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Sample records for multiple protein-protein interactions

  1. PPCM: Combing Multiple Classifiers to Improve Protein-Protein Interaction Prediction

    PubMed Central

    Yao, Jianzhuang; Guo, Hong; Yang, Xiaohan

    2015-01-01

    Determining protein-protein interaction (PPI) in biological systems is of considerable importance, and prediction of PPI has become a popular research area. Although different classifiers have been developed for PPI prediction, no single classifier seems to be able to predict PPI with high confidence. We postulated that by combining individual classifiers the accuracy of PPI prediction could be improved. We developed a method called protein-protein interaction prediction classifiers merger (PPCM), and this method combines output from two PPI prediction tools, GO2PPI and Phyloprof, using Random Forests algorithm. The performance of PPCM was tested by area under the curve (AUC) using an assembled Gold Standard database that contains both positive and negative PPI pairs. Our AUC test showed that PPCM significantly improved the PPI prediction accuracy over the corresponding individual classifiers. We found that additional classifiers incorporated into PPCM could lead to further improvement in the PPI prediction accuracy. Furthermore, cross species PPCM could achieve competitive and even better prediction accuracy compared to the single species PPCM. This study established a robust pipeline for PPI prediction by integrating multiple classifiers using Random Forests algorithm. This pipeline will be useful for predicting PPI in nonmodel species. PMID:26539460

  2. PPCM: Combing Multiple Classifiers to Improve Protein-Protein Interaction Prediction

    DOE PAGES

    Yao, Jianzhuang; Guo, Hong; Yang, Xiaohan

    2015-01-01

    Determining protein-protein interaction (PPI) in biological systems is of considerable importance, and prediction of PPI has become a popular research area. Although different classifiers have been developed for PPI prediction, no single classifier seems to be able to predict PPI with high confidence. We postulated that by combining individual classifiers the accuracy of PPI prediction could be improved. We developed a method called protein-protein interaction prediction classifiers merger (PPCM), and this method combines output from two PPI prediction tools, GO2PPI and Phyloprof, using Random Forests algorithm. The performance of PPCM was tested by area under the curve (AUC) using anmore » assembled Gold Standard database that contains both positive and negative PPI pairs. Our AUC test showed that PPCM significantly improved the PPI prediction accuracy over the corresponding individual classifiers. We found that additional classifiers incorporated into PPCM could lead to further improvement in the PPI prediction accuracy. Furthermore, cross species PPCM could achieve competitive and even better prediction accuracy compared to the single species PPCM. This study established a robust pipeline for PPI prediction by integrating multiple classifiers using Random Forests algorithm. This pipeline will be useful for predicting PPI in nonmodel species.« less

  3. N-way FRET microscopy of multiple protein-protein interactions in live cells.

    PubMed

    Hoppe, Adam D; Scott, Brandon L; Welliver, Timothy P; Straight, Samuel W; Swanson, Joel A

    2013-01-01

    Fluorescence Resonance Energy Transfer (FRET) microscopy has emerged as a powerful tool to visualize nanoscale protein-protein interactions while capturing their microscale organization and millisecond dynamics. Recently, FRET microscopy was extended to imaging of multiple donor-acceptor pairs, thereby enabling visualization of multiple biochemical events within a single living cell. These methods require numerous equations that must be defined on a case-by-case basis. Here, we present a universal multispectral microscopy method (N-Way FRET) to enable quantitative imaging for any number of interacting and non-interacting FRET pairs. This approach redefines linear unmixing to incorporate the excitation and emission couplings created by FRET, which cannot be accounted for in conventional linear unmixing. Experiments on a three-fluorophore system using blue, yellow and red fluorescent proteins validate the method in living cells. In addition, we propose a simple linear algebra scheme for error propagation from input data to estimate the uncertainty in the computed FRET images. We demonstrate the strength of this approach by monitoring the oligomerization of three FP-tagged HIV Gag proteins whose tight association in the viral capsid is readily observed. Replacement of one FP-Gag molecule with a lipid raft-targeted FP allowed direct observation of Gag oligomerization with no association between FP-Gag and raft-targeted FP. The N-Way FRET method provides a new toolbox for capturing multiple molecular processes with high spatial and temporal resolution in living cells.

  4. Global multiple protein-protein interaction network alignment by combining pairwise network alignments

    PubMed Central

    2015-01-01

    Background A wealth of protein interaction data has become available in recent years, creating an urgent need for powerful analysis techniques. In this context, the problem of finding biologically meaningful correspondences between different protein-protein interaction networks (PPIN) is of particular interest. The PPIN of a species can be compared with that of other species through the process of PPIN alignment. Such an alignment can provide insight into basic problems like species evolution and network component function determination, as well as translational problems such as target identification and elucidation of mechanisms of disease spread. Furthermore, multiple PPINs can be aligned simultaneously, expanding the analytical implications of the result. While there are several pairwise network alignment algorithms, few methods are capable of multiple network alignment. Results We propose SMAL, a MNA algorithm based on the philosophy of scaffold-based alignment. SMAL is capable of converting results from any global pairwise alignment algorithms into a MNA in linear time. Using this method, we have built multiple network alignments based on combining pairwise alignments from a number of publicly available (pairwise) network aligners. We tested SMAL using PPINs of eight species derived from the IntAct repository and employed a number of measures to evaluate performance. Additionally, as part of our experimental investigations, we compared the effectiveness of SMAL while aligning up to eight input PPINs, and examined the effect of scaffold network choice on the alignments. Conclusions A key advantage of SMAL lies in its ability to create MNAs through the use of pairwise network aligners for which native MNA implementations do not exist. Experiments indicate that the performance of SMAL was comparable to that of the native MNA implementation of established methods such as IsoRankN and SMETANA. However, in terms of computational time, SMAL was significantly faster

  5. Transient Protein-Protein Interaction of the SH3-Peptide Complex via Closely Located Multiple Binding Sites

    PubMed Central

    Hahn, Seungsoo; Kim, Dongsup

    2012-01-01

    Protein-protein interactions play an essential role in cellular processes. Certain proteins form stable complexes with their partner proteins, whereas others function by forming transient complexes. The conventional protein-protein interaction model describes an interaction between two proteins under the assumption that a protein binds to its partner protein through a single binding site. In this study, we improved the conventional interaction model by developing a Multiple-Site (MS) model in which a protein binds to its partner protein through closely located multiple binding sites on a surface of the partner protein by transiently docking at each binding site with individual binding free energies. To test this model, we used the protein-protein interaction mediated by Src homology 3 (SH3) domains. SH3 domains recognize their partners via a weak, transient interaction and are therefore promiscuous in nature. Because the MS model requires large amounts of data compared with the conventional interaction model, we used experimental data from the positionally addressable syntheses of peptides on cellulose membranes (SPOT-synthesis) technique. From the analysis of the experimental data, individual binding free energies for each binding site of peptides were extracted. A comparison of the individual binding free energies from the analysis with those from atomistic force fields gave a correlation coefficient of 0.66. Furthermore, application of the MS model to 10 SH3 domains lowers the prediction error by up to 9% compared with the conventional interaction model. This improvement in prediction originates from a more realistic description of complex formation than the conventional interaction model. The results suggested that, in many cases, SH3 domains increased the protein complex population through multiple binding sites of their partner proteins. Our study indicates that the consideration of general complex formation is important for the accurate description of

  6. Molecular modelling of protein-protein/protein-solvent interactions

    NASA Astrophysics Data System (ADS)

    Luchko, Tyler

    The inner workings of individual cells are based on intricate networks of protein-protein interactions. However, each of these individual protein interactions requires a complex physical interaction between proteins and their aqueous environment at the atomic scale. In this thesis, molecular dynamics simulations are used in three theoretical studies to gain insight at the atomic scale about protein hydration, protein structure and tubulin-tubulin (protein-protein) interactions, as found in microtubules. Also presented, in a fourth project, is a molecular model of solvation coupled with the Amber molecular modelling package, to facilitate further studies without the need of explicitly modelled water. Basic properties of a minimally solvated protein were calculated through an extended study of myoglobin hydration with explicit solvent, directly investigating water and protein polarization. Results indicate a close correlation between polarization of both water and protein and the onset of protein function. The methodology of explicit solvent molecular dynamics was further used to study tubulin and microtubules. Extensive conformational sampling of the carboxy-terminal tails of 8-tubulin was performed via replica exchange molecular dynamics, allowing the characterisation of the flexibility, secondary structure and binding domains of the C-terminal tails through statistical analysis methods. Mechanical properties of tubulin and microtubules were calculated with adaptive biasing force molecular dynamics. The function of the M-loop in microtubule stability was demonstrated in these simulations. The flexibility of this loop allowed constant contacts between the protofilaments to be maintained during simulations while the smooth deformation provided a spring-like restoring force. Additionally, calculating the free energy profile between the straight and bent tubulin configurations was used to test the proposed conformational change in tubulin, thought to cause microtubule

  7. Predicting Human Protein Subcellular Locations by the Ensemble of Multiple Predictors via Protein-Protein Interaction Network with Edge Clustering Coefficients

    PubMed Central

    Du, Pufeng; Wang, Lusheng

    2014-01-01

    One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods. PMID:24466278

  8. Identification of a novel contactin-associated transmembrane receptor with multiple domains implicated in protein-protein interactions.

    PubMed Central

    Peles, E; Nativ, M; Lustig, M; Grumet, M; Schilling, J; Martinez, R; Plowman, G D; Schlessinger, J

    1997-01-01

    Receptor protein tyrosine phosphatase beta (RPTPbeta) expressed on the surface of glial cells binds to the glycosylphosphatidylinositol (GPI)-anchored recognition molecule contactin on neuronal cells leading to neurite outgrowth. We describe the cloning of a novel contactin-associated transmembrane receptor (p190/Caspr) containing a mosaic of domains implicated in protein-protein interactions. The extracellular domain of Caspr contains a neurophilin/coagulation factor homology domain, a region related to fibrinogen beta/gamma, epidermal growth factor-like repeats, neurexin motifs as well as unique PGY repeats found in a molluscan adhesive protein. The cytoplasmic domain of Caspr contains a proline-rich sequence capable of binding to a subclass of SH3 domains of signaling molecules. Caspr and contactin exist as a complex in rat brain and are bound to each other by means of lateral (cis) interactions in the plasma membrane. We propose that Caspr may function as a signaling component of contactin, enabling recruitment and activation of intracellular signaling pathways in neurons. The binding of RPTPbeta to the contactin-Caspr complex could provide a mechanism for cell-cell communication between glial cells and neurons during development. PMID:9118959

  9. Protopia: a protein-protein interaction tool

    PubMed Central

    Real-Chicharro, Alejandro; Ruiz-Mostazo, Iván; Navas-Delgado, Ismael; Kerzazi, Amine; Chniber, Othmane; Sánchez-Jiménez, Francisca; Medina, Miguel Ángel; Aldana-Montes, José F

    2009-01-01

    Background Protein-protein interactions can be considered the basic skeleton for living organism self-organization and homeostasis. Impressive quantities of experimental data are being obtained and computational tools are essential to integrate and to organize this information. This paper presents Protopia, a biological tool that offers a way of searching for proteins and their interactions in different Protein Interaction Web Databases, as a part of a multidisciplinary initiative of our institution for the integration of biological data . Results The tool accesses the different Databases (at present, the free version of Transfac, DIP, Hprd, Int-Act and iHop), and results are expressed with biological protein names or databases codes and can be depicted as a vector or a matrix. They can be represented and handled interactively as an organic graph. Comparison among databases is carried out using the Uniprot codes annotated for each protein. Conclusion The tool locates and integrates the current information stored in the aforementioned databases, and redundancies among them are detected. Results are compatible with the most important network analysers, so that they can be compared and analysed by other world-wide known tools and platforms. The visualization possibilities help to attain this goal and they are especially interesting for handling multiple-step or complex networks. PMID:19828077

  10. PREFACE: Protein protein interactions: principles and predictions

    NASA Astrophysics Data System (ADS)

    Nussinov, Ruth; Tsai, Chung-Jung

    2005-06-01

    Proteins are the `workhorses' of the cell. Their roles span functions as diverse as being molecular machines and signalling. They carry out catalytic reactions, transport, form viral capsids, traverse membranes and form regulated channels, transmit information from DNA to RNA, making possible the synthesis of new proteins, and they are responsible for the degradation of unnecessary proteins and nucleic acids. They are the vehicles of the immune response and are responsible for viral entry into the cell. Given their importance, considerable effort has been centered on the prediction of protein function. A prime way to do this is through identification of binding partners. If the function of at least one of the components with which the protein interacts is known, that should let us assign its function(s) and the pathway(s) in which it plays a role. This holds since the vast majority of their chores in the living cell involve protein-protein interactions. Hence, through the intricate network of these interactions we can map cellular pathways, their interconnectivities and their dynamic regulation. Their identification is at the heart of functional genomics; their prediction is crucial for drug discovery. Knowledge of the pathway, its topology, length, and dynamics may provide useful information for forecasting side effects. The goal of predicting protein-protein interactions is daunting. Some associations are obligatory, others are continuously forming and dissociating. In principle, from the physical standpoint, any two proteins can interact, but under what conditions and at which strength? The principles of protein-protein interactions are general: the non-covalent interactions of two proteins are largely the outcome of the hydrophobic effect, which drives the interactions. In addition, hydrogen bonds and electrostatic interactions play important roles. Thus, many of the interactions observed in vitro are the outcome of experimental overexpression. Protein disorder

  11. Length, protein protein interactions, and complexity

    NASA Astrophysics Data System (ADS)

    Tan, Taison; Frenkel, Daan; Gupta, Vishal; Deem, Michael W.

    2005-05-01

    The evolutionary reason for the increase in gene length from archaea to prokaryotes to eukaryotes observed in large-scale genome sequencing efforts has been unclear. We propose here that the increasing complexity of protein-protein interactions has driven the selection of longer proteins, as they are more able to distinguish among a larger number of distinct interactions due to their greater average surface area. Annotated protein sequences available from the SWISS-PROT database were analyzed for 13 eukaryotes, eight bacteria, and two archaea species. The number of subcellular locations to which each protein is associated is used as a measure of the number of interactions to which a protein participates. Two databases of yeast protein-protein interactions were used as another measure of the number of interactions to which each S. cerevisiae protein participates. Protein length is shown to correlate with both number of subcellular locations to which a protein is associated and number of interactions as measured by yeast two-hybrid experiments. Protein length is also shown to correlate with the probability that the protein is encoded by an essential gene. Interestingly, average protein length and number of subcellular locations are not significantly different between all human proteins and protein targets of known, marketed drugs. Increased protein length appears to be a significant mechanism by which the increasing complexity of protein-protein interaction networks is accommodated within the natural evolution of species. Consideration of protein length may be a valuable tool in drug design, one that predicts different strategies for inhibiting interactions in aberrant and normal pathways.

  12. Protein-protein interactions in multienzyme megasynthetases.

    PubMed

    Weissman, Kira J; Müller, Rolf

    2008-04-14

    The multienzyme polyketide synthases (PKSs), nonribosomal polypeptide synthetases (NRPSs), and their hybrids are responsible for the construction in bacteria of numerous natural products of clinical value. These systems generate high structural complexity by using a simple biosynthetic logic--that of the assembly line. Each of the individual steps in building the metabolites is designated to an independently folded domain within gigantic polypeptides. The domains are clustered into functional modules, and the modules are strung out along the proteins in the order in which they act. Every metabolite results, therefore, from the successive action of up to 100 individual catalysts. Despite the conceptual simplicity of this division-of-labor organization, we are only beginning to decipher the molecular details of the numerous protein-protein interactions that support assembly-line biosynthesis, and which are critical to attempts to re-engineer these systems as a tool in drug discovery. This review aims to summarize the state of knowledge about several aspects of protein-protein interactions, including current architectural models for PKS and NRPS systems, the central role of carrier proteins, and the structural basis for intersubunit recognition.

  13. Cation-pi interactions in protein-protein interfaces.

    PubMed

    Crowley, Peter B; Golovin, Adel

    2005-05-01

    Arginine is an abundant residue in protein-protein interfaces. The importance of this residue relates to the versatility of its side chain in intermolecular interactions. Different classes of protein-protein interfaces were surveyed for cation-pi interactions. Approximately half of the protein complexes and one-third of the homodimers analyzed were found to contain at least one intermolecular cation-pi pair. Interactions between arginine and tyrosine were found to be the most abundant. The electrostatic interaction energy was calculated to be approximately 3 kcal/mol, on average. A distance-based search of guanidinium:aromatic interactions was also performed using the Macromolecular Structure Database (MSD). This search revealed that half of the guanidinium:aromatic pairs pack in a coplanar manner. Furthermore, it was found that the cationic group of the cation-pi pair is frequently involved in intermolecular hydrogen bonds. In this manner the arginine side chain can participate in multiple interactions, providing a mechanism for inter-protein specificity. Thus, the cation-pi interaction is established as an important contributor to protein-protein interfaces.

  14. Protein-protein interactions: methods for detection and analysis.

    PubMed Central

    Phizicky, E M; Fields, S

    1995-01-01

    The function and activity of a protein are often modulated by other proteins with which it interacts. This review is intended as a practical guide to the analysis of such protein-protein interactions. We discuss biochemical methods such as protein affinity chromatography, affinity blotting, coimmunoprecipitation, and cross-linking; molecular biological methods such as protein probing, the two-hybrid system, and phage display: and genetic methods such as the isolation of extragenic suppressors, synthetic mutants, and unlinked noncomplementing mutants. We next describe how binding affinities can be evaluated by techniques including protein affinity chromatography, sedimentation, gel filtration, fluorescence methods, solid-phase sampling of equilibrium solutions, and surface plasmon resonance. Finally, three examples of well-characterized domains involved in multiple protein-protein interactions are examined. The emphasis of the discussion is on variations in the approaches, concerns in evaluating the results, and advantages and disadvantages of the techniques. PMID:7708014

  15. Linkers in the structural biology of protein-protein interactions.

    PubMed

    Reddy Chichili, Vishnu Priyanka; Kumar, Veerendra; Sivaraman, J

    2013-02-01

    Linkers or spacers are short amino acid sequences created in nature to separate multiple domains in a single protein. Most of them are rigid and function to prohibit unwanted interactions between the discrete domains. However, Gly-rich linkers are flexible, connecting various domains in a single protein without interfering with the function of each domain. The advent of recombinant DNA technology made it possible to fuse two interacting partners with the introduction of artificial linkers. Often, independent proteins may not exist as stable or structured proteins until they interact with their binding partner, following which they gain stability and the essential structural elements. Gly-rich linkers have been proven useful for these types of unstable interactions, particularly where the interaction is weak and transient, by creating a covalent link between the proteins to form a stable protein-protein complex. Gly-rich linkers are also employed to form stable covalently linked dimers, and to connect two independent domains that create a ligand-binding site or recognition sequence. The lengths of linkers vary from 2 to 31 amino acids, optimized for each condition so that the linker does not impose any constraints on the conformation or interactions of the linked partners. Various structures of covalently linked protein complexes have been described using X-ray crystallography, nuclear magnetic resonance and cryo-electron microscopy techniques. In this review, we evaluate several structural studies where linkers have been used to improve protein quality, to produce stable protein-protein complexes, and to obtain protein dimers.

  16. Evolutionary reprograming of protein-protein interaction specificity.

    PubMed

    Akiva, Eyal; Babbitt, Patricia C

    2015-10-22

    Using mutation libraries and deep sequencing, Aakre et al. study the evolution of protein-protein interactions using a toxin-antitoxin model. The results indicate probable trajectories via "intermediate" proteins that are promiscuous, thus avoiding transitions via non-interactions. These results extend observations about other biological interactions and enzyme evolution, suggesting broadly general principles.

  17. Discovering interacting domains and motifs in protein-protein interactions.

    PubMed

    Hugo, Willy; Sung, Wing-Kin; Ng, See-Kiong

    2013-01-01

    Many important biological processes, such as the signaling pathways, require protein-protein interactions (PPIs) that are designed for fast response to stimuli. These interactions are usually transient, easily formed, and disrupted, yet specific. Many of these transient interactions involve the binding of a protein domain to a short stretch (3-10) of amino acid residues, which can be characterized by a sequence pattern, i.e., a short linear motif (SLiM). We call these interacting domains and motifs domain-SLiM interactions. Existing methods have focused on discovering SLiMs in the interacting proteins' sequence data. With the recent increase in protein structures, we have a new opportunity to detect SLiMs directly from the proteins' 3D structures instead of their linear sequences. In this chapter, we describe a computational method called SLiMDIet to directly detect SLiMs on domain interfaces extracted from 3D structures of PPIs. SLiMDIet comprises two steps: (1) interaction interfaces belonging to the same domain are extracted and grouped together using structural clustering and (2) the extracted interaction interfaces in each cluster are structurally aligned to extract the corresponding SLiM. Using SLiMDIet, de novo SLiMs interacting with protein domains can be computationally detected from structurally clustered domain-SLiM interactions for PFAM domains which have available 3D structures in the PDB database.

  18. Dissecting protein-protein interactions using directed evolution.

    PubMed

    Bonsor, Daniel A; Sundberg, Eric J

    2011-04-05

    Protein-protein interactions are essential for life. They are responsible for most cellular functions and when they go awry often lead to disease. Proteins are inherently complex. They are flexible macromolecules whose constituent amino acid components act in combinatorial and networked ways when they engage one another in binding interactions. It is just this complexity that allows them to conduct such a broad array of biological functions. Despite decades of intense study of the molecular basis of protein-protein interactions, key gaps in our understanding remain, hindering our ability to accurately predict the specificities and affinities of their interactions. Until recently, most protein-protein investigations have been probed experimentally at the single-amino acid level, making them, by definition, incapable of capturing the combinatorial nature of, and networked communications between, the numerous residues within and outside of the protein-protein interface. This aspect of protein-protein interactions, however, is emerging as a major driving force for protein affinity and specificity. Understanding a combinatorial process necessarily requires a combinatorial experimental tool. Much like the organisms in which they reside, proteins naturally evolve over time, through a combinatorial process of mutagenesis and selection, to functionally associate. Elucidating the process by which proteins have evolved may be one of the keys to deciphering the molecular rules that govern their interactions with one another. Directed evolution is a technique performed in the laboratory that mimics natural evolution on a tractable time scale that has been utilized widely to engineer proteins with novel capabilities, including altered binding properties. In this review, we discuss directed evolution as an emerging tool for dissecting protein-protein interactions.

  19. Direct Probing of Protein-Protein Interactions

    SciTech Connect

    Noy, A; Sulchek, T A; Friddle, R W

    2005-03-10

    This project aimed to establish feasibility of using experimental techniques based on direct measurements of interaction forces on the single molecule scale to characterize equilibrium interaction potentials between individual biological molecules. Such capability will impact several research areas, ranging from rapid interaction screening capabilities to providing verifiable inputs for computational models. It should be one of the enabling technologies for modern proteomics research. This study used a combination of Monte-Carlo simulations, theoretical considerations, and direct experimental measurements to investigate two model systems that represented typical experimental situations: force-induced melting of DNA rigidly attached to the tip, and force-induced unbinding of a protein-antibody pair connected to flexible tethers. Our results establish that for both systems researchers can use force spectroscopy measurements to extract reliable information about equilibrium interaction potentials. However, the approaches necessary to extract these potentials in each case--Jarzynski reconstruction and Dynamic Force Spectroscopy--are very different. We also show how the thermodynamics and kinetics of unbinding process dictates the choice between in each case.

  20. Protein-Protein Interaction Reagents | Office of Cancer Genomics

    Cancer.gov

    The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below. Emory_CTD^2_PPI_Reagents.xlsx Emory_CTD^2_PPI_Reagents.xlsx Contact: Haian Fu

  1. Protein-Protein Interactions (PPI) reagents: | Office of Cancer Genomics

    Cancer.gov

    The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below.

  2. Protein-Protein Interaction Reagents | Office of Cancer Genomics

    Cancer.gov

    The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below. Emory_CTD^2_PPI_Reagents.xlsx Contact: Haian Fu

  3. Computational Prediction of Protein-Protein Interactions of Human Tyrosinase

    PubMed Central

    Wang, Su-Fang; Oh, Sangho; Si, Yue-Xiu; Wang, Zhi-Jiang; Han, Hong-Yan; Lee, Jinhyuk; Qian, Guo-Ying

    2012-01-01

    The various studies on tyrosinase have recently gained the attention of researchers due to their potential application values and the biological functions. In this study, we predicted the 3D structure of human tyrosinase and simulated the protein-protein interactions between tyrosinase and three binding partners, four and half LIM domains 2 (FHL2), cytochrome b-245 alpha polypeptide (CYBA), and RNA-binding motif protein 9 (RBM9). Our interaction simulations showed significant binding energy scores of −595.3 kcal/mol for FHL2, −859.1 kcal/mol for CYBA, and −821.3 kcal/mol for RBM9. We also investigated the residues of each protein facing toward the predicted site of interaction with tyrosinase. Our computational predictions will be useful for elucidating the protein-protein interactions of tyrosinase and studying its binding mechanisms. PMID:22577521

  4. PPIM: A Protein-Protein Interaction Database for Maize1

    PubMed Central

    Wu, Aibo; Xu, Xin-Jian; Lu, Le; Liu, Jingdong; Cao, Yongwei; Chen, Luonan; Wu, Jun; Zhao, Xing-Ming

    2016-01-01

    Maize (Zea mays) is one of the most important crops worldwide. To understand the biological processes underlying various traits of the crop (e.g. yield and response to stress), a detailed protein-protein interaction (PPI) network is highly demanded. Unfortunately, there are very few such PPIs available in the literature. Therefore, in this work, we present the Protein-Protein Interaction Database for Maize (PPIM), which covers 2,762,560 interactions among 14,000 proteins. The PPIM contains not only accurately predicted PPIs but also those molecular interactions collected from the literature. The database is freely available at http://comp-sysbio.org/ppim with a user-friendly powerful interface. We believe that the PPIM resource can help biologists better understand the maize crop. PMID:26620522

  5. Noninvasive imaging of protein-protein interactions in living animals

    NASA Astrophysics Data System (ADS)

    Luker, Gary D.; Sharma, Vijay; Pica, Christina M.; Dahlheimer, Julie L.; Li, Wei; Ochesky, Joseph; Ryan, Christine E.; Piwnica-Worms, Helen; Piwnica-Worms, David

    2002-05-01

    Protein-protein interactions control transcription, cell division, and cell proliferation as well as mediate signal transduction, oncogenic transformation, and regulation of cell death. Although a variety of methods have been used to investigate protein interactions in vitro and in cultured cells, none can analyze these interactions in intact, living animals. To enable noninvasive molecular imaging of protein-protein interactions in vivo by positron-emission tomography and fluorescence imaging, we engineered a fusion reporter gene comprising a mutant herpes simplex virus 1 thymidine kinase and green fluorescent protein for readout of a tetracycline-inducible, two-hybrid system in vivo. By using micro-positron-emission tomography, interactions between p53 tumor suppressor and the large T antigen of simian virus 40 were visualized in tumor xenografts of HeLa cells stably transfected with the imaging constructs. Imaging protein-binding partners in vivo will enable functional proteomics in whole animals and provide a tool for screening compounds targeted to specific protein-protein interactions in living animals.

  6. Characterization of protein-protein interactions by isothermal titration calorimetry.

    PubMed

    Velazquez-Campoy, Adrian; Leavitt, Stephanie A; Freire, Ernesto

    2015-01-01

    The analysis of protein-protein interactions has attracted the attention of many researchers from both a fundamental point of view and a practical point of view. From a fundamental point of view, the development of an understanding of the signaling events triggered by the interaction of two or more proteins provides key information to elucidate the functioning of many cell processes. From a practical point of view, understanding protein-protein interactions at a quantitative level provides the foundation for the development of antagonists or agonists of those interactions. Isothermal Titration Calorimetry (ITC) is the only technique with the capability of measuring not only binding affinity but the enthalpic and entropic components that define affinity. Over the years, isothermal titration calorimeters have evolved in sensitivity and accuracy. Today, TA Instruments and MicroCal market instruments with the performance required to evaluate protein-protein interactions. In this methods paper, we describe general procedures to analyze heterodimeric (porcine pancreatic trypsin binding to soybean trypsin inhibitor) and homodimeric (bovine pancreatic α-chymotrypsin) protein associations by ITC.

  7. Evolution of protein-protein interaction networks in yeast.

    PubMed

    Schoenrock, Andrew; Burnside, Daniel; Moteshareie, Houman; Pitre, Sylvain; Hooshyar, Mohsen; Green, James R; Golshani, Ashkan; Dehne, Frank; Wong, Alex

    2017-01-01

    Interest in the evolution of protein-protein and genetic interaction networks has been rising in recent years, but the lack of large-scale high quality comparative datasets has acted as a barrier. Here, we carried out a comparative analysis of computationally predicted protein-protein interaction (PPI) networks from five closely related yeast species. We used the Protein-protein Interaction Prediction Engine (PIPE), which uses a database of known interactions to make sequence-based PPI predictions, to generate high quality predicted interactomes. Simulated proteomes and corresponding PPI networks were used to provide null expectations for the extent and nature of PPI network evolution. We found strong evidence for conservation of PPIs, with lower than expected levels of change in PPIs for about a quarter of the proteome. Furthermore, we found that changes in predicted PPI networks are poorly predicted by sequence divergence. Our analyses identified a number of functional classes experiencing fewer PPI changes than expected, suggestive of purifying selection on PPIs. Our results demonstrate the added benefit of considering predicted PPI networks when studying the evolution of closely related organisms.

  8. Hash subgraph pairwise kernel for protein-protein interaction extraction.

    PubMed

    Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng

    2012-01-01

    Extracting protein-protein interaction (PPI) from biomedical literature is an important task in biomedical text mining (BioTM). In this paper, we propose a hash subgraph pairwise (HSP) kernel-based approach for this task. The key to the novel kernel is to use the hierarchical hash labels to express the structural information of subgraphs in a linear time. We apply the graph kernel to compute dependency graphs representing the sentence structure for protein-protein interaction extraction task, which can efficiently make use of full graph structural information, and particularly capture the contiguous topological and label information ignored before. We evaluate the proposed approach on five publicly available PPI corpora. The experimental results show that our approach significantly outperforms all-path kernel approach on all five corpora and achieves state-of-the-art performance.

  9. Structural biology and drug discovery for protein-protein interactions.

    PubMed

    Jubb, Harry; Higueruelo, Alicia P; Winter, Anja; Blundell, Tom L

    2012-05-01

    Although targeting protein-protein interfaces of regulatory multiprotein complexes has become a significant focus in drug discovery, it continues to pose major challenges. Most interfaces would be classed as 'undruggable' by conventional analyses, as they tend to be large, flat and featureless. Over the past decade, encouragement has come from the discovery of hotspots that contribute much of the free energy of interaction, and this has led to the development of tethering methods that target small molecules to these sites, often inducing adaptive changes. Equally important has been the recognition that many protein-protein interactions involve a continuous epitope of one partner and a well-defined groove or series of specific small pockets. These observations have stimulated the development of stapled α-helical peptides and other proteomimetic approaches. They have also led to the realisation that fragments might gain low-affinity 'footholds' on some protein-protein interfaces, and that these fragments might be elaborated to useful modulators of the interactions.

  10. Geometric de-noising of protein-protein interaction networks.

    PubMed

    Kuchaiev, Oleksii; Rasajski, Marija; Higham, Desmond J; Przulj, Natasa

    2009-08-01

    Understanding complex networks of protein-protein interactions (PPIs) is one of the foremost challenges of the post-genomic era. Due to the recent advances in experimental bio-technology, including yeast-2-hybrid (Y2H), tandem affinity purification (TAP) and other high-throughput methods for protein-protein interaction (PPI) detection, huge amounts of PPI network data are becoming available. Of major concern, however, are the levels of noise and incompleteness. For example, for Y2H screens, it is thought that the false positive rate could be as high as 64%, and the false negative rate may range from 43% to 71%. TAP experiments are believed to have comparable levels of noise.We present a novel technique to assess the confidence levels of interactions in PPI networks obtained from experimental studies. We use it for predicting new interactions and thus for guiding future biological experiments. This technique is the first to utilize currently the best fitting network model for PPI networks, geometric graphs. Our approach achieves specificity of 85% and sensitivity of 90%. We use it to assign confidence scores to physical protein-protein interactions in the human PPI network downloaded from BioGRID. Using our approach, we predict 251 interactions in the human PPI network, a statistically significant fraction of which correspond to protein pairs sharing common GO terms. Moreover, we validate a statistically significant portion of our predicted interactions in the HPRD database and the newer release of BioGRID. The data and Matlab code implementing the methods are freely available from the web site: http://www.kuchaev.com/Denoising.

  11. An analysis pipeline for the inferenceof protein-protein interaction networks

    SciTech Connect

    Taylor, Ronald C.; Singhal, Mudita; Daly, Don S.; Gilmore, Jason; Cannon, Bill; Domico, Kelly; White, Amanda M.; Auberry, Deanna L; Auberry, Kenneth J; Hooker, Brian; Hurst, Gregory {Greg} B; McDermott, Jason; McDonald, W Hayes; Pelletier, Dale A; Schmoyer, Denise D; Wiley, Steven

    2009-09-01

    We present an integrated platform that is used for the reconstruction and analysis of protein-protein interaction networks inferred from Mass Spectrometry (MS) bait-prey experiment data. At the heart of this pipeline is the Software Environment for Biological Network Inference (SEBINI), an interactive environment for the deployment and testing of network inference algorithms that use high-throughput data. Among the many algorithms available in SEBINI is the Bayesian Estimator of Probabilities of Protein-Protein Associations (BEPro3) algorithm, which is used to infer interaction networks from such MS affinity isolation data. For integration, comparison and analysis of the inferred protein-protein interactions with interaction evidence obtained from multiple public sources, the pipeline connects to the Collective Analysis of Biological Interaction Networks (CABIN) software. Incorporating BEPro3 into SEBINI and automatically feeding the resulting inferred network into CABIN, we have created a structured workflow for protein-protein network inference and supplemental analysis from sets of MS bait-prey experiments.

  12. Potential disruption of protein-protein interactions by graphene oxide

    NASA Astrophysics Data System (ADS)

    Feng, Mei; Kang, Hongsuk; Yang, Zaixing; Luan, Binquan; Zhou, Ruhong

    2016-06-01

    Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions and eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.

  13. Protein-protein interactions as druggable targets: recent technological advances.

    PubMed

    Higueruelo, Alicia P; Jubb, Harry; Blundell, Tom L

    2013-10-01

    Classical target-based drug discovery, where large chemical libraries are screened using inhibitory assays for a single target, has struggled to find ligands that inhibit protein-protein interactions (PPI). Nevertheless, in the past decade there have been successes that have demonstrated that PPI can be useful drug targets, and the field is now evolving fast. This review focuses on the new approaches and concepts that are being developed to tackle these challenging targets: the use of fragment based methods to explore the chemical space, stapled peptides to regulate intracellular PPI, alternatives to competitive inhibition and the use of antibodies to enable small molecule discovery for these targets.

  14. An analysis pipeline for the inference of protein-protein interaction networks

    SciTech Connect

    Taylor, Ronald C.; Singhal, Mudita; Daly, Don S.; Gilmore, Jason M.; Cannon, William R.; Domico, Kelly O.; White, Amanda M.; Auberry, Deanna L.; Auberry, Kenneth J.; Hooker, Brian S.; Hurst, G. B.; McDermott, Jason E.; McDonald, W. H.; Pelletier, Dale A.; Schmoyer, Denise A.; Wiley, H. S.

    2009-12-01

    An analysis pipeline has been created for deployment of a novel algorithm, the Bayesian Estimator of Protein-Protein Association Probabilities (BEPro), for use in the reconstruction of protein-protein interaction networks. We have combined the Software Environment for BIological Network Inference (SEBINI), an interactive environment for the deployment and testing of network inference algorithms that use high-throughput data, and the Collective Analysis of Biological Interaction Networks (CABIN), software that allows integration and analysis of protein-protein interaction and gene-to-gene regulatory evidence obtained from multiple sources, to allow interactions computed by BEPro to be stored, visualized, and further analyzed. Incorporating BEPro into SEBINI and automatically feeding the resulting inferred network into CABIN, we have created a structured workflow for protein-protein network inference and supplemental analysis from sets of mass spectrometry bait-prey experiment data. SEBINI demo site: https://www.emsl.pnl.gov /SEBINI/ Contact: ronald.taylor@pnl.gov. BEPro is available at http://www.pnl.gov/statistics/BEPro3/index.htm. Contact: ds.daly@pnl.gov. CABIN is available at http://www.sysbio.org/dataresources/cabin.stm. Contact: mudita.singhal@pnl.gov.

  15. Finding protein-protein interaction patterns by contact map matching.

    PubMed

    Melo, R C; Ribeiro, C; Murray, C S; Veloso, C J M; da Silveira, C H; Neshich, G; Meira, W; Carceroni, R L; Santoro, M M

    2007-10-05

    We propose a novel method for defining patterns of contacts present in protein-protein complexes. A new use of the traditional contact maps (more frequently used for representation of the intra-chain contacts) is presented for analysis of inter-chain contacts. Using an algorithm based on image processing techniques, we can compare protein-protein interaction maps and also obtain a dissimilarity score between them. The same algorithm used to compare the maps can align the contacts of all the complexes and be helpful in the determination of a pattern of conserved interactions at the interfaces. We present an example for the application of this method by analyzing the pattern of interaction of bovine pancreatic trypsin inhibitors and trypsins, chymotrypsins, a thrombin, a matriptase, and a kallikrein - all classified as serine proteases. We found 20 contacts conserved in trypsins and chymotrypsins and 3 specific ones are present in all the serine protease complexes studied. The method was able to identify important contacts for the protein family studied and the results are in agreement with the literature.

  16. Protein-protein interaction network analysis of cirrhosis liver disease

    PubMed Central

    Safaei, Akram; Rezaei Tavirani, Mostafa; Arefi Oskouei, Afsaneh; Zamanian Azodi, Mona; Mohebbi, Seyed Reza; Nikzamir, Abdol Rahim

    2016-01-01

    Aim: Evaluation of biological characteristics of 13 identified proteins of patients with cirrhotic liver disease is the main aim of this research. Background: In clinical usage, liver biopsy remains the gold standard for diagnosis of hepatic fibrosis. Evaluation and confirmation of liver fibrosis stages and severity of chronic diseases require a precise and noninvasive biomarkers. Since the early detection of cirrhosis is a clinical problem, achieving a sensitive, specific and predictive novel method based on biomarkers is an important task. Methods: Essential analysis, such as gene ontology (GO) enrichment and protein-protein interactions (PPI) was undergone EXPASy, STRING Database and DAVID Bioinformatics Resources query. Results: Based on GO analysis, most of proteins are located in the endoplasmic reticulum lumen, intracellular organelle lumen, membrane-enclosed lumen, and extracellular region. The relevant molecular functions are actin binding, metal ion binding, cation binding and ion binding. Cell adhesion, biological adhesion, cellular amino acid derivative, metabolic process and homeostatic process are the related processes. Protein-protein interaction network analysis introduced five proteins (fibroblast growth factor receptor 4, tropomyosin 4, tropomyosin 2 (beta), lectin, Lectin galactoside-binding soluble 3 binding protein and apolipoprotein A-I) as hub and bottleneck proteins. Conclusion: Our result indicates that regulation of lipid metabolism and cell survival are important biological processes involved in cirrhosis disease. More investigation of above mentioned proteins will provide a better understanding of cirrhosis disease. PMID:27099671

  17. Evolvability of yeast protein-protein interaction interfaces.

    PubMed

    Talavera, David; Williams, Simon G; Norris, Matthew G S; Robertson, David L; Lovell, Simon C

    2012-06-22

    The functional importance of protein-protein interactions indicates that there should be strong evolutionary constraint on their interaction interfaces. However, binding interfaces are frequently affected by amino acid replacements. Change due to coevolution within interfaces can contribute to variability but is not ubiquitous. An alternative explanation for the ability of surfaces to accept replacements may be that many residues can be changed without affecting the interaction. Candidates for these types of residues are those that make interchain interaction only through the protein main chain, β-carbon, or associated hydrogen atoms. Since almost all residues have these atoms, we hypothesize that this subset of interface residues may be more easily substituted than those that make interactions through other atoms. We term such interactions "residue type independent." Investigating this hypothesis, we find that nearly a quarter of residues in protein interaction interfaces make exclusively interchain residue-type-independent contacts. These residues are less structurally constrained and less conserved than residues making residue-type-specific interactions. We propose that residue-type-independent interactions allow substitutions in binding interfaces while the specificity of binding is maintained.

  18. Single-Molecule Study of Protein-Protein Interaction Dynamics in a Cell Signaling System

    SciTech Connect

    Tan, Xin; Nalbant, Perihan; Toutchkine, Alexei; Hu, Dehong; Vorpagel, Erich R.; Hahn, Klaus M.; Lu, H PETER.

    2004-01-15

    We report a combined single-molecule fluorescence and molecular dynamics (MD) simulation study of protein-protein interactions in a GTP-binding intracellular signaling protein Cdc42 in complex with a downstream effector protein WASP. A 13- kDa WASP fragment which binds only the activated GTP-loaded Cdc42 was labeled with a novel solvatochromic dye and used to probe hydrophobic interactions significant to Cdc42/WASP recognition. Our single-molecule fluorescence measurements have shown conformational fluctuations of the protein complex and suggested multiple conformational states at a wide range of time scales might be involved in protein interaction dynamics. Single-molecule experiments have revealed the dynamic disorder or protein-protein interactions within the Cdc42/WASP complex, which may be important for regulating downstream signaling events.

  19. Protein-protein interactions in the synaptonemal complex.

    PubMed Central

    Tarsounas, M; Pearlman, R E; Gasser, P J; Park, M S; Moens, P B

    1997-01-01

    In mammalian systems, an approximately M(r) 30,000 Cor1 protein has been identified as a major component of the meiotic prophase chromosome cores, and a M(r) 125,000 Syn1 protein is present between homologue cores where they are synapsed and form the synaptonemal complex (SC). Immunolocalization of these proteins during meiosis suggests possible homo- and heterotypic interactions between the two as well as possible interactions with yet unrecognized proteins. We used the two-hybrid system in the yeast Saccharomyces cerevisiae to detect possible protein-protein associations. Segments of hamsters Cor1 and Syn1 proteins were tested in various combinations for homo- and heterotypic interactions. In the cause of Cor1, homotypic interactions involve regions capable of coiled-coil formation, observation confirmed by in vitro affinity coprecipitation experiments. The two-hybrid assay detects no interaction of Cor1 protein with central and C-terminal fragments of Syn1 protein and no homotypic interactions involving these fragments of Syn1. Hamster Cor1 and Syn1 proteins both associate with the human ubiquitin-conjugation enzyme Hsubc9 as well as with the hamster Ubc9 homologue. The interactions between SC proteins and the Ubc9 protein may be significant for SC disassembly, which coincides with the repulsion of homologs by late prophase I, and also for the termination of sister centromere cohesiveness at anaphase II. Images PMID:9285814

  20. Graphical models of protein-protein interaction specificity from correlated mutations and interaction data.

    PubMed

    Thomas, John; Ramakrishnan, Naren; Bailey-Kellogg, Chris

    2009-09-01

    Protein-protein interactions are mediated by complementary amino acids defining complementary surfaces. Typically not all members of a family of related proteins interact equally well with all members of a partner family; thus analysis of the sequence record can reveal the complementary amino acid partners that confer interaction specificity. This article develops methods for learning and using probabilistic graphical models of such residue "cross-coupling" constraints between interacting protein families, based on multiple sequence alignments and information about which pairs of proteins are known to interact. Our models generalize traditional consensus sequence binding motifs, and provide a probabilistic semantics enabling sound evaluation of the plausibility of new possible interactions. Furthermore, predictions made by the models can be explained in terms of the underlying residue interactions. Our approach supports different levels of prior knowledge regarding interactions, including both one-to-one (e.g., pairs of proteins from the same organism) and many-to-many (e.g., experimentally identified interactions), and we present a technique to account for possible bias in the represented interactions. We apply our approach in studies of PDZ domains and their ligands, fundamental building blocks in a number of protein assemblies. Our algorithms are able to identify biologically interesting cross-coupling constraints, to successfully identify known interactions, and to make explainable predictions about novel interactions.

  1. Network motifs in integrated cellular networks of transcription-regulation and protein-protein interaction

    NASA Astrophysics Data System (ADS)

    Yeger-Lotem, Esti; Sattath, Shmuel; Kashtan, Nadav; Itzkovitz, Shalev; Milo, Ron; Pinter, Ron Y.; Alon, Uri; Margalit, Hanah

    2004-04-01

    Genes and proteins generate molecular circuitry that enables the cell to process information and respond to stimuli. A major challenge is to identify characteristic patterns in this network of interactions that may shed light on basic cellular mechanisms. Previous studies have analyzed aspects of this network, concentrating on either transcription-regulation or protein-protein interactions. Here we search for composite network motifs: characteristic network patterns consisting of both transcription-regulation and protein-protein interactions that recur significantly more often than in random networks. To this end we developed algorithms for detecting motifs in networks with two or more types of interactions and applied them to an integrated data set of protein-protein interactions and transcription regulation in Saccharomyces cerevisiae. We found a two-protein mixed-feedback loop motif, five types of three-protein motifs exhibiting coregulation and complex formation, and many motifs involving four proteins. Virtually all four-protein motifs consisted of combinations of smaller motifs. This study presents a basic framework for detecting the building blocks of networks with multiple types of interactions.

  2. Comprehensive peptidomimetic libraries targeting protein-protein interactions.

    PubMed

    Whitby, Landon R; Boger, Dale L

    2012-10-16

    Transient protein-protein interactions (PPIs) are essential components in cellular signaling pathways as well as in important processes such as viral infection, replication, and immune suppression. The unknown or uncharacterized PPIs involved in such interaction networks often represent compelling therapeutic targets for drug discovery. To date, however, the main strategies for discovery of small molecule modulators of PPIs are typically limited to structurally characterized targets. Recent developments in molecular scaffolds that mimic the side chain display of peptide secondary structures have yielded effective designs, but few screening libraries of such mimetics are available to interrogate PPI targets. We initiated a program to prepare a comprehensive small molecule library designed to mimic the three major recognition motifs that mediate PPIs (α-helix, β-turn, and β-strand). Three libraries would be built around templates designed to mimic each such secondary structure and substituted with all triplet combinations of groups representing the 20 natural amino acid side chains. When combined, the three libraries would contain a member capable of mimicking the key interaction and recognition residues of most targetable PPIs. In this Account, we summarize the results of the design, synthesis, and validation of an 8000 member α-helix mimetic library and a 4200 member β-turn mimetic library. We expect that the screening of these libraries will not only provide lead structures against α-helix- or β-turn-mediated protein-protein or peptide-receptor interactions, even if the nature of the interaction is unknown, but also yield key insights into the recognition motif (α-helix or β-turn) and identify the key residues mediating the interaction. Consistent with this expectation, the screening of the libraries against p53/MDM2 and HIV-1 gp41 (α-helix mimetic library) or the opioid receptors (β-turn mimetic library) led to the discovery of library members expected

  3. Structural Analysis of Protein-Protein Interactions in Type I Polyketide Synthases

    PubMed Central

    Xu, Wei; Qiao, Kangjian; Tang, Yi

    2013-01-01

    Polyketide synthases (PKSs) are responsible for synthesizing a myriad of natural products with agricultural, medicinal relevance. The PKSs consist of multiple functional domains of which each can catalyze a specified chemical reaction leading to the synthesis of polyketides. Biochemical studies showed that protein-substrate and protein-protein interactions play crucial roles in these complex regio-/stereo- selective biochemical processes. Recent developments on X-ray crystallography and protein NMR techniques have allowed us to understand the biosynthetic mechanism of these enzymes from their structures. These structural studies have facilitated the elucidation of sequence-function relationship of PKSs and will ultimately contribute to the prediction of product structure. This review will focus on the current knowledge of type I PKS structures and the protein-protein interactions in this system. PMID:23249187

  4. Interface-Resolved Network of Protein-Protein Interactions

    PubMed Central

    Johnson, Margaret E.; Hummer, Gerhard

    2013-01-01

    We define an interface-interaction network (IIN) to capture the specificity and competition between protein-protein interactions (PPI). This new type of network represents interactions between individual interfaces used in functional protein binding and thereby contains the detail necessary to describe the competition and cooperation between any pair of binding partners. Here we establish a general framework for the construction of IINs that merges computational structure-based interface assignment with careful curation of available literature. To complement limited structural data, the inclusion of biochemical data is critical for achieving the accuracy and completeness necessary to analyze the specificity and competition between the protein interactions. Firstly, this procedure provides a means to clarify the information content of existing data on purported protein interactions and to remove indirect and spurious interactions. Secondly, the IIN we have constructed here for proteins involved in clathrin-mediated endocytosis (CME) exhibits distinctive topological properties. In contrast to PPI networks with their global and relatively dense connectivity, the fragmentation of the IIN into distinctive network modules suggests that different functional pressures act on the evolution of its topology. Large modules in the IIN are formed by interfaces sharing specificity for certain domain types, such as SH3 domains distributed across different proteins. The shared and distinct specificity of an interface is necessary for effective negative and positive design of highly selective binding targets. Lastly, the organization of detailed structural data in a network format allows one to identify pathways of specific binding interactions and thereby predict effects of mutations at specific surfaces on a protein and of specific binding inhibitors, as we explore in several examples. Overall, the endocytosis IIN is remarkably complex and rich in features masked in the coarser

  5. Protein-Protein Interactions of Viroporins in Coronaviruses and Paramyxoviruses: New Targets for Antivirals?

    PubMed Central

    Torres, Jaume; Surya, Wahyu; Li, Yan; Liu, Ding Xiang

    2015-01-01

    Viroporins are members of a rapidly growing family of channel-forming small polypeptides found in viruses. The present review will be focused on recent structural and protein-protein interaction information involving two viroporins found in enveloped viruses that target the respiratory tract; (i) the envelope protein in coronaviruses and (ii) the small hydrophobic protein in paramyxoviruses. Deletion of these two viroporins leads to viral attenuation in vivo, whereas data from cell culture shows involvement in the regulation of stress and inflammation. The channel activity and structure of some representative members of these viroporins have been recently characterized in some detail. In addition, searches for protein-protein interactions using yeast-two hybrid techniques have shed light on possible functional roles for their exposed cytoplasmic domains. A deeper analysis of these interactions should not only provide a more complete overview of the multiple functions of these viroporins, but also suggest novel strategies that target protein-protein interactions as much needed antivirals. These should complement current efforts to block viroporin channel activity. PMID:26053927

  6. Deciphering Supramolecular Structures with Protein-Protein Interaction Network Modeling

    PubMed Central

    Tsuji, Toshiyuki; Yoda, Takao; Shirai, Tsuyoshi

    2015-01-01

    Many biological molecules are assembled into supramolecules that are essential to perform complicated functions in the cell. However, experimental information about the structures of supramolecules is not sufficient at this point. We developed a method of predicting and modeling the structures of supramolecules in a biological network by combining structural data of the Protein Data Bank (PDB) and interaction data in IntAct databases. Templates for binary complexes in IntAct were extracted from PDB. Modeling was attempted by assembling binary complexes with superposed shared subunits. A total of 3,197 models were constructed, and 1,306 (41% of the total) contained at least one subunit absent from experimental structures. The models also suggested 970 (25% of the total) experimentally undetected subunit interfaces, and 41 human disease-related amino acid variants were mapped onto these model-suggested interfaces. The models demonstrated that protein-protein interaction network modeling is useful to fill the information gap between biological networks and structures. PMID:26549015

  7. Parallel Force Assay for Protein-Protein Interactions

    PubMed Central

    Aschenbrenner, Daniela; Pippig, Diana A.; Klamecka, Kamila; Limmer, Katja; Leonhardt, Heinrich; Gaub, Hermann E.

    2014-01-01

    Quantitative proteome research is greatly promoted by high-resolution parallel format assays. A characterization of protein complexes based on binding forces offers an unparalleled dynamic range and allows for the effective discrimination of non-specific interactions. Here we present a DNA-based Molecular Force Assay to quantify protein-protein interactions, namely the bond between different variants of GFP and GFP-binding nanobodies. We present different strategies to adjust the maximum sensitivity window of the assay by influencing the binding strength of the DNA reference duplexes. The binding of the nanobody Enhancer to the different GFP constructs is compared at high sensitivity of the assay. Whereas the binding strength to wild type and enhanced GFP are equal within experimental error, stronger binding to superfolder GFP is observed. This difference in binding strength is attributed to alterations in the amino acids that form contacts according to the crystal structure of the initial wild type GFP-Enhancer complex. Moreover, we outline the potential for large-scale parallelization of the assay. PMID:25546146

  8. Free energy decomposition of protein-protein interactions.

    PubMed Central

    Noskov, S Y; Lim, C

    2001-01-01

    A free energy decomposition scheme has been developed and tested on antibody-antigen and protease-inhibitor binding for which accurate experimental structures were available for both free and bound proteins. Using the x-ray coordinates of the free and bound proteins, the absolute binding free energy was computed assuming additivity of three well-defined, physical processes: desolvation of the x-ray structures, isomerization of the x-ray conformation to a nearby local minimum in the gas-phase, and subsequent noncovalent complex formation in the gas phase. This free energy scheme, together with the Generalized Born model for computing the electrostatic solvation free energy, yielded binding free energies in remarkable agreement with experimental data. Two assumptions commonly used in theoretical treatments; viz., the rigid-binding approximation (which assumes no conformational change upon complexation) and the neglect of vdW interactions, were found to yield large errors in the binding free energy. Protein-protein vdW and electrostatic interactions between complementary surfaces over a relatively large area (1400--1700 A(2)) were found to drive antibody-antigen and protease-inhibitor binding. PMID:11463622

  9. Using support vector machine for improving protein-protein interaction prediction utilizing domain interactions

    SciTech Connect

    Singhal, Mudita; Shah, Anuj R.; Brown, Roslyn N.; Adkins, Joshua N.

    2010-10-02

    Understanding protein interactions is essential to gain insights into the biological processes at the whole cell level. The high-throughput experimental techniques for determining protein-protein interactions (PPI) are error prone and expensive with low overlap amongst them. Although several computational methods have been proposed for predicting protein interactions there is definite room for improvement. Here we present DomainSVM, a predictive method for PPI that uses computationally inferred domain-domain interaction values in a Support Vector Machine framework to predict protein interactions. DomainSVM method utilizes evidence of multiple interacting domains to predict a protein interaction. It outperforms existing methods of PPI prediction by achieving very high explanation ratios, precision, specificity, sensitivity and F-measure values in a 10 fold cross-validation study conducted on the positive and negative PPIs in yeast. A Functional comparison study using GO annotations on the positive and the negative test sets is presented in addition to discussing novel PPI predictions in Salmonella Typhimurium.

  10. Optical methods in the study of protein-protein interactions.

    PubMed

    Masi, Alessio; Cicchi, Riccardo; Carloni, Adolfo; Pavone, Francesco Saverio; Arcangeli, Annarosa

    2010-01-01

    Förster (or Fluorescence) resonance energy transfer (FRET) is a physical process in which energy is transferred nonradiatively from an excited fluorophore, serving as a donor, to another chromophore (acceptor). Among the techniques related to fluorescence microscopy, FRET is unique in providing signals sensitive to intra- and intermolecular distances in the 1-10 nm range. Because of its potency, FRET is increasingly used to visualize and quantify the dynamics of protein-protein interaction in living cells, with high spatio-temporal resolution. Here we describe the physical bases of FRET, detailing the principal methods applied: (1) measurement of signal intensity and (2) analysis of fluorescence lifetime (FLIM). Although several technical complications must be carefully considered, both methods can be applied fruitfully to specific fields. For example, FRET based on intensity detection is more suitable to follow biological phenomena at a finely tuned spatial and temporal scale. Furthermore, a specific fluorescence signal occurring close to the plasma membrane (< or = 100 nm) can be obtained using a total internal reflection fluorescence (TIRF) microscopy system. When performing FRET experiments, care must be also taken to the method chosen for labeling interacting proteins. Two principal tools can be applied: (1) fluorophore tagged antibodies; (2) recombinant fluorescent fusion proteins. The latter method essentially takes advantage of the discovery and use of spontaneously fluorescent proteins, like the green fluorescent protein (GFP). Until now, FRET has been widely used to analyze the structural characteristics of several proteins, including integrins and ion channels. More recently, this method has been applied to clarify the interaction dynamics of these classes of membrane proteins with cytosolic signaling proteins. We report two examples in which the interaction dynamics between integrins and ion channels have been studied with FRET methods. Using

  11. Quantifying the Molecular Origins of Opposite Solvent Effects on Protein-Protein Interactions

    PubMed Central

    Vagenende, Vincent; Han, Alvin X.; Pek, Han B.; Loo, Bernard L. W.

    2013-01-01

    Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on the thermodynamic principles of preferential interaction theory and the quantitative characterization of local protein solvation from molecular dynamics simulations. We find that changes of preferential solvent interactions at the protein-protein interface quantitatively account for the opposite effects of glycerol on the antibody-antigen association constants. Detailed characterization of local protein solvation in the free and associated protein states reveals how opposite solvent effects on protein-protein interactions depend on the extent of dewetting of the protein-protein contact region and on structural changes that alter cooperative solvent-protein interactions at the periphery of the protein-protein interface. These results demonstrate the direct relationship between macroscopic solvent effects on protein-protein interactions and atom-scale solvent-protein interactions, and establish a general methodology for predicting and understanding solvent effects on protein-protein interactions in diverse biological environments. PMID:23696727

  12. Protein-protein interaction network of celiac disease

    PubMed Central

    Zamanian Azodi, Mona; Peyvandi, Hassan; Rostami-Nejad, Mohammad; Safaei, Akram; Rostami, Kamran; Vafaee, Reza; Heidari, Mohammadhossein; Hosseini, Mostafa; Zali, Mohammad Reza

    2016-01-01

    Aim: The aim of this study is to investigate the Protein-Protein Interaction Network of Celiac Disease. Background: Celiac disease (CD) is an autoimmune disease with susceptibility of individuals to gluten of wheat, rye and barley. Understanding the molecular mechanisms and involved pathway may lead to the development of drug target discovery. The protein interaction network is one of the supportive fields to discover the pathogenesis biomarkers for celiac disease. Material and methods: In the present study, we collected the articles that focused on the proteomic data in celiac disease. According to the gene expression investigations of these articles, 31 candidate proteins were selected for this study. The networks of related differentially expressed protein were explored using Cytoscape 3.3 and the PPI analysis methods such as MCODE and ClueGO. Results: According to the network analysis Ubiquitin C, Heat shock protein 90kDa alpha (cytosolic and Grp94); class A, B and 1 member, Heat shock 70kDa protein, and protein 5 (glucose-regulated protein, 78kDa), T-complex, Chaperon in containing TCP1; subunit 7 (beta) and subunit 4 (delta) and subunit 2 (beta), have been introduced as hub-bottlnecks proteins. HSP90AA1, MKKS, EZR, HSPA14, APOB and CAD have been determined as seed proteins. Conclusion: Chaperons have a bold presentation in curtail area in network therefore these key proteins beside the other hub-bottlneck proteins may be a suitable candidates biomarker panel for diagnosis, prognosis and treatment processes in celiac disease. PMID:27895852

  13. A Laboratory-Intensive Course on the Experimental Study of Protein-Protein Interactions

    ERIC Educational Resources Information Center

    Witherow, D. Scott; Carson, Sue

    2011-01-01

    The study of protein-protein interactions is important to scientists in a wide range of disciplines. We present here the assessment of a lab-intensive course that teaches students techniques used to identify and further study protein-protein interactions. One of the unique elements of the course is that students perform a yeast two-hybrid screen…

  14. A reliability measure of protein-protein interactions and a reliability measure-based search engine.

    PubMed

    Park, Byungkyu; Han, Kyungsook

    2010-02-01

    Many methods developed for estimating the reliability of protein-protein interactions are based on the topology of protein-protein interaction networks. This paper describes a new reliability measure for protein-protein interactions, which does not rely on the topology of protein interaction networks, but expresses biological information on functional roles, sub-cellular localisations and protein classes as a scoring schema. The new measure is useful for filtering many spurious interactions, as well as for estimating the reliability of protein interaction data. In particular, the reliability measure can be used to search protein-protein interactions with the desired reliability in databases. The reliability-based search engine is available at http://yeast.hpid.org. We believe this is the first search engine for interacting proteins, which is made available to public. The search engine and the reliability measure of protein interactions should provide useful information for determining proteins to focus on.

  15. Mining the characteristic interaction patterns on protein-protein binding interfaces.

    PubMed

    Li, Yan; Liu, Zhihai; Han, Li; Li, Chengke; Wang, Renxiao

    2013-09-23

    Protein-protein interactions are observed in various biological processes. They are important for understanding the underlying molecular mechanisms and can be potential targets for developing small-molecule regulators of such processes. Previous studies suggest that certain residues on protein-protein binding interfaces are "hot spots". As an extension to this concept, we have developed a residue-based method to identify the characteristic interaction patterns (CIPs) on protein-protein binding interfaces, in which each pattern is a cluster of four contacting residues. Systematic analysis was conducted on a nonredundant set of 1,222 protein-protein binding interfaces selected out of the entire Protein Data Bank. Favored interaction patterns across different protein-protein binding interfaces were retrieved by considering both geometrical and chemical conservations. As demonstrated on two test tests, our method was able to predict hot spot residues on protein-protein binding interfaces with good recall scores and acceptable precision scores. By analyzing the function annotations and the evolutionary tree of the protein-protein complexes in our data set, we also observed that protein-protein interfaces sharing common characteristic interaction patterns are normally associated with identical or similar biological functions.

  16. Development of small molecules designed to modulate protein-protein interactions.

    PubMed

    Che, Ye; Brooks, Bernard R; Marshall, Garland R

    2006-02-01

    Protein-protein interactions are ubiquitous, essential to almost all known biological processes, and offer attractive opportunities for therapeutic intervention. Developing small molecules that modulate protein-protein interactions is challenging, owing to the large size of protein-complex interface, the lack of well-defined binding pockets, etc. We describe a general approach based on the "privileged-structure hypothesis" [Che, Ph.D. Thesis, Washington University, 2003] - that any organic templates capable of mimicking surfaces of protein-recognition motifs are potential privileged scaffolds as protein-complex antagonists--to address the challenges inherent in the discovery of small-molecule inhibitors of protein-protein interactions.

  17. Protein-Protein Interactions as New Targets for Ion Channel Drug Discovery

    PubMed Central

    Stoilova-McPhie, Svetla; Ali, Syed; Laezza, Fernanda

    2014-01-01

    Protein-protein interactions (PPI) are key molecular elements that provide the basis of signaling in virtually all cellular processes. The precision and specificity of these molecular interactions have ignited a strong interest in pursuing PPI surfaces as new targets for drug discovery, especially against ion channels in the central nervous system (CNS) where selectivity and specificity are vital for developing drugs with limited side effects. Ion channels are large transmembrane domain proteins assembled with multiple regulatory proteins binding to the intracellular portion of channels. These macromolecular complexes are difficult to isolate, purify and reconstitute, posing a significant barrier in targeting these PPI for drug discovery purposes. Here, we will provide a short overview of salient features of PPI and discuss successful studies focusing on protein-channel interactions that could inspire new drug discovery campaigns targeting ion channel complexes. PMID:25485305

  18. Protein-Protein Interactions of the Baculovirus Per Os Infectivity Factors in the PIF Complex.

    PubMed

    Zheng, Qin; Shen, Yunwang; Kon, Xiangshuo; Zhang, Jianjia; Feng, Min; Wu, Xiaofeng

    2017-01-28

    After ingestion of occlusion bodies, the occlusion-derived viruses (ODVs) of baculoviruses establish the first round of infection within the larval host midgut cells. Several ODV envelope proteins, called per os infectivity factors (PIFs), have been shown to be essential for oral infection. Eight PIFs have been identified to date, including P74, PIFs1-6, and Ac110. At least six PIFs: P74, PIFs1-4, PIF6, together with three other ODV-specific proteins: Ac5, P95 (Ac83), and Ac108, have been reported to form a complex on the ODV surface. In this study, in order to understand the interactions of these PIFs, the direct protein-protein interactions of the nine components of the Autographa californica multiple nucleopolyhedrovirus (AcMNPV) PIF complex were investigated using yeast two-hybrid (Y2H) combined with bimolecular fluorescence complementation (BiFC) assay. Six direct interactions comprising PIF1-PIF2, PIF1-PIF3, PIF1-PIF4, PIF1-P95, PIF2-PIF3, and PIF3-PIF4, were identified in Y2H analysis, and these results were further verified by BiFC. For P74, PIF6, Ac5 and Ac108, no direct interaction was identified. P95 (Ac83) was identified to interact with PIF1 and further Y2H analysis of the truncations and deletion mutants showed that the predicted P95 chitin-binding domain and PIF1 100-200aa were responsible for P95 interaction with PIF1. Furthermore, a summary of the protein-protein interactions of PIFs reported so far, comprising 10 reciprocal interactions and 2 self-interactions, is presented, which will facilitate our understanding of the characteristic of PIF complex.

  19. Protein-protein interactions: principles, techniques, and their potential role in new drug development.

    PubMed

    Khan, Shagufta H; Ahmad, Faizan; Ahmad, Nihal; Flynn, Daniel C; Kumar, Raj

    2011-06-01

    A vast network of genes is inter-linked through protein-protein interactions and is critical component of almost every biological process under physiological conditions. Any disruption of the biologically essential network leads to pathological conditions resulting into related diseases. Therefore, proper understanding of biological functions warrants a comprehensive knowledge of protein-protein interactions and the molecular mechanisms that govern such processes. The importance of protein-protein interaction process is highlighted by the fact that a number of powerful techniques/methods have been developed to understand how such interactions take place under various physiological and pathological conditions. Many of the key protein-protein interactions are known to participate in disease-associated signaling pathways, and represent novel targets for therapeutic intervention. Thus, controlling protein-protein interactions offers a rich dividend for the discovery of new drug targets. Availability of various tools to study and the knowledge of human genome have put us in a unique position to understand highly complex biological network, and the mechanisms involved therein. In this review article, we have summarized protein-protein interaction networks, techniques/methods of their binding/kinetic parameters, and the role of these interactions in the development of potential tools for drug designing.

  20. Enhancing interacting residue prediction with integrated contact matrix prediction in protein-protein interaction.

    PubMed

    Du, Tianchuan; Liao, Li; Wu, Cathy H

    2016-12-01

    Identifying the residues in a protein that are involved in protein-protein interaction and identifying the contact matrix for a pair of interacting proteins are two computational tasks at different levels of an in-depth analysis of protein-protein interaction. Various methods for solving these two problems have been reported in the literature. However, the interacting residue prediction and contact matrix prediction were handled by and large independently in those existing methods, though intuitively good prediction of interacting residues will help with predicting the contact matrix. In this work, we developed a novel protein interacting residue prediction system, contact matrix-interaction profile hidden Markov model (CM-ipHMM), with the integration of contact matrix prediction and the ipHMM interaction residue prediction. We propose to leverage what is learned from the contact matrix prediction and utilize the predicted contact matrix as "feedback" to enhance the interaction residue prediction. The CM-ipHMM model showed significant improvement over the previous method that uses the ipHMM for predicting interaction residues only. It indicates that the downstream contact matrix prediction could help the interaction site prediction.

  1. Computational biology for target discovery and characterization: a feasibility study in protein-protein interaction detection

    SciTech Connect

    Zhou, C; Zemla, A

    2009-02-25

    In this work we developed new code for detecting putative multi-domain protein-protein interactions for a small network of bacterial pathogen proteins, and determined how structure-driven domain-fusion (DF) methods should be scaled up for whole-proteome analysis. Protein-protein interactions are of great interest in structural biology and are important for understanding the biology of pathogens. The ability to predict protein-protein interactions provides a means for development of anti-microbials that may interfer with key processes in pathogenicity. The function of a protein-protein complex can be elucidated through knowledge of its structure. The overall goal of this project was to determine the feasibility of extending current LLNL capabilities to produce a high-throughput systems bio-informatics capability for identification and characterization of putative interacting protein partners within known or suspected small protein networks. We extended an existing LLNL methodology for identification of putative protein-protein interacting partners (Chakicherla et al (in review)) by writing a new code to identify multi-domain-fusion linkages (3 or more per complex). We applied these codes to the proteins in the Yersinia pestis quorum sensing network, known as the lsr operon, which comprises a virulence mechanism in this pathogen. We determined that efficient application of our computational algorithms in high-throughput for detection of putative protein-protein complexes genome wide would require pre-computation of PDB domains and construction of a domain-domain association database.

  2. [Methods for analysis of protein-protein and protein-ligand interactions].

    PubMed

    Durech, M; Trčka, F; Vojtěšek, B; Müller, P

    2014-01-01

    In order to maintain cellular homeostasis, cellular proteins coexist in complex and variable molecular assemblies. Therefore, understanding of major physiological processes at molecular level is based on analysis of protein-protein interaction networks. Firstly, composition of the molecular assembly has to be qualitatively analyzed. In the next step, quantitative bio-chemical properties of the identified protein-protein interactions are determined. Detailed information about the protein-protein interaction interface can be obtained by crystallographic methods. Accordingly, the insight into the molecular architecture of these protein-protein complexes allows us to rationally design new synthetic compounds that specifically influence various physiological or pathological processes by targeted modulation of protein interactions. This review is focused on description of the most used methods applied in both qualitative and quantitative analysis of protein-protein interactions. Co- immunoprecipitation and affinity co- precipitation are basic methods designed for qualitative analysis of protein binding partners. Further bio-chemical analysis of the interaction requires definition of kinetic and thermodynamic parameters. Surface plasmon resonance (SPR) is used for description of affinity and kinetic profile of the interaction, fluorescence polarization (FP) method for fast determination of inhibition potential of inhibitors and isothermal titration calorimetry (ITC) for definition of thermodynamic parameters of the interaction (G, H and S). Besides the importance of uncovering the molecular basis of protein interactions for basic research, the same methodological approaches open new possibilities in rational design of novel therapeutic agents.

  3. Protein-protein interactions in intracellular Ca2+-release channel function.

    PubMed Central

    MacKrill, J J

    1999-01-01

    Release of Ca2+ ions from intracellular stores can occur via two classes of Ca2+-release channel (CRC) protein, the inositol 1,4, 5-trisphosphate receptors (InsP3Rs) and the ryanodine receptors (RyRs). Multiple isoforms and subtypes of each CRC class display distinct but overlapping distributions within mammalian tissues. InsP3Rs and RyRs interact with a plethora of accessory proteins which modulate the activity of their intrinsic channels. Although many aspects of CRC structure and function have been reviewed in recent years, the properties of proteins with which they interact has not been comprehensively surveyed, despite extensive current research on the roles of these modulators. The aim of this article is to review the regulation of CRC activity by accessory proteins and, wherever possible, to outline the structural details of such interactions. The CRCs are large transmembrane proteins, with the bulk of their structure located cytoplasmically. Intra- and inter-complex protein-protein interactions between these cytoplasmic domains also regulate CRC function. Some accessory proteins modulate channel activity of all CRC subtypes characterized, whereas other have class- or even isoform-specific effects. Certain accessory proteins exert both direct and indirect forms of regulation on CRCs, occasionally with opposing effects. Others are themselves modulated by changes in Ca2+ concentration, thereby participating in feedback mechanisms acting on InsP3R and RyR activity. CRCs are therefore capable of integrating numerous signalling events within a cell by virtue of such protein-protein interactions. Consequently, the functional properties of InsP3Rs and RyRs within particular cells and subcellular domains are 'customized' by the accessory proteins present. PMID:9895277

  4. Exploring NMR ensembles of calcium binding proteins: Perspectives to design inhibitors of protein-protein interactions

    PubMed Central

    2011-01-01

    Background Disrupting protein-protein interactions by small organic molecules is nowadays a promising strategy employed to block protein targets involved in different pathologies. However, structural changes occurring at the binding interfaces make difficult drug discovery processes using structure-based drug design/virtual screening approaches. Here we focused on two homologous calcium binding proteins, calmodulin and human centrin 2, involved in different cellular functions via protein-protein interactions, and known to undergo important conformational changes upon ligand binding. Results In order to find suitable protein conformations of calmodulin and centrin for further structure-based drug design/virtual screening, we performed in silico structural/energetic analysis and molecular docking of terphenyl (a mimicking alpha-helical molecule known to inhibit protein-protein interactions of calmodulin) into X-ray and NMR ensembles of calmodulin and centrin. We employed several scoring methods in order to find the best protein conformations. Our results show that docking on NMR structures of calmodulin and centrin can be very helpful to take into account conformational changes occurring at protein-protein interfaces. Conclusions NMR structures of protein-protein complexes nowadays available could efficiently be exploited for further structure-based drug design/virtual screening processes employed to design small molecule inhibitors of protein-protein interactions. PMID:21569443

  5. A Bayesian Framework for Combining Protein and Network Topology Information for Predicting Protein-Protein Interactions.

    PubMed

    Birlutiu, Adriana; d'Alché-Buc, Florence; Heskes, Tom

    2015-01-01

    Computational methods for predicting protein-protein interactions are important tools that can complement high-throughput technologies and guide biologists in designing new laboratory experiments. The proteins and the interactions between them can be described by a network which is characterized by several topological properties. Information about proteins and interactions between them, in combination with knowledge about topological properties of the network, can be used for developing computational methods that can accurately predict unknown protein-protein interactions. This paper presents a supervised learning framework based on Bayesian inference for combining two types of information: i) network topology information, and ii) information related to proteins and the interactions between them. The motivation of our model is that by combining these two types of information one can achieve a better accuracy in predicting protein-protein interactions, than by using models constructed from these two types of information independently.

  6. MCLIP Detection of Novel Protein-Protein Interactions at the Nuclear Envelope.

    PubMed

    Jafferali, Mohammed Hakim; Figueroa, Ricardo A; Hallberg, Einar

    2016-01-01

    The organization and function of the nuclear envelope (NE) involves hundreds of nuclear membrane proteins and myriad protein-protein interactions, most of which are still uncharacterized. Many NE proteins interact stably or dynamically with the nuclear lamina or chromosomes. This can make them difficult to extract under nondenaturing conditions, and greatly limits our ability to explore and identify functional protein interactions at the NE. This knowledge is needed to understand nuclear envelope structure and the mechanisms of human laminopathy diseases. This chapter provides detailed protocols for MCLIP (membrane cross-linking immunoprecipitation) identification of novel protein-protein interactions in mammalian cells.

  7. Experimental and bioinformatic approaches for interrogating protein-protein interactions to determine protein function.

    PubMed

    Droit, Arnaud; Poirier, Guy G; Hunter, Joanna M

    2005-04-01

    An ambitious goal of proteomics is to elucidate the structure, interactions and functions of all proteins within cells and organisms. One strategy to determine protein function is to identify the protein-protein interactions. The increasing use of high-throughput and large-scale bioinformatics-based studies has generated a massive amount of data stored in a number of different databases. A challenge for bioinformatics is to explore this disparate data and to uncover biologically relevant interactions and pathways. In parallel, there is clearly a need for the development of approaches that can predict novel protein-protein interaction networks in silico. Here, we present an overview of different experimental and bioinformatic methods to elucidate protein-protein interactions.

  8. Role of protein-protein interactions in cytochrome P450-mediated drug metabolism and toxicity.

    PubMed

    Kandel, Sylvie E; Lampe, Jed N

    2014-09-15

    Through their unique oxidative chemistry, cytochrome P450 monooxygenases (CYPs) catalyze the elimination of most drugs and toxins from the human body. Protein-protein interactions play a critical role in this process. Historically, the study of CYP-protein interactions has focused on their electron transfer partners and allosteric mediators, cytochrome P450 reductase and cytochrome b5. However, CYPs can bind other proteins that also affect CYP function. Some examples include the progesterone receptor membrane component 1, damage resistance protein 1, human and bovine serum albumin, and intestinal fatty acid binding protein, in addition to other CYP isoforms. Furthermore, disruption of these interactions can lead to altered paths of metabolism and the production of toxic metabolites. In this review, we summarize the available evidence for CYP protein-protein interactions from the literature and offer a discussion of the potential impact of future studies aimed at characterizing noncanonical protein-protein interactions with CYP enzymes.

  9. PPIevo: protein-protein interaction prediction from PSSM based evolutionary information.

    PubMed

    Zahiri, Javad; Yaghoubi, Omid; Mohammad-Noori, Morteza; Ebrahimpour, Reza; Masoudi-Nejad, Ali

    2013-10-01

    Protein-protein interactions regulate a variety of cellular processes. There is a great need for computational methods as a complement to experimental methods with which to predict protein interactions due to the existence of many limitations involved in experimental techniques. Here, we introduce a novel evolutionary based feature extraction algorithm for protein-protein interaction (PPI) prediction. The algorithm is called PPIevo and extracts the evolutionary feature from Position-Specific Scoring Matrix (PSSM) of protein with known sequence. The algorithm does not depend on the protein annotations, and the features are based on the evolutionary history of the proteins. This enables the algorithm to have more power for predicting protein-protein interaction than many sequence based algorithms. Results on the HPRD database show better performance and robustness of the proposed method. They also reveal that the negative dataset selection could lead to an acute performance overestimation which is the principal drawback of the available methods.

  10. Pharmacological interference with protein-protein interactions mediated by coiled-coil motifs.

    PubMed

    Strauss, H M; Keller, S

    2008-01-01

    , and a given protein can participate in multiple assembly-disassembly equilibria among several coiled coils differing in stoichiometry and topology (Portwich et al. 2007). Protein complexes whose oligomeric quaternary structures - and, hence, biological activities - depend on coiled-coil interactions include transcription factors, tRNA synthetases (Biou et al. 1994; Cusack et al. 1990), cytoskeletal and signal-transduction proteins, enzyme complexes, proteins involved in vesicular trafficking, viral coat proteins, and membrane proteins (Langosch and Heringa 1998). It is thus not surprising that coiled-coil motifs have gained great attention as potential targets for modulating protein-protein interactions implicated in a large number of diseases. In this review, we will first discuss some fundamental functional and structural aspects of a simple and well-characterized representative of coiled-coil transcription factors (Sect. 1) before considering two more complex coiled coils found in scaffolding proteins involved in mitosis and meiosis and vesicular trafficking Sect. 2). This will set the stage for addressing the role of coiled coils in viral infection (Sect. 3) as well as strategies of interfering with such protein-protein interactions therapeutically (Sect. 4 and 5).

  11. Proteins interacting with cloning scars: a source of false positive protein-protein interactions.

    PubMed

    Banks, Charles A S; Boanca, Gina; Lee, Zachary T; Florens, Laurence; Washburn, Michael P

    2015-02-23

    A common approach for exploring the interactome, the network of protein-protein interactions in cells, uses a commercially available ORF library to express affinity tagged bait proteins; these can be expressed in cells and endogenous cellular proteins that copurify with the bait can be identified as putative interacting proteins using mass spectrometry. Control experiments can be used to limit false-positive results, but in many cases, there are still a surprising number of prey proteins that appear to copurify specifically with the bait. Here, we have identified one source of false-positive interactions in such studies. We have found that a combination of: 1) the variable sequence of the C-terminus of the bait with 2) a C-terminal valine "cloning scar" present in a commercially available ORF library, can in some cases create a peptide motif that results in the aberrant co-purification of endogenous cellular proteins. Control experiments may not identify false positives resulting from such artificial motifs, as aberrant binding depends on sequences that vary from one bait to another. It is possible that such cryptic protein binding might occur in other systems using affinity tagged proteins; this study highlights the importance of conducting careful follow-up studies where novel protein-protein interactions are suspected.

  12. Developing algorithms for predicting protein-protein interactions of homology modeled proteins.

    SciTech Connect

    Martin, Shawn Bryan; Sale, Kenneth L.; Faulon, Jean-Loup Michel; Roe, Diana C.

    2006-01-01

    The goal of this project was to examine the protein-protein docking problem, especially as it relates to homology-based structures, identify the key bottlenecks in current software tools, and evaluate and prototype new algorithms that may be developed to improve these bottlenecks. This report describes the current challenges in the protein-protein docking problem: correctly predicting the binding site for the protein-protein interaction and correctly placing the sidechains. Two different and complementary approaches are taken that can help with the protein-protein docking problem. The first approach is to predict interaction sites prior to docking, and uses bioinformatics studies of protein-protein interactions to predict theses interaction site. The second approach is to improve validation of predicted complexes after docking, and uses an improved scoring function for evaluating proposed docked poses, incorporating a solvation term. This scoring function demonstrates significant improvement over current state-of-the art functions. Initial studies on both these approaches are promising, and argue for full development of these algorithms.

  13. Protein-protein interactions in complex cosolvent solutions.

    PubMed

    Javid, Nadeem; Vogtt, Karsten; Krywka, Chris; Tolan, Metin; Winter, Roland

    2007-04-02

    The effects of various kosmotropic and chaotropic cosolvents and salts on the intermolecular interaction potential of positively charged lysozyme is evaluated at varying protein concentrations by using synchrotron small-angle X-ray scattering in combination with liquid-state theoretical approaches. The experimentally derived static structure factors S(Q) obtained without and with added cosolvents and salts are analysed with a statistical mechanical model based on the Derjaguin-Landau-Verwey-Overbeek (DLVO) potential, which accounts for repulsive and attractive interactions between the protein molecules. Different cosolvents and salts influence the interactions between protein molecules differently as a result of changes in the hydration level or solvation, in charge screening, specific adsorption of the additives at the protein surface, or increased hydrophobic interactions. Intermolecular interaction effects are significant above protein concentrations of 1 wt %, and with increasing protein concentration, the repulsive nature of the intermolecular pair potential V(r) increases markedly. Kosmotropic cosolvents like glycerol and sucrose exhibit strong concentration-dependent effects on the interaction potential, leading to an increase of repulsive forces between the protein molecules at low to medium high osmolyte concentrations. Addition of trifluoroethanol exhibits a multiphasic effect on V(r) when changing its concentration. Salts like sodium chloride and potassium sulfate exhibit strong concentration-dependent changes of the interaction potential due to charge screening of the positively charged protein molecules. Guanidinium chloride (GdmCl) at low concentrations exhibits a similar charge-screening effect, resulting in increased attractive interactions between the protein molecules. At higher GdmCl concentrations, V(r) becomes more repulsive in nature due to the presence of high concentrations of Gdm(+) ions binding to the protein molecules. Our findings also

  14. Integrating protein-protein interaction networks with phenotypes reveals signs of interactions

    PubMed Central

    Vinayagam, Arunachalam; Zirin, Jonathan; Roesel, Charles; Hu, Yanhui; Yilmazel, Bahar; Samsonova, Anastasia A.; Neumüller, Ralph A.; Mohr, Stephanie E.; Perrimon, Norbert

    2013-01-01

    A major objective of systems biology is to organize molecular interactions as networks and to characterize information-flow within networks. We describe a computational framework to integrate protein-protein interaction (PPI) networks and genetic screens to predict the “signs” of interactions (i.e. activation/inhibition relationships). We constructed a Drosophila melanogaster signed PPI network, consisting of 6,125 signed PPIs connecting 3,352 proteins that can be used to identify positive and negative regulators of signaling pathways and protein complexes. We identified an unexpected role for the metabolic enzymes Enolase and Aldo-keto reductase as positive and negative regulators of proteolysis, respectively. Characterization of the activation/inhibition relationships between physically interacting proteins within signaling pathways will impact our understanding of many biological functions, including signal transduction and mechanisms of disease. PMID:24240319

  15. AAV Vectors for FRET-Based Analysis of Protein-Protein Interactions in Photoreceptor Outer Segments

    PubMed Central

    Becirovic, Elvir; Böhm, Sybille; Nguyen, Ong N. P.; Riedmayr, Lisa M.; Hammelmann, Verena; Schön, Christian; Butz, Elisabeth S.; Wahl-Schott, Christian; Biel, Martin; Michalakis, Stylianos

    2016-01-01

    Fluorescence resonance energy transfer (FRET) is a powerful method for the detection and quantification of stationary and dynamic protein-protein interactions. Technical limitations have hampered systematic in vivo FRET experiments to study protein-protein interactions in their native environment. Here, we describe a rapid and robust protocol that combines adeno-associated virus (AAV) vector-mediated in vivo delivery of genetically encoded FRET partners with ex vivo FRET measurements. The method was established on acutely isolated outer segments of murine rod and cone photoreceptors and relies on the high co-transduction efficiency of retinal photoreceptors by co-delivered AAV vectors. The procedure can be used for the systematic analysis of protein-protein interactions of wild type or mutant outer segment proteins in their native environment. Conclusively, our protocol can help to characterize the physiological and pathophysiological relevance of photoreceptor specific proteins and, in principle, should also be transferable to other cell types. PMID:27516733

  16. Inhibition of Protein-Protein Interactions and Signaling by Small Molecules

    NASA Astrophysics Data System (ADS)

    Freire, Ernesto

    2010-03-01

    Protein-protein interactions are at the core of cell signaling pathways as well as many bacterial and viral infection processes. As such, they define critical targets for drug development against diseases such as cancer, arthritis, obesity, AIDS and many others. Until now, the clinical inhibition of protein-protein interactions and signaling has been accomplished with the use of antibodies or soluble versions of receptor molecules. Small molecule replacements of these therapeutic agents have been extremely difficult to develop; either the necessary potency has been hard to achieve or the expected biological effect has not been obtained. In this presentation, we show that a rigorous thermodynamic approach that combines differential scanning calorimetry (DSC) and isothermal titration calorimetry (ITC) provides a unique platform for the identification and optimization of small molecular weight inhibitors of protein-protein interactions. Recent advances in the development of cell entry inhibitors of HIV-1 using this approach will be discussed.

  17. Prediction of protein-protein interactions: unifying evolution and structure at protein interfaces.

    PubMed

    Tuncbag, Nurcan; Gursoy, Attila; Keskin, Ozlem

    2011-06-01

    The vast majority of the chores in the living cell involve protein-protein interactions. Providing details of protein interactions at the residue level and incorporating them into protein interaction networks are crucial toward the elucidation of a dynamic picture of cells. Despite the rapid increase in the number of structurally known protein complexes, we are still far away from a complete network. Given experimental limitations, computational modeling of protein interactions is a prerequisite to proceed on the way to complete structural networks. In this work, we focus on the question 'how do proteins interact?' rather than 'which proteins interact?' and we review structure-based protein-protein interaction prediction approaches. As a sample approach for modeling protein interactions, PRISM is detailed which combines structural similarity and evolutionary conservation in protein interfaces to infer structures of complexes in the protein interaction network. This will ultimately help us to understand the role of protein interfaces in predicting bound conformations.

  18. Inferring High-Confidence Human Protein-Protein Interactions

    DTIC Science & Technology

    2012-01-01

    Similarly, the top-ranked interaction between L-threonine dehydrogenase ( TDH ) and aminoacetone synthetase (alias of GCAT) catalyzes the conversion of L...acetyltransferase TDH 2 L-threonine dehydrogenase 2 577.4 11.0 1328.0 CXCL16 4 Inducible T cell co-stimulator CXCR6 4 Inducible T cell co-stimulator

  19. Protein- protein interaction detection system using fluorescent protein microdomains

    DOEpatents

    Waldo, Geoffrey S.; Cabantous, Stephanie

    2010-02-23

    The invention provides a protein labeling and interaction detection system based on engineered fragments of fluorescent and chromophoric proteins that require fused interacting polypeptides to drive the association of the fragments, and further are soluble and stable, and do not change the solubility of polypeptides to which they are fused. In one embodiment, a test protein X is fused to a sixteen amino acid fragment of GFP (.beta.-strand 10, amino acids 198-214), engineered to not perturb fusion protein solubility. A second test protein Y is fused to a sixteen amino acid fragment of GFP (.beta.-strand 11, amino acids 215-230), engineered to not perturb fusion protein solubility. When X and Y interact, they bring the GFP strands into proximity, and are detected by complementation with a third GFP fragment consisting of GFP amino acids 1-198 (strands 1-9). When GFP strands 10 and 11 are held together by interaction of protein X and Y, they spontaneous association with GFP strands 1-9, resulting in structural complementation, folding, and concomitant GFP fluorescence.

  20. Protein-protein interaction networks in the spinocerebellar ataxias

    PubMed Central

    Rubinsztein, David C

    2006-01-01

    A large yeast two-hybrid study investigating whether the proteins mutated in different forms of spinocerebellar ataxia have interacting protein partners in common suggests that some forms do share common pathways, and will provide a valuable resource for future work on these diseases. PMID:16904001

  1. Characterization and modeling of protein protein interaction networks

    NASA Astrophysics Data System (ADS)

    Colizza, Vittoria; Flammini, Alessandro; Maritan, Amos; Vespignani, Alessandro

    2005-07-01

    The recent availability of high-throughput gene expression and proteomics techniques has created an unprecedented opportunity for a comprehensive study of the structure and dynamics of many biological networks. Global proteomic interaction data, in particular, are synthetically represented as undirected networks exhibiting features far from the random paradigm which has dominated past effort in network theory. This evidence, along with the advances in the theory of complex networks, has triggered an intense research activity aimed at exploiting the evolutionary and biological significance of the resulting network's topology. Here we present a review of the results obtained in the characterization and modeling of the yeast Saccharomyces Cerevisiae protein interaction networks obtained with different experimental techniques. We provide a comparative assessment of the topological properties and discuss possible biases in interaction networks obtained with different techniques. We report on dynamical models based on duplication mechanisms that cast the protein interaction networks in the family of dynamically growing complex networks. Finally, we discuss various results and analysis correlating the networks’ topology with the biological function of proteins.

  2. An ontology-based search engine for protein-protein interactions

    PubMed Central

    2010-01-01

    Background Keyword matching or ID matching is the most common searching method in a large database of protein-protein interactions. They are purely syntactic methods, and retrieve the records in the database that contain a keyword or ID specified in a query. Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database. Results We have developed a new method for representing protein-protein interactions and the Gene Ontology (GO) using modified Gödel numbers. This representation is hidden from users but enables a search engine using the representation to efficiently search protein-protein interactions in a biologically meaningful way. Given a query protein with optional search conditions expressed in one or more GO terms, the search engine finds all the interaction partners of the query protein by unique prime factorization of the modified Gödel numbers representing the query protein and the search conditions. Conclusion Representing the biological relations of proteins and their GO annotations by modified Gödel numbers makes a search engine efficiently find all protein-protein interactions by prime factorization of the numbers. Keyword matching or ID matching search methods often miss the interactions involving a protein that has no explicit annotations matching the search condition, but our search engine retrieves such interactions as well if they satisfy the search condition with a more specific term in the ontology. PMID:20122195

  3. TIMBAL v2: update of a database holding small molecules modulating protein-protein interactions.

    PubMed

    Higueruelo, Alicia P; Jubb, Harry; Blundell, Tom L

    2013-01-01

    TIMBAL is a database holding molecules of molecular weight <1200 Daltons that modulate protein-protein interactions. Since its first release, the database has been extended to cover 50 known protein-protein interactions drug targets, including protein complexes that can be stabilized by small molecules with therapeutic effect. The resource contains 14 890 data points for 6896 distinct small molecules. UniProt codes and Protein Data Bank entries are also included. Database URL: http://www-cryst.bioc.cam.ac.uk/timbal

  4. Detection of protein-protein interactions using tandem affinity purification.

    PubMed

    Goodfellow, Ian; Bailey, Dalan

    2014-01-01

    Tandem affinity purification (TAP) is an invaluable technique for identifying interaction partners for an affinity tagged bait protein. The approach relies on the fusion of dual tags to the bait before separate rounds of affinity purification and precipitation. Frequently two specific elution steps are also performed to increase the specificity of the overall technique. In the method detailed here, the two tags used are protein G and a short streptavidin binding peptide; however, many variations can be employed. In our example the tags are separated by a cleavable tobacco etch virus protease target sequence, allowing for specific elution after the first round of affinity purification. Proteins isolated after the final elution step in this process are concentrated before being identified by mass spectrometry. The use of dual affinity tags and specific elution in this technique dramatically increases both the specificity and stringency of the pull-downs, ensuring a low level of background nonspecific interactions.

  5. The Evolutionary Dynamics of Protein-Protein Interaction Networks Inferred from the Reconstruction of Ancient Networks

    PubMed Central

    Rattei, Thomas; Makse, Hernán A.

    2013-01-01

    Cellular functions are based on the complex interplay of proteins, therefore the structure and dynamics of these protein-protein interaction (PPI) networks are the key to the functional understanding of cells. In the last years, large-scale PPI networks of several model organisms were investigated. A number of theoretical models have been developed to explain both the network formation and the current structure. Favored are models based on duplication and divergence of genes, as they most closely represent the biological foundation of network evolution. However, studies are often based on simulated instead of empirical data or they cover only single organisms. Methodological improvements now allow the analysis of PPI networks of multiple organisms simultaneously as well as the direct modeling of ancestral networks. This provides the opportunity to challenge existing assumptions on network evolution. We utilized present-day PPI networks from integrated datasets of seven model organisms and developed a theoretical and bioinformatic framework for studying the evolutionary dynamics of PPI networks. A novel filtering approach using percolation analysis was developed to remove low confidence interactions based on topological constraints. We then reconstructed the ancient PPI networks of different ancestors, for which the ancestral proteomes, as well as the ancestral interactions, were inferred. Ancestral proteins were reconstructed using orthologous groups on different evolutionary levels. A stochastic approach, using the duplication-divergence model, was developed for estimating the probabilities of ancient interactions from today's PPI networks. The growth rates for nodes, edges, sizes and modularities of the networks indicate multiplicative growth and are consistent with the results from independent static analysis. Our results support the duplication-divergence model of evolution and indicate fractality and multiplicative growth as general properties of the PPI

  6. Inhibition of protein-protein interactions with low molecular weight compounds

    PubMed Central

    Matthews, Marilyn M.; Weber, David J.; Shapiro, Paul S.; Coop, Andrew; MacKerell, Alexander D.

    2010-01-01

    An overview of issues associated with the design and development of low molecular weight inhibitors of protein-protein interactions is presented. Areas discussed include information on the nature of protein-protein interfaces, methods to characterize those interfaces and methods by which that information is applied towards ligand identification and design. Specific examples of the strategy for the identification of inhibitors of protein-protein interactions involving the proteins p56lck kinase, ERK2 and the calcium-binding protein S100B are presented. Physical characterization of the inhibitors identified in those studies shows them to have drug-like and lead-like properties, indicating their potential to be developed into therapeutic agents. PMID:21927717

  7. Protein-protein interactions and protein modules in the control of neurotransmitter release.

    PubMed Central

    Benfenati, F; Onofri, F; Giovedí, S

    1999-01-01

    Information transfer among neurons is operated by neurotransmitters stored in synaptic vesicles and released to the extracellular space by an efficient process of regulated exocytosis. Synaptic vesicles are organized into two distinct functional pools, a large reserve pool in which vesicles are restrained by the actin-based cytoskeleton, and a quantitatively smaller releasable pool in which vesicles approach the presynaptic membrane and eventually fuse with it on stimulation. Both synaptic vesicle trafficking and neurotransmitter release depend on a precise sequence of events that include release from the reserve pool, targeting to the active zone, docking, priming, fusion and endocytotic retrieval of synaptic vesicles. These steps are mediated by a series of specific interactions among cytoskeletal, synaptic vesicle, presynaptic membrane and cytosolic proteins that, by acting in concert, promote the spatial and temporal regulation of the exocytotic machinery. The majority of these interactions are mediated by specific protein modules and domains that are found in many proteins and are involved in numerous intracellular processes. In this paper, the possible physiological role of these multiple protein-protein interactions is analysed, with ensuing updating and clarification of the present molecular model of the process of neurotransmitter release. PMID:10212473

  8. Quantification of the Influence of Protein-Protein Interactions on Adsorbed Protein Structure and Bioactivity

    PubMed Central

    Wei, Yang; Thyparambil, Aby A.; Latour, Robert A.

    2013-01-01

    While protein-surface interactions have been widely studied, relatively little is understood at this time regarding how protein-surface interaction effects are influenced by protein-protein interactions and how these effects combine with the internal stability of a protein to influence its adsorbed-state structure and bioactivity. The objectives of this study were to develop a method to study these combined effects under widely varying protein-protein interaction conditions using hen egg-white lysozyme (HEWL) adsorbed on silica glass, poly(methyl methacrylate), and polyethylene as our model systems. In order to vary protein-protein interaction effects over a wide range, HEWL was first adsorbed to each surface type under widely varying protein solution concentrations for 2 h to saturate the surface, followed by immersion in pure buffer solution for 15 h to equilibrate the adsorbed protein layers in the absence of additionally adsorbing protein. Periodic measurements were made at selected time points of the areal density of the adsorbed protein layer as an indicator of the level of protein-protein interaction effects within the layer, and these values were then correlated with measurements of the adsorbed protein’s secondary structure and bioactivity. The results from these studies indicate that protein-protein interaction effects help stabilize the structure of HEWL adsorbed on silica glass, have little influence on the structural behavior of HEWL on HDPE, and actually serve to destabilize HEWL’s structure on PMMA. The bioactivity of HEWL on silica glass and HDPE was found to decrease in direct proportion to the degree of adsorption-induce protein unfolding. A direct correlation between bioactivity and the conformational state of adsorbed HEWL was less apparent on PMMA, thus suggesting that other factors influenced HEWL’s bioactivity on this surface, such as the accessibility of HEWL’s bioactive site being blocked by neighboring proteins or the surface

  9. Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

    PubMed

    Zhang, Shu-Bo; Tang, Qiang-Rong

    2016-07-21

    Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction.

  10. Manipulating Fatty Acid Biosynthesis in Microalgae for Biofuel through Protein-Protein Interactions

    PubMed Central

    Blatti, Jillian L.; Beld, Joris; Behnke, Craig A.; Mendez, Michael; Mayfield, Stephen P.; Burkart, Michael D.

    2012-01-01

    Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP) and thioesterase (TE) govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr) as a model, a structural simulation of docking CrACP to CrTE identifies a protein-protein recognition surface between the two domains. A virtual screen reveals plant TEs with similar in silico binding to CrACP. Employing an activity-based crosslinking probe designed to selectively trap transient protein-protein interactions between the TE and ACP, we demonstrate in vitro that CrTE must functionally interact with CrACP to release fatty acids, while TEs of vascular plants show no mechanistic crosslinking to CrACP. This is recapitulated in vivo, where overproduction of the endogenous CrTE increased levels of short-chain fatty acids and engineering plant TEs into the C. reinhardtii chloroplast did not alter the fatty acid profile. These findings highlight the critical role of protein-protein interactions in manipulating fatty acid biosynthesis for algae biofuel engineering as illuminated by activity-based probes. PMID:23028438

  11. Manipulating fatty acid biosynthesis in microalgae for biofuel through protein-protein interactions.

    PubMed

    Blatti, Jillian L; Beld, Joris; Behnke, Craig A; Mendez, Michael; Mayfield, Stephen P; Burkart, Michael D

    2012-01-01

    Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP) and thioesterase (TE) govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr) as a model, a structural simulation of docking CrACP to CrTE identifies a protein-protein recognition surface between the two domains. A virtual screen reveals plant TEs with similar in silico binding to CrACP. Employing an activity-based crosslinking probe designed to selectively trap transient protein-protein interactions between the TE and ACP, we demonstrate in vitro that CrTE must functionally interact with CrACP to release fatty acids, while TEs of vascular plants show no mechanistic crosslinking to CrACP. This is recapitulated in vivo, where overproduction of the endogenous CrTE increased levels of short-chain fatty acids and engineering plant TEs into the C. reinhardtii chloroplast did not alter the fatty acid profile. These findings highlight the critical role of protein-protein interactions in manipulating fatty acid biosynthesis for algae biofuel engineering as illuminated by activity-based probes.

  12. Direct AKAP-mediated protein-protein interactions as potential drug targets.

    PubMed

    Hundsrucker, C; Klussmann, E

    2008-01-01

    A-kinase-anchoring proteins (AKAPs) are a diverse family of about 50 scaffolding proteins. They are defined by the presence of a structurally conserved protein kinase A (PKA)-binding domain. AKAPs tether PKA and other signalling proteins such as further protein kinases, protein phosphatases and phosphodiesterases by direct protein-protein interactions to cellular compartments. Thus, AKAPs form the basis of signalling modules that integrate cellular signalling processes and limit these to defined sites. Disruption of AKAP functions by gene targeting, knockdown approaches and, in particular, pharmacological disruption of defined AKAP-dependent protein-protein interactions has revealed key roles of AKAPs in numerous processes, including the regulation of cardiac myocyte contractility and vasopressin-mediated water reabsorption in the kidney. Dysregulation of such processes causes diseases, including cardiovascular and renal disorders. In this review, we discuss AKAP functions elucidated by gene targeting and knockdown approaches, but mainly focus on studies utilizing peptides for disruption of direct AKAP-mediated protein-protein interactions. The latter studies point to direct AKAP-mediated protein-protein interactions as targets for novel drugs.

  13. A fluorescent probe for imaging p53-MDM2 protein-protein interaction.

    PubMed

    Liu, Zhenzhen; Miao, Zhenyuan; Li, Jin; Fang, Kun; Zhuang, Chunlin; Du, Lupei; Sheng, Chunquan; Li, Minyong

    2015-04-01

    In this article, we describe a no-wash small-molecule fluorescent probe for detecting and imaging p53-MDM2 protein-protein interaction based on an environment-sensitive fluorescent turn-on mechanism. After extensive biological examination, this probe L1 exhibited practical activity and selectivity in vitro and in cellulo.

  14. Classification methods for finding articles describing protein-protein interactions in PubMed.

    PubMed

    Matos, Sérgio; Oliveira, José Luís

    2011-09-16

    With the rapid expansion in the number of published papers in the biomedical field, finding relevant articles has become a demanding task for researchers. This has led to increasing interest in the use of text mining tools that help search the literature and identify the most relevant documents or information. One specific topic of interest is related to the identification of articles that might be used for extracting protein-protein interactions. Using the BioCreative III Article Classification Task dataset, composed of PubMed abstracts classified as relevant or non-relevant for describing protein-protein interactions, we compare different classification methods with different sets of features. The best results--area under the interpolated precision-recall curve of 0.654--indicate that the proposed classification strategy could be incorporated in the database curation workflows in order to prioritize articles for extraction of protein-protein interactions. Furthermore, we also analysed the use of this method for ranking documents resulting from general PubMed queries, and propose that this approach could be useful for general researchers looking for publications describing protein-protein interactions within a particular topic of interest.

  15. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    PubMed Central

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-01-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases. PMID:26608097

  16. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    NASA Astrophysics Data System (ADS)

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-11-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

  17. ComPPI: a cellular compartment-specific database for protein-protein interaction network analysis.

    PubMed

    Veres, Daniel V; Gyurkó, Dávid M; Thaler, Benedek; Szalay, Kristóf Z; Fazekas, Dávid; Korcsmáros, Tamás; Csermely, Peter

    2015-01-01

    Here we present ComPPI, a cellular compartment-specific database of proteins and their interactions enabling an extensive, compartmentalized protein-protein interaction network analysis (URL: http://ComPPI.LinkGroup.hu). ComPPI enables the user to filter biologically unlikely interactions, where the two interacting proteins have no common subcellular localizations and to predict novel properties, such as compartment-specific biological functions. ComPPI is an integrated database covering four species (S. cerevisiae, C. elegans, D. melanogaster and H. sapiens). The compilation of nine protein-protein interaction and eight subcellular localization data sets had four curation steps including a manually built, comprehensive hierarchical structure of >1600 subcellular localizations. ComPPI provides confidence scores for protein subcellular localizations and protein-protein interactions. ComPPI has user-friendly search options for individual proteins giving their subcellular localization, their interactions and the likelihood of their interactions considering the subcellular localization of their interacting partners. Download options of search results, whole-proteomes, organelle-specific interactomes and subcellular localization data are available on its website. Due to its novel features, ComPPI is useful for the analysis of experimental results in biochemistry and molecular biology, as well as for proteome-wide studies in bioinformatics and network science helping cellular biology, medicine and drug design.

  18. An evaluation of in vitro protein-protein interaction techniques: assessing contaminating background proteins.

    PubMed

    Howell, Jenika M; Winstone, Tara L; Coorssen, Jens R; Turner, Raymond J

    2006-04-01

    Determination of protein-protein interactions is an important component in assigning function and discerning the biological relevance of proteins within a broader cellular context. In vitro protein-protein interaction methodologies, including affinity chromatography, coimmunoprecipitation, and newer approaches such as protein chip arrays, hold much promise in the detection of protein interactions, particularly in well-characterized organisms with sequenced genomes. However, each of these approaches attracts certain background proteins that can thwart detection and identification of true interactors. In addition, recombinant proteins expressed in Escherichia coli are also extensively used to assess protein-protein interactions, and background proteins in these isolates can thus contaminate interaction studies. Rigorous validation of a true interaction thus requires not only that an interaction be found by alternate techniques, but more importantly that researchers be aware of and control for matrix/support dependence. Here, we evaluate these methods for proteins interacting with DmsD (an E. coli redox enzyme maturation protein chaperone), in vitro, using E. coli subcellular fractions as prey sources. We compare and contrast the various in vitro interaction methods to identify some of the background proteins and protein profiles that are inherent to each of the methods in an E. coli system.

  19. Small Molecules Engage Hot Spots through Cooperative Binding To Inhibit a Tight Protein-Protein Interaction.

    PubMed

    Liu, Degang; Xu, David; Liu, Min; Knabe, William Eric; Yuan, Cai; Zhou, Donghui; Huang, Mingdong; Meroueh, Samy O

    2017-03-28

    Protein-protein interactions drive every aspect of cell signaling, yet only a few small-molecule inhibitors of these interactions exist. Despite our ability to identify critical residues known as hot spots, little is known about how to effectively engage them to disrupt protein-protein interactions. Here, we take advantage of the ease of preparation and stability of pyrrolinone 1, a small-molecule inhibitor of the tight interaction between the urokinase receptor (uPAR) and its binding partner, the urokinase-type plasminogen activator uPA, to synthesize more than 40 derivatives and explore their effect on the protein-protein interaction. We report the crystal structure of uPAR bound to previously discovered pyrazole 3 and to pyrrolinone 12. While both 3 and 12 bind to uPAR and compete with a fluorescently labeled peptide probe, only 12 and its derivatives inhibit the full uPAR·uPA interaction. Compounds 3 and 12 mimic and engage different hot-spot residues on uPA and uPAR, respectively. Interestingly, 12 is involved in a π-cation interaction with Arg-53, which is not considered a hot spot. Explicit-solvent molecular dynamics simulations reveal that 3 and 12 exhibit dramatically different correlations of motion with residues on uPAR. Free energy calculations for the wild-type and mutant uPAR bound to uPA or 12 show that Arg-53 interacts with uPA or with 12 in a highly cooperative manner, thereby altering the contributions of hot spots to uPAR binding. The direct engagement of peripheral residues not considered hot spots through π-cation or salt-bridge interactions could provide new opportunities for enhanced small-molecule engagement of hot spots to disrupt challenging protein-protein interactions.

  20. Common and specific signatures of gene expression and protein-protein interactions in autoimmune diseases.

    PubMed

    Tuller, T; Atar, S; Ruppin, E; Gurevich, M; Achiron, A

    2013-03-01

    The aim of this study is to understand intracellular regulatory mechanisms in peripheral blood mononuclear cells (PBMCs), which are either common to many autoimmune diseases or specific to some of them. We incorporated large-scale data such as protein-protein interactions, gene expression and demographical information of hundreds of patients and healthy subjects, related to six autoimmune diseases with available large-scale gene expression measurements: multiple sclerosis (MS), systemic lupus erythematosus (SLE), juvenile rheumatoid arthritis (JRA), Crohn's disease (CD), ulcerative colitis (UC) and type 1 diabetes (T1D). These data were analyzed concurrently by statistical and systems biology approaches tailored for this purpose. We found that chemokines such as CXCL1-3, 5, 6 and the interleukin (IL) IL8 tend to be differentially expressed in PBMCs of patients with the analyzed autoimmune diseases. In addition, the anti-apoptotic gene BCL3, interferon-γ (IFNG), and the vitamin D receptor (VDR) gene physically interact with significantly many genes that tend to be differentially expressed in PBMCs of patients with the analyzed autoimmune diseases. In general, similar cellular processes tend to be differentially expressed in PBMC in the analyzed autoimmune diseases. Specifically, the cellular processes related to cell proliferation (for example, epidermal growth factor, platelet-derived growth factor, nuclear factor-κB, Wnt/β-catenin signaling, stress-activated protein kinase c-Jun NH2-terminal kinase), inflammatory response (for example, interleukins IL2 and IL6, the cytokine granulocyte-macrophage colony-stimulating factor and the B-cell receptor), general signaling cascades (for example, mitogen-activated protein kinase, extracellular signal-regulated kinase, p38 and TRK) and apoptosis are activated in most of the analyzed autoimmune diseases. However, our results suggest that in each of the analyzed diseases, apoptosis and chemotaxis are activated via

  1. Crosslinking studies of protein-protein interactions in nonribosomal peptide biosynthesis.

    PubMed

    Hur, Gene H; Meier, Jordan L; Baskin, Jeremy; Codelli, Julian A; Bertozzi, Carolyn R; Marahiel, Mohamed A; Burkart, Michael D

    2009-04-24

    Selective protein-protein interactions between nonribosomal peptide synthetase (NRPS) proteins, governed by communication-mediating (COM) domains, are responsible for proper translocation of biosynthetic intermediates to produce the natural product. In this study, we developed a crosslinking assay, utilizing bioorthogonal probes compatible with carrier protein modification, for probing the protein interactions between COM domains of NRPS enzymes. Employing the Huisgen 1,3-dipolar cycloaddition of azides and alkynes, we examined crosslinking of cognate NRPS modules within the tyrocidine pathway and demonstrated the sensitivity of our panel of crosslinking probes toward the selective protein interactions of compatible COM domains. These studies indicate that copper-free crosslinking substrates uniquely offer a diagnostic probe for protein-protein interactions. Likewise, these crosslinking probes serve as ideal chemical tools for structural studies between NRPS modules where functional assays are lacking.

  2. Dynamic proteomics in modeling of the living cell. Protein-protein interactions.

    PubMed

    Terentiev, A A; Moldogazieva, N T; Shaitan, K V

    2009-12-01

    This review is devoted to describing, summarizing, and analyzing of dynamic proteomics data obtained over the last few years and concerning the role of protein-protein interactions in modeling of the living cell. Principles of modern high-throughput experimental methods for investigation of protein-protein interactions are described. Systems biology approaches based on integrative view on cellular processes are used to analyze organization of protein interaction networks. It is proposed that finding of some proteins in different protein complexes can be explained by their multi-modular and polyfunctional properties; the different protein modules can be located in the nodes of protein interaction networks. Mathematical and computational approaches to modeling of the living cell with emphasis on molecular dynamics simulation are provided. The role of the network analysis in fundamental medicine is also briefly reviewed.

  3. Optimization of rhodanine scaffold for the development of protein-protein interaction inhibitors.

    PubMed

    Ferro, Stefania; De Luca, Laura; Agharbaoui, Fatima Ezzahra; Christ, Frauke; Debyser, Zeger; Gitto, Rosaria

    2015-07-01

    Searching for novel protein-protein interactions inhibitors (PPIs) herein we describe the identification of a new series of rhodanine derivatives. The selection was performed by means virtual-screening, docking studies, Molecular Dynamic (MD) simulations and synthetic approaches. All the new obtained compounds were tested in order to evaluate their ability to inhibit the interaction between the HIV-1 integrase (IN) enzyme and the nuclear protein lens epithelium growth factor LEDGF/p75.

  4. Predicting protein-protein interactions from sequence using correlation coefficient and high-quality interaction dataset.

    PubMed

    Shi, Ming-Guang; Xia, Jun-Feng; Li, Xue-Ling; Huang, De-Shuang

    2010-03-01

    Identifying protein-protein interactions (PPIs) is critical for understanding the cellular function of the proteins and the machinery of a proteome. Data of PPIs derived from high-throughput technologies are often incomplete and noisy. Therefore, it is important to develop computational methods and high-quality interaction dataset for predicting PPIs. A sequence-based method is proposed by combining correlation coefficient (CC) transformation and support vector machine (SVM). CC transformation not only adequately considers the neighboring effect of protein sequence but describes the level of CC between two protein sequences. A gold standard positives (interacting) dataset MIPS Core and a gold standard negatives (non-interacting) dataset GO-NEG of yeast Saccharomyces cerevisiae were mined to objectively evaluate the above method and attenuate the bias. The SVM model combined with CC transformation yielded the best performance with a high accuracy of 87.94% using gold standard positives and gold standard negatives datasets. The source code of MATLAB and the datasets are available on request under smgsmg@mail.ustc.edu.cn.

  5. Single-Molecule Study of Protein-Protein Interaction Dynamics in a Cell Signaling System

    SciTech Connect

    Tan, Xin; Nalbant, Perihan; Toutchkine, Alexei; Hu, Dehong; Vorpagel, Erich R.; Hahn, Klaus M.; Lu, H. Peter

    2004-01-01

    We report a study on protein-protein noncovalent interactions in an intracellular signaling protein complex, using single-molecule spectroscopy and molecular dynamics (MD) simulations. A Wiskott-Aldrich Syndrome Protein (WASP) fragment that binds only the activated intracellular signaling protein Cdc42 was labeled with a novel solvatochromic dye and used to probe hydrophobic interactions significant to Cdc42/WASP recognition. The study shows static and dynamic inhomogeneous conformational fluctuations of the protein complex that involve bound and loosely bound states. A two-coupled, two-state Markovian kinetic model is proposed for the conformational dynamics. Finally, the MD simulations explore the origin of these conformational states and associated conformational fluctuations in this protein-protein interaction system.

  6. Predicting disease-related proteins based on clique backbone in protein-protein interaction network.

    PubMed

    Yang, Lei; Zhao, Xudong; Tang, Xianglong

    2014-01-01

    Network biology integrates different kinds of data, including physical or functional networks and disease gene sets, to interpret human disease. A clique (maximal complete subgraph) in a protein-protein interaction network is a topological module and possesses inherently biological significance. A disease-related clique possibly associates with complex diseases. Fully identifying disease components in a clique is conductive to uncovering disease mechanisms. This paper proposes an approach of predicting disease proteins based on cliques in a protein-protein interaction network. To tolerate false positive and negative interactions in protein networks, extending cliques and scoring predicted disease proteins with gene ontology terms are introduced to the clique-based method. Precisions of predicted disease proteins are verified by disease phenotypes and steadily keep to more than 95%. The predicted disease proteins associated with cliques can partly complement mapping between genotype and phenotype, and provide clues for understanding the pathogenesis of serious diseases.

  7. Specific ion and buffer effects on protein-protein interactions of a monoclonal antibody.

    PubMed

    Roberts, D; Keeling, R; Tracka, M; van der Walle, C F; Uddin, S; Warwicker, J; Curtis, R

    2015-01-05

    Better predictive ability of salt and buffer effects on protein-protein interactions requires separating out contributions due to ionic screening, protein charge neutralization by ion binding, and salting-in(out) behavior. We have carried out a systematic study by measuring protein-protein interactions for a monoclonal antibody over an ionic strength range of 25 to 525 mM at 4 pH values (5, 6.5, 8, and 9) in solutions containing sodium chloride, calcium chloride, sodium sulfate, or sodium thiocyante. The salt ions are chosen so as to represent a range of affinities for protein charged and noncharged groups. The results are compared to effects of various buffers including acetate, citrate, phosphate, histidine, succinate, or tris. In low ionic strength solutions, anion binding affinity is reflected by the ability to reduce protein-protein repulsion, which follows the order thiocyanate > sulfate > chloride. The sulfate specific effect is screened at the same ionic strength required to screen the pH dependence of protein-protein interactions indicating sulfate binding only neutralizes protein charged groups. Thiocyanate specific effects occur over a larger ionic strength range reflecting adsorption to charged and noncharged regions of the protein. The latter leads to salting-in behavior and, at low pH, a nonmonotonic interaction profile with respect to sodium thiocyanate concentration. The effects of thiocyanate can not be rationalized in terms of only neutralizing double layer forces indicating the presence of an additional short-ranged protein-protein attraction at moderate ionic strength. Conversely, buffer specific effects can be explained through a charge neutralization mechanism, where buffers with greater valency are more effective at reducing double layer forces at low pH. Citrate binding at pH 6.5 leads to protein charge inversion and the formation of attractive electrostatic interactions. Throughout the report, we highlight similarities in the measured

  8. Assessing Energetic Contributions to Binding from a Disordered Region in a Protein-Protein Interaction

    SciTech Connect

    S Cho; C Swaminathan; D Bonsor; M Kerzic; R Guan; J Yang; C Kieke; P Anderson; D Kranz; et al.

    2011-12-31

    Many functional proteins are at least partially disordered prior to binding. Although the structural transitions upon binding of disordered protein regions can influence the affinity and specificity of protein complexes, their precise energetic contributions to binding are unknown. Here, we use a model protein-protein interaction system in which a locally disordered region has been modified by directed evolution to quantitatively assess the thermodynamic and structural contributions to binding of disorder-to-order transitions. Through X-ray structure determination of the protein binding partners before and after complex formation and isothermal titration calorimetry of the interactions, we observe a correlation between protein ordering and binding affinity for complexes along this affinity maturation pathway. Additionally, we show that discrepancies between observed and calculated heat capacities based on buried surface area changes in the protein complexes can be explained largely by heat capacity changes that would result solely from folding the locally disordered region. Previously developed algorithms for predicting binding energies of protein-protein interactions, however, are unable to correctly model the energetic contributions of the structural transitions in our model system. While this highlights the shortcomings of current computational methods in modeling conformational flexibility, it suggests that the experimental methods used here could provide training sets of molecular interactions for improving these algorithms and further rationalizing molecular recognition in protein-protein interactions.

  9. A novel microfluidics-based method for probing weak protein-protein interactions.

    PubMed

    Tan, Darren Cherng-wen; Wijaya, I Putu Mahendra; Andreasson-Ochsner, Mirjam; Vasina, Elena Nikolaevna; Nallani, Madhavan; Hunziker, Walter; Sinner, Eva-Kathrin

    2012-08-07

    We report the use of a novel microfluidics-based method to detect weak protein-protein interactions between membrane proteins. The tight junction protein, claudin-2, synthesised in vitro using a cell-free expression system in the presence of polymer vesicles as membrane scaffolds, was used as a model membrane protein. Individual claudin-2 molecules interact weakly, although the cumulative effect of these interactions is significant. This effect results in a transient decrease of average vesicle dispersivity and reduction in transport speed of claudin-2-functionalised vesicles. Polymer vesicles functionalised with claudin-2 were perfused through a microfluidic channel and the time taken to traverse a defined distance within the channel was measured. Functionalised vesicles took 1.19 to 1.69 times longer to traverse this distance than unfunctionalised ones. Coating the channel walls with protein A and incubating the vesicles with anti-claudin-2 antibodies prior to perfusion resulted in the functionalised vesicles taking 1.75 to 2.5 times longer to traverse this distance compared to the controls. The data show that our system is able to detect weak as well as strong protein-protein interactions. This system offers researchers a portable, easily operated and customizable platform for the study of weak protein-protein interactions, particularly between membrane proteins.

  10. Biochemical and Physiological Characterization: Development & Apply Optical Methods for Charaterizing Biochemical Protein-Protein Interactions in MR-1

    SciTech Connect

    Weiss, Shimon

    2006-08-30

    The objectives of this report are to: Develop novel site-specific protein labeling chemistries for assaying protein-protein interactions in MR-1; and development of a novel optical acquisition and data analysis method for characterizing protein-protein interactions in MR-1 model systems. Our work on analyzing protein-protein interactions in MR-1 is divided in four areas: (1) expression and labeling of MR-1 proteins; (2) general scheme for site-specific fluorescent labeling of expressed proteins; (3) methodology development for monitoring protein-protein interactions; and (4) study of protein-protein interactions in MR-1. In this final report, we give an account for our advances in all areas.

  11. Fluorescence Anisotropy as a Tool to Study Protein-protein Interactions.

    PubMed

    Gijsbers, Abril; Nishigaki, Takuya; Sánchez-Puig, Nuria

    2016-10-21

    Protein-protein interactions play an essential role in the function of a living organism. Once an interaction has been identified and validated it is necessary to characterize it at the structural and mechanistic level. Several biochemical and biophysical methods exist for such purpose. Among them, fluorescence anisotropy is a powerful technique particularly used when the fluorescence intensity of a fluorophore-labeled protein remains constant upon protein-protein interaction. In this technique, a fluorophore-labeled protein is excited with vertically polarized light of an appropriate wavelength that selectively excites a subset of the fluorophores according to their relative orientation with the incoming beam. The resulting emission also has a directionality whose relationship in the vertical and horizontal planes defines anisotropy (r) as follows: r=(IVV-IVH)/(IVV+2IVH), where IVV and IVH are the fluorescence intensities of the vertical and horizontal components, respectively. Fluorescence anisotropy is sensitive to the rotational diffusion of a fluorophore, namely the apparent molecular size of a fluorophore attached to a protein, which is altered upon protein-protein interaction. In the present text, the use of fluorescence anisotropy as a tool to study protein-protein interactions was exemplified to address the binding between the protein mutated in the Shwachman-Diamond Syndrome (SBDS) and the Elongation factor like-1 GTPase (EFL1). Conventionally, labeling of a protein with a fluorophore is carried out on the thiol groups (cysteine) or in the amino groups (the N-terminal amine or lysine) of the protein. However, SBDS possesses several cysteines and lysines that did not allow site directed labeling of it. As an alternative technique, the dye 4',5'-bis(1,3,2 dithioarsolan-2-yl) fluorescein was used to specifically label a tetracysteine motif, Cys-Cys-Pro-Gly-Cys-Cys, genetically engineered in the C-terminus of the recombinant SBDS protein. Fitting of the

  12. A New Protein-Protein Interaction Sensor Based on Tripartite Split-GFP Association

    PubMed Central

    Cabantous, Stéphanie; Nguyen, Hau B.; Pedelacq, Jean-Denis; Koraïchi, Faten; Chaudhary, Anu; Ganguly, Kumkum; Lockard, Meghan A.; Favre, Gilles; Terwilliger, Thomas C.; Waldo, Geoffrey S.

    2013-01-01

    Monitoring protein-protein interactions in living cells is key to unraveling their roles in numerous cellular processes and various diseases. Previously described split-GFP based sensors suffer from poor folding and/or self-assembly background fluorescence. Here, we have engineered a micro-tagging system to monitor protein-protein interactions in vivo and in vitro. The assay is based on tripartite association between two twenty amino-acids long GFP tags, GFP10 and GFP11, fused to interacting protein partners, and the complementary GFP1-9 detector. When proteins interact, GFP10 and GFP11 self-associate with GFP1-9 to reconstitute a functional GFP. Using coiled-coils and FRB/FKBP12 model systems we characterize the sensor in vitro and in Escherichia coli. We extend the studies to mammalian cells and examine the FK-506 inhibition of the rapamycin-induced association of FRB/FKBP12. The small size of these tags and their minimal effect on fusion protein behavior and solubility should enable new experiments for monitoring protein-protein association by fluorescence. PMID:24092409

  13. A new protein-protein interaction sensor based on tripartite split-GFP association.

    PubMed

    Cabantous, Stéphanie; Nguyen, Hau B; Pedelacq, Jean-Denis; Koraïchi, Faten; Chaudhary, Anu; Ganguly, Kumkum; Lockard, Meghan A; Favre, Gilles; Terwilliger, Thomas C; Waldo, Geoffrey S

    2013-10-04

    Monitoring protein-protein interactions in living cells is key to unraveling their roles in numerous cellular processes and various diseases. Previously described split-GFP based sensors suffer from poor folding and/or self-assembly background fluorescence. Here, we have engineered a micro-tagging system to monitor protein-protein interactions in vivo and in vitro. The assay is based on tripartite association between two twenty amino-acids long GFP tags, GFP10 and GFP11, fused to interacting protein partners, and the complementary GFP1-9 detector. When proteins interact, GFP10 and GFP11 self-associate with GFP1-9 to reconstitute a functional GFP. Using coiled-coils and FRB/FKBP12 model systems we characterize the sensor in vitro and in Escherichia coli. We extend the studies to mammalian cells and examine the FK-506 inhibition of the rapamycin-induced association of FRB/FKBP12. The small size of these tags and their minimal effect on fusion protein behavior and solubility should enable new experiments for monitoring protein-protein association by fluorescence.

  14. Identification of essential proteins based on ranking edge-weights in protein-protein interaction networks.

    PubMed

    Wang, Yan; Sun, Huiyan; Du, Wei; Blanzieri, Enrico; Viero, Gabriella; Xu, Ying; Liang, Yanchun

    2014-01-01

    Essential proteins are those that are indispensable to cellular survival and development. Existing methods for essential protein identification generally rely on knock-out experiments and/or the relative density of their interactions (edges) with other proteins in a Protein-Protein Interaction (PPI) network. Here, we present a computational method, called EW, to first rank protein-protein interactions in terms of their Edge Weights, and then identify sub-PPI-networks consisting of only the highly-ranked edges and predict their proteins as essential proteins. We have applied this method to publicly-available PPI data on Saccharomyces cerevisiae (Yeast) and Escherichia coli (E. coli) for essential protein identification, and demonstrated that EW achieves better performance than the state-of-the-art methods in terms of the precision-recall and Jackknife measures. The highly-ranked protein-protein interactions by our prediction tend to be biologically significant in both the Yeast and E. coli PPI networks. Further analyses on systematically perturbed Yeast and E. coli PPI networks through randomly deleting edges demonstrate that the proposed method is robust and the top-ranked edges tend to be more associated with known essential proteins than the lowly-ranked edges.

  15. A conserved NAD(+) binding pocket that regulates protein-protein interactions during aging.

    PubMed

    Li, Jun; Bonkowski, Michael S; Moniot, Sébastien; Zhang, Dapeng; Hubbard, Basil P; Ling, Alvin J Y; Rajman, Luis A; Qin, Bo; Lou, Zhenkun; Gorbunova, Vera; Aravind, L; Steegborn, Clemens; Sinclair, David A

    2017-03-24

    DNA repair is essential for life, yet its efficiency declines with age for reasons that are unclear. Numerous proteins possess Nudix homology domains (NHDs) that have no known function. We show that NHDs are NAD(+) (oxidized form of nicotinamide adenine dinucleotide) binding domains that regulate protein-protein interactions. The binding of NAD(+) to the NHD domain of DBC1 (deleted in breast cancer 1) prevents it from inhibiting PARP1 [poly(adenosine diphosphate-ribose) polymerase], a critical DNA repair protein. As mice age and NAD(+) concentrations decline, DBC1 is increasingly bound to PARP1, causing DNA damage to accumulate, a process rapidly reversed by restoring the abundance of NAD(+) Thus, NAD(+) directly regulates protein-protein interactions, the modulation of which may protect against cancer, radiation, and aging.

  16. Structural Instability Tuning as a Regulatory Mechanism in Protein-Protein Interactions

    PubMed Central

    Chen, Li; Balabanidou, Vassilia; Remeta, David P.; Minetti, Conceição A.S.A.; Portaliou, Athina G.; Economou, Anastassios; Kalodimos, Charalampos G.

    2011-01-01

    SUMMARY Protein-protein interactions mediate a vast number of cellular processes. Here we present a regulatory mechanism in protein-protein interactions mediated by finely-tuned structural instability coupled with molecular mimicry. We show that a set of type III secretion (TTS) autoinhibited homodimeric chaperones adopt a molten-globule-like state that transiently exposes the substrate binding site as a means to become rapidly poised for binding to their cognate protein substrates. Packing defects at the homodimeric interface stimulate binding whereas correction of these defects results in less labile chaperones that give rise to non-functional biological systems. The protein substrates use structural mimicry to offset the “weak spots” in the chaperones and to counteract their autoinhibitory conformation. This regulatory mechanism of protein activity is evolutionary conserved among several TSS systems and presents a lucid example of functional advantage conferred upon a biological system by finely-tuned structural instability. PMID:22152477

  17. Predicting Pharmacodynamic Drug-Drug Interactions through Signaling Propagation Interference on Protein-Protein Interaction Networks

    PubMed Central

    Park, Kyunghyun; Kim, Docyong; Ha, Suhyun; Lee, Doheon

    2015-01-01

    As pharmacodynamic drug-drug interactions (PD DDIs) could lead to severe adverse effects in patients, it is important to identify potential PD DDIs in drug development. The signaling starting from drug targets is propagated through protein-protein interaction (PPI) networks. PD DDIs could occur by close interference on the same targets or within the same pathways as well as distant interference through cross-talking pathways. However, most of the previous approaches have considered only close interference by measuring distances between drug targets or comparing target neighbors. We have applied a random walk with restart algorithm to simulate signaling propagation from drug targets in order to capture the possibility of their distant interference. Cross validation with DrugBank and Kyoto Encyclopedia of Genes and Genomes DRUG shows that the proposed method outperforms the previous methods significantly. We also provide a web service with which PD DDIs for drug pairs can be analyzed at http://biosoft.kaist.ac.kr/targetrw. PMID:26469276

  18. Characterization of protein-protein interaction interfaces from a single species.

    PubMed

    Talavera, David; Robertson, David L; Lovell, Simon C

    2011-01-01

    Most proteins attain their biological functions through specific interactions with other proteins. Thus, the study of protein-protein interactions and the interfaces that mediate these interactions is of prime importance for the understanding of biological function. In particular the precise determinants of binding specificity and their contributions to binding energy within protein interfaces are not well understood. In order to better understand these determinants an appropriate description of the interaction surface is needed. Available data from the yeast Saccharomyces cerevisiae allow us to focus on a single species and to use all the available structures, correcting for redundancy, instead of using structural representatives. This allows us to control for potentially confounding factors that may affect sequence propensities. We find a significant contribution of main-chain atoms to protein-protein interactions. These include interactions both with other main-chain and side-chain atoms on the interacting chain. We find that the type of interaction depends on both amino acid and secondary structure type involved in the contact. For example, residues in α-helices and large amino acids are the most likely to be involved in interactions through their side-chain atoms. We find an intriguing homogeneity when calculating the average solvation energy of different areas of the protein surface. Unexpectedly, homo- and hetero-complexes have quite similar results for all analyses. Our findings demonstrate that the manner in which protein-protein interactions are formed is determined by the residue type and the secondary structure found in the interface. However the homogeneity of the desolvation energy despite heterogeneity of interface properties suggests a complex relationship between interface composition and binding energy.

  19. MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data

    PubMed Central

    Ohue, Masahito; Matsuzaki, Yuri; Uchikoga, Nobuyuki; Ishida, Takashi; Akiyama, Yutaka

    2014-01-01

    The elucidation of protein-protein interaction (PPI) networks is important for understanding cellular structure and function and structure-based drug design. However, the development of an effective method to conduct exhaustive PPI screening represents a computational challenge. We have been investigating a protein docking approach based on shape complementarity and physicochemical properties. We describe here the development of the protein-protein docking software package “MEGADOCK” that samples an extremely large number of protein dockings at high speed. MEGADOCK reduces the calculation time required for docking by using several techniques such as a novel scoring function called the real Pairwise Shape Complementarity (rPSC) score. We showed that MEGADOCK is capable of exhaustive PPI screening by completing docking calculations 7.5 times faster than the conventional docking software, ZDOCK, while maintaining an acceptable level of accuracy. When MEGADOCK was applied to a subset of a general benchmark dataset to predict 120 relevant interacting pairs from 120 x 120 = 14,400 combinations of proteins, an F-measure value of 0.231 was obtained. Further, we showed that MEGADOCK can be applied to a large-scale protein-protein interaction-screening problem with accuracy better than random. When our approach is combined with parallel high-performance computing systems, it is now feasible to search and analyze protein-protein interactions while taking into account three-dimensional structures at the interactome scale. MEGADOCK is freely available at http://www.bi.cs.titech.ac.jp/megadock. PMID:23855673

  20. α/β-Peptide Foldamers Targeting Intracellular Protein-Protein Interactions with Activity in Living Cells.

    PubMed

    Checco, James W; Lee, Erinna F; Evangelista, Marco; Sleebs, Nerida J; Rogers, Kelly; Pettikiriarachchi, Anne; Kershaw, Nadia J; Eddinger, Geoffrey A; Belair, David G; Wilson, Julia L; Eller, Chelcie H; Raines, Ronald T; Murphy, William L; Smith, Brian J; Gellman, Samuel H; Fairlie, W Douglas

    2015-09-09

    Peptides can be developed as effective antagonists of protein-protein interactions, but conventional peptides (i.e., oligomers of l-α-amino acids) suffer from significant limitations in vivo. Short half-lives due to rapid proteolytic degradation and an inability to cross cell membranes often preclude biological applications of peptides. Oligomers that contain both α- and β-amino acid residues ("α/β-peptides") manifest decreased susceptibility to proteolytic degradation, and when properly designed these unnatural oligomers can mimic the protein-recognition properties of analogous "α-peptides". This report documents an extension of the α/β-peptide approach to target intracellular protein-protein interactions. Specifically, we have generated α/β-peptides based on a "stapled" Bim BH3 α-peptide, which contains a hydrocarbon cross-link to enhance α-helix stability. We show that a stapled α/β-peptide can structurally and functionally mimic the parent stapled α-peptide in its ability to enter certain types of cells and block protein-protein interactions associated with apoptotic signaling. However, the α/β-peptide is nearly 100-fold more resistant to proteolysis than is the parent stapled α-peptide. These results show that backbone modification, a strategy that has received relatively little attention in terms of peptide engineering for biomedical applications, can be combined with more commonly deployed peripheral modifications such as side chain cross-linking to produce synergistic benefits.

  1. The visible touch: in planta visualization of protein-protein interactions by fluorophore-based methods

    PubMed Central

    Bhat, Riyaz A; Lahaye, Thomas; Panstruga, Ralph

    2006-01-01

    Non-invasive fluorophore-based protein interaction assays like fluorescence resonance energy transfer (FRET) and bimolecular fluorescence complementation (BiFC, also referred to as "split YFP") have been proven invaluable tools to study protein-protein interactions in living cells. Both methods are now frequently used in the plant sciences and are likely to develop into standard techniques for the identification, verification and in-depth analysis of polypeptide interactions. In this review, we address the individual strengths and weaknesses of both approaches and provide an outlook about new directions and possible future developments for both techniques. PMID:16800872

  2. A conserved patch of hydrophobic amino acids modulates Myb activity by mediating protein-protein interactions.

    PubMed

    Dukare, Sandeep; Klempnauer, Karl-Heinz

    2016-07-01

    The transcription factor c-Myb plays a key role in the control of proliferation and differentiation in hematopoietic progenitor cells and has been implicated in the development of leukemia and certain non-hematopoietic tumors. c-Myb activity is highly dependent on the interaction with the coactivator p300 which is mediated by the transactivation domain of c-Myb and the KIX domain of p300. We have previously observed that conservative valine-to-isoleucine amino acid substitutions in a conserved stretch of hydrophobic amino acids have a profound effect on Myb activity. Here, we have explored the function of the hydrophobic region as a mediator of protein-protein interactions. We show that the hydrophobic region facilitates Myb self-interaction and binding of the histone acetyl transferase Tip60, a previously identified Myb interacting protein. We show that these interactions are affected by the valine-to-isoleucine amino acid substitutions and suppress Myb activity by interfering with the interaction of Myb and the KIX domain of p300. Taken together, our work identifies the hydrophobic region in the Myb transactivation domain as a binding site for homo- and heteromeric protein interactions and leads to a picture of the c-Myb transactivation domain as a composite protein binding region that facilitates interdependent protein-protein interactions of Myb with regulatory proteins.

  3. BindML/BindML+: Detecting Protein-Protein Interaction Interface Propensity from Amino Acid Substitution Patterns.

    PubMed

    Wei, Qing; La, David; Kihara, Daisuke

    2017-01-01

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

  4. Surface energetics and protein-protein interactions: analysis and mechanistic implications

    NASA Astrophysics Data System (ADS)

    Peri, Claudio; Morra, Giulia; Colombo, Giorgio

    2016-04-01

    Understanding protein-protein interactions (PPI) at the molecular level is a fundamental task in the design of new drugs, the prediction of protein function and the clarification of the mechanisms of (dis)regulation of biochemical pathways. In this study, we use a novel computational approach to investigate the energetics of aminoacid networks located on the surface of proteins, isolated and in complex with their respective partners. Interestingly, the analysis of individual proteins identifies patches of surface residues that, when mapped on the structure of their respective complexes, reveal regions of residue-pair couplings that extend across the binding interfaces, forming continuous motifs. An enhanced effect is visible across the proteins of the dataset forming larger quaternary assemblies. The method indicates the presence of energetic signatures in the isolated proteins that are retained in the bound form, which we hypothesize to determine binding orientation upon complex formation. We propose our method, BLUEPRINT, as a complement to different approaches ranging from the ab-initio characterization of PPIs, to protein-protein docking algorithms, for the physico-chemical and functional investigation of protein-protein interactions.

  5. Towards a map of the Populus biomass protein-protein interaction network

    SciTech Connect

    Beers, Eric; Brunner, Amy; Helm, Richard; Dickerman, Allan

    2015-07-31

    Biofuels can be produced from a variety of plant feedstocks. The value of a particular feedstock for biofuels production depends in part on the degree of difficulty associated with the extraction of fermentable sugars from the plant biomass. The wood of trees is potentially a rich source fermentable sugars. However, the sugars in wood exist in a tightly cross-linked matrix of cellulose, hemicellulose, and lignin, making them largely recalcitrant to release and fermentation for biofuels production. Before breeders and genetic engineers can effectively develop plants with reduced recalcitrance to fermentation, it is necessary to gain a better understanding of the fundamental biology of the mechanisms responsible for wood formation. Regulatory, structural, and enzymatic proteins are required for the complicated process of wood formation. To function properly, proteins must interact with other proteins. Yet, very few of the protein-protein interactions necessary for wood formation are known. The main objectives of this project were to 1) identify new protein-protein interactions relevant to wood formation, and 2) perform in-depth characterizations of selected protein-protein interactions. To identify relevant protein-protein interactions, we cloned a set of approximately 400 genes that were highly expressed in the wood-forming tissue (known as secondary xylem) of poplar (Populus trichocarpa). We tested whether the proteins encoded by these biomass genes interacted with each other in a binary matrix design using the yeast two-hybrid (Y2H) method for protein-protein interaction discovery. We also tested a subset of the 400 biomass proteins for interactions with all proteins present in wood-forming tissue of poplar in a biomass library screen design using Y2H. Together, these two Y2H screens yielded over 270 interactions involving over 75 biomass proteins. For the second main objective we selected several interacting pairs or groups of interacting proteins for in

  6. Categorizing biases in high-confidence high-throughput protein-protein interaction data sets.

    PubMed

    Yu, Xueping; Ivanic, Joseph; Memisević, Vesna; Wallqvist, Anders; Reifman, Jaques

    2011-12-01

    We characterized and evaluated the functional attributes of three yeast high-confidence protein-protein interaction data sets derived from affinity purification/mass spectrometry, protein-fragment complementation assay, and yeast two-hybrid experiments. The interacting proteins retrieved from these data sets formed distinct, partially overlapping sets with different protein-protein interaction characteristics. These differences were primarily a function of the deployed experimental technologies used to recover these interactions. This affected the total coverage of interactions and was especially evident in the recovery of interactions among different functional classes of proteins. We found that the interaction data obtained by the yeast two-hybrid method was the least biased toward any particular functional characterization. In contrast, interacting proteins in the affinity purification/mass spectrometry and protein-fragment complementation assay data sets were over- and under-represented among distinct and different functional categories. We delineated how these differences affected protein complex organization in the network of interactions, in particular for strongly interacting complexes (e.g. RNA and protein synthesis) versus weak and transient interacting complexes (e.g. protein transport). We quantified methodological differences in detecting protein interactions from larger protein complexes, in the correlation of protein abundance among interacting proteins, and in their connectivity of essential proteins. In the latter case, we showed that minimizing inherent methodology biases removed many of the ambiguous conclusions about protein essentiality and protein connectivity. We used these findings to rationalize how biological insights obtained by analyzing data sets originating from different sources sometimes do not agree or may even contradict each other. An important corollary of this work was that discrepancies in biological insights did not

  7. Detecting overlapping protein complexes by rough-fuzzy clustering in protein-protein interaction networks.

    PubMed

    Wu, Hao; Gao, Lin; Dong, Jihua; Yang, Xiaofei

    2014-01-01

    In this paper, we present a novel rough-fuzzy clustering (RFC) method to detect overlapping protein complexes in protein-protein interaction (PPI) networks. RFC focuses on fuzzy relation model rather than graph model by integrating fuzzy sets and rough sets, employs the upper and lower approximations of rough sets to deal with overlapping complexes, and calculates the number of complexes automatically. Fuzzy relation between proteins is established and then transformed into fuzzy equivalence relation. Non-overlapping complexes correspond to equivalence classes satisfying certain equivalence relation. To obtain overlapping complexes, we calculate the similarity between one protein and each complex, and then determine whether the protein belongs to one or multiple complexes by computing the ratio of each similarity to maximum similarity. To validate RFC quantitatively, we test it in Gavin, Collins, Krogan and BioGRID datasets. Experiment results show that there is a good correspondence to reference complexes in MIPS and SGD databases. Then we compare RFC with several previous methods, including ClusterONE, CMC, MCL, GCE, OSLOM and CFinder. Results show the precision, sensitivity and separation are 32.4%, 42.9% and 81.9% higher than mean of the five methods in four weighted networks, and are 0.5%, 11.2% and 66.1% higher than mean of the six methods in five unweighted networks. Our method RFC works well for protein complexes detection and provides a new insight of network division, and it can also be applied to identify overlapping community structure in social networks and LFR benchmark networks.

  8. Bayesian inference for genomic data integration reduces misclassification rate in predicting protein-protein interactions.

    PubMed

    Xing, Chuanhua; Dunson, David B

    2011-07-01

    Protein-protein interactions (PPIs) are essential to most fundamental cellular processes. There has been increasing interest in reconstructing PPIs networks. However, several critical difficulties exist in obtaining reliable predictions. Noticeably, false positive rates can be as high as >80%. Error correction from each generating source can be both time-consuming and inefficient due to the difficulty of covering the errors from multiple levels of data processing procedures within a single test. We propose a novel Bayesian integration method, deemed nonparametric Bayes ensemble learning (NBEL), to lower the misclassification rate (both false positives and negatives) through automatically up-weighting data sources that are most informative, while down-weighting less informative and biased sources. Extensive studies indicate that NBEL is significantly more robust than the classic naïve Bayes to unreliable, error-prone and contaminated data. On a large human data set our NBEL approach predicts many more PPIs than naïve Bayes. This suggests that previous studies may have large numbers of not only false positives but also false negatives. The validation on two human PPIs datasets having high quality supports our observations. Our experiments demonstrate that it is feasible to predict high-throughput PPIs computationally with substantially reduced false positives and false negatives. The ability of predicting large numbers of PPIs both reliably and automatically may inspire people to use computational approaches to correct data errors in general, and may speed up PPIs prediction with high quality. Such a reliable prediction may provide a solid platform to other studies such as protein functions prediction and roles of PPIs in disease susceptibility.

  9. Effective protein-protein interaction from structure factor data of a lysozyme solution

    SciTech Connect

    Abramo, M. C.; Caccamo, C.; Costa, D.; Ruberto, R.; Wanderlingh, U.; Cavero, M.; Pellicane, G.

    2013-08-07

    We report the determination of an effective protein-protein central potential for a lysozyme solution, obtained from the direct inversion of the total structure factor of the system, as extracted from small angle neutron scattering. The inversion scheme rests on a hypernetted-chain relationship between the effective potential and the structural functions, and is preliminarily tested for the case of a Lennard-Jones interaction. The characteristics of our potential are discussed in comparison with current models of effective interactions in complex fluids. The phase behavior predictions are also investigated.

  10. Prediction of the Ebola virus infection related human genes using protein-protein interaction network.

    PubMed

    Cao, HuanHuan; Zhang, YuHang; Zhao, Jia; Zhu, Liucun; Wang, Yi; Li, JiaRui; Feng, Yuanming; Zhang, Ning

    2017-03-10

    Ebola hemorrhagic fever (EHF) is caused by Ebola virus (EBOV). It is reported that human could be infected by EBOV with a high fatality rate. However, association factors between EBOV and host still tend to be ambiguous. According to the "guilt by association" (GBA) principle, proteins interacting with each other are very likely to function similarly or the same. Based on this assumption, we tried to obtain EBOV infection-related human genes in a protein-protein interaction network using Dijkstra algorithm. We hope it could contribute to the discovery of novel effective treatments. Finally, 15 genes were selected as potential EBOV infection-related human genes.

  11. Efficient fold-change detection based on protein-protein interactions.

    PubMed

    Buijsman, W; Sheinman, M

    2014-02-01

    Various biological sensory systems exhibit a response to a relative change of the stimulus, often referred to as fold-change detection. In the past few years, fold-change detecting mechanisms, based on transcriptional networks, have been proposed. Here we present a fold-change detecting mechanism, based on protein-protein interactions, consisting of two interacting proteins. This mechanism does not consume chemical energy and is not subject to transcriptional and translational noise, in contrast to previously proposed mechanisms. We show by analytical and numerical calculations that the mechanism is robust and can have a fast, precise, and efficient response for parameters that are relevant to eukaryotic cells.

  12. Efficient fold-change detection based on protein-protein interactions

    NASA Astrophysics Data System (ADS)

    Buijsman, W.; Sheinman, M.

    2014-02-01

    Various biological sensory systems exhibit a response to a relative change of the stimulus, often referred to as fold-change detection. In the past few years, fold-change detecting mechanisms, based on transcriptional networks, have been proposed. Here we present a fold-change detecting mechanism, based on protein-protein interactions, consisting of two interacting proteins. This mechanism does not consume chemical energy and is not subject to transcriptional and translational noise, in contrast to previously proposed mechanisms. We show by analytical and numerical calculations that the mechanism is robust and can have a fast, precise, and efficient response for parameters that are relevant to eukaryotic cells.

  13. Screening for in planta protein-protein interactions combining bimolecular fluorescence complementation with flow cytometry

    PubMed Central

    2012-01-01

    Understanding protein and gene function requires identifying interaction partners using biochemical, molecular or genetic tools. In plants, searching for novel protein-protein interactions is limited to protein purification assays, heterologous in vivo systems such as the yeast-two-hybrid or mutant screens. Ideally one would be able to search for novel protein partners in living plant cells. We demonstrate that it is possible to screen for novel protein-protein interactions from a random library in protoplasted Arabidopsis plant cells and recover some of the interacting partners. Our screen is based on capturing the bi-molecular complementation of mYFP between an YN-bait fusion partner and a completely random prey YC-cDNA library with FACS. The candidate interactions were confirmed using in planta BiFC assays and in planta FRET-FLIM assays. From this work, we show that the well characterized protein Calcium Dependent Protein Kinase 3 (CPK3) interacts with APX3, HMGB5, ORP2A and a ricin B-related lectin domain containing protein At2g39050. This is one of the first randomin planta screens to be successfully employed. PMID:22789293

  14. Energy landscape of all-atom protein-protein interactions revealed by multiscale enhanced sampling.

    PubMed

    Moritsugu, Kei; Terada, Tohru; Kidera, Akinori

    2014-10-01

    Protein-protein interactions are regulated by a subtle balance of complicated atomic interactions and solvation at the interface. To understand such an elusive phenomenon, it is necessary to thoroughly survey the large configurational space from the stable complex structure to the dissociated states using the all-atom model in explicit solvent and to delineate the energy landscape of protein-protein interactions. In this study, we carried out a multiscale enhanced sampling (MSES) simulation of the formation of a barnase-barstar complex, which is a protein complex characterized by an extraordinary tight and fast binding, to determine the energy landscape of atomistic protein-protein interactions. The MSES adopts a multicopy and multiscale scheme to enable for the enhanced sampling of the all-atom model of large proteins including explicit solvent. During the 100-ns MSES simulation of the barnase-barstar system, we observed the association-dissociation processes of the atomistic protein complex in solution several times, which contained not only the native complex structure but also fully non-native configurations. The sampled distributions suggest that a large variety of non-native states went downhill to the stable complex structure, like a fast folding on a funnel-like potential. This funnel landscape is attributed to dominant configurations in the early stage of the association process characterized by near-native orientations, which will accelerate the native inter-molecular interactions. These configurations are guided mostly by the shape complementarity between barnase and barstar, and lead to the fast formation of the final complex structure along the downhill energy landscape.

  15. Identification of protein-protein interactions of the occlusion-derived virus-associated proteins of Helicoverpa armigera nucleopolyhedrovirus.

    PubMed

    Peng, Ke; Wu, Minzhi; Deng, Fei; Song, Jingjiao; Dong, Chunsheng; Wang, Hualin; Hu, Zhihong

    2010-03-01

    The purpose of this study was to identify protein-protein interactions among the components of the occlusion-derived virus (ODV) of Helicoverpa armigera nucleopolyhedrovirus (HearNPV), a group II alphabaculovirus in the family Baculoviridae. To achieve this, 39 selected genes of potential ODV structural proteins were cloned and expressed in the Gal4 yeast two-hybrid (Y2H) system. The direct-cross Y2H assays identified 22 interactions comprising 13 binary interactions [HA9-ODV-EC43, ODV-E56-38K, ODV-E56-PIF3, LEF3-helicase, LEF3-alkaline nuclease (AN), GP41-38K, GP41-HA90, 38K-PIF3, 38K-PIF2, VP80-HA100, ODV-E66-PIF3, ODV-E66-PIF2 and PIF3-PIF2] and nine self-associations (IE1, HA44, LEF3, HA66, GP41, CG30, 38K, PIF3 and P24). Five of these interactions - LEF3-helicase and LEF3-AN, and the self-associations of IE1, LEF3 and 38K - have been reported previously in Autographa californica multiple nucleopolyhedrovirus. As HA44 and HA100 were two newly identified ODV proteins of group II viruses, their interactions were further confirmed. The self-association of HA44 was verified with a His pull-down assay and the interaction of VP80-HA100 was confirmed by a co-immunoprecipitation assay. A summary of the protein-protein interactions of baculoviruses reported so far, comprising 68 interactions with 45 viral proteins and five host proteins, is presented, which will facilitate our understanding of the molecular mechanisms of baculovirus infection.

  16. Dataset of integrin-linked kinase protein: Protein interactions in cardiomyocytes identified by mass spectrometry.

    PubMed

    Traister, Alexandra; Lu, Mingliang; Coles, John G; Maynes, Jason T

    2016-06-01

    Using hearts from mice overexpressing integrin linked kinase (ILK) behind the cardiac specific promoter αMHC, we have performed immunoprecipitation and mass spectrometry to identify novel ILK protein:protein interactions that regulate cardiomyocyte activity and calcium flux. Integrin linked kinase complexes were captured from mouse heart lysates using a commercial antibody, with subsequent liquid chromatography tandem mass spectral analysis. Interacting partners were identified using the MASCOT server, and important interactions verified using reverse immunoprecipitation and mass spectrometry. All ILK interacting proteins were identified in a non-biased manner, and are stored in the ProteomeXchange Consortium via the PRIDE partner repository (reference ID PRIDE: PXD001053). The functional role of identified ILK interactions in cardiomyocyte function and arrhythmia were subsequently confirmed in human iPSC-cardiomyocytes.

  17. A method for investigating protein-protein interactions related to Salmonella typhimurium pathogenesis

    SciTech Connect

    Chowdhury, Saiful M.; Shi, Liang; Yoon, Hyunjin; Ansong, Charles; Rommereim, Leah M.; Norbeck, Angela D.; Auberry, Kenneth J.; Moore, R. J.; Adkins, Joshua N.; Heffron, Fred; Smith, Richard D.

    2009-02-10

    We successfully modified an existing method to investigate protein-protein interactions in the pathogenic bacterium Salmonella typhimurium (STM). This method includes i) addition of a histidine-biotin-histidine tag to the bait proteins via recombinant DNA techniques; ii) in vivo cross-linking with formaldehyde; iii) tandem affinity purification of bait proteins under fully denaturing conditions; and iv) identification of the proteins cross-linked to the bait proteins by liquid-chromatography in conjunction with tandem mass-spectrometry. In vivo cross-linking stabilized protein interactions permitted the subsequent two-step purification step conducted under denaturing conditions. The two-step purification greatly reduced nonspecific binding of non-cross-linked proteins to bait proteins. Two different negative controls were employed to reduce false-positive identification. In an initial demonstration of this approach, we tagged three selected STM proteins- HimD, PduB and PhoP- with known binding partners that ranged from stable (e.g., HimD) to transient (i.e., PhoP). Distinct sets of interacting proteins were identified with each bait protein, including the known binding partners such as HimA for HimD, as well as anticipated and unexpected binding partners. Our results suggest that novel protein-protein interactions may be critical to pathogenesis by Salmonella typhimurium. .

  18. Novel protein-protein interaction family proteins involved in chloroplast movement response.

    PubMed

    Kodama, Yutaka; Suetsugu, Noriyuki; Wada, Masamitsu

    2011-04-01

    To optimize photosynthetic activity, chloroplasts change their intracellular location in response to ambient light conditions; chloroplasts move toward low intensity light to maximize light capture, and away from high intensity light to avoid photodamage. Although several proteins have been reported to be involved in the chloroplast photorelocation movement response, any physical interaction among them was not found so far. We recently found a physical interaction between two plant-specific coiled-coil proteins, WEB1 (Weak Chloroplast Movement under Blue Light 1) and PMI2 (Plastid Movement Impaired 2), that were identified to regulate chloroplast movement velocity. Since the both coiled-coil regions of WEB1 and PMI2 were classified into an uncharacterized protein family having DUF827 (DUF: Domain of Unknown Function) domain, it was the first report that DUF827 proteins could mediate protein-protein interaction. In this mini-review article, we discuss regarding molecular function of WEB1 and PMI2, and also define a novel protein family composed of WEB1, PMI2 and WEB1/PMI2-like proteins for protein-protein interaction in land plants.

  19. Detection of protein-protein interactions using Aequorea victoria bioluminescence resonance energy transfer

    NASA Astrophysics Data System (ADS)

    Vinokurov, Leonid M.; Gorokhovatsky, Andrey Y.; Rudenko, Natalia V.; Marchenkov, Victor V.; Skosyrev, Vitaly S.; Arzhanov, Maxim A.; Zakharov, Mikhail V.; Burkhardt, Nils; Semisotnov, Gennady V.; Alakhov, Yuli B.

    2003-07-01

    Bioluminescence resonance energy transfer (BRET) is a naturally occurring phenomenon taking place in some marine coelenterates. Emission of light in these organisms involves the energy transfer between chromophores of donor luciferase and acceptor fluorescent protein. Due to the strict dependence of BRET efficiency on the inter-chromophore distance, the phenomenon has been applied to study protein-protein interactions by fusing interacting partners with either donor or acceptor proteins. Here we describe a BRET-based homogeneous protein-protein interaction assay exploiting novel donor-acceptor pair formed by photoproteins of jellyfish Aequorea victoria bioluminescent system, aequorin and green fluorescent protein enhanced variant (EGFP). Two known interacting proteins, streptavidin (SAV) and biotin carboxyl carrier protein (BCCP) were fused, respectively, with aequorin and EGFP. The fusions were purified after expression of the corresponding genes in Escherichia coli cells. Association of SAV-Aequorin and BCCP-EGFP was followed by BRET between aequorin (donor) and EGFP (acceptor) resulting in significantly increasing 510 nm and decreasing 470 nm bioluminescence intensity. It was shown that free biotin inhibited BRET due to its competition with BCCP-EGFP for binding to SAV-Aequorin. These properties were exploited to demonstrate competitive homogeneous BRET assay for biotin.

  20. Uncovering Viral Protein-Protein Interactions and their Role in Arenavirus Life Cycle

    PubMed Central

    Loureiro, Maria Eugenia; D’Antuono, Alejandra; Levingston Macleod, Jesica M.; López, Nora

    2012-01-01

    The Arenaviridae family includes widely distributed pathogens that cause severe hemorrhagic fever in humans. Replication and packaging of their single-stranded RNA genome involve RNA recognition by viral proteins and a number of key protein-protein interactions. Viral RNA synthesis is directed by the virus-encoded RNA dependent-RNA polymerase (L protein) and requires viral RNA encapsidation by the Nucleoprotein. In addition to the role that the interaction between L and the Nucleoprotein may have in the replication process, polymerase activity appears to be modulated by the association between L and the small multifunctional Z protein. Z is also a structural component of the virions that plays an essential role in viral morphogenesis. Indeed, interaction of the Z protein with the Nucleoprotein is critical for genome packaging. Furthermore, current evidence suggests that binding between Z and the viral envelope glycoprotein complex is required for virion infectivity, and that Z homo-oligomerization is an essential step for particle assembly and budding. Efforts to understand the molecular basis of arenavirus life cycle have revealed important details on these viral protein-protein interactions that will be reviewed in this article. PMID:23170177

  1. Essential protein identification based on essential protein-protein interaction prediction by Integrated Edge Weights.

    PubMed

    Jiang, Yuexu; Wang, Yan; Pang, Wei; Chen, Liang; Sun, Huiyan; Liang, Yanchun; Blanzieri, Enrico

    2015-07-15

    Essential proteins play a crucial role in cellular survival and development process. Experimentally, essential proteins are identified by gene knockouts or RNA interference, which are expensive and often fatal to the target organisms. Regarding this, an alternative yet important approach to essential protein identification is through computational prediction. Existing computational methods predict essential proteins based on their relative densities in a protein-protein interaction (PPI) network. Degree, betweenness, and other appropriate criteria are often used to measure the relative density. However, no matter what criterion is used, a protein is actually ordered by the attributes of this protein per se. In this research, we presented a novel computational method, Integrated Edge Weights (IEW), to first rank protein-protein interactions by integrating their edge weights, and then identified sub PPI networks consisting of those highly-ranked edges, and finally regarded the nodes in these sub networks as essential proteins. We evaluated IEW on three model organisms: Saccharomyces cerevisiae (S. cerevisiae), Escherichia coli (E. coli), and Caenorhabditis elegans (C. elegans). The experimental results showed that IEW achieved better performance than the state-of-the-art methods in terms of precision-recall and Jackknife measures. We had also demonstrated that IEW is a robust and effective method, which can retrieve biologically significant modules by its highly-ranked protein-protein interactions for S. cerevisiae, E. coli, and C. elegans. We believe that, with sufficient data provided, IEW can be used to any other organisms' essential protein identification. A website about IEW can be accessed from http://digbio.missouri.edu/IEW/index.html.

  2. HVint: A Strategy for Identifying Novel Protein-Protein Interactions in Herpes Simplex Virus Type 1*

    PubMed Central

    Hernandez, Anna; Buch, Anna; Sodeik, Beate; Cristea, Ileana Mihaela

    2016-01-01

    Human herpesviruses are widespread human pathogens with a remarkable impact on worldwide public health. Despite intense decades of research, the molecular details in many aspects of their function remain to be fully characterized. To unravel the details of how these viruses operate, a thorough understanding of the relationships between the involved components is key. Here, we present HVint, a novel protein-protein intraviral interaction resource for herpes simplex virus type 1 (HSV-1) integrating data from five external sources. To assess each interaction, we used a scoring scheme that takes into consideration aspects such as the type of detection method and the number of lines of evidence. The coverage of the initial interactome was further increased using evolutionary information, by importing interactions reported for other human herpesviruses. These latter interactions constitute, therefore, computational predictions for potential novel interactions in HSV-1. An independent experimental analysis was performed to confirm a subset of our predicted interactions. This subset covers proteins that contribute to nuclear egress and primary envelopment events, including VP26, pUL31, pUL40, and the recently characterized pUL32 and pUL21. Our findings support a coordinated crosstalk between VP26 and proteins such as pUL31, pUS9, and the CSVC complex, contributing to the development of a model describing the nuclear egress and primary envelopment pathways of newly synthesized HSV-1 capsids. The results are also consistent with recent findings on the involvement of pUL32 in capsid maturation and early tegumentation events. Further, they open the door to new hypotheses on virus-specific regulators of pUS9-dependent transport. To make this repository of interactions readily accessible for the scientific community, we also developed a user-friendly and interactive web interface. Our approach demonstrates the power of computational predictions to assist in the design of

  3. Design, synthesis, and evaluation of an alpha-helix mimetic library targeting protein-protein interactions.

    PubMed

    Shaginian, Alex; Whitby, Landon R; Hong, Sukwon; Hwang, Inkyu; Farooqi, Bilal; Searcey, Mark; Chen, Jiandong; Vogt, Peter K; Boger, Dale L

    2009-04-22

    The design and solution-phase synthesis of an alpha-helix mimetic library as an integral component of a small-molecule library targeting protein-protein interactions are described. The iterative design, synthesis, and evaluation of the candidate alpha-helix mimetic was initiated from a precedented triaryl template and refined by screening the designs for inhibition of MDM2/p53 binding. Upon identifying a chemically and biologically satisfactory design and consistent with the screening capabilities of academic collaborators, the corresponding complete library was assembled as 400 mixtures of 20 compounds (20 x 20 x 20-mix), where the added subunits are designed to mimic all possible permutations of the naturally occurring i, i + 4, i + 7 amino acid side chains of an alpha-helix. The library (8000 compounds) was prepared using a solution-phase synthetic protocol enlisting acid/base liquid-liquid extractions for purification on a scale that insures its long-term availability for screening campaigns. Screening of the library for inhibition of MDM2/p53 binding not only identified the lead alpha-helix mimetic upon which the library was based, but also suggests that a digestion of the initial screening results that accompany the use of such a comprehensive library can provide insights into the nature of the interaction (e.g., an alpha-helix mediated protein-protein interaction) and define the key residues and their characteristics responsible for recognition.

  4. 3DProIN: Protein-Protein Interaction Networks and Structure Visualization.

    PubMed

    Li, Hui; Liu, Chunmei

    2014-06-14

    3DProIN is a computational tool to visualize protein-protein interaction networks in both two dimensional (2D) and three dimensional (3D) view. It models protein-protein interactions in a graph and explores the biologically relevant features of the tertiary structures of each protein in the network. Properties such as color, shape and name of each node (protein) of the network can be edited in either 2D or 3D views. 3DProIN is implemented using 3D Java and C programming languages. The internet crawl technique is also used to parse dynamically grasped protein interactions from protein data bank (PDB). It is a java applet component that is embedded in the web page and it can be used on different platforms including Linux, Mac and Window using web browsers such as Firefox, Internet Explorer, Chrome and Safari. It also was converted into a mac app and submitted to the App store as a free app. Mac users can also download the app from our website. 3DProIN is available for academic research at http://bicompute.appspot.com.

  5. Probing protein-protein interaction in biomembranes using Fourier transform infrared spectroscopy.

    PubMed

    Haris, Parvez I

    2013-10-01

    The position, intensity and width of bands in infrared spectra that arise from vibrational modes within a protein can be used to probe protein secondary structure, amino acid side chain structure as well as protein dynamics and stability. FTIR spectroscopic studies on protein-protein interaction have been severely limited due to extensive overlap of peaks, from the interacting proteins. This problem is being addressed by combining data processing and acquisition techniques (difference spectroscopy and two-dimensional spectroscopy) with judicious modifications in the protein primary structure through molecular biological and chemical methods. These include the ability to modify amino acids (site-directed mutagenesis; chemical synthesis) and produce isotopically labelled proteins and peptides. Whilst great progress is being made towards overcoming the congestion of overlapping peaks, the slow progress in the assignment of bands continues to be a major hindrance in the use of infrared spectroscopy for obtaining highly accurate and precise information on protein structure. This review discusses some of these problems and presents examples of infrared studies on protein-protein interaction in biomembrane systems. This article is part of a Special Issue entitled: FTIR in membrane proteins and peptide studies.

  6. Two-hybrid system for characterization of protein-protein interactions in E. coli.

    PubMed

    Hays, L B; Chen, Y S; Hu, J C

    2000-08-01

    The yeast two-hybrid system has been used to characterize many protein-protein interactions. A two-hybrid system for E. coli was constructed in which one hybrid protein bound to a specific DNA site recruits another to an adjacent DNA binding site. The first hybrid comprises a test protein, the bait, fused to a chimeric protein containing the 434 repressor DNA binding domain. In the second hybrid, a second test protein, the prey, is fused downstream of a chimeric protein with the DNA binding specificity of the lambda repressor. Reporters were designed to express cat and lacZ under the control of a low-affinity lambda operator. At low expression levels, lambda repressor hybrids weakly repress the reporter genes. A high-affinity operator recognized by 434 repressor was placed nearby, in a position that does not yield repression by 434 repressor alone. If the test proteins interact, the 434 hybrid bound to the 434 operator stabilizes the binding of the lambda repressor hybrid to the lambda operator, causing increased repression of the reporter genes. Reconstruction experiments with the fos and jun leucine zippers detected protein-protein interactions between either homodimeric or heterodimeric leucine zippers.

  7. [A novel biological pathway expansion method based on the knowledge of protein-protein interactions].

    PubMed

    Zhao, Xiaolei; Zuo, Xiaoyu; Qin, Jiheng; Liang, Yan; Zhang, Naizun; Luan, Yizhao; Rao, Shaoqi

    2014-04-01

    Biological pathways have been widely used in gene function studies; however, the current knowledge for biological pathways is per se incomplete and has to be further expanded. Bioinformatics prediction provides us a cheap but effective way for pathway expansion. Here, we proposed a novel method for biological pathway prediction, by intergrating prior knowledge of protein?protein interactions and Gene Ontology (GO) database. First, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to which the interacting neighbors of a targe gene (at the level of protein?protein interaction) belong were chosen as the candidate pathways. Then, the pathways to which the target gene belong were determined by testing whether the genes in the candidate pathways were enriched in the GO terms to which the target gene were annotated. The protein?protein interaction data obtained from the Human Protein Reference Database (HPRD) and Biological General Repository for Interaction Datasets (BioGRID) were respectively used to predict the pathway attribution(s) of the target gene. The results demanstrated that both the average accuracy (the ratio of the correctly predicted pathways to the totally pathways to which all the target genes were annotated) and the relative accuracy (of the genes with at least one annotated pathway being successful predicted, the percentage of the genes with all the annotated pathways being correctly predicted) for pathway predictions were increased with the number of the interacting neighbours. When the number of interacting neighbours reached 22, the average accuracy was 96.2% (HPRD) and 96.3% (BioGRID), respectively, and the relative accuracy was 93.3% (HPRD) and 84.1% (BioGRID), respectively. Further validation analysis of 89 genes whose pathway knowledge was updated in a new database release indicated that 50 genes were correctly predicted for at least one updated pathway, and 43 genes were accurately predicted for all the updated pathways, giving an

  8. Improving protein-protein interaction article classification using biological domain knowledge.

    PubMed

    Chen, Yifei; Guo, Hongjian; Liu, Feng; Manderick, Bernard

    2015-01-01

    Interaction Article Classification (IAC) is a specific text classification application in biological domain that tries to find out which articles describe Protein-Protein Interactions (PPIs) to help extract PPIs from biological literature more efficiently. However, the existing text representation and feature weighting schemes commonly used for text classification are not well suited for IAC. We capture and utilise biological domain knowledge, i.e. gene mentions also known as protein or gene names in the articles, to address the problem. We put forward a new gene mention order-based approach that highlights the important role of gene mentions to represent the texts. Furthermore, we also incorporate the information concerning gene mentions into a novel feature weighting scheme called Gene Mention-based Term Frequency (GMTF). By conducting experiments, we show that using the proposed representation and weighting schemes, our Interaction Article Classifier (IACer) performs better than other leading systems for the moment.

  9. Prediction of protein-protein interaction network using a multi-objective optimization approach.

    PubMed

    Chowdhury, Archana; Rakshit, Pratyusha; Konar, Amit

    2016-06-01

    Protein-Protein Interactions (PPIs) are very important as they coordinate almost all cellular processes. This paper attempts to formulate PPI prediction problem in a multi-objective optimization framework. The scoring functions for the trial solution deal with simultaneous maximization of functional similarity, strength of the domain interaction profiles, and the number of common neighbors of the proteins predicted to be interacting. The above optimization problem is solved using the proposed Firefly Algorithm with Nondominated Sorting. Experiments undertaken reveal that the proposed PPI prediction technique outperforms existing methods, including gene ontology-based Relative Specific Similarity, multi-domain-based Domain Cohesion Coupling method, domain-based Random Decision Forest method, Bagging with REP Tree, and evolutionary/swarm algorithm-based approaches, with respect to sensitivity, specificity, and F1 score.

  10. Protein-protein Interaction Networks of E. coli and S. cerevisiae are similar

    PubMed Central

    Wuchty, S.; Uetz, Peter

    2014-01-01

    Only recently novel high-throughput binary interaction data in E. coli became available that allowed us to compare experimentally obtained protein-protein interaction networks of prokaryotes and eukaryotes (i.e. E. coli and S. cerevisiae). Utilizing binary-Y2H, co-complex and binary literature curated interaction sets in both organisms we found that characteristics of interaction sets that were determined with the same experimental methods were strikingly similar. While essentiality is frequently considered a question of a protein's increasing number of interactions, we found that binary-Y2H interactions failed to show such a trend in both organisms. Furthermore, essential genes are enriched in protein complexes in both organisms. In turn, binary-Y2H interactions hold more bottleneck interactions than co-complex interactions while both binary-Y2H and co-complex interactions are strongly enriched among co-regulated proteins and transcription factors. We discuss if such similarities are a consequence of the underlying methodology or rather reflect truly different biological patterns. PMID:25431098

  11. DUF581 Is Plant Specific FCS-Like Zinc Finger Involved in Protein-Protein Interaction

    PubMed Central

    K, Muhammed Jamsheer; Laxmi, Ashverya

    2014-01-01

    Zinc fingers are a ubiquitous class of protein domain with considerable variation in structure and function. Zf-FCS is a highly diverged group of C2-C2 zinc finger which is present in animals, prokaryotes and viruses, but not in plants. In this study we identified that a plant specific domain of unknown function, DUF581 is a zf-FCS type zinc finger. Based on HMM-HMM comparison and signature motif similarity we named this domain as FCS-Like Zinc finger (FLZ) domain. A genome wide survey identified that FLZ domain containing genes are bryophytic in origin and this gene family is expanded in spermatophytes. Expression analysis of selected FLZ gene family members of A. thaliana identified an overlapping expression pattern suggesting a possible redundancy in their function. Unlike the zf-FCS domain, the FLZ domain found to be highly conserved in sequence and structure. Using a combination of bioinformatic and protein-protein interaction tools, we identified that FLZ domain is involved in protein-protein interaction. PMID:24901469

  12. Dr. PIAS: an integrative system for assessing the druggability of protein-protein interactions

    PubMed Central

    2011-01-01

    Background The amount of data on protein-protein interactions (PPIs) available in public databases and in the literature has rapidly expanded in recent years. PPI data can provide useful information for researchers in pharmacology and medicine as well as those in interactome studies. There is urgent need for a novel methodology or software allowing the efficient utilization of PPI data in pharmacology and medicine. Results To address this need, we have developed the 'Druggable Protein-protein Interaction Assessment System' (Dr. PIAS). Dr. PIAS has a meta-database that stores various types of information (tertiary structures, drugs/chemicals, and biological functions associated with PPIs) retrieved from public sources. By integrating this information, Dr. PIAS assesses whether a PPI is druggable as a target for small chemical ligands by using a supervised machine-learning method, support vector machine (SVM). Dr. PIAS holds not only known druggable PPIs but also all PPIs of human, mouse, rat, and human immunodeficiency virus (HIV) proteins identified to date. Conclusions The design concept of Dr. PIAS is distinct from other published PPI databases in that it focuses on selecting the PPIs most likely to make good drug targets, rather than merely collecting PPI data. PMID:21303559

  13. Reduced native state stability in crowded cellular environment due to protein-protein interactions

    PubMed Central

    Harada, Ryuhei; Tochio, Naoya; Kigawa, Takanori; Sugita, Yuji; Feig, Michael

    2013-01-01

    The effect of cellular crowding environments on protein structure and stability is a key issue in molecular and cellular biology. The classical view of crowding emphasizes the volume exclusion effect that generally favors compact, native states. Here, results from molecular dynamics simulations and NMR experiments show that protein crowders may destabilize native states via protein-protein interactions. In the model system considered here, mixtures of villin head piece and protein G at high concentrations, villin structures become increasingly destabilized upon increasing crowder concentrations. The denatured states observed in the simulation involve partial unfolding as well as more subtle conformational shifts. The unfolded states remain overall compact and only partially overlap with unfolded ensembles at high temperature and in the presence of urea. NMR measurements on the same systems confirm structural changes upon crowding based on changes of chemical shifts relative to dilute conditions. An analysis of protein-protein interactions and energetic aspects suggests the importance of enthalpic and solvation contributions to the crowding free energies that challenge an entropic-centered view of crowding effects. PMID:23402619

  14. Protein-protein interaction network-based detection of functionally similar proteins within species.

    PubMed

    Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

    2012-07-01

    Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent.

  15. Detection of protein-protein interactions in plants using bimolecular fluorescence complementation.

    PubMed

    Bracha-Drori, Keren; Shichrur, Keren; Katz, Aviva; Oliva, Moran; Angelovici, Ruthie; Yalovsky, Shaul; Ohad, Nir

    2004-11-01

    Protein function is often mediated via formation of stable or transient complexes. Here we report the determination of protein-protein interactions in plants using bimolecular fluorescence complementation (BiFC). The yellow fluorescent protein (YFP) was split into two non-overlapping N-terminal (YN) and C-terminal (YC) fragments. Each fragment was cloned in-frame to a gene of interest, enabling expression of fusion proteins. To demonstrate the feasibility of BiFC in plants, two pairs of interacting proteins were utilized: (i) the alpha and beta subunits of the Arabidopsis protein farnesyltransferase (PFT), and (ii) the polycomb proteins, FERTILIZATION-INDEPENDENT ENDOSPERM (FIE) and MEDEA (MEA). Members of each protein pair were transiently co-expressed in leaf epidermal cells of Nicotiana benthamiana or Arabidopsis. Reconstitution of a fluorescing YFP chromophore occurred only when the inquest proteins interacted. No fluorescence was detected following co-expression of free non-fused YN and YC or non-interacting protein pairs. Yellow fluorescence was detected in the cytoplasm of cells that expressed PFT alpha and beta subunits, or in nuclei and cytoplasm of cells that expressed FIE and MEA. In vivo measurements of fluorescence spectra emitted from reconstituted YFPs were identical to that of a non-split YFP, confirming reconstitution of the chromophore. Expression of the inquest proteins was verified by immunoblot analysis using monoclonal antibodies directed against tags within the hybrid proteins. In addition, protein interactions were confirmed by immunoprecipitations. These results demonstrate that plant BiFC is a simple, reliable and relatively fast method for determining protein-protein interactions in plants.

  16. Protein-Protein Interaction Inhibitors of BRCA1 Discovered Using Small Molecule Microarrays.

    PubMed

    Na, Zhenkun; Pan, Sijun; Uttamchandani, Mahesh; Yao, Shao Q

    2017-01-01

    Microarray screening technology has transformed the life sciences arena over the last decade. The platform is widely used in the area of mapping interaction networks, to molecular fingerprinting and small molecular inhibitor discovery. The technique has significantly impacted both basic and applied research. The microarray platform can likewise enable high-throughput screening and discovery of protein-protein interaction (PPI) inhibitors. Herein we demonstrate the application of microarray-guided PPI inhibitor discovery, using human BRCA1 as an example. Mutations in BRCA1 have been implicated in ~50 % of hereditary breast cancers. By targeting the (BRCT)2 domain, we showed compound 15a and its prodrug 15b inhibited BRCA1 activities in tumor cells. Unlike previously reported peptide-based PPI inhibitors of BRCA1, the compounds identified could be directly administered to tumor cells, thus making them useful in targeting BRCA1/PARP-related pathways involved in DNA damage and repair response, for cancer therapy.

  17. Context-based retrieval of functional modules in protein-protein interaction networks.

    PubMed

    Dobay, Maria Pamela; Stertz, Silke; Delorenzi, Mauro

    2017-03-27

    Various techniques have been developed for identifying the most probable interactants of a protein under a given biological context. In this article, we dissect the effects of the choice of the protein-protein interaction network (PPI) and the manipulation of PPI settings on the network neighborhood of the influenza A virus (IAV) network, as well as hits in genome-wide small interfering RNA screen results for IAV host factors. We investigate the potential of context filtering, which uses text mining evidence linked to PPI edges, as a complement to the edge confidence scores typically provided in PPIs for filtering, for obtaining more biologically relevant network neighborhoods. Here, we estimate the maximum performance of context filtering to isolate a Kyoto Encyclopedia of Genes and Genomes (KEGG) network Ki from a union of KEGG networks and its network neighborhood. The work gives insights on the use of human PPIs in network neighborhood approaches for functional inference.

  18. Protein-Protein Interaction Inhibition (2P2I)-Oriented Chemical Library Accelerates Hit Discovery.

    PubMed

    Milhas, Sabine; Raux, Brigitt; Betzi, Stéphane; Derviaux, Carine; Roche, Philippe; Restouin, Audrey; Basse, Marie-Jeanne; Rebuffet, Etienne; Lugari, Adrien; Badol, Marion; Kashyap, Rudra; Lissitzky, Jean-Claude; Eydoux, Cécilia; Hamon, Véronique; Gourdel, Marie-Edith; Combes, Sébastien; Zimmermann, Pascale; Aurrand-Lions, Michel; Roux, Thomas; Rogers, Catherine; Müller, Susanne; Knapp, Stefan; Trinquet, Eric; Collette, Yves; Guillemot, Jean-Claude; Morelli, Xavier

    2016-08-19

    Protein-protein interactions (PPIs) represent an enormous source of opportunity for therapeutic intervention. We and others have recently pinpointed key rules that will help in identifying the next generation of innovative drugs to tackle this challenging class of targets within the next decade. We used these rules to design an oriented chemical library corresponding to a set of diverse "PPI-like" modulators with cores identified as privileged structures in therapeutics. In this work, we purchased the resulting 1664 structurally diverse compounds and evaluated them on a series of representative protein-protein interfaces with distinct "druggability" potential using homogeneous time-resolved fluorescence (HTRF) technology. For certain PPI classes, analysis of the hit rates revealed up to 100 enrichment factors compared with nonoriented chemical libraries. This observation correlates with the predicted "druggability" of the targets. A specific focus on selectivity profiles, the three-dimensional (3D) molecular modes of action resolved by X-ray crystallography, and the biological activities of identified hits targeting the well-defined "druggable" bromodomains of the bromo and extraterminal (BET) family are presented as a proof-of-concept. Overall, our present study illustrates the potency of machine learning-based oriented chemical libraries to accelerate the identification of hits targeting PPIs. A generalization of this method to a larger set of compounds will accelerate the discovery of original and potent probes for this challenging class of targets.

  19. Modeling implicit reorganization in continuum descriptions of protein-protein interactions.

    PubMed

    Olson, M A; Reinke, L T

    2000-01-01

    The determination of free energies that govern protein-protein recognition is essential for a detailed molecular understanding of biological specificity. Continuum models of macromolecular interactions, in which the solvent is treated by an implicit representation and the proteins are treated semi-microscopically, are computationally tractable for estimating free energies, yet many questions remain concerning their accuracy. This article reports a continuum analysis of the free-energy changes underlying the binding of 31 interfacial alanine substitutions of two complexes of the antihen egg white lysozyme (HEL) antibody D1.3 bound with HEL or the antibody E5.2. Two implicit schemes for modeling the effects of protein and solvent relaxation were examined, in which the protein environment was treated as either homogeneous with a "protein dielectric constant" of epsilon(p) = 4 or inhomogeneous, with epsilon(p) = 4 for neutral residues and epsilon(p) = 25 for ionized residues. The results showed that the nonuniform dielectric model reproduced the experimental differences better, with an average absolute error of +/-1.1 kcal/mol, compared with +/-1.4 kcal/mol for the uniform model. More importantly, the error for charged residues in the nonuniform model is +/-0.8 kcal/mol and is nearly half of that corresponding to the uniform model. Several substitutions were clearly problematic in determining qualitative trends and probably required explicit structural reorganization at the protein-protein interface.

  20. A comparative study of monoclonal antibodies. 1. Phase behavior and protein-protein interactions.

    PubMed

    Lewus, Rachael A; Levy, Nicholas E; Lenhoff, Abraham M; Sandler, Stanley I

    2015-01-01

    Protein phase behavior is involved in numerous aspects of downstream processing, either by design as in crystallization or precipitation processes, or as an undesired effect, such as aggregation. This work explores the phase behavior of eight monoclonal antibodies (mAbs) that exhibit liquid-liquid separation, aggregation, gelation, and crystallization. The phase behavior has been studied systematically as a function of a number of factors, including solution composition and pH, in order to explore the degree of variability among different antibodies. Comparisons of the locations of phase boundaries show consistent trends as a function of solution composition; however, changing the solution pH has different effects on each of the antibodies studied. Furthermore, the types of dense phases formed varied among the antibodies. Protein-protein interactions, as reflected by values of the osmotic second virial coefficient, are used to correlate the phase behavior. The primary findings are that values of the osmotic second virial coefficient are useful for correlating phase boundary locations, though there is appreciable variability among the antibodies in the apparent strengths of the intrinsic protein-protein attraction manifested. However, the osmotic second virial coefficient does not provide a clear basis to predict the type of dense phase likely to result under a given set of solution conditions.

  1. Protein-protein interaction and molecular dynamics analysis for identification of novel inhibitors in Burkholderia cepacia GG4.

    PubMed

    Gupta, Money; Chauhan, Rashi; Prasad, Yamuna; Wadhwa, Gulshan; Jain, Chakresh Kumar

    2016-12-01

    The lack of complete treatments and appearance of multiple drug-resistance strains of Burkholderia cepacia complex (Bcc) are causing an increased risk of lung infections in cystic fibrosis patients. Bcc infection is a big risk to human health and demands an urgent need to identify new therapeutics against these bacteria. Network biology has emerged as one of the prospective hope in identifying novel drug targets and hits. We have applied protein-protein interaction methodology to identify new drug-target candidates (orthologs) in Burkhloderia cepacia GG4, which is an important strain for studying the quorum-sensing phenomena. An evolutionary based ortholog mapping approach has been applied for generating the large scale protein-protein interactions in B. Cepacia. As a case study, one of the identified drug targets; GEM_3202, a NH (3)-dependent NAD synthetase protein has been studied and the potential ligand molecules were screened using the ZINC database. The three dimensional structure (NH (3)-dependent NAD synthetase protein) has been predicted from MODELLERv9.11 tool using multiple PDB templates such as 3DPI, 2PZ8 and 1NSY with sequence identity of 76%, 50% and 50% respectively. The structure has been validated with Ramachandaran plot having 100% residues of NadE in allowed region and overall quality factor of 81.75 using ERRAT tool. High throughput screening and Vina resulted in two potential hits against NadE such as ZINC83103551 and ZINC38008121. These molecules showed lowest binding energy of -5.7kcalmol(-1) and high stability in the binding pockets during molecular dynamics simulation analysis. The similar approach for target identification could be applied for clinical strains of other pathogenic microbes.

  2. Protein-protein interactions prediction based on iterative clique extension with gene ontology filtering.

    PubMed

    Yang, Lei; Tang, Xianglong

    2014-01-01

    Cliques (maximal complete subnets) in protein-protein interaction (PPI) network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO) annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP) and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning.

  3. Detecting Protein-Protein Interactions in Vesicular Stomatitis Virus Using a Cytoplasmic Yeast Two Hybrid System

    PubMed Central

    Moerdyk-Schauwecker, Megan; DeStephanis, Darla; Hastie, Eric; Grdzelishvili, Valery Z.

    2011-01-01

    Summary Protein-protein interactions play an important role in many virus-encoded functions and in virus-host interactions. While a “classical” yeast two-hybrid system (Y2H) is one of the most common techniques to detect such interactions, it has a number of limitations, including a requirement for the proteins of interest to be relocated to the nucleus. Modified Y2H, such as the Sos recruitment system (SRS), which detect interactions occurring in the cytoplasm rather than the nucleus, allow proteins from viruses replicating in the cytoplasm to be tested in a more natural context. In this study, a SRS was used to detect interactions involving proteins from vesicular stomatitis virus (VSV), a prototypic non-segmented negative strand RNA (NNS) virus. All five full-length VSV proteins, as well as several truncated proteins, were screened against each other. Using the SRS, most interactions demonstrated previously involving VSV phosphoprotein, nucleocapsid (N) and large polymerase proteins were confirmed independently, while difficulties were encountered using the membrane associated matrix and glycoproteins. A human cDNA library was also screened against VSV N protein and one cellular protein, SFRS18, was identified which interacted with N in this context. The system presented can be redesigned easily for studies in other less tractable NNS viruses. PMID:21320532

  4. The protein-protein interaction network of the human Sirtuin family.

    PubMed

    Sharma, Ankush; Costantini, Susan; Colonna, Giovanni

    2013-10-01

    Protein-protein interaction networks are useful for studying human diseases and to look for possible health care through a holistic approach. Networks are playing an increasing and important role in the understanding of physiological processes such as homeostasis, signaling, spatial and temporal organizations, and pathological conditions. In this article we show the complex system of interactions determined by human Sirtuins (Sirt) largely involved in many metabolic processes as well as in different diseases. The Sirtuin family consists of seven homologous Sirt-s having structurally similar cores but different terminal segments, being rather variable in length and/or intrinsically disordered. Many studies have determined their cellular location as well as biological functions although molecular mechanisms through which they act are actually little known therefore, the aim of this work was to define, explore and understand the Sirtuin-related human interactome. As a first step, we have integrated the experimentally determined protein-protein interactions of the Sirtuin-family as well as their first and second neighbors to a Sirtuin-related sub-interactome. Our data showed that the second-neighbor network of Sirtuins encompasses 25% of the entire human interactome, and exhibits a scale-free degree distribution and interconnectedness among top degree nodes. Moreover, the Sirtuin sub interactome showed a modular structure around the core comprising mixed functions. Finally, we extracted from the Sirtuin sub-interactome subnets related to cancer, aging and post-translational modifications for information on key nodes and topological space of the subnets in the Sirt family network.

  5. Establishing an osteosarcoma associated protein-protein interaction network to explore the pathogenesis of osteosarcoma

    PubMed Central

    2013-01-01

    Background The aim of this study was to establish an osteosarcoma (OS) associated protein-protein interaction network and explore the pathogenesis of osteosarcoma. Methods The gene expression profile GSE9508 was downloaded from the Gene Expression Omnibus database, including five samples of non-malignant bone (the control), seven samples for non-metastatic patients (six of which were analyzed in duplicate), and 11 samples for metastatic patients (10 of which were analyzed in duplicate). Differentially expressed genes (DEGs) between osteosarcoma and control samples were identified by packages in R with the threshold of |logFC (fold change)| > 1 and false discovery rate < 0.05. Osprey software was used to construct the interaction network of DEGs, and genes at protein-protein interaction (PPI) nodes with high degrees were identified. The Database for Annotation, Visualization and Integrated Discovery and WebGestalt software were then used to perform functional annotation and pathway enrichment analyses for PPI networks, in which P < 0.05 was considered statistically significant. Results Compared to the control samples, the expressions of 42 and 341 genes were altered in non-metastatic OS and metastatic OS samples, respectively. A total of 15 significantly enriched functions were obtained with Gene Ontology analysis (P < 0.05). The DEGs were classified and significantly enriched in three pathways, including the tricarboxylic acid cycle, lysosome and axon guidance. Genes such as HRAS, IDH3A, ATP6ap1, ATP6V0D2, SEMA3F and SEMA3A were involved in the enriched pathways. Conclusions The hub genes from metastatic OS samples are not only bio-markers of OS, but also help to improve therapies for OS. PMID:24330838

  6. PPISEARCHENGINE: gene ontology-based search for protein-protein interactions.

    PubMed

    Park, Byungkyu; Cui, Guangyu; Lee, Hyunjin; Huang, De-Shuang; Han, Kyungsook

    2013-01-01

    This paper presents a new search engine called PPISearchEngine which finds protein-protein interactions (PPIs) using the gene ontology (GO) and the biological relations of proteins. For efficient retrieval of PPIs, each GO term is assigned a prime number and the relation between the terms is represented by the product of prime numbers. This representation is hidden from users but facilitates the search for the interactions of a query protein by unique prime factorisation of the number that represents the query protein. For a query protein, PPISearchEngine considers not only the GO term associated with the query protein but also the GO terms at the lower level than the GO term in the GO hierarchy, and finds all the interactions of the query protein which satisfy the search condition. In contrast, the standard keyword-matching or ID-matching search method cannot find the interactions of a protein unless the interactions involve a protein with explicit annotations. To the best of our knowledge, this search engine is the first method that can process queries like 'for protein p with GO [Formula: see text], find p's interaction partners with GO [Formula: see text]'. PPISearchEngine is freely available to academics at http://search.hpid.org/.

  7. Improving analytical methods for protein-protein interaction through implementation of chemically inducible dimerization

    PubMed Central

    Andersen, Tonni Grube; Nintemann, Sebastian J.; Marek, Magdalena; Halkier, Barbara A.; Schulz, Alexander; Burow, Meike

    2016-01-01

    When investigating interactions between two proteins with complementary reporter tags in yeast two-hybrid or split GFP assays, it remains troublesome to discriminate true- from false-negative results and challenging to compare the level of interaction across experiments. This leads to decreased sensitivity and renders analysis of weak or transient interactions difficult to perform. In this work, we describe the development of reporters that can be chemically induced to dimerize independently of the investigated interactions and thus alleviate these issues. We incorporated our reporters into the widely used split ubiquitin-, bimolecular fluorescence complementation (BiFC)- and Förster resonance energy transfer (FRET)- based methods and investigated different protein-protein interactions in yeast and plants. We demonstrate the functionality of this concept by the analysis of weakly interacting proteins from specialized metabolism in the model plant Arabidopsis thaliana. Our results illustrate that chemically induced dimerization can function as a built-in control for split-based systems that is easily implemented and allows for direct evaluation of functionality. PMID:27282591

  8. A profile of protein-protein interaction: Crystal structure of a lectin-lectin complex.

    PubMed

    Surya, Sukumaran; Abhilash, Joseph; Geethanandan, Krishnan; Sadasivan, Chittalakkottu; Haridas, Madhathilkovilakathu

    2016-06-01

    Proteins may utilize complex networks of interactions to create/proceed signaling pathways of highly adaptive responses such as programmed cell death. Direct binary interactions study of proteins may help propose models for protein-protein interaction. Towards this goal we applied a combination of thermodynamic kinetics and crystal structure analyses to elucidate the complexity and diversity in such interactions. By determining the heat change on the association of two galactose-specific legume lectins from Butea monosperma (BML) and Spatholobus parviflorus (SPL) belonging to Fabaceae family helped to compute the binding equilibrium. It was extended further by X-ray structural analysis of BML-SPL binary complex. In order to chart the proteins interacting mainly through their interfaces, identification of the nature of forces which stabilized the association of the lectin-lectin complex was examined. Comprehensive analysis of the BMLSPL complex by isothermal titration calorimetry and X-ray crystal structure threw new light on the lectin-lectin interactions suggesting of their use in diverse areas of glycobiology.

  9. Peptide inhibitors of the Keap1-Nrf2 protein-protein interaction.

    PubMed

    Hancock, Rowena; Bertrand, Hélène C; Tsujita, Tadayuki; Naz, Shama; El-Bakry, Ayman; Laoruchupong, Jitnueng; Hayes, John D; Wells, Geoff

    2012-01-15

    Disruption of the interaction between the ubiquitination facilitator protein Keap1 and the cap'n'collar basic-region leucine-zipper transcription factor Nrf2 is a potential strategy to enhance expression of antioxidant and free radical detoxification gene products regulated by Nrf2. Agents that disrupt this protein-protein interaction may be useful pharmacological probes and future cancer-chemopreventive agents. We describe the structure-activity relationships for a series of peptides based upon regions of the Nrf2 Neh2 domain, of varying length and sequence, that interact with the Keap1 Kelch domain and disrupt the interaction with Nrf2. We have also investigated sequestosome-1 (p62) and prothymosin-α sequences that have been reported to interact with Keap1. To achieve this we have developed a high-throughput fluorescence polarization (FP) assay to screen inhibitors. In addition to screening synthetic peptides, we have used a phage display library approach to identify putative peptide ligands with non-native sequence motifs. Candidate peptides from the phage display library screening protocol were evaluated in the FP assay to quantify their binding activity. Hybrid peptides based upon the Nrf2 "ETGE" motif and the sequestosome-1 "Keap1-interaction region" have superior binding activity compared to either native peptide alone.

  10. Screening bicyclic peptide libraries for protein-protein interaction inhibitors: discovery of a tumor necrosis factor-α antagonist.

    PubMed

    Lian, Wenlong; Upadhyaya, Punit; Rhodes, Curran A; Liu, Yusen; Pei, Dehua

    2013-08-14

    Protein-protein interactions represent a new class of exciting but challenging drug targets, because their large, flat binding sites lack well-defined pockets for small molecules to bind. We report here a methodology for chemical synthesis and screening of large combinatorial libraries of bicyclic peptides displayed on rigid small-molecule scaffolds. With planar trimesic acid as the scaffold, the resulting bicyclic peptides are effective for binding to protein surfaces such as the interfaces of protein-protein interactions. Screening of a bicyclic peptide library against tumor necrosis factor-α (TNFα) identified a potent antagonist that inhibits the TNFα-TNFα receptor interaction and protects cells from TNFα-induced cell death. Bicyclic peptides of this type may provide a general solution for inhibition of protein-protein interactions.

  11. Plant nuclear hormone receptors: a role for small molecules in protein-protein interactions.

    PubMed

    Lumba, Shelley; Cutler, Sean; McCourt, Peter

    2010-01-01

    Plant hormones are a group of chemically diverse small molecules that direct processes ranging from growth and development to biotic and abiotic stress responses. Surprisingly, genome analyses suggest that classic animal nuclear hormone receptor homologs do not exist in plants. It now appears that plants have co-opted several protein families to perceive hormones within the nucleus. In one solution to the problem, the hormones auxin and jasmonate (JA) act as “molecular glue” that promotes protein-protein interactions between receptor F-boxes and downstream corepressor targets. In another solution, gibberellins (GAs) bind and elicit a conformational change in a novel soluble receptor family related to hormone-sensitive lipases. Abscisic acid (ABA), like GA, also acts through an allosteric mechanism involving a START-domain protein. The molecular identification of plant nuclear hormone receptors will allow comparisons with animal nuclear receptors and testing of fundamental questions about hormone function in plant development and evolution.

  12. Protein-protein interactions from linear-scaling first-principles quantum-mechanical calculations

    NASA Astrophysics Data System (ADS)

    Cole, D. J.; Skylaris, C.-K.; Rajendra, E.; Venkitaraman, A. R.; Payne, M. C.

    2010-08-01

    A modification of the MM-PBSA technique for calculating binding affinities of biomolecular complexes is presented. Classical molecular dynamics is used to explore the motion of the extended interface between two peptides derived from the BRC4 repeat of BRCA2 and the eukaryotic recombinase RAD51. The resulting trajectory is sampled using the linear-scaling density functional theory code, onetep, to determine from first principles, and with high computational efficiency, the relative free energies of binding of the ~2800 atom receptor-ligand complexes. This new method provides the basis for computational interrogation of protein-protein and protein-ligand interactions within fields ranging from chemical biological studies to small-molecule binding behaviour, with both unprecedented chemical accuracy and affordable computational expense.

  13. Protein-Protein Interactions from Linear-Scaling First Principles Quantum Mechanical Calculations

    NASA Astrophysics Data System (ADS)

    Cole, Daniel; Skylaris, Chris-Kriton; Rajendra, Eeson; Venkitaraman, Ashok; Payne, Mike

    2010-03-01

    A modification of the MM-PBSA technique for calculating binding affinities of biomolecular complexes is presented. Classical molecular dynamics is used to explore the motion of the extended interface between two peptides derived from the BRC4 repeat of BRCA2 and the eukaryotic recombinase RAD51. The resulting trajectory is sampled using the linear-scaling density functional theory code, onetep, to determine from first principles, and with high computational efficiency, the relative free energies of binding of the ˜2800 atom receptor-ligand complexes. This new method provides the basis for computational interrogation of protein-protein and protein-ligand interactions, within fields ranging from chemical biological studies to small molecule binding behaviour, with both unprecedented chemical accuracy and affordable computational expense.

  14. Focused chemical libraries--design and enrichment: an example of protein-protein interaction chemical space.

    PubMed

    Zhang, Xu; Betzi, Stéphane; Morelli, Xavier; Roche, Philippe

    2014-07-01

    One of the many obstacles in the development of new drugs lies in the limited number of therapeutic targets and in the quality of screening collections of compounds. In this review, we present general strategies for building target-focused chemical libraries with a particular emphasis on protein-protein interactions (PPIs). We describe the chemical spaces spanned by nine commercially available PPI-focused libraries and compare them to our 2P2I3D academic library, dedicated to orthosteric PPI modulators. We show that although PPI-focused libraries have been designed using different strategies, they share common subspaces. PPI inhibitors are larger and more hydrophobic than standard drugs; however, an effort has been made to improve the drug-likeness of focused chemical libraries dedicated to this challenging class of targets.

  15. Overcoming Chemical, Biological, and Computational Challenges in the Development of Inhibitors Targeting Protein-Protein Interactions

    PubMed Central

    Laraia, Luca; McKenzie, Grahame; Spring, David R.; Venkitaraman, Ashok R.; Huggins, David J.

    2015-01-01

    Protein-protein interactions (PPIs) underlie the majority of biological processes, signaling, and disease. Approaches to modulate PPIs with small molecules have therefore attracted increasing interest over the past decade. However, there are a number of challenges inherent in developing small-molecule PPI inhibitors that have prevented these approaches from reaching their full potential. From target validation to small-molecule screening and lead optimization, identifying therapeutically relevant PPIs that can be successfully modulated by small molecules is not a simple task. Following the recent review by Arkin et al., which summarized the lessons learnt from prior successes, we focus in this article on the specific challenges of developing PPI inhibitors and detail the recent advances in chemistry, biology, and computation that facilitate overcoming them. We conclude by providing a perspective on the field and outlining four innovations that we see as key enabling steps for successful development of small-molecule inhibitors targeting PPIs. PMID:26091166

  16. Prediction of Protein-Protein Interactions with Physicochemical Descriptors and Wavelet Transform via Random Forests.

    PubMed

    Jia, Jianhua; Xiao, Xuan; Liu, Bingxiang

    2016-06-01

    Protein-protein interactions (PPIs) provide valuable insight into the inner workings of cells, and it is significant to study the network of PPIs. It is vitally important to develop an automated method as a high-throughput tool to timely predict PPIs. Based on the physicochemical descriptors, a protein was converted into several digital signals, and then wavelet transform was used to analyze them. With such a formulation frame to represent the samples of protein sequences, the random forests algorithm was adopted to conduct prediction. The results on a large-scale independent-test data set show that the proposed model can achieve a good performance with an accuracy value of about 0.86 and a geometric mean value of about 0.85. Therefore, it can be a usefully supplementary tool for PPI prediction. The predictor used in this article is freely available at http://www.jci-bioinfo.cn/PPI_RF.

  17. Network analysis and in silico prediction of protein-protein interactions with applications in drug discovery.

    PubMed

    Murakami, Yoichi; Tripathi, Lokesh P; Prathipati, Philip; Mizuguchi, Kenji

    2017-03-29

    Protein-protein interactions (PPIs) are vital to maintaining cellular homeostasis. Several PPI dysregulations have been implicated in the etiology of various diseases and hence PPIs have emerged as promising targets for drug discovery. Surface residues and hotspot residues at the interface of PPIs form the core regions, which play a key role in modulating cellular processes such as signal transduction and are used as starting points for drug design. In this review, we briefly discuss how PPI networks (PPINs) inferred from experimentally characterized PPI data have been utilized for knowledge discovery and how in silico approaches to PPI characterization can contribute to PPIN-based biological research. Next, we describe the principles of in silico PPI prediction and survey the existing PPI and PPI site prediction servers that are useful for drug discovery. Finally, we discuss the potential of in silico PPI prediction in drug discovery.

  18. Application of shotgun proteomics for discovery-driven protein-protein interaction.

    PubMed

    Goto-Silva, Livia; Maliga, Zoltan; Slabicki, Mikolaj; Murillo, Jimmy Rodriguez; Junqueira, Magno

    2014-01-01

    Affinity purification of protein complexes and identification of co-purified proteins by mass spectrometry is a powerful method to discover novel protein-protein interactions. Application of this method to the study of biological systems often requires the ability to process a large number of samples. Hence, there is great need to generate proteomic workflows compatible with large-scale studies. The major goal of this protocol is to present a fast, reliable, and scalable method to characterize protein complexes by mass spectrometry to overcome the limitations of conventional geLC-MS/MS or MudPIT protocols. This method was successfully employed for the discovery and characterization of novel protein complexes in cultured yeast, mammalian cells, and mice.

  19. Identifying Novel Candidate Genes Related to Apoptosis from a Protein-Protein Interaction Network

    PubMed Central

    Wang, Baoman; Yuan, Fei; Kong, Xiangyin; Hu, Lan-Dian; Cai, Yu-Dong

    2015-01-01

    Apoptosis is the process of programmed cell death (PCD) that occurs in multicellular organisms. This process of normal cell death is required to maintain the balance of homeostasis. In addition, some diseases, such as obesity, cancer, and neurodegenerative diseases, can be cured through apoptosis, which produces few side effects. An effective comprehension of the mechanisms underlying apoptosis will be helpful to prevent and treat some diseases. The identification of genes related to apoptosis is essential to uncover its underlying mechanisms. In this study, a computational method was proposed to identify novel candidate genes related to apoptosis. First, protein-protein interaction information was used to construct a weighted graph. Second, a shortest path algorithm was applied to the graph to search for new candidate genes. Finally, the obtained genes were filtered by a permutation test. As a result, 26 genes were obtained, and we discuss their likelihood of being novel apoptosis-related genes by collecting evidence from published literature. PMID:26543496

  20. Diversity-oriented synthetic strategy for developing a chemical modulator of protein-protein interaction

    NASA Astrophysics Data System (ADS)

    Kim, Jonghoon; Jung, Jinjoo; Koo, Jaeyoung; Cho, Wansang; Lee, Won Seok; Kim, Chanwoo; Park, Wonwoo; Park, Seung Bum

    2016-10-01

    Diversity-oriented synthesis (DOS) can provide a collection of diverse and complex drug-like small molecules, which is critical in the development of new chemical probes for biological research of undruggable targets. However, the design and synthesis of small-molecule libraries with improved biological relevance as well as maximized molecular diversity represent a key challenge. Herein, we employ functional group-pairing strategy for the DOS of a chemical library containing privileged substructures, pyrimidodiazepine or pyrimidine moieties, as chemical navigators towards unexplored bioactive chemical space. To validate the utility of this DOS library, we identify a new small-molecule inhibitor of leucyl-tRNA synthetase-RagD protein-protein interaction, which regulates the amino acid-dependent activation of mechanistic target of rapamycin complex 1 signalling pathway. This work highlights that privileged substructure-based DOS strategy can be a powerful research tool for the construction of drug-like compounds to address challenging biological targets.

  1. CombiMotif: A new algorithm for network motifs discovery in protein-protein interaction networks

    NASA Astrophysics Data System (ADS)

    Luo, Jiawei; Li, Guanghui; Song, Dan; Liang, Cheng

    2014-12-01

    Discovering motifs in protein-protein interaction networks is becoming a current major challenge in computational biology, since the distribution of the number of network motifs can reveal significant systemic differences among species. However, this task can be computationally expensive because of the involvement of graph isomorphic detection. In this paper, we present a new algorithm (CombiMotif) that incorporates combinatorial techniques to count non-induced occurrences of subgraph topologies in the form of trees. The efficiency of our algorithm is demonstrated by comparing the obtained results with the current state-of-the art subgraph counting algorithms. We also show major differences between unicellular and multicellular organisms. The datasets and source code of CombiMotif are freely available upon request.

  2. Information theory in systems biology. Part II: protein-protein interaction and signaling networks.

    PubMed

    Mousavian, Zaynab; Díaz, José; Masoudi-Nejad, Ali

    2016-03-01

    By the development of information theory in 1948 by Claude Shannon to address the problems in the field of data storage and data communication over (noisy) communication channel, it has been successfully applied in many other research areas such as bioinformatics and systems biology. In this manuscript, we attempt to review some of the existing literatures in systems biology, which are using the information theory measures in their calculations. As we have reviewed most of the existing information-theoretic methods in gene regulatory and metabolic networks in the first part of the review, so in the second part of our study, the application of information theory in other types of biological networks including protein-protein interaction and signaling networks will be surveyed.

  3. Investigation of stable and transient protein-protein interactions: past, present and future

    PubMed Central

    Ngounou Wetie, Armand G.; Sokolowska, Izabela; Woods, Alisa G.; Roy, Urmi; Loo, Joseph A.; Darie, Costel C.

    2013-01-01

    This article presents an overview of the literature and a review of recent advances in the analysis of stable and transient protein-protein interactions (PPIs) with a focus on their function within cells, organs and organisms. The significance of post-translational modifications within the PPIs is also discussed. We focus on methods to study PPIs and methods of detecting PPIs, with particular emphasis on electrophoresis-based and mass spectrometry (MS)-based investigation of PPIs, including specific examples. The validation of PPIs is emphasized and the limitations of the current methods for studying stable and transient PPIs are discussed. Perspectives regarding PPIs, with focus on bioinformatics and transient PPIs are also provided. PMID:23193082

  4. Protein-protein interaction networks studies and importance of 3D structure knowledge.

    PubMed

    Lu, Hui-Chun; Fornili, Arianna; Fraternali, Franca

    2013-12-01

    Protein-protein interaction networks (PPINs) are a powerful tool to study biological processes in living cells. In this review, we present the progress of PPIN studies from abstract to more detailed representations. We will focus on 3D interactome networks, which offer detailed information at the atomic level. This information can be exploited in understanding not only the underlying cellular mechanisms, but also how human variants and disease-causing mutations affect protein functions and complexes' stability. Recent studies have used structural information on PPINs to also understand the molecular mechanisms of binding partner selection. We will address the challenges in generating 3D PPINs due to the restricted number of solved protein structures. Finally, some of the current use of 3D PPINs will be discussed, highlighting their contribution to the studies in genotype-phenotype relationships and in the optimization of targeted studies to design novel chemical compounds for medical treatments.

  5. Thermodynamic measures of cancer: Gibbs free energy and entropy of protein-protein interactions.

    PubMed

    Rietman, Edward A; Platig, John; Tuszynski, Jack A; Lakka Klement, Giannoula

    2016-06-01

    Thermodynamics is an important driving factor for chemical processes and for life. Earlier work has shown that each cancer has its own molecular signaling network that supports its life cycle and that different cancers have different thermodynamic entropies characterizing their signaling networks. The respective thermodynamic entropies correlate with 5-year survival for each cancer. We now show that by overlaying mRNA transcription data from a specific tumor type onto a human protein-protein interaction network, we can derive the Gibbs free energy for the specific cancer. The Gibbs free energy correlates with 5-year survival (Pearson correlation of -0.7181, p value of 0.0294). Using an expression relating entropy and Gibbs free energy to enthalpy, we derive an empirical relation for cancer network enthalpy. Combining this with previously published results, we now show a complete set of extensive thermodynamic properties and cancer type with 5-year survival.

  6. Overcoming Chemical, Biological, and Computational Challenges in the Development of Inhibitors Targeting Protein-Protein Interactions.

    PubMed

    Laraia, Luca; McKenzie, Grahame; Spring, David R; Venkitaraman, Ashok R; Huggins, David J

    2015-06-18

    Protein-protein interactions (PPIs) underlie the majority of biological processes, signaling, and disease. Approaches to modulate PPIs with small molecules have therefore attracted increasing interest over the past decade. However, there are a number of challenges inherent in developing small-molecule PPI inhibitors that have prevented these approaches from reaching their full potential. From target validation to small-molecule screening and lead optimization, identifying therapeutically relevant PPIs that can be successfully modulated by small molecules is not a simple task. Following the recent review by Arkin et al., which summarized the lessons learnt from prior successes, we focus in this article on the specific challenges of developing PPI inhibitors and detail the recent advances in chemistry, biology, and computation that facilitate overcoming them. We conclude by providing a perspective on the field and outlining four innovations that we see as key enabling steps for successful development of small-molecule inhibitors targeting PPIs.

  7. CapsidMaps: protein-protein interaction pattern discovery platform for the structural analysis of virus capsids using Google Maps.

    PubMed

    Carrillo-Tripp, Mauricio; Montiel-García, Daniel Jorge; Brooks, Charles L; Reddy, Vijay S

    2015-04-01

    Structural analysis and visualization of protein-protein interactions is a challenging task since it is difficult to appreciate easily the extent of all contacts made by the residues forming the interfaces. In the case of viruses, structural analysis becomes even more demanding because several interfaces coexist and, in most cases, these are formed by hundreds of contacting residues that belong to multiple interacting coat proteins. CapsidMaps is an interactive analysis and visualization tool that is designed to benefit the structural virology community. Developed as an improved extension of the φ-ψ Explorer, here we describe the details of its design and implementation. We present results of analysis of a spherical virus to showcase the features and utility of the new tool. CapsidMaps also facilitates the comparison of quaternary interactions between two spherical virus particles by computing a similarity (S)-score. The tool can also be used to identify residues that are solvent exposed and in the process of locating antigenic epitope regions as well as residues forming the inside surface of the capsid that interact with the nucleic acid genome. CapsidMaps is part of the VIPERdb Science Gateway, and is freely available as a web-based and cross-browser compliant application at http://viperdb.scripps.edu.

  8. RefSOFI for Mapping Nanoscale Organization of Protein-protein Interactions in Living cells

    PubMed Central

    Hertel, Fabian; Mo, Gary C. H.; Duwé, Sam; Dedecker, Peter; Zhang, Jin

    2015-01-01

    Summary It has become increasingly clear that protein-protein interactions (PPIs) are compartmentalized in nanoscale domains that define the biochemical architecture of the cell. Despite tremendous advances in super-resolution imaging, strategies to observe PPIs at sufficient resolution to discern their organization are just emerging. Here we describe a strategy in which PPIs induce reconstitution of fluorescent proteins (FPs) that are capable of exhibiting single-molecule fluctuations suitable for Stochastic Optical Fluctuation Imaging (SOFI). Subsequently, spatial maps of these interactions can be resolved in super-resolution in living cells. Using this strategy, termed reconstituted fluorescence-based SOFI (refSOFI), we investigated the interaction between the endoplasmic reticulum Ca2+ sensor STIM1 and the pore-forming channel subunit ORAI1, a crucial process in store-operated Ca2+ entry (SOCE). Stimulating SOCE does not appear to change the size of existing STIM1/ORAI1 interaction puncta at the ER-plasma membrane junctions, but results in an apparent increase in the number of interaction puncta. PMID:26748717

  9. Constrained Cyclic Peptides as Immunomodulatory Inhibitors of the CD2:CD58 Protein-Protein Interaction.

    PubMed

    Sable, Rushikesh; Durek, Thomas; Taneja, Veena; Craik, David J; Pallerla, Sandeep; Gauthier, Ted; Jois, Seetharama

    2016-08-19

    The interaction between the cell-cell adhesion proteins CD2 and CD58 plays a crucial role in lymphocyte recruitment to inflammatory sites, and inhibitors of this interaction have potential as immunomodulatory drugs in autoimmune diseases. Peptides from the CD2 adhesion domain were designed to inhibit CD2:CD58 interactions. To improve the stability of the peptides, β-sheet epitopes from the CD2 region implicated in CD58 recognition were grafted into the cyclic peptide frameworks of sunflower trypsin inhibitor and rhesus theta defensin. The designed multicyclic peptides were evaluated for their ability to modulate cell-cell interactions in three different cell adhesion assays, with one candidate, SFTI-a, showing potent activity in the nanomolar range (IC50: 51 nM). This peptide also suppresses the immune responses in T cells obtained from mice that exhibit the autoimmune disease rheumatoid arthritis. SFTI-a was resistant to thermal denaturation, as judged by circular dichroism spectroscopy and mass spectrometry, and had a half-life of ∼24 h in human serum. Binding of this peptide to CD58 was predicted by molecular docking studies and experimentally confirmed by surface plasmon resonance experiments. Our results suggest that cyclic peptides from natural sources are promising scaffolds for modulating protein-protein interactions that are typically difficult to target with small-molecule compounds.

  10. PPIcons: identification of protein-protein interaction sites in selected organisms.

    PubMed

    Sriwastava, Brijesh K; Basu, Subhadip; Maulik, Ujjwal; Plewczynski, Dariusz

    2013-09-01

    The physico-chemical properties of interaction interfaces have a crucial role in characterization of protein-protein interactions (PPI). In silico prediction of participating amino acids helps to identify interface residues for further experimental verification using mutational analysis, or inhibition studies by screening library of ligands against given protein. Given the unbound structure of a protein and the fact that it forms a complex with another known protein, the objective of this work is to identify the residues that are involved in the interaction. We attempt to predict interaction sites in protein complexes using local composition of amino acids together with their physico-chemical characteristics. The local sequence segments (LSS) are dissected from the protein sequences using a sliding window of 21 amino acids. The list of LSSs is passed to the support vector machine (SVM) predictor, which identifies interacting residue pairs considering their inter-atom distances. We have analyzed three different model organisms of Escherichia coli, Saccharomyces Cerevisiae and Homo sapiens, where the numbers of considered hetero-complexes are equal to 40, 123 and 33 respectively. Moreover, the unified multi-organism PPI meta-predictor is also developed under the current work by combining the training databases of above organisms. The PPIcons interface residues prediction method is measured by the area under ROC curve (AUC) equal to 0.82, 0.75, 0.72 and 0.76 for the aforementioned organisms and the meta-predictor respectively.

  11. Simulated Evolution of Protein-Protein Interaction Networks with Realistic Topology

    PubMed Central

    Peterson, G. Jack; Pressé, Steve; Peterson, Kristin S.; Dill, Ken A.

    2012-01-01

    We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein’s neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution. PMID:22768057

  12. Designing specific protein-protein interactions using computation, experimental library screening, or integrated methods.

    PubMed

    Chen, T Scott; Keating, Amy E

    2012-07-01

    Given the importance of protein-protein interactions for nearly all biological processes, the design of protein affinity reagents for use in research, diagnosis or therapy is an important endeavor. Engineered proteins would ideally have high specificities for their intended targets, but achieving interaction specificity by design can be challenging. There are two major approaches to protein design or redesign. Most commonly, proteins and peptides are engineered using experimental library screening and/or in vitro evolution. An alternative approach involves using protein structure and computational modeling to rationally choose sequences predicted to have desirable properties. Computational design has successfully produced novel proteins with enhanced stability, desired interactions and enzymatic function. Here we review the strengths and limitations of experimental library screening and computational structure-based design, giving examples where these methods have been applied to designing protein interaction specificity. We highlight recent studies that demonstrate strategies for combining computational modeling with library screening. The computational methods provide focused libraries predicted to be enriched in sequences with the properties of interest. Such integrated approaches represent a promising way to increase the efficiency of protein design and to engineer complex functionality such as interaction specificity.

  13. The food colorant erythrosine is a promiscuous protein-protein interaction inhibitor.

    PubMed

    Ganesan, Lakshmi; Margolles-Clark, Emilio; Song, Yun; Buchwald, Peter

    2011-03-15

    Following our observation that erythrosine B (FD&C Red No. 3) is a relatively potent inhibitor of the TNF-R-TNFα and CD40-CD154 protein-protein interactions, we investigated whether this inhibitory activity extends to any other protein-protein interactions (PPI) as well as whether any other approved food colors possess such inhibitory activity. We found erythrosine, a poly-iodinated xanthene dye, to be a non-specific promiscuous inhibitor of a number of PPIs within the tumor necrosis factor superfamily (TNF-R-TNFα, CD40-CD154, BAFF-R-BAFF, RANK-RANKL, OX40-OX40L, 4-1BB-4-1BBL) as well as outside of it (EGF-R-EGF) with a remarkably consistent median inhibitory concentration (IC(50)) in the 2-20 μM (approximately 2-20mg/L) range. In agreement with this, erythrosine also showed cellular effects including clear cytotoxic effects around this concentration range (IC₅₀≈50 μM). Among the seven FDA-approved food colorants, only erythrosine showed consistent PPI inhibitory activity in the sub-100 μM range, which might also explain (at least partially) why it also has the lowest approved acceptable daily intake (ADI) (0.1 mg/kg body weight/day). Among a number of xanthene structural analogs of erythrosine tested for activity, rose Bengal, a food colorant approved in Japan, showed similar, maybe even more pronounced, promiscuous inhibitory activity, whereas fluorescein was inactive and gallein, phloxine, and eosin were somewhat active in some of the assays.

  14. Effect of the quality of the interaction data on predicting protein function from protein-protein interactions.

    PubMed

    Ni, Qing-Shan; Wang, Zheng-Zhi; Li, Gang-Guo; Wang, Guang-Yun; Zhao, Ying-Jie

    2009-03-01

    Protein function prediction is an important issue in the post-genomic era. When protein function is deduced from protein interaction data, the traditional methods treat each interaction sample equally, where the qualities of the interaction samples are seldom taken into account. In this paper, we investigate the effect of the quality of protein-protein interaction data on predicting protein function. Moreover, two improved methods, weight neighbour counting method (WNC) and weight chi-square method (WCHI), are proposed by considering the quality of interaction samples with the neighbour counting method (NC) and chi-square method (CHI). Experimental results have shown that the qualities of interaction samples affect the performances of protein function prediction methods seriously. It is also demonstrated that WNC and WCHI methods outperform NC and CHI methods in protein function prediction when example weights are chosen properly.

  15. SynechoNET: integrated protein-protein interaction database of a model cyanobacterium Synechocystis sp. PCC 6803

    PubMed Central

    Kim, Woo-Yeon; Kang, Sungsoo; Kim, Byoung-Chul; Oh, Jeehyun; Cho, Seongwoong; Bhak, Jong; Choi, Jong-Soon

    2008-01-01

    Background Cyanobacteria are model organisms for studying photosynthesis, carbon and nitrogen assimilation, evolution of plant plastids, and adaptability to environmental stresses. Despite many studies on cyanobacteria, there is no web-based database of their regulatory and signaling protein-protein interaction networks to date. Description We report a database and website SynechoNET that provides predicted protein-protein interactions. SynechoNET shows cyanobacterial domain-domain interactions as well as their protein-level interactions using the model cyanobacterium, Synechocystis sp. PCC 6803. It predicts the protein-protein interactions using public interaction databases that contain mutually complementary and redundant data. Furthermore, SynechoNET provides information on transmembrane topology, signal peptide, and domain structure in order to support the analysis of regulatory membrane proteins. Such biological information can be queried and visualized in user-friendly web interfaces that include the interactive network viewer and search pages by keyword and functional category. Conclusion SynechoNET is an integrated protein-protein interaction database designed to analyze regulatory membrane proteins in cyanobacteria. It provides a platform for biologists to extend the genomic data of cyanobacteria by predicting interaction partners, membrane association, and membrane topology of Synechocystis proteins. SynechoNET is freely available at or directly at . PMID:18315852

  16. Targeting protein-protein interactions in hematologic malignancies: still a challenge or a great opportunity for future therapies?

    PubMed Central

    Cierpicki, Tomasz; Grembecka, Jolanta

    2015-01-01

    Summary Over the past several years, there has been an increasing research effort focused on inhibition of protein-protein interactions (PPIs) to develop novel therapeutic approaches for cancer, including hematologic malignancies. These efforts have led to development of small molecule inhibitors of PPIs, some of which already advanced to the stage of clinical trials while others are at different stages of pre-clinical optimization, emphasizing PPIs as an emerging and attractive class of drug targets. Here, we review several examples of recently developed inhibitors of protein-protein interactions highly relevant to hematologic cancers. We address the existing skepticism about feasibility of targeting PPIs and emphasize potential therapeutic benefit from blocking PPIs in hematologic malignancies. We then use these examples to discuss the approaches for successful identification of PPI inhibitors and provide analysis of the protein-protein interfaces, with the goal to address ‘druggability’ of new PPIs relevant to hematology. We discuss lessons learned to improve the success of targeting new protein-protein interactions and evaluate prospects and limits of the research in this field. We conclude that not all PPIs are equally tractable for blocking by small molecules, and detailed analysis of PPI interfaces is critical for selection of those with the highest chance of success. Together, our analysis uncovers patterns that should help to advance drug discovery in hematologic malignancies by successful targeting of new protein-protein interactions. PMID:25510283

  17. A protein-protein interaction map of yeast RNA polymerase III.

    PubMed

    Flores, A; Briand, J F; Gadal, O; Andrau, J C; Rubbi, L; Van Mullem, V; Boschiero, C; Goussot, M; Marck, C; Carles, C; Thuriaux, P; Sentenac, A; Werner, M

    1999-07-06

    The structure of the yeast RNA polymerase (pol) III was investigated by exhaustive two-hybrid screening using a library of random genomic fragments fused to the Gal4 activation domain. This procedure allowed us to identify contacts between individual polypeptides, localize the contact domains, and deduce a protein-protein interaction map of the multisubunit enzyme. In all but one case, pol III subunits were able to interact in vivo with one or sometimes two partner subunits of the enzyme or with subunits of TFIIIC. Four subunits that are common to pol I, II, and III (ABC27, ABC14.5, ABC10alpha, and ABC10beta), two that are common to pol I and III (AC40 and AC19), and one pol III-specific subunit (C11) can associate with defined regions of the two large subunits. These regions overlapped with highly conserved domains. C53, a pol III-specific subunit, interacted with a 37-kDa polypeptide that copurifies with the enzyme and therefore appears to be a unique pol III subunit (C37). Together with parallel interaction studies based on dosage-dependent suppression of conditional mutants, our data suggest a model of the pol III preinitiation complex.

  18. Transcription Factor Functional Protein-Protein Interactions in Plant Defense Responses

    PubMed Central

    Alves, Murilo S.; Dadalto, Silvana P.; Gonçalves, Amanda B.; de Souza, Gilza B.; Barros, Vanessa A.; Fietto, Luciano G.

    2014-01-01

    Responses to biotic stress in plants lead to dramatic reprogramming of gene expression, favoring stress responses at the expense of normal cellular functions. Transcription factors are master regulators of gene expression at the transcriptional level, and controlling the activity of these factors alters the transcriptome of the plant, leading to metabolic and phenotypic changes in response to stress. The functional analysis of interactions between transcription factors and other proteins is very important for elucidating the role of these transcriptional regulators in different signaling cascades. In this review, we present an overview of protein-protein interactions for the six major families of transcription factors involved in plant defense: basic leucine zipper containing domain proteins (bZIP), amino-acid sequence WRKYGQK (WRKY), myelocytomatosis related proteins (MYC), myeloblastosis related proteins (MYB), APETALA2/ ETHYLENE-RESPONSIVE ELEMENT BINDING FACTORS (AP2/EREBP) and no apical meristem (NAM), Arabidopsis transcription activation factor (ATAF), and cup-shaped cotyledon (CUC) (NAC). We describe the interaction partners of these transcription factors as molecular responses during pathogen attack and the key components of signal transduction pathways that take place during plant defense responses. These interactions determine the activation or repression of response pathways and are crucial to understanding the regulatory networks that modulate plant defense responses. PMID:28250372

  19. A General System for Studying Protein-Protein Interactions in Gram-Negative Bacteria

    SciTech Connect

    Pelletier, Dale A; Auberry, Deanna L; Buchanan, Michelle V; Cannon, Bill; Daly, Don S.; Doktycz, Mitchel John; Foote, Linda J; Hervey, IV, William Judson; Hooker, Brian; Hurst, Gregory {Greg} B; Kennel, Steve J; Lankford, Patricia K; Larimer, Frank W; Lu, Tse-Yuan S; McDonald, W Hayes; McKeown, Catherine K; Morrell-Falvey, Jennifer L; Owens, Elizabeth T; Schmoyer, Denise D; Shah, Manesh B; Wiley, Steven; Wang, Yisong; Gilmore, Jason

    2008-01-01

    Abstract One of the most promising methods for large-scale studies of protein interactions is isolation of an affinity-tagged protein with its in vivo interaction partners, followed by mass spectrometric identification of the copurified proteins. Previous studies have generated affinity-tagged proteins using genetic tools or cloning systems that are specific to a particular organism. To enable protein-protein interaction studies across a wider range of Gram-negative bacteria, we have developed a methodology based on expression of affinity-tagged bait proteins from a medium copy-number plasmid. This construct is based on a broad-host-range vector backbone (pBBR1MCS5). The vector has been modified to incorporate the Gateway DEST vector recombination region, to facilitate cloning and expression of fusion proteins bearing a variety of affinity, fluorescent, or other tags. We demonstrate this methodology by characterizing interactions among subunits of the DNA-dependent RNA polymerase complex in two metabolically versatile Gram-negative microbial species of environmental interest, Rhodopseudomonas palustris CGA010 and Shewanella oneidensis MR-1. Results compared favorably with those for both plasmid and chromosomally encoded affinity-tagged fusion proteins expressed in a model organism, Escherichia coli.

  20. Extraction of Protein-Protein Interaction from Scientific Articles by Predicting Dominant Keywords.

    PubMed

    Koyabu, Shun; Phan, Thi Thanh Thuy; Ohkawa, Takenao

    2015-01-01

    For the automatic extraction of protein-protein interaction information from scientific articles, a machine learning approach is useful. The classifier is generated from training data represented using several features to decide whether a protein pair in each sentence has an interaction. Such a specific keyword that is directly related to interaction as "bind" or "interact" plays an important role for training classifiers. We call it a dominant keyword that affects the capability of the classifier. Although it is important to identify the dominant keywords, whether a keyword is dominant depends on the context in which it occurs. Therefore, we propose a method for predicting whether a keyword is dominant for each instance. In this method, a keyword that derives imbalanced classification results is tentatively assumed to be a dominant keyword initially. Then the classifiers are separately trained from the instance with and without the assumed dominant keywords. The validity of the assumed dominant keyword is evaluated based on the classification results of the generated classifiers. The assumption is updated by the evaluation result. Repeating this process increases the prediction accuracy of the dominant keyword. Our experimental results using five corpora show the effectiveness of our proposed method with dominant keyword prediction.

  1. Techniques for the Analysis of Protein-Protein Interactions in Vivo1[OPEN

    PubMed Central

    Xing, Shuping; Wallmeroth, Niklas; Berendzen, Kenneth W.

    2016-01-01

    Identifying key players and their interactions is fundamental for understanding biochemical mechanisms at the molecular level. The ever-increasing number of alternative ways to detect protein-protein interactions (PPIs) speaks volumes about the creativity of scientists in hunting for the optimal technique. PPIs derived from single experiments or high-throughput screens enable the decoding of binary interactions, the building of large-scale interaction maps of single organisms, and the establishment of cross-species networks. This review provides a historical view of the development of PPI technology over the past three decades, particularly focusing on in vivo PPI techniques that are inexpensive to perform and/or easy to implement in a state-of-the-art molecular biology laboratory. Special emphasis is given to their feasibility and application for plant biology as well as recent improvements or additions to these established techniques. The biology behind each method and its advantages and disadvantages are discussed in detail, as are the design, execution, and evaluation of PPI analysis. We also aim to raise awareness about the technological considerations and the inherent flaws of these methods, which may have an impact on the biological interpretation of PPIs. Ultimately, we hope this review serves as a useful reference when choosing the most suitable PPI technique. PMID:27208310

  2. Development of a Capillary Electrophoresis Platform for Identifying Inhibitors of Protein-Protein Interactions

    PubMed Central

    Rauch, Jennifer N.; Nie, Jing; Buchholz, Tonia J.; Gestwicki, Jason E.; Kennedy, Robert T.

    2013-01-01

    Methods for identifying chemical inhibitors of protein-protein interactions (PPIs) are often prone to discovery of false positives, particularly those caused by molecules that induce protein aggregation. Thus, there is interest in developing new platforms that might allow earlier identification of these problematic compounds. Capillary electrophoresis (CE) has been evaluated as a method to screen for PPI inhibitors using the challenging system of Hsp70 interacting with its co-chaperone Bag3. In the method, Hsp70 is labeled with a fluorophore, mixed with Bag3, and the resulting bound and free Hsp70 separated and detected by CE with laser-induced fluorescence detection. The method used a chemically modified CE capillary to prevent protein adsorption. Inhibitors of the Hsp70-Bag3 interaction were detected by observing a reduction in the bound to free ratio. The method was used to screen a library of 3,443 compounds and results compared to those from a flow cytometry protein interaction assay. CE was found to produce a lower hit rate with more compounds that reconfirmed in subsequent testing suggesting greater specificity. This finding was attributed to use of electropherograms to detect artifacts such as aggregators and to differences in protein modifications required to perform the different assays. Increases in throughput are required to make the CE method suitable for primary screens but at the current stage of development it is attractive as a secondary screen to test hits found by higher throughput methods. PMID:24060167

  3. Development of a capillary electrophoresis platform for identifying inhibitors of protein-protein interactions.

    PubMed

    Rauch, Jennifer N; Nie, Jing; Buchholz, Tonia J; Gestwicki, Jason E; Kennedy, Robert T

    2013-10-15

    Methods for identifying chemical inhibitors of protein-protein interactions (PPIs) are often prone to discovery of false positives, particularly those caused by molecules that induce protein aggregation. Thus, there is interest in developing new platforms that might allow earlier identification of these problematic compounds. Capillary electrophoresis (CE) has been evaluated as a method to screen for PPI inhibitors using the challenging system of Hsp70 interacting with its co-chaperone Bag3. In the method, Hsp70 is labeled with a fluorophore, mixed with Bag3, and the resulting bound and free Hsp70 are separated and detected by CE with laser-induced fluorescence detection. The method used a chemically modified CE capillary to prevent protein adsorption. Inhibitors of the Hsp70-Bag3 interaction were detected by observing a reduction in the bound-to-free ratio. The method was used to screen a library of 3443 compounds, and the results were compared to those from a flow cytometry protein interaction assay. CE was found to produce a lower hit rate with more compounds that were reconfirmed in subsequent testing, suggesting greater specificity. This finding was attributed to the use of electropherograms to detect artifacts such as aggregators and to differences in protein modifications required to perform the different assays. Increases in throughput are required to make the CE method suitable for primary screens, but at the current stage of development it is attractive as a secondary screen to test hits found by higher-throughput methods.

  4. Pathway Analysis Incorporating Protein-Protein Interaction Networks Identified Candidate Pathways for the Seven Common Diseases

    PubMed Central

    Lin, Peng-Lin; Yu, Ya-Wen

    2016-01-01

    Pathway analysis has become popular as a secondary analysis strategy for genome-wide association studies (GWAS). Most of the current pathway analysis methods aggregate signals from the main effects of single nucleotide polymorphisms (SNPs) in genes within a pathway without considering the effects of gene-gene interactions. However, gene-gene interactions can also have critical effects on complex diseases. Protein-protein interaction (PPI) networks have been used to define gene pairs for the gene-gene interaction tests. Incorporating the PPI information to define gene pairs for interaction tests within pathways can increase the power for pathway-based association tests. We propose a pathway association test, which aggregates the interaction signals in PPI networks within a pathway, for GWAS with case-control samples. Gene size is properly considered in the test so that genes do not contribute more to the test statistic simply due to their size. Simulation studies were performed to verify that the method is a valid test and can have more power than other pathway association tests in the presence of gene-gene interactions within a pathway under different scenarios. We applied the test to the Wellcome Trust Case Control Consortium GWAS datasets for seven common diseases. The most significant pathway is the chaperones modulate interferon signaling pathway for Crohn’s disease (p-value = 0.0003). The pathway modulates interferon gamma, which induces the JAK/STAT pathway that is involved in Crohn’s disease. Several other pathways that have functional implications for the seven diseases were also identified. The proposed test based on gene-gene interaction signals in PPI networks can be used as a complementary tool to the current existing pathway analysis methods focusing on main effects of genes. An efficient software implementing the method is freely available at http://puppi.sourceforge.net. PMID:27622767

  5. Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

    PubMed

    Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

    2008-10-01

    Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

  6. Network Biomarkers Constructed from Gene Expression and Protein-Protein Interaction Data for Accurate Prediction of Leukemia

    PubMed Central

    Yuan, Xuye; Chen, Jiajia; Lin, Yuxin; Li, Yin; Xu, Lihua; Chen, Luonan; Hua, Haiying; Shen, Bairong

    2017-01-01

    Leukemia is a leading cause of cancer deaths in the developed countries. Great efforts have been undertaken in search of diagnostic biomarkers of leukemia. However, leukemia is highly complex and heterogeneous, involving interaction among multiple molecular components. Individual molecules are not necessarily sensitive diagnostic indicators. Network biomarkers are considered to outperform individual molecules in disease characterization. We applied an integrative approach that identifies active network modules as putative biomarkers for leukemia diagnosis. We first reconstructed the leukemia-specific PPI network using protein-protein interactions from the Protein Interaction Network Analysis (PINA) and protein annotations from GeneGo. The network was further integrated with gene expression profiles to identify active modules with leukemia relevance. Finally, the candidate network-based biomarker was evaluated for the diagnosing performance. A network of 97 genes and 400 interactions was identified for accurate diagnosis of leukemia. Functional enrichment analysis revealed that the network biomarkers were enriched in pathways in cancer. The network biomarkers could discriminate leukemia samples from the normal controls more effectively than the known biomarkers. The network biomarkers provide a useful tool to diagnose leukemia and also aids in further understanding the molecular basis of leukemia. PMID:28243332

  7. Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions

    SciTech Connect

    Shatsky, Maxim; Dong, Ming; Liu, Haichuan; Yang, Lee Lisheng; Choi, Megan; Singer, Mary; Geller, Jil; Fisher, Susan; Hall, Steven; Hazen, Terry C.; Brenner, Steven; Butland, Gareth; Jin, Jian; Witkowska, H. Ewa; Chandonia, John-Marc; Biggin, Mark D.

    2016-04-20

    Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification of endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.

  8. Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions*

    PubMed Central

    Shatsky, Maxim; Dong, Ming; Liu, Haichuan; Yang, Lee Lisheng; Choi, Megan; Singer, Mary E.; Geller, Jil T.; Fisher, Susan J.; Hall, Steven C.; Hazen, Terry C.; Brenner, Steven E.; Butland, Gareth; Jin, Jian; Witkowska, H. Ewa; Chandonia, John-Marc; Biggin, Mark D.

    2016-01-01

    Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification of endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR. PMID:27099342

  9. Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions

    DOE PAGES

    Shatsky, Maxim; Dong, Ming; Liu, Haichuan; ...

    2016-04-20

    Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification ofmore » endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.« less

  10. Molecular modeling of the inhibition of protein-protein interactions with small molecules: The IL2-IL2Rα case

    NASA Astrophysics Data System (ADS)

    Pieraccini, Stefano; De Gonda, Riccardo; Sironi, Maurizio

    2011-12-01

    Developing drug like molecules targeting protein-protein interactions is one of the main goals of current medicinal chemistry. To drive the design process it is fundamental to locate those sites on the protein-protein contact surface that are more critical for protein binding, which are the most eligible targets to affect the protein complex formation. In this work we show how computational alanine scanning can be used to identify such critical sites and evaluate their interactions with small molecules designed to inhibit the complex formation. Complex of protein IL2 with IL2Rα and with some small molecule inhibitors are used as an example.

  11. Lanthanide-based imaging of protein-protein interactions in live cells.

    PubMed

    Rajendran, Megha; Yapici, Engin; Miller, Lawrence W

    2014-02-17

    In order to deduce the molecular mechanisms of biological function, it is necessary to monitor changes in the subcellular location, activation, and interaction of proteins within living cells in real time. Förster resonance energy-transfer (FRET)-based biosensors that incorporate genetically encoded, fluorescent proteins permit high spatial resolution imaging of protein-protein interactions or protein conformational dynamics. However, a nonspecific fluorescence background often obscures small FRET signal changes, and intensity-based biosensor measurements require careful interpretation and several control experiments. These problems can be overcome by using lanthanide [Tb(III) or Eu(III)] complexes as donors and green fluorescent protein (GFP) or other conventional fluorophores as acceptors. Essential features of this approach are the long-lifetime (approximately milliseconds) luminescence of Tb(III) complexes and time-gated luminescence microscopy. This allows pulsed excitation, followed by a brief delay, which eliminates nonspecific fluorescence before the detection of Tb(III)-to-GFP emission. The challenges of intracellular delivery, selective protein labeling, and time-gated imaging of lanthanide luminescence are presented, and recent efforts to investigate the cellular uptake of lanthanide probes are reviewed. Data are presented showing that conjugation to arginine-rich, cell-penetrating peptides (CPPs) can be used as a general strategy for the cellular delivery of membrane-impermeable lanthanide complexes. A heterodimer of a luminescent Tb(III) complex, Lumi4, linked to trimethoprim and conjugated to nonaarginine via a reducible disulfide linker rapidly (∼10 min) translocates into the cytoplasm of Maden Darby canine kidney cells from the culture medium. With this reagent, the intracellular interaction between GFP fused to FK506 binding protein 12 (GFP-FKBP12) and the rapamycin binding domain of mTOR fused to Escherichia coli dihydrofolate reductase (FRB

  12. Transient protein-protein interactions perturb E. coli metabolome and cause gene dosage toxicity

    PubMed Central

    Bhattacharyya, Sanchari; Bershtein, Shimon; Yan, Jin; Argun, Tijda; Gilson, Amy I; Trauger, Sunia A; Shakhnovich, Eugene I

    2016-01-01

    Gene dosage toxicity (GDT) is an important factor that determines optimal levels of protein abundances, yet its molecular underpinnings remain unknown. Here, we demonstrate that overexpression of DHFR in E. coli causes a toxic metabolic imbalance triggered by interactions with several functionally related enzymes. Though deleterious in the overexpression regime, surprisingly, these interactions are beneficial at physiological concentrations, implying their functional significance in vivo. Moreover, we found that overexpression of orthologous DHFR proteins had minimal effect on all levels of cellular organization – molecular, systems, and phenotypic, in sharp contrast to E. coli DHFR. Dramatic difference of GDT between ‘E. coli’s self’ and ‘foreign’ proteins suggests the crucial role of evolutionary selection in shaping protein-protein interaction (PPI) networks at the whole proteome level. This study shows how protein overexpression perturbs a dynamic metabolon of weak yet potentially functional PPI, with consequences for the metabolic state of cells and their fitness. DOI: http://dx.doi.org/10.7554/eLife.20309.001 PMID:27938662

  13. Targeting a dynamic protein-protein interaction: fragment screening against the malaria myosin A motor complex.

    PubMed

    Douse, Christopher H; Vrielink, Nina; Wenlin, Zhang; Cota, Ernesto; Tate, Edward W

    2015-01-01

    Motility is a vital feature of the complex life cycle of Plasmodium falciparum, the apicomplexan parasite that causes human malaria. Processes such as host cell invasion are thought to be powered by a conserved actomyosin motor (containing myosin A or myoA), correct localization of which is dependent on a tight interaction with myosin A tail domain interacting protein (MTIP) at the inner membrane of the parasite. Although disruption of this protein-protein interaction represents an attractive means to investigate the putative roles of myoA-based motility and to inhibit the parasitic life cycle, no small molecules have been identified that bind to MTIP. Furthermore, it has not been possible to obtain a crystal structure of the free protein, which is highly dynamic and unstable in the absence of its natural myoA tail partner. Herein we report the de novo identification of the first molecules that bind to and stabilize MTIP via a fragment-based, integrated biophysical approach and structural investigations to examine the binding modes of hit compounds. The challenges of targeting such a dynamic system with traditional fragment screening workflows are addressed throughout.

  14. Mining topological structures of protein-protein interaction networks for human brain-specific genes.

    PubMed

    Cui, W J; Gong, X J; Yu, H; Zhang, X C

    2015-10-16

    Compared to other placental mammals, humans have unique thinking and cognitive abilities because of their developed cerebral cortex composed of billions of neurons and synaptic connections. As the primary effectors of the mechanisms of life, proteins and their interactions form the basis of cellular and molecular functions in the living body. In this paper, we developed a pipeline for mining topological structures, identifying functional modules, and analyzing their functions from publically available datasets. A human brain-specific protein-protein interaction network with 1482 nodes and 3105 edges was built using a MapReduce based shortest path algorithm. Within this, 7 functional cliques were identified using a network clustering method, 98 hub proteins were obtained by the calculation of betweenness and connectivity, and 5 closest relationship to clique connector proteins were recognized by the combination scores of topological distance and gene ontology similarity. Furthermore, we discovered functional modules interacting with TP53 protein, which involves several fragmented research study conclusions and might be an important clue for further in vivo or in silico experiments to confirm these associations.

  15. Regulation of dopamine transporter function by protein-protein interactions: new discoveries and methodological challenges.

    PubMed

    Eriksen, Jacob; Jørgensen, Trine Nygaard; Gether, Ulrik

    2010-04-01

    The dopamine transporter (DAT) plays a key role in regulating dopaminergic signalling in the brain by mediating rapid clearance of dopamine from the synaptic clefts. The psychostimulatory actions of cocaine and amphetamine are primarily the result of a direct interaction of these compounds with DAT leading to attenuated dopamine clearance and for amphetamine even increased dopamine release. In the last decade, intensive efforts have been directed towards understanding the molecular and cellular mechanisms governing the activity and availability of DAT in the plasma membrane of the pre-synaptic neurons. This has led to the identification of a plethora of different kinases, receptors and scaffolding proteins that interact with DAT and hereby either modulate the catalytic activity of the transporter or regulate its trafficking and degradation. Several new tools for studying DAT regulation in live cells have also recently become available such as fluorescently tagged cocaine analogues and fluorescent substrates. Here we review the current knowledge about the role of protein-protein interactions in DAT regulation as well as we describe the most recent methodological developments that have been established to overcome the challenges associated with the study of DAT in endogenous systems.

  16. Protein-Protein Interaction Network and Subcellular Localization of the Arabidopsis Thaliana ESCRT Machinery.

    PubMed

    Richardson, Lynn G L; Howard, Alexander S M; Khuu, Nicholas; Gidda, Satinder K; McCartney, Andrew; Morphy, Brett J; Mullen, Robert T

    2011-01-01

    The endosomal sorting complex required for transport (ESCRT) consists of several multi-protein subcomplexes which assemble sequentially at the endosomal surface and function in multivesicular body (MVB) biogenesis. While ESCRT has been relatively well characterized in yeasts and mammals, comparably little is known about ESCRT in plants. Here we explored the yeast two-hybrid protein interaction network and subcellular localization of the Arabidopsis thaliana ESCRT machinery. We show that the Arabidopsis ESCRT interactome possesses a number of protein-protein interactions that are either conserved in yeasts and mammals or distinct to plants. We show also that most of the Arabidopsis ESCRT proteins examined at least partially localize to MVBs in plant cells when ectopically expressed on their own or co-expressed with other interacting ESCRT proteins, and some also induce abnormal MVB phenotypes, consistent with their proposed functional role(s) as part of the ESCRT machinery in Arabidopsis. Overall, our results help define the plant ESCRT machinery by highlighting both conserved and unique features when compared to ESCRT in other evolutionarily diverse organisms, providing a foundation for further exploration of ESCRT in plants.

  17. Prediction of Intra-Species Protein-Protein Interactions in Enteropathogens Facilitating Systems Biology Study

    PubMed Central

    Barman, Ranjan Kumar; Jana, Tanmoy; Das, Santasabuj; Saha, Sudipto

    2015-01-01

    Protein-protein interactions in Escherichia coli (E. coli) has been studied extensively using high throughput methods such as tandem affinity purification followed by mass spectrometry and yeast two-hybrid method. This can in turn be used to understand the mechanisms of bacterial cellular processes. However, experimental characterization of such huge amount of interactions data is not available for other important enteropathogens. Here, we propose a support vector machine (SVM)-based prediction model using the known PPIs data of E. coli that can be used to predict PPIs in other enteropathogens, such as Vibrio cholerae, Salmonella Typhi, Shigella flexneri and Yersinia entrocolitica. Different features such as domain-domain association (DDA), network topology, and sequence information were used in developing the SVM model. The proposed model using DDA, degree and amino acid composition features has achieved an accuracy of 82% and 62% on 5-fold cross validation and blind E. coli datasets, respectively. The predicted interactions were validated by Gene Ontology (GO) semantic similarity measure and String PPIs database (experimental PPIs only). Finally, we have developed a user-friendly webserver named EnPPIpred to predict intra-species PPIs in enteropathogens, which will be of great help for the experimental biologists. The webserver EnPPIpred is freely available at http://bicresources.jcbose.ac.in/ssaha4/EnPPIpred/. PMID:26717407

  18. Prediction of Intra-Species Protein-Protein Interactions in Enteropathogens Facilitating Systems Biology Study.

    PubMed

    Barman, Ranjan Kumar; Jana, Tanmoy; Das, Santasabuj; Saha, Sudipto

    2015-01-01

    Protein-protein interactions in Escherichia coli (E. coli) has been studied extensively using high throughput methods such as tandem affinity purification followed by mass spectrometry and yeast two-hybrid method. This can in turn be used to understand the mechanisms of bacterial cellular processes. However, experimental characterization of such huge amount of interactions data is not available for other important enteropathogens. Here, we propose a support vector machine (SVM)-based prediction model using the known PPIs data of E. coli that can be used to predict PPIs in other enteropathogens, such as Vibrio cholerae, Salmonella Typhi, Shigella flexneri and Yersinia entrocolitica. Different features such as domain-domain association (DDA), network topology, and sequence information were used in developing the SVM model. The proposed model using DDA, degree and amino acid composition features has achieved an accuracy of 82% and 62% on 5-fold cross validation and blind E. coli datasets, respectively. The predicted interactions were validated by Gene Ontology (GO) semantic similarity measure and String PPIs database (experimental PPIs only). Finally, we have developed a user-friendly webserver named EnPPIpred to predict intra-species PPIs in enteropathogens, which will be of great help for the experimental biologists. The webserver EnPPIpred is freely available at http://bicresources.jcbose.ac.in/ssaha4/EnPPIpred/.

  19. Anticancer osmium complex inhibitors of the HIF-1α and p300 protein-protein interaction

    PubMed Central

    Yang, Chao; Wang, Wanhe; Li, Guo-Dong; Zhong, Hai-Jing; Dong, Zhen-Zhen; Wong, Chun-Yuen; Kwong, Daniel W. J.; Ma, Dik-Lung; Leung, Chung-Hang

    2017-01-01

    The hypoxia inducible factor (HIF) pathway has been considered to be an attractive anti-cancer target. One strategy to inhibit HIF activity is through the disruption of the HIF-1α–p300 protein-protein interaction. We report herein the identification of an osmium(II) complex as the first metal-based inhibitor of the HIF-1α–p300 interaction. We evaluated the effect of complex 1 on HIF-1α signaling pathway in vitro and in cellulo by using the dual luciferase reporter assay, co-immunoprecipitation assay, and immunoblot assay. Complex 1 exhibited a dose-dependent inhibition of HRE-driven luciferase activity, with an IC50 value of 1.22 μM. Complex 1 interfered with the HIF-1α–p300 interaction as revealed by a dose-dependent reduction of p300 co-precipitated with HIF-1α as the concentration of complex 1 was increased. Complex 1 repressed the phosphorylation of SRC, AKT and STAT3, and had no discernible effect on the activity of NF-κB. We anticipate that complex 1 could be utilized as a promising scaffold for the further development of more potent HIF-1α inhibitors for anti-cancer treatment. PMID:28225008

  20. Protein-Protein Interaction Investigated by Steered Molecular Dynamics: The TCR-pMHC Complex

    PubMed Central

    Cuendet, Michel A.; Michielin, Olivier

    2008-01-01

    We present a novel steered molecular dynamics scheme to induce the dissociation of large protein-protein complexes. We apply this scheme to study the interaction of a T cell receptor (TCR) with a major histocompatibility complex (MHC) presenting a peptide (p). Two TCR-pMHC complexes are considered, which only differ by the mutation of a single amino acid on the peptide; one is a strong agonist that produces T cell activation in vivo, while the other is an antagonist. We investigate the interaction mechanism from a large number of unbinding trajectories by analyzing van der Waals and electrostatic interactions and by computing energy changes in proteins and solvent. In addition, dissociation potentials of mean force are calculated with the Jarzynski identity, using an averaging method developed for our steering scheme. We analyze the convergence of the Jarzynski exponential average, which is hampered by the large amount of dissipative work involved and the complexity of the system. The resulting dissociation free energies largely underestimate experimental values, but the simulations are able to clearly differentiate between wild-type and mutated TCR-pMHC and give insights into the dissociation mechanism. PMID:18621828

  1. Protein Cross-Linking Capillary Electrophoresis for Protein-Protein Interaction Analysis.

    PubMed

    Ouimet, Claire M; Shao, Hao; Rauch, Jennifer N; Dawod, Mohamed; Nordhues, Bryce; Dickey, Chad A; Gestwicki, Jason E; Kennedy, Robert T

    2016-08-16

    Capillary electrophoresis (CE) has been identified as a useful platform for detecting, quantifying, and screening for modulators of protein-protein interactions (PPIs). In this method, one protein binding partner is labeled with a fluorophore, the protein binding partners are mixed, and then, the complex is separated from free protein to allow direct determination of bound to free ratios. Although it possesses many advantages for PPI studies, the method is limited by the need to have separation conditions that both prevent protein adsorption to capillary and maintain protein interactions during the separation. In this work, we use protein cross-linking capillary electrophoresis (PXCE) to overcome this limitation. In PXCE, the proteins are cross-linked under binding conditions and then separated. This approach eliminates the need to maintain noncovalent interactions during electrophoresis and facilitates method development. We report PXCE methods for an antibody-antigen interaction and heterodimer and homodimer heat shock protein complexes. Complexes are cross-linked by short treatments with formaldehyde after reaching binding equilibrium. Cross-linked complexes are separated by electrophoretic mobility using free solution CE or by size using sieving electrophoresis of SDS complexes. The method gives good quantitative results; e.g., a lysozyme-antibody interaction was found to have Kd = 24 ± 3 nM by PXCE and Kd = 17 ± 2 nM using isothermal calorimetry (ITC). Heat shock protein 70 (Hsp70) in complex with bcl2 associated athanogene 3 (Bag3) was found to have Kd = 25 ± 5 nM by PXCE which agrees with Kd values reported without cross-linking. Hsp70-Bag3 binding site mutants and small molecule inhibitors of Hsp70-Bag3 were characterized by PXCE with good agreement to inhibitory constants and IC50 values obtained by a bead-based flow cytometry protein interaction assay (FCPIA). PXCE allows rapid method development for quantitative analysis of PPIs.

  2. Testis-Specific Y-Centric Protein-Protein Interaction Network Provides Clues to the Etiology of Severe Spermatogenic Failure.

    PubMed

    Ansari-Pour, Naser; Razaghi-Moghadam, Zahra; Barneh, Farnaz; Jafari, Mohieddin

    2016-03-04

    Pinpointing causal genes for spermatogenic failure (SpF) on the Y chromosome has been an ever daunting challenge with setbacks during the past decade. Since complex diseases result from the interaction of multiple genes and also display considerable missing heritability, network analysis is more likely to explicate an etiological molecular basis. We therefore took a network medicine approach by integrating interactome (protein-protein interaction (PPI)) and transcriptome data to reconstruct a Y-centric SpF network. Two sets of seed genes (Y genes and SpF-implicated genes (SIGs)) were used for network reconstruction. Since no PPI was observed among Y genes, we identified their common immediate interactors. Interestingly, 81% (N = 175) of these interactors not only interacted directly with SIGs, but also they were enriched for differentially expressed genes (89.6%; N = 43). The SpF network, formed mainly by the dys-regulated interactors and the two seed gene sets, comprised three modules enriched for ribosomal proteins and nuclear receptors for sex hormones. Ribosomal proteins generally showed significant dys-regulation with RPL39L, thought to be expressed at the onset of spermatogenesis, strongly down-regulated. This network is the first global PPI network pertaining to severe SpF and if experimentally validated on independent data sets can lead to more accurate diagnosis and potential fertility recovery of patients.

  3. Specific anion effects on the pressure dependence of the protein-protein interaction potential.

    PubMed

    Möller, Johannes; Grobelny, Sebastian; Schulze, Julian; Steffen, Andre; Bieder, Steffen; Paulus, Michael; Tolan, Metin; Winter, Roland

    2014-04-28

    We present a study on ion specific effects on the intermolecular interaction potential V(r) of dense protein solutions under high hydrostatic pressure conditions. Small-angle X-ray scattering in combination with a liquid-state theoretical approach was used to determine the effect of structure breaking/making salt anions (Cl(-), SO4(2-), PO4(3-)) on the intermolecular interaction of lysozyme molecules. It was found that besides the Debye-Hückel charge screening effect, reducing the repulsiveness of the interaction potential V(r) at low salt concentrations, a specific ion effect is observed at high salt concentrations for the multivalent kosmotropic anions, which modulates also the pressure dependence of the protein-protein interaction potential. Whereas sulfate and phosphate strongly influence the pressure dependence of V(r), chloride anions do not. The strong structure-making effect of the multivalent anions, dominating for the triply charged PO4(3-), renders the solution structure less bulk-water-like at high salt concentrations, which leads to an altered behavior of the pressure dependence of V(r). Hence, the particular structural properties of the salt solutions are able to influence the spatial organization and the intermolecular interactions of the proteins, in particular upon compression. These results are of interest for exploring the combined effects of ionic strength, temperature and pressure on the phase behavior of protein solutions, but may also be of relevance for understanding pressure effects on the hydration behavior of biological matter under extreme environmental conditions.

  4. Tetramer formation in Arabidopsis MADS domain proteins: analysis of a protein-protein interaction network

    PubMed Central

    2014-01-01

    Background MADS domain proteins are transcription factors that coordinate several important developmental processes in plants. These proteins interact with other MADS domain proteins to form dimers, and it has been proposed that they are able to associate as tetrameric complexes that regulate transcription of target genes. Whether the formation of functional tetramers is a widespread property of plant MADS domain proteins, or it is specific to few of these transcriptional regulators remains unclear. Results We analyzed the structure of the network of physical interactions among MADS domain proteins in Arabidopsis thaliana. We determined the abundance of subgraphs that represent the connection pattern expected for a MADS domain protein heterotetramer. These subgraphs were significantly more abundant in the MADS domain protein interaction network than in randomized analogous networks. Importantly, these subgraphs are not significantly frequent in a protein interaction network of TCP plant transcription factors, when compared to expectation by chance. In addition, we found that MADS domain proteins in tetramer-like subgraphs are more likely to be expressed jointly than proteins in other subgraphs. This effect is mainly due to proteins in the monophyletic MIKC clade, as there is no association between tetramer-like subgraphs and co-expression for proteins outside this clade. Conclusions Our results support that the tendency to form functional tetramers is widespread in the MADS domain protein-protein interaction network. Our observations also suggest that this trend is prevalent, or perhaps exclusive, for proteins in the MIKC clade. Because it is possible to retrodict several experimental results from our analyses, our work can be an important aid to make new predictions and facilitates experimental research on plant MADS domain proteins. PMID:24468197

  5. Stabilization of collagen through bioconversion: An insight in protein-protein interaction.

    PubMed

    Usharani, Nagarajan; Jayakumar, Gladstone Christopher; Kanth, Swarna Vinodh; Rao, Jonnalagadda Raghava

    2014-08-01

    Collagen is a natural protein, which is used as a vital biomaterial in tissue engineering. The major concern about native collagen is lack of its thermal stability and weak resistance to proteolytic degradation. In this scenario, the crosslinking compounds used for stabilization of collagen are mostly of chemical nature and exhibit toxicity. The enzyme mediated crosslinking of collagen provides a novel alternative, nontoxic method for stabilization. In this study, aldehyde forming enzyme (AFE) is used in the bioconversion of hydroxylmethyl groups of collagen to formyl groups that results in the formation of peptidyl aldehyde. The resulted peptidyl aldehyde interacts with bipolar ions of basic amino acid residues of collagen. Further interaction leads to the formation of conjugated double bonds (aldol condensation involving the aldehyde group of peptidyl aldehyde) within the collagen. The enzyme modified collagen matrices have shown an increase in the denaturation temperature, when compared with native collagen. Enzyme modified collagen membranes exhibit resistance toward collagenolytic activity. Moreover, they exhibited a nontoxic nature. The catalytic activity of AFE on collagen as a substrate establishes an efficient modification, which enhances the structural stability of collagen. This finds new avenues in the context of protein-protein stabilization and discovers paramount application in tissue engineering.

  6. PIE: an online prediction system for protein-protein interactions from text.

    PubMed

    Kim, Sun; Shin, Soo-Yong; Lee, In-Hee; Kim, Soo-Jin; Sriram, Ram; Zhang, Byoung-Tak

    2008-07-01

    Protein-protein interaction (PPI) extraction has been an important research topic in bio-text mining area, since the PPI information is critical for understanding biological processes. However, there are very few open systems available on the Web and most of the systems focus on keyword searching based on predefined PPIs. PIE (Protein Interaction information Extraction system) is a configurable Web service to extract PPIs from literature, including user-provided papers as well as PubMed articles. After providing abstracts or papers, the prediction results are displayed in an easily readable form with essential, yet compact features. The PIE interface supports more features such as PDF file extraction, PubMed search tool and network communication, which are useful for biologists and bio-system developers. The PIE system utilizes natural language processing techniques and machine learning methodologies to predict PPI sentences, which results in high precision performance for Web users. PIE is freely available at http://bi.snu.ac.kr/pie/.

  7. Trifunctional cross-linker for mapping protein-protein interaction networks and comparing protein conformational states

    PubMed Central

    Tan, Dan; Li, Qiang; Zhang, Mei-Jun; Liu, Chao; Ma, Chengying; Zhang, Pan; Ding, Yue-He; Fan, Sheng-Bo; Tao, Li; Yang, Bing; Li, Xiangke; Ma, Shoucai; Liu, Junjie; Feng, Boya; Liu, Xiaohui; Wang, Hong-Wei; He, Si-Min; Gao, Ning; Ye, Keqiong; Dong, Meng-Qiu; Lei, Xiaoguang

    2016-01-01

    To improve chemical cross-linking of proteins coupled with mass spectrometry (CXMS), we developed a lysine-targeted enrichable cross-linker containing a biotin tag for affinity purification, a chemical cleavage site to separate cross-linked peptides away from biotin after enrichment, and a spacer arm that can be labeled with stable isotopes for quantitation. By locating the flexible proteins on the surface of 70S ribosome, we show that this trifunctional cross-linker is effective at attaining structural information not easily attainable by crystallography and electron microscopy. From a crude Rrp46 immunoprecipitate, it helped identify two direct binding partners of Rrp46 and 15 protein-protein interactions (PPIs) among the co-immunoprecipitated exosome subunits. Applying it to E. coli and C. elegans lysates, we identified 3130 and 893 inter-linked lysine pairs, representing 677 and 121 PPIs. Using a quantitative CXMS workflow we demonstrate that it can reveal changes in the reactivity of lysine residues due to protein-nucleic acid interaction. DOI: http://dx.doi.org/10.7554/eLife.12509.001 PMID:26952210

  8. Predicting Protein-Protein Interaction Sites with a Novel Membership Based Fuzzy SVM Classifier.

    PubMed

    Sriwastava, Brijesh K; Basu, Subhadip; Maulik, Ujjwal

    2015-01-01

    Predicting residues that participate in protein-protein interactions (PPI) helps to identify, which amino acids are located at the interface. In this paper, we show that the performance of the classical support vector machine (SVM) algorithm can further be improved with the use of a custom-designed fuzzy membership function, for the partner-specific PPI interface prediction problem. We evaluated the performances of both classical SVM and fuzzy SVM (F-SVM) on the PPI databases of three different model proteomes of Homo sapiens, Escherichia coli and Saccharomyces Cerevisiae and calculated the statistical significance of the developed F-SVM over classical SVM algorithm. We also compared our performance with the available state-of-the-art fuzzy methods in this domain and observed significant performance improvements. To predict interaction sites in protein complexes, local composition of amino acids together with their physico-chemical characteristics are used, where the F-SVM based prediction method exploits the membership function for each pair of sequence fragments. The average F-SVM performance (area under ROC curve) on the test samples in 10-fold cross validation experiment are measured as 77.07, 78.39, and 74.91 percent for the aforementioned organisms respectively. Performances on independent test sets are obtained as 72.09, 73.24 and 82.74 percent respectively. The software is available for free download from http://code.google.com/p/cmater-bioinfo.

  9. Protein-protein interactions among components of the Drosophila primary sex determination signal.

    PubMed

    Liu, Y; Belote, J M

    1995-07-28

    Sex determination in Drosophila melanogaster is initiated in the early embryo by a signal provided by three types of genes: (1) X-linked numerator elements [e.g., sisterless-a (sis-a) and sisterless-b (sis-b)], (2) autosomally linked denominator elements [e.g., deadpan (dpn)], and (3) maternal factors [e.g., daughterless (da)]. This signal acts to stimulate transcription from an embryo-specific promoter of the master regulatory gene Sex-lethal (Sxl) in embryos that have two X chromosomes (females), while it fails to activate Sxl in those with only one X (males). It has been previously proposed that competitive dimerizations among the components of this signal might provide the molecular basis for this sex specificity. Here, we use the yeast two-hybrid system to demonstrate specific protein-protein interactions among the above-mentioned factors, and to delimit their interacting domains. These results support and extend the model of the molecular basis of the X/A ratio signal.

  10. Analysis of protein-protein interaction network in chronic obstructive pulmonary disease.

    PubMed

    Yuan, Y P; Shi, Y H; Gu, W C

    2014-10-31

    Chronic obstructive pulmonary disease (COPD) is a growing cause of morbidity and mortality throughout the world. The purpose of our study was to uncover biomarkers and explore its pathogenic mechanisms at the molecular level. The gene expression profiles of COPD samples and normal controls were downloaded from Gene Expression Omnibus. Matlab was used for data preprocessing and SAM4.0 was applied to determine the differentially expressed genes (DEGs). Furthermore, a protein-protein interaction (PPI) network was constructed by mapping the DEGs into PPI data, and functional analysis of the network was conducted with BiNGO. A total of 348 DEGs and 765 interactive genes were identified. The hub genes were mainly involved in metabolic processes and ribosome biogenesis. Several genes related to COPD in the PPI network were found, including CAMK1D, ALB, KIT, and DDX3Y. In conclusion, CAMK1D, ALB, KIT, and DDX3Y were chosen as candidate genes, which have the potential to be biomarkers or candidate target molecules to apply in clinical diagnosis and treatment of COPD.

  11. A coclustering approach for mining large protein-protein interaction networks.

    PubMed

    Pizzuti, Clara; Rombo, Simona E

    2012-01-01

    Several approaches have been presented in the literature to cluster Protein-Protein Interaction (PPI) networks. They can be grouped in two main categories: those allowing a protein to participate in different clusters and those generating only nonoverlapping clusters. In both cases, a challenging task is to find a suitable compromise between the biological relevance of the results and a comprehensive coverage of the analyzed networks. Indeed, methods returning high accurate results are often able to cover only small parts of the input PPI network, especially when low-characterized networks are considered. We present a coclustering-based technique able to generate both overlapping and nonoverlapping clusters. The density of the clusters to search for can also be set by the user. We tested our method on the two networks of yeast and human, and compared it to other five well-known techniques on the same interaction data sets. The results showed that, for all the examples considered, our approach always reaches a good compromise between accuracy and network coverage. Furthermore, the behavior of our algorithm is not influenced by the structure of the input network, different from all the techniques considered in the comparison, which returned very good results on the yeast network, while on the human network their outcomes are rather poor.

  12. Introduction of inflammatory bowel disease biomarkers panel using protein-protein interaction (PPI) network analysis

    PubMed Central

    Asadzadeh-Aghdaee, Hamid; Shahrokh, Shabnam; Norouzinia, Mohsen; Hosseini, Mostafa; Keramatinia, Aliasghar; Jamalan, Mostafa; Naghibzadeh, Bijan; Sadeghi, Ali; Jahani Sherafat, Somayeh; Zali, Mohammad Reza

    2016-01-01

    Aim: In the present study, a protein-protein interaction network construction is conducted for IBD. Background: Inflammatory bowel diseases as serious chronic gastrointestinal disorders attracted many molecular investigations. Diverse molecular information is present for IBD. However, these molecular findings are not highlighted based on interactome analysis. On the other hand, PPI network analysis is a powerful method for study of molecular interactions in the protein level that provide useful information for highlighting the desired key proteins. Methods: Cytoscape is the used software with its plug-ins for detailed analysis. Two centrality parameters including degree and betweenness are determined and the crucial proteins based on these parameters are introduced. Results: The 75 proteins among 100 initial proteins are included in the network of IBD. Seventy-five nodes and 260 edges constructed the network as a scale free network. The findings indicate that there are seven hub-bottleneck proteins in the IBD network. Conclusion: More examination revealed the essential roles of these key proteins in the integrity of the network. Finally, the indicator panel including NFKB1, CD40, TNFA, TYK2, NOD2, IL23R, and STAT3 is presented as a possible molecular index for IBD. PMID:28224022

  13. Targeting Plant Ethylene Responses by Controlling Essential Protein-Protein Interactions in the Ethylene Pathway.

    PubMed

    Bisson, Melanie M A; Groth, Georg

    2015-08-01

    The gaseous plant hormone ethylene regulates many processes of high agronomic relevance throughout the life span of plants. A central element in ethylene signaling is the endoplasmic reticulum (ER)-localized membrane protein ethylene insensitive2 (EIN2). Recent studies indicate that in response to ethylene, the extra-membranous C-terminal end of EIN2 is proteolytically processed and translocated from the ER to the nucleus. Here, we report that the conserved nuclear localization signal (NLS) mediating nuclear import of the EIN2 C-terminus provides an important domain for complex formation with ethylene receptor ethylene response1 (ETR1). EIN2 lacking the NLS domain shows strongly reduced affinity for the receptor. Interaction of EIN2 and ETR1 is also blocked by a synthetic peptide of the NLS motif. The corresponding peptide substantially reduces ethylene responses in planta. Our results uncover a novel mechanism and type of inhibitor interfering with ethylene signal transduction and ethylene responses in plants. Disruption of essential protein-protein interactions in the ethylene signaling pathway as shown in our study for the EIN2-ETR1 complex has the potential to guide the development of innovative ethylene antagonists for modern agriculture and horticulture.

  14. Construction of a protein-protein interaction network of Wilms' tumor and pathway prediction of molecular complexes.

    PubMed

    Teng, W J; Zhou, C; Liu, L J; Cao, X J; Zhuang, J; Liu, G X; Sun, C G

    2016-05-23

    Wilms' tumor (WT), or nephroblastoma, is the most common malignant renal cancer that affects the pediatric population. Great progress has been achieved in the treatment of WT, but it cannot be cured at present. Nonetheless, a protein-protein interaction network of WT should provide some new ideas and methods. The purpose of this study was to analyze the protein-protein interaction network of WT. We screened the confirmed disease-related genes using the Online Mendelian Inheritance in Man database, created a protein-protein interaction network based on biological function in the Cytoscape software, and detected molecular complexes and relevant pathways that may be included in the network. The results showed that the protein-protein interaction network of WT contains 654 nodes, 1544 edges, and 5 molecular complexes. Among them, complex 1 is predicted to be related to the Jak-STAT signaling pathway, regulation of hematopoiesis by cytokines, cytokine-cytokine receptor interaction, cytokine and inflammatory responses, and hematopoietic cell lineage pathways. Molecular complex 4 shows a correlation of WT with colorectal cancer and the ErbB signaling pathway. The proposed method can provide the bioinformatic foundation for further elucidation of the mechanisms of WT development.

  15. Compartmentalization and Functionality of Nuclear Disorder: Intrinsic Disorder and Protein-Protein Interactions in Intra-Nuclear Compartments.

    PubMed

    Meng, Fanchi; Na, Insung; Kurgan, Lukasz; Uversky, Vladimir N

    2015-12-25

    The cell nucleus contains a number of membrane-less organelles or intra-nuclear compartments. These compartments are dynamic structures representing liquid-droplet phases which are only slightly denser than the bulk intra-nuclear fluid. They possess different functions, have diverse morphologies, and are typically composed of RNA (or, in some cases, DNA) and proteins. We analyzed 3005 mouse proteins localized in specific intra-nuclear organelles, such as nucleolus, chromatin, Cajal bodies, nuclear speckles, promyelocytic leukemia (PML) nuclear bodies, nuclear lamina, nuclear pores, and perinuclear compartment and compared them with ~29,863 non-nuclear proteins from mouse proteome. Our analysis revealed that intrinsic disorder is enriched in the majority of intra-nuclear compartments, except for the nuclear pore and lamina. These compartments are depleted in proteins that lack disordered domains and enriched in proteins that have multiple disordered domains. Moonlighting proteins found in multiple intra-nuclear compartments are more likely to have multiple disordered domains. Protein-protein interaction networks in the intra-nuclear compartments are denser and include more hubs compared to the non-nuclear proteins. Hubs in the intra-nuclear compartments (except for the nuclear pore) are enriched in disorder compared with non-nuclear hubs and non-nuclear proteins. Therefore, our work provides support to the idea of the functional importance of intrinsic disorder in the cell nucleus and shows that many proteins associated with sub-nuclear organelles in nuclei of mouse cells are enriched in disorder. This high level of disorder in the mouse nuclear proteins defines their ability to serve as very promiscuous binders, possessing both large quantities of potential disorder-based interaction sites and the ability of a single such site to be involved in a large number of interactions.

  16. Small molecule inhibitors of PSD95-nNOS protein-protein interactions as novel analgesics

    PubMed Central

    Lee, Wan-Hung; Xu, Zhili; Ashpole, Nicole M.; Hudmon, Andy; Kulkarni, Pushkar M.; Thakur, Ganesh A.; Lai, Yvonne Y.; Hohmann, Andrea G.

    2015-01-01

    Aberrant increases in NMDA receptor (NMDAR) signaling contributes to central nervous system sensitization and chronic pain by activating neuronal nitric oxide synthase (nNOS) and generating nitric oxide (NO). Because the scaffolding protein postsynaptic density 95kDA (PSD95) tethers nNOS to NMDARs, the PSD95-nNOS complex represents a therapeutic target. Small molecule inhibitors IC87201 (EC5O: 23.94 µM) and ZL006 (EC50: 12.88 µM) directly inhibited binding of purified PSD95 and nNOS proteins in AlphaScreen without altering binding of PSD95 to ErbB4. Both PSD95-nNOS inhibitors suppressed glutamate-induced cell death with efficacy comparable to MK-801. IC87201 and ZL006 preferentially suppressed phase 2A pain behavior in the formalin test and suppressed allodynia induced by intraplantar complete Freund’s adjuvant administration. IC87201 and ZL006 suppressed mechanical and cold allodynia induced by the chemotherapeutic agent paclitaxel (ED50s: 2.47 and 0.93 mg/kg i.p. for IC87201 and ZL006, respectively). Efficacy of PSD95-nNOS disruptors was similar to MK-801. Motor ataxic effects were induced by MK-801 but not by ZL006 or IC87201. Finally, MK-801 produced hyperalgesia in the tail-flick test whereas IC87201 and ZL006 did not alter basal nociceptive thresholds. Our studies establish the utility of using AlphaScreen and purified protein pairs to establish and quantify disruption of protein-protein interactions. Our results demonstrate previously unrecognized antinociceptive efficacy of ZL006 and establish, using two small molecules, a broad application for PSD95-nNOS inhibitors in treating neuropathic and inflammatory pain. Collectively, our results demonstrate that disrupting PSD95-nNOS protein-protein interactions is effective in attenuating pathological pain without producing unwanted side effects (i.e. motor ataxia) associated with NMDAR antagonists. PMID:26071110

  17. PPI-IRO: a two-stage method for protein-protein interaction extraction based on interaction relation ontology.

    PubMed

    Li, Chuan-Xi; Chen, Peng; Wang, Ru-Jing; Wang, Xiu-Jie; Su, Ya-Ru; Li, Jinyan

    2014-01-01

    Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identification of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifies and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At first, IRO is applied in a binary classifier to determine whether sentences contain a relation or not. Then, IRO is taken to guide PPI extraction by building sentence dependency parse tree. Comprehensive and quantitative evaluations and detailed analyses are used to demonstrate the significant performance of IRO on relation sentences classification and PPI extraction. Our PPI extraction method yielded a recall of around 80% and 90% and an F1 of around 54% and 66% on corpora of AIMed and BioInfer, respectively, which are superior to most existing extraction methods.

  18. Lighting the Way to Protein-Protein Interactions: Recommendations on Best Practices for Bimolecular Fluorescence Complementation Analyses[OPEN

    PubMed Central

    Kudla, Jörg

    2016-01-01

    Techniques to detect and verify interactions between proteins in vivo have become invaluable tools in functional genomic research. While many of the initially developed interaction assays (e.g., yeast two-hybrid system and split-ubiquitin assay) usually are conducted in heterologous systems, assays relying on bimolecular fluorescence complementation (BiFC; also referred to as split-YFP assays) are applicable to the analysis of protein-protein interactions in most native systems, including plant cells. Like all protein-protein interaction assays, BiFC can produce false positive and false negative results. The purpose of this commentary is to (1) highlight shortcomings of and potential pitfalls in BiFC assays, (2) provide guidelines for avoiding artifactual interactions, and (3) suggest suitable approaches to scrutinize potential interactions and validate them by independent methods. PMID:27099259

  19. Prediction of protein-protein interaction sites using an ensemble method

    PubMed Central

    2009-01-01

    Background Prediction of protein-protein interaction sites is one of the most challenging and intriguing problems in the field of computational biology. Although much progress has been achieved by using various machine learning methods and a variety of available features, the problem is still far from being solved. Results In this paper, an ensemble method is proposed, which combines bootstrap resampling technique, SVM-based fusion classifiers and weighted voting strategy, to overcome the imbalanced problem and effectively utilize a wide variety of features. We evaluate the ensemble classifier using a dataset extracted from 99 polypeptide chains with 10-fold cross validation, and get a AUC score of 0.86, with a sensitivity of 0.76 and a specificity of 0.78, which are better than that of the existing methods. To improve the usefulness of the proposed method, two special ensemble classifiers are designed to handle the cases of missing homologues and structural information respectively, and the performance is still encouraging. The robustness of the ensemble method is also evaluated by effectively classifying interaction sites from surface residues as well as from all residues in proteins. Moreover, we demonstrate the applicability of the proposed method to identify interaction sites from the non-structural proteins (NS) of the influenza A virus, which may be utilized as potential drug target sites. Conclusion Our experimental results show that the ensemble classifiers are quite effective in predicting protein interaction sites. The Sub-EnClassifiers with resampling technique can alleviate the imbalanced problem and the combination of Sub-EnClassifiers with a wide variety of feature groups can significantly improve prediction performance. PMID:20015386

  20. Protein-Protein Interactions Suggest Novel Activities of Human Cytomegalovirus Tegument Protein pUL103

    PubMed Central

    Ortiz, Daniel A.; Glassbrook, James E.

    2016-01-01

    cellular protein-protein interactions to identify and understand the range of pUL103 functions. We found that pUL103 interacts with cellular antiviral defense systems and proteins involved in organelle biogenesis and transport of cytoplasmic vesicles and is present in infected cell nuclei. These results expand our understanding of the functional repertoire of pUL103 to include activities that extend from the earliest stages of infection through virion assembly and egress. PMID:27334581

  1. Emory University: High-Throughput Protein-Protein Interaction Analysis for Hippo Pathway Profiling | Office of Cancer Genomics

    Cancer.gov

    The CTD2 Center at Emory University used high-throughput protein-protein interaction (PPI) mapping for Hippo signaling pathway profiling to rapidly unveil promising PPIs as potential therapeutic targets and advance functional understanding of signaling circuitry in cells. Read the abstract.

  2. Modulation of nociceptive ion channels and receptors via protein-protein interactions: implications for pain relief

    PubMed Central

    Rouwette, Tom; Avenali, Luca; Sondermann, Julia; Narayanan, Pratibha; Gomez-Varela, David; Schmidt, Manuela

    2015-01-01

    In the last 2 decades biomedical research has provided great insights into the molecular signatures underlying painful conditions. However, chronic pain still imposes substantial challenges to researchers, clinicians and patients alike. Under pathological conditions, pain therapeutics often lack efficacy and exhibit only minimal safety profiles, which can be largely attributed to the targeting of molecules with key physiological functions throughout the body. In light of these difficulties, the identification of molecules and associated protein complexes specifically involved in chronic pain states is of paramount importance for designing selective interventions. Ion channels and receptors represent primary targets, as they critically shape nociceptive signaling from the periphery to the brain. Moreover, their function requires tight control, which is usually implemented by protein-protein interactions (PPIs). Indeed, manipulation of such PPIs entails the modulation of ion channel activity with widespread implications for influencing nociceptive signaling in a more specific way. In this review, we highlight recent advances in modulating ion channels and receptors via their PPI networks in the pursuit of relieving chronic pain. Moreover, we critically discuss the potential of targeting PPIs for developing novel pain therapies exhibiting higher efficacy and improved safety profiles. PMID:26039491

  3. The EED protein-protein interaction inhibitor A-395 inactivates the PRC2 complex.

    PubMed

    He, Yupeng; Selvaraju, Sujatha; Curtin, Michael L; Jakob, Clarissa G; Zhu, Haizhong; Comess, Kenneth M; Shaw, Bailin; The, Juliana; Lima-Fernandes, Evelyne; Szewczyk, Magdalena M; Cheng, Dong; Klinge, Kelly L; Li, Huan-Qiu; Pliushchev, Marina; Algire, Mikkel A; Maag, David; Guo, Jun; Dietrich, Justin; Panchal, Sanjay C; Petros, Andrew M; Sweis, Ramzi F; Torrent, Maricel; Bigelow, Lance J; Senisterra, Guillermo; Li, Fengling; Kennedy, Steven; Wu, Qin; Osterling, Donald J; Lindley, David J; Gao, Wenqing; Galasinski, Scott; Barsyte-Lovejoy, Dalia; Vedadi, Masoud; Buchanan, Fritz G; Arrowsmith, Cheryl H; Chiang, Gary G; Sun, Chaohong; Pappano, William N

    2017-04-01

    Polycomb repressive complex 2 (PRC2) is a regulator of epigenetic states required for development and homeostasis. PRC2 trimethylates histone H3 at lysine 27 (H3K27me3), which leads to gene silencing, and is dysregulated in many cancers. The embryonic ectoderm development (EED) protein is an essential subunit of PRC2 that has both a scaffolding function and an H3K27me3-binding function. Here we report the identification of A-395, a potent antagonist of the H3K27me3 binding functions of EED. Structural studies demonstrate that A-395 binds to EED in the H3K27me3-binding pocket, thereby preventing allosteric activation of the catalytic activity of PRC2. Phenotypic effects observed in vitro and in vivo are similar to those of known PRC2 enzymatic inhibitors; however, A-395 retains potent activity against cell lines resistant to the catalytic inhibitors. A-395 represents a first-in-class antagonist of PRC2 protein-protein interactions (PPI) for use as a chemical probe to investigate the roles of EED-containing protein complexes.

  4. Classification of protein-protein interaction full-text documents using text and citation network features.

    PubMed

    Kolchinsky, Artemy; Abi-Haidar, Alaa; Kaur, Jasleen; Hamed, Ahmed Abdeen; Rocha, Luis M

    2010-01-01

    We participated (as Team 9) in the Article Classification Task of the Biocreative II.5 Challenge: binary classification of full-text documents relevant for protein-protein interaction. We used two distinct classifiers for the online and offline challenges: 1) the lightweight Variable Trigonometric Threshold (VTT) linear classifier we successfully introduced in BioCreative 2 for binary classification of abstracts and 2) a novel Naive Bayes classifier using features from the citation network of the relevant literature. We supplemented the supplied training data with full-text documents from the MIPS database. The lightweight VTT classifier was very competitive in this new full-text scenario: it was a top-performing submission in this task, taking into account the rank product of the Area Under the interpolated precision and recall Curve, Accuracy, Balanced F-Score, and Matthew's Correlation Coefficient performance measures. The novel citation network classifier for the biomedical text mining domain, while not a top performing classifier in the challenge, performed above the central tendency of all submissions, and therefore indicates a promising new avenue to investigate further in bibliome informatics.

  5. Dissecting the Human Protein-Protein Interaction Network via Phylogenetic Decomposition

    PubMed Central

    Chen, Cho-Yi; Ho, Andy; Huang, Hsin-Yuan; Juan, Hsueh-Fen; Huang, Hsuan-Cheng

    2014-01-01

    The protein-protein interaction (PPI) network offers a conceptual framework for better understanding the functional organization of the proteome. However, the intricacy of network complexity complicates comprehensive analysis. Here, we adopted a phylogenic grouping method combined with force-directed graph simulation to decompose the human PPI network in a multi-dimensional manner. This network model enabled us to associate the network topological properties with evolutionary and biological implications. First, we found that ancient proteins occupy the core of the network, whereas young proteins tend to reside on the periphery. Second, the presence of age homophily suggests a possible selection pressure may have acted on the duplication and divergence process during the PPI network evolution. Lastly, functional analysis revealed that each age group possesses high specificity of enriched biological processes and pathway engagements, which could correspond to their evolutionary roles in eukaryotic cells. More interestingly, the network landscape closely coincides with the subcellular localization of proteins. Together, these findings suggest the potential of using conceptual frameworks to mimic the true functional organization in a living cell. PMID:25412639

  6. Imbalance in chemical space: How to facilitate the identification of protein-protein interaction inhibitors

    NASA Astrophysics Data System (ADS)

    Kuenemann, Mélaine A.; Labbé, Céline M.; Cerdan, Adrien H.; Sperandio, Olivier

    2016-04-01

    Protein-protein interactions (PPIs) play vital roles in life and provide new opportunities for therapeutic interventions. In this large data analysis, 3,300 inhibitors of PPIs (iPPIs) were compared to 17 reference datasets of collectively ~566,000 compounds (including natural compounds, existing drugs, active compounds on conventional targets, etc.) using a chemoinformatics approach. Using this procedure, we showed that comparable classes of PPI targets can be formed using either the similarity of their ligands or the shared properties of their binding cavities, constituting a proof-of-concept that not only can binding pockets be used to group PPI targets, but that these pockets certainly condition the properties of their corresponding ligands. These results demonstrate that matching regions in both chemical space and target space can be found. Such identified classes of targets could lead to the design of PPI-class-specific chemical libraries and therefore facilitate the development of iPPIs to the stage of drug candidates.

  7. Therapeutic design of peptide modulators of protein-protein interactions in membranes.

    PubMed

    Stone, Tracy A; Deber, Charles M

    2017-04-01

    Membrane proteins play the central roles in a variety of cellular processes, ranging from nutrient uptake and signalling, to cell-cell communication. Their biological functions are directly related to how they fold and assemble; defects often lead to disease. Protein-protein interactions (PPIs) within the membrane are therefore of great interest as therapeutic targets. Here we review the progress in the application of membrane-insertable peptides for the disruption or stabilization of membrane-based PPIs. We describe the design and preparation of transmembrane peptide mimics; and of several categories of peptidomimetics used for study, including d-enantiomers, non-natural amino acids, peptoids, and β-peptides. Further aspects of the review describe modifications to membrane-insertable peptides, including lipidation and cyclization via hydrocarbon stapling. These approaches provide a pathway toward the development of metabolically stable, non-toxic, and efficacious peptide modulators of membrane-based PPIs. This article is part of a Special Issue entitled: Lipid order/lipid defects and lipid-control of protein activity edited by Dirk Schneider.

  8. Genome-wide protein-protein interactions and protein function exploration in cyanobacteria.

    PubMed

    Lv, Qi; Ma, Weimin; Liu, Hui; Li, Jiang; Wang, Huan; Lu, Fang; Zhao, Chen; Shi, Tieliu

    2015-10-22

    Genome-wide network analysis is well implemented to study proteins of unknown function. Here, we effectively explored protein functions and the biological mechanism based on inferred high confident protein-protein interaction (PPI) network in cyanobacteria. We integrated data from seven different sources and predicted 1,997 PPIs, which were evaluated by experiments in molecular mechanism, text mining of literatures in proved direct/indirect evidences, and "interologs" in conservation. Combined the predicted PPIs with known PPIs, we obtained 4,715 no-redundant PPIs (involving 3,231 proteins covering over 90% of genome) to generate the PPI network. Based on the PPI network, terms in Gene ontology (GO) were assigned to function-unknown proteins. Functional modules were identified by dissecting the PPI network into sub-networks and analyzing pathway enrichment, with which we investigated novel function of underlying proteins in protein complexes and pathways. Examples of photosynthesis and DNA repair indicate that the network approach is a powerful tool in protein function analysis. Overall, this systems biology approach provides a new insight into posterior functional analysis of PPIs in cyanobacteria.

  9. Identifying protein complexes in protein-protein interaction networks by using clique seeds and graph entropy.

    PubMed

    Chen, Bolin; Shi, Jinhong; Zhang, Shenggui; Wu, Fang-Xiang

    2013-01-01

    The identification of protein complexes plays a key role in understanding major cellular processes and biological functions. Various computational algorithms have been proposed to identify protein complexes from protein-protein interaction (PPI) networks. In this paper, we first introduce a new seed-selection strategy for seed-growth style algorithms. Cliques rather than individual vertices are employed as initial seeds. After that, a result-modification approach is proposed based on this seed-selection strategy. Predictions generated by higher order clique seeds are employed to modify results that are generated by lower order ones. The performance of this seed-selection strategy and the result-modification approach are tested by using the entropy-based algorithm, which is currently the best seed-growth style algorithm to detect protein complexes from PPI networks. In addition, we investigate four pairs of strategies for this algorithm in order to improve its accuracy. The numerical experiments are conducted on a Saccharomyces cerevisiae PPI network. The group of best predictions consists of 1711 clusters, with the average f-score at 0.68 after removing all similar and redundant clusters. We conclude that higher order clique seeds can generate predictions with higher accuracy and that our improved entropy-based algorithm outputs more reasonable predictions than the original one.

  10. t-LSE: a novel robust geometric approach for modeling protein-protein interaction networks.

    PubMed

    Zhu, Lin; You, Zhu-Hong; Huang, De-Shuang; Wang, Bing

    2013-01-01

    Protein-protein interaction (PPI) networks provide insights into understanding of biological processes, function and the underlying complex evolutionary mechanisms of the cell. Modeling PPI network is an important and fundamental problem in system biology, where it is still of major concern to find a better fitting model that requires less structural assumptions and is more robust against the large fraction of noisy PPIs. In this paper, we propose a new approach called t-logistic semantic embedding (t-LSE) to model PPI networks. t-LSE tries to adaptively learn a metric embedding under the simple geometric assumption of PPI networks, and a non-convex cost function was adopted to deal with the noise in PPI networks. The experimental results show the superiority of the fit of t-LSE over other network models to PPI data. Furthermore, the robust loss function adopted here leads to big improvements for dealing with the noise in PPI network. The proposed model could thus facilitate further graph-based studies of PPIs and may help infer the hidden underlying biological knowledge. The Matlab code implementing the proposed method is freely available from the web site: http://home.ustc.edu.cn/~yzh33108/PPIModel.htm.

  11. Self protein-protein interactions are involved in TPPP/p25 mediated microtubule bundling

    PubMed Central

    DeBonis, Salvatore; Neumann, Emmanuelle; Skoufias, Dimitrios A.

    2015-01-01

    TPPP/p25 is a microtubule-associated protein, detected in protein inclusions associated with various neurodegenerative diseases. Deletion analysis data show that TPPP/p25 has two microtubule binding sites, both located in intrinsically disordered domains, one at the N-terminal and the other in the C-terminal domain. In copolymerization assays the full-length protein exhibits microtubule stimulation and bundling activity. In contrast, at the same ratio relative to tubulin, truncated forms of TPPP/p25 exhibit either lower or no microtubule stimulation and no bundling activity, suggesting a cooperative phenomenon which is enhanced by the presence of the two binding sites. The binding characteristics of the N- and C-terminally truncated proteins to taxol-stabilized microtubules are similar to the full-length protein. However, the C-terminally truncated TPPP/p25 shows a lower Bmax for microtubule binding, suggesting that it may bind to a site of tubulin that is masked in microtubules. Bimolecular fluorescent complementation assays in cells expressing combinations of various TPPP/p25 fragments, but not that of the central folded domain, resulted in the generation of a fluorescence signal colocalized with perinuclear microtubule bundles insensitive to microtubule inhibitors. The data suggest that the central folded domain of TPPP/p25 following binding to microtubules can drive s homotypic protein-protein interactions leading to bundled microtubules. PMID:26289831

  12. Interrogating noise in protein sequences from the perspective of protein-protein interactions prediction.

    PubMed

    Wang, Yongcui; Ren, Xianwen; Zhang, Chunhua; Deng, Naiyang; Zhang, Xiangsun

    2012-12-21

    The past decades witnessed extensive efforts to study the relationship among proteins. Particularly, sequence-based protein-protein interactions (PPIs) prediction is fundamentally important in speeding up the process of mapping interactomes of organisms. High-throughput experimental methodologies make many model organism's PPIs known, which allows us to apply machine learning methods to learn understandable rules from the available PPIs. Under the machine learning framework, the composition vectors are usually applied to encode proteins as real-value vectors. However, the composition vector value might be highly correlated to the distribution of amino acids, i.e., amino acids which are frequently observed in nature tend to have a large value of composition vectors. Thus formulation to estimate the noise induced by the background distribution of amino acids may be needed during representations. Here, we introduce two kinds of denoising composition vectors, which were successfully used in construction of phylogenetic trees, to eliminate the noise. When validating these two denoising composition vectors on Escherichia coli (E. coli), Saccharomyces cerevisiae (S. cerevisiae) and human PPIs datasets, surprisingly, the predictive performance is not improved, and even worse than non-denoised prediction. These results suggest that the noise in phylogenetic tree construction may be valuable information in PPIs prediction.

  13. Clustered microRNAs' coordination in regulating protein-protein interaction network

    PubMed Central

    Yuan, Xiongying; Liu, Changning; Yang, Pengcheng; He, Shunmin; Liao, Qi; Kang, Shuli; Zhao, Yi

    2009-01-01

    Background MicroRNAs (miRNAs), a growing class of small RNAs with crucial regulatory roles at the post-transcriptional level, are usually found to be clustered on chromosomes. However, with the exception of a few individual cases, so far little is known about the functional consequence of this conserved clustering of miRNA loci. In animal genomes such clusters often contain non-homologous miRNA genes. One hypothesis to explain this heterogeneity suggests that clustered miRNAs are functionally related by virtue of co-targeting downstream pathways. Results Integrating of miRNA cluster information with protein protein interaction (PPI) network data, our research supports the hypothesis of the functional coordination of clustered miRNAs and links it to the topological features of miRNAs' targets in PPI network. Specifically, our results demonstrate that clustered miRNAs jointly regulate proteins in close proximity of the PPI network. The possibility that two proteins yield to this coordinated regulation is negatively correlated with their distance in PPI network. Guided by the knowledge of this preference, we found several network communities enriched with target genes of miRNA clusters. In addition, our results demonstrate that the variance of this propensity can also partly be explained by protein's connectivity and miRNA's conservation. Conclusion In summary, this work supports the hypothesis of intra-cluster coordination and investigates the extent of this coordination. PMID:19558649

  14. Small-Molecule Stabilization of 14-3-3 Protein-Protein Interactions Stimulates Axon Regeneration.

    PubMed

    Kaplan, Andrew; Morquette, Barbara; Kroner, Antje; Leong, SooYuen; Madwar, Carolin; Sanz, Ricardo; Banerjee, Sara L; Antel, Jack; Bisson, Nicolas; David, Samuel; Fournier, Alyson E

    2017-03-08

    Damaged central nervous system (CNS) neurons have a poor ability to spontaneously regenerate, causing persistent functional deficits after injury. Therapies that stimulate axon growth are needed to repair CNS damage. 14-3-3 adaptors are hub proteins that are attractive targets to manipulate cell signaling. We identify a positive role for 14-3-3s in axon growth and uncover a developmental regulation of the phosphorylation and function of 14-3-3s. We show that fusicoccin-A (FC-A), a small-molecule stabilizer of 14-3-3 protein-protein interactions, stimulates axon growth in vitro and regeneration in vivo. We show that FC-A stabilizes a complex between 14-3-3 and the stress response regulator GCN1, inducing GCN1 turnover and neurite outgrowth. These findings show that 14-3-3 adaptor protein complexes are druggable targets and identify a new class of small molecules that may be further optimized for the repair of CNS damage.

  15. Disease Gene Prioritization Based on Topological Similarity in Protein-Protein Interaction Networks

    NASA Astrophysics Data System (ADS)

    Erten, Sinan; Bebek, Gurkan; Koyutürk, Mehmet

    In recent years, many algorithms have been developed to narrow down the set of candidate disease genes implicated by genome wide association studies (GWAS), using knowledge on protein-protein interactions (PPIs). All of these algorithms are based on a common principle; functional association between proteins is correlated with their connectivity/proximity in the PPI network. However, recent research also reveals that networks are organized into recurrent network schemes that underlie the mechanisms of cooperation among proteins with different function, as well as the crosstalk between different cellular processes. In this paper, we hypothesize that proteins that are associated with similar diseases may exhibit patterns of "topological similarity" in PPI networks. Motivated by these observations, we introduce the notion of "topological profile", which represents the location of a protein in the network with respect to other proteins. Based on this notion, we develop a novel measure to assess the topological similarity of proteins in a PPI network. We then use this measure to develop algorithms that prioritize candidate disease genes based on the topological similarity of their products and the products of known disease genes. Systematic experimental studies using an integrated human PPI network and the Online Mendelian Inheritance (OMIM) database show that the proposed algorithm, Vavien, clearly outperforms state-of-the-art network based prioritization algorithms. Vavien is available as a web service at http://www.diseasegenes.org .

  16. Expanding the Number of “Druggable” Targets: Non-Enzymes and Protein-Protein Interactions

    PubMed Central

    Makley, Leah N.; Gestwicki, Jason E.

    2012-01-01

    Following sequencing and assembly of the human genome, the preferred methods for identification of new drug targets have changed dramatically. Modern tactics such as genome-wide association studies (GWAS) and deep sequencing are fundamentally different from the pharmacology-guided approaches used previously, in which knowledge of small molecule ligands acting at their cellular targets was the primary discovery engine. A consequence of the “target-first, pharmacology-second” strategy is that many predicted drug targets are non-enzymes, such as scaffolding, regulatory or structural proteins, and their activities are often dependent on protein-protein interactions (PPIs). These types of targets create unique challenges to drug discovery efforts because enzymatic turnover cannot be used as a convenient surrogate for compound potency. Moreover, it is often challenging to predict how ligand binding to non-enzymes might affect changes in protein function and/or pathobiology. Thus, in the post-genomic era, targets might be strongly implicated by molecular biology-based methods, yet they often later earn the designation of “undruggable.” Can the scope of available targets be widened to include these promising, but challenging, non-enzymes? In this review, we discuss advances in high throughput screening technology and chemical library design that are emerging to deal with these challenges. PMID:23253128

  17. Lipid demixing and protein-protein interactions in the adsorption of charged proteins on mixed membranes.

    PubMed Central

    May, S; Harries, D; Ben-Shaul, A

    2000-01-01

    The adsorption free energy of charged proteins on mixed membranes, containing varying amounts of (oppositely) charged lipids, is calculated based on a mean-field free energy expression that accounts explicitly for the ability of the lipids to demix locally, and for lateral interactions between the adsorbed proteins. Minimization of this free energy functional yields the familiar nonlinear Poisson-Boltzmann equation and the boundary condition at the membrane surface that allows for lipid charge rearrangement. These two self-consistent equations are solved simultaneously. The proteins are modeled as uniformly charged spheres and the (bare) membrane as an ideal two-dimensional binary mixture of charged and neutral lipids. Substantial variations in the lipid charge density profiles are found when highly charged proteins adsorb on weakly charged membranes; the lipids, at a certain demixing entropy penalty, adjust their concentration in the vicinity of the adsorbed protein to achieve optimal charge matching. Lateral repulsive interactions between the adsorbed proteins affect the lipid modulation profile and, at high densities, result in substantial lowering of the binding energy. Adsorption isotherms demonstrating the importance of lipid mobility and protein-protein interactions are calculated using an adsorption equation with a coverage-dependent binding constant. Typically, at bulk-surface equilibrium (i.e., when the membrane surface is "saturated" by adsorbed proteins), the membrane charges are "overcompensated" by the protein charges, because only about half of the protein charges (those on the hemispheres facing the membrane) are involved in charge neutralization. Finally, it is argued that the formation of lipid-protein domains may be enhanced by electrostatic adsorption of proteins, but its origin (e.g., elastic deformations associated with lipid demixing) is not purely electrostatic. PMID:11023883

  18. Comparative interactomics for virus-human protein-protein interactions: DNA viruses versus RNA viruses.

    PubMed

    Durmuş, Saliha; Ülgen, Kutlu Ö

    2017-01-01

    Viruses are obligatory intracellular pathogens and completely depend on their hosts for survival and reproduction. The strategies adopted by viruses to exploit host cell processes and to evade host immune systems during infections may differ largely with the type of the viral genetic material. An improved understanding of these viral infection mechanisms is only possible through a better understanding of the pathogen-host interactions (PHIs) that enable viruses to enter into the host cells and manipulate the cellular mechanisms to their own advantage. Experimentally-verified protein-protein interaction (PPI) data of pathogen-host systems only became available at large scale within the last decade. In this study, we comparatively analyzed the current PHI networks belonging to DNA and RNA viruses and their human host, to get insights into the infection strategies used by these viral groups. We investigated the functional properties of human proteins in the PHI networks, to observe and compare the attack strategies of DNA and RNA viruses. We observed that DNA viruses are able to attack both human cellular and metabolic processes simultaneously during infections. On the other hand, RNA viruses preferentially interact with human proteins functioning in specific cellular processes as well as in intracellular transport and localization within the cell. Observing virus-targeted human proteins, we propose heterogeneous nuclear ribonucleoproteins and transporter proteins as potential antiviral therapeutic targets. The observed common and specific infection mechanisms in terms of viral strategies to attack human proteins may provide crucial information for further design of broad and specific next-generation antiviral therapeutics.

  19. Revealing the potential pathogenesis of glioma by utilizing a glioma associated protein-protein interaction network.

    PubMed

    Pan, Weiran; Li, Gang; Yang, Xiaoxiao; Miao, Jinming

    2015-04-01

    This study aims to explore the potential mechanism of glioma through bioinformatic approaches. The gene expression profile (GSE4290) of glioma tumor and non-tumor samples was downloaded from Gene Expression Omnibus database. A total of 180 samples were available, including 23 non-tumor and 157 tumor samples. Then the raw data were preprocessed using robust multiarray analysis, and 8,890 differentially expressed genes (DEGs) were identified by using t-test (false discovery rate < 0.0005). Furthermore, 16 known glioma related genes were abstracted from Genetic Association Database. After mapping 8,890 DEGs and 16 known glioma related genes to Human Protein Reference Database, a glioma associated protein-protein interaction network (GAPN) was constructed. In addition, 51 sub-networks in GAPN were screened out through Molecular Complex Detection (score ≥ 1), and sub-network 1 was found to have the closest interaction (score = 3). What' more, for the top 10 sub-networks, Gene Ontology (GO) enrichment analysis (p value < 0.05) was performed, and DEGs involved in sub-network 1 and 2, such as BRMS1L and CCNA1, were predicted to regulate cell growth, cell cycle, and DNA replication via interacting with known glioma related genes. Finally, the overlaps of DEGs and human essential, housekeeping, tissue-specific genes were calculated (p value = 1.0, 1.0, and 0.00014, respectively) and visualized by Venn Diagram package in R. About 61% of human tissue-specific genes were DEGs as well. This research shed new light on the pathogenesis of glioma based on DEGs and GAPN, and our findings might provide potential targets for clinical glioma treatment.

  20. Predicting gene ontology annotations of orphan GWAS genes using protein-protein interactions

    PubMed Central

    2014-01-01

    Background The number of genome-wide association studies (GWAS) has increased rapidly in the past couple of years, resulting in the identification of genes associated with different diseases. The next step in translating these findings into biomedically useful information is to find out the mechanism of the action of these genes. However, GWAS studies often implicate genes whose functions are currently unknown; for example, MYEOV, ANKLE1, TMEM45B and ORAOV1 are found to be associated with breast cancer, but their molecular function is unknown. Results We carried out Bayesian inference of Gene Ontology (GO) term annotations of genes by employing the directed acyclic graph structure of GO and the network of protein-protein interactions (PPIs). The approach is designed based on the fact that two proteins that interact biophysically would be in physical proximity of each other, would possess complementary molecular function, and play role in related biological processes. Predicted GO terms were ranked according to their relative association scores and the approach was evaluated quantitatively by plotting the precision versus recall values and F-scores (the harmonic mean of precision and recall) versus varying thresholds. Precisions of ~58% and ~ 40% for localization and functions respectively of proteins were determined at a threshold of ~30 (top 30 GO terms in the ranked list). Comparison with function prediction based on semantic similarity among nodes in an ontology and incorporation of those similarities in a k-nearest neighbor classifier confirmed that our results compared favorably. Conclusions This approach was applied to predict the cellular component and molecular function GO terms of all human proteins that have interacting partners possessing at least one known GO annotation. The list of predictions is available at http://severus.dbmi.pitt.edu/engo/GOPRED.html. We present the algorithm, evaluations and the results of the computational predictions

  1. Protease-inhibitor interaction predictions: Lessons on the complexity of protein-protein interactions.

    PubMed

    Fortelny, Nikolaus; Butler, Georgina S; Overall, Christopher Mark; Pavlidis, Paul

    2017-04-06

    Protein interactions shape proteome function and thus biology. Identification of protein interactions is a major goal in molecular biology, but biochemical methods, although improving, remain limited in coverage and accuracy. Whereas computational predictions can guide biochemical experiments, low validation rates of predictions remain a major limitation. Here, we investigated computational methods in the prediction of a specific type of interaction, the inhibitory interactions between proteases and their inhibitors. Proteases generate thousands of proteoforms that dynamically shape the functional state of proteomes. Despite the important regulatory role of proteases, knowledge of their inhibitors remains largely incomplete with the vast majority of proteases lacking an annotated inhibitor. To link inhibitors to their target proteases on a large scale, we applied computational methods to predict inhibitory interactions between proteases and their inhibitors based on complementary data including coexpression, phylogenetic similarity, structural information, co-annotation, and colocalization, and also surveyed general protein interaction networks for potential inhibitory interactions. In testing nine predicted interactions biochemically, we validated the inhibition of kallikrein 5 by serpin B12. Despite the use of a wide array of complementary data, we found a high false positive rate of computational predictions in biochemical follow-up. Based on a protease-specific definition of true negatives derived from the biochemical classification of proteases and inhibitors, we analyzed prediction accuracy of individual features. Thereby we identified feature-specific limitations, which also affected general protein interaction prediction methods. Interestingly, proteases were often not coexpressed with most of their functional inhibitors, contrary to what is commonly assumed and extrapolated predominantly from cell culture experiments. Predictions of inhibitory interactions

  2. Predicting protein-protein interactions between human and hepatitis C virus via an ensemble learning method.

    PubMed

    Emamjomeh, Abbasali; Goliaei, Bahram; Zahiri, Javad; Ebrahimpour, Reza

    2014-12-01

    An estimated 170 million people, approximately 3% of the world population, are chronically infected with the hepatitis C virus (HCV). More than 350,000 deaths are reported annually, which are caused by HCV. HCV, similar to a variety of viruses, causes disease in humans by altering protein-protein interactions within the host cells. Experimental approaches for the detection of host-virus PPIs have many inherent limitations. Computational approaches to predict these interactions are therefore of significant importance. While many studies have been developed to predict intra-species PPIs in the last decade, predictions on inter-species PPIs such as human-HCV PPIs are rare. In this study, we developed an ensemble learning method to predict PPIs between human and HCV proteins. Our model utilises four well-established diverse learners as base classifiers including random forest (RF), Naïve Bayes (NB), support vector machine (SVM) and multilayer perceptron (MLP). In addition, an MLP was used as a meta-learner to combine base learners' predictions to provide the final prediction. To encode human and HCV proteins as feature vectors, we used six different descriptors as follows: amino acid composition (ACC), pseudo amino acid composition (PAC), evolutionary information feature, network centrality measures, tissue information and post-translational modification information. To assess the prediction power of the proposed method, we assembled a benchmark dataset composed of confident positive and negative PPIs. In a 10-fold cross-validation experiment, our prediction method achieved accuracy and specificity as high as 83% and 94%, respectively. Furthermore, in an independent test set the proposed method achieved an accuracy of 84% and a specificity of 92%. When compared with the existing method, our method showed a better performance. These results revealed that our method is suitable for performing PPI prediction in a host-pathogen context.

  3. Multiplex detection of protein-protein interactions using a next generation luciferase reporter.

    PubMed

    Verhoef, Lisette G G C; Mattioli, Michela; Ricci, Fernanda; Li, Yao-Cheng; Wade, Mark

    2016-02-01

    Cell-based assays of protein-protein interactions (PPIs) using split reporter proteins can be used to identify PPI agonists and antagonists. Generally, such assays measure one PPI at a time, and thus counterscreens for on-target activity must be run in parallel or at a subsequent stage; this increases both the cost and time during screening. Split luciferase systems offer advantages over those that use split fluorescent proteins (FPs). This is since split luciferase offers a greater signal:noise ratio and, unlike split FPs, the PPI can be reversed upon small molecule treatment. While multiplexed PPI assays using luciferase have been reported, they suffer from low signal:noise and require fairly complex spectral deconvolution during analysis. Furthermore, the luciferase enzymes used are large, which limits the range of PPIs that can be interrogated due to steric hindrance from the split luciferase fragments. Here, we report a multiplexed PPI assay based on split luciferases from Photinus pyralis (firefly luciferase, FLUC) and the deep-sea shrimp, Oplophorus gracilirostris (NanoLuc, NLUC). Specifically, we show that the binding of the p53 tumor suppressor to its two major negative regulators, MDM2 and MDM4, can be simultaneously measured within the same sample, without the requirement for complex filters or deconvolution. We provide chemical and genetic validation of this system using MDM2-targeted small molecules and mutagenesis, respectively. Combined with the superior signal:noise and smaller size of split NanoLuc, this multiplexed PPI assay format can be exploited to study the induction or disruption of pairwise interactions that are prominent in many cell signaling pathways.

  4. Cholesterol transport in steroid biosynthesis: Role of protein-protein interactions and implications in disease states

    PubMed Central

    Rone, Malena B.; Fan, Jinjiang; Papadopoulos, Vassilios

    2009-01-01

    The transfer of cholesterol from the outer to the inner mitochondrial membrane is the rate-limiting step in hormone-induced steroid formation. To ensure that this step is achieved efficiently, free cholesterol must accumulate in excess at the outer mitochondrial membrane and then be transferred to the inner membrane. This is accomplished through a series of steps that involve various intracellular organelles, including lysosomes and lipid droplets, and proteins such as the translocator protein (18 kDa, TSPO) and steroidogenic acute regulatory (StAR) proteins. TSPO, previously known as the peripheral-type benzodiazepine receptor, is a high-affinity drug- and cholesterol-binding mitochondrial protein. StAR is a hormone-induced mitochondria-targeted protein that has been shown to initiate cholesterol transfer into mitochondria. Through the assistance of proteins such as the cAMP-dependent protein kinase regulatory subunit Iα (PKA-RIα) and the PKA-Rlα TSPO-associated acyl-coenzyme A binding domain containing 3 (ACBD3) protein, PAP7, cholesterol is transferred to and docked at the outer mitochondrial membrane. The TSPO-dependent import of StAR into mitochondria, and the association of TSPO with the outer/inner mitochondrial membrane contact sites, drives the intramitochondrial cholesterol transfer and subsequent steroid formation. The focus of this review is on (i) the intracellular pathways and protein-protein interactions involved in cholesterol transport and steroid biosynthesis and (ii) the roles and interactions of these proteins in endocrine pathologies and neurological diseases where steroid synthesis plays a critical role. PMID:19286473

  5. Towards a rigorous network of protein-protein interactions of the model sulfate reducer Desulfovibrio vulgaris Hildenborough.

    PubMed

    Chhabra, Swapnil R; Joachimiak, Marcin P; Petzold, Christopher J; Zane, Grant M; Price, Morgan N; Reveco, Sonia A; Fok, Veronica; Johanson, Alyssa R; Batth, Tanveer S; Singer, Mary; Chandonia, John-Marc; Joyner, Dominique; Hazen, Terry C; Arkin, Adam P; Wall, Judy D; Singh, Anup K; Keasling, Jay D

    2011-01-01

    Protein-protein interactions offer an insight into cellular processes beyond what may be obtained by the quantitative functional genomics tools of proteomics and transcriptomics. The aforementioned tools have been extensively applied to study Escherichia coli and other aerobes and more recently to study the stress response behavior of Desulfovibrio vulgaris Hildenborough, a model obligate anaerobe and sulfate reducer and the subject of this study. Here we carried out affinity purification followed by mass spectrometry to reconstruct an interaction network among 12 chromosomally encoded bait and 90 prey proteins based on 134 bait-prey interactions identified to be of high confidence. Protein-protein interaction data are often plagued by the lack of adequate controls and replication analyses necessary to assess confidence in the results, including identification of potential false positives. We addressed these issues through the use of biological replication, exponentially modified protein abundance indices, results from an experimental negative control, and a statistical test to assign confidence to each putative interacting pair applicable to small interaction data studies. We discuss the biological significance of metabolic features of D. vulgaris revealed by these protein-protein interaction data and the observed protein modifications. These include the distinct role of the putative carbon monoxide-induced hydrogenase, unique electron transfer routes associated with different oxidoreductases, and the possible role of methylation in regulating sulfate reduction.

  6. PIPINO: A Software Package to Facilitate the Identification of Protein-Protein Interactions from Affinity Purification Mass Spectrometry Data

    PubMed Central

    Schildbach, Stefan; Blumert, Conny; Horn, Friedemann; von Bergen, Martin; Labudde, Dirk

    2016-01-01

    The functionality of most proteins is regulated by protein-protein interactions. Hence, the comprehensive characterization of the interactome is the next milestone on the path to understand the biochemistry of the cell. A powerful method to detect protein-protein interactions is a combination of coimmunoprecipitation or affinity purification with quantitative mass spectrometry. Nevertheless, both methods tend to precipitate a high number of background proteins due to nonspecific interactions. To address this challenge the software Protein-Protein-Interaction-Optimizer (PIPINO) was developed to perform an automated data analysis, to facilitate the selection of bona fide binding partners, and to compare the dynamic of interaction networks. In this study we investigated the STAT1 interaction network and its activation dependent dynamics. Stable isotope labeling by amino acids in cell culture (SILAC) was applied to analyze the STAT1 interactome after streptavidin pull-down of biotagged STAT1 from human embryonic kidney 293T cells with and without activation. Starting from more than 2,000 captured proteins 30 potential STAT1 interaction partners were extracted. Interestingly, more than 50% of these were already reported or predicted to bind STAT1. Furthermore, 16 proteins were found to affect the binding behavior depending on STAT1 phosphorylation such as STAT3 or the importin subunits alpha 1 and alpha 6. PMID:26966684

  7. Prediction of Protein-Protein Interactions by NanoLuc-Based Protein-Fragment Complementation Assay | Office of Cancer Genomics

    Cancer.gov

    The CTD2 Center at Emory has developed a new NanoLuc®-based protein-fragment complementation assay (NanoPCA) which allows the detection of novel protein-protein interactions (PPI). NanoPCA allows the study of PPI dynamics with reversible interactions.  Read the abstract. Experimental Approaches Read the detailed Experimetnal Approaches. 

  8. Identification of polycystic ovary syndrome potential drug targets based on pathobiological similarity in the protein-protein interaction network

    PubMed Central

    Li, Wan; Wei, Wenqing; Li, Yiran; Xie, Ruiqiang; Guo, Shanshan; Wang, Yahui; Jiang, Jing; Chen, Binbin; Lv, Junjie; Zhang, Nana; Chen, Lina; He, Weiming

    2016-01-01

    Polycystic ovary syndrome (PCOS) is one of the most common endocrinological disorders in reproductive aged women. PCOS and Type 2 Diabetes (T2D) are closely linked in multiple levels and possess high pathobiological similarity. Here, we put forward a new computational approach based on the pathobiological similarity to identify PCOS potential drug target modules (PPDT-Modules) and PCOS potential drug targets in the protein-protein interaction network (PPIN). From the systems level and biological background, 1 PPDT-Module and 22 PCOS potential drug targets were identified, 21 of which were verified by literatures to be associated with the pathogenesis of PCOS. 42 drugs targeting to 13 PCOS potential drug targets were investigated experimentally or clinically for PCOS. Evaluated by independent datasets, the whole PPDT-Module and 22 PCOS potential drug targets could not only reveal the drug response, but also distinguish the statuses between normal and disease. Our identified PPDT-Module and PCOS potential drug targets would shed light on the treatment of PCOS. And our approach would provide valuable insights to research on the pathogenesis and drug response of other diseases. PMID:27191267

  9. Abundance and Temperature Dependency of Protein-Protein Interaction Revealed by Interface Structure Analysis and Stability Evolution.

    PubMed

    He, Yi-Ming; Ma, Bin-Guang

    2016-05-25

    Protein complexes are major forms of protein-protein interactions and implement essential biological functions. The subunit interface in a protein complex is related to its thermostability. Though the roles of interface properties in thermal adaptation have been investigated for protein complexes, the relationship between the interface size and the expression level of the subunits remains unknown. In the present work, we studied this relationship and found a positive correlation in thermophiles rather than mesophiles. Moreover, we found that the protein interaction strength in complexes is not only temperature-dependent but also abundance-dependent. The underlying mechanism for the observed correlation was explored by simulating the evolution of protein interface stability, which highlights the avoidance of misinteraction. Our findings make more complete the picture of the mechanisms for protein complex thermal adaptation and provide new insights into the principles of protein-protein interactions.

  10. A Near-Infrared BiFC Reporter for In Vivo Imaging of Protein-Protein Interactions

    PubMed Central

    Filonov, Grigory S.; Verkhusha, Vladislav V.

    2013-01-01

    SUMMARY Studies of protein-protein interactions deep in organs and in whole mammals have been hindered by a lack of genetically encoded fluorescent probes in near-infrared region for which mammalian tissues are the most transparent. We have used a near-infrared fluorescent protein iRFP engineered from a bacterial phytochrome as the template to develop an in vivo split fluorescence complementation probe. The domain architecture-based rational design resulted in an iSplit reporter with the spectra optimal for whole-body imaging, high photostability, and high complementation contrast, which compares favorably to that of other available split fluorescent protein-based probes. Successful visualization of interaction of two known protein partners in a living mouse model suggests iSplit as the probe of choice for noninvasive detection of protein-protein interactions in vivo, whereas its fast intracellular degradation enables time-resolved monitoring of repetitive binding events. PMID:23891149

  11. Abundance and Temperature Dependency of Protein-Protein Interaction Revealed by Interface Structure Analysis and Stability Evolution

    PubMed Central

    He, Yi-Ming; Ma, Bin-Guang

    2016-01-01

    Protein complexes are major forms of protein-protein interactions and implement essential biological functions. The subunit interface in a protein complex is related to its thermostability. Though the roles of interface properties in thermal adaptation have been investigated for protein complexes, the relationship between the interface size and the expression level of the subunits remains unknown. In the present work, we studied this relationship and found a positive correlation in thermophiles rather than mesophiles. Moreover, we found that the protein interaction strength in complexes is not only temperature-dependent but also abundance-dependent. The underlying mechanism for the observed correlation was explored by simulating the evolution of protein interface stability, which highlights the avoidance of misinteraction. Our findings make more complete the picture of the mechanisms for protein complex thermal adaptation and provide new insights into the principles of protein-protein interactions. PMID:27220911

  12. PADPIN: protein-protein interaction networks of angiogenesis, arteriogenesis, and inflammation in peripheral arterial disease

    PubMed Central

    Vijay, Chaitanya G.; Annex, Brian H.; Bader, Joel S.; Popel, Aleksander S.

    2015-01-01

    Peripheral arterial disease (PAD) results from an obstruction of blood flow in the arteries other than the heart, most commonly the arteries that supply the legs. The complexity of the known signaling pathways involved in PAD, including various growth factor pathways and their cross talks, suggests that analyses of high-throughput experimental data could lead to a new level of understanding of the disease as well as novel and heretofore unanticipated potential targets. Such bioinformatic analyses have not been systematically performed for PAD. We constructed global protein-protein interaction networks of angiogenesis (Angiome), immune response (Immunome), and arteriogenesis (Arteriome) using our previously developed algorithm GeneHits. The term “PADPIN” refers to the angiome, immunome, and arteriome in PAD. Here we analyze four microarray gene expression datasets from ischemic and nonischemic gastrocnemius muscles at day 3 posthindlimb ischemia (HLI) in two genetically different C57BL/6 and BALB/c mouse strains that display differential susceptibility to HLI to identify potential targets and signaling pathways in angiogenesis, immune, and arteriogenesis networks. We hypothesize that identification of the differentially expressed genes in ischemic and nonischemic muscles between the strains that recovers better (C57BL/6) vs. the strain that recovers more poorly (BALB/c) will help for the prediction of target genes in PAD. Our bioinformatics analysis identified several genes that are differentially expressed between the two mouse strains with known functions in PAD including TLR4, THBS1, and PRKAA2 and several genes with unknown functions in PAD including EphA4, TSPAN7, SLC22A4, and EIF2a. PMID:26058837

  13. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics

    PubMed Central

    Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Gui, Jie; Nie, Ru

    2016-01-01

    Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM) classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori) datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research. PMID:27571061

  14. Construction and analysis of protein-protein interaction networks based on proteomics data of prostate cancer

    PubMed Central

    CHEN, CHEN; SHEN, HONG; ZHANG, LI-GUO; LIU, JIAN; CAO, XIAO-GE; YAO, AN-LIANG; KANG, SHAO-SAN; GAO, WEI-XING; HAN, HUI; CAO, FENG-HONG; LI, ZHI-GUO

    2016-01-01

    Currently, using human prostate cancer (PCa) tissue samples to conduct proteomics research has generated a large amount of data; however, only a very small amount has been thoroughly investigated. In this study, we manually carried out the mining of the full text of proteomics literature that involved comparisons between PCa and normal or benign tissue and identified 41 differentially expressed proteins verified or reported more than 2 times from different research studies. We regarded these proteins as seed proteins to construct a protein-protein interaction (PPI) network. The extended network included one giant network, which consisted of 1,264 nodes connected via 1,744 edges, and 3 small separate components. The backbone network was then constructed, which was derived from key nodes and the subnetwork consisting of the shortest path between seed proteins. Topological analyses of these networks were conducted to identify proteins essential for the genesis of PCa. Solute carrier family 2 (facilitated glucose transporter), member 4 (SLC2A4) had the highest closeness centrality located in the center of each network, and the highest betweenness centrality and largest degree in the backbone network. Tubulin, beta 2C (TUBB2C) had the largest degree in the giant network and subnetwork. In addition, using module analysis of the whole PPI network, we obtained a densely connected region. Functional annotation indicated that the Ras protein signal transduction biological process, mitogen-activated protein kinase (MAPK), neurotrophin and the gonadotropin-releasing hormone (GnRH) signaling pathway may play an important role in the genesis and development of PCa. Further investigation of the SLC2A4, TUBB2C proteins, and these biological processes and pathways may therefore provide a potential target for the diagnosis and treatment of PCa. PMID:27121963

  15. Construction and analysis of protein-protein interaction networks based on proteomics data of prostate cancer.

    PubMed

    Chen, Chen; Shen, Hong; Zhang, Li-Guo; Liu, Jian; Cao, Xiao-Ge; Yao, An-Liang; Kang, Shao-San; Gao, Wei-Xing; Han, Hui; Cao, Feng-Hong; Li, Zhi-Guo

    2016-06-01

    Currently, using human prostate cancer (PCa) tissue samples to conduct proteomics research has generated a large amount of data; however, only a very small amount has been thoroughly investigated. In this study, we manually carried out the mining of the full text of proteomics literature that involved comparisons between PCa and normal or benign tissue and identified 41 differentially expressed proteins verified or reported more than 2 times from different research studies. We regarded these proteins as seed proteins to construct a protein-protein interaction (PPI) network. The extended network included one giant network, which consisted of 1,264 nodes connected via 1,744 edges, and 3 small separate components. The backbone network was then constructed, which was derived from key nodes and the subnetwork consisting of the shortest path between seed proteins. Topological analyses of these networks were conducted to identify proteins essential for the genesis of PCa. Solute carrier family 2 (facilitated glucose transporter), member 4 (SLC2A4) had the highest closeness centrality located in the center of each network, and the highest betweenness centrality and largest degree in the backbone network. Tubulin, beta 2C (TUBB2C) had the largest degree in the giant network and subnetwork. In addition, using module analysis of the whole PPI network, we obtained a densely connected region. Functional annotation indicated that the Ras protein signal transduction biological process, mitogen-activated protein kinase (MAPK), neurotrophin and the gonadotropin-releasing hormone (GnRH) signaling pathway may play an important role in the genesis and development of PCa. Further investigation of the SLC2A4, TUBB2C proteins, and these biological processes and pathways may therefore provide a potential target for the diagnosis and treatment of PCa.

  16. Evaluation of liver cirrhosis and hepatocellular carcinoma using Protein-Protein Interaction Networks

    PubMed Central

    Ehsani Ardakani, Mohammad Javad; Safaei, Akram; Arefi Oskouie, Afsaneh; Haghparast, Hesam; Haghazali, Mehrdad; Mohaghegh Shalmani, Hamid; Peyvandi, Hassan; Naderi, Nosratollah; Zali, Mohammad Reza

    2016-01-01

    Aim: In the current study, we analysised only the articles that investigate serum proteome profile of cirrhosis patients or HCC patients versus healthy controls. Background: Increased understanding of cancer biology has enabled identification of molecular events that lead to the discovery of numerous potential biomarkers in diseases. Protein-protein interaction networks is one of aspect that could elevate the understanding level of molecular events and protein connections that lead to the identification of genes and proteins associated with diseases. Methods: Gene expression data, including 63 gene or protein names for hepatocellular carcinoma and 29 gene or protein names for cirrhosis, were extracted from a number of previous investigations. The networks of related differentially expressed genes were explored using Cytoscape and the PPI analysis methods such as MCODE and ClueGO. Centrality and cluster screening identified hub genes, including APOE, TTR, CLU, and APOA1 in cirrhosis. Results: CLU and APOE belong to the regulation of positive regulation of neurofibrillary tangle assembly. HP and APOE involved in cellular oxidant detoxification. C4B and C4BP belong to the complement activation, classical pathway and acute inflammation response pathway. Also, it was reported TTR, TFRC, VWF, CLU, A2M, APOA1, CKAP5, ZNF648, CASP8, and HSP27 as hubs in HCC. In HCC, these include A2M that are corresponding to platelet degranulation, humoral immune response, and negative regulation of immune effector process. CLU belong to the reverse cholesterol transport, platelet degranulation and human immune response. APOA1 corresponds to the reverse cholesterol transport, platelet degranulation and humoral immune response, as well as negative regulation of immune effector process pathway. Conclusion: In conclusion, this study suggests that there is a common molecular relationship between cirrhosis and hepatocellular cancer that may help with identification of target molecules for

  17. Controllability of protein-protein interaction phosphorylation-based networks: Participation of the hub 14-3-3 protein family

    PubMed Central

    Uhart, Marina; Flores, Gabriel; Bustos, Diego M.

    2016-01-01

    Posttranslational regulation of protein function is an ubiquitous mechanism in eukaryotic cells. Here, we analyzed biological properties of nodes and edges of a human protein-protein interaction phosphorylation-based network, especially of those nodes critical for the network controllability. We found that the minimal number of critical nodes needed to control the whole network is 29%, which is considerably lower compared to other real networks. These critical nodes are more regulated by posttranslational modifications and contain more binding domains to these modifications than other kinds of nodes in the network, suggesting an intra-group fast regulation. Also, when we analyzed the edges characteristics that connect critical and non-critical nodes, we found that the former are enriched in domain-to-eukaryotic linear motif interactions, whereas the later are enriched in domain-domain interactions. Our findings suggest a possible structure for protein-protein interaction networks with a densely interconnected and self-regulated central core, composed of critical nodes with a high participation in the controllability of the full network, and less regulated peripheral nodes. Our study offers a deeper understanding of complex network control and bridges the controllability theorems for complex networks and biological protein-protein interaction phosphorylation-based networked systems. PMID:27195976

  18. Controllability of protein-protein interaction phosphorylation-based networks: Participation of the hub 14-3-3 protein family.

    PubMed

    Uhart, Marina; Flores, Gabriel; Bustos, Diego M

    2016-05-19

    Posttranslational regulation of protein function is an ubiquitous mechanism in eukaryotic cells. Here, we analyzed biological properties of nodes and edges of a human protein-protein interaction phosphorylation-based network, especially of those nodes critical for the network controllability. We found that the minimal number of critical nodes needed to control the whole network is 29%, which is considerably lower compared to other real networks. These critical nodes are more regulated by posttranslational modifications and contain more binding domains to these modifications than other kinds of nodes in the network, suggesting an intra-group fast regulation. Also, when we analyzed the edges characteristics that connect critical and non-critical nodes, we found that the former are enriched in domain-to-eukaryotic linear motif interactions, whereas the later are enriched in domain-domain interactions. Our findings suggest a possible structure for protein-protein interaction networks with a densely interconnected and self-regulated central core, composed of critical nodes with a high participation in the controllability of the full network, and less regulated peripheral nodes. Our study offers a deeper understanding of complex network control and bridges the controllability theorems for complex networks and biological protein-protein interaction phosphorylation-based networked systems.

  19. Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods

    PubMed Central

    Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O.; Sperandio, Olivier

    2010-01-01

    Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is

  20. Exosome engineering for efficient intracellular delivery of soluble proteins using optically reversible protein-protein interaction module.

    PubMed

    Yim, Nambin; Ryu, Seung-Wook; Choi, Kyungsun; Lee, Kwang Ryeol; Lee, Seunghee; Choi, Hojun; Kim, Jeongjin; Shaker, Mohammed R; Sun, Woong; Park, Ji-Ho; Kim, Daesoo; Heo, Won Do; Choi, Chulhee

    2016-07-22

    Nanoparticle-mediated delivery of functional macromolecules is a promising method for treating a variety of human diseases. Among nanoparticles, cell-derived exosomes have recently been highlighted as a new therapeutic strategy for the in vivo delivery of nucleotides and chemical drugs. Here we describe a new tool for intracellular delivery of target proteins, named 'exosomes for protein loading via optically reversible protein-protein interactions' (EXPLORs). By integrating a reversible protein-protein interaction module controlled by blue light with the endogenous process of exosome biogenesis, we are able to successfully load cargo proteins into newly generated exosomes. Treatment with protein-loaded EXPLORs is shown to significantly increase intracellular levels of cargo proteins and their function in recipient cells in vitro and in vivo. These results clearly indicate the potential of EXPLORs as a mechanism for the efficient intracellular transfer of protein-based therapeutics into recipient cells and tissues.

  1. GeneSense: a new approach for human gene annotation integrated with protein-protein interaction networks.

    PubMed

    Chen, Zhongzhong; Zhang, Tianhong; Lin, Jun; Yan, Zidan; Wang, Yongren; Zheng, Weiqiang; Weng, Kevin C

    2014-03-26

    Virtually all cellular functions involve protein-protein interactions (PPIs). As an increasing number of PPIs are identified and vast amount of information accumulated, researchers are finding different ways to interrogate the data and understand the interactions in context. However, it is widely recognized that a significant portion of the data is scattered, redundant, not considered high quality, and not readily accessible to researchers in a systematic fashion. In addition, it is challenging to identify the optimal protein targets in the current PPI networks. The GeneSense server was developed to integrate gene annotation and PPI networks in an expandable architecture that incorporates selected databases with the aim to assemble, analyze, evaluate and disseminate protein-protein association information in a comprehensive and user-friendly manner. Three network models including nodenet, leafnet and loopnet are used to identify the optimal protein targets in the complex networks. GeneSense is freely available at www.biomedsense.org/genesense.php.

  2. Evaluating protein-protein interaction (PPI) networks for diseases pathway, target discovery, and drug-design using 'in silico pharmacology'.

    PubMed

    Chakraborty, Chiranjib; Doss C, George Priya; Chen, Luonan; Zhu, Hailong

    2014-01-01

    In silico pharmacology is a promising field in the current state-of drug discovery. This area exploits "protein-protein Interaction (PPI) network analysis for drug discovery using the drug "target class". To document the current status, we have discussed in this article how this an integrated system of PPI networks contribute to understand the disease pathways, present state-of-the-art drug target discovery and drug discovery process. This review article enhances our knowledge on conventional drug discovery and current drug discovery using in silico techniques, best "target class", universal architecture of PPI networks, the present scenario of disease pathways and protein-protein interaction networks as well as the method to comprehend the PPI networks. Taken all together, ultimately a snapshot has been discussed to be familiar with how PPI network architecture can used to validate a drug target. At the conclusion, we have illustrated the future directions of PPI in target discovery and drug-design.

  3. Targeting protein-protein interactions within the cyclic AMP signaling system as a therapeutic strategy for cardiovascular disease.

    PubMed

    Lee, Louisa C Y; Maurice, Donald H; Baillie, George S

    2013-03-01

    The cAMP signaling system can trigger precise physiological cellular responses that depend on the fidelity of many protein-protein interactions, which act to bring together signaling intermediates at defined locations within cells. In the heart, cAMP participates in the fine control of excitation-contraction coupling, hence, any disregulation of this signaling cascade can lead to cardiac disease. Due to the ubiquitous nature of the cAMP pathway, general inhibitors of cAMP signaling proteins such as PKA, EPAC and PDEs would act non-specifically and universally, increasing the likelihood of serious 'off target' effects. Recent advances in the discovery of peptides and small molecules that disrupt the protein-protein interactions that underpin cellular targeting of cAMP signaling proteins are described and discussed.

  4. Protein-Protein Interactions: Gene Acronym Redundancies and Current Limitations Precluding Automated Data Integration

    PubMed Central

    Casado-Vela, Juan; Matthiesen, Rune; Sellés, Susana; Naranjo, José Ramón

    2013-01-01

    Understanding protein interaction networks and their dynamic changes is a major challenge in modern biology. Currently, several experimental and in silico approaches allow the screening of protein interactors in a large-scale manner. Therefore, the bulk of information on protein interactions deposited in databases and peer-reviewed published literature is constantly growing. Multiple databases interfaced from user-friendly web tools recently emerged to facilitate the task of protein interaction data retrieval and data integration. Nevertheless, as we evidence in this report, despite the current efforts towards data integration, the quality of the information on protein interactions retrieved by in silico approaches is frequently incomplete and may even list false interactions. Here we point to some obstacles precluding confident data integration, with special emphasis on protein interactions, which include gene acronym redundancies and protein synonyms. Three human proteins (choline kinase, PPIase and uromodulin) and three different web-based data search engines focused on protein interaction data retrieval (PSICQUIC, DASMI and BIPS) were used to explain the potential occurrence of undesired errors that should be considered by researchers in the field. We demonstrate that, despite the recent initiatives towards data standardization, manual curation of protein interaction networks based on literature searches are still required to remove potential false positives. A three-step workflow consisting of: (i) data retrieval from multiple databases, (ii) peer-reviewed literature searches, and (iii) data curation and integration, is proposed as the best strategy to gather updated information on protein interactions. Finally, this strategy was applied to compile bona fide information on human DREAM protein interactome, which constitutes liable training datasets that can be used to improve computational predictions. PMID:28250396

  5. Protein-Protein Interactions: Gene Acronym Redundancies and Current Limitations Precluding Automated Data Integration.

    PubMed

    Casado-Vela, Juan; Matthiesen, Rune; Sellés, Susana; Naranjo, José Ramón

    2013-05-31

    Understanding protein interaction networks and their dynamic changes is a major challenge in modern biology. Currently, several experimental and in silico approaches allow the screening of protein interactors in a large-scale manner. Therefore, the bulk of information on protein interactions deposited in databases and peer-reviewed published literature is constantly growing. Multiple databases interfaced from user-friendly web tools recently emerged to facilitate the task of protein interaction data retrieval and data integration. Nevertheless, as we evidence in this report, despite the current efforts towards data integration, the quality of the information on protein interactions retrieved by in silico approaches is frequently incomplete and may even list false interactions. Here we point to some obstacles precluding confident data integration, with special emphasis on protein interactions, which include gene acronym redundancies and protein synonyms. Three human proteins (choline kinase, PPIase and uromodulin) and three different web-based data search engines focused on protein interaction data retrieval (PSICQUIC, DASMI and BIPS) were used to explain the potential occurrence of undesired errors that should be considered by researchers in the field. We demonstrate that, despite the recent initiatives towards data standardization, manual curation of protein interaction networks based on literature searches are still required to remove potential false positives. A three-step workflow consisting of: (i) data retrieval from multiple databases, (ii) peer-reviewed literature searches, and (iii) data curation and integration, is proposed as the best strategy to gather updated information on protein interactions. Finally, this strategy was applied to compile bona fide information on human DREAM protein interactome, which constitutes liable training datasets that can be used to improve computational predictions.

  6. Development of a Model Protein Interaction Pair as a Benchmarking Tool for the Quantitative Analysis of 2-Site Protein-Protein Interactions.

    PubMed

    Yamniuk, Aaron P; Newitt, John A; Doyle, Michael L; Arisaka, Fumio; Giannetti, Anthony M; Hensley, Preston; Myszka, David G; Schwarz, Fred P; Thomson, James A; Eisenstein, Edward

    2015-12-01

    A significant challenge in the molecular interaction field is to accurately determine the stoichiometry and stepwise binding affinity constants for macromolecules having >1 binding site. The mission of the Molecular Interactions Research Group (MIRG) of the Association of Biomolecular Resource Facilities (ABRF) is to show how biophysical technologies are used to quantitatively characterize molecular interactions, and to educate the ABRF members and scientific community on the utility and limitations of core technologies [such as biosensor, microcalorimetry, or analytic ultracentrifugation (AUC)]. In the present work, the MIRG has developed a robust model protein interaction pair consisting of a bivalent variant of the Bacillus amyloliquefaciens extracellular RNase barnase and a variant of its natural monovalent intracellular inhibitor protein barstar. It is demonstrated that this system can serve as a benchmarking tool for the quantitative analysis of 2-site protein-protein interactions. The protein interaction pair enables determination of precise binding constants for the barstar protein binding to 2 distinct sites on the bivalent barnase binding partner (termed binase), where the 2 binding sites were engineered to possess affinities that differed by 2 orders of magnitude. Multiple MIRG laboratories characterized the interaction using isothermal titration calorimetry (ITC), AUC, and surface plasmon resonance (SPR) methods to evaluate the feasibility of the system as a benchmarking model. Although general agreement was seen for the binding constants measured using solution-based ITC and AUC approaches, weaker affinity was seen for surface-based method SPR, with protein immobilization likely affecting affinity. An analysis of the results from multiple MIRG laboratories suggests that the bivalent barnase-barstar system is a suitable model for benchmarking new approaches for the quantitative characterization of complex biomolecular interactions.

  7. Biophysical and computational fragment-based approaches to targeting protein-protein interactions: applications in structure-guided drug discovery.

    PubMed

    Winter, Anja; Higueruelo, Alicia P; Marsh, May; Sigurdardottir, Anna; Pitt, Will R; Blundell, Tom L

    2012-11-01

    Drug discovery has classically targeted the active sites of enzymes or ligand-binding sites of receptors and ion channels. In an attempt to improve selectivity of drug candidates, modulation of protein-protein interfaces (PPIs) of multiprotein complexes that mediate conformation or colocation of components of cell-regulatory pathways has become a focus of interest. However, PPIs in multiprotein systems continue to pose significant challenges, as they are generally large, flat and poor in distinguishing features, making the design of small molecule antagonists a difficult task. Nevertheless, encouragement has come from the recognition that a few amino acids - so-called hotspots - may contribute the majority of interaction-free energy. The challenges posed by protein-protein interactions have led to a wellspring of creative approaches, including proteomimetics, stapled α-helical peptides and a plethora of antibody inspired molecular designs. Here, we review a more generic approach: fragment-based drug discovery. Fragments allow novel areas of chemical space to be explored more efficiently, but the initial hits have low affinity. This means that they will not normally disrupt PPIs, unless they are tethered, an approach that has been pioneered by Wells and co-workers. An alternative fragment-based approach is to stabilise the uncomplexed components of the multiprotein system in solution and employ conventional fragment-based screening. Here, we describe the current knowledge of the structures and properties of protein-protein interactions and the small molecules that can modulate them. We then describe the use of sensitive biophysical methods - nuclear magnetic resonance, X-ray crystallography, surface plasmon resonance, differential scanning fluorimetry or isothermal calorimetry - to screen and validate fragment binding. Fragment hits can subsequently be evolved into larger molecules with higher affinity and potency. These may provide new leads for drug candidates

  8. An integrated strategy for the discovery of drug targets by the analysis of protein-protein interactions

    NASA Astrophysics Data System (ADS)

    Peltier, John M.; Askovic, Srdjan; Becklin, Robert R.; Chepanoske, Cindy Lou; Ho, Yew-Seng J.; Kery, Vladimir; Lai, Shuping; Mujtaba, Tahmina; Pyne, Mike; Robbins, Paul B.; Rechenberg, Moritz Von; Richardson, Bonnie; Savage, Justin; Sheffield, Peter; Thompson, Sam; Weir, Lawrence; Widjaja, Kartika; Xu, Nafei; Zhen, Yuejun; Boniface, J. Jay

    2004-11-01

    Proteomics-based technologies have the potential to accelerate the development of drugs, but such technologies must be well integrated in order to have a positive impact. We describe, herein, a multi-step process for the discovery of protein-protein interactions. It is shown that process stages are interdependent and can influence, either positively or negatively, subsequent steps. Optimization of each step, in the context of the full process, is essential for the overall success of the experiment.

  9. A cautionary note on the use of split-YFP/BiFC in plant protein-protein interaction studies.

    PubMed

    Horstman, Anneke; Tonaco, Isabella Antonia Nougalli; Boutilier, Kim; Immink, Richard G H

    2014-05-30

    Since its introduction in plants 10 years ago, the bimolecular fluorescence complementation (BiFC) method, or split-YFP (yellow fluorescent protein), has gained popularity within the plant biology field as a method to study protein-protein interactions. BiFC is based on the restoration of fluorescence after the two non-fluorescent halves of a fluorescent protein are brought together by a protein-protein interaction event. The major drawback of BiFC is that the fluorescent protein halves are prone to self-assembly independent of a protein-protein interaction event. To circumvent this problem, several modifications of the technique have been suggested, but these modifications have not lead to improvements in plant BiFC protocols. Therefore, it remains crucial to include appropriate internal controls. Our literature survey of recent BiFC studies in plants shows that most studies use inappropriate controls, and a qualitative rather than quantitative read-out of fluorescence. Therefore, we provide a cautionary note and beginner's guideline for the setup of BiFC experiments, discussing each step of the protocol, including vector choice, plant expression systems, negative controls, and signal detection. In addition, we present our experience with BiFC with respect to self-assembly, peptide linkers, and incubation temperature. With this note, we aim to provide a guideline that will improve the quality of plant BiFC experiments.

  10. Protein-protein interaction and gene co-expression maps of ARFs and Aux/IAAs in Arabidopsis

    PubMed Central

    Piya, Sarbottam; Shrestha, Sandesh K.; Binder, Brad; Stewart, C. Neal; Hewezi, Tarek

    2014-01-01

    The phytohormone auxin regulates nearly all aspects of plant growth and development. Based on the current model in Arabidopsis thaliana, Auxin/indole-3-acetic acid (Aux/IAA) proteins repress auxin-inducible genes by inhibiting auxin response transcription factors (ARFs). Experimental evidence suggests that heterodimerization between Aux/IAA and ARF proteins are related to their unique biological functions. The objective of this study was to generate the Aux/IAA-ARF protein-protein interaction map using full length sequences and locate the interacting protein pairs to specific gene co-expression networks in order to define tissue-specific responses of the Aux/IAA-ARF interactome. Pairwise interactions between 19 ARFs and 29 Aux/IAAs resulted in the identification of 213 specific interactions of which 79 interactions were previously unknown. The incorporation of co-expression profiles with protein-protein interaction data revealed a strong correlation of gene co-expression for 70% of the ARF-Aux/IAA interacting pairs in at least one tissue/organ, indicative of the biological significance of these interactions. Importantly, ARF4-8 and 19, which were found to interact with almost all Aux-Aux/IAA showed broad co-expression relationships with Aux/IAA genes, thus, formed the central hubs of the co-expression network. Our analyses provide new insights into the biological significance of ARF-Aux/IAA associations in the morphogenesis and development of various plant tissues and organs. PMID:25566309

  11. Bimolecular Fluorescence Complementation (BiFC) Assay for Direct Visualization of Protein-Protein Interaction in vivo.

    PubMed

    Lai, Hsien-Tsung; Chiang, Cheng-Ming

    Bimolecular Fluorescence Complementation (BiFC) assay is a method used to directly visualize protein-protein interaction in vivo using live-cell imaging or fixed cells. This protocol described here is based on our recent paper describing the functional association of human chromatin adaptor and transcription cofactor Brd4 with p53 tumor suppressor protein (Wu et al., 2013). BiFC was first described by Hu et al. (2002) using two non-fluorescent protein fragments of enhanced yellow fluorescent protein (EYFP), which is an Aequorea victoria GFP variant protein, fused respectively to a Rel family protein and a bZIP family transcription factor to investigate interactions between these two family members in living cells. The YFP was later improved by introducing mutations to reduce its sensitivity to pH and chloride ions, thus generating a super-enhanced YFP, named Venus fluorescent protein, without showing diminished fluorescence at 37 °C as typically observed with EYFP (Nagai et al., 2006). The fluorescence signal is regenerated by complementation of two non-fluorescent fragments (e.g., the Venus N-terminal 1-158 amino acid residues, called Venus-N, and its C-terminal 159-239 amino acid residues, named Venus-C; see Figure 1A and Gully et al., 2012; Ding et al., 2006; Kerppola, 2006) that are brought together by interaction between their respective fusion partners (e.g., Venus-N to p53, and Venus-C to the PDID domain of human Brd4; see Figure 1B and 1C). The intensity and cellular location of the regenerated fluorescence signals can be detected by fluorescence microscope. The advantages of the proximity-based BiFC assay are: first, it allows a direct visualization of spatial and temporal interaction between two partner proteins in vivo; second, the fluorescence signal provides a sensitive readout for detecting protein-protein interaction even at a low expression level comparable to that of the endogenous proteins; third, the intensity of the fluorescence signal is

  12. Molecular insights into the stabilization of protein-protein interactions with small molecule: The FKBP12-rapamycin-FRB case study

    NASA Astrophysics Data System (ADS)

    Chaurasia, Shilpi; Pieraccini, Stefano; De Gonda, Riccardo; Conti, Simone; Sironi, Maurizio

    2013-11-01

    Targetting protein-protein interactions is a challenging task in drug discovery process. Despite the challenges, several studies provided evidences for the development of small molecules modulating protein-protein interactions. Here we consider a typical case of protein-protein interaction stabilization: the complex between FKBP12 and FRB with rapamycin. We have analyzed the stability of the complex and characterized its interactions at the atomic level by performing free energy calculations and computational alanine scanning. It is shown that rapamycin stabilizes the complex by acting as a bridge between the two proteins; and the complex is stable only in the presence of rapamycin.

  13. Stapled Voltage-Gated Calcium Channel (CaV) α-Interaction Domain (AID) Peptides Act As Selective Protein-Protein Interaction Inhibitors of CaV Function.

    PubMed

    Findeisen, Felix; Campiglio, Marta; Jo, Hyunil; Abderemane-Ali, Fayal; Rumpf, Christine H; Pope, Lianne; Rossen, Nathan D; Flucher, Bernhard E; DeGrado, William F; Minor, Daniel L

    2017-03-17

    For many voltage-gated ion channels (VGICs), creation of a properly functioning ion channel requires the formation of specific protein-protein interactions between the transmembrane pore-forming subunits and cystoplasmic accessory subunits. Despite the importance of such protein-protein interactions in VGIC function and assembly, their potential as sites for VGIC modulator development has been largely overlooked. Here, we develop meta-xylyl (m-xylyl) stapled peptides that target a prototypic VGIC high affinity protein-protein interaction, the interaction between the voltage-gated calcium channel (CaV) pore-forming subunit α-interaction domain (AID) and cytoplasmic β-subunit (CaVβ). We show using circular dichroism spectroscopy, X-ray crystallography, and isothermal titration calorimetry that the m-xylyl staples enhance AID helix formation are structurally compatible with native-like AID:CaVβ interactions and reduce the entropic penalty associated with AID binding to CaVβ. Importantly, electrophysiological studies reveal that stapled AID peptides act as effective inhibitors of the CaVα1:CaVβ interaction that modulate CaV function in an CaVβ isoform-selective manner. Together, our studies provide a proof-of-concept demonstration of the use of protein-protein interaction inhibitors to control VGIC function and point to strategies for improved AID-based CaV modulator design.

  14. Detection of protein-protein interactions in plants using the transrepressive activity of the EAR motif repression domain.

    PubMed

    Matsui, Kyoko; Ohme-Takagi, Masaru

    2010-02-01

    The activities of many regulatory factors involve interactions with other proteins. We demonstrate here that the ERF-associated amphiphilic repression (EAR) motif repression domain (SRDX) can convert a transcriptional complex into a repressor via transrepression that is mediated by protein-protein interactions and show that transrepressive activity of SRDX can be used to detect such protein-protein interactions. When we fused a protein that interacts with a transcription factor with SRDX and co-expressed the product with the transcription factor in plant cells, the expression of genes that are targets of the transcription factor was suppressed by transrepression. We demonstrated the transrepressive activity of SRDX using FOS and JUN as a model system and used two MADS box plant proteins, PISTILLATA and APETALA3, which are known to form heterodimers. Furthermore, the transgenic plants that expressed TTG1, which is a WD40 protein and interacts with bHLH transcription factors, fused to SRDX exhibited a phenotype similar to ttg1 mutants by transrepression and the regions of TTG1 required for interaction to the bHLH protein were detected using our system. We also used this system to analyse a protein factor that might be incorporated into a transcriptional complex and identified an Arabidopsis WD40 protein PWP2 (AtPWP2) interacting with AtTBP1 through comparison of phenotypes induced by 35S:AtPWP2-SRDX with that induced by the chimeric repressor. Our results indicate that the transrepression mediated by SRDX can be used to detect and confirm protein-protein interactions in plants and should be useful in identifying factors that form transcriptional protein complexes.

  15. Bacterioferritin: Structure, Dynamics, and Protein-Protein Interactions at Play in Iron Storage and Mobilization.

    PubMed

    Rivera, Mario

    2017-02-21

    . It remains to be seen whether similar studies with E. coli Bfr will reveal distinct cooperative motions contributing to the stability of its FCs. Mobilization of Fe(3+) stored in BfrB requires interaction with a ferredoxin (Bfd), which transfers electrons to reduce Fe(3+) in the internal cavity of BfrB for subsequent release of Fe(2+). The structure of the BfrB/Bfd complex furnished the only known structure of a ferritin molecule in complex with a physiological protein partner. The BfrB/Bfd complex is stabilized by hot-spot residues in both proteins, which interweave into a highly complementary hot region. The hot-spot residues are conserved in the sequences of Bfr and Bfd proteins from a number of bacteria, indicating that the BfrB/Bfd interaction is of widespread significance in bacterial iron metabolism. The BfrB/Bfd structure also furnished the only known structure of a Bfd, which revealed a novel helix-turn-helix fold different from the β-strand and α-helix fold of plant and vertebrate [2Fe-2S]-ferredoxins. Bfds seem to be unique to bacteria; consequently, although mobilization of iron from eukaryotic ferritins may also be facilitated by protein-protein interactions, the nature of the protein that delivers electrons to the ferric core of eukaryotic ferritins remains unknown.

  16. Protein-protein interactions within the ensemble, eukaryotic V-ATPase, and its concerted interactions with cellular machineries.

    PubMed

    Balakrishna, Asha Manikkoth; Manimekalai, Malathy Sony Subramanian; Grüber, Gerhard

    2015-10-01

    The V1VO-ATPase (V-ATPase) is the important proton-pump in eukaryotic cells, responsible for pH-homeostasis, pH-sensing and amino acid sensing, and therefore essential for cell growths and metabolism. ATP-cleavage in the catalytic A3B3-hexamer of V1 has to be communicated via several so-called central and peripheral stalk units to the proton-pumping VO-part, which is membrane-embedded. A unique feature of V1VO-ATPase regulation is its reversible disassembly of the V1 and VO domain. Actin provides a network to hold the V1 in proximity to the VO, enabling effective V1VO-assembly to occur. Besides binding to actin, the 14-subunit V-ATPase interacts with multi-subunit machineries to form cellular sensors, which regulate the pH in cellular compartments or amino acid signaling in lysosomes. Here we describe a variety of subunit-subunit interactions within the V-ATPase enzyme during catalysis and its protein-protein assembling with key cellular machineries, essential for cellular function.

  17. Complex structure of cytochrome c-cytochrome c oxidase reveals a novel protein-protein interaction mode.

    PubMed

    Shimada, Satoru; Shinzawa-Itoh, Kyoko; Baba, Junpei; Aoe, Shimpei; Shimada, Atsuhiro; Yamashita, Eiki; Kang, Jiyoung; Tateno, Masaru; Yoshikawa, Shinya; Tsukihara, Tomitake

    2017-02-01

    Mitochondrial cytochrome c oxidase (CcO) transfers electrons from cytochrome c (Cyt.c) to O2 to generate H2O, a process coupled to proton pumping. To elucidate the mechanism of electron transfer, we determined the structure of the mammalian Cyt.c-CcO complex at 2.0-Å resolution and identified an electron transfer pathway from Cyt.c to CcO. The specific interaction between Cyt.c and CcO is stabilized by a few electrostatic interactions between side chains within a small contact surface area. Between the two proteins are three water layers with a long inter-molecular span, one of which lies between the other two layers without significant direct interaction with either protein. Cyt.c undergoes large structural fluctuations, using the interacting regions with CcO as a fulcrum. These features of the protein-protein interaction at the docking interface represent the first known example of a new class of protein-protein interaction, which we term "soft and specific". This interaction is likely to contribute to the rapid association/dissociation of the Cyt.c-CcO complex, which facilitates the sequential supply of four electrons for the O2 reduction reaction.

  18. Towards a Rigorous Network of Protein-Protein Interactions of the Model Sulfate Reducer Desulfovibrio vulgaris Hildenborough

    PubMed Central

    Petzold, Christopher J.; Zane, Grant M.; Price, Morgan N.; Reveco, Sonia A.; Fok, Veronica; Johanson, Alyssa R.; Batth, Tanveer S.; Singer, Mary; Chandonia, John-Marc; Joyner, Dominique; Hazen, Terry C.; Arkin, Adam P.; Wall, Judy D.; Singh, Anup K.; Keasling, Jay D.

    2011-01-01

    Protein–protein interactions offer an insight into cellular processes beyond what may be obtained by the quantitative functional genomics tools of proteomics and transcriptomics. The aforementioned tools have been extensively applied to study Escherichia coli and other aerobes and more recently to study the stress response behavior of Desulfovibrio vulgaris Hildenborough, a model obligate anaerobe and sulfate reducer and the subject of this study. Here we carried out affinity purification followed by mass spectrometry to reconstruct an interaction network among 12 chromosomally encoded bait and 90 prey proteins based on 134 bait-prey interactions identified to be of high confidence. Protein-protein interaction data are often plagued by the lack of adequate controls and replication analyses necessary to assess confidence in the results, including identification of potential false positives. We addressed these issues through the use of biological replication, exponentially modified protein abundance indices, results from an experimental negative control, and a statistical test to assign confidence to each putative interacting pair applicable to small interaction data studies. We discuss the biological significance of metabolic features of D. vulgaris revealed by these protein-protein interaction data and the observed protein modifications. These include the distinct role of the putative carbon monoxide-induced hydrogenase, unique electron transfer routes associated with different oxidoreductases, and the possible role of methylation in regulating sulfate reduction. PMID:21738675

  19. A plasmid-based expression system to study protein-protein interactions at the Golgi in vivo.

    PubMed

    Bera, Sujoy; Raghuram, Vijeta; Mikhaylova, Marina; Kreutz, Michael R

    2016-06-01

    There is still an unmet need for simple methods to verify, visualize, and confirm protein-protein interactions in vivo. Here we describe a plasmid-based system to study such interactions. The system is based on the transmembrane domain (TMD) of the EF-hand Ca(2+) sensor protein calneuron-2. We show that fusion of 28 amino acids that include the TMD of calneuron-2 to proteins of interest results in prominent localization on the cytoplasmic side of the Golgi. The recruitment of binding partners to the protein of interest fused to this sequence can then be easily visualized by fluorescent tags.

  20. Molecular interactions between multihaem cytochromes: probing the protein-protein interactions between pentahaem cytochromes of a nitrite reductase complex.

    PubMed

    Lockwood, Colin; Butt, Julea N; Clarke, Thomas A; Richardson, David J

    2011-01-01

    The cytochrome c nitrite reductase NrfA is a 53 kDa pentahaem enzyme that crystallizes as a decahaem homodimer. NrfA catalyses the reduction of NO2- to NH4+ through a six electron reduction pathway that is of major physiological significance to the anaerobic metabolism of enteric and sulfate reducing bacteria. NrfA receives electrons from the 21 kDa pentahaem NrfB donor protein. This requires that redox complexes form between the NrfA and NrfB pentahaem cytochromes. The formation of these complexes can be monitored using a range of methodologies for studying protein-protein interactions, including dynamic light scattering, gel filtration, analytical ultracentrifugation and visible spectroscopy. These methods have been used to show that oxidized NrfA exists in dynamic monomer-dimer equilibrium with a Kd (dissociation constant) of 4 μM. Significantly, the monomeric and dimeric forms of NrfA are equally active for either the six electron reduction of NO2- or HSO3-. When mixed together, NrfA and NrfB exist in equilibrium with NrfAB, which is described by a Kd of 50 nM. Thus, since NrfA and NrfB are present in micromolar concentrations in the periplasmic compartment, it is likely that NrfB remains tightly associated with its NrfA redox partner under physiological conditions.

  1. A Library of Plasmodium vivax Recombinant Merozoite Proteins Reveals New Vaccine Candidates and Protein-Protein Interactions

    PubMed Central

    Hostetler, Jessica B.; Sharma, Sumana; Bartholdson, S. Josefin; Wright, Gavin J.; Fairhurst, Rick M.; Rayner, Julian C.

    2015-01-01

    Background A vaccine targeting Plasmodium vivax will be an essential component of any comprehensive malaria elimination program, but major gaps in our understanding of P. vivax biology, including the protein-protein interactions that mediate merozoite invasion of reticulocytes, hinder the search for candidate antigens. Only one ligand-receptor interaction has been identified, that between P. vivax Duffy Binding Protein (PvDBP) and the erythrocyte Duffy Antigen Receptor for Chemokines (DARC), and strain-specific immune responses to PvDBP make it a complex vaccine target. To broaden the repertoire of potential P. vivax merozoite-stage vaccine targets, we exploited a recent breakthrough in expressing full-length ectodomains of Plasmodium proteins in a functionally-active form in mammalian cells and initiated a large-scale study of P. vivax merozoite proteins that are potentially involved in reticulocyte binding and invasion. Methodology/Principal Findings We selected 39 P. vivax proteins that are predicted to localize to the merozoite surface or invasive secretory organelles, some of which show homology to P. falciparum vaccine candidates. Of these, we were able to express 37 full-length protein ectodomains in a mammalian expression system, which has been previously used to express P. falciparum invasion ligands such as PfRH5. To establish whether the expressed proteins were correctly folded, we assessed whether they were recognized by antibodies from Cambodian patients with acute vivax malaria. IgG from these samples showed at least a two-fold change in reactivity over naïve controls in 27 of 34 antigens tested, and the majority showed heat-labile IgG immunoreactivity, suggesting the presence of conformation-sensitive epitopes and native tertiary protein structures. Using a method specifically designed to detect low-affinity, extracellular protein-protein interactions, we confirmed a predicted interaction between P. vivax 6-cysteine proteins P12 and P41, further

  2. A general system for studying protein-protein interactions in gram-negative bacteria

    SciTech Connect

    Pelletier, Dale A.; Hurst, G. B.; Foote, Linda J.; Lankford, Patricia K.; McKeown, Cathy K.; Lu, Tse-Yuan S.; Schmoyer, Denise D.; Shah, Manesh B.; Hervey IV, W. J.; McDonald, W. Hayes; Hooker, Brian S.; Cannon, William R.; Daly, Don S.; Gilmore, Jason M.; Wiley, H. S.; Auberry, Deanna L.; Wang, Yisong; Larimer, Frank; Kennel, S. J.; Doktycz, M. J.; Morrell-Falvey, Jennifer; Owens, Elizabeth T.; Buchanan, M. V.

    2008-08-01

    One of the most promising of the emerging methods for large-scale studies of interactions among proteins is co-isolation of an affinity-tagged protein and its interaction partners, followed by mass spectrometric identification of the co-purifying proteins. We describe a methodology for systematically identifying the proteins that interact with affinity-tagged “bait” proteins expressed from a medium copy plasmid, which are based on a broad host range (pBBR1MCS5) vector backbone that has been modified to incorporate the Gateway DEST plasmid multiple cloning region. This construct was designed to facilitate expression of fusion proteins bearing an affinity tag, across a range of Gram negative bacterial hosts. We demonstrate the performance of this methodology by characterizing interactions among subunits of the DNA-dependent RNA polymerase complex in two metabolically versatile Gram negative microbial species of environmental interest, Rhodopseudomonas palustris CGA010 and Shewanella oneidensis MR-1. Results from the RNA polymerase complex from these two species compared favorably with those for both plasmid- and chromosomally-encoded affinity-tagged fusion proteins expressed in a model organism, E. coli.

  3. Toward a rigorous network of protein-protein interactions of the model sulfate reducer Desulfovibrio vulgaris Hildenborough

    SciTech Connect

    Chhabra, S.R.; Joachimiak, M.P.; Petzold, C.J.; Zane, G.M.; Price, M.N.; Gaucher, S.; Reveco, S.A.; Fok, V.; Johanson, A.R.; Batth, T.S.; Singer, M.; Chandonia, J.M.; Joyner, D.; Hazen, T.C.; Arkin, A.P.; Wall, J.D.; Singh, A.K.; Keasling, J.D.

    2011-05-01

    Protein–protein interactions offer an insight into cellular processes beyond what may be obtained by the quantitative functional genomics tools of proteomics and transcriptomics. The aforementioned tools have been extensively applied to study E. coli and other aerobes and more recently to study the stress response behavior of Desulfovibrio 5 vulgaris Hildenborough, a model anaerobe and sulfate reducer. In this paper we present the first attempt to identify protein-protein interactions in an obligate anaerobic bacterium. We used suicide vector-assisted chromosomal modification of 12 open reading frames encoded by this sulfate reducer to append an eight amino acid affinity tag to the carboxy-terminus of the chosen proteins. Three biological replicates of the 10 ‘pulled-down’ proteins were separated and analyzed using liquid chromatography-mass spectrometry. Replicate agreement ranged between 35% and 69%. An interaction network among 12 bait and 90 prey proteins was reconstructed based on 134 bait-prey interactions computationally identified to be of high confidence. We discuss the biological significance of several unique metabolic features of D. vulgaris revealed by this protein-protein interaction data 15 and protein modifications that were observed. These include the distinct role of the putative carbon monoxide-induced hydrogenase, unique electron transfer routes associated with different oxidoreductases, and the possible role of methylation in regulating sulfate reduction.

  4. Protein-spanning water networks and implications for prediction of protein-protein interactions mediated through hydrophobic effects.

    PubMed

    Cui, Di; Ou, Shuching; Patel, Sandeep

    2014-12-01

    Hydrophobic effects, often conflated with hydrophobic forces, are implicated as major determinants in biological association and self-assembly processes. Protein-protein interactions involved in signaling pathways in living systems are a prime example where hydrophobic effects have profound implications. In the context of protein-protein interactions, a priori knowledge of relevant binding interfaces (i.e., clusters of residues involved directly with binding interactions) is difficult. In the case of hydrophobically mediated interactions, use of hydropathy-based methods relying on single residue hydrophobicity properties are routinely and widely used to predict propensities for such residues to be present in hydrophobic interfaces. However, recent studies suggest that consideration of hydrophobicity for single residues on a protein surface require accounting of the local environment dictated by neighboring residues and local water. In this study, we use a method derived from percolation theory to evaluate spanning water networks in the first hydration shells of a series of small proteins. We use residue-based water density and single-linkage clustering methods to predict hydrophobic regions of proteins; these regions are putatively involved in binding interactions. We find that this simple method is able to predict with sufficient accuracy and coverage the binding interface residues of a series of proteins. The approach is competitive with automated servers. The results of this study highlight the importance of accounting of local environment in determining the hydrophobic nature of individual residues on protein surfaces.

  5. Calculation of weak protein-protein interactions: the pH dependence of the second virial coefficient.

    PubMed

    Elcock, A H; McCammon, J A

    2001-02-01

    Interactions between proteins are often sufficiently weak that their study through the use of conventional structural techniques becomes problematic. Of the few techniques capable of providing experimental measures of weak protein-protein interactions, perhaps the most useful is the second virial coefficient, B(22), which quantifies a protein solution's deviations from ideal behavior. It has long been known that B(22) can in principle be computed, but only very recently has it been demonstrated that such calculations can be performed using protein models of true atomic detail (Biophys. J. 1998, 75:2469-2477). The work reported here extends these previous efforts in an attempt to develop a transferable energetic model capable of reproducing the experimental trends obtained for two different proteins over a range of pH and ionic strengths. We describe protein-protein interaction energies by a combination of three separate terms: (i) an electrostatic interaction term based on the use of effective charges, (ii) a term describing the electrostatic desolvation that occurs when charged groups are buried by an approaching protein partner, and (iii) a solvent-accessible surface area term that is used to describe contributions from van der Waals and hydrophobic interactions. The magnitude of the third term is governed by an adjustable, empirical parameter, gamma, that is altered to optimize agreement between calculated and experimental values of B(22). The model is applied separately to the proteins lysozyme and chymotrypsinogen, yielding optimal values of gamma that are almost identical. There are, however, clear difficulties in reproducing B(22) values at the extremes of pH. Explicit calculation of the protonation states of ionizable amino acids in the 200 most energetically favorable protein-protein structures suggest that these difficulties are due to a neglect of the protonation state changes that can accompany complexation. Proper reproduction of the pH dependence of B

  6. Quantification of the HIV transcriptional activator complex in live cells by image-based protein-protein interaction analysis.

    PubMed

    Asamitsu, Kaori; Omagari, Katsumi; Okuda, Tomoya; Hibi, Yurina; Okamoto, Takashi

    2016-07-01

    The virus-encoded Tat protein is essential for HIV transcription in infected cells. The interaction of Tat with the cellular transcription elongation factor P-TEFb (positive transcriptional elongation factor b) containing cyclin T1 (CycT1) and cyclin-dependent kinase 9 (CDK9) is critical for its activity. In this study, we use the Fluoppi (fluorescent-based technology detecting protein-protein interaction) system, which enables the quantification of interactions between biomolecules, such as proteins, in live cells. Quantitative measurement of the molecular interactions among Tat, CycT1 and CDK9 has showed that any third molecule enhances the binding between the other two molecules. These findings suggest that each component of the Tat:P-TEFb complex stabilizes the overall complex, thereby supporting the efficient transcriptional elongation during viral RNA synthesis. These interactions may serve as appropriate targets for novel anti-HIV therapy.

  7. Conformational selection in a protein-protein interaction revealed by dynamic pathway analysis

    DOE PAGES

    Chakrabarti, Kalyan S.; Agafonov, Roman V.; Pontiggia, Francesco; ...

    2015-12-24

    Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection) or are caused in response to ligand binding (induced fit). Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsinmore » kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using NMR spectroscopy, stopped-flow kinetics and isothermal titration calorimetry we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Lastly, protein dynamics in free recoverin limits the overall rate of binding.« less

  8. What induces pocket openings on protein surface patches involved in protein-protein interactions?

    NASA Astrophysics Data System (ADS)

    Eyrisch, Susanne; Helms, Volkhard

    2009-02-01

    We previously showed for the proteins BCL-XL, IL-2, and MDM2 that transient pockets at their protein-protein binding interfaces can be identified by applying the PASS algorithm to molecular dynamics (MD) snapshots. We now investigated which aspects of the natural conformational dynamics of proteins induce the formation of such pockets. The pocket detection protocol was applied to three different conformational ensembles for the same proteins that were extracted from MD simulations of the inhibitor bound crystal conformation in water and the free crystal/NMR structure in water and in methanol. Additional MD simulations studied the impact of backbone mobility. The more efficient CONCOORD or normal mode analysis (NMA) techniques gave significantly smaller pockets than MD simulations, whereas tCONCOORD generated pockets comparable to those observed in MD simulations for two of the three systems. Our findings emphasize the influence of solvent polarity and backbone rearrangements on the formation of pockets on protein surfaces and should be helpful in future generation of transient pockets as putative ligand binding sites at protein-protein interfaces.

  9. Conformational selection in a protein-protein interaction revealed by dynamic pathway analysis

    SciTech Connect

    Chakrabarti, Kalyan S.; Agafonov, Roman V.; Pontiggia, Francesco; Otten, Renee; Higgins, Matthew K.; Schertler, Gebhard F. X.; Oprian, Daniel D.; Kern, Dorothee

    2015-12-24

    Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection) or are caused in response to ligand binding (induced fit). Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsin kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using NMR spectroscopy, stopped-flow kinetics and isothermal titration calorimetry we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Lastly, protein dynamics in free recoverin limits the overall rate of binding.

  10. Inhibition of the p53/hDM2 protein-protein interaction by cyclometallated iridium(III) compounds

    PubMed Central

    Liu, Li-Juan; He, Bingyong; Miles, Jennifer A.; Wang, Wanhe; Mao, Zhifeng; Che, Weng Ian; Lu, Jin-Jian; Chen, Xiu-Ping; Wilson, Andrew J.; Ma, Dik-Lung; Leung, Chung-Hang

    2016-01-01

    Inactivation of the p53 transcription factor by mutation or other mechanisms is a frequent event in tumorigenesis. One of the major endogenous negative regulators of p53 in humans is hDM2, a ubiquitin E3 ligase that binds to p53 causing proteasomal p53 degradation. In this work, a library of organometallic iridium(III) compounds were synthesized and evaluated for their ability to disrupt the p53/hDM2 protein-protein interaction. The novel cyclometallated iridium(III) compound 1 [Ir(eppy)2(dcphen)](PF6) (where eppy = 2-(4-ethylphenyl)pyridine and dcphen = 4, 7-dichloro-1, 10-phenanthroline) blocked the interaction of p53/hDM2 in human amelanotic melanoma cells. Finally, 1 exhibited anti-proliferative activity and induced apoptosis in cancer cell lines consistent with inhibition of the p53/hDM2 interaction. Compound 1 represents the first reported organometallic p53/hDM2 protein-protein interaction inhibitor. PMID:26883110

  11. Prediction of protein-protein interactions in dengue virus coat proteins guided by low resolution cryoEM structures

    PubMed Central

    2010-01-01

    Background Dengue virus along with the other members of the flaviviridae family has reemerged as deadly human pathogens. Understanding the mechanistic details of these infections can be highly rewarding in developing effective antivirals. During maturation of the virus inside the host cell, the coat proteins E and M undergo conformational changes, altering the morphology of the viral coat. However, due to low resolution nature of the available 3-D structures of viral assemblies, the atomic details of these changes are still elusive. Results In the present analysis, starting from Cα positions of low resolution cryo electron microscopic structures the residue level details of protein-protein interaction interfaces of dengue virus coat proteins have been predicted. By comparing the preexisting structures of virus in different phases of life cycle, the changes taking place in these predicted protein-protein interaction interfaces were followed as a function of maturation process of the virus. Besides changing the current notion about the presence of only homodimers in the mature viral coat, the present analysis indicated presence of a proline-rich motif at the protein-protein interaction interface of the coat protein. Investigating the conservation status of these seemingly functionally crucial residues across other members of flaviviridae family enabled dissecting common mechanisms used for infections by these viruses. Conclusions Thus, using computational approach the present analysis has provided better insights into the preexisting low resolution structures of virus assemblies, the findings of which can be made use of in designing effective antivirals against these deadly human pathogens. PMID:20550721

  12. Improving protein-protein interaction prediction using evolutionary information from low-quality MSAs

    PubMed Central

    Várnai, Csilla; Burkoff, Nikolas S.; Wild, David L.

    2017-01-01

    Evolutionary information stored in multiple sequence alignments (MSAs) has been used to identify the interaction interface of protein complexes, by measuring either co-conservation or co-mutation of amino acid residues across the interface. Recently, maximum entropy related correlated mutation measures (CMMs) such as direct information, decoupling direct from indirect interactions, have been developed to identify residue pairs interacting across the protein complex interface. These studies have focussed on carefully selected protein complexes with large, good-quality MSAs. In this work, we study protein complexes with a more typical MSA consisting of fewer than 400 sequences, using a set of 79 intramolecular protein complexes. Using a maximum entropy based CMM at the residue level, we develop an interface level CMM score to be used in re-ranking docking decoys. We demonstrate that our interface level CMM score compares favourably to the complementarity trace score, an evolutionary information-based score measuring co-conservation, when combined with the number of interface residues, a knowledge-based potential and the variability score of individual amino acid sites. We also demonstrate, that, since co-mutation and co-complementarity in the MSA contain orthogonal information, the best prediction performance using evolutionary information can be achieved by combining the co-mutation information of the CMM with co-conservation information of a complementarity trace score, predicting a near-native structure as the top prediction for 41% of the dataset. The method presented is not restricted to small MSAs, and will likely improve interface prediction also for complexes with large and good-quality MSAs. PMID:28166227

  13. Photolytic Cross-Linking to Probe Protein-Protein and Protein-Matrix Interactions in Lyophilized Powders.

    PubMed

    Iyer, Lavanya K; Moorthy, Balakrishnan S; Topp, Elizabeth M

    2015-09-08

    Protein structure and local environment in lyophilized formulations were probed using high-resolution solid-state photolytic cross-linking with mass spectrometric analysis (ssPC-MS). In order to characterize structure and microenvironment, protein-protein, protein-excipient, and protein-water interactions in lyophilized powders were identified. Myoglobin (Mb) was derivatized in solution with the heterobifunctional probe succinimidyl 4,4'-azipentanoate (SDA) and the structural integrity of the labeled protein (Mb-SDA) confirmed using CD spectroscopy and liquid chromatography/mass spectrometry (LC-MS). Mb-SDA was then formulated with and without excipients (raffinose, guanidine hydrochloride (Gdn HCl)) and lyophilized. The freeze-dried powder was irradiated with ultraviolet light at 365 nm for 30 min to produce cross-linked adducts that were analyzed at the intact protein level and after trypsin digestion. SDA-labeling produced Mb carrying up to five labels, as detected by LC-MS. Following lyophilization and irradiation, cross-linked peptide-peptide, peptide-water, and peptide-raffinose adducts were detected. The exposure of Mb side chains to the matrix was quantified based on the number of different peptide-peptide, peptide-water, and peptide-excipient adducts detected. In the absence of excipients, peptide-peptide adducts involving the CD, DE, and EF loops and helix H were common. In the raffinose formulation, peptide-peptide adducts were more distributed throughout the molecule. The Gdn HCl formulation showed more protein-protein and protein-water adducts than the other formulations, consistent with protein unfolding and increased matrix interactions. The results demonstrate that ssPC-MS can be used to distinguish excipient effects and characterize the local protein environment in lyophilized formulations with high resolution.

  14. Prediction of protein-protein interactions using chaos game representation and wavelet transform via the random forest algorithm.

    PubMed

    Jia, J H; Liu, Z; Chen, X; Xiao, X; Liu, B X

    2015-10-02

    Studying the network of protein-protein interactions (PPIs) will provide valuable insights into the inner workings of cells. It is vitally important to develop an automated, high-throughput tool that efficiently predicts protein-protein interactions. This study proposes a new model for PPI prediction based on the concept of chaos game representation and the wavelet transform, which means that a considerable amount of sequence-order effects can be incorporated into a set of discrete numbers. The advantage of using chaos game representation and the wavelet transform to formulate the protein sequence is that it can more effectively reflect its overall sequence-order characteristics than the conventional correlation factors. Using such a formulation frame to represent the protein sequences means that the random forest algorithm can be used to conduct the prediction. The results for a large-scale independent test dataset show that the proposed model can achieve an excellent performance with an accuracy value of about 0.86 and a geometry mean value of about 0.85. The model is therefore a useful supplementary tool for PPI predictions. The predictor used in this article is freely available at http://www.jci-bioinfo.cn/PPI.

  15. Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors.

    PubMed

    Sable, Rushikesh; Jois, Seetharama

    2015-06-23

    Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers.

  16. Prediction of protein-protein interaction sites from weakly homologous template structures using meta-threading and machine learning.

    PubMed

    Maheshwari, Surabhi; Brylinski, Michal

    2015-01-01

    The identification of protein-protein interactions is vital for understanding protein function, elucidating interaction mechanisms, and for practical applications in drug discovery. With the exponentially growing protein sequence data, fully automated computational methods that predict interactions between proteins are becoming essential components of system-level function inference. A thorough analysis of protein complex structures demonstrated that binding site locations as well as the interfacial geometry are highly conserved across evolutionarily related proteins. Because the conformational space of protein-protein interactions is highly covered by experimental structures, sensitive protein threading techniques can be used to identify suitable templates for the accurate prediction of interfacial residues. Toward this goal, we developed eFindSite(PPI) , an algorithm that uses the three-dimensional structure of a target protein, evolutionarily remotely related templates and machine learning techniques to predict binding residues. Using crystal structures, the average sensitivity (specificity) of eFindSite(PPI) in interfacial residue prediction is 0.46 (0.92). For weakly homologous protein models, these values only slightly decrease to 0.40-0.43 (0.91-0.92) demonstrating that eFindSite(PPI) performs well not only using experimental data but also tolerates structural imperfections in computer-generated structures. In addition, eFindSite(PPI) detects specific molecular interactions at the interface; for instance, it correctly predicts approximately one half of hydrogen bonds and aromatic interactions, as well as one third of salt bridges and hydrophobic contacts. Comparative benchmarks against several dimer datasets show that eFindSite(PPI) outperforms other methods for protein-binding residue prediction. It also features a carefully tuned confidence estimation system, which is particularly useful in large-scale applications using raw genomic data. eFindSite(PPI) is

  17. Toponomics: studying protein-protein interactions and protein networks in intact tissue.

    PubMed

    Pierre, Sandra; Scholich, Klaus

    2010-04-01

    The function of a protein is determined on several levels including the genome, transcriptome, proteome, and the recently introduced toponome. The toponome describes the topology of all proteins, protein complexes and protein networks which constitute and influence the microenvironment of a given protein. It has long been known that cellular function or dysfunction of proteins strongly depends on their microenvironment and even small changes in protein arrangements can dramatically alter their activity/function. Thus, deciphering the topology of the multi-dimensional networks which control normal and disease-related pathways will give a better understanding of the mechanisms underlying disease development. While various powerful proteomic tools allow simultaneous quantification of proteins, only a limited number of techniques are available to visualize protein networks in intact cells and tissues. This review discusses a novel approach to map and decipher functional molecular networks of proteins in intact cells or tissues. Multi-epitope-ligand-cartography (MELC) is an imaging technology that identifies and quantifies protein networks at the subcellular level of morphologically-intact specimens. This immunohistochemistry-based method allows serial visualization and biomathematical analysis of up to 100 cellular components using fluorescence-labelled tags. The resulting toponome maps, simultaneously ranging from the subcellular to the supracellular scale, have the potential to provide the basis for a mathematical description of the dynamic topology of protein networks, and will complement current proteomic data to enhance the understanding of physiological and pathophysiological cell functions.

  18. Consequences of inducing intrinsic disorder in a high-affinity protein-protein interaction.

    PubMed

    Papadakos, Grigorios; Sharma, Amit; Lancaster, Lorna E; Bowen, Rebecca; Kaminska, Renata; Leech, Andrew P; Walker, Daniel; Redfield, Christina; Kleanthous, Colin

    2015-04-29

    The kinetic and thermodynamic consequences of intrinsic disorder in protein-protein recognition are controversial. We address this by inducing one partner of the high-affinity colicin E3 rRNase domain-Im3 complex (K(d) ≈ 10(-12) M) to become an intrinsically disordered protein (IDP). Through a variety of biophysical measurements, we show that a single alanine mutation at Tyr507 within the hydrophobic core of the isolated colicin E3 rRNase domain causes the enzyme to become an IDP (E3 rRNase(IDP)). E3 rRNase(IDP) binds stoichiometrically to Im3 and forms a structure that is essentially identical to the wild-type complex. However, binding of E3 rRNase(IDP) to Im3 is 4 orders of magnitude weaker than that of the folded rRNase, with thermodynamic parameters reflecting the disorder-to-order transition on forming the complex. Critically, pre-steady-state kinetic analysis of the E3 rRNase(IDP)-Im3 complex demonstrates that the decrease in affinity is mostly accounted for by a drop in the electrostatically steered association rate. Our study shows that, notwithstanding the advantages intrinsic disorder brings to biological systems, this can come at severe kinetic and thermodynamic cost.

  19. An integrative C. elegans protein-protein interaction network with reliability assessment based on a probabilistic graphical model.

    PubMed

    Huang, Xiao-Tai; Zhu, Yuan; Chan, Leanne Lai Hang; Zhao, Zhongying; Yan, Hong

    2016-01-01

    In Caenorhabditis elegans, a large number of protein-protein interactions (PPIs) are identified by different experiments. However, a comprehensive weighted PPI network, which is essential for signaling pathway inference, is not yet available in this model organism. Therefore, we firstly construct an integrative PPI network in C. elegans with 12,951 interactions involving 5039 proteins from seven molecular interaction databases. Then, a reliability score based on a probabilistic graphical model (RSPGM) is proposed to assess PPIs. It assumes that the random number of interactions between two proteins comes from the Bernoulli distribution to avoid multi-links. The main parameter of the RSPGM score contains a few latent variables which can be considered as several common properties between two proteins. Validations on high-confidence yeast datasets show that RSPGM provides more accurate evaluation than other approaches, and the PPIs in the reconstructed PPI network have higher biological relevance than that in the original network in terms of gene ontology, gene expression, essentiality and the prediction of known protein complexes. Furthermore, this weighted integrative PPI network in C. elegans is employed on inferring interaction path of the canonical Wnt/β-catenin pathway as well. Most genes on the inferred interaction path have been validated to be Wnt pathway components. Therefore, RSPGM is essential and effective for evaluating PPIs and inferring interaction path. Finally, the PPI network with RSPGM scores can be queried and visualized on a user interactive website, which is freely available at .

  20. Time-domain fluorescence lifetime imaging microscopy: a quantitative method to follow transient protein-protein interactions in living cells.

    PubMed

    Padilla-Parra, Sergi; Audugé, Nicolas; Tramier, Marc; Coppey-Moisan, Maïté

    2015-06-01

    Quantitative analysis in Förster resonance energy transfer (FRET) imaging studies of protein-protein interactions within live cells is still a challenging issue. Many cellular biology applications aim at the determination of the space and time variations of the relative amount of interacting fluorescently tagged proteins occurring in cells. This relevant quantitative parameter can be, at least partially, obtained at a pixel-level resolution by using fluorescence lifetime imaging microscopy (FLIM). Indeed, fluorescence decay analysis of a two-component system (FRET and no FRET donor species), leads to the intrinsic FRET efficiency value (E) and the fraction of the donor-tagged protein that undergoes FRET (fD). To simultaneously obtain fD and E values from a two-exponential fit, data must be acquired with a high number of photons, so that the statistics are robust enough to reduce fitting ambiguities. This is a time-consuming procedure. However, when fast-FLIM acquisitions are used to monitor dynamic changes in protein-protein interactions at high spatial and temporal resolutions in living cells, photon statistics and time resolution are limited. In this case, fitting procedures are unreliable, even for single lifetime donors. We introduce the concept of a minimal fraction of donor molecules involved in FRET (mfD), obtained from the mathematical minimization of fD. Here, we discuss different FLIM techniques and the compromises that must be made between precision and time invested in acquiring FLIM measurements. We show that mfD constitutes an interesting quantitative parameter for fast FLIM because it gives quantitative information about transient interactions in live cells.

  1. Detection of Protein-Protein Interaction Within an RNA-Protein Complex Via Unnatural-Amino-Acid-Mediated Photochemical Crosslinking.

    PubMed

    Yeh, Fu-Lung; Tung, Luh; Chang, Tien-Hsien

    2016-01-01

    Although DExD/H-box proteins are known to unwind RNA duplexes and modulate RNA structures in vitro, it is highly plausible that, in vivo, some may function to remodel RNA-protein complexes. Precisely how the latter is achieved remains a mystery. We investigated this critical issue by using yeast Prp28p, an evolutionarily conserved DExD/H-box splicing factor, as a model system. To probe how Prp28p interacts with spliceosome, we strategically placed p-benzoyl-phenylalanine (BPA), a photoactivatable unnatural amino acid, along the body of Prp28p in vivo. Extracts prepared from these engineered strains were then used to assemble in vitro splicing reactions for BPA-mediated protein-protein crosslinkings. This enabled us, for the first time, to "capture" Prp28p in action. This approach may be applicable to studying the roles of other DExD/H-box proteins functioning in diverse RNA-related pathways, as well as to investigating protein-protein contacts within an RNA-protein complex.

  2. Bioluminescence methodology for the detection of protein-protein interactions within the voltage-gated sodium channel macromolecular complex.

    PubMed

    Shavkunov, Alexander; Panova, Neli; Prasai, Anesh; Veselenak, Ron; Bourne, Nigel; Stoilova-McPhie, Svetla; Laezza, Fernanda

    2012-04-01

    Protein-protein interactions are critical molecular determinants of ion channel function and emerging targets for pharmacological interventions. Yet, current methodologies for the rapid detection of ion channel macromolecular complexes are still lacking. In this study we have adapted a split-luciferase complementation assay (LCA) for detecting the assembly of the voltage-gated Na+ (Nav) channel C-tail and the intracellular fibroblast growth factor 14 (FGF14), a functionally relevant component of the Nav channelosome that controls gating and targeting of Nav channels through direct interaction with the channel C-tail. In the LCA, two complementary N-terminus and C-terminus fragments of the firefly luciferase were fused, respectively, to a chimera of the CD4 transmembrane segment and the C-tail of Nav1.6 channel (CD4-Nav1.6-NLuc) or FGF14 (CLuc-FGF14). Co-expression of CLuc-FGF14 and CD4-Nav1.6-NLuc in live cells led to a robust assembly of the FGF14:Nav1.6 C-tail complex, which was attenuated by introducing single-point mutations at the predicted FGF14:Nav channel interface. To evaluate the dynamic regulation of the FGF14:Nav1.6 C-tail complex by signaling pathways, we investigated the effect of kinase inhibitors on the complex formation. Through a platform of counter screenings, we show that the p38/MAPK inhibitor, PD169316, and the IκB kinase inhibitor, BAY 11-7082, reduce the FGF14:Nav1.6 C-tail complementation, highlighting a potential role of the p38MAPK and the IκB/NFκB pathways in controlling neuronal excitability through protein-protein interactions. We envision the methodology presented here as a new valuable tool to allow functional evaluations of protein-channel complexes toward probe development and drug discovery targeting ion channels implicated in human disorders.

  3. Protein-protein interactions involving voltage-gated sodium channels: Post-translational regulation, intracellular trafficking and functional expression.

    PubMed

    Shao, Dongmin; Okuse, Kenji; Djamgoz, Mustafa B A

    2009-07-01

    Voltage-gated sodium channels (VGSCs), classically known to play a central role in excitability and signalling in nerves and muscles, have also been found to be expressed in a range of 'non-excitable' cells, including lymphocytes, fibroblasts and endothelia. VGSC abnormalities are associated with various diseases including epilepsy, long-QT syndrome 3, Brugada syndrome, sudden infant death syndrome and, more recently, various human cancers. Given their pivotal role in a wide range of physiological and pathophysiological processes, regulation of functional VGSC expression has been the subject of intense study. An emerging theme is post-translational regulation and macro-molecular complexing by protein-protein interactions and intracellular trafficking, leading to changes in functional VGSC expression in plasma membrane. This partially involves endoplasmic reticulum associated degradation and ubiquitin-proteasome system. Several proteins have been shown to associate with VGSCs. Here, we review the interactions involving VGSCs and the following proteins: p11, ankyrin, syntrophin, beta-subunit of VGSC, papin, ERM and Nedd4 proteins. Protein kinases A and C, as well as Ca(2+)-calmodulin dependent kinase II that have also been shown to regulate intracellular trafficking of VGSCs by changing the balance of externalization vs. internalization, and an effort is made to separate these effects from the short-term phosphorylation of mature proteins in plasma membrane. Two further modulatory mechanisms are reciprocal interactions with the cytoskeleton and, late-stage, activity-dependent regulation. Thus, the review gives an updated account of the range of post-translational molecular mechanisms regulating functional VGSC expression. However, many details of VGSC subtype-specific regulation and pathophysiological aspects remain unknown and these are highlighted throughout for completeness.

  4. Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

    PubMed Central

    Doktycz, M. J.; Qi, H.; Morrell-Falvey, J. L.

    2006-01-01

    The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction. Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors. PMID:23165043

  5. Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

    DOE PAGES

    Venkatraman, S.; Doktycz, M. J.; Qi, H.; ...

    2006-01-01

    The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction.more » Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors.« less

  6. Integrating structure to protein-protein interaction networks that drive metastasis to brain and lung in breast cancer.

    PubMed

    Engin, H Billur; Guney, Emre; Keskin, Ozlem; Oliva, Baldo; Gursoy, Attila

    2013-01-01

    Blocking specific protein interactions can lead to human diseases. Accordingly, protein interactions and the structural knowledge on interacting surfaces of proteins (interfaces) have an important role in predicting the genotype-phenotype relationship. We have built the phenotype specific sub-networks of protein-protein interactions (PPIs) involving the relevant genes responsible for lung and brain metastasis from primary tumor in breast cancer. First, we selected the PPIs most relevant to metastasis causing genes (seed genes), by using the "guilt-by-association" principle. Then, we modeled structures of the interactions whose complex forms are not available in Protein Databank (PDB). Finally, we mapped mutations to interface structures (real and modeled), in order to spot the interactions that might be manipulated by these mutations. Functional analyses performed on these sub-networks revealed the potential relationship between immune system-infectious diseases and lung metastasis progression, but this connection was not observed significantly in the brain metastasis. Besides, structural analyses showed that some PPI interfaces in both metastasis sub-networks are originating from microbial proteins, which in turn were mostly related with cell adhesion. Cell adhesion is a key mechanism in metastasis, therefore these PPIs may be involved in similar molecular pathways that are shared by infectious disease and metastasis. Finally, by mapping the mutations and amino acid variations on the interface regions of the proteins in the metastasis sub-networks we found evidence for some mutations to be involved in the mechanisms differentiating the type of the metastasis.

  7. Protein-protein interaction network prediction by using rigid-body docking tools: application to bacterial chemotaxis.

    PubMed

    Matsuzaki, Yuri; Ohue, Masahito; Uchikoga, Nobuyuki; Akiyama, Yutaka

    2014-01-01

    Core elements of cell regulation are made up of protein-protein interaction (PPI) networks. However, many parts of the cell regulatory systems include unknown PPIs. To approach this problem, we have developed a computational method of high-throughput PPI network prediction based on all-to-all rigid-body docking of protein tertiary structures. The prediction system accepts a set of data comprising protein tertiary structures as input and generates a list of possible interacting pairs from all the combinations as output. A crucial advantage of this docking based method is in providing predictions of protein pairs that increases our understanding of biological pathways by analyzing the structures of candidate complex structures, which gives insight into novel interaction mechanisms. Although such exhaustive docking calculation requires massive computational resources, recent advancements in the computational sciences have made such large-scale calculations feasible. In this study we applied our prediction method to a pathway reconstruction problem of bacterial chemotaxis by using two different rigid-body docking tools with different scoring models. We found that the predicted interactions were different between the results from the two tools. When the positive predictions from both of the docking tools were combined, all the core signaling interactions were correctly predicted with the exception of interactions activated by protein phosphorylation. Large-scale PPI prediction using tertiary structures is an effective approach that has a wide range of potential applications. This method is especially useful for identifying novel PPIs of new pathways that control cellular behavior.

  8. Bimolecular fluorescence complementation (BiFC) assay for protein-protein interaction in onion cells using the helios gene gun.

    PubMed

    Hollender, Courtney A; Liu, Zhongchi

    2010-06-12

    Investigation of gene function in diverse organisms relies on knowledge of how the gene products interact with each other in their normal cellular environment. The Bimolecular Fluorescence Complementation (BiFC) Assay(1) allows researchers to visualize protein-protein interactions in living cells and has become an essential research tool. This assay is based on the facilitated association of two fragments of a fluorescent protein (GFP) that are each fused to a potential interacting protein partner. The interaction of the two protein partners would facilitate the association of the N-terminal and C-terminal fragment of GFP, leading to fluorescence. For plant researchers, onion epidermal cells are an ideal experimental system for conducting the BiFC assay because of the ease in obtaining and preparing onion tissues and the direct visualization of fluorescence with minimal background fluorescence. The Helios Gene Gun (BioRad) is commonly used for bombarding plasmid DNA into onion cells. We demonstrate the use of Helios Gene Gun to introduce plasmid constructs for two interacting Arabidopsis thaliana transcription factors, SEUSS (SEU) and LEUNIG HOMOLOG (LUH)(2) and the visualization of their interactions mediated by BiFC in onion epidermal cells.

  9. In silico and experimental validation of protein-protein interactions between PknI and Rv2159c from Mycobacterium tuberculosis.

    PubMed

    Venkatesan, Arunkumar; Hassan, Sameer; Palaniyandi, Kannan; Narayanan, Sujatha

    2015-11-01

    Protein-protein interactions control the diverse and essential molecular processes inside the cell. To maintain the cellular physiology, protein kinases not only signal their substrates through reversible phosphorylation, but they also physically interact with them. PknI, a serine/threonine protein kinase of Mycobacterium tuberculosis is known to be important for cellular homoeostasis. In this study, we have identified the interacting proteins for PknI. We screened for proteins interacting with PknI using an in vitro assay, Far-western blot. This protein kinase specifically interacts with two peroxidase proteins of M. tuberculosis, Rv2159c and Rv0148. The PknI-Rv2159c interaction pair was further studied for the critical amino acid residues in Rv2159c that are responsible for the interaction. Rv2159c, a hypothetical protein is predicted to be an antioxidant with peroxidase activity. We performed homology modelling of Rv2159c protein and molecular docking using multiple docking servers such as Z-Dock and ClusPro. Further, the most favorable conformation of PknI-Rv2159c interaction was obtained using molecular dynamics simulation. The critical amino acid residues of the Rv2159c involved in interaction with PknI were identified. Mutation and docking analysis showed that the Ala1-Gly2-Trp3 residues in Rv2159c structure are responsible for the interaction. The free binding energy between the wild type and mutant complexes using MM-GBSA has provided insight about the stability of PknI-Rv2159c interaction. We propose that, PknI physically interacts with Rv2159c both in vitro and in silico studies.

  10. MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform.

    PubMed

    Gupta, Surya; De Puysseleyr, Veronic; Van der Heyden, José; Maddelein, Davy; Lemmens, Irma; Lievens, Sam; Degroeve, Sven; Tavernier, Jan; Martens, Lennart

    2017-01-18

    Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction- Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments.

  11. Categorizing Biases in High-Confidence High-Throughput Protein-Protein Interaction Data Sets

    DTIC Science & Technology

    2011-01-01

    interaction data sets derived from affinity purification/mass spec- trometry, protein-fragment complementation assay, and yeast two-hybrid experiments . The...characteristics. These differences were primarily a func- tion of the deployed experimental technologies used to recover these interactions. This affected the total...the protein interaction data within their experimental or cellular con- text provided the best avenue for overcoming biases and inferring biological

  12. Community-wide Evaluation of Methods for Predicting the Effect of Mutations on Protein-Protein Interactions

    PubMed Central

    Moretti, Rocco; Fleishman, Sarel J.; Agius, Rudi; Torchala, Mieczyslaw; Bates, Paul A.; Kastritis, Panagiotis L.; Rodrigues, João P. G. L. M.; Trellet, Mikaël; Bonvin, Alexandre M. J. J.; Cui, Meng; Rooman, Marianne; Gillis, Dimitri; Dehouck, Yves; Moal, Iain; Romero-Durana, Miguel; Perez-Cano, Laura; Pallara, Chiara; Jimenez, Brian; Fernandez-Recio, Juan; Flores, Samuel; Pacella, Michael; Kilambi, Krishna Praneeth; Gray, Jeffrey J.; Popov, Petr; Grudinin, Sergei; Esquivel-Rodríguez, Juan; Kihara, Daisuke; Zhao, Nan; Korkin, Dmitry; Zhu, Xiaolei; Demerdash, Omar N. A.; Mitchell, Julie C.; Kanamori, Eiji; Tsuchiya, Yuko; Nakamura, Haruki; Lee, Hasup; Park, Hahnbeom; Seok, Chaok; Sarmiento, Jamica; Liang, Shide; Teraguchi, Shusuke; Standley, Daron M.; Shimoyama, Hiromitsu; Terashi, Genki; Takeda-Shitaka, Mayuko; Iwadate, Mitsuo; Umeyama, Hideaki; Beglov, Dmitri; Hall, David R.; Kozakov, Dima; Vajda, Sandor; Pierce, Brian G.; Hwang, Howook; Vreven, Thom; Weng, Zhiping; Huang, Yangyu; Li, Haotian; Yang, Xiufeng; Ji, Xiaofeng; Liu, Shiyong; Xiao, Yi; Zacharias, Martin; Qin, Sanbo; Zhou, Huan-Xiang; Huang, Sheng-You; Zou, Xiaoqin; Velankar, Sameer; Janin, Joël; Wodak, Shoshana J.; Baker, David

    2014-01-01

    Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side chain sampling and backbone relaxation, and evaluated packing, electrostatic and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of methodological improvement. PMID:23843247

  13. Förster resonance energy transfer microscopy and spectroscopy for localizing protein-protein interactions in living cells

    PubMed Central

    Sun, Yuansheng; Rombola, Christina; Jyothikumar, Vinod; Periasamy, Ammasi

    2014-01-01

    The fundamental theory of Förster resonance energy transfer (FRET) was established in the 1940's. Its great power was only realized in the past 20 years after different techniques were developed and applied to biological experiments. This success was made possible by the availability of suitable fluorescent probes, advanced optics, detectors, microscopy instrumentation and analytical tools. Combined with state-of-the-art microscopy and spectroscopy, FRET imaging allows scientists to study a variety of phenomena that produce changes in molecular proximity, thereby leading to many significant findings in the life sciences. In this review, we outline various FRET imaging techniques and their strengths and limitations; we also provide a biological model to demonstrate how to investigate protein-protein interactions in living cells using both intensity- and fluorescence lifetime-based FRET microscopy methods. PMID:23813736

  14. Predicting protein-protein interactions from multimodal biological data sources via nonnegative matrix tri-factorization.

    PubMed

    Wang, Hua; Huang, Heng; Ding, Chris; Nie, Feiping

    2013-04-01

    Protein interactions are central to all the biological processes and structural scaffolds in living organisms, because they orchestrate a number of cellular processes such as metabolic pathways and immunological recognition. Several high-throughput methods, for example, yeast two-hybrid system and mass spectrometry method, can help determine protein interactions, which, however, suffer from high false-positive rates. Moreover, many protein interactions predicted by one method are not supported by another. Therefore, computational methods are necessary and crucial to complete the interactome expeditiously. In this work, we formulate the problem of predicting protein interactions from a new mathematical perspective--sparse matrix completion, and propose a novel nonnegative matrix factorization (NMF)-based matrix completion approach to predict new protein interactions from existing protein interaction networks. Through using manifold regularization, we further develop our method to integrate different biological data sources, such as protein sequences, gene expressions, protein structure information, etc. Extensive experimental results on four species, Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, and Caenorhabditis elegans, have shown that our new methods outperform related state-of-the-art protein interaction prediction methods.

  15. Beyond hairballs: the use of quantitative mass spectrometry data to understand protein-protein interactions

    PubMed Central

    Gingras, Anne-Claude; Raught, Brian

    2012-01-01

    The past 10 years have witnessed a dramatic proliferation in the availability of protein interaction data. However, for interaction mapping based on affinity purification coupled with mass spectrometry (AP-MS), there is a wealth of information present in the datasets that often goes unrecorded in public repositories, and as such remains largely unexplored. Further, how this type of data is represented and used by bioinformaticians has not been well established. Here, we point out some common mistakes in how AP-MS data are handled, and describe how protein complex organization and interaction dynamics can be inferred using quantitative AP-MS approaches. PMID:22710165

  16. Protein-protein interactions of tandem affinity purification-tagged protein kinases in rice.

    PubMed

    Rohila, Jai S; Chen, Mei; Chen, Shuo; Chen, Johann; Cerny, Ronald; Dardick, Chris; Canlas, Patrick; Xu, Xia; Gribskov, Michael; Kanrar, Siddhartha; Zhu, Jian-Kang; Ronald, Pamela; Fromm, Michael E

    2006-04-01

    Forty-one rice cDNAs encoding protein kinases were fused to the tandem affinity purification (TAP) tag and expressed in transgenic rice plants. The TAP-tagged kinases and interacting proteins were purified from the T1 progeny of the transgenic rice plants and identified by mass spectrometry. Ninety-five percent of the TAP-tagged kinases were recovered. Fifty-six percent of the TAP-tagged kinases were found to interact with other rice proteins. A number of these interactions were consistent with known protein complexes found in other species, validating the TAP-tag method in rice plants. Phosphorylation sites were identified on four of the kinases that interacted with either 14-3-3 proteins or cyclins.

  17. Tissue-Specific Molecular Biomarker Signatures of Type 2 Diabetes: An Integrative Analysis of Transcriptomics and Protein-Protein Interaction Data.

    PubMed

    Calimlioglu, Beste; Karagoz, Kubra; Sevimoglu, Tuba; Kilic, Elif; Gov, Esra; Arga, Kazim Yalcin

    2015-09-01

    Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a "systems medicine" approach to biomarker and novel diagnostic discovery, not to mention data integration across omics-es. In the present study, transcriptomics data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with protein-protein interaction data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active protein-protein interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common signature at genome level, and activation-ppara reaction, which stimulates a nuclear receptor protein, was found out as the mutual reporter at metabolic level. Moreover, miR-335 and miR-16-5p came into prominence in regulation of transcription at different tissues. On the other hand, distinct signatures were observed for different tissues at the metabolome level. Various coenzyme-A derivatives were significantly enriched metabolites in pancreatic islets, whereas skeletal muscle was enriched for cholesterol, malate, L-carnitine, and several amino acids. Results have showed utmost importance concerning relations between T2D and cancer, blood coagulation, neurodegenerative diseases, and specific metabolic and signaling pathways.

  18. Characterization of domain-peptide interaction interface: prediction of SH3 domain-mediated protein-protein interaction network in yeast by generic structure-based models.

    PubMed

    Hou, Tingjun; Li, Nan; Li, Youyong; Wang, Wei

    2012-05-04

    Determination of the binding specificity of SH3 domain, a peptide recognition module (PRM), is important to understand their biological functions and reconstruct the SH3-mediated protein-protein interaction network. In the present study, the SH3-peptide interactions for both class I and II SH3 domains were characterized by the intermolecular residue-residue interaction network. We developed generic MIEC-SVM models to infer SH3 domain-peptide recognition specificity that achieved satisfactory prediction accuracy. By investigating the domain-peptide recognition mechanisms at the residue level, we found that the class-I and class-II binding peptides have different binding modes even though they occupy the same binding site of SH3. Furthermore, we predicted the potential binding partners of SH3 domains in the yeast proteome and constructed the SH3-mediated protein-protein interaction network. Comparison with the experimentally determined interactions confirmed the effectiveness of our approach. This study showed that our sophisticated computational approach not only provides a powerful platform to decipher protein recognition code at the molecular level but also allows identification of peptide-mediated protein interactions at a proteomic scale. We believe that such an approach is general to be applicable to other domain-peptide interactions.

  19. Kinetic Measurements Reveal Enhanced Protein-Protein Interactions at Intercellular Junctions

    PubMed Central

    Shashikanth, Nitesh; Kisting, Meridith A.; Leckband, Deborah E.

    2016-01-01

    The binding properties of adhesion proteins are typically quantified from measurements with soluble fragments, under conditions that differ radically from the confined microenvironment of membrane bound proteins in adhesion zones. Using classical cadherin as a model adhesion protein, we tested the postulate that confinement within quasi two-dimensional intercellular gaps exposes weak protein interactions that are not detected in solution binding assays. Micropipette-based measurements of cadherin-mediated, cell-cell binding kinetics identified a unique kinetic signature that reflects both adhesive (trans) bonds between cadherins on opposing cells and lateral (cis) interactions between cadherins on the same cell. In solution, proposed lateral interactions were not detected, even at high cadherin concentrations. Mutations postulated to disrupt lateral cadherin association altered the kinetic signatures, but did not affect the adhesive (trans) binding affinity. Perturbed kinetics further coincided with altered cadherin distributions at junctions, wound healing dynamics, and paracellular permeability. Intercellular binding kinetics thus revealed cadherin interactions that occur within confined, intermembrane gaps but not in solution. Findings further demonstrate the impact of these revealed interactions on the organization and function of intercellular junctions. PMID:27009566

  20. Protein-protein interactions of tandem affinity purified protein kinases from rice.

    PubMed

    Rohila, Jai S; Chen, Mei; Chen, Shuo; Chen, Johann; Cerny, Ronald L; Dardick, Christopher; Canlas, Patrick; Fujii, Hiroaki; Gribskov, Michael; Kanrar, Siddhartha; Knoflicek, Lucas; Stevenson, Becky; Xie, Mingtang; Xu, Xia; Zheng, Xianwu; Zhu, Jian-Kang; Ronald, Pamela; Fromm, Michael E

    2009-08-19

    Eighty-eight rice (Oryza sativa) cDNAs encoding rice leaf expressed protein kinases (PKs) were fused to a Tandem Affinity Purification tag (TAP-tag) and expressed in transgenic rice plants. The TAP-tagged PKs and interacting proteins were purified from the T1 progeny of the transgenic rice plants and identified by tandem mass spectrometry. Forty-five TAP-tagged PKs were recovered in this study and thirteen of these were found to interact with other rice proteins with a high probability score. In vivo phosphorylated sites were found for three of the PKs. A comparison of the TAP-tagged data from a combined analysis of 129 TAP-tagged rice protein kinases with a concurrent screen using yeast two hybrid methods identified an evolutionarily new rice protein that interacts with the well conserved cell division cycle 2 (CDC2) protein complex.

  1. Protein-Protein Interactions of Tandem Affinity Purified Protein Kinases from Rice

    PubMed Central

    Rohila, Jai S.; Chen, Mei; Chen, Shuo; Chen, Johann; Cerny, Ronald L.; Dardick, Christopher; Canlas, Patrick; Fujii, Hiroaki; Gribskov, Michael; Kanrar, Siddhartha; Knoflicek, Lucas; Stevenson, Becky; Xie, Mingtang; Xu, Xia; Zheng, Xianwu; Zhu, Jian-Kang; Ronald, Pamela; Fromm, Michael E.

    2009-01-01

    Eighty-eight rice (Oryza sativa) cDNAs encoding rice leaf expressed protein kinases (PKs) were fused to a Tandem Affinity Purification tag (TAP-tag) and expressed in transgenic rice plants. The TAP-tagged PKs and interacting proteins were purified from the T1 progeny of the transgenic rice plants and identified by tandem mass spectrometry. Forty-five TAP-tagged PKs were recovered in this study and thirteen of these were found to interact with other rice proteins with a high probability score. In vivo phosphorylated sites were found for three of the PKs. A comparison of the TAP-tagged data from a combined analysis of 129 TAP-tagged rice protein kinases with a concurrent screen using yeast two hybrid methods identified an evolutionarily new rice protein that interacts with the well conserved cell division cycle 2 (CDC2) protein complex. PMID:19690613

  2. Inhibition of CDC25B Phosphatase Through Disruption of Protein-Protein Interaction

    SciTech Connect

    Lund, George; Dudkin, Sergii; Borkin, Dmitry; Ni, Wendi; Grembecka, Jolanta; Cierpicki, Tomasz

    2015-04-29

    CDC25 phosphatases are key cell cycle regulators and represent very attractive but challenging targets for anticancer drug discovery. Here, we explored whether fragment-based screening represents a valid approach to identify inhibitors of CDC25B. This resulted in identification of 2-fluoro-4-hydroxybenzonitrile, which directly binds to the catalytic domain of CDC25B. Interestingly, NMR data and the crystal structure demonstrate that this compound binds to the pocket distant from the active site and adjacent to the protein–protein interaction interface with CDK2/Cyclin A substrate. Furthermore, we developed a more potent analogue that disrupts CDC25B interaction with CDK2/Cyclin A and inhibits dephosphorylation of CDK2. Based on these studies, we provide a proof of concept that targeting CDC25 phosphatases by inhibiting their protein–protein interactions with CDK2/Cyclin A substrate represents a novel, viable opportunity to target this important class of enzymes.

  3. Protein function prediction using neighbor relativity in protein-protein interaction network.

    PubMed

    Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

    2013-04-01

    There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network.

  4. The Role of Protein-Protein and Protein-Membrane Interactions on P450 Function

    PubMed Central

    Scott, Emily E.; Wolf, C. Roland; Otyepka, Michal; Humphreys, Sara C.; Reed, James R.; Henderson, Colin J.; McLaughlin, Lesley A.; Paloncýová, Markéta; Navrátilová, Veronika; Berka, Karel; Anzenbacher, Pavel; Dahal, Upendra P.; Barnaba, Carlo; Brozik, James A.; Jones, Jeffrey P.; Estrada, D. Fernando; Laurence, Jennifer S.; Park, Ji Won

    2016-01-01

    This symposium summary, sponsored by the ASPET, was held at Experimental Biology 2015 on March 29, 2015, in Boston, Massachusetts. The symposium focused on: 1) the interactions of cytochrome P450s (P450s) with their redox partners; and 2) the role of the lipid membrane in their orientation and stabilization. Two presentations discussed the interactions of P450s with NADPH-P450 reductase (CPR) and cytochrome b5. First, solution nuclear magnetic resonance was used to compare the protein interactions that facilitated either the hydroxylase or lyase activities of CYP17A1. The lyase interaction was stimulated by the presence of b5 and 17α-hydroxypregnenolone, whereas the hydroxylase reaction was predominant in the absence of b5. The role of b5 was also shown in vivo by selective hepatic knockout of b5 from mice expressing CYP3A4 and CYP2D6; the lack of b5 caused a decrease in the clearance of several substrates. The role of the membrane on P450 orientation was examined using computational methods, showing that the proximal region of the P450 molecule faced the aqueous phase. The distal region, containing the substrate-access channel, was associated with the membrane. The interaction of NADPH-P450 reductase (CPR) with the membrane was also described, showing the ability of CPR to “helicopter” above the membrane. Finally, the endoplasmic reticulum (ER) was shown to be heterogeneous, having ordered membrane regions containing cholesterol and more disordered regions. Interestingly, two closely related P450s, CYP1A1 and CYP1A2, resided in different regions of the ER. The structural characteristics of their localization were examined. These studies emphasize the importance of P450 protein organization to their function. PMID:26851242

  5. Using the Gene Ontology tool to produce de novo protein-protein interaction networks with IS_A relationship.

    PubMed

    Oliveira, G S; Santos, A R

    2016-12-19

    Since the first assembled genomes, gene sequences alone have not been sufficient to understand complex metabolic processes involving several genes, each playing distinct roles. To identify their roles, a network of interactions, wherein each gene is a node, should be created. Edges connecting nodes are evidence of interaction, for instance, of gene products coexisting in the same cellular component. Such interaction networks are called protein-protein interactions (PPIs). After genome assembling, PPI mapping is used to predict the possibility of proteins interacting with other proteins based on literature evidence and several databases, thus enriching genome annotations. Identifying PPIs involves analyzing each possible protein pair for a set of features, for instance, participation in the same biological process and having the same function and status in a cellular component. Here, we investigated using the three categories of the Gene Ontology (GO) database for efficient PPI prediction, because it provides data about the three features exemplified here. For a broader conclusion, we investigated the genomes of ten different human pathogens, looking for commonality regarding the GO hierarchical relationship-denominated IS_A. The plasmids were examined separately from their main genomes. Protein pairs sharing at least one IS_A value were considered as interacting proteins. STRING results certified the probed interactions as sensitivity (score >0.75) and specificity (score <0.25) analysis. The average areas under the receiver operating characteristic curve for all organisms were 0.66 and 0.53 for their genomes and plasmids, respectively. Thus, GO categories alone could not potentially provide reliable PPI prediction. However, using additional features can improve predictions.

  6. Identification of Protein-Protein Interactions via a Novel Matrix-Based Sequence Representation Model with Amino Acid Contact Information.

    PubMed

    Ding, Yijie; Tang, Jijun; Guo, Fei

    2016-09-24

    Identification of protein-protein interactions (PPIs) is a difficult and important problem in biology. Since experimental methods for predicting PPIs are both expensive and time-consuming, many computational methods have been developed to predict PPIs and interaction networks, which can be used to complement experimental approaches. However, these methods have limitations to overcome. They need a large number of homology proteins or literature to be applied in their method. In this paper, we propose a novel matrix-based protein sequence representation approach to predict PPIs, using an ensemble learning method for classification. We construct the matrix of Amino Acid Contact (AAC), based on the statistical analysis of residue-pairing frequencies in a database of 6323 protein-protein complexes. We first represent the protein sequence as a Substitution Matrix Representation (SMR) matrix. Then, the feature vector is extracted by applying algorithms of Histogram of Oriented Gradient (HOG) and Singular Value Decomposition (SVD) on the SMR matrix. Finally, we feed the feature vector into a Random Forest (RF) for judging interaction pairs and non-interaction pairs. Our method is applied to several PPI datasets to evaluate its performance. On the S . c e r e v i s i a e dataset, our method achieves 94 . 83 % accuracy and 92 . 40 % sensitivity. Compared with existing methods, and the accuracy of our method is increased by 0 . 11 percentage points. On the H . p y l o r i dataset, our method achieves 89 . 06 % accuracy and 88 . 15 % sensitivity, the accuracy of our method is increased by 0 . 76 % . On the H u m a n PPI dataset, our method achieves 97 . 60 % accuracy and 96 . 37 % sensitivity, and the accuracy of our method is increased by 1 . 30 % . In addition, we test our method on a very important PPI network, and it achieves 92 . 71 % accuracy. In the Wnt-related network, the accuracy of our method is increased by 16 . 67 % . The source code and all datasets are available

  7. Evolution of acyl-ACP-thioesterases and β-ketoacyl-ACP-synthases revealed by protein-protein interactions

    PubMed Central

    Beld, Joris; Blatti, Jillian L.; Behnke, Craig; Mendez, Michael; Burkart, Michael D.

    2014-01-01

    The fatty acid synthase (FAS) is a conserved primary metabolic enzyme complex capable of tolerating cross-species engineering of domains for the development of modified and overproduced fatty acids. In eukaryotes, acyl-acyl carrier protein thioesterases (TEs) off-load mature cargo from the acyl carrier protein (ACP), and plants have developed TEs for short/medium-chain fatty acids. We showed that engineering plant TEs into the green microalga Chlamydomonas reinhardtii does not result in the predicted shift in fatty acid profile. Since fatty acid biosynthesis relies on substrate recognition and protein-protein interactions between the ACP and its partner enzymes, we hypothesized that plant TEs and algal ACP do not functionally interact. Phylogenetic analysis revealed major evolutionary differences between FAS enzymes, including TEs and ketoacyl synthases (KSs), in which the former is present only in some species, whereas the latter is present in all, and has a common ancestor. In line with these results, TEs appeared to be selective towards their ACP partners whereas KSs showed promiscuous behavior across bacterial, plant and algal species. Based on phylogenetic analyses, in silico docking, in vitro mechanistic crosslinking and in vivo algal engineering, we propose that phylogeny can predict effective interactions between ACPs and partner enzymes. PMID:25110394

  8. Complexity of the Ruminococcus flavefaciens FD-1 cellulosome reflects an expansion of family-related protein-protein interactions

    PubMed Central

    Israeli-Ruimy, Vered; Bule, Pedro; Jindou, Sadanari; Dassa, Bareket; Moraïs, Sarah; Borovok, Ilya; Barak, Yoav; Slutzki, Michal; Hamberg, Yuval; Cardoso, Vânia; Alves, Victor D.; Najmudin, Shabir; White, Bryan A.; Flint, Harry J.; Gilbert, Harry J.; Lamed, Raphael; Fontes, Carlos M. G. A.; Bayer, Edward A.

    2017-01-01

    Protein-protein interactions play a vital role in cellular processes as exemplified by assembly of the intricate multi-enzyme cellulosome complex. Cellulosomes are assembled by selective high-affinity binding of enzyme-borne dockerin modules to repeated cohesin modules of structural proteins termed scaffoldins. Recent sequencing of the fiber-degrading Ruminococcus flavefaciens FD-1 genome revealed a particularly elaborate cellulosome system. In total, 223 dockerin-bearing ORFs potentially involved in cellulosome assembly and a variety of multi-modular scaffoldins were identified, and the dockerins were classified into six major groups. Here, extensive screening employing three complementary medium- to high-throughput platforms was used to characterize the different cohesin-dockerin specificities. The platforms included (i) cellulose-coated microarray assay, (ii) enzyme-linked immunosorbent assay (ELISA) and (iii) in-vivo co-expression and screening in Escherichia coli. The data revealed a collection of unique cohesin-dockerin interactions and support the functional relevance of dockerin classification into groups. In contrast to observations reported previously, a dual-binding mode is involved in cellulosome cell-surface attachment, whereas single-binding interactions operate for cellulosome integration of enzymes. This sui generis cellulosome model enhances our understanding of the mechanisms governing the remarkable ability of R. flavefaciens to degrade carbohydrates in the bovine rumen and provides a basis for constructing efficient nano-machines applied to biological processes. PMID:28186207

  9. Complexity of the Ruminococcus flavefaciens FD-1 cellulosome reflects an expansion of family-related protein-protein interactions.

    PubMed

    Israeli-Ruimy, Vered; Bule, Pedro; Jindou, Sadanari; Dassa, Bareket; Moraïs, Sarah; Borovok, Ilya; Barak, Yoav; Slutzki, Michal; Hamberg, Yuval; Cardoso, Vânia; Alves, Victor D; Najmudin, Shabir; White, Bryan A; Flint, Harry J; Gilbert, Harry J; Lamed, Raphael; Fontes, Carlos M G A; Bayer, Edward A

    2017-02-10

    Protein-protein interactions play a vital role in cellular processes as exemplified by assembly of the intricate multi-enzyme cellulosome complex. Cellulosomes are assembled by selective high-affinity binding of enzyme-borne dockerin modules to repeated cohesin modules of structural proteins termed scaffoldins. Recent sequencing of the fiber-degrading Ruminococcus flavefaciens FD-1 genome revealed a particularly elaborate cellulosome system. In total, 223 dockerin-bearing ORFs potentially involved in cellulosome assembly and a variety of multi-modular scaffoldins were identified, and the dockerins were classified into six major groups. Here, extensive screening employing three complementary medium- to high-throughput platforms was used to characterize the different cohesin-dockerin specificities. The platforms included (i) cellulose-coated microarray assay, (ii) enzyme-linked immunosorbent assay (ELISA) and (iii) in-vivo co-expression and screening in Escherichia coli. The data revealed a collection of unique cohesin-dockerin interactions and support the functional relevance of dockerin classification into groups. In contrast to observations reported previously, a dual-binding mode is involved in cellulosome cell-surface attachment, whereas single-binding interactions operate for cellulosome integration of enzymes. This sui generis cellulosome model enhances our understanding of the mechanisms governing the remarkable ability of R. flavefaciens to degrade carbohydrates in the bovine rumen and provides a basis for constructing efficient nano-machines applied to biological processes.

  10. In Vivo Analysis of Protein-Protein Interactions with Bioluminescence Resonance Energy Transfer (BRET): Progress and Prospects.

    PubMed

    Sun, Sihuai; Yang, Xiaobing; Wang, Yao; Shen, Xihui

    2016-10-11

    Proteins are the elementary machinery of life, and their functions are carried out mostly by molecular interactions. Among those interactions, protein-protein interactions (PPIs) are the most important as they participate in or mediate all essential biological processes. However, many common methods for PPI investigations are slightly unreliable and suffer from various limitations, especially in the studies of dynamic PPIs. To solve this problem, a method called Bioluminescence Resonance Energy Transfer (BRET) was developed about seventeen years ago. Since then, BRET has evolved into a whole class of methods that can be used to survey virtually any kinds of PPIs. Compared to many traditional methods, BRET is highly sensitive, reliable, easy to perform, and relatively inexpensive. However, most importantly, it can be done in vivo and allows the real-time monitoring of dynamic PPIs with the easily detectable light signal, which is extremely valuable for the PPI functional research. This review will take a comprehensive look at this powerful technique, including its principles, comparisons with other methods, experimental approaches, classifications, applications, early developments, recent progress, and prospects.

  11. Discovery of potent Keap1-Nrf2 protein-protein interaction inhibitor based on molecular binding determinants analysis.

    PubMed

    Jiang, Zheng-Yu; Lu, Meng-Chen; Xu, Li Li; Yang, Ting-Ting; Xi, Mei-Yang; Xu, Xiao-Li; Guo, Xiao-Ke; Zhang, Xiao-Jin; You, Qi-Dong; Sun, Hao-Peng

    2014-03-27

    Keap1 is known to mediate the ubiquitination of Nrf2, a master regulator of the antioxidant response. Directly interrupting the Keap1-Nrf2 interaction has been emerged as a promising strategy to develop novel class of antioxidant, antiinflammatory, and anticancer agents. On the basis of the molecular binding determinants analysis of Keap1, we successfully designed and characterized the most potent protein-protein interaction (PPI) inhibitor of Keap1-Nrf2, compound 2, with K(D) value of 3.59 nM binding to Keap1 for the first time to single-digit nanomolar. Compound 2 can effectively disrupt the Nrf2-Keap1 interaction with an EC50 of 28.6 nM in the fluorescence polarization assay. It can also activate the Nrf2 transcription activity in the cell-based ARE-luciferase reporter assay in a dose-dependent manner. The qRT-PCR results of Nrf2 transcription targets gave the consistent results. These results confirm direct and highly efficient interruption of the Keap1-Nrf2 PPI can be fully achieved by small molecules.

  12. Prediction of residue-residue contact matrix for protein-protein interaction with Fisher score features and deep learning.

    PubMed

    Du, Tianchuan; Liao, Li; Wu, Cathy H; Sun, Bilin

    2016-11-01

    Protein-protein interactions play essential roles in many biological processes. Acquiring knowledge of the residue-residue contact information of two interacting proteins is not only helpful in annotating functions for proteins, but also critical for structure-based drug design. The prediction of the protein residue-residue contact matrix of the interfacial regions is challenging. In this work, we introduced deep learning techniques (specifically, stacked autoencoders) to build deep neural network models to tackled the residue-residue contact prediction problem. In tandem with interaction profile Hidden Markov Models, which was used first to extract Fisher score features from protein sequences, stacked autoencoders were deployed to extract and learn hidden abstract features. The deep learning model showed significant improvement over the traditional machine learning model, Support Vector Machines (SVM), with the overall accuracy increased by 15% from 65.40% to 80.82%. We showed that the stacked autoencoders could extract novel features, which can be utilized by deep neural networks and other classifiers to enhance learning, out of the Fisher score features. It is further shown that deep neural networks have significant advantages over SVM in making use of the newly extracted features.

  13. Simulation-Based Fitting of Protein-Protein Interaction Potentials to SAXS Experiments

    SciTech Connect

    Kim, Seung Joong; Dumont, Charles; Gruebele, Martin

    2008-07-08

    We present a new method for computing interaction potentials of solvated proteins directly from small-angle x-ray scattering data. An ensemble of proteins is modeled by Monte Carlo or molecular dynamics simulation. The global x-ray scattering of the whole model ensemble is then computed at each snapshot of the simulation, and averaged to obtain the x-ray scattering intensity. Finally, the interaction potential parameters are adjusted by an optimization algorithm, and the procedure is iterated until the best agreement between simulation and experiment is obtained. This new approach obviates the need for approximations that must be made in simplified analytical models. We apply the method to lambda repressor fragment 6-85 and fyn-SH3. With the increased availability of fast computer clusters, Monte Carlo and molecular dynamics analysis using residue-level or even atomistic potentials may soon become feasible.

  14. Protein-protein interactions in RSV assembly: potential targets for attenuating RSV strains.

    PubMed

    Ghildyal, Reena; Jans, David A; Bardin, Philip G; Mills, John

    2012-04-01

    Respiratory syncytial virus (RSV) is the major respiratory pathogen of infants and children worldwide, with no effective treatment or vaccine available. Steady progress has been made in understanding the respiratory syncytial virus lifecycle and the consequences of infection, but some areas of RSV still remain poorly understood. Although many of the interactions between virus proteins that are required for efficient RSV assembly have been elucidated, many questions still remain regarding viral assembly, as well as the mechanisms of RSV budding. This review will summarise the current understanding of RSV assembly, including the various interactions between virus proteins and the involvement of cellular factors with a view to identifying possible attenuation and/or drug targets within the assembly pathway.

  15. Carbene footprinting accurately maps binding sites in protein-ligand and protein-protein interactions.

    PubMed

    Manzi, Lucio; Barrow, Andrew S; Scott, Daniel; Layfield, Robert; Wright, Timothy G; Moses, John E; Oldham, Neil J

    2016-11-16

    Specific interactions between proteins and their binding partners are fundamental to life processes. The ability to detect protein complexes, and map their sites of binding, is crucial to understanding basic biology at the molecular level. Methods that employ sensitive analytical techniques such as mass spectrometry have the potential to provide valuable insights with very little material and on short time scales. Here we present a differential protein footprinting technique employing an efficient photo-activated probe for use with mass spectrometry. Using this methodology the location of a carbohydrate substrate was accurately mapped to the binding cleft of lysozyme, and in a more complex example, the interactions between a 100 kDa, multi-domain deubiquitinating enzyme, USP5 and a diubiquitin substrate were located to different functional domains. The much improved properties of this probe make carbene footprinting a viable method for rapid and accurate identification of protein binding sites utilizing benign, near-UV photoactivation.

  16. Carbene footprinting accurately maps binding sites in protein-ligand and protein-protein interactions

    NASA Astrophysics Data System (ADS)

    Manzi, Lucio; Barrow, Andrew S.; Scott, Daniel; Layfield, Robert; Wright, Timothy G.; Moses, John E.; Oldham, Neil J.

    2016-11-01

    Specific interactions between proteins and their binding partners are fundamental to life processes. The ability to detect protein complexes, and map their sites of binding, is crucial to understanding basic biology at the molecular level. Methods that employ sensitive analytical techniques such as mass spectrometry have the potential to provide valuable insights with very little material and on short time scales. Here we present a differential protein footprinting technique employing an efficient photo-activated probe for use with mass spectrometry. Using this methodology the location of a carbohydrate substrate was accurately mapped to the binding cleft of lysozyme, and in a more complex example, the interactions between a 100 kDa, multi-domain deubiquitinating enzyme, USP5 and a diubiquitin substrate were located to different functional domains. The much improved properties of this probe make carbene footprinting a viable method for rapid and accurate identification of protein binding sites utilizing benign, near-UV photoactivation.

  17. Investigating the Role of Large-Scale Domain Dynamics in Protein-Protein Interactions

    PubMed Central

    Delaforge, Elise; Milles, Sigrid; Huang, Jie-rong; Bouvier, Denis; Jensen, Malene Ringkjøbing; Sattler, Michael; Hart, Darren J.; Blackledge, Martin

    2016-01-01

    Intrinsically disordered linkers provide multi-domain proteins with degrees of conformational freedom that are often essential for function. These highly dynamic assemblies represent a significant fraction of all proteomes, and deciphering the physical basis of their interactions represents a considerable challenge. Here we describe the difficulties associated with mapping the large-scale domain dynamics and describe two recent examples where solution state methods, in particular NMR spectroscopy, are used to investigate conformational exchange on very different timescales. PMID:27679800

  18. Cross-Species Virus-Host Protein-Protein Interactions Inhibiting Innate Immunity

    DTIC Science & Technology

    2016-07-01

    protein complex crystal structure. The black arrows indicate residue positions that are both present at the MDA5 – PIV5 V protein PPI interface and...16 Figure 15. Sequence comparison of host and putative host MDA5 sequences. MDA5 residues ( black bars) predicted to directly interact with V...polymerase subunit PB1 and human MAVS proteins. Virus Res., 172, 75-80 (2013). Scientific Presentations: L. Wayne Schultz, Joseph R. Luft, Eleanor Cook

  19. Yeast mitochondrial protein-protein interactions reveal diverse complexes and disease-relevant functional relationships.

    PubMed

    Jin, Ke; Musso, Gabriel; Vlasblom, James; Jessulat, Matthew; Deineko, Viktor; Negroni, Jacopo; Mosca, Roberto; Malty, Ramy; Nguyen-Tran, Diem-Hang; Aoki, Hiroyuki; Minic, Zoran; Freywald, Tanya; Phanse, Sadhna; Xiang, Qian; Freywald, Andrew; Aloy, Patrick; Zhang, Zhaolei; Babu, Mohan

    2015-02-06

    Although detailed, focused, and mechanistic analyses of associations among mitochondrial proteins (MPs) have identified their importance in varied biological processes, a systematic understanding of how MPs function in concert both with one another and with extra-mitochondrial proteins remains incomplete. Consequently, many questions regarding the role of mitochondrial dysfunction in the development of human disease remain unanswered. To address this, we compiled all existing mitochondrial physical interaction data for over 1200 experimentally defined yeast MPs and, through bioinformatic analysis, identified hundreds of heteromeric MP complexes having extensive associations both within and outside the mitochondria. We provide support for these complexes through structure prediction analysis, morphological comparisons of deletion strains, and protein co-immunoprecipitation. The integration of these MP complexes with reported genetic interaction data reveals substantial crosstalk between MPs and non-MPs and identifies novel factors in endoplasmic reticulum-mitochondrial organization, membrane structure, and mitochondrial lipid homeostasis. More than one-third of these MP complexes are conserved in humans, with many containing members linked to clinical pathologies, enabling us to identify genes with putative disease function through guilt-by-association. Although still remaining incomplete, existing mitochondrial interaction data suggests that the relevant molecular machinery is modular, yet highly integrated with non-mitochondrial processes.

  20. Systematic protein-protein interaction mapping for clinically relevant human GPCRs.

    PubMed

    Sokolina, Kate; Kittanakom, Saranya; Snider, Jamie; Kotlyar, Max; Maurice, Pascal; Gandía, Jorge; Benleulmi-Chaachoua, Abla; Tadagaki, Kenjiro; Oishi, Atsuro; Wong, Victoria; Malty, Ramy H; Deineko, Viktor; Aoki, Hiroyuki; Amin, Shahreen; Yao, Zhong; Morató, Xavier; Otasek, David; Kobayashi, Hiroyuki; Menendez, Javier; Auerbach, Daniel; Angers, Stephane; Pržulj, Natasa; Bouvier, Michel; Babu, Mohan; Ciruela, Francisco; Jockers, Ralf; Jurisica, Igor; Stagljar, Igor

    2017-03-15

    G-protein-coupled receptors (GPCRs) are the largest family of integral membrane receptors with key roles in regulating signaling pathways targeted by therapeutics, but are difficult to study using existing proteomics technologies due to their complex biochemical features. To obtain a global view of GPCR-mediated signaling and to identify novel components of their pathways, we used a modified membrane yeast two-hybrid (MYTH) approach and identified interacting partners for 48 selected full-length human ligand-unoccupied GPCRs in their native membrane environment. The resulting GPCR interactome connects 686 proteins by 987 unique interactions, including 299 membrane proteins involved in a diverse range of cellular functions. To demonstrate the biological relevance of the GPCR interactome, we validated novel interactions of the GPR37, serotonin 5-HT4d, and adenosine ADORA2A receptors. Our data represent the first large-scale interactome mapping for human GPCRs and provide a valuable resource for the analysis of signaling pathways involving this druggable family of integral membrane proteins.

  1. Exploring of protein - protein interactions at the solid - aqueous interface by means of contact angle measurements.

    PubMed

    Grabowska, I; Dehaen, W; Radecka, H; Radecki, J

    2016-05-01

    In this article we present the results of the studies on interactions between the VC1 domain of the Receptor for Advanced Glycation End Products (RAGE) and its ligand, the S100B protein, performed by contact angle measurements. Histidine-tagged (His6) VC1-RAGE domain was covalently bonded to Cu(II) or Ni(II) complexes with dipyrromethene (DPM) self-assembled on gold surface. The method based on the theory of van Oss was used for the purpose of determining the Lifshitz-van der Waals (γ(LW)) component as well as the electron acceptor-electron donor (the Lewis acid-base, γ(+)-γ(-)) parameters of the VC1-RAGE-S100B complex. Moreover, the surface free energies of the interactions between the VC1 domain attached to the surface and the ligand present in the aqueous phase were determined. The specificity of the VC1- RAGE interactions with the ligand studied was also proved.

  2. Allele-Specific Suppression by Formation of New Protein-Protein Interactions in Yeast

    PubMed Central

    Sandrock, T. M.; O'Dell, J. L.; Adams, AEM.

    1997-01-01

    Yeast fimbrin is encoded by the SAC6 gene, mutations of which suppress temperature-sensitive mutations in the actin gene (ACT1). To examine the mechanism of suppression, we have conducted a biochemical analysis of the interaction between various combinations of wild-type and mutant actin and Sac6 proteins. Previously, we showed that actin mutations that are suppressed by sac6 mutations encode proteins with a reduced affinity for wild-type Sac6p. In the present study, we have found that mutant Sac6 proteins bind more tightly to mutant actin than does wild-type Sac6p, and thus compensate for weakened interactions caused by the mutant actin. Remarkably, we have also found that mutant Sac6 proteins bind more tightly to wild-type actin than does wild-type Sac6p. This result indicates that suppression does not occur through the restoration of the original contact site, but rather through the formation of a novel contact site. This finding argues against suppression occurring through a ``lock-and-key'' mechanism and suggests a mechanism involving more global increases in affinity between the two proteins. We propose that the most common kind of suppressors involving interacting proteins will likely occur through this less specific mechanism. PMID:9409826

  3. Investigating CFTR and KCa3.1 Protein/Protein Interactions

    PubMed Central

    Trinh, Nguyen Thu Ngan; Luo, Yishan; Wiseman, Paul W.; Hanrahan, John W.; Brochiero, Emmanuelle; Sauvé, Rémy

    2016-01-01

    In epithelia, Cl- channels play a prominent role in fluid and electrolyte transport. Of particular importance is the cAMP-dependent cystic fibrosis transmembrane conductance regulator Cl- channel (CFTR) with mutations of the CFTR encoding gene causing cystic fibrosis. The bulk transepithelial transport of Cl- ions and electrolytes needs however to be coupled to an increase in K+ conductance in order to recycle K+ and maintain an electrical driving force for anion exit across the apical membrane. In several epithelia, this K+ efflux is ensured by K+ channels, including KCa3.1, which is expressed at both the apical and basolateral membranes. We show here for the first time that CFTR and KCa3.1 can physically interact. We first performed a two-hybrid screen to identify which KCa3.1 cytosolic domains might mediate an interaction with CFTR. Our results showed that both the N-terminal fragment M1-M40 of KCa3.1 and part of the KCa3.1 calmodulin binding domain (residues L345-A400) interact with the NBD2 segment (G1237-Y1420) and C- region of CFTR (residues T1387-L1480), respectively. An association of CFTR and F508del-CFTR with KCa3.1 was further confirmed in co-immunoprecipitation experiments demonstrating the formation of immunoprecipitable CFTR/KCa3.1 complexes in CFBE cells. Co-expression of KCa3.1 and CFTR in HEK cells did not impact CFTR expression at the cell surface, and KCa3.1 trafficking appeared independent of CFTR stimulation. Finally, evidence is presented through cross-correlation spectroscopy measurements that KCa3.1 and CFTR colocalize at the plasma membrane and that KCa3.1 channels tend to aggregate consequent to an enhanced interaction with CFTR channels at the plasma membrane following an increase in intracellular Ca2+ concentration. Altogether, these results suggest 1) that the physical interaction KCa3.1/CFTR can occur early during the biogenesis of both proteins and 2) that KCa3.1 and CFTR form a dynamic complex, the formation of which depends on

  4. Investigating CFTR and KCa3.1 Protein/Protein Interactions.

    PubMed

    Klein, Hélène; Abu-Arish, Asmahan; Trinh, Nguyen Thu Ngan; Luo, Yishan; Wiseman, Paul W; Hanrahan, John W; Brochiero, Emmanuelle; Sauvé, Rémy

    2016-01-01

    In epithelia, Cl- channels play a prominent role in fluid and electrolyte transport. Of particular importance is the cAMP-dependent cystic fibrosis transmembrane conductance regulator Cl- channel (CFTR) with mutations of the CFTR encoding gene causing cystic fibrosis. The bulk transepithelial transport of Cl- ions and electrolytes needs however to be coupled to an increase in K+ conductance in order to recycle K+ and maintain an electrical driving force for anion exit across the apical membrane. In several epithelia, this K+ efflux is ensured by K+ channels, including KCa3.1, which is expressed at both the apical and basolateral membranes. We show here for the first time that CFTR and KCa3.1 can physically interact. We first performed a two-hybrid screen to identify which KCa3.1 cytosolic domains might mediate an interaction with CFTR. Our results showed that both the N-terminal fragment M1-M40 of KCa3.1 and part of the KCa3.1 calmodulin binding domain (residues L345-A400) interact with the NBD2 segment (G1237-Y1420) and C- region of CFTR (residues T1387-L1480), respectively. An association of CFTR and F508del-CFTR with KCa3.1 was further confirmed in co-immunoprecipitation experiments demonstrating the formation of immunoprecipitable CFTR/KCa3.1 complexes in CFBE cells. Co-expression of KCa3.1 and CFTR in HEK cells did not impact CFTR expression at the cell surface, and KCa3.1 trafficking appeared independent of CFTR stimulation. Finally, evidence is presented through cross-correlation spectroscopy measurements that KCa3.1 and CFTR colocalize at the plasma membrane and that KCa3.1 channels tend to aggregate consequent to an enhanced interaction with CFTR channels at the plasma membrane following an increase in intracellular Ca2+ concentration. Altogether, these results suggest 1) that the physical interaction KCa3.1/CFTR can occur early during the biogenesis of both proteins and 2) that KCa3.1 and CFTR form a dynamic complex, the formation of which depends on

  5. Stress-Responsive Expression, Subcellular Localization and Protein-Protein Interactions of the Rice Metacaspase Family.

    PubMed

    Huang, Lei; Zhang, Huijuan; Hong, Yongbo; Liu, Shixia; Li, Dayong; Song, Fengming

    2015-07-17

    Metacaspases, a class of cysteine-dependent proteases like caspases in animals, are important regulators of programmed cell death (PCD) during development and stress responses in plants. The present study was focused on comprehensive analyses of expression patterns of the rice metacaspase (OsMC) genes in response to abiotic and biotic stresses and stress-related hormones. Results indicate that members of the OsMC family displayed differential expression patterns in response to abiotic (e.g., drought, salt, cold, and heat) and biotic (e.g., infection by Magnaporthe oryzae, Xanthomonas oryzae pv. oryzae and Rhizoctonia solani) stresses and stress-related hormones such as abscisic acid, salicylic acid, jasmonic acid, and 1-amino cyclopropane-1-carboxylic acid (a precursor of ethylene), although the responsiveness to these stresses or hormones varies to some extent. Subcellular localization analyses revealed that OsMC1 was solely localized and OsMC2 was mainly localized in the nucleus. Whereas OsMC3, OsMC4, and OsMC7 were evenly distributed in the cells, OsMC5, OsMC6, and OsMC8 were localized in cytoplasm. OsMC1 interacted with OsLSD1 and OsLSD3 while OsMC3 only interacted with OsLSD1 and that the zinc finger domain in OsMC1 is responsible for the interaction activity. The systematic expression and biochemical analyses of the OsMC family provide valuable information for further functional studies on the biological roles of OsMCs in PCD that is related to abiotic and biotic stress responses.

  6. Protein-protein interactions involved in the recognition of p27 by E3 ubiquitin ligase.

    PubMed Central

    Xu, Kui; Belunis, Charles; Chu, Wei; Weber, David; Podlaski, Frank; Huang, Kuo-Sen; Reed, Steven I; Vassilev, Lyubomir T

    2003-01-01

    The p27(Kip1) protein is a potent cyclin-dependent kinase inhibitor, the level of which is decreased in many common human cancers as a result of enhanced ubiquitin-dependent degradation. The multiprotein complex SCF(Skp2) has been identified as the ubiquitin ligase that targets p27, but the functional interactions within this complex are not well understood. One component, the F-box protein Skp2, binds p27 when the latter is phosphorylated on Thr(187), thus providing substrate specificity for the ligase. Recently, we and others have shown that the small cell cycle regulatory protein Cks1 plays a critical role in p27 ubiquitination by increasing the binding affinity of Skp2 for p27. Here we report the development of a homogeneous time-resolved fluorescence assay that allows the quantification of the molecular interactions between human recombinant Skp2, Cks1 and a p27-derived peptide phosphorylated on Thr(187). Using this assay, we have determined the dissociation constant of the Skp2-Cks1 complex (K(d) 140 +/- 14 nM) and have shown that Skp2 binds phosphorylated p27 peptide with high affinity only in the presence of Cks1 (K(d) 37 +/- 2 nM). Cks1 does not bind directly to the p27 phosphopeptide or to Skp1, which confirms its suggested role as an allosteric effector of Skp2. PMID:12529174

  7. Unraveling Protein-Protein Interactions in Clathrin Assemblies via Atomic Force Spectroscopy

    PubMed Central

    Jin, Albert J.; Lafer, Eileen M.; Peng, Jennifer Q.; Smith, Paul D.; Nossal, Ralph

    2013-01-01

    Atomic force microscopy (AFM), single molecule force spectroscopy (SMFS), and single particle force spectroscopy (SPFS) are used to characterize intermolecular interactions and domain structures of clathrin triskelia and clathrin-coated vesicles (CCVs). The latter are involved in receptor-mediated endocytosis (RME) and other trafficking pathways. Here, we subject individual triskelia, bovine-brain CCVs, and reconstituted clathrin-AP180 coats to AFM-SMFS and AFM-SPFS pulling experiments and apply novel analytics to extract force-extension relations from very large data sets. The spectroscopic fingerprints of these samples differ markedly, providing important new information about the mechanism of CCV uncoating. For individual triskelia, SMFS reveals a series of events associated with heavy chain alpha-helix hairpin unfolding, as well as cooperative unraveling of several hairpin domains. SPFS of clathrin assemblies exposes weaker clathrin-clathrin interactions that are indicative of inter-leg association essential for RME and intracellular trafficking. Clathrin-AP180 coats are energetically easier to unravel than the coats of CCVs, with a non-trivial dependence on force-loading rate. PMID:23270814

  8. Unraveling protein-protein interactions in clathrin assemblies via atomic force spectroscopy.

    PubMed

    Jin, Albert J; Lafer, Eileen M; Peng, Jennifer Q; Smith, Paul D; Nossal, Ralph

    2013-03-01

    Atomic force microscopy (AFM), single molecule force spectroscopy (SMFS), and single particle force spectroscopy (SPFS) are used to characterize intermolecular interactions and domain structures of clathrin triskelia and clathrin-coated vesicles (CCVs). The latter are involved in receptor-mediated endocytosis (RME) and other trafficking pathways. Here, we subject individual triskelia, bovine-brain CCVs, and reconstituted clathrin-AP180 coats to AFM-SMFS and AFM-SPFS pulling experiments and apply novel analytics to extract force-extension relations from very large data sets. The spectroscopic fingerprints of these samples differ markedly, providing important new information about the mechanism of CCV uncoating. For individual triskelia, SMFS reveals a series of events associated with heavy chain alpha-helix hairpin unfolding, as well as cooperative unraveling of several hairpin domains. SPFS of clathrin assemblies exposes weaker clathrin-clathrin interactions that are indicative of inter-leg association essential for RME and intracellular trafficking. Clathrin-AP180 coats are energetically easier to unravel than the coats of CCVs, with a non-trivial dependence on force-loading rate.

  9. Peptides interfering with protein-protein interactions in the ethylene signaling pathway delay tomato fruit ripening

    NASA Astrophysics Data System (ADS)

    Bisson, Melanie M. A.; Kessenbrock, Mareike; Müller, Lena; Hofmann, Alexander; Schmitz, Florian; Cristescu, Simona M.; Groth, Georg

    2016-08-01

    The plant hormone ethylene is involved in the regulation of several processes with high importance for agricultural applications, e.g. ripening, aging and senescence. Previous work in our group has identified a small peptide (NOP-1) derived from the nuclear localization signal of the Arabidopsis ethylene regulator ETHYLENE INSENSITIVE-2 (EIN2) C-terminal part as efficient inhibitor of ethylene responses. Here, we show that NOP-1 is also able to efficiently disrupt EIN2-ETR1 complex formation in tomato, indicating that the NOP-1 inhibition mode is conserved across plant species. Surface application of NOP-1 on green tomato fruits delays ripening similar to known inhibitors of ethylene perception (MCP) and ethylene biosynthesis (AVG). Fruits treated with NOP-1 showed similar ethylene production as untreated controls underlining that NOP-1 blocks ethylene signaling by targeting an essential interaction in this pathway, while having no effect on ethylene biosynthesis.

  10. Rosetta stone method for detecting protein function and protein-protein interactions from genome sequences

    DOEpatents

    Eisenberg, David; Marcotte, Edward M.; Pellegrini, Matteo; Thompson, Michael J.; Yeates, Todd O.

    2002-10-15

    A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

  11. Peptides interfering with protein-protein interactions in the ethylene signaling pathway delay tomato fruit ripening

    PubMed Central

    Bisson, Melanie M. A.; Kessenbrock, Mareike; Müller, Lena; Hofmann, Alexander; Schmitz, Florian; Cristescu, Simona M.; Groth, Georg

    2016-01-01

    The plant hormone ethylene is involved in the regulation of several processes with high importance for agricultural applications, e.g. ripening, aging and senescence. Previous work in our group has identified a small peptide (NOP-1) derived from the nuclear localization signal of the Arabidopsis ethylene regulator ETHYLENE INSENSITIVE-2 (EIN2) C-terminal part as efficient inhibitor of ethylene responses. Here, we show that NOP-1 is also able to efficiently disrupt EIN2-ETR1 complex formation in tomato, indicating that the NOP-1 inhibition mode is conserved across plant species. Surface application of NOP-1 on green tomato fruits delays ripening similar to known inhibitors of ethylene perception (MCP) and ethylene biosynthesis (AVG). Fruits treated with NOP-1 showed similar ethylene production as untreated controls underlining that NOP-1 blocks ethylene signaling by targeting an essential interaction in this pathway, while having no effect on ethylene biosynthesis. PMID:27477591

  12. Cerebral Cavernous Malformations: Review of the Genetic and Protein-Protein Interactions Resulting in Disease Pathogenesis.

    PubMed

    Baranoski, Jacob F; Kalani, M Yashar S; Przybylowski, Colin J; Zabramski, Joseph M

    2016-01-01

    Mutations in the genes KRIT1, CCM2, and PDCD10 are known to result in the formation of cerebral cavernous malformations (CCMs). CCMs are intracranial lesions composed of aberrantly enlarged "cavernous" endothelial channels that can result in cerebral hemorrhage, seizures, and neurologic deficits. Although these genes have been known to be associated with CCMs since the 1990s, numerous discoveries have been made that better elucidate how they and their subsequent protein products are involved in CCM pathogenesis. Since our last review of the molecular genetics of CCM pathogenesis in 2012, breakthroughs include a more thorough understanding of the protein structures of the gene products, involvement with integrin proteins, and MEKK3 signaling pathways, and the importance of CCM2-PDCD10 interactions. In this review, we highlight the advances that further our understanding of the "gene to protein to disease" relationships of CCMs.

  13. MicroRNA-Regulated Protein-Protein Interaction Networks and Their Functions in Breast Cancer

    PubMed Central

    Lee, Chia-Hsien; Kuo, Wen-Hong; Lin, Chen-Ching; Oyang, Yen-Jen; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

    2013-01-01

    MicroRNAs, which are small endogenous RNA regulators, have been associated with various types of cancer. Breast cancer is a major health threat for women worldwide. Many miRNAs were reported to be associated with the progression and carcinogenesis of breast cancer. In this study, we aimed to discover novel breast cancer-related miRNAs and to elucidate their functions. First, we identified confident miRNA-target pairs by combining data from miRNA target prediction databases and expression profiles of miRNA and mRNA. Then, miRNA-regulated protein interaction networks (PINs) were constructed with confident pairs and known interaction data in the human protein reference database (HPRD). Finally, the functions of miRNA-regulated PINs were elucidated by functional enrichment analysis. From the results, we identified some previously reported breast cancer-related miRNAs and functions of the PINs, e.g., miR-125b, miR-125a, miR-21, and miR-497. Some novel miRNAs without known association to breast cancer were also found, and the putative functions of their PINs were also elucidated. These include miR-139 and miR-383. Furthermore, we validated our results by receiver operating characteristic (ROC) curve analysis using our miRNA expression profile data, gene expression-based outcome for breast cancer online (GOBO) survival analysis, and a literature search. Our results may provide new insights for research in breast cancer-associated miRNAs. PMID:23722663

  14. GPR37 Surface Expression Enhancement via N-Terminal Truncation or Protein-Protein Interactions1

    PubMed Central

    Dunham, Jill H.; Meyer, Rebecca C.; Garcia, Erin L.; Hall, Randy A.

    2009-01-01

    GPR37, also known as the parkin-associated endothelin-like receptor (Pael-R), is an orphan G protein-coupled receptor (GPCR) that exhibits poor plasma membrane expression when expressed in most cell types. We sought to find ways to enhance GPR37 trafficking to the cell surface in order to facilitate studies of GPR37 functional activity in heterologous cells. In truncation studies, we found that removing the GPR37 N-terminus (NT) dramatically enhanced the receptor’s plasma membrane insertion. Further studies on sequential NT truncations revealed that removal of the first 210 amino acids increased surface expression nearly as much as removal of the entire NT. In studies examining the effects of co-expression of GPR37 with a variety of other GPCRs, we observed significant increases in GPR37 surface expression when the receptor was co-expressed with the adenosine receptor A2AR or the dopamine receptor D2R. Co-immunoprecipitation experiments revealed that full-length GPR37 and, to a greater extent, the truncated GPR37 were capable of robustly associating with D2R, resulting in modestly-altered D2R affinity for both agonists and antagonists. In studies examining potential interactions of GPR37 with PDZ scaffolds, we observed a specific interaction between GPR37 and syntenin-1, which resulted in a dramatic increase in GPR37 surface expression in HEK-293 cells. These findings reveal three independent approaches – N-terminal truncation, co-expression with other receptors and co-expression with syntenin-1 – by which GPR37 surface trafficking in heterologous cells can be greatly enhanced to facilitate functional studies on this orphan receptor. PMID:19799451

  15. Proteomic Analysis of Protein-Protein Interactions within the CSD Fe-S Cluster Biogenesis System

    PubMed Central

    Bolstad, Heather M.; Botelho, Danielle J.; Wood, Matthew J.

    2010-01-01

    Fe-S cluster biogenesis is of interest to many fields, including bioenergetics and gene regulation. The CSD system is one of three Fe-S cluster biogenesis systems in E. coli and is comprised of the cysteine desulfurase CsdA, the sulfur acceptor protein CsdE, and the E1-like protein CsdL. The biological role, biochemical mechanism, and protein targets of the system remain uncharacterized. Here we present that the active site CsdE C61 has a lowered pKa value of 6.5, which is nearly identical to that of C51 in the homologous SufE protein and which is likely critical for its function. We observed that CsdE forms disulfide bonds with multiple proteins and identified the proteins that copurify with CsdE. The identification of Fe-S proteins and both putative and established Fe-S cluster assembly (ErpA, glutaredoxin-3, glutaredoxin-4) and sulfur trafficking (CsdL, YchN) proteins supports the two-pathway model, in which the CSD system is hypothesized to synthesize both Fe-S clusters and other sulfur-containing cofactors. We suggest that the identified Fe-S cluster assembly proteins may be the scaffold and/or shuttle proteins for the CSD system. By comparison with previous analysis of SufE, we demonstrate that there is some overlap in the CsdE and SufE interactomes. PMID:20734996

  16. Construction and analysis of a protein-protein interaction network related to self-renewal of mouse spermatogonial stem cells.

    PubMed

    Xie, Wenhai; Sun, Jin; Wu, Ji

    2015-03-01

    Spermatogonial stem cells (SSCs) are responsible for sustained spermatogenesis throughout the reproductive life of the male. Extensive studies of SSCs have identified dozens of genes that play important roles in sustaining or controlling the pool of SSCs in the mammalian testis. However, there is still limited knowledge of whether or how these key genes interact with each other during SSC self-renewal. Here, we constructed a protein-protein interaction (PPI) network for SSC self-renewal based on interactions between 23 genes essential for SSC self-renewal, which were obtained from a text mining system, and the interacting partners of the 23 key genes, which were differentially expressed in SSCs. The SSC self-renewal PPI network consisted of 246 nodes connected by 844 edges. Topological analyses of the PPI network were conducted to identify genes essential for maintenance of SSC self-renewal. The subnetwork of the SSC self-renewal network suggested that the 23 key genes involved in SSC self-renewal were connected together through other 94 genes. Clustering of the whole network and subnetwork of SSC self-renewal revealed several densely connected regions, implying significant molecular interaction modules essential for SSC self-renewal. Notably, we found the 23 genes to be responsible for SSC self-renewal by forming a continuous PPI network centered on Pou5f1. Our study indicates that it is feasible to explore important proteins and regulatory pathways in biological activities by combining a PPI database with the high-throughput data of gene expression profiles.

  17. Virtual Screening and Experimental Validation Identify Novel Inhibitors of the Plasmodium falciparum Atg8-Atg3 Protein-Protein Interaction.

    PubMed

    Hain, Adelaide U P; Miller, Alexia S; Levitskaya, Jelena; Bosch, Jürgen

    2016-04-19

    New therapies are needed against malaria, a parasitic infection caused by Plasmodium falciparum, as drug resistance emerges against the current treatment, artemisinin. We previously characterized the Atg8-Atg3 protein-protein interaction (PPI), which is essential for autophagy and parasite survival. Herein we illustrate the use of virtual library screening to selectively block the PPI in the parasite without inhibiting the homologous interaction in humans by targeting the A-loop of PfAtg8. This A-loop is important for Atg3 binding in Plasmodium, but is absent from the human Atg8 homologues. In this proof-of-concept study, we demonstrate a shift in lipidation state of PfAtg8 and inhibition of P. falciparum growth in both blood- and liver-stage cultures upon drug treatment. Our results illustrate how in silico screening and structure-aided drug design against a PPI can be used to identify new hits for drug development. Additionally, as we targeted a region of Atg8 that is conserved within apicomplexans, we predict that our small molecule will have cross-reactivity against other disease-causing apicomplexans, such as Toxoplasma, Cryptosporidium, Theileria, Neospora, Eimeria, and Babesia.

  18. Small-Molecule Stabilization of the 14-3-3/Gab2 Protein-Protein Interaction (PPI) Interface.

    PubMed

    Bier, David; Bartel, Maria; Sies, Katharina; Halbach, Sebastian; Higuchi, Yusuke; Haranosono, Yu; Brummer, Tilman; Kato, Nobuo; Ottmann, Christian

    2016-04-19

    Small-molecule modulation of protein-protein interactions (PPIs) is one of the most promising new areas in drug discovery. In the vast majority of cases only inhibition or disruption of PPIs is realized, whereas the complementary strategy of targeted stabilization of PPIs is clearly under-represented. Here, we report the example of a semi-synthetic natural product derivative--ISIR-005--that stabilizes the cancer-relevant interaction of the adaptor protein 14-3-3 and Gab2. The crystal structure of ISIR-005 in complex with 14-3-3 and the binding motif of Gab2 comprising two phosphorylation sites (Gab2pS210pT391) showed how the stabilizing molecule binds to the rim-of-the-interface of the protein complex. Only in the direct vicinity of 14-3-3/Gab2pT391 site is a pre-formed pocket occupied by ISIR-005; binding of the Gab2pS210 motif to 14-3-3 does not create an interface pocket suitable for the molecule. Accordingly, ISIR-005 only stabilizes the binding of the Gab2pT391 but not the Gab2pS210 site. This study represents structural and biochemical proof of the druggability of the 14-3-3/Gab2 PPI interface with important implications for the development of PPI stabilizers.

  19. LexA repressor forms stable dimers in solution. The role of specific dna in tightening protein-protein interactions.

    PubMed

    Mohana-Borges, R; Pacheco, A B; Sousa, F J; Foguel, D; Almeida, D F; Silva, J L

    2000-02-18

    Cooperativity in the interactions among proteins subunits and DNA is crucial for DNA recognition. LexA repressor was originally thought to bind DNA as a monomer, with cooperativity leading to tighter binding of the second monomer. The main support for this model was a high value of the dissociation constant for the LexA dimer (micromolar range). Here we show that the protein is a dimer at nanomolar concentrations under different conditions. The reversible dissociation of LexA dimer was investigated by the effects of hydrostatic pressure or urea, using fluorescence emission and polarization to monitor the dissociation process. The dissociation constant lies in the picomolar range (lower than 20 pM). LexA monomers associate with an unusual large volume change (340 ml/mol), indicating the burial of a large surface area upon dimerization. Whereas nonspecific DNA has no stabilizing effect, specific DNA induces tightening of the dimer and a 750-fold decrease in the K(d). In contrast to the previous model, a tight dimer rather than a monomer is the functional repressor. Accordingly, the LexA dimer only loses its ability to recognize a specific DNA sequence by RecA-induced autoproteolysis. Our work provides insights into the linkage between protein-protein interactions, DNA recognition, and DNA repair.

  20. A Systems Biology Comparison of Ovarian Cancers Implicates Putative Somatic Driver Mutations through Protein-Protein Interaction Models

    PubMed Central

    Yang, Mary Qu; Elnitski, Laura

    2016-01-01

    Ovarian carcinomas can be aggressive with a high mortality rate (e.g., high-grade serous ovarian carcinomas, or HGSOCs), or indolent with much better long-term outcomes (e.g., low-malignant-potential, or LMP, serous ovarian carcinomas). By comparing LMP and HGSOC tumors, we can gain insight into the mechanisms underlying malignant progression in ovarian cancer. However, previous studies of the two subtypes have been focused on gene expression analysis. Here, we applied a systems biology approach, integrating gene expression profiles derived from two independent data sets containing both LMP and HGSOC tumors with protein-protein interaction data. Genes and related networks implicated by both data sets involved both known and novel disease mechanisms and highlighted the different roles of BRCA1 and CREBBP in the two tumor types. In addition, the incorporation of somatic mutation data revealed that amplification of PAK4 is associated with poor survival in patients with HGSOC. Thus, perturbations in protein interaction networks demonstrate differential trafficking of network information between malignant and benign ovarian cancers. The novel network-based molecular signatures identified here may be used to identify new targets for intervention and to improve the treatment of invasive ovarian cancer as well as early diagnosis. PMID:27788148

  1. InterEvDock: a docking server to predict the structure of protein-protein interactions using evolutionary information.

    PubMed

    Yu, Jinchao; Vavrusa, Marek; Andreani, Jessica; Rey, Julien; Tufféry, Pierre; Guerois, Raphaël

    2016-07-08

    The structural modeling of protein-protein interactions is key in understanding how cell machineries cross-talk with each other. Molecular docking simulations provide efficient means to explore how two unbound protein structures interact. InterEvDock is a server for protein docking based on a free rigid-body docking strategy. A systematic rigid-body docking search is performed using the FRODOCK program and the resulting models are re-scored with InterEvScore and SOAP-PP statistical potentials. The InterEvScore potential was specifically designed to integrate co-evolutionary information in the docking process. InterEvDock server is thus particularly well suited in case homologous sequences are available for both binding partners. The server returns 10 structures of the most likely consensus models together with 10 predicted residues most likely involved in the interface. In 91% of all complexes tested in the benchmark, at least one residue out of the 10 predicted is involved in the interface, providing useful guidelines for mutagenesis. InterEvDock is able to identify a correct model among the top10 models for 49% of the rigid-body cases with evolutionary information, making it a unique and efficient tool to explore structural interactomes under an evolutionary perspective. The InterEvDock web interface is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock/.

  2. The OncoPPi network of cancer-focused protein-protein interactions to inform biological insights and therapeutic strategies.

    PubMed

    Li, Zenggang; Ivanov, Andrei A; Su, Rina; Gonzalez-Pecchi, Valentina; Qi, Qi; Liu, Songlin; Webber, Philip; McMillan, Elizabeth; Rusnak, Lauren; Pham, Cau; Chen, Xiaoqian; Mo, Xiulei; Revennaugh, Brian; Zhou, Wei; Marcus, Adam; Harati, Sahar; Chen, Xiang; Johns, Margaret A; White, Michael A; Moreno, Carlos; Cooper, Lee A D; Du, Yuhong; Khuri, Fadlo R; Fu, Haian

    2017-02-16

    As genomics advances reveal the cancer gene landscape, a daunting task is to understand how these genes contribute to dysregulated oncogenic pathways. Integration of cancer genes into networks offers opportunities to reveal protein-protein interactions (PPIs) with functional and therapeutic significance. Here, we report the generation of a cancer-focused PPI network, termed OncoPPi, and identification of >260 cancer-associated PPIs not in other large-scale interactomes. PPI hubs reveal new regulatory mechanisms for cancer genes like MYC, STK11, RASSF1 and CDK4. As example, the NSD3 (WHSC1L1)-MYC interaction suggests a new mechanism for NSD3/BRD4 chromatin complex regulation of MYC-driven tumours. Association of undruggable tumour suppressors with drug targets informs therapeutic options. Based on OncoPPi-derived STK11-CDK4 connectivity, we observe enhanced sensitivity of STK11-silenced lung cancer cells to the FDA-approved CDK4 inhibitor palbociclib. OncoPPi is a focused PPI resource that links cancer genes into a signalling network for discovery of PPI targets and network-implicated tumour vulnerabilities for therapeutic interrogation.

  3. Protein-protein interaction network construction for cancer using a new L1/2-penalized Net-SVM model.

    PubMed

    Chai, H; Huang, H H; Jiang, H K; Liang, Y; Xia, L Y

    2016-07-25

    Identifying biomarker genes and characterizing interaction pathways with high-dimensional and low-sample size microarray data is a major challenge in computational biology. In this field, the construction of protein-protein interaction (PPI) networks using disease-related selected genes has garnered much attention. Support vector machines (SVMs) are commonly used to classify patients, and a number of useful tools such as lasso, elastic net, SCAD, or other regularization methods can be combined with SVM models to select genes that are related to a disease. In the current study, we propose a new Net-SVM model that is different from other SVM models as it is combined with L1/2-norm regularization, which has good performance with high-dimensional and low-sample size microarray data for cancer classification, gene selection, and PPI network construction. Both simulation studies and real data experiments demonstrated that our proposed method outperformed other regularization methods such as lasso, SCAD, and elastic net. In conclusion, our model may help to select fewer but more relevant genes, and can be used to construct simple and informative PPI networks that are highly relevant to cancer.

  4. Role of protein-protein interactions in the antiapoptotic function of EWS-Fli-1.

    PubMed

    Ramakrishnan, Ramugounder; Fujimura, Yasuo; Zou, Jian Ping; Liu, Fang; Lee, Leo; Rao, Veena N; Reddy, E Shyam P

    2004-09-16

    In the majority of Ewing's family tumors, chromosomal translocation t(11;22) leads to aberrant fusion of RNA-binding protein EWS with DNA-binding ETS transcriptional factor Fli-1. EWS-Fli-1 has altered the transcriptional activity and modulating its downstream target genes through this transcriptional activity is thought to be responsible for this tumor. We have previously shown that both EWS-Fli-1 and Fli-1 have antiapoptotic activity against several apoptotic inducers. Here, we show that the transcriptional activity of EWS-Fli-1 and Fli-1 is not essential for its antiapoptotic activity. We also demonstrate that EWS-Fli-1 and Fli-1 interact with CBP through its amino-terminal region and inhibit the CBP-dependent transcriptional activity of RXR. This activity appears to be independent of DNA-binding activity of EWS-Fli-1. Introduction of the dominant-negative form of CBP into Ewing's sarcoma cells sensitizes these cells against genotoxic or retinoic-acid induced apoptosis. These results suggest that the ability of EWS-Fli-1/Fli-1 to target transcriptional cofactor(s) and modulate apoptotic pathways may be responsible for its antiapoptotic and tumorigenic activities.

  5. Targeting Protein-Protein Interactions with Trimeric Ligands: High Affinity Inhibitors of the MAGUK Protein Family

    PubMed Central

    Nissen, Klaus B.; Haugaard-Kedström, Linda M.; Wilbek, Theis S.; Nielsen, Line S.; Åberg, Emma; Kristensen, Anders S.; Bach, Anders; Jemth, Per; Strømgaard, Kristian

    2015-01-01

    PDZ domains in general, and those of PSD-95 in particular, are emerging as promising drug targets for diseases such as ischemic stroke. We have previously shown that dimeric ligands that simultaneously target PDZ1 and PDZ2 of PSD-95 are highly potent inhibitors of PSD-95. However, PSD-95 and the related MAGUK proteins contain three consecutive PDZ domains, hence we envisioned that targeting all three PDZ domains simultaneously would lead to more potent and potentially more specific interactions with the MAGUK proteins. Here we describe the design, synthesis and characterization of a series of trimeric ligands targeting all three PDZ domains of PSD-95 and the related MAGUK proteins, PSD-93, SAP-97 and SAP-102. Using our dimeric ligands targeting the PDZ1-2 tandem as starting point, we designed novel trimeric ligands by introducing a PDZ3-binding peptide moiety via a cysteine-derivatized NPEG linker. The trimeric ligands generally displayed increased affinities compared to the dimeric ligands in fluorescence polarization binding experiments and optimized trimeric ligands showed low nanomolar inhibition towards the four MAGUK proteins, thus being the most potent inhibitors described. Kinetic experiments using stopped-flow spectrometry showed that the increase in affinity is caused by a decrease in the dissociation rate of the trimeric ligand as compared to the dimeric ligands, likely reflecting the lower probability of simultaneous dissociation of all three PDZ ligands. Thus, we have provided novel inhibitors of the MAGUK proteins with exceptionally high affinity, which can be used to further elucidate the therapeutic potential of these proteins. PMID:25658767

  6. Targeting protein-protein interactions with trimeric ligands: high affinity inhibitors of the MAGUK protein family.

    PubMed

    Nissen, Klaus B; Haugaard-Kedström, Linda M; Wilbek, Theis S; Nielsen, Line S; Åberg, Emma; Kristensen, Anders S; Bach, Anders; Jemth, Per; Strømgaard, Kristian

    2015-01-01

    PDZ domains in general, and those of PSD-95 in particular, are emerging as promising drug targets for diseases such as ischemic stroke. We have previously shown that dimeric ligands that simultaneously target PDZ1 and PDZ2 of PSD-95 are highly potent inhibitors of PSD-95. However, PSD-95 and the related MAGUK proteins contain three consecutive PDZ domains, hence we envisioned that targeting all three PDZ domains simultaneously would lead to more potent and potentially more specific interactions with the MAGUK proteins. Here we describe the design, synthesis and characterization of a series of trimeric ligands targeting all three PDZ domains of PSD-95 and the related MAGUK proteins, PSD-93, SAP-97 and SAP-102. Using our dimeric ligands targeting the PDZ1-2 tandem as starting point, we designed novel trimeric ligands by introducing a PDZ3-binding peptide moiety via a cysteine-derivatized NPEG linker. The trimeric ligands generally displayed increased affinities compared to the dimeric ligands in fluorescence polarization binding experiments and optimized trimeric ligands showed low nanomolar inhibition towards the four MAGUK proteins, thus being the most potent inhibitors described. Kinetic experiments using stopped-flow spectrometry showed that the increase in affinity is caused by a decrease in the dissociation rate of the trimeric ligand as compared to the dimeric ligands, likely reflecting the lower probability of simultaneous dissociation of all three PDZ ligands. Thus, we have provided novel inhibitors of the MAGUK proteins with exceptionally high affinity, which can be used to further elucidate the therapeutic potential of these proteins.

  7. Fuzzy regions in an intrinsically disordered protein impair protein-protein interactions.

    PubMed

    Gruet, Antoine; Dosnon, Marion; Blocquel, David; Brunel, Joanna; Gerlier, Denis; Das, Rahul K; Bonetti, Daniela; Gianni, Stefano; Fuxreiter, Monika; Longhi, Sonia; Bignon, Christophe

    2016-02-01

    Despite the partial disorder-to-order transition that intrinsically disordered proteins often undergo upon binding to their partners, a considerable amount of residual disorder may be retained in the bound form, resulting in a fuzzy complex. Fuzzy regions flanking molecular recognition elements may enable partner fishing through non-specific, transient contacts, thereby facilitating binding, but may also disfavor binding through various mechanisms. So far, few computational or experimental studies have addressed the effect of fuzzy appendages on partner recognition by intrinsically disordered proteins. In order to shed light onto this issue, we used the interaction between the intrinsically disordered C-terminal domain of the measles virus (MeV) nucleoprotein (NTAIL ) and the X domain (XD) of the viral phosphoprotein as model system. After binding to XD, the N-terminal region of NTAIL remains conspicuously disordered, with α-helical folding taking place only within a short molecular recognition element. To study the effect of the N-terminal fuzzy region on NTAIL /XD binding, we generated N-terminal truncation variants of NTAIL , and assessed their binding abilities towards XD. The results revealed that binding increases with shortening of the N-terminal fuzzy region, with this also being observed with hsp70 (another MeV NTAIL binding partner), and for the homologous NTAIL /XD pairs from the Nipah and Hendra viruses. Finally, similar results were obtained when the MeV NTAIL fuzzy region was replaced with a highly dissimilar artificial disordered sequence, supporting a sequence-independent inhibitory effect of the fuzzy region.

  8. Mutant analysis, protein-protein interactions and subcellular localization of the Arabidopsis B sister (ABS) protein.

    PubMed

    Kaufmann, Kerstin; Anfang, Nicole; Saedler, Heinz; Theissen, Günter

    2005-09-01

    Recently, close relatives of class B floral homeotic genes, termed B(sister) genes, have been identified in both angiosperms and gymnosperms. In contrast to the B genes themselves, B(sister) genes are exclusively expressed in female reproductive organs, especially in the envelopes or integuments surrounding the ovules. This suggests an important ancient function in ovule or seed development for B(sister) genes, which has been conserved for about 300 million years. However, investigation of the first loss-of-function mutant for a B(sister) gene (ABS/TT16 from Arabidopsis) revealed only a weak phenotype affecting endothelium formation. Here, we present an analysis of two additional mutant alleles, which corroborates this weak phenotype. Transgenic plants that ectopically express ABS show changes in the growth and identity of floral organs, suggesting that ABS can interact with floral homeotic proteins. Yeast-two-hybrid and three-hybrid analyses indicated that ABS can form dimers with SEPALLATA (SEP) floral homeotic proteins and multimeric complexes that also include the AGAMOUS-like proteins SEEDSTICK (STK) or SHATTERPROOF1/2 (SHP1, SHP2). These data suggest that the formation of multimeric transcription factor complexes might be a general phenomenon among MIKC-type MADS-domain proteins in angiosperms. Heterodimerization of ABS with SEP3 was confirmed by gel retardation assays. Fusion proteins tagged with CFP (Cyan Fluorescent Protein) and YFP (Yellow Fluorescent Protein) in Arabidopsis protoplasts showed that ABS is localized in the nucleus. Phylogenetic analysis revealed the presence of a structurally deviant, but closely related, paralogue of ABS in the Arabidopsis genome. Thus the evolutionary developmental genetics of B(sister) genes can probably only be understood as part of a complex and redundant gene network that may govern ovule formation in a conserved manner, which has yet to be fully explored.

  9. S-linked protein homocysteinylation: identifying targets based on structural, physicochemical and protein-protein interactions of homocysteinylated proteins.

    PubMed

    Silla, Yumnam; Sundaramoorthy, Elayanambi; Talwar, Puneet; Sengupta, Shantanu

    2013-05-01

    An elevated level of homocysteine, a thiol-containing amino acid is associated with a wide spectrum of disease conditions. A majority (>80 %) of the circulating homocysteine exist in protein-bound form. Homocysteine can bind to free cysteine residues in the protein or could cleave accessible cysteine disulfide bonds via thiol disulfide exchange reaction. Binding of homocysteine to proteins could potentially alter the structure and/or function of the protein. To date only 21 proteins have been experimentally shown to bind homocysteine. In this study we attempted to identify other proteins that could potentially bind to homocysteine based on the criteria that such proteins will have significant 3D structural homology with the proteins that have been experimentally validated and have solvent accessible cysteine residues either with high dihedral strain energy (for cysteine-cysteine disulfide bonds) or low pKa (for free cysteine residues). This analysis led us to the identification of 78 such proteins of which 68 proteins had 154 solvent accessible disulfide cysteine pairs with high dihedral strain energy and 10 proteins had free cysteine residues with low pKa that could potentially bind to homocysteine. Further, protein-protein interaction network was built to identify the interacting partners of these putative homocysteine binding proteins. We found that the 21 experimentally validated proteins had 174 interacting partners while the 78 proteins identified in our analysis had 445 first interacting partners. These proteins are mainly involved in biological activities such as complement and coagulation pathway, focal adhesion, ECM-receptor, ErbB signalling and cancer pathways, etc. paralleling the disease-specific attributes associated with hyperhomocysteinemia.

  10. Exploring Bacterial Organelle Interactomes: A Model of the Protein-Protein Interaction Network in the Pdu Microcompartment

    PubMed Central

    Jorda, Julien; Liu, Yu; Bobik, Thomas A.; Yeates, Todd O.

    2015-01-01

    Bacterial microcompartments (MCPs) are protein-bound organelles that carry out diverse metabolic pathways in a wide range of bacteria. These supramolecular assemblies consist of a thin outer protein shell, reminiscent of a viral capsid, which encapsulates sequentially acting enzymes. The most complex MCP elucidated so far is the propanediol utilizing (Pdu) microcompartment. It contains the reactions for degrading 1,2-propanediol. While several experimental studies on the Pdu system have provided hints about its organization, a clear picture of how all the individual components interact has not emerged yet. Here we use co-evolution-based methods, involving pairwise comparisons of protein phylogenetic trees, to predict the protein-protein interaction (PPI) network governing the assembly of the Pdu MCP. We propose a model of the Pdu interactome, from which selected PPIs are further inspected via computational docking simulations. We find that shell protein PduA is able to serve as a “universal hub” for targeting an array of enzymes presenting special N-terminal extensions, namely PduC, D, E, L and P. The varied N-terminal peptides are predicted to bind in the same cleft on the presumptive luminal face of the PduA hexamer. We also propose that PduV, a protein of unknown function with remote homology to the Ras-like GTPase superfamily, is likely to localize outside the MCP, interacting with the protruding β-barrel of the hexameric PduU shell protein. Preliminary experiments involving a bacterial two-hybrid assay are presented that corroborate the existence of a PduU-PduV interaction. This first systematic computational study aimed at characterizing the interactome of a bacterial microcompartment provides fresh insight into the organization of the Pdu MCP. PMID:25646976

  11. Characterizing alpha helical properties of Ebola viral proteins as potential targets for inhibition of alpha-helix mediated protein-protein interactions

    PubMed Central

    Chakraborty, Sandeep; Rao, Basuthkar J.; Asgeirsson, Bjarni; Dandekar, Abhaya

    2015-01-01

    Ebola, considered till recently as a rare and endemic disease, has dramatically transformed into a potentially global humanitarian crisis. The genome of Ebola, a member of the Filoviridae family, encodes seven proteins. Based on the recently implemented software (PAGAL) for analyzing the hydrophobicity and amphipathicity properties of alpha helices (AH) in proteins, we characterize the helices in the Ebola proteome. We demonstrate that AHs with characteristically unique features are involved in critical interactions with the host proteins. For example, the Ebola virus membrane fusion subunit, GP2, from the envelope glycoprotein ectodomain has an AH with a large hydrophobic moment. The neutralizing antibody (KZ52) derived from a human survivor of the 1995 Kikwit outbreak recognizes a protein epitope on this AH, emphasizing the critical nature of this secondary structure in the virulence of the Ebola virus. Our method ensures a comprehensive list of such `hotspots'. These helices probably are or can be the target of molecules designed to inhibit AH mediated protein-protein interactions. Further, by comparing the AHs in proteins of the related Marburg viruses, we are able to elicit subtle changes in the proteins that might render them ineffective to previously successful drugs. Such differences are difficult to identify by a simple sequence or structural alignment. Thus, analyzing AHs in the small Ebola proteome can aid rational design aimed at countering the `largest Ebola epidemic, affecting multiple countries in West Africa' ( http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/index.html). PMID:25717367

  12. Identification of novel candidate drivers connecting different dysfunctional levels for lung adenocarcinoma using protein-protein interactions and a shortest path approach

    PubMed Central

    Chen, Lei; Huang, Tao; Zhang, Yu-Hang; Jiang, Yang; Zheng, Mingyue; Cai, Yu-Dong

    2016-01-01

    Tumors are formed by the abnormal proliferation of somatic cells with disordered growth regulation under the influence of tumorigenic factors. Recently, the theory of “cancer drivers” connects tumor initiation with several specific mutations in the so-called cancer driver genes. According to the differentiation of four basic levels between tumor and adjacent normal tissues, the cancer drivers can be divided into the following: (1) Methylation level, (2) microRNA level, (3) mutation level, and (4) mRNA level. In this study, a computational method is proposed to identify novel lung adenocarcinoma drivers based on dysfunctional genes on the methylation, microRNA, mutation and mRNA levels. First, a large network was constructed using protein-protein interactions. Next, we searched all of the shortest paths connecting dysfunctional genes on different levels and extracted new candidate genes lying on these paths. Finally, the obtained candidate genes were filtered by a permutation test and an additional strict selection procedure involving a betweenness ratio and an interaction score. Several candidate genes remained, which are deemed to be related to two different levels of cancer. The analyses confirmed our assertions that some have the potential to contribute to the tumorigenesis process on multiple levels. PMID:27412431

  13. Identification of novel candidate drivers connecting different dysfunctional levels for lung adenocarcinoma using protein-protein interactions and a shortest path approach

    NASA Astrophysics Data System (ADS)

    Chen, Lei; Huang, Tao; Zhang, Yu-Hang; Jiang, Yang; Zheng, Mingyue; Cai, Yu-Dong

    2016-07-01

    Tumors are formed by the abnormal proliferation of somatic cells with disordered growth regulation under the influence of tumorigenic factors. Recently, the theory of “cancer drivers” connects tumor initiation with several specific mutations in the so-called cancer driver genes. According to the differentiation of four basic levels between tumor and adjacent normal tissues, the cancer drivers can be divided into the following: (1) Methylation level, (2) microRNA level, (3) mutation level, and (4) mRNA level. In this study, a computational method is proposed to identify novel lung adenocarcinoma drivers based on dysfunctional genes on the methylation, microRNA, mutation and mRNA levels. First, a large network was constructed using protein-protein interactions. Next, we searched all of the shortest paths connecting dysfunctional genes on different levels and extracted new candidate genes lying on these paths. Finally, the obtained candidate genes were filtered by a permutation test and an additional strict selection procedure involving a betweenness ratio and an interaction score. Several candidate genes remained, which are deemed to be related to two different levels of cancer. The analyses confirmed our assertions that some have the potential to contribute to the tumorigenesis process on multiple levels.

  14. Identification of Genes Associated with Breast Cancer Metastasis to Bone on a Protein-Protein Interaction Network with a Shortest Path Algorithm.

    PubMed

    Cai, Yu-Dong; Zhang, Qing; Zhang, Yu-Hang; Chen, Lei; Huang, Tao

    2017-02-03

    Tumor metastasis is defined as the spread of tumor cells from one organ or part to another that is not directly connected to it, which significantly contributes to the progression and aggravation of tumorigenesis. Because it always involves multiple organs, the metastatic process is difficult to study in its entirety. Complete identification of the genes related to this process is an alternative way to study metastasis. In this study, we developed a computational method to identify such genes. To test our method, we selected breast cancer bone metastasis. A large network was constructed using human protein-protein interactions. On the basis of the validated genes related to breast and bone cancer, a shortest path algorithm was applied to the network to search for novel genes that may mediate breast cancer metastasis to bone. In addition, further rules constructed using the permutation FDR, the betweenness ratio, and the max-min interaction score were also employed in the method to make the inferred genes more reliable. Eighteen putative genes were identified by the method and were extensively analyzed. The confirmation results indicate that these genes participate in metastasis.

  15. The PUB domain: a putative protein-protein interaction domain implicated in the ubiquitin-proteasome pathway.

    PubMed

    Suzuki, T; Park, H; Till, E A; Lennarz, W J

    2001-10-12

    Cytoplasmic peptide:N-glycanase (PNGase) is a de-N-glycosylating enzyme which may be involved in the proteasome-dependent pathway for degradation of misfolded glycoproteins formed in the endoplasmic reticulum (ER) that are exported into the cytoplasm. A cytoplasmic PNGase found in Saccharomyces cerevisiae, Png1p, is widely distributed in higher eukaryotes as well as in yeast (Suzuki, T., et al. J. Cell Biol. 149, 1039-1051, 2000). The recently uncovered complete genome sequence of Arabidopsis thaliana prompted us to search for the protein homologue of Png1p in this organism. Interestingly, when the mouse Png1p homologue sequence was used as a query, not only a Png1p homologue containing a transglutaminase-like domain that is believed to contain a catalytic triad for PNGase activity, but also four proteins which had a domain of 46 amino acids in length that exhibited significant similarity to the N-terminus of mouse Png1p were identified. Moreover, three of these homologous proteins were also found to possess a UBA or UBX domain, which are found in various proteins involved in the ubiquitin-related pathway. We name this newly found homologous region the PUB (Peptide:N-glycanase/UBA or UBX-containing proteins) domain and propose that this domain may mediate protein-protein interactions.

  16. The essential and downstream common proteins of amyotrophic lateral sclerosis: A protein-protein interaction network analysis

    PubMed Central

    Chen, Le; Heckman, C. J.

    2017-01-01

    Amyotrophic Lateral Sclerosis (ALS) is a devastative neurodegenerative disease characterized by selective loss of motoneurons. While several breakthroughs have been made in identifying ALS genetic defects, the detailed molecular mechanisms are still unclear. These genetic defects involve in numerous biological processes, which converge to a common destiny: motoneuron degeneration. In addition, the common comorbid Frontotemporal Dementia (FTD) further complicates the investigation of ALS etiology. In this study, we aimed to explore the protein-protein interaction network built on known ALS-causative genes to identify essential proteins and common downstream proteins between classical ALS and ALS+FTD (classical ALS + ALS/FTD) groups. The results suggest that classical ALS and ALS+FTD share similar essential protein set (VCP, FUS, TDP-43 and hnRNPA1) but have distinctive functional enrichment profiles. Thus, disruptions to these essential proteins might cause motoneuron susceptible to cellular stresses and eventually vulnerable to proteinopathies. Moreover, we identified a common downstream protein, ubiquitin-C, extensively interconnected with ALS-causative proteins (22 out of 24) which was not linked to ALS previously. Our in silico approach provides the computational background for identifying ALS therapeutic targets, and points out the potential downstream common ground of ALS-causative mutations. PMID:28282387

  17. Application of Genetic Programming (GP) Formalism for Building Disease Predictive Models from Protein-Protein Interactions (PPI) Data.

    PubMed

    Vyas, Renu; Bapat, Sanket; Goel, Purva; Karthikeyan, Muthukumarasamy; Tambe, Sanjeev S; Kulkarni, Bhaskar D

    2016-10-26

    Protein-protein interactions (PPIs) play a vital role in the biological processes involved in the cell functions and disease pathways. The experimental methods known to predict PPIs require tremendous efforts and the results are often hindered by the presence of a large number of false positives. Herein, we demonstrate the use of a new Genetic Programming (GP) based Symbolic Regression (SR) approach for predicting PPIs related to a disease. In a case study, a dataset consisting of one hundred and thirty five PPI complexes related to cancer was used to construct a generic PPI predicting model with good PPI prediction accuracy and generalization ability. A high correlation coefficient(CC) of 0.893, low root mean square error (RMSE) and mean absolute percentage error (MAPE) values of 478.221 and 0.239, respectively were achieved for both the training and test set outputs. To validate the discriminatory nature of the model, it was applied on a dataset of diabetes complexes where it yielded significantly low CC values. Thus, the GP model developed here serves a dual purpose: (a)a predictor of the binding energy of cancer related PPI complexes, and (b)a classifier for discriminating PPI complexes related to cancer from those of other diseases.

  18. Prediction of Protein-Protein Interaction Sites with Machine-Learning-Based Data-Cleaning and Post-Filtering Procedures.

    PubMed

    Liu, Guang-Hui; Shen, Hong-Bin; Yu, Dong-Jun

    2016-04-01

    Accurately predicting protein-protein interaction sites (PPIs) is currently a hot topic because it has been demonstrated to be very useful for understanding disease mechanisms and designing drugs. Machine-learning-based computational approaches have been broadly utilized and demonstrated to be useful for PPI prediction. However, directly applying traditional machine learning algorithms, which often assume that samples in different classes are balanced, often leads to poor performance because of the severe class imbalance that exists in the PPI prediction problem. In this study, we propose a novel method for improving PPI prediction performance by relieving the severity of class imbalance using a data-cleaning procedure and reducing predicted false positives with a post-filtering procedure: First, a machine-learning-based data-cleaning procedure is applied to remove those marginal targets, which may potentially have a negative effect on training a model with a clear classification boundary, from the majority samples to relieve the severity of class imbalance in the original training dataset; then, a prediction model is trained on the cleaned dataset; finally, an effective post-filtering procedure is further used to reduce potential false positive predictions. Stringent cross-validation and independent validation tests on benchmark datasets demonstrated the efficacy of the proposed method, which exhibits highly competitive performance compared with existing state-of-the-art sequence-based PPIs predictors and should supplement existing PPI prediction methods.

  19. Design of novel ligands of CDP-methylerythritol kinase by mimicking direct protein-protein and solvent-mediated interactions.

    PubMed

    Giménez-Oya, Victor; Villacañas, Oscar; Obiol-Pardo, Cristian; Antolin-Llovera, Meritxell; Rubio-Martinez, Jaime; Imperial, Santiago

    2011-01-01

    The methylerythritol 4-phosphate (MEP) pathway for the biosynthesis of the isoprenoid universal building blocks (isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP)) is present in most of human pathogens and is absent in animals, turning it into a promising therapeutic druggable pathway. Two different strategies, a pharmacophore-directed virtual screening and a protein-protein interaction (PPI)-mimicking cyclic peptide were used to search for compounds that bind to the PPI surface of the 4-(cytidine 5-diphospho)-2C-methyl-D-erythritol kinase (CMK), which catalyzes the fourth step of the MEP pathway. A significant part of the pharmacophore hypothesis used in this study was designed by mimicking water-mediated PPI relevant in the CMK homodimer complex stabilization. After database search and with the aid of docking and molecular dynamics (MD) simulations, a 7H-furo[3,2-g]chromen-7-one derivative and a cyclic peptide were chosen as candidates to be ligands of CMK. Their binding affinities were measured using surface plasmon resonance (SPR) technology.

  20. Prioritization of candidate genes for cattle reproductive traits, based on protein-protein interactions, gene expression, and text-mining.

    PubMed

    Hulsegge, Ina; Woelders, Henri; Smits, Mari; Schokker, Dirkjan; Jiang, Li; Sørensen, Peter

    2013-05-15

    Reproduction is of significant economic importance in dairy cattle. Improved understanding of mechanisms that control estrous behavior and other reproduction traits could help in developing strategies to improve and/or monitor these traits. The objective of this study was to predict and rank genes and processes in brain areas and pituitary involved in reproductive traits in cattle using information derived from three different data sources: gene expression, protein-protein interactions, and literature. We identified 59, 89, 53, 23, and 71 genes in bovine amygdala, dorsal hypothalamus, hippocampus, pituitary, and ventral hypothalamus, respectively, potentially involved in processes underlying estrus and estrous behavior. Functional annotation of the candidate genes points to a number of tissue-specific processes of which the "neurotransmitter/ion channel/synapse" process in the amygdala, "steroid hormone receptor activity/ion binding" in the pituitary, "extracellular region" in the ventral hypothalamus, and "positive regulation of transcription/metabolic process" in the dorsal hypothalamus are most prominent. The regulation of the functional processes in the various tissues operate at different biological levels, including transcriptional, posttranscriptional, extracellular, and intercellular signaling levels.

  1. Protein-Protein interaction networks: why static MpK model works and preferential attachment does not

    NASA Astrophysics Data System (ADS)

    Zhang, Jingshan; Shakhnovich, Eugene

    2007-03-01

    Various approaches have been proposed to explain the observed scale free structure p(k) ˜k^-γ of protein-protein interaction networks. We argue that the preferential attachment coming from gene duplication[1] is questionable. A static ``MpK'' model produces the scale free structure via computer simulations[2] for unexplained reasons. On the other hand, it was analytically proved[3] that deterministic threshold models produce scale free networks (with γ≡2) if fitness distributions are exponential. We study the static MpK model further and find the above analytical proof applicable with extensions, and γ dependent on the threshold parameter. This work not only predicts the dependence of γ on protein concentrations, but also provides a generic mechanism of scale free networks. The clustering coefficient distribution in the model is interpreted by a simple picture. [1] A.-L. Barab'asi and Z. N. Oltvai, Nature Reviews Genetics 5, 101 (2004). [2] E. J. Deeds, O. Ashenberg, E. I. Shakhnovich, Proc. Natl. Acad. Sci. USA 103, 311 (2006). [3] G. Caldarelli, A. Capocci, P. De Los Rios, and M. A. Muñoz, Phys. Rev. Lett. 89, 258702 (2002).

  2. Mechanism of Enzymatic Reaction and Protein-Protein Interactions of PLD from a 3D Structural Model

    PubMed Central

    Mahankali, Madhu; Alter, Gerald; Gomez-Cambronero, Julian

    2014-01-01

    The phospholipase D (PLD) superfamily catalyzes the hydrolysis of cell membrane phospholipids generating the key intracellular lipid second messenger phosphatidic acid. However, there is not yet any resolved structure either from a crystallized protein or from NMR of any mammalian PLDs. We propose here a 3D model of the PLD2 by combining homology and ab initio 3 dimensional structural modeling methods, and docking conformation. This model is in agreement with the biochemical and physiological behavior of PLD in cells. For the lipase activity, the N- and C-terminal histidines of the HKD motifs (His 442/His 756) form a catalytic pocket, which accommodates phosphatidylcholine head group (but not phosphatidylethanolamine or phosphatidyl serine). The model explains the mechanism of the reaction catalysis, with nucleophilic attacks of His 442 and water, the latter aided by His 756. Further, the secondary structure regions superimposed with bacterial PLD crystal structure, which indicated an agreement structure model obtained. It also explains protein-protein interactions, such as PLD2-Rac2 transmodulation (with a 1:2 stoichiometry), PLD2 GEF activity on Rac2 that is relevant for actin polymerization and cell migration, and a biding site for phosphoinositides. Since tumor-aggravating properties have been found in mice overexpressing PLD2 enzyme, the 3D model of PLD2 will be also useful, to a large extent, in developing pharmaceuticals to modulate its in vivo activity. PMID:25308783

  3. A split horseradish peroxidase for detection of intercellular protein-protein interactions and sensitive visualization of synapses

    PubMed Central

    Martell, Jeffrey D.; Yamagata, Masahito; Deerinck, Thomas J.; Phan, Sébastien; Kwa, Carolyn G.; Ellisman, Mark H.; Sanes, Joshua R.; Ting, Alice Y.

    2016-01-01

    Intercellular protein-protein interactions (PPIs) enable communication between cells in diverse biological processes, including cell proliferation, immune responses, infection and synaptic transmission, but they are challenging to visualize because existing techniques1,2,3 have insufficient sensitivity and/or specificity. Here we report split horseradish peroxidase (sHRP) as a sensitive and specific tool for detection of intercellular PPIs. The two sHRP fragments, engineered through screening of 17 cut sites in HRP followed by directed evolution, reconstitute into an active form when driven together by an intercellular PPI, producing bright fluorescence or contrast for electron microscopy. Fusing the sHRP fragments to the proteins neurexin (NRX) and neuroligin (NLG), which bind each other across the synaptic cleft4, enabled sensitive visualization of synapses between specific sets of neurons, including two classes of synapses in the mouse visual system. sHRP should be widely applicable for studying mechanisms of communication between a variety of cell types. PMID:27240195

  4. Prioritizing disease candidate proteins in cardiomyopathy-specific protein-protein interaction networks based on "guilt by association" analysis.

    PubMed

    Li, Wan; Chen, Lina; He, Weiming; Li, Weiguo; Qu, Xiaoli; Liang, Binhua; Gao, Qianping; Feng, Chenchen; Jia, Xu; Lv, Yana; Zhang, Siya; Li, Xia

    2013-01-01

    The cardiomyopathies are a group of heart muscle diseases which can be inherited (familial). Identifying potential disease-related proteins is important to understand mechanisms of cardiomyopathies. Experimental identification of cardiomyophthies is costly and labour-intensive. In contrast, bioinformatics approach has a competitive advantage over experimental method. Based on "guilt by association" analysis, we prioritized candidate proteins involving in human cardiomyopathies. We first built weighted human cardiomyopathy-specific protein-protein interaction networks for three subtypes of cardiomyopathies using the known disease proteins from Online Mendelian Inheritance in Man as seeds. We then developed a method in prioritizing disease candidate proteins to rank candidate proteins in the network based on "guilt by association" analysis. It was found that most candidate proteins with high scores shared disease-related pathways with disease seed proteins. These top ranked candidate proteins were related with the corresponding disease subtypes, and were potential disease-related proteins. Cross-validation and comparison with other methods indicated that our approach could be used for the identification of potentially novel disease proteins, which may provide insights into cardiomyopathy-related mechanisms in a more comprehensive and integrated way.

  5. A High-Throughput Screening Strategy for Development of RNF8-Ubc13 Protein-Protein Interaction Inhibitors.

    PubMed

    Weber, Elisabeth; Rothenaigner, Ina; Brandner, Stefanie; Hadian, Kamyar; Schorpp, Kenji

    2017-03-01

    The ubiquitin-proteasome system plays an essential role in a broad range of cellular signaling pathways. Ubiquitination is a posttranslational protein modification that involves the action of an enzymatic cascade (E1, E2, and E3 enzymes) for the covalent attachment of ubiquitin to target proteins. The emerging knowledge of the molecular mechanisms and correlation of deregulation of the ubiquitin system in human diseases is uncovering new opportunities for therapeutics development. The E3 ligase RNF8 acts in cooperation with the heterodimeric E2 enzyme Ubc13/Uev1a to generate ubiquitin conjugates at the sides of DNA double-strand breaks, and recent findings suggest RNF8 as a potential therapeutic target for the treatment of breast cancer. Here, we present a novel high-throughput screening (HTS)-compatible assay based on the AlphaScreen technology to identify inhibitors of the RNF8-Ubc13 protein-protein interaction, along with a follow-up strategy for subsequent validation. We have adapted the AlphaScreen assay to a 384-well format and demonstrate its reliability, reproducibility, and suitability for automated HTS campaigns. In addition, we have established a biochemical orthogonal homogeneous time-resolved fluorescence (HTRF) assay in HTS format and a cellular microscopy-based assay allowing verification of the primary hits. This strategy will be useful for drug screening programs aimed at RNF8-Ubc13 modulation.

  6. The essential and downstream common proteins of amyotrophic lateral sclerosis: A protein-protein interaction network analysis.

    PubMed

    Mao, Yimin; Kuo, Su-Wei; Chen, Le; Heckman, C J; Jiang, M C

    2017-01-01

    Amyotrophic Lateral Sclerosis (ALS) is a devastative neurodegenerative disease characterized by selective loss of motoneurons. While several breakthroughs have been made in identifying ALS genetic defects, the detailed molecular mechanisms are still unclear. These genetic defects involve in numerous biological processes, which converge to a common destiny: motoneuron degeneration. In addition, the common comorbid Frontotemporal Dementia (FTD) further complicates the investigation of ALS etiology. In this study, we aimed to explore the protein-protein interaction network built on known ALS-causative genes to identify essential proteins and common downstream proteins between classical ALS and ALS+FTD (classical ALS + ALS/FTD) groups. The results suggest that classical ALS and ALS+FTD share similar essential protein set (VCP, FUS, TDP-43 and hnRNPA1) but have distinctive functional enrichment profiles. Thus, disruptions to these essential proteins might cause motoneuron susceptible to cellular stresses and eventually vulnerable to proteinopathies. Moreover, we identified a common downstream protein, ubiquitin-C, extensively interconnected with ALS-causative proteins (22 out of 24) which was not linked to ALS previously. Our in silico approach provides the computational background for identifying ALS therapeutic targets, and points out the potential downstream common ground of ALS-causative mutations.

  7. Molecular Dynamics Simulations and Structural Analysis of Giardia duodenalis 14-3-3 Protein-Protein Interactions.

    PubMed

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

    2015-12-28

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

  8. Lectin Receptor Kinases Participate in Protein-Protein Interactions to Mediate Plasma Membrane-Cell Wall Adhesions in Arabidopsis1

    PubMed Central

    Gouget, Anne; Senchou, Virginie; Govers, Francine; Sanson, Arnaud; Barre, Annick; Rougé, Pierre; Pont-Lezica, Rafael; Canut, Hervé

    2006-01-01

    Interactions between plant cell walls and plasma membranes are essential for cells to function properly, but the molecules that mediate the structural continuity between wall and membrane are unknown. Some of these interactions, which are visualized upon tissue plasmolysis in Arabidopsis (Arabidopsis thaliana), are disrupted by the RGD (arginine-glycine-aspartic acid) tripeptide sequence, a characteristic cell adhesion motif in mammals. In planta induced-O (IPI-O) is an RGD-containing protein from the plant pathogen Phytophthora infestans that can disrupt cell wall-plasma membrane adhesions through its RGD motif. To identify peptide sequences that specifically bind the RGD motif of the IPI-O protein and potentially play a role in receptor recognition, we screened a heptamer peptide library displayed in a filamentous phage and selected two peptides acting as inhibitors of the plasma membrane RGD-binding activity of Arabidopsis. Moreover, the two peptides also disrupted cell wall-plasma membrane adhesions. Sequence comparison of the RGD-binding peptides with the Arabidopsis proteome revealed 12 proteins containing amino acid sequences in their extracellular domains common with the two RGD-binding peptides. Eight belong to the receptor-like kinase family, four of which have a lectin-like extracellular domain. The lectin domain of one of these, At5g60300, recognized the RGD motif both in peptides and proteins. These results imply that lectin receptor kinases are involved in protein-protein interactions with RGD-containing proteins as potential ligands, and play a structural and signaling role at the plant cell surfaces. PMID:16361528

  9. Lectin receptor kinases participate in protein-protein interactions to mediate plasma membrane-cell wall adhesions in Arabidopsis.

    PubMed

    Gouget, Anne; Senchou, Virginie; Govers, Francine; Sanson, Arnaud; Barre, Annick; Rougé, Pierre; Pont-Lezica, Rafael; Canut, Hervé

    2006-01-01

    Interactions between plant cell walls and plasma membranes are essential for cells to function properly, but the molecules that mediate the structural continuity between wall and membrane are unknown. Some of these interactions, which are visualized upon tissue plasmolysis in Arabidopsis (Arabidopsis thaliana), are disrupted by the RGD (arginine-glycine-aspartic acid) tripeptide sequence, a characteristic cell adhesion motif in mammals. In planta induced-O (IPI-O) is an RGD-containing protein from the plant pathogen Phytophthora infestans that can disrupt cell wall-plasma membrane adhesions through its RGD motif. To identify peptide sequences that specifically bind the RGD motif of the IPI-O protein and potentially play a role in receptor recognition, we screened a heptamer peptide library displayed in a filamentous phage and selected two peptides acting as inhibitors of the plasma membrane RGD-binding activity of Arabidopsis. Moreover, the two peptides also disrupted cell wall-plasma membrane adhesions. Sequence comparison of the RGD-binding peptides with the Arabidopsis proteome revealed 12 proteins containing amino acid sequences in their extracellular domains common with the two RGD-binding peptides. Eight belong to the receptor-like kinase family, four of which have a lectin-like extracellular domain. The lectin domain of one of these, At5g60300, recognized the RGD motif both in peptides and proteins. These results imply that lectin receptor kinases are involved in protein-protein interactions with RGD-containing proteins as potential ligands, and play a structural and signaling role at the plant cell surfaces.

  10. Identification of Protein-Protein Interactions and Topologies in Living Cells with Chemical Cross-linking and Mass Spectrometry*S⃞

    PubMed Central

    Zhang, Haizhen; Tang, Xiaoting; Munske, Gerhard R.; Tolic, Nikola; Anderson, Gordon A.; Bruce, James E.

    2009-01-01

    We present results from a novel strategy that enables concurrent identification of protein-protein interactions and topologies in living cells without specific antibodies or genetic manipulations for immuno-/affinity purifications. The strategy consists of (i) a chemical cross-linking reaction: intact cell labeling with a novel class of chemical cross-linkers, protein interaction reporters (PIRs); (ii) two-stage mass spectrometric analysis: stage 1 identification of PIR-labeled proteins and construction of a restricted database by two-dimensional LC/MSMS and stage 2 analysis of PIR-labeled peptides by multiplexed LC/FTICR-MS; and (iii) data analysis: identification of cross-linked peptides and proteins of origin using accurate mass and other constraints. The primary advantage of the PIR approach and distinction from current technology is that protein interactions together with topologies are detected in native biological systems by stabilizing protein complexes with new covalent bonds while the proteins are present in the original cellular environment. Thus, weak or transient interactions or interactions that require properly folded, localized, or membrane-bound proteins can be labeled and identified through the PIR approach. This strategy was applied to Shewanella oneidensis bacterial cells, and initial studies resulted in identification of a set of protein-protein interactions and their contact/binding regions. Furthermore most identified interactions involved membrane proteins, suggesting that the PIR approach is particularly suited for studies of membrane protein-protein interactions, an area under-represented with current widely used approaches. PMID:18936057

  11. A Chemically Inducible Helper Module for Detecting Protein-Protein Interactions with Tunable Sensitivity Based on KIPPIS.

    PubMed

    Kashima, Daiki; Kawade, Raiji; Nagamune, Teruyuki; Kawahara, Masahiro

    2017-04-13

    As protein-protein interactions (PPIs) play essential roles in regulating their functional consequences in cells, methods to detect PPIs in living cells are desired for correct understanding of intracellular PPIs and pharmaceutical development therefrom. Here we demonstrate a c-kit-based PPI screening (KIPPIS) system in combination with a chemically inducible helper module for detecting PPIs in living mammalian cells. In this system, a mutant of FK506-binding protein 12 (FKBPF36 V) is fused with a protein of interest and the intracellular domain of a receptor tyrosine kinase c-kit. Constitutive expression of two fusion proteins with interacting proteins of interest in interleukin-3 (IL-3)-dependent cells results in dimerization and subsequent activation of the c-kit intracellular domains, which allows cell proliferation in a culture medium devoid of IL-3. A helper ligand, a small synthetic chemical that homodimerizes FKBPF36 V, assists the formation of stable complexes of the fusion proteins and serves as a tuner for sensitivity of the system. Using this system, two model PPIs were successfully detected on the basis of cell proliferation, which was featured by the helper-ligand- and PPI-dependent phosphorylation of the Src family kinases, a hallmark of the c-kit signaling. Notably, the inclusion of the helper module enabled PPI detection with tunable sensitivity. The helper-assisted KIPPIS allows us to configure various affinity thresholds by changing the concentration of the helper ligand, which may be applied to select affinity-matured variants using the advantage of cell proliferation.

  12. Construction and analysis of the protein-protein interaction networks for schizophrenia, bipolar disorder, and major depression

    PubMed Central

    2011-01-01

    Background Schizophrenia, bipolar disorder, and major depression are devastating mental diseases, each with distinctive yet overlapping epidemiologic characteristics. Microarray and proteomics data have revealed genes which expressed abnormally in patients. Several single nucleotide polymorphisms (SNPs) and mutations are associated with one or more of the three diseases. Nevertheless, there are few studies on the interactions among the disease-associated genes and proteins. Results This study, for the first time, incorporated microarray and protein-protein interaction (PPI) databases to construct the PPI network of abnormally expressed genes in postmortem brain samples of schizophrenia, bipolar disorder, and major depression patients. The samples were collected from Brodmann area (BA) 10 of the prefrontal cortex. Abnormally expressed disease genes were selected by t-tests comparing the disease and control samples. These genes were involved in housekeeping functions (e.g. translation, transcription, energy conversion, and metabolism), in brain specific functions (e.g. signal transduction, neuron cell differentiation, and cytoskeleton), or in stress responses (e.g. heat shocks and biotic stress). The diseases were interconnected through several “switchboard”-like nodes in the PPI network or shared abnormally expressed genes. A “core” functional module which consisted of a tightly knitted sub-network of clique-5 and -4s was also observed. These cliques were formed by 12 genes highly expressed in both disease and control samples. Conclusions Several previously unidentified disease marker genes and drug targets, such as SBNO2 (schizophrenia), SEC24C (bipolar disorder), and SRRT (major depression), were identified based on statistical and topological analyses of the PPI network. The shared or interconnecting marker genes may explain the shared symptoms of the studied diseases. Furthermore, the “switchboard” genes, such as APP, UBC, and YWHAZ, are proposed as

  13. De novo designed library of linear helical peptides: an exploratory tool in the discovery of protein-protein interaction modulators.

    PubMed

    Bonache, M Ángeles; Balsera, Beatriz; López-Méndez, Blanca; Millet, Oscar; Brancaccio, Diego; Gómez-Monterrey, Isabel; Carotenuto, Alfonso; Pavone, Luigi M; Reille-Seroussi, Marie; Gagey-Eilstein, Nathalie; Vidal, Michel; de la Torre-Martinez, Roberto; Fernández-Carvajal, Asia; Ferrer-Montiel, Antonio; García-López, M Teresa; Martín-Martínez, Mercedes; de Vega, M Jesús Pérez; González-Muñiz, Rosario

    2014-05-12

    Protein-protein interactions (PPIs) have emerged as important targets for pharmaceutical intervention because of their essential role in numerous physiological and pathological processes, but screening efforts using small-molecules have led to very low hit rates. Linear peptides could represent a quick and effective approach to discover initial PPI hits, particularly if they have inherent ability to adopt specific peptide secondary structures. Here, we address this hypothesis through a linear helical peptide library, composed of four sublibraries, which was designed by theoretical predictions of helicity (Agadir software). The 13-mer peptides of this collection fixes either a combination of three aromatic or two aromatic and one aliphatic residues on one face of the helix (Ac-SSEEX(5)ARNX(9)AAX(12)N-NH2), since these are structural features quite common at PPIs interfaces. The 81 designed peptides were conveniently synthesized by parallel solid-phase methodologies, and the tendency of some representative library components to adopt the intended secondary structure was corroborated through CD and NMR experiments. As proof of concept in the search for PPI modulators, the usefulness of this library was verified on the widely studied p53-MDM2 interaction and on the communication between VEGF and its receptor Flt-1, two PPIs for which a hydrophobic α-helix is essential for the interaction. We have demonstrated here that, in both cases, selected peptides from the library, containing the right hydrophobic sequence of the hot-spot in one of the protein partners, are able to interact with the complementary protein. Moreover, we have discover some new, quite potent inhibitors of the VEGF-Flt-1 interaction, just by replacing one of the aromatic residues of the initial F(5)Y(9)Y(12) peptide by W, in agreement with previous results on related antiangiogenic peptides. Finally, the HTS evaluation of the full collection on thermoTRPs has led to a few antagonists of TRPV1 and TRPA

  14. Protein fragment bimolecular fluorescence complementation analyses for the in vivo study of protein-protein interactions and cellular protein complex localizations

    PubMed Central

    Waadt, Rainer; Schlücking, Kathrin; Schroeder, Julian I.; Kudla, Jörg

    2014-01-01

    Summary The analyses of protein-protein interactions is crucial for understanding cellular processes including signal transduction, protein trafficking and movement. Protein fragment complementation assays are based on the reconstitution of protein function when non-active protein fragments are brought together by interacting proteins that were genetically fused to these protein fragments. Bimolecular fluorescence complementation (BiFC) relies on the reconstitution of fluorescent proteins and enables both the analysis of protein-protein interactions and the visualization of protein complex formations in vivo. Transient expression of proteins is a convenient approach to study protein functions in planta or in other organisms, and minimizes the need for time-consuming generation of stably expressing transgenic organisms. Here we describe protocols for BiFC analyses in Nicotiana benthamiana and Arabidopsis thaliana leaves transiently transformed by Agrobacterium infiltration. Further we discuss different BiFC applications and provide examples for proper BiFC analyses in planta. PMID:24057390

  15. Analysis of origin and protein-protein interaction maps suggests distinct oncogenic role of nuclear EGFR during cancer evolution

    PubMed Central

    Sharip, Ainur; Abdukhakimova, Diyora; Wang, Xiao; Kim, Alexey; Kim, Yevgeniy; Sharip, Aigul; Orakov, Askarbek; Miao, Lixia; Sun, Qinglei; Chen, Yue; Chen, Zhenbang; Xie, Yingqiu

    2017-01-01

    Receptor tyrosine kinase EGFR usually is localized on plasma membrane to induce progression of many cancers including cancers in children (Bodey et al. In Vivo. 2005, 19:931-41), but it contains a nuclear localization signal (NLS) that mediates EGFR nuclear translocation (Lin et al. Nat Cell Biol. 2001, 3:802-8). Here we report that NLS of EGFR has its old evolutionary origin. Protein-protein interaction maps suggests that nEGFR pathways are different from membrane EGFR and EGF is not found in nEGFR network while androgen receptor (AR) is found, which suggests the evolution of prostate cancer, a well-known AR driven cancer, through changes in androgen- or EGF-dependence. Database analysis suggests that nEGFR correlates with the tumor grades especially in prostate cancer patients. Structural predication analysis suggests that NLS can compromise the differential protein binding to EGFR through stretch linkers with evolutionary mutation from N to V. In experiment, elevation of nEGFR but not membrane EGFR was found in castration resistant prostate cancer cells. Finally, systems analysis of NLS and transmembrane domain (TM) suggests that NLS has old origin while NLS neighboring domain of TM has been undergone accelerated evolution. Thus nEGFR has an old origin resembling the cancer evolution but TM may interfere with NLS driven signaling for natural selection of survival to evade NLS induced aggressive cancers. Our data suggest NLS is a dynamic inducer of EGFR oncogenesis during evolution for advanced cancers. Our model provides novel insights into the evolutionary role of NLS of oncogenic kinases in cancers. PMID:28382154

  16. Targeting the K-Ras/PDEδ protein-protein interaction: the solution for Ras-driven cancers or just another therapeutic mirage?

    PubMed

    Frett, Brendan; Wang, Yuanxiang; Li, Hong-Yu

    2013-10-01

    The holy grail, finally? After years of unsuccessful attempts at drugging the Ras oncogene, a recent paper by Zimmerman et al. has revealed the possibility of inhibiting Ras signaling on a clinically relevant level by blocking the K-Ras/PDEδ protein-protein interaction. The results, reported in Nature, are highlighted herein with future implications and directions to evaluate the full clinical potential of this research.

  17. Detection and analysis of protein-protein interactions in organellar and prokaryotic proteomes by native gel electrophoresis: (Membrane) protein complexes and supercomplexes.

    PubMed

    Krause, Frank

    2006-07-01

    It is an essential and challenging task to unravel protein-protein interactions in their actual in vivo context. Native gel systems provide a separation platform allowing the analysis of protein complexes on a rather proteome-wide scale in a single experiment. This review focus on blue-native (BN)-PAGE as the most versatile and successful gel-based approach to separate soluble and membrane protein complexes of intricate protein mixtures derived from all biological sources. BN-PAGE is a charge-shift method with a running pH of 7.5 relying on the gentle binding of anionic CBB dye to all membrane and many soluble protein complexes, leading to separation of protein species essentially according to their size and superior resolution than other fractionation techniques can offer. The closely related colorless-native (CN)-PAGE, whose applicability is restricted to protein species with intrinsic negative net charge, proved to provide an especially mild separation capable of preserving weak protein-protein interactions better than BN-PAGE. The essential conditions determining the success of detecting protein-protein interactions are the sample preparations, e.g. the efficiency/mildness of the detergent solubilization of membrane protein complexes. A broad overview about the achievements of BN- and CN-PAGE studies to elucidate protein-protein interactions in organelles and prokaryotes is presented, e.g. the mitochondrial protein import machinery and oxidative phosphorylation supercomplexes. In many cases, solubilization with digitonin was demonstrated to facilitate an efficient and particularly gentle extraction of membrane protein complexes prone to dissociation by treatment with other detergents. In general, analyses of protein interactomes should be carried out by both BN- and CN-PAGE.

  18. Enabling systematic interrogation of protein-protein interactions in live cells with a versatile ultra-high-throughput biosensor platform | Office of Cancer Genomics

    Cancer.gov

    The vast datasets generated by next generation gene sequencing and expression profiling have transformed biological and translational research. However, technologies to produce large-scale functional genomics datasets, such as high-throughput detection of protein-protein interactions (PPIs), are still in early development. While a number of powerful technologies have been employed to detect PPIs, a singular PPI biosensor platform featured with both high sensitivity and robustness in a mammalian cell environment remains to be established.

  19. Property Focused Structure-Based Optimization of Small Molecule Inhibitors of the Protein-Protein Interaction between Menin and Mixed Lineage Leukemia (MLL).

    PubMed

    Borkin, Dmitry; Pollock, Jonathan; Kempinska, Katarzyna; Purohit, Trupta; Li, Xiaoqin; Wen, Bo; Zhao, Ting; Miao, Hongzhi; Shukla, Shirish; He, Miao; Sun, Duxin; Cierpicki, Tomasz; Grembecka, Jolanta

    2016-02-11

    Development of potent small molecule inhibitors of protein-protein interactions with optimized druglike properties represents a challenging task in lead optimization process. Here, we report synthesis and structure-based optimization of new thienopyrimidine class of compounds, which block the protein-protein interaction between menin and MLL fusion proteins that plays an important role in acute leukemias with MLL translocations. We performed simultaneous optimization of both activity and druglike properties through systematic exploration of substituents introduced to the indole ring of lead compound 1 (MI-136) to identify compounds suitable for in vivo studies in mice. This work resulted in the identification of compound 27 (MI-538), which showed significantly increased activity, selectivity, polarity, and pharmacokinetic profile over 1 and demonstrated a pronounced effect in a mouse model of MLL leukemia. This study, which reports detailed structure-activity and structure-property relationships for the menin-MLL inhibitors, demonstrates challenges in optimizing inhibitors of protein-protein interactions for potential therapeutic applications.

  20. Flow Cytometric Single-Cell Analysis for Quantitative in Vivo Detection of Protein-Protein Interactions via Relative Reporter Protein Expression Measurement.

    PubMed

    Wu, Lina; Wang, Xu; Zhang, Jianqiang; Luan, Tian; Bouveret, Emmanuelle; Yan, Xiaomei

    2017-03-07

    Cell-based two-hybrid assays have been key players in identifying pairwise interactions, yet quantitative measurement of protein-protein interactions in vivo remains challenging. Here, we show that by using relative reporter protein expression (RRPE), defined as the level of reporter expression normalized to that of the interacting protein, quantitative analysis of protein interactions in a bacterial adenylate cyclase two-hybrid (BACTH) system can be achieved. A multicolor flow cytometer was used to measure simultaneously the expression levels of one of the two putative interacting proteins and the β-galactosidase (β-gal) reporter protein upon dual immunofluorescence staining. Single-cell analysis revealed that there exists bistability in the BACTH system and the RRPE is an intrinsic characteristic associated with the binding strength between the two interacting proteins. The RRPE-BACTH method provides an efficient tool to confirm interacting pairs of proteins, investigate determinant residues in protein-protein interaction, and compare interaction strength of different pairs.

  1. Design, synthesis, and validation of a β-turn mimetic library targeting protein-protein and peptide-receptor interactions.

    PubMed

    Whitby, Landon R; Ando, Yoshio; Setola, Vincent; Vogt, Peter K; Roth, Bryan L; Boger, Dale L

    2011-07-06

    The design and synthesis of a β-turn mimetic library as a key component of a small-molecule library targeting the major recognition motifs involved in protein-protein interactions is described. Analysis of a geometric characterization of 10,245 β-turns in the protein data bank (PDB) suggested that trans-pyrrolidine-3,4-dicarboxamide could serve as an effective and synthetically accessible library template. This was confirmed by initially screening select compounds against a series of peptide-activated GPCRs that recognize a β-turn structure in their endogenous ligands. This validation study was highlighted by identification of both nonbasic and basic small molecules with high affinities (K(i) = 390 and 23 nM, respectively) for the κ-opioid receptor (KOR). Consistent with the screening capabilities of collaborators and following the design validation, the complete library was assembled as 210 mixtures of 20 compounds, providing a total of 4200 compounds designed to mimic all possible permutations of 3 of the 4 residues in a naturally occurring β-turn. Unique to the design and because of the C(2) symmetry of the template, a typical 20 × 20 × 20-mix (8000 compounds prepared as 400 mixtures of 20 compounds) needed to represent 20 variations in the side chains of three amino acid residues reduces to a 210 × 20-mix, thereby simplifying the library synthesis and subsequent screening. The library was prepared using a solution-phase synthetic protocol with liquid-liquid or liquid-solid extractions for purification and conducted on a scale that insures its long-term availability for screening campaigns. Screening the library against the human opioid receptors (KOR, MOR, and DOR) identified not only the activity of library members expected to mimic the opioid receptor peptide ligands but also additional side-chain combinations that provided enhanced receptor binding selectivities (>100-fold) and affinities (as low as K(i) = 80 nM for KOR). A key insight to emerge from

  2. Protein-protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM.

    PubMed

    Sriwastava, Brijesh Kumar; Basu, Subhadip; Maulik, Ujjwal

    2015-10-01

    Protein-protein interaction (PPI) site prediction aids to ascertain the interface residues that participate in interaction processes. Fuzzy support vector machine (F-SVM) is proposed as an effective method to solve this problem, and we have shown that the performance of the classical SVM can be enhanced with the help of an interaction-affinity based fuzzy membership function. The performances of both SVM and F-SVM on the PPI databases of the Homo sapiens and E. coli organisms are evaluated and estimated the statistical significance of the developed method over classical SVM and other fuzzy membership-based SVM methods available in the literature. Our membership function uses the residue-level interaction affinity scores for each pair of positive and negative sequence fragments. The average AUC scores in the 10-fold cross-validation experiments are measured as 79.94% and 80.48% for the Homo sapiens and E. coli organisms respectively. On the independent test datasets, AUC scores are obtained as 76.59% and 80.17% respectively for the two organisms. In almost all cases, the developed F-SVM method improves the performances obtained by the corresponding classical SVM and the other classifiers, available in the literature.

  3. Protein-Protein Interactions in the Yeast Pheromone Response Pathway: Ste5p Interacts with All Members of the Map Kinase Cascade

    PubMed Central

    Printen, J. A.; Sprague-Jr., G. F.

    1994-01-01

    We have used the two-hybrid system of Fields and Song to identify protein-protein interactions that occur in the pheromone response pathway of the yeast Saccharomyces cerevisiae. Pathway components Ste4p, Ste5p, Ste7p, Ste11p, Ste12p, Ste20p, Fus3p and Kss1p were tested in all pairwise combinations. All of the interactions we detected involved at least one member of the MAP kinase cascade that is a central element of the response pathway. Ste5p, a protein of unknown biochemical function, interacted with protein kinases that operate at each step of the MAP kinase cascade, specifically with Ste11p (an MEKK), Ste7p (an MEK), and Fus3p (a MAP kinase). This finding suggests that one role of Ste5p is to serve as a scaffold to facilitate interactions among members of the kinase cascade. In this role as facilitator, Ste5p may make both signal propagation and signal attenuation more efficient. Ste5p may also help minimize cross-talk with other MAP kinase cascades and thus ensure the integrity of the pheromone response pathway. We also found that both Ste11p and Ste7p interact with Fus3p and Kss1p. Finally, we detected an interaction between one of the MAP kinases, Kss1p, and a presumptive target, the transcription factor Ste12p. We failed to detect interactions of Ste4p or Ste20p with any other component of the response pathway. PMID:7851759

  4. The isolation, total synthesis and structure elucidation of chlorofusin, a natural product inhibitor of the p53-MDM2 protein-protein interaction

    PubMed Central

    Clark, Ryan C.; Lee, Sang Yeul; Searcey, Mark; Boger, Dale L.

    2009-01-01

    Inhibitors of key protein-protein interactions are emerging as exciting therapeutic targets for the treatment of cancer. One such interaction between MDM2 (HDM2) and p53, that silences the tumour suppression activities of p53, was found to be inhibited by the recently isolated natural product chlorofusin. Synthetic studies on this complex natural product summarized herein have served to reassign its chromophore relative stereochemistry, assign its absolute stereochemistry, and provided access to a series of key analogues and partial structures for biological evaluation. PMID:19642417

  5. NMR Identification of the Binding Surfaces Involved in the Salmonella and Shigella Type III Secretion Tip-Translocon Protein-Protein Interactions

    PubMed Central

    McShan, Andrew C.; Kaur, Kawaljit; Chatterjee, Srirupa; Knight, Kevin M.; De Guzman, Roberto N.

    2017-01-01

    The type III secretion system (T3SS) is essential for the pathogenesis of many bacteria including Salmonella and Shigella, which together are responsible for millions of deaths worldwide each year. The structural component of the T3SS consists of the needle apparatus, which is assembled in part by the protein-protein interaction between the tip and the translocon. The atomic detail of the interaction between the tip and the translocon proteins is currently unknown. Here, we used NMR methods to identify that the N-terminal domain of the Salmonella SipB translocon protein interacts with the SipD tip protein at a surface at the distal region of the tip formed by the mixed α/β domain and a portion of its coiled-coil domain. Likewise, the Shigella IpaB translocon protein and the IpaD tip protein interact with each other using similar surfaces identified for the Salmonella homologs. Furthermore, removal of the extreme N-terminal residues of the translocon protein, previously thought to be important for the interaction, had little change on the binding surface. Finally, mutations at the binding surface of SipD reduced invasion of Salmonella into human intestinal epithelial cells. Together, these results reveal the binding surfaces involved in the tip-translocon protein-protein interaction and advance our understanding of the assembly of the T3SS needle apparatus. PMID:27093649

  6. New protein-protein interactions identified for the regulatory and structural components and substrates of the type III Secretion system of the phytopathogen Xanthomonas axonopodis Pathovar citri.

    PubMed

    Alegria, Marcos C; Docena, Cassia; Khater, Leticia; Ramos, Carlos H I; da Silva, Ana C R; Farah, Chuck S

    2004-09-01

    We have initiated a project to identify protein-protein interactions involved in the pathogenicity of the bacterial plant pathogen Xanthomonas axonopodis pv. citri. Using a yeast two-hybrid system based on Gal4 DNA-binding and activation domains, we have focused on identifying interactions involving subunits, regulators, and substrates of the type III secretion system coded by the hrp (for hypersensitive response and pathogenicity), hrc (for hrp conserved), and hpa (for hrp associated) genes. We have identified several previously uncharacterized interactions involving (i) HrpG, a two-component system response regulator responsible for the expression of X. axonopodis pv. citri hrp operons, and XAC0095, a previously uncharacterized protein encountered only in Xanthomonas spp.; (ii) HpaA, a protein secreted by the type III secretion system, HpaB, and the C-terminal domain of HrcV; (iii) HrpB1, HrpD6, and HrpW; and (iv) HrpB2 and HrcU. Homotropic interactions were also identified for the ATPase HrcN. These newly identified protein-protein interactions increase our understanding of the functional integration of phytopathogen-specific type III secretion system components and suggest new hypotheses regarding the molecular mechanisms underlying Xanthomonas pathogenicity.

  7. Expression of domains for protein-protein interaction of nucleotide excision repair proteins modifies cancer cell sensitivity to platinum derivatives and genomic stability.

    PubMed

    Jordheim, Lars Petter; Cros-Perrial, Emeline; Matera, Eva-Laure; Bouledrak, Karima; Dumontet, Charles

    2014-10-01

    Nucleotide excision repair (NER) is involved in the repair of DNA damage caused by platinum derivatives and has been shown to decrease the cytotoxic activity of these drugs. Because protein-protein interactions are essential for NER activity, we transfected human cancer cell lines (A549 and HCT116) with plasmids coding the amino acid sequences corresponding to the interacting domains between excision repair cross-complementation group 1 (ERCC1) and xeroderma pigmentosum, complementation group A (XPA), as well as ERCC1 and xeroderma pigmentosum, complementation group F (XPF), all NER proteins. Using the 3-(4,5-dimethyl-2 thiazoyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay and annexin V staining, we showed that transfected A549 cells were sensitized 1.2-2.2-fold to carboplatin and that transfected HCT116 cells were sensitized 1.4-5.4-fold to oxaliplatin in vitro. In addition, transfected cells exhibited modified in vivo sensitivity to the same drugs. Finally, in particular cell models of the interaction between ERCC1 and XPF, DNA repair was decreased, as evidenced by increased phosphorylation of the histone 2AX after exposure to mitomycin C, and genomic instability was increased, as determined by comparative genomic hybridization studies. The results indicate that the interacting peptides act as dominant negatives and decrease NER activity through inhibition of protein-protein interactions.

  8. Diversity in Genetic In Vivo Methods for Protein-Protein Interaction Studies: from the Yeast Two-Hybrid System to the Mammalian Split-Luciferase System

    PubMed Central

    Stynen, Bram; Tournu, Hélène; Tavernier, Jan

    2012-01-01

    Summary: The yeast two-hybrid system pioneered the field of in vivo protein-protein interaction methods and undisputedly gave rise to a palette of ingenious techniques that are constantly pushing further the limits of the original method. Sensitivity and selectivity have improved because of various technical tricks and experimental designs. Here we present an exhaustive overview of the genetic approaches available to study in vivo binary protein interactions, based on two-hybrid and protein fragment complementation assays. These methods have been engineered and employed successfully in microorganisms such as Saccharomyces cerevisiae and Escherichia coli, but also in higher eukaryotes. From single binary pairwise interactions to whole-genome interactome mapping, the self-reassembly concept has been employed widely. Innovative studies report the use of proteins such as ubiquitin, dihydrofolate reductase, and adenylate cyclase as reconstituted reporters. Protein fragment complementation assays have extended the possibilities in protein-protein interaction studies, with technologies that enable spatial and temporal analyses of protein complexes. In addition, one-hybrid and three-hybrid systems have broadened the types of interactions that can be studied and the findings that can be obtained. Applications of these technologies are discussed, together with the advantages and limitations of the available assays. PMID:22688816

  9. Multiplicities in high energy interactions

    SciTech Connect

    Derrick, M.

    1985-05-13

    This paper reviews the data on multiplicities in high energy interactions. Results from e/sup +/e/sup -/ annihilation, from neutrino interactions, and from hadronic collisions, both diffractive and nondiffractive, are compared and contrasted. The energy dependence of the mean charged multiplicity, , as well as the rapidity density at Y = 0 are presented. For hadronic collisions, the data on neutral pion production shows a strong correlation with . The heavy particle fractions increase with ..sqrt..s up to the highest energies. The charged particle multiplicity distributions for each type of reaction show a scaling behavior when expressed in terms of the mean. Attempts to understand this behavior, which was first predicted by Koba, Nielsen, and Olesen, are discussed. The multiplicity correlations and the energy variation of the shape of the KNO scaling distribution provide important constraints on models. Some extrapolations to the energies of the Superconducting Super Collider are made. 51 refs., 27 figs.

  10. Updates to the integrated protein-protein interaction benchmarks: Docking benchmark version 5 and affinity benchmark version 2

    PubMed Central

    Vreven, Thom; Moal, Iain H.; Vangone, Anna; Pierce, Brian G.; Kastritis, Panagiotis L.; Torchala, Mieczyslaw; Chaleil, Raphael; Jiménez-García, Brian; Bates, Paul A.; Fernandez-Recio, Juan; Bonvin, Alexandre M.J.J.; Weng, Zhiping

    2015-01-01

    We present an updated and integrated version of our widely used protein-protein docking and binding affinity benchmarks. The benchmarks consist of non-redundant, high quality structures of protein-protein complexes along with the unbound structures of their components. Fifty-five new complexes were added to the docking benchmark, 35 of which have experimentally-measured binding affinities. These updated docking and affinity benchmarks now contain 230 and 179 entries, respectively. In particular, the number of antibody-antigen complexes has increased significantly, by 67% and 74% in the docking and affinity benchmarks, respectively. We tested previously developed docking and affinity prediction algorithms on the new cases. Considering only the top ten docking predictions per benchmark case, a prediction accuracy of 38% is achieved on all 55 cases, and up to 50% for the 32 rigid-body cases only. Predicted affinity scores are found to correlate with experimental binding energies up to r=0.52 overall, and r=0.72 for the rigid complexes. PMID:26231283

  11. Updates to the Integrated Protein-Protein Interaction Benchmarks: Docking Benchmark Version 5 and Affinity Benchmark Version 2.

    PubMed

    Vreven, Thom; Moal, Iain H; Vangone, Anna; Pierce, Brian G; Kastritis, Panagiotis L; Torchala, Mieczyslaw; Chaleil, Raphael; Jiménez-García, Brian; Bates, Paul A; Fernandez-Recio, Juan; Bonvin, Alexandre M J J; Weng, Zhiping

    2015-09-25

    We present an updated and integrated version of our widely used protein-protein docking and binding affinity benchmarks. The benchmarks consist of non-redundant, high-quality structures of protein-protein complexes along with the unbound structures of their components. Fifty-five new complexes were added to the docking benchmark, 35 of which have experimentally measured binding affinities. These updated docking and affinity benchmarks now contain 230 and 179 entries, respectively. In particular, the number of antibody-antigen complexes has increased significantly, by 67% and 74% in the docking and affinity benchmarks, respectively. We tested previously developed docking and affinity prediction algorithms on the new cases. Considering only the top 10 docking predictions per benchmark case, a prediction accuracy of 38% is achieved on all 55 cases and up to 50% for the 32 rigid-body cases only. Predicted affinity scores are found to correlate with experimental binding energies up to r=0.52 overall and r=0.72 for the rigid complexes.

  12. Targeting the MDM2-p53 Protein-Protein Interaction for New Cancer Therapy: Progress and Challenges.

    PubMed

    Wang, Shaomeng; Zhao, Yujun; Aguilar, Angelo; Bernard, Denzil; Yang, Chao-Yie

    2017-03-07

    MDM2 is a primary cellular inhibitor of p53. It inhibits p53 function by multiple mechanisms, each of which, however, is mediated by their direct interaction. It has been proposed that small-molecule inhibitors designed to block the MDM2-p53 interaction may be effective in the treatment of human cancer retaining wild-type p53 by reactivating the p53 tumor suppressor function. Through nearly two decades of intense efforts, a number of structurally distinct, highly potent, nonpeptide, small-molecule inhibitors of the MDM2-p53 interaction (MDM2 inhibitors) have been successfully designed and developed, and at least seven such compounds have now been advanced into human clinical trials as new anticancer drugs. This review offers a perspective on the design and development of MDM2 small-molecule inhibitors and discusses early clinical data for some of the MDM2 small-molecule inhibitors and future challenges for the successful clinical development of MDM2 inhibitors for cancer treatment.

  13. The application of an emerging technique for protein-protein interaction interface mapping: the combination of photo-initiated cross-linking protein nanoprobes with mass spectrometry.

    PubMed

    Ptáčková, Renata; Ječmen, Tomáš; Novák, Petr; Hudeček, Jiří; Stiborová, Marie; Šulc, Miroslav

    2014-05-26

    Protein-protein interaction was investigated using a protein nanoprobe capable of photo-initiated cross-linking in combination with high-resolution and tandem mass spectrometry. This emerging experimental approach introduces photo-analogs of amino acids within a protein sequence during its recombinant expression, preserves native protein structure and is suitable for mapping the contact between two proteins. The contact surface regions involved in the well-characterized interaction between two molecules of human 14-3-3ζ regulatory protein were used as a model. The employed photo-initiated cross-linking techniques extend the number of residues shown to be within interaction distance in the contact surface of the 14-3-3ζ dimer (Gln8-Met78). The results of this study are in agreement with our previously published data from molecular dynamic calculations based on high-resolution chemical cross-linking data and Hydrogen/Deuterium exchange mass spectrometry. The observed contact is also in accord with the 14-3-3ζ X-ray crystal structure (PDB 3dhr). The results of the present work are relevant to the structural biology of transient interaction in the 14-3-3ζ protein, and demonstrate the ability of the chosen methodology (the combination of photo-initiated cross-linking protein nanoprobes and mass spectrometry analysis) to map the protein-protein interface or regions with a flexible structure.

  14. Toward optimized potential functions for protein-protein interactions in aqueous solutions: osmotic second virial coefficient calculations using the MARTINI coarse-grained force field.

    PubMed

    Stark, Austin C; Andrews, Casey T; Elcock, Adrian H

    2013-09-10

    Coarse-grained (CG) simulation methods are now widely used to model the structure and dynamics of large biomolecular systems. One important issue for using such methods - especially with regard to using them to model, for example, intracellular environments - is to demonstrate that they can reproduce experimental data on the thermodynamics of protein-protein interactions in aqueous solutions. To examine this issue, we describe here simulations performed using the popular coarse-grained MARTINI force field, aimed at computing the thermodynamics of lysozyme and chymotrypsinogen self-interactions in aqueous solution. Using molecular dynamics simulations to compute potentials of mean force between a pair of protein molecules, we show that the original parameterization of the MARTINI force field is likely to significantly overestimate the strength of protein-protein interactions to the extent that the computed osmotic second virial coefficients are orders of magnitude more negative than experimental estimates. We then show that a simple down-scaling of the van der Waals parameters that describe the interactions between protein pseudo-atoms can bring the simulated thermodynamics into much closer agreement with experiment. Overall, the work shows that it is feasible to test explicit-solvent CG force fields directly against thermodynamic data for proteins in aqueous solutions, and highlights the potential usefulness of osmotic second virial coefficient measurements for fully parameterizing such force fields.

  15. Building and analysis of protein-protein interactions related to diabetes mellitus using support vector machine, biomedical text mining and network analysis.

    PubMed

    Vyas, Renu; Bapat, Sanket; Jain, Esha; Karthikeyan, Muthukumarasamy; Tambe, Sanjeev; Kulkarni, Bhaskar D

    2016-12-01

    In order to understand the molecular mechanism underlying any disease, knowledge about the interacting proteins in the disease pathway is essential. The number of revealed protein-protein interactions (PPI) is still very limited compared to the available protein sequences of different organisms. Experiment based high-throughput technologies though provide some data about these interactions, those are often fairly noisy. Computational techniques for predicting protein-protein interactions therefore assume significance. 1296 binary fingerprints that encode a combination of structural and geometric properties were developed using the crystallographic data of 15,000 protein complexes in the pdb server. In a case study, these fingerprints were created for proteins implicated in the Type 2 diabetes mellitus disease. The fingerprints were input into a SVM based model for discriminating disease proteins from non disease proteins yielding a classification accuracy of 78.2% (AUC value of 0.78) on an external data set composed of proteins retrieved via text mining of diabetes related literature. A PPI network was constructed and analysed to explore new disease targets. The integrated approach exemplified here has a potential for identifying disease related proteins, functional annotation and other proteomics studies.

  16. Discovery of a junctional epitope antibody that stabilizes IL-6 and gp80 protein:protein interaction and modulates its downstream signaling

    PubMed Central

    Adams, Ralph; Burnley, Rebecca J.; Valenzano, Chiara R.; Qureshi, Omar; Doyle, Carl; Lumb, Simon; del Carmen Lopez, Maria; Griffin, Robert; McMillan, David; Taylor, Richard D.; Meier, Chris; Mori, Prashant; Griffin, Laura M.; Wernery, Ulrich; Kinne, Jörg; Rapecki, Stephen; Baker, Terry S.; Lawson, Alastair D. G.; Wright, Michael; Ettorre, Anna

    2017-01-01

    Protein:protein interactions are fundamental in living organism homeostasis. Here we introduce VHH6, a junctional epitope antibody capable of specifically recognizing a neo-epitope when two proteins interact, albeit transiently, to form a complex. Orthogonal biophysical techniques have been used to prove the “junctional epitope” nature of VHH6, a camelid single domain antibody recognizing the IL-6–gp80 complex but not the individual components alone. X-ray crystallography, HDX-MS and SPR analysis confirmed that the CDR regions of VHH6 interact simultaneously with IL-6 and gp80, locking the two proteins together. At the cellular level, VHH6 was able to alter the response of endothelial cells to exogenous IL-6, promoting a sustained STAT3 phosphorylation signal, an accumulation of IL-6 in vesicles and an overall pro-inflammatory phenotype supported further by transcriptomic analysis. Junctional epitope antibodies, like VHH6, not only offer new opportunities in screening and structure-aided drug discovery, but could also be exploited as therapeutics to modulate complex protein:protein interactions. PMID:28134246

  17. Toward optimized potential functions for protein-protein interactions in aqueous solutions: osmotic second virial coefficient calculations using the MARTINI coarse-grained force field

    PubMed Central

    Stark, Austin C.; Andrews, Casey T.

    2013-01-01

    Coarse-grained (CG) simulation methods are now widely used to model the structure and dynamics of large biomolecular systems. One important issue for using such methods – especially with regard to using them to model, for example, intracellular environments – is to demonstrate that they can reproduce experimental data on the thermodynamics of protein-protein interactions in aqueous solutions. To examine this issue, we describe here simulations performed using the popular coarse-grained MARTINI force field, aimed at computing the thermodynamics of lysozyme and chymotrypsinogen self-interactions in aqueous solution. Using molecular dynamics simulations to compute potentials of mean force between a pair of protein molecules, we show that the original parameterization of the MARTINI force field is likely to significantly overestimate the strength of protein-protein interactions to the extent that the computed osmotic second virial coefficients are orders of magnitude more negative than experimental estimates. We then show that a simple down-scaling of the van der Waals parameters that describe the interactions between protein pseudo-atoms can bring the simulated thermodynamics into much closer agreement with experiment. Overall, the work shows that it is feasible to test explicit-solvent CG force fields directly against thermodynamic data for proteins in aqueous solutions, and highlights the potential usefulness of osmotic second virial coefficient measurements for fully parameterizing such force fields. PMID:24223529

  18. An alternative easy method for antibody purification and analysis of protein-protein interaction using GST fusion proteins immobilized onto glutathione-agarose.

    PubMed

    Zalazar, L; Alonso, C A I; De Castro, R E; Cesari, A

    2014-01-01

    Immobilization of small proteins designed to perform protein-protein assays can be a difficult task. Often, the modification of reactive residues necessary for the interaction between the immobilized protein and the matrix compromises the interaction between the protein and its target. In these cases, glutathione-S-transferase (GST) is a valuable tag providing a long arm that makes the bait protein accessible to the mobile flow phase of the chromatography. In the present report, we used a GST fusion version of the 8-kDa protein serine protease inhibitor Kazal-type 3 (SPINK3) as the bait to purify anti-SPINK3 antibodies from a rabbit crude serum. The protocol for immobilization of GST-SPINK3 to glutathione-agarose beads was modified from previously reported protocols by using an alternative bifunctional cross-linker (dithiobis(succinimidyl propionate)) in a very simple procedure and by using simple buffers under physiological conditions. We concluded that the immobilized protein remained bound to the column after elution with low pH, allowing the reuse of the column for alternative uses, such as screening for other protein-protein interactions using SPINK3 as the bait.

  19. Competing Lipid-Protein and Protein-Protein Interactions Determine Clustering and Gating Patterns in the Potassium Channel from Streptomyces lividans (KcsA)*

    PubMed Central

    Molina, M. Luisa; Giudici, A. Marcela; Poveda, José A.; Fernández-Ballester, Gregorio; Montoya, Estefanía; Renart, M. Lourdes; Fernández, Asia M.; Encinar, José A.; Riquelme, Gloria; Morales, Andrés; González-Ros, José M.

    2015-01-01

    There is increasing evidence to support the notion that membrane proteins, instead of being isolated components floating in a fluid lipid environment, can be assembled into supramolecular complexes that take part in a variety of cooperative cellular functions. The interplay between lipid-protein and protein-protein interactions is expected to be a determinant factor in the assembly and dynamics of such membrane complexes. Here we report on a role of anionic phospholipids in determining the extent of clustering of KcsA, a model potassium channel. Assembly/disassembly of channel clusters occurs, at least partly, as a consequence of competing lipid-protein and protein-protein interactions at nonannular lipid binding sites on the channel surface and brings about profound changes in the gating properties of the channel. Our results suggest that these latter effects of anionic lipids are mediated via the Trp67–Glu71–Asp80 inactivation triad within the channel structure and its bearing on the selectivity filter. PMID:26336105

  20. The solution structure of the outer membrane lipoprotein OmlA from Xanthomonas axonopodis pv. citri reveals a protein fold implicated in protein-protein interaction.

    PubMed

    Vanini, Marina Marques Teixeira; Spisni, Alberto; Sforça, Maurício Luis; Pertinhez, Thelma Aguiar; Benedetti, Celso Eduardo

    2008-06-01

    The outer membrane lipoprotein A (OmlA) belongs to a family of bacterial small lipoproteins widely distributed across the beta and gamma proteobacteria. Although the role of numerous bacterial lipoproteins is known, the biological function of OmlA remains elusive. We found that in the citrus canker pathogen, Xanthomonas axonopodis pv. citri (X. citri), OmlA is coregulated with the ferric uptake regulator (Fur) and their expression is enhanced when X. citri is grown on citrus leaves, suggesting that these proteins are involved in plant-pathogen interaction. To gain insights into the function of OmlA, its conformational and dynamic features were determined by nuclear magnetic resonance. The protein has highly flexible N- and C- termini and a structurally well defined core composed of three beta-strands and two small alpha-helices, which pack against each other forming a two-layer alpha/beta scaffold. This protein fold resembles the domains of the beta-lactamase inhibitory protein BLIP, involved in protein-protein binding. In conclusion, the structure of OmlA does suggest that this protein may be implicated in protein-protein interactions required during X. citri infection.

  1. Leucine periodicity of U2 small nuclear ribonucleoprotein particle (snRNP) A' protein is implicated in snRNP assembly via protein-protein interactions.

    PubMed Central

    Fresco, L D; Harper, D S; Keene, J D

    1991-01-01

    Recombinant A' protein could be reconstituted into U2 small nuclear ribonucleoprotein particles (snRNPs) upon addition to HeLa cell extracts as determined by coimmunoprecipitation and particle density; however, direct binding to U2 RNA could not be demonstrated except in the presence of the U2 snRNP B" protein. Mutational analysis indicated that a central core region of A' was required for particle reconstitution. This region consists of five tandem repeats of approximately 24 amino acids each that exhibit a periodicity of leucine and asparagine residues that is distinct from the leucine zipper. Similar leucine-rich (Leu-Leu motif) repeats are characteristic of a diverse array of soluble and membrane-associated proteins from yeasts to humans but have not been reported previously to reside in nuclear proteins. Several of these proteins, including Toll, chaoptin, RNase/angiogenin inhibitors, lutropin-choriogonadotropin receptor, carboxypeptidase N, adenylyl cyclase, CD14, and human immunodeficiency virus type 1 Rev, may be involved in protein-protein interactions. Our findings suggest that in cell extracts the Leu-Leu motif of A' is required for reconstitution with U2 snRNPs and perhaps with other components involved in splicing through protein-protein interactions. Images PMID:1825347

  2. FRET-Based System for Probing Protein-Protein Interactions between σR and RsrA from Streptomyces Coelicolor in Response to the Redox Environment

    PubMed Central

    Wei, Zi-Han; Chen, Huan; Zhang, Chang; Ye, Bang-Ce

    2014-01-01

    Protein-protein interactions between sigma factor σR and its corresponding zinc-binding anti-sigma (ZAS) protein RsrA trigger the thioredoxin system for maintaining cellular redox homeostasis in S. coelicolor. RsrA bound to zinc associates with σR, inhibiting its transcriptional activity in a reducing environment. During disulfide stress it forms intramolecular disulfide bonds, leading to zinc release and dissociation from σR, which initiates transcription to produce reductase and thioredoxin. We designed a fluorescence resonance energy transfer (FRET) based system for monitoring protein-protein interactions between σR and RsrA to further understand how this redox switch regulates the thioredoxin system in S. coelicolor in response to its redox environment, especially various reactive oxygen species (ROS) derived from different metabolic pathways, and clarify the different response mechanisms between Zn-RsrA and apo-RsrA. By the use of the FRET approach described here, we showed that zinc protected thiols in RsrA and causes the σR-RsrA complex to form a more compact structure. This system was also utilized to detect changes in redox status induced by ROS and diamide in real time in E. coli cells. PMID:24651617

  3. FRET-based system for probing protein-protein interactions between σR and RsrA from Streptomyces coelicolor in response to the redox environment.

    PubMed

    Wei, Zi-Han; Chen, Huan; Zhang, Chang; Ye, Bang-Ce

    2014-01-01

    Protein-protein interactions between sigma factor σ(R) and its corresponding zinc-binding anti-sigma (ZAS) protein RsrA trigger the thioredoxin system for maintaining cellular redox homeostasis in S. coelicolor. RsrA bound to zinc associates with σ(R), inhibiting its transcriptional activity in a reducing environment. During disulfide stress it forms intramolecular disulfide bonds, leading to zinc release and dissociation from σ(R), which initiates transcription to produce reductase and thioredoxin. We designed a fluorescence resonance energy transfer (FRET) based system for monitoring protein-protein interactions between σ(R) and RsrA to further understand how this redox switch regulates the thioredoxin system in S. coelicolor in response to its redox environment, especially various reactive oxygen species (ROS) derived from different metabolic pathways, and clarify the different response mechanisms between Zn-RsrA and apo-RsrA. By the use of the FRET approach described here, we showed that zinc protected thiols in RsrA and causes the σ(R)-RsrA complex to form a more compact structure. This system was also utilized to detect changes in redox status induced by ROS and diamide in real time in E. coli cells.

  4. Combining random gene fission and rational gene fusion to discover near-infrared fluorescent protein fragments that report on protein-protein interactions.

    PubMed

    Pandey, Naresh; Nobles, Christopher L; Zechiedrich, Lynn; Maresso, Anthony W; Silberg, Jonathan J

    2015-05-15

    Gene fission can convert monomeric proteins into two-piece catalysts, reporters, and transcription factors for systems and synthetic biology. However, some proteins can be challenging to fragment without disrupting function, such as near-infrared fluorescent protein (IFP). We describe a directed evolution strategy that can overcome this challenge by randomly fragmenting proteins and concomitantly fusing the protein fragments to pairs of proteins or peptides that associate. We used this method to create libraries that express fragmented IFP as fusions to a pair of associating peptides (IAAL-E3 and IAAL-K3) and proteins (CheA and CheY) and screened for fragmented IFP with detectable near-infrared fluorescence. Thirteen novel fragmented IFPs were identified, all of which arose from backbone fission proximal to the interdomain linker. Either the IAAL-E3 and IAAL-K3 peptides or CheA and CheY proteins could assist with IFP fragment complementation, although the IAAL-E3 and IAAL-K3 peptides consistently yielded higher fluorescence. These results demonstrate how random gene fission can be coupled to rational gene fusion to create libraries enriched in fragmented proteins with AND gate logic that is dependent upon a protein-protein interaction, and they suggest that these near-infrared fluorescent protein fragments will be suitable as reporters for pairs of promoters and protein-protein interactions within whole animals.

  5. Single-step protease cleavage elution for identification of protein-protein interactions from GST pull-down and mass spectrometry.

    PubMed

    Luo, Lin; King, Nathan P; Yeo, Jeremy C; Jones, Alun; Stow, Jennifer L

    2014-01-01

    The study of protein-protein interactions is a major theme in biological disciplines. Pull-down or affinity-precipitation assays using GST fusion proteins have become one of the most common and valuable approaches to identify novel binding partners for proteins of interest (bait). Non-specific binding of prey proteins to the beads or to GST itself, however, inevitably complicates and impedes subsequent analysis of pull-down results. A variety of measures, each with inherent advantages and limitations, can minimise the extent of the background. This technical brief details and tests a modification of established GST pull-down protocols. By specifically eluting only the bait (minus the GST tag) and the associated non-specific binding proteins with a simple, single-step protease cleavage, a cleaner platform for downstream protein identification with MS is established. We present a proof of concept for this method, as evidenced by a GST pull-down/MS case study of the small guanosine triphosphatase (GTPase) Rab31 in which: (i) sensitivity was enhanced, (ii) a reduced level of background was observed, (iii) distinguishability of non-specific contaminant proteins from genuine binders was improved and (iv) a putative new protein-protein interaction was discovered. Our protease cleavage step is readily applicable to all further affinity tag pull-downs.

  6. Probing the relation between protein-protein interactions and DNA binding for a linker mutant of the bacterial nucleoid protein H-NS.

    PubMed

    Giangrossi, Mara; Wintraecken, Kathelijne; Spurio, Roberto; de Vries, Renko

    2014-02-01

    We have investigated the relationship between oligomerization in solution and DNA binding for the bacterial nucleoid protein H-NS. This was done by comparing oligomerization and DNA binding of H-NS with that of a H-NS D68V-D71V linker mutant. The double linker mutation D68V-D71V, that makes the linker significantly more hydrophobic, leads to a dramatically enhanced and strongly temperature-dependent H-NS oligomerization in solution, as detected by dynamic light scattering. The DNA binding affinity of H-NS D68V-D71V for the hns promoter region is lower and has stronger temperature dependence than that of H-NS. DNase I footprinting experiments show that at high concentrations, regions protected by H-NS D68V-D71V are larger and less defined than for H-NS. In vitro transcription assays show that the enhanced protection also leads to enhanced transcriptional repression. Whereas the lower affinity of the H-NS D68V-D71V for DNA could be caused by competition between oligomerization in solution and oligomerization on DNA, the larger size of protected regions clearly confirms the notion that cooperative binding of H-NS to DNA is related to protein-protein interactions. These results emphasize the relative contributions of protein-protein interactions and substrate-dependent oligomerization in the control of gene repression operated by H-NS.

  7. How to link ontologies and protein-protein interactions to literature: text-mining approaches and the BioCreative experience.

    PubMed

    Krallinger, Martin; Leitner, Florian; Vazquez, Miguel; Salgado, David; Marcelle, Christophe; Tyers, Mike; Valencia, Alfonso; Chatr-aryamontri, Andrew

    2012-01-01

    There is an increasing interest in developing ontologies and controlled vocabularies to improve the efficiency and consistency of manual literature curation, to enable more formal biocuration workflow results and ultimately to improve analysis of biological data. Two ontologies that have been successfully used for this purpose are the Gene Ontology (GO) for annotating aspects of gene products and the Molecular Interaction ontology (PSI-MI) used by databases that archive protein-protein interactions. The examination of protein interactions has proven to be extremely promising for the understanding of cellular processes. Manual mapping of information from the biomedical literature to bio-ontology terms is one of the most challenging components in the curation pipeline. It requires that expert curators interpret the natural language descriptions contained in articles and infer their semantic equivalents in the ontology (controlled vocabulary). Since manual curation is a time-consuming process, there is strong motivation to implement text-mining techniques to automatically extract annotations from free text. A range of text mining strategies has been devised to assist in the automated extraction of biological data. These strategies either recognize technical terms used recurrently in the literature and propose them as candidates for inclusion in ontologies, or retrieve passages that serve as evidential support for annotating an ontology term, e.g. from the PSI-MI or GO controlled vocabularies. Here, we provide a general overview of current text-mining methods to automatically extract annotations of GO and PSI-MI ontology terms in the context of the BioCreative (Critical Assessment of Information Extraction Systems in Biology) challenge. Special emphasis is given to protein-protein interaction data and PSI-MI terms referring to interaction detection methods.

  8. Perturbation of the c-Myc-Max protein-protein interaction via synthetic α-helix mimetics.

    PubMed

    Jung, Kwan-Young; Wang, Huabo; Teriete, Peter; Yap, Jeremy L; Chen, Lijia; Lanning, Maryanna E; Hu, Angela; Lambert, Lester J; Holien, Toril; Sundan, Anders; Cosford, Nicholas D P; Prochownik, Edward V; Fletcher, Steven

    2015-04-09

    The rational design of inhibitors of the bHLH-ZIP oncoprotein c-Myc is hampered by a lack of structure in its monomeric state. We describe herein the design of novel, low-molecular-weight, synthetic α-helix mimetics that recognize helical c-Myc in its transcriptionally active coiled-coil structure in association with its obligate bHLH-ZIP partner Max. These compounds perturb the heterodimer's binding to its canonical E-box DNA sequence without causing protein-protein dissociation, heralding a new mechanistic class of "direct" c-Myc inhibitors. In addition to electrophoretic mobility shift assays, this model was corroborated by further biophysical methods, including NMR spectroscopy and surface plasmon resonance. Several compounds demonstrated a 2-fold or greater selectivity for c-Myc-Max heterodimers over Max-Max homodimers with IC50 values as low as 5.6 μM. Finally, these compounds inhibited the proliferation of c-Myc-expressing cell lines in a concentration-dependent manner that correlated with the loss of expression of a c-Myc-dependent reporter plasmid despite the fact that c-Myc-Max heterodimers remained intact.

  9. The Application of Ligand-Mapping Molecular Dynamics Simulations to the Rational Design of Peptidic Modulators of Protein-Protein Interactions.

    PubMed

    Tan, Yaw Sing; Spring, David R; Abell, Chris; Verma, Chandra S

    2015-07-14

    A computational ligand-mapping approach to detect protein surface pockets that interact with hydrophobic moieties is presented. In this method, we incorporated benzene molecules into explicit solvent molecular dynamics simulations of various protein targets. The benzene molecules successfully identified the binding locations of hydrophobic hot-spot residues and all-hydrocarbon cross-links from known peptidic ligands. They also unveiled cryptic binding sites that are occluded by side chains and the protein backbone. Our results demonstrate that ligand-mapping molecular dynamics simulations hold immense promise to guide the rational design of peptidic modulators of protein-protein interactions, including that of stapled peptides, which show promise as an exciting new class of cell-penetrating therapeutic molecules.

  10. Analysis of Protein-protein Interaction Interface between Yeast Mitochondrial Proteins Rim1 and Pif1 Using Chemical Cross-linking Mass Spectrometry.

    PubMed

    Zybailov, Boris; Gokulan, Kuppan; Wiese, Jadon; Ramanagoudr-Bhojappa, Ramanagouda; Byrd, Alicia K; Glazko, Galina; Jaiswal, Mihir; Mackintosh, Samuel; Varughese, Kottayil I; Raney, Kevin D

    2015-11-01

    Defining protein-protein contacts is a challenging problem and cross-linking is a promising solution. Here, we present a case of mitochondrial single strand binding protein Rim1 and helicase Pif1, an interaction first observed in immuno-affinity pull-down from yeast cells using Pif1 bait. We found that only the short succinimidyl-diazirine cross-linker or formaldehyde captured the interaction between recombinant Rim1 and Pif1. In addition, Pif1 needed to be stripped of its N-terminal and C-terminal domains, and Rim1's C-terminus needed to be modified for the cross-linked product to become visible. Our report is an example of a non-trivial analysis, where a previously identified stable interaction escapes initial capture with cross-linking agents and requires substantial modification to recombinant proteins and fine-tuning of the mass spectrometry-based methods for the cross-links to become detectable. We used high resolution mass spectrometry to detect the cross-linked peptides. A 1:1 mixture of (15)N and (14)N-labeled Rim1 was used to validate the cross-links by their mass shift in the LC-MS profiles. Two sites on Rim1 were confirmed: 1) the N-terminus, and 2) the K29 residue. Performing cross-linking with a K29A variant visibly reduced the cross-linked product. Further, K29A-Rim1 showed a five-fold lower affinity to single stranded DNA compared to wild-type Rim1. Both the K29A variant and wild type Rim1 showed similar degrees of stimulation of Pif1 helicase activity. We propose structural models of the Pif1-Rim1 interaction and discuss its functional significance. Our work represents a non-trivial protein-protein interface analysis and demonstrates utility of short and non-specific cross-linkers.

  11. The in silico identification of small molecules for protein-protein interaction inhibition in AKAP-Lbc-RhoA signaling complex.

    PubMed

    Khan, Asifullah; Munir, Mehwish; Aiman, Sara; Wadood, Abdul; Khan, Arif-Ullah

    2017-04-01

    The rational design of small molecules that mimic key residues at the interface of interacting proteins can be a successful approach to target certain biological signaling cascades causing pathophysiological outcome. The A-Kinase Anchoring Protein, i.e. AKAP-Lbc, catalyses nucleotide exchange on RhoA and is involved in cardiac repolarization. The oncogenic AKAP-Lbc induces the RhoA GTPase hyperactivity and aberrantly amplifies the signaling pathway leading to hypertrophic cardiomyocytes. We took advantage of the AKAP-Lbc-RhoA complex crystal structure to design in silico small molecules predicted to inhibit the associated pathological signaling cascade. We adopted the strategies of pharmacophore building, virtual screening and molecular docking to identify the small molecules capable to target AKAP-Lbc and RhoA interactions. The pharmacophore model based virtual screening unveils two lead compounds from the TIMBAL database of small molecules modulating the targeted protein-protein interactions. The molecular docking analysis revealed the lead compounds' potentialities to establish the essential chemical interactions with the key interactive residues of the complex. These features provided a road map for designing additional potent chemical derivatives and fragments of the original lead compounds to perturb the AKAP-Lbc and RhoA interactions. Experimental validations may elucidate the therapeutic potential of these lead chemical scaffolds to deal with aberrant AKAP-Lbc signaling based cardiac hypertrophy.

  12. Development of Cell-Permeable, Non-Helical Constrained Peptides to Target a Key Protein-Protein Interaction in Ovarian Cancer.

    PubMed

    Wiedmann, Mareike M; Tan, Yaw Sing; Wu, Yuteng; Aibara, Shintaro; Xu, Wenshu; Sore, Hannah F; Verma, Chandra S; Itzhaki, Laura; Stewart, Murray; Brenton, James D; Spring, David R

    2017-01-09

    There is a lack of current treatment options for ovarian clear cell carcinoma (CCC) and the cancer is often resistant to platinum-based chemotherapy. Hence there is an urgent need for novel therapeutics. The transcription factor hepatocyte nuclear factor 1β (HNF1β) is ubiquitously overexpressed in CCC and is seen as an attractive therapeutic target. This was validated through shRNA-mediated knockdown of the target protein, HNF1β, in five high- and low-HNF1β-expressing CCC lines. To inhibit the protein function, cell-permeable, non-helical constrained proteomimetics to target the HNF1β-importin α protein-protein interaction were designed, guided by X-ray crystallographic data and molecular dynamics simulations. In this way, we developed the first reported series of constrained peptide nuclear import inhibitors. Importantly, this general approach may be extended to other transcription factors.

  13. Identification of Significant Pathways Induced by PAX5 Haploinsufficiency Based on Protein-Protein Interaction Networks and Cluster Analysis in Raji Cell Line

    PubMed Central

    Gu, Jia; Li, TongJuan; Zhao, Lei; Liang, Xue; Fu, Xing; Wang, Jue; Shang, Zhen; Zhou, Jianfeng

    2017-01-01

    PAX5 encodes a transcription factor essential for B-cell differentiation, and PAX5 haploinsufficiency is involved in tumorigenesis. There were few studies on how PAX5 haploinsufficiency regulated genes expression to promote tumorigenesis. In this study, we constructed the cell model of PAX5 haploinsufficiency using gene editing technology in Raji cells, detected differentially expressed genes in PAX5 haploinsufficiency Raji cells, and used protein-protein interaction networks and cluster analysis to comprehensively investigate the cellular pathways involved in PAX5 haploinsufficiency. The clusters of gene transcription, inflammatory and immune response, and cancer pathways were identified as three important pathways associated with PAX5 haploinsufficiency in Raji cells. These changes hinted that the mechanism of PAX5 haploinsufficiency promoting tumorigenesis may be related to genomic instability, immune tolerance, and tumor pathways. PMID:28316978

  14. Detection of protein-protein interactions among lens crystallins in a mammalian two-hybrid system assay.

    PubMed

    Fu, Ling; Liang, Jack J-N

    2002-02-08

    alpha-Crystallin consists of two subunits, alphaA and alphaB, and each can form an oligomer by itself or with the other. The aggregation arises from interdomain interactions. However, it is not known whether such interactions also exist among alpha-, beta-, and gamma-crystallins. This heterogeneous crystallin interaction is far weaker than the homogeneous crystallin interaction and is difficult to detect by conventional spectroscopic measurements. We used a mammalian two-hybrid system in this study. The major crystallin components, alphaA-, alphaB-, betaB2-, and gammaC-crystallin genes, were subcloned into the DNA binding domain and transcription activation domain vectors of the two-hybrid system, and they were cotransfected along with a chloramphenicol acetyltransferase (CAT) reporter vector into HeLa cells. Chloramphenicol acetyltransferase activity indicated that there were interactions between alphaA- (or alphaB-) and betaB2- or gammaC-crystallins but with an intensity of one-third that of alphaA-alphaB interactions. Hsp27, a member of the family of the small heat-shock proteins, showed a similar interaction property with alphaB-crystallin. Using the N- and C-terminal domain-truncated mutants, we demonstrated that both domains were important in the alphaA-crystallin self-interaction, but that only the C-terminal domain was important in the alphaB-crystallin self-interaction. These results show that the two-hybrid system can detect interactions among various crystallins and may be used in mapping interaction domains.

  15. Identification of new protein-protein interactions involving the products of the chromosome- and plasmid-encoded type IV secretion loci of the phytopathogen Xanthomonas axonopodis pv. citri.

    PubMed

    Alegria, Marcos C; Souza, Diorge P; Andrade, Maxuel O; Docena, Cassia; Khater, Leticia; Ramos, Carlos H I; da Silva, Ana C R; Farah, Chuck S

    2005-04-01

    The recently sequenced genome of the bacterial plant pathogen Xanthomonas axonopodis pv. citri contains two virB gene clusters, one on the chromosome and one on a 64-kb plasmid, each of which codes for a previously uncharacterized type IV secretion system (T4SS). Here we used a yeast two-hybrid assay to identify protein-protein interactions in these two systems. Our results revealed interactions between known T4SS components as well as previously uncharacterized interactions involving hypothetical proteins coded by open reading frames in the two X. axonopodis pv. citri virB loci. Our results indicate that both loci may code for previously unidentified VirB7 proteins, which we show interact with either VirB6 or VirB9 or with a hypothetical protein coded by the same locus. Furthermore, a set of previously uncharacterized Xanthomonas proteins have been found to interact with VirD4, whose gene is adjacent to the chromosomal virB locus. The gene for one member of this family is found within the chromosomal virB locus. All these uncharacterized proteins possess a conserved 120-amino-acid domain in their C termini and may represent a family of cofactors or substrates of the Xanthomonas T4SS.

  16. DynaFace: Discrimination between Obligatory and Non-obligatory Protein-Protein Interactions Based on the Complex’s Dynamics

    PubMed Central

    Soner, Seren; Ozbek, Pemra; Garzon, Jose Ignacio; Ben-Tal, Nir; Haliloglu, Turkan

    2015-01-01

    Protein-protein interfaces have been evolutionarily-designed to enable transduction between the interacting proteins. Thus, we hypothesize that analysis of the dynamics of the complex can reveal details about the nature of the interaction, and in particular whether it is obligatory, i.e., persists throughout the entire lifetime of the proteins, or not. Indeed, normal mode analysis, using the Gaussian network model, shows that for the most part obligatory and non-obligatory complexes differ in their decomposition into dynamic domains, i.e., the mobile elements of the protein complex. The dynamic domains of obligatory complexes often mix segments from the interacting chains, and the hinges between them do not overlap with the interface between the chains. In contrast, in non-obligatory complexes the interface often hinges between dynamic domains, held together through few anchor residues on one side of the interface that interact with their counterpart grooves in the other end. In automatic analysis, 117 of 139 obligatory (84.2%) and 203 of 246 non-obligatory (82.5%) complexes are correctly classified by our method: DynaFace. We further use DynaFace to predict obligatory and non-obligatory interactions among a set of 300 putative protein complexes. DynaFace is available at: http://safir.prc.boun.edu.tr/dynaface. PMID:26506003

  17. SAINT-MS1: protein-protein interaction scoring using label-free intensity data in affinity purification-mass spectrometry experiments.

    PubMed

    Choi, Hyungwon; Glatter, Timo; Gstaiger, Mathias; Nesvizhskii, Alexey I

    2012-04-06

    We present a statistical method SAINT-MS1 for scoring protein-protein interactions based on the label-free MS1 intensity data from affinity purification-mass spectrometry (AP-MS) experiments. The method is an extension of Significance Analysis of INTeractome (SAINT), a model-based method previously developed for spectral count data. We reformulated the statistical model for log-transformed intensity data, including adequate treatment of missing observations, that is, interactions identified in some but not all replicate purifications. We demonstrate the performance of SAINT-MS1 using two recently published data sets: a small LTQ-Orbitrap data set with three replicate purifications of single human bait protein and control purifications and a larger drosophila data set targeting insulin receptor/target of rapamycin signaling pathway generated using an LTQ-FT instrument. Using the drosophila data set, we also compare and discuss the performance of SAINT analysis based on spectral count and MS1 intensity data in terms of the recovery of orthologous and literature-curated interactions. Given rapid advances in high mass accuracy instrumentation and intensity-based label-free quantification software, we expect that SAINT-MS1 will become a useful tool allowing improved detection of protein interactions in label-free AP-MS data, especially in the low abundance range.

  18. SAINT-MS1: protein-protein interaction scoring using label-free intensity data in affinity purification – mass spectrometry experiments

    PubMed Central

    Choi, Hyungwon; Glatter, Timo; Gstaiger, Mathias; Nesvizhskii, Alexey I.

    2013-01-01

    We present a statistical method SAINT-MS1 for scoring protein-protein interactions based on the label-free MS1 intensity data from affinity purification - mass spectrometry (AP-MS) experiments. The method is an extension of Significance Analysis of INTeractome (SAINT), a model-based method previously developed for spectral count data. We reformulated the statistical model for the log-transformed intensity data, including adequate treatment of missing observations, i.e. interactions whose quantitative data are inconsistent over replicate purifications. We demonstrate the performance of SAINT-MS1 using two recently published datasets: a small LTQ-Orbitrap dataset with three replicate purifications of single human bait protein and control purifications, and a larger drosophila dataset targeting insulin receptor/target of rapamycin signaling pathway generated using an LTQ-FT instrument. Using the drosophila dataset, we also compare and discuss the performance of SAINT analysis based on spectral count and MS1 intensity data in terms of the recovery of orthologous and literature-curated interactions. Given rapid advances in high mass accuracy instrumentation and intensity-based label-free quantification software, we expect that SAINT-MS1 will become a useful tool allowing improved detection of protein interactions in label-free AP-MS data, especially in the low abundance range. PMID:22352807

  19. On the integration of protein-protein interaction networks with gene expression and 3D structural data: What can be gained?

    NASA Astrophysics Data System (ADS)

    Bertolazzi, Paola; Bock, Mary Ellen; Guerra, Concettina; Paci, Paola; Santoni, Daniele

    2014-06-01

    The biological role of proteins has been analyzed from different perspectives, initially by considering proteins as isolated biological entities, then as cooperating entities that perform their function by interacting with other molecules. There are other dimensions that are important for the complete understanding of the biological processes: time and location. However a protein is rarely annotated with temporal and spatial information. Experimental Protein-Proteins Interaction (PPI) data are static; furthermore they generally do not include transient interactions which are a considerable fraction of the interactome of many organisms. One way to incorporate temporal and condition information is to use other sources of information, such as gene expression data and 3D structural data. Here we review work done to understand the insight that can be gained by enriching PPI data with gene expression and 3D structural data. In particular, we address the following questions: Can the dynamics of a single protein or of an interaction be accurately derived from these data? Can the assembly-disassembly of protein complexes be traced over time? What type of topological changes occur in a PPI network architecture over time?

  20. Specific Protein-Protein Interaction between Basic Helix-Loop-Helix Transcription Factors and Homeoproteins of the Pitx Family

    PubMed Central

    Poulin, Gino; Lebel, Mélanie; Chamberland, Michel; Paradis, Francois W.; Drouin, Jacques

    2000-01-01

    Homeoproteins and basic helix-loop-helix (bHLH) transcription factors are known for their critical role in development and cellular differentiation. The pituitary pro-opiomelanocortin (POMC) gene is a target for factors of both families. Indeed, pituitary-specific transcription of POMC depends on the action of the homeodomain-containing transcription factor Pitx1 and of bHLH heterodimers containing NeuroD1. We now show lineage-restricted expression of NeuroD1 in pituitary corticotroph cells and a direct physical interaction between bHLH heterodimers and Pitx1 that results in transcriptional synergism. The interaction between the bHLH and homeodomains is restricted to ubiquitous (class A) bHLH and to the Pitx subfamily. Since bHLH heterodimers interact with Pitx factors through their ubiquitous moiety, this mechanism may be implicated in other developmental processes involving bHLH factors, such as neurogenesis and myogenesis. PMID:10848608

  1. Exploration of the Dynamic Properties of Protein Complexes Predicted from Spatially Constrained Protein-Protein Interaction Networks

    PubMed Central

    Yen, Eric A.; Tsay, Aaron; Waldispuhl, Jerome; Vogel, Jackie

    2014-01-01

    Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and visualization of the hidden

  2. Exploring weak, transient protein--protein interactions in crowded in vivo environments by in-cell nuclear magnetic resonance spectroscopy.

    PubMed

    Wang, Qinghua; Zhuravleva, Anastasia; Gierasch, Lila M

    2011-11-01

    Biology relies on functional interplay of proteins in the crowded and heterogeneous environment inside cells, and functional protein interactions are often weak and transient. Thus, methods that preserve these interactions and provide information about them are needed. In-cell nuclear magnetic resonance (NMR) spectroscopy is an attractive method for studying a protein's behavior in cells because it may provide residue-level structural and dynamic information, yet several factors limit the feasibility of protein NMR spectroscopy in cells; among them, slow rotational diffusion has emerged as the most important. In this paper, we seek to elucidate the causes of the dramatically slow protein tumbling in cells and in so doing to gain insight into how the intracellular viscosity and weak, transient interactions modulate protein mobility. To address these questions, we characterized the rotational diffusion of three model globular proteins in Escherichia coli cells using two-dimensional heteronuclear NMR spectroscopy. These proteins have a similar molecular size and globular fold but very different surface properties, and indeed, they show very different rotational diffusion in the E. coli intracellular environment. Our data are consistent with an intracellular viscosity approximately 8 times that of water, too low to be a limiting factor for observation of small globular proteins by in-cell NMR spectroscopy. Thus, we conclude that transient interactions with cytoplasmic components significantly and differentially affect the mobility of proteins and therefore their NMR detectability. Moreover, we suggest that an intricate interplay of total protein charge and hydrophobic interactions plays a key role in regulating these weak intermolecular interactions in cells.

  3. Multi-label ℓ2-regularized logistic regression for predicting activation/inhibition relationships in human protein-protein interaction networks

    PubMed Central

    Mei, Suyu; Zhang, Kun

    2016-01-01

    Protein-protein interaction (PPI) networks are naturally viewed as infrastructure to infer signalling pathways. The descriptors of signal events between two interacting proteins such as upstream/downstream signal flow, activation/inhibition relationship and protein modification are indispensable for inferring signalling pathways from PPI networks. However, such descriptors are not available in most cases as most PPI networks are seldom semantically annotated. In this work, we extend ℓ2-regularized logistic regression to the scenario of multi-label learning for predicting the activation/inhibition relationships in human PPI networks. The phenomenon that both activation and inhibition relationships exist between two interacting proteins is computationally modelled by multi-label learning framework. The problem of GO (gene ontology) sparsity is tackled by introducing the homolog knowledge as independent homolog instances. ℓ2-regularized logistic regression is accordingly adopted here to penalize the homolog noise and to reduce the computational complexity of the double-sized training data. Computational results show that the proposed method achieves satisfactory multi-label learning performance and outperforms the existing phenotype correlation method on the experimental data of Drosophila melanogaster. Several predictions have been validated against recent literature. The predicted activation/inhibition relationships in human PPI networks are provided in the supplementary file for further biomedical research. PMID:27819359

  4. Human papillomavirus 16 E2 stability and transcriptional activation is enhanced by E1 via a direct protein-protein interaction

    SciTech Connect

    King, Lauren E.; Dornan, Edward S.; Donaldson, Mary M.; Morgan, Iain M.

    2011-05-25

    Human papillomavirus 16 E1 and E2 interact with cellular factors to replicate the viral genome. E2 forms homodimers and binds to 12 bp palindromic sequences adjacent to the viral origin and recruits E1 to the origin. E1 forms a di-hexameric helicase complex that replicates the viral genome. This manuscript demonstrates that E1 stabilises the E2 protein, increasing the half life in both C33a and 293 T cells respectively. This stabilisation requires a direct protein--protein interaction. In addition, the E1 protein enhances E2 transcription function in a manner that suggests the E1 protein itself can contribute to transcriptional regulation not simply by E2 stabilisation but by direct stimulation of transcription. This activation of E2 transcription is again dependent upon an interaction with E1. Overall the results suggest that in the viral life cycle, co-expression of E1 with E2 can increase E2 stability and enhance E2 function.

  5. Investigating the dynamic aspects of drug-protein recognition through a combination of MD and NMR analyses: implications for the development of protein-protein interaction inhibitors.

    PubMed

    Meli, Massimiliano; Pagano, Katiuscia; Ragona, Laura; Colombo, Giorgio

    2014-01-01

    In this paper, we investigate the dynamic aspects of the molecular recognition between a small molecule ligand and a flat, exposed protein surface, representing a typical target in the development of protein-protein interaction inhibitors. Specifically, we analyze the complex between the protein Fibroblast Growth Factor 2 (FGF2) and a recently discovered small molecule inhibitor, labeled sm27 for which the binding site and the residues mainly involved in small molecule recognition have been previously characterized. We have approached this problem using microsecond MD simulations and NMR-based characterizations of the dynamics of the apo and holo states of the system. Using direct combination and cross-validation of the results of the two techniques, we select the set of conformational states that best recapitulate the principal dynamic and structural properties of the complex. We then use this information to generate a multi-structure representation of the sm27-FGF2 interaction. We propose this kind of representation and approach as a useful tool in particular for the characterization of systems where the mutual dynamic influence between the interacting partners is expected to play an important role. The results presented can also be used to generate new rules for the rational expansion of the chemical diversity space of FGF2 inhibitors.

  6. Protein-Protein Interactions between Intermediate Chains and the Docking Complex of Chlamydomonas Flagellar Outer Arm Dynein

    PubMed Central

    Ide, Takahiro; Owa, Mikito; King, Stephen M.; Kamiya, Ritsu; Wakabayashi, Ken-ichi

    2013-01-01

    Outer arm dynein (OAD) is bound to specific loci on outer-doublet-microtubules by interactions at two sites: via intermediate chain 1 (IC1) and the outer dynein arm docking complex (ODA-DC). Studies using Chlamydomonas mutants have suggested that the individual sites have rather weak affinities for microtubules, and therefore strong OAD attachment to microtubules is achieved by their cooperation. To test this idea, we examined interactions between IC1, IC2 (another intermediate chain) and ODA-DC using recombinant proteins. Recombinant IC1 and IC2 were found to form a 1:1 complex, and this complex associated with ODA-DC in vitro. Binding of IC1 to mutant axonemes revealed that there are specific binding sites for IC1. From these data, we propose a novel model of OAD-outer doublet association. PMID:23747306

  7. Differential protein-protein interactions of LRRK1 and LRRK2 indicate roles in distinct cellular signaling pathways

    PubMed Central

    Reyniers, Lauran; Del Giudice, Maria Grazia; Civiero, Laura; Belluzzi, Elisa; Lobbestael, Evy; Beilina, Alexandra; Arrigoni, Giorgio; Derua, Rita; Waelkens, Etienne; Li, Yan; Crosio, Claudia; Iaccarino, Ciro; Cookson, Mark R.; Baekelandt, Veerle; Greggio, Elisa; Taymans, Jean-Marc

    2014-01-01

    Genetic studies show that LRRK2, and not its closest paralogue LRRK1, is linked to Parkinson’s disease. To gain insight into the molecular and cellular basis of this discrepancy, we searched for LRRK1- and LRRK2-specific cellular processes by identifying their distinct interacting proteins. A protein microarray-based interaction screen was performed with recombinant 3xFlag-LRRK1 and 3xFlag-LRRK2 and, in parallel, co-immunoprecipitation followed by mass spectrometry was performed from SH-SY5Y neuroblastoma cell lines stably expressing 3xFlag-LRRK1 or 3xFlag-LRRK2. We identified a set of LRRK1- and LRRK2-specific as well as common interactors. One of our most prominent findings was that both screens pointed to epidermal growth factor receptor (EGF-R) as a LRRK1-specific interactor, while 14-3-3 proteins were LRRK2-specific. This is consistent with phosphosite mapping of LRRK1, revealing phosphosites outside of 14-3-3 consensus binding motifs. To assess the functional relevance of these interactions, SH-SY5Y-LRRK1 and -LRRK2 cell lines were treated with LRRK2 kinase inhibitors that disrupt 14-3-3 binding, or with EGF, an EGF-R agonist. Redistribution of LRRK2, not LRRK1, from diffuse cytoplasmic to filamentous aggregates was observed after inhibitor treatment. Similarly, EGF induced translocation of LRRK1, but not of LRRK2, to endosomes. Our study confirms that LRRK1 and LRRK2 can carry out distinct functions by interacting with different cellular proteins. PMID:24947832

  8. Ligand-induced structural changes in the Escherichia coli ferric citrate transporter reveal modes for regulating protein-protein interactions.

    PubMed

    Mokdad, Audrey; Herrick, Dawn Z; Kahn, Ali K; Andrews, Emily; Kim, Miyeon; Cafiso, David S

    2012-11-09

    Outer-membrane TonB-dependent transporters, such as the Escherichia coli ferric citrate transporter FecA, interact with the inner-membrane protein TonB through an energy-coupling segment termed the Ton box. In FecA, which regulates its own transcription, the Ton box is preceded by an N-terminal extension that interacts with the inner-membrane protein FecR. Here, site-directed spin labeling was used to examine the structural basis for transcriptional signaling and Ton box regulation in FecA. EPR spectroscopy indicates that regions of the N-terminal domain are in conformational exchange, consistent with its role as a protein binding element; however, the local fold and dynamics of the domain are not altered by substrate or TonB. Distance restraints derived from pulse EPR were used to generate models for the position of the extension in the apo, substrate-, and TonB-bound states. In the apo state, this domain is positioned at the periplasmic surface of FecA, where it interacts with the Ton box and blocks access of the Ton box to the periplasm. Substrate addition rotates the transcriptional domain and exposes the Ton box, leading to a disorder transition in the Ton box that may facilitate interactions with TonB. When a soluble fragment of TonB is bound to FecA, the transcriptional domain is displaced to one edge of the barrel, consistent with a proposed β-strand exchange mechanism. However, neither substrate nor TonB displaces the N-terminus further into the periplasm. This result suggests that the intact TonB system mediates both signaling and transport by unfolding portions of the transporter.

  9. The TissueNet v.2 database: A quantitative view of protein-protein interactions across human tissues

    PubMed Central

    Basha, Omer; Barshir, Ruth; Sharon, Moran; Lerman, Eugene; Kirson, Binyamin F.; Hekselman, Idan; Yeger-Lotem, Esti

    2017-01-01

    Knowledge of the molecular interactions of human proteins within tissues is important for identifying their tissue-specific roles and for shedding light on tissue phenotypes. However, many protein–protein interactions (PPIs) have no tissue-contexts. The TissueNet database bridges this gap by associating experimentally-identified PPIs with human tissues that were shown to express both pair-mates. Users can select a protein and a tissue, and obtain a network view of the query protein and its tissue-associated PPIs. TissueNet v.2 is an updated version of the TissueNet database previously featured in NAR. It includes over 40 human tissues profiled via RNA-sequencing or protein-based assays. Users can select their preferred expression data source and interactively set the expression threshold for determining tissue-association. The output of TissueNet v.2 emphasizes qualitative and quantitative features of query proteins and their PPIs. The tissue-specificity view highlights tissue-specific and globally-expressed proteins, and the quantitative view highlights proteins that were differentially expressed in the selected tissue relative to all other tissues. Together, these views allow users to quickly assess the unique versus global functionality of query proteins. Thus, TissueNet v.2 offers an extensive, quantitative and user-friendly interface to study the roles of human proteins across tissues. TissueNet v.2 is available at http://netbio.bgu.ac.il/tissuenet. PMID:27899616

  10. Discovery of a Potent Inhibitor of Replication Protein A Protein-Protein Interactions Using a Fragment-Linking Approach

    SciTech Connect

    Frank, Andreas O.; Feldkamp, Michael D.; Kennedy, J. Phillip; Waterson, Alex G.; Pelz, Nicholas F.; Patrone, James D.; Vangamudi, Bhavatarini; Camper, DeMarco V.; Rossanese, Olivia W.; Chazin, Walter J.; Fesik, Stephen W.

    2013-10-22

    Replication protein A (RPA), the major eukaryotic single-stranded DNA (ssDNA)-binding protein, is involved in nearly all cellular DNA transactions. The RPA N-terminal domain (RPA70N) is a recruitment site for proteins involved in DNA-damage response and repair. Selective inhibition of these protein–protein interactions has the potential to inhibit the DNA-damage response and to sensitize cancer cells to DNA-damaging agents without affecting other functions of RPA. To discover a potent, selective inhibitor of the RPA70N protein–protein interactions to test this hypothesis, we used NMR spectroscopy to identify fragment hits that bind to two adjacent sites in the basic cleft of RPA70N. High-resolution X-ray crystal structures of RPA70N–ligand complexes revealed how these fragments bind to RPA and guided the design of linked compounds that simultaneously occupy both sites. We have synthesized linked molecules that bind to RPA70N with submicromolar affinity and minimal disruption of RPA’s interaction with ssDNA.

  11. Disulfide Bond Formation and N-Glycosylation Modulate Protein-Protein Interactions in GPI-Transamidase (GPIT)

    PubMed Central

    Yi, Lina; Bozkurt, Gunes; Li, Qiubai; Lo, Stanley; Menon, Anant K.; Wu, Hao

    2017-01-01

    Glycosylphosphatidylinositol (GPI) transamidase (GPIT), the enzyme that attaches GPI anchors to proteins as they enter the lumen of the endoplasmic reticulum, is a membrane-bound hetero-pentameric complex consisting of Gpi8, Gpi16, Gaa1, Gpi17 and Gab1. Here, we expressed and purified the luminal domain of Saccharomyces cerevisiae (S. cerevisiae) Gpi8 using different expression systems, and examined its interaction with insect cell expressed luminal domain of S. cerevisiae Gpi16. We found that the N-terminal caspase-like domain of Gpi8 forms a disulfide-linked dimer, which is strengthened by N-glycosylation. The non-core domain of Gpi8 following the caspase-like domain inhibits this dimerization. In contrast to the previously reported disulfide linkage between Gpi8 and Gpi16 in human and trypanosome GPIT, our data show that the luminal domains of S. cerevisiae Gpi8 and S. cerevisiae Gpi16 do not interact directly, nor do they form a disulfide bond in the intact S. cerevisiae GPIT. Our data suggest that subunit interactions within the GPIT complex from different species may vary, a feature that should be taken into account in future structural and functional studies. PMID:28374821

  12. 3D model for Cancerous Inhibitor of Protein Phosphatase 2A armadillo domain unveils highly conserved protein-protein interaction characteristics.

    PubMed

    Dahlström, Käthe M; Salminen, Tiina A

    2015-12-07

    Cancerous Inhibitor of Protein Phosphatase 2A (CIP2A) is a human oncoprotein, which exerts its cancer-promoting function through interaction with other proteins, for example Protein Phosphatase 2A (PP2A) and MYC. The lack of structural information for CIP2A significantly prevents the design of anti-cancer therapeutics targeting this protein. In an attempt to counteract this fact, we modeled the three-dimensional structure of the N-terminal domain (CIP2A-ArmRP), analyzed key areas and amino acids, and coupled the results to the existing literature. The model reliably shows a stable armadillo repeat fold with a positively charged groove. The fact that this conserved groove highly likely binds peptides is corroborated by the presence of a conserved polar ladder, which is essential for the proper peptide-binding mode of armadillo repeat proteins and, according to our results, several known CIP2A interaction partners appropriately possess an ArmRP-binding consensus motif. Moreover, we show that Arg229Gln, which has been linked to the development of cancer,