binding site, and the mutation at 23 did not have strong effects thanks to the side chain being pointed away from the binding site. Molecular dynamics simulations followed by binding free energy calculation were performed on mutants with promising results from docking, and also at those where the amino acid at position 24 was replaced for bulkier or longer polar chain. The key mutants were also prepared in vitro and their binding properties determined by isothermal titration calorimetry. Combination of the used methods proved to be able to predict changes in the lectin performance and helped in explaining the data observed experimentally.

Thermodynamic Insights into Effects of Water Displacement and Rearrangement upon Ligand Modification using Molecular Dynamics Simulations.

PubMed

Wahl, Joel; Smiesko, Martin

2018-05-04

Computational methods, namely Molecular Dynamics Simulations (MD simulations) in combination with Inhomogeneous Fluid Solvation Theory (IFST) were used to retrospectively investigate various cases of ligand structure modifications that led to the displacement of binding site water molecules. Our findings are that the water displacement per se is energetically unfavorable in the discussed examples, and that it is merely the fine balance between change in protein-ligand interaction energy, ligand solvation free energies and binding site solvation free energies that determine if water displacement is favorable or not. We furthermore evaluated if we can reproduce experimental binding affinities by a computational approach combining changes in solvation free energies with changes in protein-ligand interaction energies and entropies. In two of the seven cases, this estimation led to large errors, implying that accurate predictions of relative binding free energies based on solvent thermodynamics is challenging. Still, MD simulations can provide insights into which water molecules can be targeted for displacement. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

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

Visel, Axel; Blow, Matthew J.; Li, Zirong

2009-02-01

A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. Wemore » tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.« less

Genome-wide identification of novel expression signatures reveal distinct patterns and prevalence of binding motifs for p53, nuclear factor-κB and other signal transcription factors in head and neck squamous cell carcinoma

PubMed Central

Yan, Bin; Yang, Xinping; Lee, Tin-Lap; Friedman, Jay; Tang, Jun; Van Waes, Carter; Chen, Zhong

2007-01-01

Background Differentially expressed gene profiles have previously been observed among pathologically defined cancers by microarray technologies, including head and neck squamous cell carcinomas (HNSCCs). However, the molecular expression signatures and transcriptional regulatory controls that underlie the heterogeneity in HNSCCs are not well defined. Results Genome-wide cDNA microarray profiling of ten HNSCC cell lines revealed novel gene expression signatures that distinguished cancer cell subsets associated with p53 status. Three major clusters of over-expressed genes (A to C) were defined through hierarchical clustering, Gene Ontology, and statistical modeling. The promoters of genes in these clusters exhibited different patterns and prevalence of transcription factor binding sites for p53, nuclear factor-κB (NF-κB), activator protein (AP)-1, signal transducer and activator of transcription (STAT)3 and early growth response (EGR)1, as compared with the frequency in vertebrate promoters. Cluster A genes involved in chromatin structure and function exhibited enrichment for p53 and decreased AP-1 binding sites, whereas clusters B and C, containing cytokine and antiapoptotic genes, exhibited a significant increase in prevalence of NF-κB binding sites. An increase in STAT3 and EGR1 binding sites was distributed among the over-expressed clusters. Novel regulatory modules containing p53 or NF-κB concomitant with other transcription factor binding motifs were identified, and experimental data supported the predicted transcriptional regulation and binding activity. Conclusion The transcription factors p53, NF-κB, and AP-1 may be important determinants of the heterogeneous pattern of gene expression, whereas STAT3 and EGR1 may broadly enhance gene expression in HNSCCs. Defining these novel gene signatures and regulatory mechanisms will be important for establishing new molecular classifications and subtyping, which in turn will promote development of targeted therapeutics for HNSCC. PMID:17498291

Probing electrostatic interactions and ligand binding in aspartyl-tRNA synthetase through site-directed mutagenesis and computer simulations.

PubMed

Thompson, Damien; Lazennec, Christine; Plateau, Pierre; Simonson, Thomas

2008-05-15

Faithful genetic code translation requires that each aminoacyl-tRNA synthetase recognise its cognate amino acid ligand specifically. Aspartyl-tRNA synthetase (AspRS) distinguishes between its negatively-charged Asp substrate and two competitors, neutral Asn and di-negative succinate, using a complex network of electrostatic interactions. Here, we used molecular dynamics simulations and site-directed mutagenesis experiments to probe these interactions further. We attempt to decrease the Asp/Asn binding free energy difference via single, double and triple mutations that reduce the net positive charge in the active site of Escherichia coli AspRS. Earlier, Glutamine 199 was changed to a negatively-charged glutamate, giving a computed reduction in Asp affinity in good agreement with experiment. Here, Lysine 198 was changed to a neutral leucine; then, Lys198 and Gln199 were mutated simultaneously. Both mutants are predicted to have reduced Asp binding and improved Asn binding, but the changes are insufficient to overcome the initial, high specificity of the native enzyme, which retains a preference for Asp. Probing the aminoacyl-adenylation reaction through pyrophosphate exchange experiments, we found no detectable activity for the mutant enzymes, indicating weaker Asp binding and/or poorer transition state stabilization. The simulations show that the mutations' effect is partly offset by proton uptake by a nearby histidine. Therefore, we performed additional simulations where the nearby Histidines 448 and 449 were mutated to neutral or negative residues: (Lys198Leu, His448Gln, His449Gln), and (Lys198Leu, His448Glu, His449Gln). This led to unexpected conformational changes and loss of active site preorganization, suggesting that the AspRS active site has a limited structural tolerance for electrostatic modifications. The data give insights into the complex electrostatic network in the AspRS active site and illustrate the difficulty in engineering charged-to-neutral changes of the preferred ligand. 2007 Wiley-Liss, Inc.

Advancing viral RNA structure prediction: measuring the thermodynamics of pyrimidine-rich internal loops.

PubMed

Phan, Andy; Mailey, Katherine; Saeki, Jessica; Gu, Xiaobo; Schroeder, Susan J

2017-05-01

Accurate thermodynamic parameters improve RNA structure predictions and thus accelerate understanding of RNA function and the identification of RNA drug binding sites. Many viral RNA structures, such as internal ribosome entry sites, have internal loops and bulges that are potential drug target sites. Current models used to predict internal loops are biased toward small, symmetric purine loops, and thus poorly predict asymmetric, pyrimidine-rich loops with >6 nucleotides (nt) that occur frequently in viral RNA. This article presents new thermodynamic data for 40 pyrimidine loops, many of which can form UU or protonated CC base pairs. Uracil and protonated cytosine base pairs stabilize asymmetric internal loops. Accurate prediction rules are presented that account for all thermodynamic measurements of RNA asymmetric internal loops. New loop initiation terms for loops with >6 nt are presented that do not follow previous assumptions that increasing asymmetry destabilizes loops. Since the last 2004 update, 126 new loops with asymmetry or sizes greater than 2 × 2 have been measured. These new measurements significantly deepen and diversify the thermodynamic database for RNA. These results will help better predict internal loops that are larger, pyrimidine-rich, and occur within viral structures such as internal ribosome entry sites. © 2017 Phan et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Naturally occurring deletions of hunchback binding sites in the even-skipped stripe 3+7 enhancer.

PubMed

Palsson, Arnar; Wesolowska, Natalia; Reynisdóttir, Sigrún; Ludwig, Michael Z; Kreitman, Martin

2014-01-01

Changes in regulatory DNA contribute to phenotypic differences within and between taxa. Comparative studies show that many transcription factor binding sites (TFBS) are conserved between species whereas functional studies reveal that some mutations segregating within species alter TFBS function. Consistently, in this analysis of 13 regulatory elements in Drosophila melanogaster populations, single base and insertion/deletion polymorphism are rare in characterized regulatory elements. Experimentally defined TFBS are nearly devoid of segregating mutations and, as has been shown before, are quite conserved. For instance 8 of 11 Hunchback binding sites in the stripe 3+7 enhancer of even-skipped are conserved between D. melanogaster and Drosophila virilis. Oddly, we found a 72 bp deletion that removes one of these binding sites (Hb8), segregating within D. melanogaster. Furthermore, a 45 bp deletion polymorphism in the spacer between the stripe 3+7 and stripe 2 enhancers, removes another predicted Hunchback site. These two deletions are separated by ∼250 bp, sit on distinct haplotypes, and segregate at appreciable frequency. The Hb8Δ is at 5 to 35% frequency in the new world, but also shows cosmopolitan distribution. There is depletion of sequence variation on the Hb8Δ-carrying haplotype. Quantitative genetic tests indicate that Hb8Δ affects developmental time, but not viability of offspring. The Eve expression pattern differs between inbred lines, but the stripe 3 and 7 boundaries seem unaffected by Hb8Δ. The data reveal segregating variation in regulatory elements, which may reflect evolutionary turnover of characterized TFBS due to drift or co-evolution.

Fatty acid modulated human serum albumin binding of the β-carboline alkaloids norharmane and harmane.

PubMed

Domonkos, Celesztina; Fitos, Ilona; Visy, Júlia; Zsila, Ferenc

2013-12-02

Harmane and norharmane are representative members of the large group of natural β-carboline alkaloids featured with diverse pharmacological activities. In blood, these agents are transported by human serum albumin (HSA) which has a profound impact on the pharmacokinetic and pharmacodynamic properties of many therapeutic drugs and xenobiotics. By combination of various spectroscopic methods, the present contribution is aimed to elucidate how nonesterified fatty acids (FAs), the primary endogenous ligands of HSA, affect the binding properties of harmane and norharmane. Analysis of induced circular dichroism (CD) and fluorescence spectroscopic data indicates the inclusion of the neutral form of both molecules into the binding pocket of subdomain IIIA, which hosts two FA binding sites, too. The induced CD and UV absorption spectra of harmane and norharmane exhibit peculiar changes upon addition of FAs, suggesting the formation of ternary complexes in which the lipid ligands significantly alter the binding mode of the alkaloids via cooperative allosteric mechanism. To our knowledge, it is the first instance of the demonstration of drug-FA cobinding at site IIIA. In line with these results, molecular docking calculations showed two distinct binding positions of norharmane within subdomain IIIA. The profound increase in the affinity constants of β-carbolines estimated in the presence of FAs predicts that the unbound, pharmacologically active serum fraction of these compounds strongly depends on the actual lipid binding profile of HSA.

A Biophysical Model of CRISPR/Cas9 Activity for Rational Design of Genome Editing and Gene Regulation

PubMed Central

Farasat, Iman; Salis, Howard M.

2016-01-01

The ability to precisely modify genomes and regulate specific genes will greatly accelerate several medical and engineering applications. The CRISPR/Cas9 (Type II) system binds and cuts DNA using guide RNAs, though the variables that control its on-target and off-target activity remain poorly characterized. Here, we develop and parameterize a system-wide biophysical model of Cas9-based genome editing and gene regulation to predict how changing guide RNA sequences, DNA superhelical densities, Cas9 and crRNA expression levels, organisms and growth conditions, and experimental conditions collectively control the dynamics of dCas9-based binding and Cas9-based cleavage at all DNA sites with both canonical and non-canonical PAMs. We combine statistical thermodynamics and kinetics to model Cas9:crRNA complex formation, diffusion, site selection, reversible R-loop formation, and cleavage, using large amounts of structural, biochemical, expression, and next-generation sequencing data to determine kinetic parameters and develop free energy models. Our results identify DNA supercoiling as a novel mechanism controlling Cas9 binding. Using the model, we predict Cas9 off-target binding frequencies across the lambdaphage and human genomes, and explain why Cas9’s off-target activity can be so high. With this improved understanding, we propose several rules for designing experiments for minimizing off-target activity. We also discuss the implications for engineering dCas9-based genetic circuits. PMID:26824432

Characterization of nicotine binding to the rat brain P/sub 2/ preparation: the identification of multiple binding sites which include specific up-regulatory site(s)

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

Sloan, J.W.

1984-01-01

These studies show that nicotine binds to the rat brain P/sub 2/ preparation by saturable and reversible processes. Multiple binding sites were revealed by the configuration of saturation, kinetic and Scatchard plots. A least squares best fit of Scatchard data using nonlinear curve fitting programs confirmed the presence of a very high affinity site, an up-regulatory site, a high affinity site and one or two low affinity sites. Stereospecificity was demonstrated for the up-regulatory site where (+)-nicotine was more effective and for the high affinity site where (-)-nicotine had a higher affinity. Drugs which selectively up-regulate nicotine binding site(s) havemore » been identified. Further, separate very high and high affinity sites were identified for (-)- and (+)-(/sup 3/H)nicotine, based on evidence that the site density for the (-)-isomer is 10 times greater than that for the (+)-isomer at these sites. Enhanced nicotine binding has been shown to be a statistically significant phenomenon which appears to be a consequence of drugs binding to specific site(s) which up-regulate binding at other site(s). Although Scatchard and Hill plots indicate positive cooperatively, up-regulation more adequately describes the function of these site(s). A separate up-regulatory site is suggested by the following: (1) Drugs vary markedly in their ability to up-regulate binding. (2) Both the affinity and the degree of up-regulation can be altered by structural changes in ligands. (3) Drugs with specificity for up-regulation have been identified. (4) Some drugs enhance binding in a dose-related manner. (5) Competition studies employing cold (-)- and (+)-nicotine against (-)- and (+)-(/sup 3/H)nicotine show that the isomers bind to separate sites which up-regulate binding at the (-)- and (+)-nicotine high affinity sites and in this regard (+)-nicotine is more specific and efficacious than (-)-nicotine.« less

Computational Identification of Diverse Mechanisms Underlying Transcription Factor-DNA Occupancy

PubMed Central

Cheng, Qiong; Kazemian, Majid; Pham, Hannah; Blatti, Charles; Celniker, Susan E.; Wolfe, Scot A.; Brodsky, Michael H.; Sinha, Saurabh

2013-01-01

ChIP-based genome-wide assays of transcription factor (TF) occupancy have emerged as a powerful, high-throughput method to understand transcriptional regulation, especially on a global scale. This has led to great interest in the underlying biochemical mechanisms that direct TF-DNA binding, with the ultimate goal of computationally predicting a TF's occupancy profile in any cellular condition. In this study, we examined the influence of various potential determinants of TF-DNA binding on a much larger scale than previously undertaken. We used a thermodynamics-based model of TF-DNA binding, called “STAP,” to analyze 45 TF-ChIP data sets from Drosophila embryonic development. We built a cross-validation framework that compares a baseline model, based on the ChIP'ed (“primary”) TF's motif, to more complex models where binding by secondary TFs is hypothesized to influence the primary TF's occupancy. Candidates interacting TFs were chosen based on RNA-SEQ expression data from the time point of the ChIP experiment. We found widespread evidence of both cooperative and antagonistic effects by secondary TFs, and explicitly quantified these effects. We were able to identify multiple classes of interactions, including (1) long-range interactions between primary and secondary motifs (separated by ≤150 bp), suggestive of indirect effects such as chromatin remodeling, (2) short-range interactions with specific inter-site spacing biases, suggestive of direct physical interactions, and (3) overlapping binding sites suggesting competitive binding. Furthermore, by factoring out the previously reported strong correlation between TF occupancy and DNA accessibility, we were able to categorize the effects into those that are likely to be mediated by the secondary TF's effect on local accessibility and those that utilize accessibility-independent mechanisms. Finally, we conducted in vitro pull-down assays to test model-based predictions of short-range cooperative interactions, and found that seven of the eight TF pairs tested physically interact and that some of these interactions mediate cooperative binding to DNA. PMID:23935523

Molecular mechanisms underlying deoxy‐ADP.Pi activation of pre‐powerstroke myosin

PubMed Central

Nowakowski, Sarah G.

2017-01-01

Abstract Myosin activation is a viable approach to treat systolic heart failure. We previously demonstrated that striated muscle myosin is a promiscuous ATPase that can use most nucleoside triphosphates as energy substrates for contraction. When 2‐deoxy ATP (dATP) is used, it acts as a myosin activator, enhancing cross‐bridge binding and cycling. In vivo, we have demonstrated that elevated dATP levels increase basal cardiac function and rescues function of infarcted rodent and pig hearts. Here we investigate the molecular mechanism underlying this physiological effect. We show with molecular dynamics simulations that the binding of dADP.Pi (dATP hydrolysis products) to myosin alters the structure and dynamics of the nucleotide binding pocket, myosin cleft conformation, and actin binding sites, which collectively yield a myosin conformation that we predict favors weak, electrostatic binding to actin. In vitro motility assays at high ionic strength were conducted to test this prediction and we found that dATP increased motility. These results highlight alterations to myosin that enhance cross‐bridge formation and reveal a potential mechanism that may underlie dATP‐induced improvements in cardiac function. PMID:28097776

Engineering Transition-Metal-Coated Tungsten Carbides for Efficient and Selective Electrochemical Reduction of CO2 to Methane.

PubMed

Wannakao, Sippakorn; Artrith, Nongnuch; Limtrakul, Jumras; Kolpak, Alexie M

2015-08-24

The design of catalysts for CO2 reduction is challenging because of the fundamental relationships between the binding energies of the reaction intermediates. Metal carbides have shown promise for transcending these relationships and enabling low-cost alternatives. Herein, we show that directional bonding arising from the mixed covalent/metallic character plays a critical role in governing the surface chemistry. This behavior can be described by consideration of individual d-band components. We use this model to predict efficient catalysts based on tungsten carbide with a sub-monolayer of iron adatoms. Our approach can be used to predict site-preference and binding-energy trends for complex catalyst surfaces. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

miRTar2GO: a novel rule-based model learning method for cell line specific microRNA target prediction that integrates Ago2 CLIP-Seq and validated microRNA-target interaction data.

PubMed

Ahadi, Alireza; Sablok, Gaurav; Hutvagner, Gyorgy

2017-04-07

MicroRNAs (miRNAs) are ∼19-22 nucleotides (nt) long regulatory RNAs that regulate gene expression by recognizing and binding to complementary sequences on mRNAs. The key step in revealing the function of a miRNA, is the identification of miRNA target genes. Recent biochemical advances including PAR-CLIP and HITS-CLIP allow for improved miRNA target predictions and are widely used to validate miRNA targets. Here, we present miRTar2GO, which is a model, trained on the common rules of miRNA-target interactions, Argonaute (Ago) CLIP-Seq data and experimentally validated miRNA target interactions. miRTar2GO is designed to predict miRNA target sites using more relaxed miRNA-target binding characteristics. More importantly, miRTar2GO allows for the prediction of cell-type specific miRNA targets. We have evaluated miRTar2GO against other widely used miRNA target prediction algorithms and demonstrated that miRTar2GO produced significantly higher F1 and G scores. Target predictions, binding specifications, results of the pathway analysis and gene ontology enrichment of miRNA targets are freely available at http://www.mirtar2go.org. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Regulation of the mouse Treacher Collins syndrome homolog (Tcof1) promoter through differential repression of constitutive expression.

PubMed

Shows, Kathryn H; Shiang, Rita

2008-11-01

Treacher Collins syndrome is an autosomal-dominant mandibulofacial dysostosis caused by haploinsufficiency of the TCOF1 gene product treacle. Mouse Tcof1 protein is approximately 61% identical and 71% similar to treacle, and heterozygous knockout of Tcof1 causes craniofacial malformation. Tcof1 expression is high in developing neural crest, but much lower in other tissues. To investigate this dual regulation, highly conserved regions upstream of TCOF1 homologs were tested through deletion and mutation reporter assays, and conserved predicted transcription factor binding sites were assessed through chromatin binding studies. Assays were performed in mouse P19 embryonic carcinoma cells and in HEK293 cells to determine differential activation in cell types at different stages of differentiation. Binding of Cebpb, Zfp161, and Sp1 transcription factors was specific to the Tcof1 regulatory region in P19 cells. The Zfp161 binding site demonstrated P19 cell-specific repression, while the Sp1/Sp3 candidate site demonstrated HEK293 cell-specific activation. Moreover, presence of c-myb and Zfp161 transcripts was specific to P19 cells. A minimal promoter fragment from -253 to +43 bp directs constitutive expression in both cell types, and dual regulation of Tcof1 appears to be through differential repression of this minimal promoter. The CpG island at the transcription start site remains unmethylated in P19 cells, 11.5 dpc mouse embryonic tissue, and adult mouse ear, which supports constitutive activation of the Tcof1 promoter.

Splicing factor SFRS1 recognizes a functionally diverse landscape of RNA transcripts.

PubMed

Sanford, Jeremy R; Wang, Xin; Mort, Matthew; Vanduyn, Natalia; Cooper, David N; Mooney, Sean D; Edenberg, Howard J; Liu, Yunlong

2009-03-01

Metazoan genes are encrypted with at least two superimposed codes: the genetic code to specify the primary structure of proteins and the splicing code to expand their proteomic output via alternative splicing. Here, we define the specificity of a central regulator of pre-mRNA splicing, the conserved, essential splicing factor SFRS1. Cross-linking immunoprecipitation and high-throughput sequencing (CLIP-seq) identified 23,632 binding sites for SFRS1 in the transcriptome of cultured human embryonic kidney cells. SFRS1 was found to engage many different classes of functionally distinct transcripts including mRNA, miRNA, snoRNAs, ncRNAs, and conserved intergenic transcripts of unknown function. The majority of these diverse transcripts share a purine-rich consensus motif corresponding to the canonical SFRS1 binding site. The consensus site was not only enriched in exons cross-linked to SFRS1 in vivo, but was also enriched in close proximity to splice sites. mRNAs encoding RNA processing factors were significantly overrepresented, suggesting that SFRS1 may broadly influence the post-transcriptional control of gene expression in vivo. Finally, a search for the SFRS1 consensus motif within the Human Gene Mutation Database identified 181 mutations in 82 different genes that disrupt predicted SFRS1 binding sites. This comprehensive analysis substantially expands the known roles of human SR proteins in the regulation of a diverse array of RNA transcripts.

Structural analysis of substrate-mimicking inhibitors in complex with Neisseria meningitidis 3-deoxy-d-arabino-heptulosonate 7-phosphate synthase - The importance of accommodating the active site water.

PubMed

Heyes, Logan C; Reichau, Sebastian; Cross, Penelope J; Jameson, Geoffrey B; Parker, Emily J

2014-12-01

3-Deoxy-d-arabino-heptulosonate 7-phosphate synthase (DAH7PS) catalyses the first committed step of the shikimate pathway, which produces the aromatic amino acids as well as many other aromatic metabolites. DAH7PS catalyses an aldol-like reaction between phosphoenolpyruvate and erythrose 4-phosphate. Three phosphoenolpyruvate mimics, (R)-phospholactate, (S)-phospholactate and vinyl phosphonate [(E)-2-methyl-3-phosphonoacrylate], were found to competitively inhibit DAH7PS from Neisseria meningitidis, which is the pathogen responsible for bacterial meningitis. The most potent inhibitor was the vinyl phosphonate with a Ki value of 3.9±0.4μM. We report for the first time crystal structures of these compounds bound in the active site of a DAH7PS enzyme which reveals that the inhibitors bind to the active site of the enzyme in binding modes that mimic those of the predicted oxocarbenium and tetrahedral intermediates of the enzyme-catalysed reaction. Furthermore, the inhibitors accommodate the binding of a key active site water molecule. Together, these observations provide strong evidence that this active site water participates directly in the DAH7PS reaction, enabling the facial selectivity of the enzyme-catalysed reaction sequence to be delineated. Copyright © 2014 Elsevier Inc. All rights reserved.

Structure-based design of novel naproxen derivatives targeting monomeric nucleoprotein of Influenza A virus

PubMed Central

Tarus, Bogdan; Bertrand, Hélène; Zedda, Gloria; Di Primo, Carmelo; Quideau, Stéphane; Slama-Schwok, Anny

2015-01-01

The nucleoprotein (NP) binds the viral RNA genome as oligomers assembled with the polymerase in a ribonucleoprotein complex required for transcription and replication of influenza A virus. Novel antiviral candidates targeting the nucleoprotein either induced higher order oligomers or reduced NP oligomerization by targeting the oligomerization loop and blocking its insertion into adjacent nucleoprotein subunit. In this study, we used a different structure-based approach to stabilize monomers of the nucleoprotein by drugs binding in its RNA-binding groove. We recently identified naproxen as a drug competing with RNA binding to NP with antiinflammatory and antiviral effects against influenza A virus. Here, we designed novel derivatives of naproxen by fragment extension for improved binding to NP. Molecular dynamics simulations suggested that among these derivatives, naproxen A and C0 were most promising. Their chemical synthesis is described. Both derivatives markedly stabilized NP monomer against thermal denaturation. Naproxen C0 bound tighter to NP than naproxen at a binding site predicted by MD simulations and shown by competition experiments using wt NP or single-point mutants as determined by surface plasmon resonance. MD simulations suggested that impeded oligomerization and stabilization of monomeric NP is likely to be achieved by drugs binding in the RNA grove and inducing close to their binding site conformational changes of key residues hosting the oligomerization loop as observed for the naproxen derivatives. Naproxen C0 is a potential antiviral candidate blocking influenza nucleoprotein function. PMID:25333630

Structure-based design of novel naproxen derivatives targeting monomeric nucleoprotein of Influenza A virus.

PubMed

Tarus, Bogdan; Bertrand, Hélène; Zedda, Gloria; Di Primo, Carmelo; Quideau, Stéphane; Slama-Schwok, Anny

2015-09-01

The nucleoprotein (NP) binds the viral RNA genome as oligomers assembled with the polymerase in a ribonucleoprotein complex required for transcription and replication of influenza A virus. Novel antiviral candidates targeting the nucleoprotein either induced higher order oligomers or reduced NP oligomerization by targeting the oligomerization loop and blocking its insertion into adjacent nucleoprotein subunit. In this study, we used a different structure-based approach to stabilize monomers of the nucleoprotein by drugs binding in its RNA-binding groove. We recently identified naproxen as a drug competing with RNA binding to NP with antiinflammatory and antiviral effects against influenza A virus. Here, we designed novel derivatives of naproxen by fragment extension for improved binding to NP. Molecular dynamics simulations suggested that among these derivatives, naproxen A and C0 were most promising. Their chemical synthesis is described. Both derivatives markedly stabilized NP monomer against thermal denaturation. Naproxen C0 bound tighter to NP than naproxen at a binding site predicted by MD simulations and shown by competition experiments using wt NP or single-point mutants as determined by surface plasmon resonance. MD simulations suggested that impeded oligomerization and stabilization of monomeric NP is likely to be achieved by drugs binding in the RNA grove and inducing close to their binding site conformational changes of key residues hosting the oligomerization loop as observed for the naproxen derivatives. Naproxen C0 is a potential antiviral candidate blocking influenza nucleoprotein function.

Insights from molecular modeling and dynamics simulation of pathogen resistance (R) protein from brinjal.

PubMed

Shrivastava, Dipty; Nain, Vikrant; Sahi, Shakti; Verma, Anju; Sharma, Priyanka; Sharma, Prakash Chand; Kumar, Polumetla Ananda

2011-01-22

Resistance (R) protein recognizes molecular signature of pathogen infection and activates downstream hypersensitive response signalling in plants. R protein works as a molecular switch for pathogen defence signalling and represent one of the largest plant gene family. Hence, understanding molecular structure and function of R proteins has been of paramount importance for plant biologists. The present study is aimed at predicting structure of R proteins signalling domains (CC-NBS) by creating a homology model, refining and optimising the model by molecular dynamics simulation and comparing ADP and ATP binding. Based on sequence similarity with proteins of known structures, CC-NBS domains were initially modelled using CED- 4 (cell death abnormality protein) and APAF-1 (apoptotic protease activating factor) as multiple templates. The final CC-NBS structural model was built and optimized by molecular dynamic simulation for 5 nanoseconds (ns). Docking of ADP and ATP at active site shows that both ligand bind specifically with same residues and with minor difference (1 Kcal/mol) in binding energy. Sharing of binding site by ADP and ATP and low difference in their binding site makes CC-NBS suitable for working as molecular switch. Furthermore, structural superimposition elucidate that CC-NBS and CARD (caspase recruitment domains) domain of CED-4 have low RMSD value of 0.9 A° Availability of 3D structural model for both CC and NBS domains will . help in getting deeper insight in these pathogen defence genes.

Key binding and susceptibility of NS3/4A serine protease inhibitors against hepatitis C virus.

PubMed

Meeprasert, Arthitaya; Hannongbua, Supot; Rungrotmongkol, Thanyada

2014-04-28

Hepatitis C virus (HCV) causes an infectious disease that manifests itself as liver inflammation, cirrhosis, and can lead to the development of liver cancer. Its NS3/4A serine protease is a potent target for drug design and development since it is responsible for cleavage of the scissile peptide bonds in the polyprotein important for the HCV life cycle. Herein, the ligand-target interactions and the binding free energy of the four current NS3/4A inhibitors (boceprevir, telaprevir, danoprevir, and BI201335) were investigated by all-atom molecular dynamics simulations with three different initial atomic velocities. The per-residue free energy decomposition suggests that the key residues involved in inhibitor binding were residues 41-43, 57, 81, 136-139, 155-159, and 168 in the NS3 domain. The van der Waals interactions yielded the main driving force for inhibitor binding at the protease active site for the cleavage reaction. In addition, the highest number of hydrogen bonds was formed at the reactive P1 site of the four studied inhibitors. Although the hydrogen bond patterns of these inhibitors were different, their P3 site was most likely to be recognized by the A157 backbone. Both molecular mechanic (MM)/Poisson-Boltzmann surface area and MM/generalized Born surface area approaches predicted the relative binding affinities of the four inhibitors in a somewhat similar trend to their experimentally derived biological activities.

Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data.

PubMed

Tsou, Ann-Ping; Sun, Yi-Ming; Liu, Chia-Lin; Huang, Hsien-Da; Horng, Jorng-Tzong; Tsai, Meng-Feng; Liu, Baw-Juine

2006-07-01

Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.

Deconvoluting AMP-activated protein kinase (AMPK) adenine nucleotide binding and sensing

PubMed Central

Gu, Xin; Yan, Yan; Novick, Scott J.; Kovach, Amanda; Goswami, Devrishi; Ke, Jiyuan; Tan, M. H. Eileen; Wang, Lili; Li, Xiaodan; de Waal, Parker W.; Webb, Martin R.; Griffin, Patrick R.; Xu, H. Eric

2017-01-01

AMP-activated protein kinase (AMPK) is a central cellular energy sensor that adapts metabolism and growth to the energy state of the cell. AMPK senses the ratio of adenine nucleotides (adenylate energy charge) by competitive binding of AMP, ADP, and ATP to three sites (CBS1, CBS3, and CBS4) in its γ-subunit. Because these three binding sites are functionally interconnected, it remains unclear how nucleotides bind to individual sites, which nucleotides occupy each site under physiological conditions, and how binding to one site affects binding to the other sites. Here, we comprehensively analyze nucleotide binding to wild-type and mutant AMPK protein complexes by quantitative competition assays and by hydrogen-deuterium exchange MS. We also demonstrate that NADPH, in addition to the known AMPK ligand NADH, directly and competitively binds AMPK at the AMP-sensing CBS3 site. Our findings reveal how AMP binding to one site affects the conformation and adenine nucleotide binding at the other two sites and establish CBS3, and not CBS1, as the high affinity exchangeable AMP/ADP/ATP-binding site. We further show that AMP binding at CBS4 increases AMP binding at CBS3 by 2 orders of magnitude and reverses the AMP/ATP preference of CBS3. Together, these results illustrate how the three CBS sites collaborate to enable highly sensitive detection of cellular energy states to maintain the tight ATP homeostastis required for cellular metabolism. PMID:28615457

Synthesis, hydrolysis rates, supercomputer modeling, and antibacterial activity of bicyclic tetrahydropyridazinones.

PubMed

Jungheim, L N; Boyd, D B; Indelicato, J M; Pasini, C E; Preston, D A; Alborn, W E

1991-05-01

Bicyclic tetrahydropyridazinones, such as 13, where X are strongly electron-withdrawing groups, were synthesized to investigate their antibacterial activity. These delta-lactams are homologues of bicyclic pyrazolidinones 15, which were the first non-beta-lactam containing compounds reported to bind to penicillin-binding proteins (PBPs). The delta-lactam compounds exhibit poor antibacterial activity despite having reactivity comparable to the gamma-lactams. Molecular modeling based on semiempirical molecular orbital calculations on a Cray X-MP supercomputer, predicted that the reason for the inactivity is steric bulk hindering high affinity of the compounds to PBPs, as well as high conformational flexibility of the tetrahydropyridazinone ring hampering effective alignment of the molecule in the active site. Subsequent PBP binding experiments confirmed that this class of compound does not bind to PBPs.

An Electrostatic Funnel in the GABA-Binding Pathway

PubMed Central

Lightstone, Felice C.

2016-01-01

The γ-aminobutyric acid type A receptor (GABAA-R) is a major inhibitory neuroreceptor that is activated by the binding of GABA. The structure of the GABAA-R is well characterized, and many of the binding site residues have been identified. However, most of these residues are obscured behind the C-loop that acts as a cover to the binding site. Thus, the mechanism by which the GABA molecule recognizes the binding site, and the pathway it takes to enter the binding site are both unclear. Through the completion and detailed analysis of 100 short, unbiased, independent molecular dynamics simulations, we have investigated this phenomenon of GABA entering the binding site. In each system, GABA was placed quasi-randomly near the binding site of a GABAA-R homology model, and atomistic simulations were carried out to observe the behavior of the GABA molecules. GABA fully entered the binding site in 19 of the 100 simulations. The pathway taken by these molecules was consistent and non-random; the GABA molecules approach the binding site from below, before passing up behind the C-loop and into the binding site. This binding pathway is driven by long-range electrostatic interactions, whereby the electrostatic field acts as a ‘funnel’ that sweeps the GABA molecules towards the binding site, at which point more specific atomic interactions take over. These findings define a nuanced mechanism whereby the GABAA-R uses the general zwitterionic features of the GABA molecule to identify a potential ligand some 2 nm away from the binding site. PMID:27119953

Modeling Complex Equilibria in ITC Experiments: Thermodynamic Parameters Estimation for a Three Binding Site Model

PubMed Central

Le, Vu H.; Buscaglia, Robert; Chaires, Jonathan B.; Lewis, Edwin A.

2013-01-01

Isothermal Titration Calorimetry, ITC, is a powerful technique that can be used to estimate a complete set of thermodynamic parameters (e.g. Keq (or ΔG), ΔH, ΔS, and n) for a ligand binding interaction described by a thermodynamic model. Thermodynamic models are constructed by combination of equilibrium constant, mass balance, and charge balance equations for the system under study. Commercial ITC instruments are supplied with software that includes a number of simple interaction models, for example one binding site, two binding sites, sequential sites, and n-independent binding sites. More complex models for example, three or more binding sites, one site with multiple binding mechanisms, linked equilibria, or equilibria involving macromolecular conformational selection through ligand binding need to be developed on a case by case basis by the ITC user. In this paper we provide an algorithm (and a link to our MATLAB program) for the non-linear regression analysis of a multiple binding site model with up to four overlapping binding equilibria. Error analysis demonstrates that fitting ITC data for multiple parameters (e.g. up to nine parameters in the three binding site model) yields thermodynamic parameters with acceptable accuracy. PMID:23262283

Discovery of novel indole derivatives as allosteric inhibitors of fructose-1,6-bisphosphatase.

PubMed

Bie, Jianbo; Liu, Shuainan; Li, Zhanmei; Mu, Yongzhao; Xu, Bailing; Shen, Zhufang

2015-01-27

A series of novel indole derivatives was designed and synthesized as inhibitors of fructose-1,6-bisphosphatase (FBPase). The most potent compound 14c was identified with an IC50 value of 0.10 μM by testing the inhibitory activity against recombinant human FBPase. The structure-activity relationships were investigated on the substitution at 4- and 5-position of the indole scaffold. The binding interactions of the title compounds at AMP binding site of FBPase were predicted using CDOCKER algorithm. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

In silico studies and fluorescence binding assays of potential anti-prion compounds reveal an important binding site for prion inhibition from PrP(C) to PrP(Sc).

PubMed

Pagadala, Nataraj S; Perez-Pineiro, Rolando; Wishart, David S; Tuszynski, Jack A

2015-02-16

To understand the pharmacophore properties of 2-aminothiazoles and design novel inhibitors against the prion protein, a highly predictive 3D quantitative structure-activity relationship (QSAR) has been developed by performing comparative molecular field analysis (CoMFA) and comparative similarity analysis (CoMSIA). Both CoMFA and CoMSIA maps reveal the presence of the oxymethyl groups in meta and para positions on the phenyl ring of compound 17 (N-[4-(3,4-dimethoxyphenyl)-1,3-thiazol-2-yl]quinolin-2-amine), is necessary for activity while electro-negative nitrogen of quinoline is highly favorable to enhance activity. The blind docking results for these compounds show that the compound with quinoline binds with higher affinity than isoquinoline and naphthalene groups. Out of 150 novel compounds retrieved using finger print analysis by pharmacophoric model predicted based on five test sets of compounds, five compounds with diverse scaffolds were selected for biological evaluation as possible PrP inhibitors. Molecular docking combined with fluorescence quenching studies show that these compounds bind to pocket-D of SHaPrP near Trp145. The new antiprion compounds 3 and 6, which bind with the interaction energies of -12.1 and -13.2 kcal/mol, respectively, show fluorescence quenching with binding constant (Kd) values of 15.5 and 44.14 μM, respectively. Further fluorescence binding assays with compound 5, which is similar to 2-aminothiazole as a positive control, also show that the molecule binds to the pocket-D with the binding constant (Kd) value of 84.7 μM. Finally, both molecular docking and a fluorescence binding assay of noscapine as a negative control reveals the same binding site on the surface of pocket-A near a rigid loop between β2 and α2 interacting with Arg164. This high level of correlation between molecular docking and fluorescence quenching studies confirm that these five compounds are likely to act as inhibitors for prion propagation while noscapine might act as a prion accelerator from PrP(C) to PrP(Sc). Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Comparing alchemical and physical pathway methods for computing the absolute binding free energy of charged ligands.

PubMed

Deng, Nanjie; Cui, Di; Zhang, Bin W; Xia, Junchao; Cruz, Jeffrey; Levy, Ronald

2018-06-13

Accurately predicting absolute binding free energies of protein-ligand complexes is important as a fundamental problem in both computational biophysics and pharmaceutical discovery. Calculating binding free energies for charged ligands is generally considered to be challenging because of the strong electrostatic interactions between the ligand and its environment in aqueous solution. In this work, we compare the performance of the potential of mean force (PMF) method and the double decoupling method (DDM) for computing absolute binding free energies for charged ligands. We first clarify an unresolved issue concerning the explicit use of the binding site volume to define the complexed state in DDM together with the use of harmonic restraints. We also provide an alternative derivation for the formula for absolute binding free energy using the PMF approach. We use these formulas to compute the binding free energy of charged ligands at an allosteric site of HIV-1 integrase, which has emerged in recent years as a promising target for developing antiviral therapy. As compared with the experimental results, the absolute binding free energies obtained by using the PMF approach show unsigned errors of 1.5-3.4 kcal mol-1, which are somewhat better than the results from DDM (unsigned errors of 1.6-4.3 kcal mol-1) using the same amount of CPU time. According to the DDM decomposition of the binding free energy, the ligand binding appears to be dominated by nonpolar interactions despite the presence of very large and favorable intermolecular ligand-receptor electrostatic interactions, which are almost completely cancelled out by the equally large free energy cost of desolvation of the charged moiety of the ligands in solution. We discuss the relative strengths of computing absolute binding free energies using the alchemical and physical pathway methods.

Statistical mechanical model of coupled transcription from multiple promoters due to transcription factor titration

PubMed Central

Rydenfelt, Mattias; Cox, Robert Sidney; Garcia, Hernan; Phillips, Rob

2014-01-01

Transcription factors (TFs) with regulatory action at multiple promoter targets is the rule rather than the exception, with examples ranging from the cAMP receptor protein (CRP) in E. coli that regulates hundreds of different genes simultaneously to situations involving multiple copies of the same gene, such as plasmids, retrotransposons, or highly replicated viral DNA. When the number of TFs heavily exceeds the number of binding sites, TF binding to each promoter can be regarded as independent. However, when the number of TF molecules is comparable to the number of binding sites, TF titration will result in correlation (“promoter entanglement”) between transcription of different genes. We develop a statistical mechanical model which takes the TF titration effect into account and use it to predict both the level of gene expression for a general set of promoters and the resulting correlation in transcription rates of different genes. Our results show that the TF titration effect could be important for understanding gene expression in many regulatory settings. PMID:24580252

Protonation of key acidic residues is critical for the K+-selectivity of the Na/K pump

PubMed Central

Yu, Haibo; Ratheal, Ian; Artigas, Pablo; Roux, Benoît

2011-01-01

The sodium-potassium (Na/K) pump is a P-type ATPase that generates Na+ and K+ concentration gradients across the cell membrane. For each ATP molecule, the pump extrudes three Na+ and imports two K+ by alternating between outward- and inward-facing conformations that preferentially bind K+ or Na+, respectively. Remarkably, the selective K+ and Na+ binding sites share several residues, and how the pump is able to achieve the selectivity required for the functional cycle is unclear. Here, free energy perturbation molecular dynamics (FEP/MD) simulations based on the crystal structures of the Na/K pump in a K+-loaded state (E2·Pi) reveal that protonation of the high-field acidic side-chains involved in the binding sites is critical to achieve the proper K+ selectivity. This prediction is tested with electrophysiological experiments showing that the selectivity of the E2P state for K+ over Na+ is affected by extracellular pH. PMID:21909093

Analysis of the interaction of calcitriol with the disulfide isomerase ERp57

NASA Astrophysics Data System (ADS)

Gaucci, Elisa; Raimondo, Domenico; Grillo, Caterina; Cervoni, Laura; Altieri, Fabio; Nittari, Giulio; Eufemi, Margherita; Chichiarelli, Silvia

2016-11-01

Calcitriol, the active form of vitamin D3, can regulate the gene expression through the binding to the nuclear receptor VDR, but it can also display nongenomic actions, acting through a membrane-associated receptor, which has been discovered as the disulfide isomerase ERp57. The aim of our research is to identify the binding sites for calcitriol in ERp57 and to analyze their interaction. We first studied the interaction through bioinformatics and fluorimetric analyses. Subsequently, we focused on two protein mutants containing the predicted interaction domains with calcitriol: abb’-ERp57, containing the first three domains, and a’-ERp57, the fourth domain only. To consolidate the achievements we used the calorimetric approach to the whole protein and its mutants. Our results allow us to hypothesize that the interaction with the a’ domain contributes to a greater extent than the other potential binding sites to the dissociation constant, calculated as a Kd of about 10-9 M.