WorldWideScience

Sample records for analyse protein-protein interactions

  1. DockAnalyse: an application for the analysis of protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Cedano Juan

    2010-10-01

    Full Text Available Abstract Background Is it possible to identify what the best solution of a docking program is? The usual answer to this question is the highest score solution, but interactions between proteins are dynamic processes, and many times the interaction regions are wide enough to permit protein-protein interactions with different orientations and/or interaction energies. In some cases, as in a multimeric protein complex, several interaction regions are possible among the monomers. These dynamic processes involve interactions with surface displacements between the proteins to finally achieve the functional configuration of the protein complex. Consequently, there is not a static and single solution for the interaction between proteins, but there are several important configurations that also have to be analyzed. Results To extract those representative solutions from the docking output datafile, we have developed an unsupervised and automatic clustering application, named DockAnalyse. This application is based on the already existing DBscan clustering method, which searches for continuities among the clusters generated by the docking output data representation. The DBscan clustering method is very robust and, moreover, solves some of the inconsistency problems of the classical clustering methods like, for example, the treatment of outliers and the dependence of the previously defined number of clusters. Conclusions DockAnalyse makes the interpretation of the docking solutions through graphical and visual representations easier by guiding the user to find the representative solutions. We have applied our new approach to analyze several protein interactions and model the dynamic protein interaction behavior of a protein complex. DockAnalyse might also be used to describe interaction regions between proteins and, therefore, guide future flexible dockings. The application (implemented in the R package is accessible.

  2. DockAnalyse: an application for the analysis of protein-protein interactions

    OpenAIRE

    Cedano Juan; Querol Enrique; Bonàs Sílvia; Gómez Antonio; Delicado Pedro; Amela Isaac

    2010-01-01

    Abstract Background Is it possible to identify what the best solution of a docking program is? The usual answer to this question is the highest score solution, but interactions between proteins are dynamic processes, and many times the interaction regions are wide enough to permit protein-protein interactions with different orientations and/or interaction energies. In some cases, as in a multimeric protein complex, several interaction regions are possible among the monomers. These dynamic pro...

  3. Protein-protein interactions

    DEFF Research Database (Denmark)

    Byron, Olwyn; Vestergaard, Bente

    2015-01-01

    Responsive formation of protein:protein interaction (PPI) upon diverse stimuli is a fundament of cellular function. As a consequence, PPIs are complex, adaptive entities, and exist in structurally heterogeneous interplays defined by the energetic states of the free and complexed protomers. The...

  4. Protein-Protein Interaction Databases

    DEFF Research Database (Denmark)

    Szklarczyk, Damian; Jensen, Lars Juhl

    2015-01-01

    of research are explored. Here we present an overview of the most widely used protein-protein interaction databases and the methods they employ to gather, combine, and predict interactions. We also point out the trade-off between comprehensiveness and accuracy and the main pitfall scientists have to be aware...

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

    Science.gov (United States)

    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

  6. Principles of protein-protein interactions.

    OpenAIRE

    Jones, S; Thornton, J. M.

    1996-01-01

    This review examines protein complexes in the Brookhaven Protein Databank to gain a better understanding of the principles governing the interactions involved in protein-protein recognition. The factors that influence the formation of protein-protein complexes are explored in four different types of protein-protein complexes--homodimeric proteins, heterodimeric proteins, enzyme-inhibitor complexes, and antibody-protein complexes. The comparison between the complexes highlights differences tha...

  7. Protein-Protein Interaction Analysis by Docking

    OpenAIRE

    Stephan Ederer; Florian Fink; Wolfram Gronwald

    2009-01-01

    Based on a protein-protein docking approach we have developed a procedure to verify or falsify protein-protein interactions that were proposed by other methods such as yeast-2-hybrid assays. Our method currently utilizes intermolecular energies but can be expanded to incorporate additional terms such as amino acid based pair-potentials. We show some early results that demonstrate the general applicability of our approach.

  8. SPIDer: Saccharomyces protein-protein interaction database

    Directory of Open Access Journals (Sweden)

    Li Zhenbo

    2006-12-01

    Full Text Available Abstract Background Since proteins perform their functions by interacting with one another and with other biomolecules, reconstructing a map of the protein-protein interactions of a cell, experimentally or computationally, is an important first step toward understanding cellular function and machinery of a proteome. Solely derived from the Gene Ontology (GO, we have defined an effective method of reconstructing a yeast protein interaction network by measuring relative specificity similarity (RSS between two GO terms. Description Based on the RSS method, here, we introduce a predicted Saccharomyces protein-protein interaction database called SPIDer. It houses a gold standard positive dataset (GSP with high confidence level that covered 79.2% of the high-quality interaction dataset. Our predicted protein-protein interaction network reconstructed from the GSPs consists of 92 257 interactions among 3600 proteins, and forms 23 connected components. It also provides general links to connect predicted protein-protein interactions with three other databases, DIP, BIND and MIPS. An Internet-based interface provides users with fast and convenient access to protein-protein interactions based on various search features (searching by protein information, GO term information or sequence similarity. In addition, the RSS value of two GO terms in the same ontology, and the inter-member interactions in a list of proteins of interest or in a protein complex could be retrieved. Furthermore, the database presents a user-friendly graphical interface which is created dynamically for visualizing an interaction sub-network. The database is accessible at http://cmb.bnu.edu.cn/SPIDer/index.html. Conclusion SPIDer is a public database server for protein-protein interactions based on the yeast genome. It provides a variety of search options and graphical visualization of an interaction network. In particular, it will be very useful for the study of inter-member interactions

  9. PREFACE: Protein protein interactions: principles and predictions

    Science.gov (United States)

    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

  10. Anisotropic Contributions to Protein-Protein Interactions.

    Science.gov (United States)

    Quang, Leigh J; Sandler, Stanley I; Lenhoff, Abraham M

    2014-02-11

    The anisotropy of shape and functionality of proteins complicates the prediction of protein-protein interactions. We examine the distribution of electrostatic and nonelectrostatic contributions to these interactions for two globular proteins, lysozyme and chymosin B, which differ in molecular weight by about a factor of 2. The interaction trends for these proteins are computed in terms of contributions to the osmotic second virial coefficient that are evaluated using atomistic models of the proteins. Our emphasis is on identifying the orientational configurations that contribute most strongly to the overall interactions due to high-complementarity interactions, and on calculating the effect of ionic strength on such interactions. The results emphasize the quantitative importance of several features of protein interactions, notably that despite differences in their frequency of occurrence, configurations differing appreciably in interaction energy can contribute meaningfully to overall interactions. However, relatively small effects due to charge anisotropy or specific hydration can affect the overall interaction significantly only if they contribute to strongly attractive configurations. The results emphasize the necessity of accounting for detailed anisotropy to capture actual experimental trends, and the sensitivity of even very detailed atomistic models to subtle solution contributions. PMID:26580057

  11. How do oncoprotein mutations rewire protein-protein interaction networks?

    Science.gov (United States)

    Bowler, Emily H; Wang, Zhenghe; Ewing, Rob M

    2015-01-01

    The acquisition of mutations that activate oncogenes or inactivate tumor suppressors is a primary feature of most cancers. Mutations that directly alter protein sequence and structure drive the development of tumors through aberrant expression and modification of proteins, in many cases directly impacting components of signal transduction pathways and cellular architecture. Cancer-associated mutations may have direct or indirect effects on proteins and their interactions and while the effects of mutations on signaling pathways have been widely studied, how mutations alter underlying protein-protein interaction networks is much less well understood. Systematic mapping of oncoprotein protein interactions using proteomics techniques as well as computational network analyses is revealing how oncoprotein mutations perturb protein-protein interaction networks and drive the cancer phenotype. PMID:26325016

  12. Protein-protein interaction databases: keeping up with growing interactomes

    OpenAIRE

    Lehne Benjamin; Schlitt Thomas

    2009-01-01

    Abstract Over the past few years, the number of known protein-protein interactions has increased substantially. To make this information more readily available, a number of publicly available databases have set out to collect and store protein-protein interaction data. Protein-protein interactions have been retrieved from six major databases, integrated and the results compared. The six databases (the Biological General Repository for Interaction Datasets [BioGRID], the Molecular INTeraction ...

  13. The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

    Institute of Scientific and Technical Information of China (English)

    Wei Gong; Kun He; Mike Covington; S.R Dinesh-Kumar; Michael Snyder; Stacey L.Harmer; Yu-Xian Zhu; Xing Wang Deng

    2008-01-01

    We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to constructprotein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and proteinprotein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale.

  14. New approach for predicting protein-protein interactions

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    @@ Protein-protein interactions (PPIs) are of vital importance for virtually all processes of a living cell. The study of these associations of protein molecules could improve people's understanding of diseases and provide basis for therapeutic approaches.

  15. Geometric De-noising of Protein-Protein Interaction Networks

    OpenAIRE

    Kuchaiev, Oleksii; Rasajski, Marija; Higham, Desmond J.; Przul, Natasa; Przytycka, Teresa Maria

    2009-01-01

    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, i...

  16. How Many Protein-Protein Interactions Types Exist in Nature?

    OpenAIRE

    Garma, Leonardo; Mukherjee, Srayanta; Mitra, Pralay; Zhang, Yang

    2012-01-01

    “Protein quaternary structure universe” refers to the ensemble of all protein-protein complexes across all organisms in nature. The number of quaternary folds thus corresponds to the number of ways proteins physically interact with other proteins. This study focuses on answering two basic questions: Whether the number of protein-protein interactions is limited and, if yes, how many different quaternary folds exist in nature. By all-to-all sequence and structure comparisons, we grouped the pro...

  17. How Many Protein-Protein Interactions Types Exist in Nature?

    OpenAIRE

    Leonardo Garma; Srayanta Mukherjee; Pralay Mitra; Yang Zhang

    2012-01-01

    "Protein quaternary structure universe" refers to the ensemble of all protein-protein complexes across all organisms in nature. The number of quaternary folds thus corresponds to the number of ways proteins physically interact with other proteins. This study focuses on answering two basic questions: Whether the number of protein-protein interactions is limited and, if yes, how many different quaternary folds exist in nature. By all-to-all sequence and structure comparisons, we grouped the pro...

  18. Protein-protein interaction databases: keeping up with growing interactomes

    Directory of Open Access Journals (Sweden)

    Lehne Benjamin

    2009-04-01

    Full Text Available Abstract Over the past few years, the number of known protein-protein interactions has increased substantially. To make this information more readily available, a number of publicly available databases have set out to collect and store protein-protein interaction data. Protein-protein interactions have been retrieved from six major databases, integrated and the results compared. The six databases (the Biological General Repository for Interaction Datasets [BioGRID], the Molecular INTeraction database [MINT], the Biomolecular Interaction Network Database [BIND], the Database of Interacting Proteins [DIP], the IntAct molecular interaction database [IntAct] and the Human Protein Reference Database [HPRD] differ in scope and content; integration of all datasets is non-trivial owing to differences in data annotation. With respect to human protein-protein interaction data, HPRD seems to be the most comprehensive. To obtain a complete dataset, however, interactions from all six databases have to be combined. To overcome this limitation, meta-databases such as the Agile Protein Interaction Database (APID offer access to integrated protein-protein interaction datasets, although these also currently have certain restrictions.

  19. Information assessment on predicting protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Gerstein Mark

    2004-10-01

    Full Text Available Abstract Background Identifying protein-protein interactions is fundamental for understanding the molecular machinery of the cell. Proteome-wide studies of protein-protein interactions are of significant value, but the high-throughput experimental technologies suffer from high rates of both false positive and false negative predictions. In addition to high-throughput experimental data, many diverse types of genomic data can help predict protein-protein interactions, such as mRNA expression, localization, essentiality, and functional annotation. Evaluations of the information contributions from different evidences help to establish more parsimonious models with comparable or better prediction accuracy, and to obtain biological insights of the relationships between protein-protein interactions and other genomic information. Results Our assessment is based on the genomic features used in a Bayesian network approach to predict protein-protein interactions genome-wide in yeast. In the special case, when one does not have any missing information about any of the features, our analysis shows that there is a larger information contribution from the functional-classification than from expression correlations or essentiality. We also show that in this case alternative models, such as logistic regression and random forest, may be more effective than Bayesian networks for predicting interactions. Conclusions In the restricted problem posed by the complete-information subset, we identified that the MIPS and Gene Ontology (GO functional similarity datasets as the dominating information contributors for predicting the protein-protein interactions under the framework proposed by Jansen et al. Random forests based on the MIPS and GO information alone can give highly accurate classifications. In this particular subset of complete information, adding other genomic data does little for improving predictions. We also found that the data discretizations used in the

  20. Detecting mutually exclusive interactions in protein-protein interaction maps.

    KAUST Repository

    Sánchez Claros, Carmen

    2012-06-08

    Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.

  1. Direct Probing of Protein-Protein Interactions

    International Nuclear Information System (INIS)

    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

  2. Direct Probing of Protein-Protein Interactions

    Energy Technology Data Exchange (ETDEWEB)

    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.

  3. Transient protein-protein interactions visualized by solution NMR.

    Science.gov (United States)

    Liu, Zhu; Gong, Zhou; Dong, Xu; Tang, Chun

    2016-01-01

    Proteins interact with each other to establish their identities in cell. The affinities for the interactions span more than ten orders of magnitude, and KD values in μM-mM regimen are considered transient and are important in cell signaling. Solution NMR including diamagnetic and paramagnetic techniques has enabled atomic-resolution depictions of transient protein-protein interactions. Diamagnetic NMR allows characterization of protein complexes with KD values up to several mM, whereas ultraweak and fleeting complexes can be modeled with the use of paramagnetic NMR especially paramagnetic relaxation enhancement (PRE). When tackling ever-larger protein complexes, PRE can be particularly useful in providing long-range intermolecular distance restraints. As NMR measurements are averaged over the ensemble of complex structures, structural information for dynamic protein-protein interactions besides the stereospecific one can often be extracted. Herein the protein interaction dynamics are exemplified by encounter complexes, alternative binding modes, and coupled binding/folding of intrinsically disordered proteins. Further integration of NMR with other biophysical techniques should allow better visualization of transient protein-protein interactions. In particular, single-molecule data may facilitate the interpretation of ensemble-averaged NMR data. Though same structures of proteins and protein complexes were found in cell as in diluted solution, we anticipate that the dynamics of transient protein protein-protein interactions be different, which awaits awaits exploration by NMR. This article is part of a Special Issue entitled: Physiological Enzymology and Protein Functions. This article is part of a Special Issue entitled: Physiological Enzymology and Protein Functions. PMID:25896389

  4. Detecting protein-protein interactions in living cells

    DEFF Research Database (Denmark)

    Gottschalk, Marie; Bach, Anders; Hansen, Jakob Lerche;

    2009-01-01

    to the endogenous C-terminal peptide of the NMDA receptor, as evaluated by a cell-free protein-protein interaction assay. However, it is important to address both membrane permeability and effect in living cells. Therefore a bioluminescence resonance energy transfer (BRET) assay was established, where the C...

  5. Hub Promiscuity in Protein-Protein Interaction Networks

    OpenAIRE

    Haruki Nakamura; Kengo Kinoshita; Ashwini Patil

    2010-01-01

    Hubs are proteins with a large number of interactions in a protein-protein interaction network. They are the principal agents in the interaction network and affect its function and stability. Their specific recognition of many different protein partners is of great interest from the structural viewpoint. Over the last few years, the structural properties of hubs have been extensively studied. We review the currently known features that are particular to hubs, possibly affecting their binding ...

  6. Protein-Protein Interaction Detection: Methods and Analysis

    OpenAIRE

    V. Srinivasa Rao; Srinivas, K.; Sujini, G. N.; G. N. Sunand Kumar

    2014-01-01

    Protein-protein interaction plays key role in predicting the protein function of target protein and drug ability of molecules. The majority of genes and proteins realize resulting phenotype functions as a set of interactions. The in vitro and in vivo methods like affinity purification, Y2H (yeast 2 hybrid), TAP (tandem affinity purification), and so forth have their own limitations like cost, time, and so forth, and the resultant data sets are noisy and have more false positives to annotate t...

  7. Targeting protein-protein interactions as an anticancer strategy

    OpenAIRE

    Ivanov, Andrei A.; Khuri, Fadlo R.; Fu, Haian

    2013-01-01

    The emergence and convergence of cancer genomics, targeted therapies, and network oncology have significantly expanded the landscape of protein-protein interaction (PPI) networks in cancer for therapeutic discovery. Extensive biological and clinical investigations have led to the identification of protein interaction hubs and nodes that are critical for the acquisition and maintaining characteristics of cancer essential for cell transformation. Such cancer enabling PPIs have become promising ...

  8. Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

    OpenAIRE

    Peng Liu; Lei Yang; Daming Shi; Xianglong Tang

    2015-01-01

    A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction net...

  9. Sentence Simplification Aids Protein-Protein Interaction Extraction

    OpenAIRE

    Jonnalagadda, Siddhartha; Gonzalez, Graciela

    2010-01-01

    Accurate systems for extracting Protein-Protein Interactions (PPIs) automatically from biomedical articles can help accelerate biomedical research. Biomedical Informatics researchers are collaborating to provide metaservices and advance the state-of-art in PPI extraction. One problem often neglected by current Natural Language Processing systems is the characteristic complexity of the sentences in biomedical literature. In this paper, we report on the impact that automatic simplification of s...

  10. Detecting overlapping protein complexes in protein-protein interaction networks

    OpenAIRE

    Nepusz, Tamás; Yu, Haiyuan; Paccanaro, Alberto

    2012-01-01

    We introduce clustering with overlapping neighborhood expansion (ClusterONE), a method for detecting potentially overlapping protein complexes from protein-protein interaction data. ClusterONE-derived complexes for several yeast data sets showed better correspondence with reference complexes in the Munich Information Center for Protein Sequence (MIPS) catalog and complexes derived from the Saccharomyces Genome Database (SGD) than the results of seven popular methods. The results also showed a...

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

    Directory of Open Access Journals (Sweden)

    Oleksii Kuchaiev

    2009-08-01

    Full Text Available 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.

  12. Understanding Protein-Protein Interactions Using Local Structural Features

    DEFF Research Database (Denmark)

    Planas-Iglesias, Joan; Bonet, Jaume; García-García, Javier;

    2013-01-01

    Protein-protein interactions (PPIs) play a relevant role among the different functions of a cell. Identifying the PPI network of a given organism (interactome) is useful to shed light on the key molecular mechanisms within a biological system. In this work, we show the role of structural features...... interacting and non-interacting protein pairs to classify the structural features that sustain the binding (or non-binding) behavior. Our study indicates that not only the interacting region but also the rest of the protein surface are important for the interaction fate. The interpretation of this...... classification suggests that the balance between favoring and disfavoring structural features determines if a pair of proteins interacts or not. Our results are in agreement with previous works and support the funnel-like intermolecular energy landscape theory that explains PPIs. We have used these features to...

  13. Protein-protein interactions in DNA mismatch repair.

    Science.gov (United States)

    Friedhoff, Peter; Li, Pingping; Gotthardt, Julia

    2016-02-01

    The principal DNA mismatch repair proteins MutS and MutL are versatile enzymes that couple DNA mismatch or damage recognition to other cellular processes. Besides interaction with their DNA substrates this involves transient interactions with other proteins which is triggered by the DNA mismatch or damage and controlled by conformational changes. Both MutS and MutL proteins have ATPase activity, which adds another level to control their activity and interactions with DNA substrates and other proteins. Here we focus on the protein-protein interactions, protein interaction sites and the different levels of structural knowledge about the protein complexes formed with MutS and MutL during the mismatch repair reaction. PMID:26725162

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

    Science.gov (United States)

    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.

  15. Sentence Simplification Aids Protein-Protein Interaction Extraction

    CERN Document Server

    Jonnalagadda, Siddhartha

    2010-01-01

    Accurate systems for extracting Protein-Protein Interactions (PPIs) automatically from biomedical articles can help accelerate biomedical research. Biomedical Informatics researchers are collaborating to provide metaservices and advance the state-of-art in PPI extraction. One problem often neglected by current Natural Language Processing systems is the characteristic complexity of the sentences in biomedical literature. In this paper, we report on the impact that automatic simplification of sentences has on the performance of a state-of-art PPI extraction system, showing a substantial improvement in recall (8%) when the sentence simplification method is applied, without significant impact to precision.

  16. Bioinformatic Prediction of WSSV-Host Protein-Protein Interaction

    Directory of Open Access Journals (Sweden)

    Zheng Sun

    2014-01-01

    Full Text Available WSSV is one of the most dangerous pathogens in shrimp aquaculture. However, the molecular mechanism of how WSSV interacts with shrimp is still not very clear. In the present study, bioinformatic approaches were used to predict interactions between proteins from WSSV and shrimp. The genome data of WSSV (NC_003225.1 and the constructed transcriptome data of F. chinensis were used to screen potentially interacting proteins by searching in protein interaction databases, including STRING, Reactome, and DIP. Forty-four pairs of proteins were suggested to have interactions between WSSV and the shrimp. Gene ontology analysis revealed that 6 pairs of these interacting proteins were classified into “extracellular region” or “receptor complex” GO-terms. KEGG pathway analysis showed that they were involved in the “ECM-receptor interaction pathway.” In the 6 pairs of interacting proteins, an envelope protein called “collagen-like protein” (WSSV-CLP encoded by an early virus gene “wsv001” in WSSV interacted with 6 deduced proteins from the shrimp, including three integrin alpha (ITGA, two integrin beta (ITGB, and one syndecan (SDC. Sequence analysis on WSSV-CLP, ITGA, ITGB, and SDC revealed that they possessed the sequence features for protein-protein interactions. This study might provide new insights into the interaction mechanisms between WSSV and shrimp.

  17. Mapping Protein-Protein Interactions by Quantitative Proteomics

    DEFF Research Database (Denmark)

    Dengjel, Joern; Kratchmarova, Irina; Blagoev, Blagoy

    2010-01-01

    Proteins exert their function inside a cell generally in multiprotein complexes. These complexes are highly dynamic structures changing their composition over time and cell state. The same protein may thereby fulfill different functions depending on its binding partners. Quantitative mass...... spectrometry (MS)-based proteomics in combination with affinity purification protocols has become the method of choice to map and track the dynamic changes in protein-protein interactions, including the ones occurring during cellular signaling events. Different quantitative MS strategies have been used to...... characterize protein interaction networks. In this chapter we describe in detail the use of stable isotope labeling by amino acids in cell culture (SILAC) for the quantitative analysis of stimulus-dependent dynamic protein interactions....

  18. Next-Generation Sequencing for Binary Protein-Protein Interactions

    Directory of Open Access Journals (Sweden)

    Bernhard eSuter

    2015-12-01

    Full Text Available The yeast two-hybrid (Y2H system exploits host cell genetics in order to display binary protein-protein interactions (PPIs via defined and selectable phenotypes. Numerous improvements have been made to this method, adapting the screening principle for diverse applications, including drug discovery and the scale-up for proteome wide interaction screens in human and other organisms. Here we discuss a systematic workflow and analysis scheme for screening data generated by Y2H and related assays that includes high-throughput selection procedures, readout of comprehensive results via next-generation sequencing (NGS, and the interpretation of interaction data via quantitative statistics. The novel assays and tools will serve the broader scientific community to harness the power of NGS technology to address PPI networks in health and disease. We discuss examples of how this next-generation platform can be applied to address specific questions in diverse fields of biology and medicine.

  19. Prediction and redesign of protein-protein interactions.

    Science.gov (United States)

    Lua, Rhonald C; Marciano, David C; Katsonis, Panagiotis; Adikesavan, Anbu K; Wilkins, Angela D; Lichtarge, Olivier

    2014-01-01

    Understanding the molecular basis of protein function remains a central goal of biology, with the hope to elucidate the role of human genes in health and in disease, and to rationally design therapies through targeted molecular perturbations. We review here some of the computational techniques and resources available for characterizing a critical aspect of protein function - those mediated by protein-protein interactions (PPI). We describe several applications and recent successes of the Evolutionary Trace (ET) in identifying molecular events and shapes that underlie protein function and specificity in both eukaryotes and prokaryotes. ET is a part of analytical approaches based on the successes and failures of evolution that enable the rational control of PPI. PMID:24878423

  20. Protein-protein interaction based on pairwise similarity

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    Zaki Nazar

    2009-05-01

    Full Text Available Abstract Background Protein-protein interaction (PPI is essential to most biological processes. Abnormal interactions may have implications in a number of neurological syndromes. Given that the association and dissociation of protein molecules is crucial, computational tools capable of effectively identifying PPI are desirable. In this paper, we propose a simple yet effective method to detect PPI based on pairwise similarity and using only the primary structure of the protein. The PPI based on Pairwise Similarity (PPI-PS method consists of a representation of each protein sequence by a vector of pairwise similarities against large subsequences of amino acids created by a shifting window which passes over concatenated protein training sequences. Each coordinate of this vector is typically the E-value of the Smith-Waterman score. These vectors are then used to compute the kernel matrix which will be exploited in conjunction with support vector machines. Results To assess the ability of the proposed method to recognize the difference between "interacted" and "non-interacted" proteins pairs, we applied it on different datasets from the available yeast saccharomyces cerevisiae protein interaction. The proposed method achieved reasonable improvement over the existing state-of-the-art methods for PPI prediction. Conclusion Pairwise similarity score provides a relevant measure of similarity between protein sequences. This similarity incorporates biological knowledge about proteins and it is extremely powerful when combined with support vector machine to predict PPI.

  1. Prediction of Protein-Protein Interactions Using Protein Signature Profiling

    Institute of Scientific and Technical Information of China (English)

    Mahmood; A.; Mahdavi; Yen-Han; Lin

    2007-01-01

    Protein domains are conserved and functionally independent structures that play an important role in interactions among related proteins. Domain-domain inter- actions have been recently used to predict protein-protein interactions (PPI). In general, the interaction probability of a pair of domains is scored using a trained scoring function. Satisfying a threshold, the protein pairs carrying those domains are regarded as "interacting". In this study, the signature contents of proteins were utilized to predict PPI pairs in Saccharomyces cerevisiae, Caenorhabditis ele- gans, and Homo sapiens. Similarity between protein signature patterns was scored and PPI predictions were drawn based on the binary similarity scoring function. Results show that the true positive rate of prediction by the proposed approach is approximately 32% higher than that using the maximum likelihood estimation method when compared with a test set, resulting in 22% increase in the area un- der the receiver operating characteristic (ROC) curve. When proteins containing one or two signatures were removed, the sensitivity of the predicted PPI pairs in- creased significantly. The predicted PPI pairs are on average 11 times more likely to interact than the random selection at a confidence level of 0.95, and on aver- age 4 times better than those predicted by either phylogenetic profiling or gene expression profiling.

  2. Discover protein sequence signatures from protein-protein interaction data

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    Haasl Ryan J

    2005-11-01

    Full Text Available Abstract Background The development of high-throughput technologies such as yeast two-hybrid systems and mass spectrometry technologies has made it possible to generate large protein-protein interaction (PPI datasets. Mining these datasets for underlying biological knowledge has, however, remained a challenge. Results A total of 3108 sequence signatures were found, each of which was shared by a set of guest proteins interacting with one of 944 host proteins in Saccharomyces cerevisiae genome. Approximately 94% of these sequence signatures matched entries in InterPro member databases. We identified 84 distinct sequence signatures from the remaining 172 unknown signatures. The signature sharing information was then applied in predicting sub-cellular localization of yeast proteins and the novel signatures were used in identifying possible interacting sites. Conclusion We reported a method of PPI data mining that facilitated the discovery of novel sequence signatures using a large PPI dataset from S. cerevisiae genome as input. The fact that 94% of discovered signatures were known validated the ability of the approach to identify large numbers of signatures from PPI data. The significance of these discovered signatures was demonstrated by their application in predicting sub-cellular localizations and identifying potential interaction binding sites of yeast proteins.

  3. Studying protein-protein interactions: progress, pitfalls and solutions.

    Science.gov (United States)

    Hayes, Sheri; Malacrida, Beatrice; Kiely, Maeve; Kiely, Patrick A

    2016-08-15

    Signalling proteins are intrinsic to all biological processes and interact with each other in tightly regulated and orchestrated signalling complexes and pathways. Characterization of protein binding can help to elucidate protein function within signalling pathways. This information is vital for researchers to gain a more comprehensive knowledge of cellular networks which can then be used to develop new therapeutic strategies for disease. However, studying protein-protein interactions (PPIs) can be challenging as the interactions can be extremely transient downstream of specific environmental cues. There are many powerful techniques currently available to identify and confirm PPIs. Choosing the most appropriate range of techniques merits serious consideration. The aim of this review is to provide a starting point for researchers embarking on a PPI study. We provide an overview and point of reference for some of the many methods available to identify interactions from in silico analysis and large scale screening tools through to the methods used to validate potential PPIs. We discuss the advantages and disadvantages of each method and we also provide a workflow chart to highlight the main experimental questions to consider when planning cell lysis to maximize experimental success. PMID:27528744

  4. Analysis and application of large-scale protein-protein interaction data sets

    Institute of Scientific and Technical Information of China (English)

    SUN Jingchun; XU Jinlin; LI Yixue; SHI Tieliu

    2005-01-01

    Protein-protein interactions play key roles in cells. Lots of experimental approaches and in silico methods have been developed to identify and predict large-scale protein-protein interactions. However, compared with the traditionally experimental results, the high-throughput protein-protein interaction data often contain the false positives in high probability. In order to fully utilize the large-scale data, it is necessary to develop bioinformatic methods for systematically evaluating those data in order to further improve the data reliability and mine biological information. This review summarizes the methodologies of analysis and application of high-throughput protein-protein interaction data, including the evaluation methods, the relationship between protein-protein interaction data and other protein biological information, and their applications in biological study. In addition, this paper also suggests some interesting topics on mining high-throughput protein-protein interaction data.

  5. A novel in vivo assay for the analysis of protein-protein interaction.

    OpenAIRE

    Maroun, M; Aronheim, A

    1999-01-01

    The Ras Recruitment System (RRS) is a method for identification and isolation of protein-protein interaction. The method is based on translocation of cytoplasmic mammalian Ras protein to the inner leaflet of the plasma membrane through protein-protein interaction. The system is studied in a temperature-sensitive yeast strain where the yeast Ras guanyl nucleotide exchange factor is inactive at 36 degrees C. Protein-protein interaction results in cell growth at the restrictive temperature. We d...

  6. Motif mediated protein-protein interactions as drug targets.

    Science.gov (United States)

    Corbi-Verge, Carles; Kim, Philip M

    2016-01-01

    Protein-protein interactions (PPI) are involved in virtually every cellular process and thus represent an attractive target for therapeutic interventions. A significant number of protein interactions are frequently formed between globular domains and short linear peptide motifs (DMI). Targeting these DMIs has proven challenging and classical approaches to inhibiting such interactions with small molecules have had limited success. However, recent new approaches have led to the discovery of potent inhibitors, some of them, such as Obatoclax, ABT-199, AEG-40826 and SAH-p53-8 are likely to become approved drugs. These novel inhibitors belong to a wide range of different molecule classes, ranging from small molecules to peptidomimetics and biologicals. This article reviews the main reasons for limited success in targeting PPIs, discusses how successful approaches overcome these obstacles to discovery promising inhibitors for human protein double minute 2 (HDM2), B-cell lymphoma 2 (Bcl-2), X-linked inhibitor of apoptosis protein (XIAP), and provides a summary of the promising approaches currently in development that indicate the future potential of PPI inhibitors in drug discovery. PMID:26936767

  7. Modulation of opioid receptor function by protein-protein interactions.

    Science.gov (United States)

    Alfaras-Melainis, Konstantinos; Gomes, Ivone; Rozenfeld, Raphael; Zachariou, Venetia; Devi, Lakshmi

    2009-01-01

    Opioid receptors, MORP, DORP and KORP, belong to the family A of G protein coupled receptors (GPCR), and have been found to modulate a large number of physiological functions, including mood, stress, appetite, nociception and immune responses. Exogenously applied opioid alkaloids produce analgesia, hedonia and addiction. Addiction is linked to alterations in function and responsiveness of all three opioid receptors in the brain. Over the last few years, a large number of studies identified protein-protein interactions that play an essential role in opioid receptor function and responsiveness. Here, we summarize interactions shown to affect receptor biogenesis and trafficking, as well as those affecting signal transduction events following receptor activation. This article also examines protein interactions modulating the rate of receptor endocytosis and degradation, events that play a major role in opiate analgesia. Like several other GPCRs, opioid receptors may form homo or heterodimers. The last part of this review summarizes recent knowledge on proteins known to affect opioid receptor dimerization. PMID:19273296

  8. Sequence motifs in MADS transcription factors responsible for specificity and diversification of protein-protein interaction.

    Directory of Open Access Journals (Sweden)

    Aalt D J van Dijk

    Full Text Available Protein sequences encompass tertiary structures and contain information about specific molecular interactions, which in turn determine biological functions of proteins. Knowledge about how protein sequences define interaction specificity is largely missing, in particular for paralogous protein families with high sequence similarity, such as the plant MADS domain transcription factor family. In comparison to the situation in mammalian species, this important family of transcription regulators has expanded enormously in plant species and contains over 100 members in the model plant species Arabidopsis thaliana. Here, we provide insight into the mechanisms that determine protein-protein interaction specificity for the Arabidopsis MADS domain transcription factor family, using an integrated computational and experimental approach. Plant MADS proteins have highly similar amino acid sequences, but their dimerization patterns vary substantially. Our computational analysis uncovered small sequence regions that explain observed differences in dimerization patterns with reasonable accuracy. Furthermore, we show the usefulness of the method for prediction of MADS domain transcription factor interaction networks in other plant species. Introduction of mutations in the predicted interaction motifs demonstrated that single amino acid mutations can have a large effect and lead to loss or gain of specific interactions. In addition, various performed bioinformatics analyses shed light on the way evolution has shaped MADS domain transcription factor interaction specificity. Identified protein-protein interaction motifs appeared to be strongly conserved among orthologs, indicating their evolutionary importance. We also provide evidence that mutations in these motifs can be a source for sub- or neo-functionalization. The analyses presented here take us a step forward in understanding protein-protein interactions and the interplay between protein sequences and

  9. Parallel force assay for protein-protein interactions.

    Directory of Open Access Journals (Sweden)

    Daniela Aschenbrenner

    Full Text Available 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.

  10. Protein-protein interaction as a predictor of subcellular location

    Directory of Open Access Journals (Sweden)

    Davis Melissa J

    2009-02-01

    Full Text Available Abstract Background Many biological processes are mediated by dynamic interactions between and among proteins. In order to interact, two proteins must co-occur spatially and temporally. As protein-protein interactions (PPIs and subcellular location (SCL are discovered via separate empirical approaches, PPI and SCL annotations are independent and might complement each other in helping us to understand the role of individual proteins in cellular networks. We expect reliable PPI annotations to show that proteins interacting in vivo are co-located in the same cellular compartment. Our goal here is to evaluate the potential of using PPI annotation in determining SCL of proteins in human, mouse, fly and yeast, and to identify and quantify the factors that contribute to this complementarity. Results Using publicly available data, we evaluate the hypothesis that interacting proteins must be co-located within the same subcellular compartment. Based on a large, manually curated PPI dataset, we demonstrate that a substantial proportion of interacting proteins are in fact co-located. We develop an approach to predict the SCL of a protein based on the SCL of its interaction partners, given sufficient confidence in the interaction itself. The frequency of false positive PPIs can be reduced by use of six lines of supporting evidence, three based on type of recorded evidence (empirical approach, multiplicity of databases, and multiplicity of literature citations and three based on type of biological evidence (inferred biological process, domain-domain interactions, and orthology relationships, with biological evidence more-effective than recorded evidence. Our approach performs better than four existing prediction methods in identifying the SCL of membrane proteins, and as well as or better for soluble proteins. Conclusion Understanding cellular systems requires knowledge of the SCL of interacting proteins. We show how PPI data can be used more effectively to

  11. Modularity detection in protein-protein interaction networks

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    Narayanan Tejaswini

    2011-12-01

    Full Text Available Abstract Background Many recent studies have investigated modularity in biological networks, and its role in functional and structural characterization of constituent biomolecules. A technique that has shown considerable promise in the domain of modularity detection is the Newman and Girvan (NG algorithm, which relies on the number of shortest-paths across pairs of vertices in the network traversing a given edge, referred to as the betweenness of that edge. The edge with the highest betweenness is iteratively eliminated from the network, with the betweenness of the remaining edges recalculated in every iteration. This generates a complete dendrogram, from which modules are extracted by applying a quality metric called modularity denoted by Q. This exhaustive computation can be prohibitively expensive for large networks such as Protein-Protein Interaction Networks. In this paper, we present a novel optimization to the modularity detection algorithm, in terms of an efficient termination criterion based on a target edge betweenness value, using which the process of iterative edge removal may be terminated. Results We validate the robustness of our approach by applying our algorithm on real-world protein-protein interaction networks of Yeast, C.Elegans and Drosophila, and demonstrate that our algorithm consistently has significant computational gains in terms of reduced runtime, when compared to the NG algorithm. Furthermore, our algorithm produces modules comparable to those from the NG algorithm, qualitatively and quantitatively. We illustrate this using comparison metrics such as module distribution, module membership cardinality, modularity Q, and Jaccard Similarity Coefficient. Conclusions We have presented an optimized approach for efficient modularity detection in networks. The intuition driving our approach is the extraction of holistic measures of centrality from graphs, which are representative of inherent modular structure of the

  12. A novel method for protein-protein interaction site prediction using phylogenetic substitution models

    OpenAIRE

    La, David; Kihara, Daisuke

    2011-01-01

    Protein-protein binding events mediate many critical biological functions in the cell. Typically, functionally important sites in proteins can be well identified by considering sequence conservation. However, protein-protein interaction sites exhibit higher sequence variation than other functional regions, such as catalytic sites of enzymes. Consequently, the mutational behavior leading to weak sequence conservation poses significant challenges to the protein-protein interaction site predicti...

  13. Identifying Protein-Protein Interaction Sites Using Covering Algorithm

    OpenAIRE

    Jie Song; Jiaxing Cheng; Xiuquan Du

    2009-01-01

    Identification of protein-protein interface residues is crucial for structural biology. This paper proposes a covering algorithm for predicting protein-protein interface residues with features including protein sequence profile and residue accessible area. This method adequately utilizes the characters of a covering algorithm which have simple, lower complexity and high accuracy for high dimension data. The covering algorithm can achieve a comparable performance (69.62%, Complete dataset; 60....

  14. Targeting protein-protein interactions for parasite control.

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    Christina M Taylor

    Full Text Available Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific orthologous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank. EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite and B. malayi (H. sapiens parasite, which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly

  15. Protein-protein interactions within late pre-40S ribosomes.

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    Melody G Campbell

    Full Text Available Ribosome assembly in eukaryotic organisms requires more than 200 assembly factors to facilitate and coordinate rRNA transcription, processing, and folding with the binding of the ribosomal proteins. Many of these assembly factors bind and dissociate at defined times giving rise to discrete assembly intermediates, some of which have been partially characterized with regards to their protein and RNA composition. Here, we have analyzed the protein-protein interactions between the seven assembly factors bound to late cytoplasmic pre-40S ribosomes using recombinant proteins in binding assays. Our data show that these factors form two modules: one comprising Enp1 and the export adaptor Ltv1 near the beak structure, and the second comprising the kinase Rio2, the nuclease Nob1, and a regulatory RNA binding protein Dim2/Pno1 on the front of the head. The GTPase-like Tsr1 and the universally conserved methylase Dim1 are also peripherally connected to this second module. Additionally, in an effort to further define the locations for these essential proteins, we have analyzed the interactions between these assembly factors and six ribosomal proteins: Rps0, Rps3, Rps5, Rps14, Rps15 and Rps29. Together, these results and previous RNA-protein crosslinking data allow us to propose a model for the binding sites of these seven assembly factors. Furthermore, our data show that the essential kinase Rio2 is located at the center of the pre-ribosomal particle and interacts, directly or indirectly, with every other assembly factor, as well as three ribosomal proteins required for cytoplasmic 40S maturation. These data suggest that Rio2 could play a central role in regulating cytoplasmic maturation steps.

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

    Science.gov (United States)

    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…

  17. Dynamics of protein-protein interactions studied by paramagnetic NMR spectroscopy

    NARCIS (Netherlands)

    Somireddy Venkata, Bharat Kumar Reddy

    2012-01-01

    Protein-protein interactions play an important role in all cellular processes such as signal transduction, electron transfer, gene regulation, transcription, and translation. Understanding these protein-protein interactions at the molecular level, is an important aim in structural biology. The prote

  18. Cerebral malaria: insights from host-parasite protein-protein interactions

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    Bulusu Gopalakrishnan

    2010-06-01

    Full Text Available Abstract Background Cerebral malaria is a form of human malaria wherein Plasmodium falciparum-infected red blood cells adhere to the blood capillaries in the brain, potentially leading to coma and death. Interactions between parasite and host proteins are important in understanding the pathogenesis of this deadly form of malaria. It is, therefore, necessary to study available protein-protein interactions to identify lesser known interactions that could throw light on key events of cerebral malaria. Methods Sequestration, haemostasis dysfunction, systemic inflammation and neuronal damage are key processes of cerebral malaria. Key events were identified from literature as being crucial to these processes. An integrated interactome was created using available experimental and predicted datasets as well as from literature. Interactions from this interactome were filtered based on Gene Ontology and tissue-specific annotations, and further analysed for relevance to the key events. Results PfEMP1 presentation, platelet activation and astrocyte dysfunction were identified as the key events influencing the disease. 48896 host-parasite along with other host-parasite, host-host and parasite-parasite protein-protein interactions obtained from a disease-specific corpus were combined to form an integrated interactome. Filtering of the interactome resulted in five host-parasite PPI, six parasite-parasite and two host-host PPI. The analysis of these interactions revealed the potential significance of apolipoproteins and temperature/Hsp expression on efficient PfEMP1 presentation; role of MSP-1 in platelet activation; effect of parasite proteins in TGF-β regulation and the role of albumin in astrocyte dysfunction. Conclusions This work links key host-parasite, parasite-parasite and host-host protein-protein interactions to key processes of cerebral malaria and generates hypotheses for disease pathogenesis based on a filtered interaction dataset. These

  19. Comprehensive, atomic-level characterization of structurally characterized protein-protein interactions: the PICCOLO database

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    Bickerton George R

    2011-07-01

    Full Text Available Abstract Background Structural studies are increasingly providing huge amounts of information on multi-protein assemblies. Although a complete understanding of cellular processes will be dependent on an explicit characterization of the intermolecular interactions that underlie these assemblies and mediate molecular recognition, these are not well described by standard representations. Results Here we present PICCOLO, a comprehensive relational database capturing the details of structurally characterized protein-protein interactions. Interactions are described at the level of interacting pairs of atoms, residues and polypeptide chains, with the physico-chemical nature of the interactions being characterized. Distance and angle terms are used to distinguish 12 different interaction types, including van der Waals contacts, hydrogen bonds and hydrophobic contacts. The explicit aim of PICCOLO is to underpin large-scale analyses of the properties of protein-protein interfaces. This is exemplified by an analysis of residue propensity and interface contact preferences derived from a much larger data set than previously reported. However, PICCOLO also supports detailed inspection of particular systems of interest. Conclusions The current PICCOLO database comprises more than 260 million interacting atom pairs from 38,202 protein complexes. A web interface for the database is available at http://www-cryst.bioc.cam.ac.uk/piccolo.

  20. Ribo-Proteomics Approach to Profile RNA-Protein and Protein-Protein Interaction Networks.

    Science.gov (United States)

    Yeh, Hsin-Sung; Chang, Jae-Woong; Yong, Jeongsik

    2016-01-01

    Characterizing protein-protein and protein-RNA interaction networks is a fundamental step to understanding the function of an RNA-binding protein. In many cases, these interactions are transient and highly dynamic. Therefore, capturing stable as well as transient interactions in living cells for the identification of protein-binding partners and the mapping of RNA-binding sequences is key to a successful establishment of the molecular interaction network. In this chapter, we will describe a method for capturing the molecular interactions in living cells using formaldehyde as a crosslinker and enriching a specific RNA-protein complex from cell extracts followed by mass spectrometry and Next-Gen sequencing analyses. PMID:26965265

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

    Science.gov (United States)

    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. PMID:23930922

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

    OpenAIRE

    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-whit...

  3. Domain-Domain Interactions Underlying Herpesvirus-Human Protein-Protein Interaction Networks

    OpenAIRE

    Zohar Itzhaki

    2011-01-01

    Protein-domains play an important role in mediating protein-protein interactions. Furthermore, the same domain-pairs mediate different interactions in different contexts and in various organisms, and therefore domain-pairs are considered as the building blocks of interactome networks. Here we extend these principles to the host-virus interface and find the domain-pairs that potentially mediate human-herpesvirus interactions. Notably, we find that the same domain-pairs used by other organisms ...

  4. Template-based structure modeling of protein-protein interactions

    OpenAIRE

    Szilagyi, Andras; Zhang, Yang

    2013-01-01

    The structure of protein-protein complexes can be constructed by using the known structure of other protein complexes as a template. The complex structure templates are generally detected either by homology-based sequence alignments or, given the structure of monomer components, by structure-based comparisons. Critical improvements have been made in recent years by utilizing interface recognition and by recombining monomer and complex template libraries. Encouraging progress has also been wit...

  5. Pin-Align: A New Dynamic Programming Approach to Align Protein-Protein Interaction Networks

    OpenAIRE

    Farid Amir-Ghiasvand; Abbas Nowzari-Dalini; Vida Momenzadeh

    2014-01-01

    To date, few tools for aligning protein-protein interaction networks have been suggested. These tools typically find conserved interaction patterns using various local or global alignment algorithms. However, the improvement of the speed, scalability, simplification, and accuracy of network alignment tools is still the target of new researches. In this paper, we introduce Pin-Align, a new tool for local alignment of protein-protein interaction networks. Pin-Align accuracy is tested on protein...

  6. A Cell-Based Protein-Protein Interaction Method Using a Permuted Luciferase Reporter

    OpenAIRE

    Eishingdrelo, Haifeng; Cai, Jidong; Weissensee, Paul; Sharma, Praveen; Tocci, Michael J; Wright, Paul S

    2011-01-01

    We have developed a novel cell-based protein-protein interaction assay method. The method relies on conversion of an inactive permuted luciferase containing a Tobacco Etch Virus protease (TEV) cleavage sequence fused onto protein (A) to an active luciferase upon interaction and cleavage by another protein (B) fused with the TEV protease. We demonstrate assay applicability for ligand-induced protein-protein interactions including G-protein coupled receptors, receptor tyrosine kinases and nucle...

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

    OpenAIRE

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

    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 th...

  8. Neutral evolution of Protein-protein interactions: a computational study using simple models

    OpenAIRE

    Simonson Thomas; Noirel Josselin

    2007-01-01

    Abstract Background Protein-protein interactions are central to cellular organization, and must have appeared at an early stage of evolution. To understand better their role, we consider a simple model of protein evolution and determine the effect of an explicit selection for Protein-protein interactions. Results In the model, viable sequences all have the same fitness, following the neutral evolution theory. A very simple, two-dimensional lattice representation of the protein structures is u...

  9. Inferring protein function by domain context similarities in protein-protein interaction networks

    OpenAIRE

    Sun Zhirong; Liu Ke; Chen Hu; Zhang Song

    2009-01-01

    Abstract Background Genome sequencing projects generate massive amounts of sequence data but there are still many proteins whose functions remain unknown. The availability of large scale protein-protein interaction data sets makes it possible to develop new function prediction methods based on protein-protein interaction (PPI) networks. Although several existing methods combine multiple information resources, there is no study that integrates protein domain information and PPI networks to pre...

  10. The Role of Shape Complementarity in the Protein-Protein Interactions

    OpenAIRE

    Li, Ye; Zhang, Xianren; Cao, Dapeng

    2013-01-01

    We use a dissipative particle dynamic simulation to investigate the effects of shape complementarity on the protein-protein interactions. By monitoring different kinds of protein shape-complementarity modes, we gave a clear mechanism to reveal the role of the shape complementarity in the protein-protein interactions, i.e., when the two proteins with shape complementarity approach each other, the conformation of lipid chains between two proteins would be restricted significantly. The lipid mol...

  11. Protein-Protein Interactions in a Crowded Environment: An Analysis via Cross-Docking Simulations and Evolutionary Information

    OpenAIRE

    Lopes, Anne; Sacquin-Mora, Sophie; Dimitrova, Viktoriya; Laine, Elodie; Ponty, Yann; Carbone, Alessandra

    2013-01-01

    Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information sh...

  12. Positive Selection and Centrality in the Yeast and Fly Protein-Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Sandip Chakraborty

    2016-01-01

    Full Text Available Proteins within a molecular network are expected to be subject to different selective pressures depending on their relative hierarchical positions. However, it is not obvious what genes within a network should be more likely to evolve under positive selection. On one hand, only mutations at genes with a relatively high degree of control over adaptive phenotypes (such as those encoding highly connected proteins are expected to be “seen” by natural selection. On the other hand, a high degree of pleiotropy at these genes is expected to hinder adaptation. Previous analyses of the human protein-protein interaction network have shown that genes under long-term, recurrent positive selection (as inferred from interspecific comparisons tend to act at the periphery of the network. It is unknown, however, whether these trends apply to other organisms. Here, we show that long-term positive selection has preferentially targeted the periphery of the yeast interactome. Conversely, in flies, genes under positive selection encode significantly more connected and central proteins. These observations are not due to covariation of genes’ adaptability and centrality with confounding factors. Therefore, the distribution of proteins encoded by genes under recurrent positive selection across protein-protein interaction networks varies from one species to another.

  13. The role of shape complementarity in the protein-protein interactions.

    Science.gov (United States)

    Li, Ye; Zhang, Xianren; Cao, Dapeng

    2013-01-01

    We use a dissipative particle dynamic simulation to investigate the effects of shape complementarity on the protein-protein interactions. By monitoring different kinds of protein shape-complementarity modes, we gave a clear mechanism to reveal the role of the shape complementarity in the protein-protein interactions, i.e., when the two proteins with shape complementarity approach each other, the conformation of lipid chains between two proteins would be restricted significantly. The lipid molecules tend to leave the gap formed by two proteins to maximize the configuration entropy, and therefore yield an effective entropy-induced protein-protein attraction, which enhances the protein aggregation. In short, this work provides an insight into understanding the importance of the shape complementarity in the protein-protein interactions especially for protein aggregation and antibody-antigen complexes. Definitely, the shape complementarity is the third key factor affecting protein aggregation and complex, besides the electrostatic-complementarity and hydrophobic complementarity. PMID:24253561

  14. On the analysis of protein-protein interactions via knowledge-based potentials for the prediction of protein-protein docking

    DEFF Research Database (Denmark)

    Feliu, Elisenda; Aloy, Patrick; Oliva, Baldo

    2011-01-01

    results were compared with a residue-pair potential scoring function (RPScore) and an atomic-detailed scoring function (Zrank). We have combined knowledge-based potentials to score protein-protein poses of decoys of complexes classified either as transient or as permanent protein-protein interactions......Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions for...... selecting rigid-body docking poses. These potentials include the energetic component that provides the residues with a particular secondary structure and surface accessibility. These scoring functions have been tested on a state-of-art benchmark dataset and on a decoy dataset of permanent interactions. Our...

  15. Single Bead Affinity Detection (SINBAD) for the Analysis of Protein-Protein Interactions

    OpenAIRE

    Schulte, Roberta; Talamas, Jessica; Doucet, Christine; Hetzer, Martin W.

    2008-01-01

    We present a miniaturized pull-down method for the detection of protein-protein interactions using standard affinity chromatography reagents. Binding events between different proteins, which are color-coded with quantum dots (QDs), are visualized on single affinity chromatography beads by fluorescence microscopy. The use of QDs for single molecule detection allows the simultaneous analysis of multiple protein-protein binding events and reduces the amount of time and material needed to perform...

  16. Photolytic Crosslinking to Probe Protein-Protein and Protein-Matrix Interactions In Lyophilized Powders

    OpenAIRE

    Iyer, Lavanya K.; Moorthy, Balakrishnan S.; Topp, Elizabeth M.

    2015-01-01

    Protein structure and local environment in lyophilized formulations were probed using high-resolution solid-state photolytic crosslinking 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 l...

  17. Genetically Encoded Molecular Tension Probe for Tracing Protein-Protein Interactions in Mammalian Cells.

    Science.gov (United States)

    Kim, Sung Bae; Nishihara, Ryo; Citterio, Daniel; Suzuki, Koji

    2016-02-17

    Optical imaging of protein-protein interactions (PPIs) facilitates comprehensive elucidation of intracellular molecular events. We demonstrate an optical measure for visualizing molecular tension triggered by any PPI in mammalian cells. Twenty-three kinds of candidate designs were fabricated, in which a full-length artificial luciferase (ALuc) was sandwiched between two model proteins of interest, e.g., FKBP and FRB. One of the designs greatly enhanced the bioluminescence in response to varying concentrations of rapamycin. It is confirmed with negative controls that the elevated bioluminescence is solely motivated from the molecular tension. The probe design was further modified toward eliminating the C-terminal end of ALuc and was found to improve signal-to-background ratios, named "a combinational probe". The utilities were elucidated with detailed substrate selectivity, bioluminescence imaging of live cells, and different PPI models. This study expands capabilities of luciferases as a tool for analyses of molecular dynamics and cell signaling in living subjects. PMID:26322739

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

    Science.gov (United States)

    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. PMID:26945504

  19. A modified resonant recognition model to predict protein-protein interaction

    Institute of Scientific and Technical Information of China (English)

    LIU Xiang; WANG Yifei

    2007-01-01

    Proteins are fundamental components of all living cells and the protein-protein interaction plays an important role in vital movement.This paper briefly introduced the original Resonant Recognition Model (RRM),and then modified it by using the wavelet transform to acquire the Modified Resonant Recognition Model (MRRM).The key characteristic of the new model is that it can predict directly the proteinprotein interaction from the primary sequence,and the MRRM is more suitable than the RRM for this prediction.The results of numerical experiments show that the MRRM is effective for predicting the protein-protein interaction.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  1. Coevolution study of mitochondria respiratory chain proteins:Toward the understanding of protein-protein interaction

    Institute of Scientific and Technical Information of China (English)

    Ming Yang; Yan Ge; Jiayan Wu; Jingfa Xiao; Jun Yu

    2011-01-01

    Coevolution can be seen as the interdependency between evolutionary histories. In the context of protein evolution, functional correlation proteins are ever-present coordinated evolutionary characters without disruption of organismal integrity. As to complex system, there are two forms of protein-protein interactions in vivo, which refer to inter-complex interaction and intra-complex interaction. In this paper, we studied the difference of coevolution characters between inter-complex interaction and intra-complex interaction using "Mirror tree" method on the respiratory chain (RC) proteins. We divided the correlation coefficients of every pairwise RC proteins into two groups corresponding to the binary protein-protein interaction in intra-complex and the binary protein-protein interaction in inter-complex, respectively. A dramatical discrepancy is detected between the coevolution characters of the two sets of protein interactions (Wilcoxon test, p-value = 4.4 x 10-6). Our finding reveals some critical information on coevolutionary study and assists the mechanical investigation of protein-protein interaction.Furthermore, the results also provide some unique clue for supramolecular organization of protein complexes in the mitochondrial inner membrane. More detailed binding sites map and genome information of nuclear encoded RC proteins will be extraordinary valuable for the further mitochondria dynamics study.

  2. Protein-protein interactions of PDE4 family members - Functions, interactions and therapeutic value.

    Science.gov (United States)

    Klussmann, Enno

    2016-07-01

    The second messenger cyclic adenosine monophosphate (cAMP) is ubiquitous and directs a plethora of functions in all cells. Although theoretically freely diffusible through the cell from the site of its synthesis it is not evenly distributed. It rather is shaped into gradients and these gradients are established by phospodiesterases (PDEs), the only enzymes that hydrolyse cAMP and thereby terminate cAMP signalling upstream of cAMP's effector systems. Miles D. Houslay has devoted most of his scientific life highly successfully to a particular family of PDEs, the PDE4 family. The family is encoded by four genes and gives rise to around 20 enzymes, all with different functions. M. Houslay has discovered many of these functions and realised early on that PDE4 family enzymes are attractive drug targets in a variety of human diseases, but not their catalytic activity as that is encoded in conserved domains in all family members. He postulated that targeting the intracellular location would provide the specificity that modern innovative drugs require to improve disease conditions with fewer side effects than conventional drugs. Due to the wealth of M. Houslay's work, this article can only summarize some of his discoveries and, therefore, focuses on protein-protein interactions of PDE4. The aim is to discuss functions of selected protein-protein interactions and peptide spot technology, which M. Houslay introduced into the PDE4 field for identifying interacting domains. The therapeutic potential of PDE4 interactions will also be discussed. PMID:26498857

  3. Protein-protein interactions of mitochondrial-associated protein via bioluminescence resonance energy transfer

    Science.gov (United States)

    Koshiba, Takumi

    2015-01-01

    Protein-protein interactions are essential biological reactions occurring at inter- and intra-cellular levels. The analysis of their mechanism is generally required in order link to understand their various cellular functions. Bioluminescence resonance energy transfer (BRET), which is based on an enzymatic activity of luciferase, is a useful tool for investigating protein-protein interactions in live cells. The combination of the BRET system and biomolecular fluorescence complementation (BiFC) would provide us a better understanding of the hetero-oligomeric structural states of protein complexes. In this review, we discuss the application of BRET to the protein-protein interactions of mitochondrial-associated proteins and discuss its physiological relevance. PMID:27493852

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

    Science.gov (United States)

    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

  5. A proteomics strategy to elucidate functional protein-protein interactions applied to EGF signaling

    DEFF Research Database (Denmark)

    Blagoev, B.; Kratchmarova, I.; Ong, S.E.;

    2003-01-01

    Mass spectrometry-based proteomics can reveal protein-protein interactions on a large scale, but it has been difficult to separate background binding from functionally important interactions and still preserve weak binders. To investigate the epidermal growth factor receptor (EGFR) pathway, we em...

  6. Characterization of Protein Complexes and Subcomplexes in Protein-Protein Interaction Databases

    OpenAIRE

    Nazar Zaki; Elfadil A. Mohamed; Antonio Mora

    2015-01-01

    The identification and characterization of protein complexes implicated in protein-protein interaction data are crucial to the understanding of the molecular events under normal and abnormal physiological conditions. This paper provides a novel characterization of subcomplexes in protein interaction databases, stressing definition and representation issues, quantification, biological validation, network metrics, motifs, modularity, and gene ontology (GO) terms. The paper introduces the concep...

  7. Analysis of correlations between protein complex and protein-protein interaction and mRNA expression

    Institute of Scientific and Technical Information of China (English)

    CAI Lun; XUE Hong; LU Hongchao; ZHAO Yi; ZHU Xiaopeng; BU Dongbo; LING Lunjiang; CHEN Runsheng

    2003-01-01

    Protein-protein interaction is a physical interaction of two proteins in living cells. In budding yeast Saccharomyces cerevisiae, large-scale protein-protein interaction data have been obtained through high-throughput yeast two-hybrid systems (Y2H) and protein complex purification techniques based on mass-spectrometry. Here, we collect 11855 interactions between total 2617 proteins. Through seriate genome-wide mRNA expression data, similarity between two genes could be measured. Protein complex data can also be obtained publicly and can be translated to pair relationship that any two proteins can only exist in the same complex or not. Analysis of protein complex data, protein-protein interaction data and mRNA expression data can elucidate correlations between them. The results show that proteins that have interactions or similar expression patterns have a higher possibility to be in the same protein complex than randomized selected proteins, and proteins which have interactions and similar expression patterns are even more possible to exist in the same protein complex. The work indicates that comprehensive integration and analysis of public large-scale bioinformatical data, such as protein complex data, protein-protein interaction data and mRNA expression data, may help to uncover their relationships and common biological information underlying these data. The strategies described here may help to integrate and analyze other functional genomic and proteomic data, such as gene expression profiling, protein-localization mapping and large-scale phenotypic data, both in yeast and in other organisms.

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

    OpenAIRE

    G Jack Peterson; Steve Pressé; 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 t...

  9. Evolving new protein-protein interaction specificity through promiscuous intermediates.

    Science.gov (United States)

    Aakre, Christopher D; Herrou, Julien; Phung, Tuyen N; Perchuk, Barrett S; Crosson, Sean; Laub, Michael T

    2015-10-22

    Interacting proteins typically coevolve, and the identification of coevolving amino acids can pinpoint residues required for interaction specificity. This approach often assumes that an interface-disrupting mutation in one protein drives selection of a compensatory mutation in its partner during evolution. However, this model requires a non-functional intermediate state prior to the compensatory change. Alternatively, a mutation in one protein could first broaden its specificity, allowing changes in its partner, followed by a specificity-restricting mutation. Using bacterial toxin-antitoxin systems, we demonstrate the plausibility of this second, promiscuity-based model. By screening large libraries of interface mutants, we show that toxins and antitoxins with high specificity are frequently connected in sequence space to more promiscuous variants that can serve as intermediates during a reprogramming of interaction specificity. We propose that the abundance of promiscuous variants promotes the expansion and diversification of toxin-antitoxin systems and other paralogous protein families during evolution. PMID:26478181

  10. Alignment of non-covalent interactions at protein-protein interfaces.

    Directory of Open Access Journals (Sweden)

    Hongbo Zhu

    Full Text Available BACKGROUND: The study and comparison of protein-protein interfaces is essential for the understanding of the mechanisms of interaction between proteins. While there are many methods for comparing protein structures and protein binding sites, so far no methods have been reported for comparing the geometry of non-covalent interactions occurring at protein-protein interfaces. METHODOLOGY/PRINCIPAL FINDINGS: Here we present a method for aligning non-covalent interactions between different protein-protein interfaces. The method aligns the vector representations of van der Waals interactions and hydrogen bonds based on their geometry. The method has been applied to a dataset which comprises a variety of protein-protein interfaces. The alignments are consistent to a large extent with the results obtained using two other complementary approaches. In addition, we apply the method to three examples of protein mimicry. The method successfully aligns respective interfaces and allows for recognizing conserved interface regions. CONCLUSIONS/SIGNIFICANCE: The Galinter method has been validated in the comparison of interfaces in which homologous subunits are involved, including cases of mimicry. The method is also applicable to comparing interfaces involving non-peptidic compounds. Galinter assists users in identifying local interface regions with similar patterns of non-covalent interactions. This is particularly relevant to the investigation of the molecular basis of interaction mimicry.

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

    Science.gov (United States)

    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.

  12. Evaluation of clustering algorithms for protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    van Helden Jacques

    2006-11-01

    Full Text Available Abstract Background Protein interactions are crucial components of all cellular processes. Recently, high-throughput methods have been developed to obtain a global description of the interactome (the whole network of protein interactions for a given organism. In 2002, the yeast interactome was estimated to contain up to 80,000 potential interactions. This estimate is based on the integration of data sets obtained by various methods (mass spectrometry, two-hybrid methods, genetic studies. High-throughput methods are known, however, to yield a non-negligible rate of false positives, and to miss a fraction of existing interactions. The interactome can be represented as a graph where nodes correspond with proteins and edges with pairwise interactions. In recent years clustering methods have been developed and applied in order to extract relevant modules from such graphs. These algorithms require the specification of parameters that may drastically affect the results. In this paper we present a comparative assessment of four algorithms: Markov Clustering (MCL, Restricted Neighborhood Search Clustering (RNSC, Super Paramagnetic Clustering (SPC, and Molecular Complex Detection (MCODE. Results A test graph was built on the basis of 220 complexes annotated in the MIPS database. To evaluate the robustness to false positives and false negatives, we derived 41 altered graphs by randomly removing edges from or adding edges to the test graph in various proportions. Each clustering algorithm was applied to these graphs with various parameter settings, and the clusters were compared with the annotated complexes. We analyzed the sensitivity of the algorithms to the parameters and determined their optimal parameter values. We also evaluated their robustness to alterations of the test graph. We then applied the four algorithms to six graphs obtained from high-throughput experiments and compared the resulting clusters with the annotated complexes. Conclusion This

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

    Science.gov (United States)

    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. PMID:27117309

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

    Directory of Open Access Journals (Sweden)

    Jillian L Blatti

    Full Text Available 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.

  15. Quantifying protein-protein interactions in the ubiquitin pathway by surface plasmon resonance

    DEFF Research Database (Denmark)

    Hartmann-Petersen, Rasmus; Gordon, Colin

    2005-01-01

    The commercial availability of instruments, such as Biacore, that are capable of monitoring surface plasmon resonance (SPR) has greatly simplified the quantification of protein-protein interactions. Already, this technique has been used for some studies of the ubiquitin-proteasome system. Here we...

  16. The effect of protein-protein and protein-membrane interactions on membrane fouling in ultrafiltration

    NARCIS (Netherlands)

    Huisman, I.H.; Prádanos, P.; Hernández, A.

    2000-01-01

    It was studied how protein-protein and protein-membrane interactions influence the filtration performance during the ultrafiltration of protein solutions over polymeric membranes. This was done by measuring flux, streaming potential, and protein transmission during filtration of bovine serum albumin

  17. Versatile screening for binary protein-protein interactions by yeast two-hybrid mating

    NARCIS (Netherlands)

    Letteboer, S.J.F.; Roepman, R.

    2008-01-01

    Identification of binary protein-protein interactions is a crucial step in determining the molecular context and functional pathways of proteins. State-of-the-art proteomics techniques provide high-throughput information on the content of proteomes and protein complexes, but give little information

  18. Protein-protein interaction networks: unraveling the wiring of molecular machines within the cell.

    Science.gov (United States)

    De Las Rivas, Javier; Fontanillo, Celia

    2012-11-01

    Mapping and understanding of the protein interaction networks with their key modules and hubs can provide deeper insights into the molecular machinery underlying complex phenotypes. In this article, we present the basic characteristics and definitions of protein networks, starting with a distinction of the different types of associations between proteins. We focus the review on protein-protein interactions (PPIs), a subset of associations defined as physical contacts between proteins that occur by selective molecular docking in a particular biological context. We present such definition as opposed to other types of protein associations derived from regulatory, genetic, structural or functional relations. To determine PPIs, a variety of binary and co-complex methods exist; however, not all the technologies provide the same information and data quality. A way of increasing confidence in a given protein interaction is to integrate orthogonal experimental evidences. The use of several complementary methods testing each single interaction assesses the accuracy of PPI data and tries to minimize the occurrence of false interactions. Following this approach there have been important efforts to unify primary databases of experimentally proven PPIs into integrated databases. These meta-databases provide a measure of the confidence of interactions based on the number of experimental proofs that report them. As a conclusion, we can state that integrated information allows the building of more reliable interaction networks. Identification of communities, cliques, modules and hubs by analysing the topological parameters and graph properties of the protein networks allows the discovery of central/critical nodes, which are candidates to regulate cellular flux and dynamics. PMID:22908212

  19. Predicting multiplex subcellular localization of proteins using protein-protein interaction network: a comparative study

    OpenAIRE

    Jiang Jonathan Q; Wu Maoying

    2012-01-01

    Abstract Background Proteins that interact in vivo tend to reside within the same or "adjacent" subcellular compartments. This observation provides opportunities to reveal protein subcellular localization in the context of the protein-protein interaction (PPI) network. However, so far, only a few efforts based on heuristic rules have been made in this regard. Results We systematically and quantitatively validate the hypothesis that proteins physically interacting with each other probably shar...

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

    OpenAIRE

    Panstruga Ralph; Lahaye Thomas; Bhat Riyaz A

    2006-01-01

    Abstract 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...

  1. Alternative splicing tends to avoid partial removals of protein-protein interaction sites

    OpenAIRE

    Colantoni, Alessio; Bianchi, Valerio; Gherardini, Pier Federico; Scalia Tomba, Gianpaolo; Ausiello, Gabriele; Helmer-Citterich, Manuela; Ferrè, Fabrizio

    2013-01-01

    Background Anecdotal evidence of the involvement of alternative splicing (AS) in the regulation of protein-protein interactions has been reported by several studies. AS events have been shown to significantly occur in regions where a protein interaction domain or a short linear motif is present. Several AS variants show partial or complete loss of interface residues, suggesting that AS can play a major role in the interaction regulation by selectively targeting the protein binding sites. In t...

  2. Filtering high-throughput protein-protein interaction data using a combination of genomic features

    Directory of Open Access Journals (Sweden)

    Patil Ashwini

    2005-04-01

    Full Text Available Abstract Background Protein-protein interaction data used in the creation or prediction of molecular networks is usually obtained from large scale or high-throughput experiments. This experimental data is liable to contain a large number of spurious interactions. Hence, there is a need to validate the interactions and filter out the incorrect data before using them in prediction studies. Results In this study, we use a combination of 3 genomic features – structurally known interacting Pfam domains, Gene Ontology annotations and sequence homology – as a means to assign reliability to the protein-protein interactions in Saccharomyces cerevisiae determined by high-throughput experiments. Using Bayesian network approaches, we show that protein-protein interactions from high-throughput data supported by one or more genomic features have a higher likelihood ratio and hence are more likely to be real interactions. Our method has a high sensitivity (90% and good specificity (63%. We show that 56% of the interactions from high-throughput experiments in Saccharomyces cerevisiae have high reliability. We use the method to estimate the number of true interactions in the high-throughput protein-protein interaction data sets in Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens to be 27%, 18% and 68% respectively. Our results are available for searching and downloading at http://helix.protein.osaka-u.ac.jp/htp/. Conclusion A combination of genomic features that include sequence, structure and annotation information is a good predictor of true interactions in large and noisy high-throughput data sets. The method has a very high sensitivity and good specificity and can be used to assign a likelihood ratio, corresponding to the reliability, to each interaction.

  3. Globular and disordered-the non-identical twins in protein-protein interactions.

    Science.gov (United States)

    Teilum, Kaare; Olsen, Johan G; Kragelund, Birthe B

    2015-01-01

    In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs) and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol(-1). PMID:26217672

  4. Globular and disordered-the non-identical twins in protein-protein interactions

    DEFF Research Database (Denmark)

    Teilum, Kaare; Olsen, Johan Gotthardt; Kragelund, Birthe Brandt

    2015-01-01

    In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs) and other proteins rely on changes in flexibility and this is seen as a...... strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those...... of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol(-1)....

  5. Globular and disordered – the non-identical twins in protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Kaare eTeilum

    2015-07-01

    Full Text Available In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP’s bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol-1.

  6. TPPII, MYBBP1A and CDK2 form a protein-protein interaction network.

    Science.gov (United States)

    Nahálková, Jarmila; Tomkinson, Birgitta

    2014-12-15

    Tripeptidyl-peptidase II (TPPII) is an aminopeptidase with suggested regulatory effects on cell cycle, apoptosis and senescence. A protein-protein interaction study revealed that TPPII physically interacts with the tumor suppressor MYBBP1A and the cell cycle regulator protein CDK2. Mutual protein-protein interaction was detected between MYBBP1A and CDK2 as well. In situ Proximity Ligation Assay (PLA) using HEK293 cells overexpressing TPPII forming highly enzymatically active oligomeric complexes showed that the cytoplasmic interaction frequency of TPPII with MYBBP1A increased with the protein expression of TPPII and using serum-free cell growth conditions. A specific reversible inhibitor of TPPII, butabindide, suppressed the cytoplasmic interactions of TPPII and MYBBP1A both in control HEK293 and the cells overexpressing murine TPPII. The interaction of MYBBP1A with CDK2 was confirmed by in situ PLA in two different mammalian cell lines. Functional link between TPPII and MYBBP1A has been verified by gene expression study during anoikis, where overexpression of TPP II decreased mRNA expression level of MYBBP1A at the cell detachment conditions. All three interacting proteins TPPII, MYBBP1A and CDK2 have been previously implicated in the research for development of tumor-suppressing agents. This is the first report presenting mutual protein-protein interaction network of these proteins. PMID:25303791

  7. Investigating Protein-protein Interactions in Live Cells Using Bioluminescence Resonance Energy Transfer

    Science.gov (United States)

    Estruch, Sara B.; Fisher, Simon E.

    2014-01-01

    Assays based on Bioluminescence Resonance Energy Transfer (BRET) provide a sensitive and reliable means to monitor protein-protein interactions in live cells. BRET is the non-radiative transfer of energy from a 'donor' luciferase enzyme to an 'acceptor' fluorescent protein. In the most common configuration of this assay, the donor is Renilla reniformis luciferase and the acceptor is Yellow Fluorescent Protein (YFP). Because the efficiency of energy transfer is strongly distance-dependent, observation of the BRET phenomenon requires that the donor and acceptor be in close proximity. To test for an interaction between two proteins of interest in cultured mammalian cells, one protein is expressed as a fusion with luciferase and the second as a fusion with YFP. An interaction between the two proteins of interest may bring the donor and acceptor sufficiently close for energy transfer to occur. Compared to other techniques for investigating protein-protein interactions, the BRET assay is sensitive, requires little hands-on time and few reagents, and is able to detect interactions which are weak, transient, or dependent on the biochemical environment found within a live cell. It is therefore an ideal approach for confirming putative interactions suggested by yeast two-hybrid or mass spectrometry proteomics studies, and in addition it is well-suited for mapping interacting regions, assessing the effect of post-translational modifications on protein-protein interactions, and evaluating the impact of mutations identified in patient DNA. PMID:24893771

  8. Sequence-based prediction of protein-protein interaction sites with L1-logreg classifier.

    Science.gov (United States)

    Dhole, Kaustubh; Singh, Gurdeep; Pai, Priyadarshini P; Mondal, Sukanta

    2014-05-01

    Protein-protein interactions are of central importance for virtually every process in a living cell. Information about the interaction sites in proteins improves our understanding of disease mechanisms and can provide the basis for new therapeutic approaches. Since a multitude of unique residue-residue contacts facilitate the interactions, protein-protein interaction sites prediction has become one of the most important and challenging problems of computational biology. Although much progress in this field has been reported, this problem is yet to be satisfactorily solved. Here, a novel method (LORIS: L1-regularized LOgistic Regression based protein-protein Interaction Sites predictor) is proposed, that identifies interaction residues, using sequence features and is implemented via the L1-logreg classifier. Results show that LORIS is not only quite effective, but also, performs better than existing state-of-the art methods. LORIS, available as standalone package, can be useful for facilitating drug-design and targeted mutation related studies, which require a deeper knowledge of protein interactions sites. PMID:24486250

  9. Globular and disordered-the non-identical twins in protein-protein interactions

    OpenAIRE

    Teilum, Kaare; Olsen, Johan G.; Kragelund, Birthe B.

    2015-01-01

    In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs) and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein...

  10. Protein-Protein Interactions Prediction Based on Iterative Clique Extension with Gene Ontology Filtering

    OpenAIRE

    Lei Yang; Xianglong Tang

    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 m...

  11. PIMA: Protein-Protein interactions in Macromolecular Assembly - a web server for its Analysis and Visualization

    OpenAIRE

    Kaleeckal Mathew, Oommen; Sowdhamini, Ramanathan

    2016-01-01

    Protein-protein interactions are essential for the basic biological machinery of the cell. This is important for processes like protein synthesis, enzyme kinetics, molecular assembly and signal transduction. A high number of macromolecular structural complexes are known due to recent advances in structure determination techniques. Therefore, it is of interest to develop an interactive tool to objectively analyze large protein complexes. Hence, we describe the development and utility of a web ...

  12. Topology analysis and visualization of Potyvirus protein-protein interaction network

    OpenAIRE

    Bosque, Gabriel; Folch-Fortuny, Abel; Picó, Jesús; Ferrer, Alberto; Santiago, F Elena

    2014-01-01

    Background One of the central interests of Virology is the identification of host factors that contribute to virus infection. Despite tremendous efforts, the list of factors identified remains limited. With omics techniques, the focus has changed from identifying and thoroughly characterizing individual host factors to the simultaneous analysis of thousands of interactions, framing them on the context of protein-protein interaction networks and of transcriptional regulatory networks. This new...

  13. 3D-interologs: an evolution database of physical protein- protein interactions across multiple genomes

    OpenAIRE

    Chen Yung-Chiang; Lo Yu-Shu; Yang Jinn-Moon

    2010-01-01

    Abstract Background Comprehensive exploration of protein-protein interactions is a challenging route to understand biological processes. For efficiently enlarging protein interactions annotated with residue-based binding models, we proposed a new concept "3D-domain interolog mapping" with a scoring system to explore all possible protein pairs between the two homolog families, derived from a known 3D-structure dimmer (template), across multiple species. Each family consists of homologous prote...

  14. Discover Protein Complexes in Protein-Protein Interaction Networks Using Parametric Local Modularity

    OpenAIRE

    Tan Kai; Kim Jongkwang

    2010-01-01

    Abstract Background Recent advances in proteomic technologies have enabled us to create detailed protein-protein interaction maps in multiple species and in both normal and diseased cells. As the size of the interaction dataset increases, powerful computational methods are required in order to effectively distil network models from large-scale interactome data. Results We present an algorithm, miPALM (Module Inference by Parametric Local Modularity), to infer protein complexes in a protein-pr...

  15. Discovering Distinct Functional Modules of Specific Cancer Types Using Protein-Protein Interaction Networks

    OpenAIRE

    Ru Shen; Xiaosheng Wang; Chittibabu Guda

    2015-01-01

    Background. The molecular profiles exhibited in different cancer types are very different; hence, discovering distinct functional modules associated with specific cancer types is very important to understand the distinct functions associated with them. Protein-protein interaction networks carry vital information about molecular interactions in cellular systems, and identification of functional modules (subgraphs) in these networks is one of the most important applications of biological networ...

  16. Probabilistic methods for predicting protein functions in protein-protein interaction networks

    OpenAIRE

    Best, Christoph; Zimmer, Ralf; Apostolakis, Joannis

    2005-01-01

    We discuss probabilistic methods for predicting protein functions from protein-protein interaction networks. Previous work based on Markov Randon Fields is extended and compared to a general machine-learning theoretic approach. Using actual protein interaction networks for yeast from the MIPS database and GO-SLIM function assignments, we compare the predictions of the different probabilistic methods and of a standard support vector machine. It turns out that, with the currently available netw...

  17. A gateway-based system for fast evaluation of protein-protein interactions in bacteria.

    Directory of Open Access Journals (Sweden)

    Thorsten Wille

    Full Text Available Protein-protein interactions are important layers of regulation in all kingdoms of life. Identification and characterization of these interactions is one challenging task of the post-genomic era and crucial for understanding of molecular processes within a cell. Several methods have been successfully employed during the past decades to identify protein-protein interactions in bacteria, but most of them include tedious and time-consuming manipulations of DNA. In contrast, the MultiSite Gateway system is a fast tool for transfer of multiple DNA fragments between plasmids enabling simultaneous and site directed cloning of up to four fragments into one construct. Here we developed a new set of Gateway vectors including custom made entry vectors and modular Destination vectors for studying protein-protein interactions via Fluorescence Resonance Energy Transfer (FRET, Bacterial two Hybrid (B2H and split Gaussia luciferase (Gluc, as well as for fusions with SNAP-tag and HaloTag for dual-color super-resolution microscopy. As proof of principle, we characterized the interaction between the Salmonella effector SipA and its chaperone InvB via split Gluc and B2H approach. The suitability for FRET analysis as well as functionality of fusions with SNAP- and HaloTag could be demonstrated by studying the transient interaction between chemotaxis response regulator CheY and its phosphatase CheZ.

  18. Identification of hot-spot residues in protein-protein interactions by computational docking

    Directory of Open Access Journals (Sweden)

    Fernández-Recio Juan

    2008-10-01

    Full Text Available Abstract Background The study of protein-protein interactions is becoming increasingly important for biotechnological and therapeutic reasons. We can define two major areas therein: the structural prediction of protein-protein binding mode, and the identification of the relevant residues for the interaction (so called 'hot-spots'. These hot-spot residues have high interest since they are considered one of the possible ways of disrupting a protein-protein interaction. Unfortunately, large-scale experimental measurement of residue contribution to the binding energy, based on alanine-scanning experiments, is costly and thus data is fairly limited. Recent computational approaches for hot-spot prediction have been reported, but they usually require the structure of the complex. Results We have applied here normalized interface propensity (NIP values derived from rigid-body docking with electrostatics and desolvation scoring for the prediction of interaction hot-spots. This parameter identifies hot-spot residues on interacting proteins with predictive rates that are comparable to other existing methods (up to 80% positive predictive value, and the advantage of not requiring any prior structural knowledge of the complex. Conclusion The NIP values derived from rigid-body docking can reliably identify a number of hot-spot residues whose contribution to the interaction arises from electrostatics and desolvation effects. Our method can propose residues to guide experiments in complexes of biological or therapeutic interest, even in cases with no available 3D structure of the complex.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  20. CPL:Detecting Protein Complexes by Propagating Labels on Protein-Protein Interaction Network

    Institute of Scientific and Technical Information of China (English)

    代启国; 郭茂祖; 刘晓燕; 滕志霞; 王春宇

    2014-01-01

    Proteins usually bind together to form complexes, which play an important role in cellular activities. Many graph clustering methods have been proposed to identify protein complexes by finding dense regions in protein-protein interaction networks. We present a novel framework (CPL) that detects protein complexes by propagating labels through interactions in a network, in which labels denote complex identifiers. With proper propagation in CPL, proteins in the same complex will be assigned with the same labels. CPL does not make any strong assumptions about the topological structures of the complexes, as in previous methods. The CPL algorithm is tested on several publicly available yeast protein-protein interaction networks and compared with several state-of-the-art methods. The results suggest that CPL performs better than the existing methods. An analysis of the functional homogeneity based on a gene ontology analysis shows that the detected complexes of CPL are highly biologically relevant.

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

    Science.gov (United States)

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

    2015-01-01

    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

  2. The Intrinsic Geometric Structure of Protein-Protein Interaction Networks for Protein Interaction Prediction.

    Science.gov (United States)

    Fang, Yi; Sun, Mengtian; Dai, Guoxian; Ramain, Karthik

    2016-01-01

    Recent developments in high-throughput technologies for measuring protein-protein interaction (PPI) have profoundly advanced our ability to systematically infer protein function and regulation. However, inherently high false positive and false negative rates in measurement have posed great challenges in computational approaches for the prediction of PPI. A good PPI predictor should be 1) resistant to high rate of missing and spurious PPIs, and 2) robust against incompleteness of observed PPI networks. To predict PPI in a network, we developed an intrinsic geometry structure (IGS) for network, which exploits the intrinsic and hidden relationship among proteins in network through a heat diffusion process. In this process, all explicit PPIs participate simultaneously to glue local infinitesimal and noisy experimental interaction data to generate a global macroscopic descriptions about relationships among proteins. The revealed implicit relationship can be interpreted as the probability of two proteins interacting with each other. The revealed relationship is intrinsic and robust against individual, local and explicit protein interactions in the original network. We apply our approach to publicly available PPI network data for the evaluation of the performance of PPI prediction. Experimental results indicate that, under different levels of the missing and spurious PPIs, IGS is able to robustly exploit the intrinsic and hidden relationship for PPI prediction with a higher sensitivity and specificity compared to that of recently proposed methods. PMID:26886733

  3. Topological Properties of Protein-Protein and Metabolic Interaction Networks of Drosophila melanogaster

    Institute of Scientific and Technical Information of China (English)

    Thanigaimani Rajarathinam; Yen-Han Lin

    2006-01-01

    The underlying principle governing the natural phenomena of life is one of the critical issues receiving due importance in recent years. A key feature of the scale-free architecture is the vitality of the most connected nodes (hubs). The major objective of this article was to analyze the protein-protein and metabolic interaction networks of Drosophila melanogaster by considering the architectural patterns and the consequence of removal of hubs on the topological parameter of the two interaction systems. Analysis showed that both interaction networks follow a scale-free model, establishing the fact that most real world networks,from varied situations, conform to the small world pattern. The average path length showed a two-fold and a three-fold increase (changing from 9.42 to 20.93 and from 5.29 to 17.75, respectively) for the protein-protein and metabolic interaction networks, respectively, due to the deletion of hubs. On the contrary, the arbitrary elimination of nodes did not show any remarkable disparity in the topological parameter of the protein-protein and metabolic interaction networks (average path length: 9.42±0.02 and 5.27±0.01, respectively). This aberrant behavior for the two cases underscores the significance of the most linked nodes to the natural topology of the networks.

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

    Directory of Open Access Journals (Sweden)

    Jaume Torres

    2015-06-01

    Full Text Available 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.

  5. Discover Protein Complexes in Protein-Protein Interaction Networks Using Parametric Local Modularity

    Directory of Open Access Journals (Sweden)

    Tan Kai

    2010-10-01

    Full Text Available Abstract Background Recent advances in proteomic technologies have enabled us to create detailed protein-protein interaction maps in multiple species and in both normal and diseased cells. As the size of the interaction dataset increases, powerful computational methods are required in order to effectively distil network models from large-scale interactome data. Results We present an algorithm, miPALM (Module Inference by Parametric Local Modularity, to infer protein complexes in a protein-protein interaction network. The algorithm uses a novel graph theoretic measure, parametric local modularity, to identify highly connected sub-networks as candidate protein complexes. Using gold standard sets of protein complexes and protein function and localization annotations, we show our algorithm achieved an overall improvement over previous algorithms in terms of precision, recall, and biological relevance of the predicted complexes. We applied our algorithm to predict and characterize a set of 138 novel protein complexes in S. cerevisiae. Conclusions miPALM is a novel algorithm for detecting protein complexes from large protein-protein interaction networks with improved accuracy than previous methods. The software is implemented in Matlab and is freely available at http://www.medicine.uiowa.edu/Labs/tan/software.html.

  6. Structural interface parameters are discriminatory in recognising near-native poses of protein-protein interactions.

    Directory of Open Access Journals (Sweden)

    Sony Malhotra

    Full Text Available Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets.

  7. Constructing a robust protein-protein interaction network by integrating multiple public databases

    OpenAIRE

    Ding Don; Tong Weida; Fang Hong; Ye Yanbin; Su Zhenqiang; Guo Li; Liu Zhichao; Martha Venkata-Swamy; Xu Xiaowei

    2011-01-01

    Abstract Background Protein-protein interactions (PPIs) are a critical component for many underlying biological processes. A PPI network can provide insight into the mechanisms of these processes, as well as the relationships among different proteins and toxicants that are potentially involved in the processes. There are many PPI databases publicly available, each with a specific focus. The challenge is how to effectively combine their contents to generate a robust and biologically relevant P...

  8. Inferring the Brassica rapa interactome using protein-protein interaction data from Arabidopsis thaliana

    OpenAIRE

    Jianhua eYang; Kim eOsman; Mudassar eIqbal; Stekel, Dov J; Zewei eLuo; Armstrong, Susan J; Franklin, F. Chris H.

    2013-01-01

    Following successful completion of the Brassica rapa sequencing project, the next step is to investigate functions of individual genes/proteins. For Arabidopsis thaliana, large amounts of protein-protein interaction (PPI) data are available from the major PPI databases. It is known that Brassica crop species are closely related to A. thaliana. This provides an opportunity to infer the B. rapa interactome using PPI data available from A. thaliana. In this paper, we present an inferred B. rapa ...

  9. Bias tradeoffs in the creation and analysis of protein-protein interaction networks

    OpenAIRE

    Gillis, Jesse; Ballouz, Sara; Pavlidis, Paul

    2014-01-01

    Networks constructed from aggregated protein-protein interaction data are commonplace in biology. But the studies these data are derived from were conducted with their own hypotheses and foci. Focusing on data from budding yeast present in BioGRID, we determine that many of the downstream signals present in network data are significantly impacted by biases in the original data. We determine the degree to which selection bias in favor of biologically interesting bait proteins goes down with st...

  10. Exploring virus relationships based on virus-host protein-protein interaction network

    OpenAIRE

    Xu Feng; Zhao Chen; Li Yuhua; Li Jiang; Deng Youping; Shi Tieliu

    2011-01-01

    Abstract Background Currently, several systems have been proposed to classify viruses and indicate the relationships between different ones, though each system has its limitations because of the complexity of viral origins and their rapid evolution rate. We hereby propose a new method to explore the relationships between different viruses. Method A new method, which is based on the virus-host protein-protein interaction network, is proposed in this paper to categorize viruses. The distances b...

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

    OpenAIRE

    Claudio Peri; Giulia Morra; Giorgio Colombo

    2016-01-01

    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 identifi...

  12. Functional organization and its implication in evolution of the human protein-protein interaction network

    OpenAIRE

    Zhao Yiqiang; Mooney Sean D

    2012-01-01

    Abstract Background Based on the distinguishing properties of protein-protein interaction networks such as power-law degree distribution and modularity structure, several stochastic models for the evolution of these networks have been purposed, motivated by the idea that a validated model should reproduce similar topological properties of the empirical network. However, being able to capture topological properties does not necessarily mean it correctly reproduces how networks emerge and evolv...

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

    OpenAIRE

    Jillian L Blatti; Joris Beld; Behnke, Craig A; Michael Mendez; 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...

  14. An Algorithm for Finding Functional Modules and Protein Complexes in Protein-Protein Interaction Networks

    OpenAIRE

    Guangyu Cui; Yu Chen; De-Shuang Huang; Kyungsook Han

    2008-01-01

    Biological processes are often performed by a group of proteins rather than by individual proteins, and proteins in a same biological group form a densely connected subgraph in a protein-protein interaction network. Therefore, finding a densely connected subgraph provides useful information to predict the function or protein complex of uncharacterized proteins in the highly connected subgraph. We have developed an efficient algorithm and program for finding cliques and near-cliques in a prote...

  15. HKC: An Algorithm to Predict Protein Complexes in Protein-Protein Interaction Networks

    OpenAIRE

    Xiaomin Wang; Zhengzhi Wang; Jun Ye

    2011-01-01

    With the availability of more and more genome-scale protein-protein interaction (PPI) networks, research interests gradually shift to Systematic Analysis on these large data sets. A key topic is to predict protein complexes in PPI networks by identifying clusters that are densely connected within themselves but sparsely connected with the rest of the network. In this paper, we present a new topology-based algorithm, HKC, to detect protein complexes in genome-scale PPI networks. HKC mainly use...

  16. Improving accuracy of protein-protein interaction prediction by considering the converse problem for sequence representation

    Directory of Open Access Journals (Sweden)

    Wang Yong

    2011-10-01

    Full Text Available Abstract Background With the development of genome-sequencing technologies, protein sequences are readily obtained by translating the measured mRNAs. Therefore predicting protein-protein interactions from the sequences is of great demand. The reason lies in the fact that identifying protein-protein interactions is becoming a bottleneck for eventually understanding the functions of proteins, especially for those organisms barely characterized. Although a few methods have been proposed, the converse problem, if the features used extract sufficient and unbiased information from protein sequences, is almost untouched. Results In this study, we interrogate this problem theoretically by an optimization scheme. Motivated by the theoretical investigation, we find novel encoding methods for both protein sequences and protein pairs. Our new methods exploit sufficiently the information of protein sequences and reduce artificial bias and computational cost. Thus, it significantly outperforms the available methods regarding sensitivity, specificity, precision, and recall with cross-validation evaluation and reaches ~80% and ~90% accuracy in Escherichia coli and Saccharomyces cerevisiae respectively. Our findings here hold important implication for other sequence-based prediction tasks because representation of biological sequence is always the first step in computational biology. Conclusions By considering the converse problem, we propose new representation methods for both protein sequences and protein pairs. The results show that our method significantly improves the accuracy of protein-protein interaction predictions.

  17. Utilizing shared interacting domain patterns and Gene Ontology information to improve protein-protein interaction prediction.

    Science.gov (United States)

    Roslan, Rosfuzah; Othman, Razib M; Shah, Zuraini A; Kasim, Shahreen; Asmuni, Hishammuddin; Taliba, Jumail; Hassan, Rohayanti; Zakaria, Zalmiyah

    2010-06-01

    Protein-protein interactions (PPIs) play a significant role in many crucial cellular operations such as metabolism, signaling and regulations. The computational methods for predicting PPIs have shown tremendous growth in recent years, but problem such as huge false positive rates has contributed to the lack of solid PPI information. We aimed at enhancing the overlap between computational predictions and experimental results in an effort to partially remove PPIs falsely predicted. The use of protein function predictor named PFP() that are based on shared interacting domain patterns is introduced in this study with the purpose of aiding the Gene Ontology Annotations (GOA). We used GOA and PFP() as agents in a filtering process to reduce false positive pairs in the computationally predicted PPI datasets. The functions predicted by PFP() were extracted from cross-species PPI data in order to assign novel functional annotations for the uncharacterized proteins and also as additional functions for those that are already characterized by the GO (Gene Ontology). The implementation of PFP() managed to increase the chances of finding matching function annotation for the first rule in the filtration process as much as 20%. To assess the capability of the proposed framework in filtering false PPIs, we applied it on the available S. cerevisiae PPIs and measured the performance in two aspects, the improvement made indicated as Signal-to-Noise Ratio (SNR) and the strength of improvement, respectively. The proposed filtering framework significantly achieved better performance than without it in both metrics. PMID:20417930

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

    Directory of Open Access Journals (Sweden)

    Panstruga Ralph

    2006-06-01

    Full Text Available Abstract 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.

  19. Globular and disordered-the non-identical twins in protein-protein interactions

    DEFF Research Database (Denmark)

    Teilum, Kaare; Olsen, Johan G; Kragelund, Birthe B

    2015-01-01

    In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs) and other proteins rely on changes in flexibility and this is seen as a str...... of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol(-1)....

  20. Towards a better understanding of the specificity of protein-protein interaction

    Czech Academy of Sciences Publication Activity Database

    Kysilka, Jiří; Vondrášek, Jiří

    2012-01-01

    Roč. 25, č. 11 (2012), s. 604-615. ISSN 0952-3499 R&D Projects: GA ČR GAP208/10/0725; GA ČR GAP302/10/0427; GA MŠk(CZ) LH11020 Institutional research plan: CEZ:AV0Z40550506; CEZ:AV0Z50520701 Keywords : protein-protein interaction * molecular recognition * x-ray structure analysis * empirical potentials * side chain-side chain interaction * interaction energy * bioinformatics Subject RIV: CE - Biochemistry Impact factor: 3.006, year: 2012

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

    Science.gov (United States)

    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. PMID:27080133

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

    Science.gov (United States)

    Peri, Claudio; Morra, Giulia; Colombo, Giorgio

    2016-01-01

    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. PMID:27050828

  3. A Cascade Random Forests Algorithm for Predicting Protein-Protein Interaction Sites.

    Science.gov (United States)

    Wei, Zhi-Sen; Yang, Jing-Yu; Shen, Hong-Bin; Yu, Dong-Jun

    2015-10-01

    Protein-protein interactions exist ubiquitously and play important roles in the life cycles of living cells. The interaction sites (residues) are essential to understanding the underlying mechanisms of protein-protein interactions. Previous research has demonstrated that the accurate identification of protein-protein interaction sites (PPIs) is helpful for developing new therapeutic drugs because many drugs will interact directly with those residues. Because of its significant potential in biological research and drug development, the prediction of PPIs has become an important topic in computational biology. However, a severe data imbalance exists in the PPIs prediction problem, where the number of the majority class samples (non-interacting residues) is far larger than that of the minority class samples (interacting residues). Thus, we developed a novel cascade random forests algorithm (CRF) to address the serious data imbalance that exists in the PPIs prediction problem. The proposed CRF resolves the negative effect of data imbalance by connecting multiple random forests in a cascade-like manner, each of which is trained with a balanced training subset that includes all minority samples and a subset of majority samples using an effective ensemble protocol. Based on the proposed CRF, we implemented a new sequence-based PPIs predictor, called CRF-PPI, which takes the combined features of position-specific scoring matrices, averaged cumulative hydropathy, and predicted relative solvent accessibility as model inputs. Benchmark experiments on both the cross validation and independent validation datasets demonstrated that the proposed CRF-PPI outperformed the state-of-the-art sequence-based PPIs predictors. The source code for CRF-PPI and the benchmark datasets are available online at http://csbio.njust.edu.cn/bioinf/CRF-PPI for free academic use. PMID:26441427

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

    KAUST Repository

    Li, Chuanxi

    2014-01-01

    Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identifi cation of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifi es and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At fi rst, IRO is applied in a binary classifi er 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 signifi cant performance of IRO on relation sentences classifi cation 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. Copyright © 2014 Inderscience Enterprises Ltd.

  5. Reconstruction of the yeast protein-protein interaction network involved in nutrient sensing and global metabolic regulation

    OpenAIRE

    Nielsen Jens; Jouhten Paula; Nandy Subir K

    2010-01-01

    Abstract Background Several protein-protein interaction studies have been performed for the yeast Saccharomyces cerevisiae using different high-throughput experimental techniques. All these results are collected in the BioGRID database and the SGD database provide detailed annotation of the different proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives. Results Here we des...

  6. Studies of Dynamic Protein-Protein Interactions in Bacteria Using Renilla Luciferase Complementation Are Undermined by Nonspecific Enzyme Inhibition

    OpenAIRE

    Hatzios, Stavroula-Artemis K.; Ringgaard, Simon; Davis, Brigid; Waldor, Matthew K.

    2012-01-01

    The luciferase protein fragment complementation assay is a powerful tool for studying protein-protein interactions. Two inactive fragments of luciferase are genetically fused to interacting proteins, and when these two proteins interact, the luciferase fragments can reversibly associate and reconstitute enzyme activity. Though this technology has been used extensively in live eukaryotic cells, split luciferase complementation has not yet been applied to studies of dynamic protein-protein inte...

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

    International Nuclear Information System (INIS)

    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

  8. Novel Technology for Protein-Protein Interaction-based Targeted Drug Discovery

    Directory of Open Access Journals (Sweden)

    Jung Me Hwang

    2011-12-01

    Full Text Available We have developed a simple but highly efficient in-cell protein-protein interaction (PPI discovery system based on the translocation properties of protein kinase C- and its C1a domain in live cells. This system allows the visual detection of trimeric and dimeric protein interactions including cytosolic, nuclear, and/or membrane proteins with their cognate ligands. In addition, this system can be used to identify pharmacological small compounds that inhibit specific PPIs. These properties make this PPI system an attractive tool for screening drug candidates and mapping the protein interactome.

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    -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...

  10. 3DProIN: Protein-Protein Interaction Networks and Structure Visualization

    OpenAIRE

    Hui LI; Liu, Chunmei

    2014-01-01

    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 interne...

  11. Reconstruction of the yeast protein-protein interaction network involved in nutrient sensing and global metabolic regulation

    DEFF Research Database (Denmark)

    Nandy, Subir Kumar; Jouhten, Paula; Nielsen, Jens

    2010-01-01

    BACKGROUND: Several protein-protein interaction studies have been performed for the yeast Saccharomyces cerevisiae using different high-throughput experimental techniques. All these results are collected in the BioGRID database and the SGD database provide detailed annotation of the different...... proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives. RESULTS: Here we describe an annotated reconstruction of the protein-protein interactions around four key nutrient-sensing and...... metabolic regulatory signal transduction pathways (STP) operating in Saccharomyces cerevisiae. The reconstructed STP network includes a full protein-protein interaction network including the key nodes Snf1, Tor1, Hog1 and Pka1. The network includes a total of 623 structural open reading frames (ORFs) and...

  12. Recovering protein-protein and domain-domain interactions from aggregation of IP-MS proteomics of coregulator complexes.

    Directory of Open Access Journals (Sweden)

    Amin R Mazloom

    2011-12-01

    Full Text Available Coregulator proteins (CoRegs are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP followed by mass spectrometry (MS applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/.

  13. Protein-Protein Interactions in the Regulation of WRKY Transcription Factors

    Institute of Scientific and Technical Information of China (English)

    Yingjun Chi; Yan Yang; Yuan Zhou; Jie Zhou; Baofang Fan; Jing-Quan Yu; Zhixiang Chen

    2013-01-01

    It has been almost 20 years since the first report of a WRKY transcription factor,SPF1,from sweet potato.Great progress has been made since then in establishing the diverse biological roles of WRKY transcription factors in plant growth,development,and responses to biotic and abiotic stress.Despite the functional diversity,almost all analyzed WRKY proteins recognize the TrGACC/T W-box sequences and,therefore,mechanisms other than mere recognition of the core W-box promoter elements are necessary to achieve the regulatory specificity of WRKY transcription factors.Research over the past several years has revealed that WRKY transcription factors physically interact with a wide range of proteins with roles in signaling,transcription,and chromatin remodeling.Studies of WRKY-interacting proteins have provided important insights into the regulation and mode of action of members of the important family of transcription factors.It has also emerged that the slightly varied WRKY domains and other protein motifs conserved within each of the seven WRKY subfamilies participate in protein-protein interactions and mediate complex functional interactions between WRKY proteins and between WRKY and other regulatory proteins in the modulation of important biological processes.In this review,we summarize studies of protein-protein interactions for WRKY transcription factors and discuss how the interacting partners contribute,at different levels,to the establishment of the complex regulatory and functional network of WRKY transcription factors.

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

    Science.gov (United States)

    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. PMID:27121963

  15. Integrated cellular network of transcription regulations and protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Chen Bor-Sen

    2010-03-01

    Full Text Available Abstract Background With the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway. Results In this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated. Conclusions We successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology.

  16. Pharmacological manipulation of transcription factor protein-protein interactions: opportunities and obstacles.

    Science.gov (United States)

    Fontaine, Frank; Overman, Jeroen; François, Mathias

    2015-01-01

    Much research on transcription factor biology and their genetic pathways has been undertaken over the last 30 years, especially in the field of developmental biology and cancer. Yet, very little is known about the molecular modalities of highly dynamic interactions between transcription factors, genomic DNA, and protein partners. Methodological breakthroughs such as RNA-seq (RNA-sequencing), ChIP-seq (chromatin immunoprecipitation sequencing), RIME (rapid immunoprecipitation mass spectrometry of endogenous proteins), and single-molecule imaging will dramatically accelerate the discovery rate of their molecular mode of action in the next few years. From a pharmacological viewpoint, conventional methods used to target transcription factor activity with molecules mimicking endogenous ligands fail to achieve high specificity and are limited by a lack of identification of new molecular targets. Protein-protein interactions are likely to represent one of the next major classes of therapeutic targets. Transcription factors, known to act mostly via protein-protein interaction, may well be at the forefront of this type of drug development. One hurdle in this field remains the difficulty to collate structural data into meaningful information for rational drug design. Another hurdle is the lack of chemical libraries meeting the structural requirements of protein-protein interaction disruption. As more attempts at modulating transcription factor activity are undertaken, valuable knowledge will be accumulated on the modality of action required to modulate transcription and how these findings can be applied to developing transcription factor drugs. Key discoveries will spawn into new therapeutic approaches not only as anticancer targets but also for other indications, such as those with an inflammatory component including neurodegenerative disorders, diabetes, and chronic liver and kidney diseases. PMID:25848531

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

    Science.gov (United States)

    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. PMID:27408918

  18. Critical assessment of sequence-based protein-protein interaction prediction methods that do not require homologous protein sequences

    OpenAIRE

    Park Yungki

    2009-01-01

    Abstract Background Protein-protein interactions underlie many important biological processes. Computational prediction methods can nicely complement experimental approaches for identifying protein-protein interactions. Recently, a unique category of sequence-based prediction methods has been put forward - unique in the sense that it does not require homologous protein sequences. This enables it to be universally applicable to all protein sequences unlike many of previous sequence-based predi...

  19. Ensemble learning prediction of protein-protein interactions using proteins functional annotations.

    Science.gov (United States)

    Saha, Indrajit; Zubek, Julian; Klingström, Tomas; Forsberg, Simon; Wikander, Johan; Kierczak, Marcin; Maulik, Ujjwal; Plewczynski, Dariusz

    2014-04-01

    Protein-protein interactions are important for the majority of biological processes. A significant number of computational methods have been developed to predict protein-protein interactions using protein sequence, structural and genomic data. Vast experimental data is publicly available on the Internet, but it is scattered across numerous databases. This fact motivated us to create and evaluate new high-throughput datasets of interacting proteins. We extracted interaction data from DIP, MINT, BioGRID and IntAct databases. Then we constructed descriptive features for machine learning purposes based on data from Gene Ontology and DOMINE. Thereafter, four well-established machine learning methods: Support Vector Machine, Random Forest, Decision Tree and Naïve Bayes, were used on these datasets to build an Ensemble Learning method based on majority voting. In cross-validation experiment, sensitivity exceeded 80% and classification/prediction accuracy reached 90% for the Ensemble Learning method. We extended the experiment to a bigger and more realistic dataset maintaining sensitivity over 70%. These results confirmed that our datasets are suitable for performing PPI prediction and Ensemble Learning method is well suited for this task. Both the processed PPI datasets and the software are available at . PMID:24469380

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

    Energy Technology Data Exchange (ETDEWEB)

    Chowdhury, Saiful M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Shi, Liang [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Yoon, Hyunjin [Dartmouth College, Hanover, NH (United States); Ansong, Charles [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Rommereim, Leah M. [Dartmouth College, Hanover, NH (United States); Norbeck, Angela D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Auberry, Kenneth J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Moore, R. J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Adkins, Joshua N. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Heffron, Fred [Oregon Health and Science Univ., Portland, OR (United States); Smith, Richard D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    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. .

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

    Directory of Open Access Journals (Sweden)

    Nora López

    2012-09-01

    Full Text Available 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.

  2. Phthalic Acid Chemical Probes Synthesized for Protein-Protein Interaction Analysis

    Directory of Open Access Journals (Sweden)

    Chin-Jen Wu

    2013-06-01

    Full Text Available Plasticizers are additives that are used to increase the flexibility of plastic during manufacturing. However, in injection molding processes, plasticizers cannot be generated with monomers because they can peel off from the plastics into the surrounding environment, water, or food, or become attached to skin. Among the various plasticizers that are used, 1,2-benzenedicarboxylic acid (phthalic acid is a typical precursor to generate phthalates. In addition, phthalic acid is a metabolite of diethylhexyl phthalate (DEHP. According to Gene_Ontology gene/protein database, phthalates can cause genital diseases, cardiotoxicity, hepatotoxicity, nephrotoxicity, etc. In this study, a silanized linker (3-aminopropyl triethoxyslane, APTES was deposited on silicon dioxides (SiO2 particles and phthalate chemical probes were manufactured from phthalic acid and APTES–SiO2. These probes could be used for detecting proteins that targeted phthalic acid and for protein-protein interactions. The phthalic acid chemical probes we produced were incubated with epithelioid cell lysates of normal rat kidney (NRK-52E cells to detect the interactions between phthalic acid and NRK-52E extracted proteins. These chemical probes interacted with a number of chaperones such as protein disulfide-isomerase A6, heat shock proteins, and Serpin H1. Ingenuity Pathways Analysis (IPA software showed that these chemical probes were a practical technique for protein-protein interaction analysis.

  3. Multi-level integrative analysis of Protein Protein Interaction networks: connecting completeness, depth and robustness.

    Science.gov (United States)

    Blayney, Jaine K; Zheng, Huiru; Wang, Haiying; Azuaje, Francisco

    2010-01-01

    A fully extended Protein Protein Interaction (PPI) network can consist of upwards of several thousand nodes and edges. To simplify analysis, smaller child samples are often used in substitution of the global network. In this study, the impact of different levels of sampling was evaluated on six PPI networks. Results from the case studies suggest that restricting analysis to the first network level, using metrics such as degree and BC, could lead to misrepresentative results, omitting potentially significant nodes. Fault-tolerance analysis also indicates that key nodes within the second network level, and above, contribute to the stability of the global network. PMID:20693609

  4. [Recent advances in the techniques of protein-protein interaction study].

    Science.gov (United States)

    Wang, Ming-Qiang; Wu, Jin-Xia; Zhang, Yu-Hong; Han, Ning; Bian, Hong-Wu; Zhu, Mu-Yuan

    2013-11-01

    Protein-protein interactions play key roles in the development of organisms and the response to biotic and abiotic stresses. Several wet-lab methods have been developed to study this challenging area,including yeast two-hybrid system, tandem affinity purification, Co-immunoprecipitation, GST Pull-down, bimolecular fluorescence complementation, fluorescence resonance energy transfer and surface plasmon resonance analysis. In this review, we discuss theoretical principles and relative advantages and disvantages of these techniques,with an emphasis on recent advances to compensate for limitations. PMID:24579310

  5. Protein-protein interaction map is a key gateway into liver regeneration

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Recent studies indicate that the process of liver regeneration involves multiple signaling pathways and a variety of genes,cytokines and growth factors. Protein-protein interactions(PPIs)play a role in nearly all events that take place within the cell and PPI maps should be helpful in further understanding the process of liver regeneration.In this review,we discuss recent progress in understanding the PPIs that occur during liver regeneration especially those in the transforming growth factorβsignaling path...

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

    OpenAIRE

    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 intera...

  7. PIPE: a protein-protein interaction passage extraction module for BioCreative challenge.

    Science.gov (United States)

    Chang, Yung-Chun; Chu, Chun-Han; Su, Yu-Chen; Chen, Chien Chin; Hsu, Wen-Lian

    2016-01-01

    Identifying the interactions between proteins mentioned in biomedical literatures is one of the frequently discussed topics of text mining in the life science field. In this article, we propose PIPE, an interaction pattern generation module used in the Collaborative Biocurator Assistant Task at BioCreative V (http://www.biocreative.org/) to capture frequent protein-protein interaction (PPI) patterns within text. We also present an interaction pattern tree (IPT) kernel method that integrates the PPI patterns with convolution tree kernel (CTK) to extract PPIs. Methods were evaluated on LLL, IEPA, HPRD50, AIMed and BioInfer corpora using cross-validation, cross-learning and cross-corpus evaluation. Empirical evaluations demonstrate that our method is effective and outperforms several well-known PPI extraction methods. DATABASE URL. PMID:27524807

  8. A protein-protein interaction map of the Trypanosoma brucei paraflagellar rod.

    Directory of Open Access Journals (Sweden)

    Sylvain Lacomble

    Full Text Available We have conducted a protein interaction study of components within a specific sub-compartment of a eukaryotic flagellum. The trypanosome flagellum contains a para-crystalline extra-axonemal structure termed the paraflagellar rod (PFR with around forty identified components. We have used a Gateway cloning approach coupled with yeast two-hybrid, RNAi and 2D DiGE to define a protein-protein interaction network taking place in this structure. We define two clusters of interactions; the first being characterised by two proteins with a shared domain which is not sufficient for maintaining the interaction. The other cohort is populated by eight proteins, a number of which possess a PFR domain and sub-populations of this network exhibit dependency relationships. Finally, we provide clues as to the structural organisation of the PFR at the molecular level. This multi-strand approach shows that protein interactome data can be generated for insoluble protein complexes.

  9. A novel functional module detection algorithm for protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Zhang Aidong

    2006-12-01

    Full Text Available Abstract Background The sparse connectivity of protein-protein interaction data sets makes identification of functional modules challenging. The purpose of this study is to critically evaluate a novel clustering technique for clustering and detecting functional modules in protein-protein interaction networks, termed STM. Results STM selects representative proteins for each cluster and iteratively refines clusters based on a combination of the signal transduced and graph topology. STM is found to be effective at detecting clusters with a diverse range of interaction structures that are significant on measures of biological relevance. The STM approach is compared to six competing approaches including the maximum clique, quasi-clique, minimum cut, betweeness cut and Markov Clustering (MCL algorithms. The clusters obtained by each technique are compared for enrichment of biological function. STM generates larger clusters and the clusters identified have p-values that are approximately 125-fold better than the other methods on biological function. An important strength of STM is that the percentage of proteins that are discarded to create clusters is much lower than the other approaches. Conclusion STM outperforms competing approaches and is capable of effectively detecting both densely and sparsely connected, biologically relevant functional modules with fewer discards.

  10. Widely predicting specific protein functions based on protein-protein interaction data and gene expression profile

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    GESTs (gene expression similarity and taxonomy similarity), a gene functional prediction approach previously proposed by us, is based on gene expression similarity and concept similarity of functional classes defined in Gene Ontology (GO). In this paper, we extend this method to protein-protein interac-tion data by introducing several methods to filter the neighbors in protein interaction networks for a protein of unknown function(s). Unlike other conventional methods, the proposed approach automati-cally selects the most appropriate functional classes as specific as possible during the learning proc-ess, and calls on genes annotated to nearby classes to support the predictions to some small-sized specific classes in GO. Based on the yeast protein-protein interaction information from MIPS and a dataset of gene expression profiles, we assess the performances of our approach for predicting protein functions to “biology process” by three measures particularly designed for functional classes organ-ized in GO. Results show that our method is powerful for widely predicting gene functions with very specific functional terms. Based on the GO database published in December 2004, we predict some proteins whose functions were unknown at that time, and some of the predictions have been confirmed by the new SGD annotation data published in April, 2006.

  11. Widely predicting specific protein functions based on protein-protein interaction data and gene expression profile

    Institute of Scientific and Technical Information of China (English)

    GAO Lei; LI Xia; GUO Zheng; ZHU MingZhu; LI YanHui; RAO ShaoQi

    2007-01-01

    GESTs (gene expression similarity and taxonomy similarity), a gene functional prediction approach previously proposed by us, is based on gene expression similarity and concept similarity of functional classes defined in Gene Ontology (GO). In this paper, we extend this method to protein-protein interaction data by introducing several methods to filter the neighbors in protein interaction networks for a protein of unknown function(s). Unlike other conventional methods, the proposed approach automatically selects the most appropriate functional classes as specific as possible during the learning process, and calls on genes annotated to nearby classes to support the predictions to some small-sized specific classes in GO. Based on the yeast protein-protein interaction information from MIPS and a dataset of gene expression profiles, we assess the performances of our approach for predicting protein functions to "biology process" by three measures particularly designed for functional classes organized in GO. Results show that our method is powerful for widely predicting gene functions with very specific functional terms. Based on the GO database published in December 2004, we predict some proteins whose functions were unknown at that time, and some of the predictions have been confirmed by the new SGD annotation data published in April, 2006.

  12. Prediction of protein-protein interactions between viruses and human by an SVM model

    Directory of Open Access Journals (Sweden)

    Cui Guangyu

    2012-05-01

    Full Text Available Abstract Background Several computational methods have been developed to predict protein-protein interactions from amino acid sequences, but most of those methods are intended for the interactions within a species rather than for interactions across different species. Methods for predicting interactions between homogeneous proteins are not appropriate for finding those between heterogeneous proteins since they do not distinguish the interactions between proteins of the same species from those of different species. Results We developed a new method for representing a protein sequence of variable length in a frequency vector of fixed length, which encodes the relative frequency of three consecutive amino acids of a sequence. We built a support vector machine (SVM model to predict human proteins that interact with virus proteins. In two types of viruses, human papillomaviruses (HPV and hepatitis C virus (HCV, our SVM model achieved an average accuracy above 80%, which is higher than that of another SVM model with a different representation scheme. Using the SVM model and Gene Ontology (GO annotations of proteins, we predicted new interactions between virus proteins and human proteins. Conclusions Encoding the relative frequency of amino acid triplets of a protein sequence is a simple yet powerful representation method for predicting protein-protein interactions across different species. The representation method has several advantages: (1 it enables a prediction model to achieve a better performance than other representations, (2 it generates feature vectors of fixed length regardless of the sequence length, and (3 the same representation is applicable to different types of proteins.

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

    Science.gov (United States)

    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

  14. Robustness of indispensable nodes in controlling protein-protein interaction network

    CERN Document Server

    Zhang, Xizhe; Yang, Yunyi

    2016-01-01

    Recently, the structural controllability theory has been introduced to analyze the Protein-Protein Interaction (PPI) network. The indispensable nodes, which their removal increase the number of driver nodes to control the network, are found essential in PPI network. However, the PPI network is far from complete and there may exist many false-positive or false-negative interactions, which promotes us to question: are these indispensable nodes robust to structural change? Here we systematically investigate the robustness of indispensable nodes of PPI network by removing and adding possible interactions. We found that the indispensable nodes are sensitive to the structural change and very few edges can change the type of many indispensable nodes. The finding may promote our understanding to the control principle of PPI network.

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

    Science.gov (United States)

    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. PMID:26846814

  16. Fluorescence lifetime imaging microscopy (FLIM) to quantify protein-protein interactions inside cells.

    Science.gov (United States)

    Duncan, R R

    2006-11-01

    Recent developments in cellular imaging spectroscopy now permit the minimally invasive study of protein dynamics inside living cells. These advances are of interest to cell biologists, as proteins rarely act in isolation, but rather in concert with others in forming cellular machinery. Until recently, all protein interactions had to be determined in vitro using biochemical approaches: this biochemical legacy has provided cell biologists with the basis to test defined protein-protein interactions not only inside cells, but now also with high spatial resolution. These techniques can detect and quantify protein behaviours down to the single-molecule level, all inside living cells. More recent developments in TCSPC (time-correlated single-photon counting) imaging are now also driving towards being able to determine protein interaction rates with similar spatial resolution, and together, these experimental advances allow investigators to perform biochemical experiments inside living cells. PMID:17052173

  17. Prediction and systematic study of protein-protein interaction networks of Leptospira interrogans

    Institute of Scientific and Technical Information of China (English)

    SUN Jingchun; XU Jinlin; CAO Jianping; LIU Qi; GUO Xiaokui; SHI Tieliu; LI Yixue

    2006-01-01

    Leptospira interrogans serovar Lai is a pathogenic bacterium that causes a spirochetal zoonosis in humans and some animals. With its complete genome sequence available, it is possible to analyze protein-protein interactions from a whole- genome standpoint. Here we combine four recently developed computational approaches (gene fusion method, gene neighbor method, phylogenetic profiles method, and operon method) to predict protein-pro- tein interaction networks of Leptospira interrogans strain Lai. Through comprehensive analysis on in- teractions among proteins of motility and chemotaxis system, signal transduction, lipopolysaccaride bio- synthesis and a series of proteins related to adhesion and invasion, we provided information for further studying on its pathogenic mechanism. In addition, we also assigned 203 previously uncharacterized proteins with possible functions based on the known functions of its interacting partners. This work is helpful for further investigating L. interrogans strain Lai.

  18. Targeted in vivo inhibition of specific protein-protein interactions using recombinant antibodies.

    Directory of Open Access Journals (Sweden)

    Matej Zábrady

    Full Text Available With the growing availability of genomic sequence information, there is an increasing need for gene function analysis. Antibody-mediated "silencing" represents an intriguing alternative for the precise inhibition of a particular function of biomolecules. Here, we describe a method for selecting recombinant antibodies with a specific purpose in mind, which is to inhibit intrinsic protein-protein interactions in the cytosol of plant cells. Experimental procedures were designed for conveniently evaluating desired properties of recombinant antibodies in consecutive steps. Our selection method was successfully used to develop a recombinant antibody inhibiting the interaction of ARABIDOPSIS HISTIDINE PHOSPHOTRANSFER PROTEIN 3 with such of its upstream interaction partners as the receiver domain of CYTOKININ INDEPENDENT HISTIDINE KINASE 1. The specific down-regulation of the cytokinin signaling pathway in vivo demonstrates the validity of our approach. This selection method can serve as a prototype for developing unique recombinant antibodies able to interfere with virtually any biomolecule in the living cell.

  19. Neutral evolution of Protein-protein interactions: a computational study using simple models

    Directory of Open Access Journals (Sweden)

    Simonson Thomas

    2007-11-01

    Full Text Available Abstract Background Protein-protein interactions are central to cellular organization, and must have appeared at an early stage of evolution. To understand better their role, we consider a simple model of protein evolution and determine the effect of an explicit selection for Protein-protein interactions. Results In the model, viable sequences all have the same fitness, following the neutral evolution theory. A very simple, two-dimensional lattice representation of the protein structures is used, and the model only considers two kinds of amino acids: hydrophobic and polar. With these approximations, exact calculations are performed. The results do not depend too strongly on these assumptions, since a model using a 3D, off-lattice representation of the proteins gives results in qualitative agreement with the 2D one. With both models, the evolutionary dynamics lead to a steady state population that is enriched in sequences that dimerize with a high affinity, well beyond the minimal level needed to survive. Correspondingly, sequences close to the viability threshold are less abundant in the steady state, being subject to a larger proportion of lethal mutations. The set of viable sequences has a "funnel" shape, consistent with earlier studies: sequences that are highly populated in the steady state are "close" to each other (with proximity being measured by the number of amino acids that differ. Conclusion This bias in the the steady state sequences should lead to an increased resistance of the population to environmental change and an increased ability to evolve.

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

    Directory of Open Access Journals (Sweden)

    Furuya Toshio

    2011-02-01

    Full Text Available Abstract 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.

  1. Protein-protein interaction antagonists as novel inhibitors of non-canonical polyubiquitylation.

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    Johanna Scheper

    Full Text Available BACKGROUND: Several pathways that control cell survival under stress, namely RNF8-dependent DNA damage recognition and repair, PCNA-dependent DNA damage tolerance and activation of NF-kappaB by extrinsic signals, are regulated by the tagging of key proteins with lysine 63-based polyubiquitylated chains, catalyzed by the conserved ubiquitin conjugating heterodimeric enzyme Ubc13-Uev. METHODOLOGY/PRINCIPAL FINDINGS: By applying a selection based on in vivo protein-protein interaction assays of compounds from a combinatorial chemical library followed by virtual screening, we have developed small molecules that efficiently antagonize the Ubc13-Uev1 protein-protein interaction, inhibiting the enzymatic activity of the heterodimer. In mammalian cells, they inhibit lysine 63-type polyubiquitylation of PCNA, inhibit activation of NF-kappaB by TNF-alpha and sensitize tumor cells to chemotherapeutic agents. One of these compounds significantly inhibited invasiveness, clonogenicity and tumor growth of prostate cancer cells. CONCLUSIONS/SIGNIFICANCE: This is the first development of pharmacological inhibitors of non-canonical polyubiquitylation that show that these compounds produce selective biological effects with potential therapeutic applications.

  2. DUF581 is plant specific FCS-like zinc finger involved in protein-protein interaction.

    Directory of Open Access Journals (Sweden)

    Muhammed Jamsheer K

    Full Text Available 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.

  3. Structure of the Q237W mutant of HhaI DNA methyltransferase: an insight into protein-protein interactions

    OpenAIRE

    Dong, Aiping; Zhou, Lan; Zhang, Xing; Stickel, Shawn; Roberts, Richard J.; Cheng, Xiaodong

    2004-01-01

    We have determined the structure of a mutant (Q237W) of HhaI DNA methyltransferase, complexed with the methyl-donor product AdoHcy. The Q237W mutant proteins were crystallized in the monoclinic space group C2 with two molecules in the crystallographic asymmetric unit. Protein-protein interface calculations in the crystal lattices suggest that the dimer interface has the specific characteristics for homodimer protein-protein interactions, while the two active sites are spatially...

  4. Proteomic dissection of biological pathways/processes through profiling protein-protein interaction networks

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Cellular functions, either under the normal or pathological conditions or under different stresses, are the results of the coordinated action of multiple proteins interacting in macromolecular complexes or assemblies. The precise determination of the specific composition of protein complexes, especially using scalable and high-throughput methods, represents a systematic approach toward revealing particular cellular biological functions. In this regard, the direct profiling protein-protein interactions (PPIs) represent an efficient way to dissect functional pathways for revealing novel protein functions. In this review, we illustrate the technological evolution for the large-scale and precise identification of PPIs toward higher physiologically relevant accuracy. These techniques aim at improving the efficiency of complex pull-down, the signal specificity and accuracy in distinguishing specific PPIs, and the accuracy of identifying physiological relevant PPIs. A newly developed streamline proteomic approach for mapping the binary relationship of PPIs in a protein complex is introduced.

  5. Blue-native PAGE in plants: a tool in analysis of protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Millar A Harvey

    2005-11-01

    Full Text Available Abstract Intact protein complexes can be separated by apparent molecular mass using a standard polyacrylamide gel electrophoresis system combining mild detergents and the dye Coomassie Blue. Referring to the blue coloured gel and the gentle method of solubilization yielding native and enzymatically active protein complexes, this technique has been named Blue-Native Polyacrylamide Gel-Electrophoresis (BN-PAGE. BN-PAGE has become the method of choice for the investigation of the respiratory protein complexes of the electron transfer chains of a range of organisms, including bacteria, yeasts, animals and plants. It allows the separation in two dimensions of extremely hydrophobic protein sets for analysis and also provides information on their native interactions. In this review we discuss the capabilities of BN-PAGE in proteomics and the wider investigation of protein:protein interactions with a focus on its use and potential in plant science.

  6. A Quantitative Approach to Analyzing Genome Reductive Evolution Using Protein-Protein Interaction Networks: A Case Study of Mycobacterium leprae.

    Science.gov (United States)

    Akinola, Richard O; Mazandu, Gaston K; Mulder, Nicola J

    2016-01-01

    The advance in high-throughput sequencing technologies has yielded complete genome sequences of several organisms, including complete bacterial genomes. The growing number of these available sequenced genomes has enabled analyses of their dynamics, as well as the molecular and evolutionary processes which these organisms are under. Comparative genomics of different bacterial genomes have highlighted their genome size and gene content in association with lifestyles and adaptation to various environments and have contributed to enhancing our understanding of the mechanisms of their evolution. Protein-protein functional interactions mediate many essential processes for maintaining the stability of the biological systems under changing environmental conditions. Thus, these interactions play crucial roles in the evolutionary processes of different organisms, especially for obligate intracellular bacteria, proven to generally have reduced genome sizes compared to their nearest free-living relatives. In this study, we used the approach based on the Renormalization Group (RG) analysis technique and the Maximum-Excluded-Mass-Burning (MEMB) model to investigate the evolutionary process of genome reduction in relation to the organization of functional networks of two organisms. Using a Mycobacterium leprae (MLP) network in comparison with a Mycobacterium tuberculosis (MTB) network as a case study, we show that reductive evolution in MLP was as a result of removal of important proteins from neighbors of corresponding orthologous MTB proteins. While each orthologous MTB protein had an increase in number of interacting partners in most instances, the corresponding MLP protein had lost some of them. This work provides a quantitative model for mapping reductive evolution and protein-protein functional interaction network organization in terms of roles played by different proteins in the network structure. PMID:27066064

  7. Reconstruction of the yeast protein-protein interaction network involved in nutrient sensing and global metabolic regulation

    Directory of Open Access Journals (Sweden)

    Nielsen Jens

    2010-05-01

    Full Text Available Abstract Background Several protein-protein interaction studies have been performed for the yeast Saccharomyces cerevisiae using different high-throughput experimental techniques. All these results are collected in the BioGRID database and the SGD database provide detailed annotation of the different proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives. Results Here we describe an annotated reconstruction of the protein-protein interactions around four key nutrient-sensing and metabolic regulatory signal transduction pathways (STP operating in Saccharomyces cerevisiae. The reconstructed STP network includes a full protein-protein interaction network including the key nodes Snf1, Tor1, Hog1 and Pka1. The network includes a total of 623 structural open reading frames (ORFs and 779 protein-protein interactions. A number of proteins were identified having interactions with more than one of the protein kinases. The fully reconstructed interaction network includes all the information available in separate databases for all the proteins included in the network (nodes and for all the interactions between them (edges. The annotated information is readily available utilizing the functionalities of network modelling tools such as Cytoscape and CellDesigner. Conclusions The reported fully annotated interaction model serves as a platform for integrated systems biology studies of nutrient sensing and regulation in S. cerevisiae. Furthermore, we propose this annotated reconstruction as a first step towards generation of an extensive annotated protein-protein interaction network of signal transduction and metabolic regulation in this yeast.

  8. Intragenic suppressor of Osiaa23 revealed a conserved tryptophan residue crucial for protein-protein interactions.

    Directory of Open Access Journals (Sweden)

    Jun Ni

    Full Text Available The Auxin/Indole-3-Acetic Acid (Aux/IAA and Auxin Response Factor (ARF are two important families that play key roles in auxin signal transduction. Both of the families contain a similar carboxyl-terminal domain (Domain III/IV that facilitates interactions between these two families. In spite of the importance of protein-protein interactions among these transcription factors, the mechanisms involved in these interactions are largely unknown. In this study, we isolated six intragenic suppressors of an auxin insensitive mutant, Osiaa23. Among these suppressors, Osiaa23-R5 successfully rescued all the defects of the mutant. Sequence analysis revealed that an amino acid substitution occurred in the Tryptophan (W residue in Domain IV of Osiaa23. Yeast two-hybrid experiments showed that the mutation in Domain IV prevents the protein-protein interactions between Osiaa23 and OsARFs. Phylogenetic analysis revealed that the W residue is conserved in both OsIAAs and OsARFs. Next, we performed site-specific amino acid substitutions within Domain IV of OsARFs, and the conserved W in Domain IV was exchanged by Serine (S. The mutated OsARF(WSs can be released from the inhibition of Osiaa23 and maintain the transcriptional activities. Expression of OsARF(WSs in Osiaa23 mutant rescued different defects of the mutant. Our results suggest a previously unknown importance of Domain IV in both families and provide an indirect way to investigate functions of OsARFs.

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

    Science.gov (United States)

    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. PMID:24578640

  10. PathPPI: an integrated dataset of human pathways and protein-protein interactions.

    Science.gov (United States)

    Tang, HaiLin; Zhong, Fan; Liu, Wei; He, FuChu; Xie, HongWei

    2015-06-01

    Integration of pathway and protein-protein interaction (PPI) data can provide more information that could lead to new biological insights. PPIs are usually represented by a simple binary model, whereas pathways are represented by more complicated models. We developed a series of rules for transforming protein interactions from pathway to binary model, and the protein interactions from seven pathway databases, including PID, BioCarta, Reactome, NetPath, INOH, SPIKE and KEGG, were transformed based on these rules. These pathway-derived binary protein interactions were integrated with PPIs from other five PPI databases including HPRD, IntAct, BioGRID, MINT and DIP, to develop integrated dataset (named PathPPI). More detailed interaction type and modification information on protein interactions can be preserved in PathPPI than other existing datasets. Comparison analysis results indicate that most of the interaction overlaps values (O AB) among these pathway databases were less than 5%, and these databases must be used conjunctively. The PathPPI data was provided at http://proteomeview.hupo.org.cn/PathPPI/PathPPI.html. PMID:25591449

  11. Protein-Protein Interactions Prediction Based on Iterative Clique Extension with Gene Ontology Filtering

    Directory of Open Access Journals (Sweden)

    Lei Yang

    2014-01-01

    Full Text Available 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.

  12. The role of exon shuffling in shaping protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    França Gustavo S

    2010-12-01

    Full Text Available Abstract Background Physical protein-protein interaction (PPI is a critical phenomenon for the function of most proteins in living organisms and a significant fraction of PPIs are the result of domain-domain interactions. Exon shuffling, intron-mediated recombination of exons from existing genes, is known to have been a major mechanism of domain shuffling in metazoans. Thus, we hypothesized that exon shuffling could have a significant influence in shaping the topology of PPI networks. Results We tested our hypothesis by compiling exon shuffling and PPI data from six eukaryotic species: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Cryptococcus neoformans and Arabidopsis thaliana. For all four metazoan species, genes enriched in exon shuffling events presented on average higher vertex degree (number of interacting partners in PPI networks. Furthermore, we verified that a set of protein domains that are simultaneously promiscuous (known to interact to multiple types of other domains, self-interacting (able to interact with another copy of themselves and abundant in the genomes presents a stronger signal for exon shuffling. Conclusions Exon shuffling appears to have been a recurrent mechanism for the emergence of new PPIs along metazoan evolution. In metazoan genomes, exon shuffling also promoted the expansion of some protein domains. We speculate that their promiscuous and self-interacting properties may have been decisive for that expansion.

  13. Development of a multiplexed microfluidic proteomic reactor and its application for studying protein-protein interactions.

    Science.gov (United States)

    Tian, Ruijun; Hoa, Xuyen Dai; Lambert, Jean-Philippe; Pezacki, John Paul; Veres, Teodor; Figeys, Daniel

    2011-06-01

    Mass spectrometry-based proteomics techniques have been very successful for the identification and study of protein-protein interactions. Typically, immunopurification of protein complexes is conducted, followed by protein separation by gel electrophoresis and in-gel protein digestion, and finally, mass spectrometry is performed to identify the interacting partners. However, the manual processing of the samples is time-consuming and error-prone. Here, we developed a polymer-based microfluidic proteomic reactor aimed at the parallel analysis of minute amounts of protein samples obtained from immunoprecipitation. The design of the proteomic reactor allows for the simultaneous processing of multiple samples on the same devices. Each proteomic reactor on the device consists of SCX beads packed and restricted into a 1 cm microchannel by two integrated pillar frits. The device is fabricated using a combination of low-cost hard cyclic olefin copolymer thermoplastic and elastomeric thermoplastic materials (styrene/(ethylene/butylenes)/styrene) using rapid hot-embossing replication techniques with a polymer-based stamp. Three immunopurified protein samples are simultaneously captured, reduced, alkylated, and digested on the device within 2-3 h instead of the days required for the conventional protein-protein interaction studies. The limit of detection of the microfluidic proteomic reactor was shown to be lower than 2 ng of protein. Furthermore, the application of the microfluidic proteomic reactor was demonstrated for the simultaneous processing of the interactome of the histone variant Htz1 in wild-type yeast and in a swr1Δ yeast strain compared to an untagged control using a novel three-channel microfluidic proteomic reactor. PMID:21520965

  14. Computational prediction of virus-human protein-protein interactions using embedding kernelized heterogeneous data.

    Science.gov (United States)

    Nourani, Esmaeil; Khunjush, Farshad; Durmuş, Saliha

    2016-05-24

    Pathogenic microorganisms exploit host cellular mechanisms and evade host defense mechanisms through molecular pathogen-host interactions (PHIs). Therefore, comprehensive analysis of these PHI networks should be an initial step for developing effective therapeutics against infectious diseases. Computational prediction of PHI data is gaining increasing demand because of scarcity of experimental data. Prediction of protein-protein interactions (PPIs) within PHI systems can be formulated as a classification problem, which requires the knowledge of non-interacting protein pairs. This is a restricting requirement since we lack datasets that report non-interacting protein pairs. In this study, we formulated the "computational prediction of PHI data" problem using kernel embedding of heterogeneous data. This eliminates the abovementioned requirement and enables us to predict new interactions without randomly labeling protein pairs as non-interacting. Domain-domain associations are used to filter the predicted results leading to 175 novel PHIs between 170 human proteins and 105 viral proteins. To compare our results with the state-of-the-art studies that use a binary classification formulation, we modified our settings to consider the same formulation. Detailed evaluations are conducted and our results provide more than 10 percent improvements for accuracy and AUC (area under the receiving operating curve) results in comparison with state-of-the-art methods. PMID:27072625

  15. Dynamic circadian protein-protein interaction networks predict temporal organization of cellular functions.

    Directory of Open Access Journals (Sweden)

    Thomas Wallach

    2013-03-01

    Full Text Available Essentially all biological processes depend on protein-protein interactions (PPIs. Timing of such interactions is crucial for regulatory function. Although circadian (~24-hour clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc. contributing to temporal organization of cellular physiology in an unprecedented manner.

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

    Science.gov (United States)

    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

  17. The centrality of cancer proteins in human protein-protein interaction network: a revisit.

    Science.gov (United States)

    Xiong, Wei; Xie, Luyu; Zhou, Shuigeng; Liu, Hui; Guan, Jihong

    2014-01-01

    Topological analysis of protein-protein interaction (PPI) networks has been widely applied to the investigation on cancer mechanisms. However, there is still a debate on whether cancer proteins exhibit more topological centrality compared to the other proteins in the human PPI network. To resolve this debate, we first identified four sets of human proteins, and then mapped these proteins into the yeast PPI network by homologous genes. Finally, we compared these proteins' properties in human and yeast PPI networks. Experiments over two real datasets demonstrated that cancer proteins tend to have higher degree and smaller clustering coefficient than non-cancer proteins. Experimental results also validated that cancer proteins have larger betweenness centrality compared to the other proteins on the STRING dataset. However, on the BioGRID dataset, the average betweenness centrality of cancer proteins is larger than that of disease and control proteins, but smaller than that of essential proteins. PMID:24878726

  18. An ALuc-Based Molecular Tension Probe for Sensing Intramolecular Protein-Protein Interactions.

    Science.gov (United States)

    Kim, Sung-Bae; Nishihara, Ryo; Suzuki, Koji

    2016-01-01

    Optical imaging of protein-protein interactions (PPIs) facilitates comprehensive elucidation of intracellular molecular events. The present protocol demonstrates an optical measure for visualizing molecular tension triggered by any PPI in mammalian cells. A unique design of single-chain probes was fabricated, in which a full-length artificial luciferase (ALuc(®)) was sandwiched between two model proteins of interest, e.g., FKBP and FRB. A molecular tension probe comprising ALuc23 greatly enhances the bioluminescence in response to varying concentrations of rapamycin, and named "tension probe (TP)." The basic probe design can be further modified towards eliminating the C-terminal end of ALuc and was found to improve signal-to-background ratios, named "combinational probe." TPs may become an important addition to the tool box of bioassays in the determination of protein dynamics of interest in mammalian cells. PMID:27424905

  19. Reconstruction of Protein-Protein Interaction Pathways by Mining Subject-Verb-Objects Intermediates

    CERN Document Server

    Ling, Maurice HT; Nicholas, Kevin R; Lin, Feng

    2007-01-01

    The exponential increase in publication rate of new articles is limiting access of researchers to relevant literature. This has prompted the use of text mining tools to extract key biological information. Previous studies have reported extensive modification of existing generic text processors to process biological text. However, this requirement for modification had not been examined. In this study, we have constructed Muscorian, using MontyLingua, a generic text processor. It uses a two-layered generalization-specialization paradigm previously proposed where text was generically processed to a suitable intermediate format before domain-specific data extraction techniques are applied at the specialization layer. Evaluation using a corpus and experts indicated 86-90% precision and approximately 30% recall in extracting protein-protein interactions, which was comparable to previous studies using either specialized biological text processing tools or modified existing tools. Our study had also demonstrated the ...

  20. Role of -methyl-8-(alkoxy)quinolinium iodide in suppression of protein-protein interactions

    Indian Academy of Sciences (India)

    Bimlesh Ojha; Cirantan Kar; Gopal Das

    2013-03-01

    There is a great deal of interest in developing small molecule inhibitors of protein misfolding and aggregation due to a growing number of pathologic states known as amyloid disorders. In searching for alternative ways to reduce protein-protein interactions or to inhibit the amyloid formation, the inhibitory effects of cationic amphiphile viz. -methyl-8-(alkoxy)quinolinium iodide on aggregation behaviour of hen egg white lysozyme (HEWL) at alkaline pH has been studied. Even though the compounds did not protect native HEWL from conformational changes, they were effective in diminishing HEWL amyloid formation, delaying both nucleation and elongation phases. It is likely that strong binding in the HEWL compound complex, raises the activation energy barrier for protein misfolding and subsequent aggregation, thereby retarding the aggregation kinetics substantially.

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

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    Baoman Wang

    2015-01-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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. PMID:25882187

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

    Science.gov (United States)

    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. PMID:26691180

  6. The origins of the evolutionary signal used to predict protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Swapna Lakshmipuram S

    2012-12-01

    Full Text Available Abstract Background The correlation of genetic distances between pairs of protein sequence alignments has been used to infer protein-protein interactions. It has been suggested that these correlations are based on the signal of co-evolution between interacting proteins. However, although mutations in different proteins associated with maintaining an interaction clearly occur (particularly in binding interfaces and neighbourhoods, many other factors contribute to correlated rates of sequence evolution. Proteins in the same genome are usually linked by shared evolutionary history and so it would be expected that there would be topological similarities in their phylogenetic trees, whether they are interacting or not. For this reason the underlying species tree is often corrected for. Moreover processes such as expression level, are known to effect evolutionary rates. However, it has been argued that the correlated rates of evolution used to predict protein interaction explicitly includes shared evolutionary history; here we test this hypothesis. Results In order to identify the evolutionary mechanisms giving rise to the correlations between interaction proteins, we use phylogenetic methods to distinguish similarities in tree topologies from similarities in genetic distances. We use a range of datasets of interacting and non-interacting proteins from Saccharomyces cerevisiae. We find that the signal of correlated evolution between interacting proteins is predominantly a result of shared evolutionary rates, rather than similarities in tree topology, independent of evolutionary divergence. Conclusions Since interacting proteins do not have tree topologies that are more similar than the control group of non-interacting proteins, it is likely that coevolution does not contribute much to, if any, of the observed correlations.

  7. Analysis of intraviral protein-protein interactions of the SARS coronavirus ORFeome.

    Directory of Open Access Journals (Sweden)

    Albrecht von Brunn

    Full Text Available The severe acute respiratory syndrome coronavirus (SARS-CoV genome is predicted to encode 14 functional open reading frames, leading to the expression of up to 30 structural and non-structural protein products. The functions of a large number of viral ORFs are poorly understood or unknown. In order to gain more insight into functions and modes of action and interaction of the different proteins, we cloned the viral ORFeome and performed a genome-wide analysis for intraviral protein interactions and for intracellular localization. 900 pairwise interactions were tested by yeast-two-hybrid matrix analysis, and more than 65 positive non-redundant interactions, including six self interactions, were identified. About 38% of interactions were subsequently confirmed by CoIP in mammalian cells. Nsp2, nsp8 and ORF9b showed a wide range of interactions with other viral proteins. Nsp8 interacts with replicase proteins nsp2, nsp5, nsp6, nsp7, nsp8, nsp9, nsp12, nsp13 and nsp14, indicating a crucial role as a major player within the replication complex machinery. It was shown by others that nsp8 is essential for viral replication in vitro, whereas nsp2 is not. We show that also accessory protein ORF9b does not play a pivotal role for viral replication, as it can be deleted from the virus displaying normal plaque sizes and growth characteristics in Vero cells. However, it can be expected to be important for the virus-host interplay and for pathogenicity, due to its large number of interactions, by enhancing the global stability of the SARS proteome network, or play some unrealized role in regulating protein-protein interactions. The interactions identified provide valuable material for future studies.

  8. Utilization of lysine {sup 13}C-methylation NMR for protein-protein interaction studies

    Energy Technology Data Exchange (ETDEWEB)

    Hattori, Yoshikazu; Furuita, Kyoko [Osaka University, Institute for Protein Research (Japan); Ohki, Izuru, E-mail: i-ooki@bs.naist.jp [Nara Institute of Science and Technology (NAIST), Graduate School of Biological Sciences (Japan); Ikegami, Takahisa [Osaka University, Institute for Protein Research (Japan); Fukada, Harumi [Osaka Prefecture University, Graduate School of Life and Environmental Sciences (Japan); Shirakawa, Masahiro [Kyoto University, Graduate School of Engineering (Japan); Fujiwara, Toshimichi; Kojima, Chojiro, E-mail: kojima@protein.osaka-u.ac.jp [Osaka University, Institute for Protein Research (Japan)

    2013-01-15

    Chemical modification is an easy way for stable isotope labeling of non-labeled proteins. The reductive {sup 13}C-methylation of the amino group of the lysine side-chain by {sup 13}C-formaldehyde is a post-modification and is applicable to most proteins since this chemical modification specifically and quickly proceeds under mild conditions such as 4 Degree-Sign C, pH 6.8, overnight. {sup 13}C-methylation has been used for NMR to study the interactions between the methylated proteins and various molecules, such as small ligands, nucleic acids and peptides. Here we applied lysine {sup 13}C-methylation NMR to monitor protein-protein interactions. The affinity and the intermolecular interaction sites of methylated ubiquitin with three ubiquitin-interacting proteins were successfully determined using chemical-shift perturbation experiments via the {sup 1}H-{sup 13}C HSQC spectra of the {sup 13}C-methylated-lysine methyl groups. The lysine {sup 13}C-methylation NMR results also emphasized the importance of the usage of side-chain signals to monitor the intermolecular interaction sites, and was applicable to studying samples with concentrations in the low sub-micromolar range.

  9. Noise reduction in protein-protein interaction graphs by the implementation of a novel weighting scheme

    Directory of Open Access Journals (Sweden)

    Moschopoulos Charalampos

    2011-06-01

    Full Text Available Abstract Background Recent technological advances applied to biology such as yeast-two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of protein interaction networks. These interaction networks represent a rich, yet noisy, source of data that could be used to extract meaningful information, such as protein complexes. Several interaction network weighting schemes have been proposed so far in the literature in order to eliminate the noise inherent in interactome data. In this paper, we propose a novel weighting scheme and apply it to the S. cerevisiae interactome. Complex prediction rates are improved by up to 39%, depending on the clustering algorithm applied. Results We adopt a two step procedure. During the first step, by applying both novel and well established protein-protein interaction (PPI weighting methods, weights are introduced to the original interactome graph based on the confidence level that a given interaction is a true-positive one. The second step applies clustering using established algorithms in the field of graph theory, as well as two variations of Spectral clustering. The clustered interactome networks are also cross-validated against the confirmed protein complexes present in the MIPS database. Conclusions The results of our experimental work demonstrate that interactome graph weighting methods clearly improve the clustering results of several clustering algorithms. Moreover, our proposed weighting scheme outperforms other approaches of PPI graph weighting.

  10. Simulated evolution of protein-protein interaction networks with realistic topology.

    Directory of Open Access Journals (Sweden)

    G Jack Peterson

    Full Text Available 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.

  11. C2 Domains as Protein-Protein Interaction Modules in the Ciliary Transition Zone

    Directory of Open Access Journals (Sweden)

    Kim Remans

    2014-07-01

    Full Text Available RPGR-interacting protein 1 (RPGRIP1 is mutated in the eye disease Leber congenital amaurosis (LCA and its structural homolog, RPGRIP1-like (RPGRIP1L, is mutated in many different ciliopathies. Both are multidomain proteins that are predicted to interact with retinitis pigmentosa G-protein regulator (RPGR. RPGR is mutated in X-linked retinitis pigmentosa and is located in photoreceptors and primary cilia. We solved the crystal structure of the complex between the RPGR-interacting domain (RID of RPGRIP1 and RPGR and demonstrate that RPGRIP1L binds to RPGR similarly. RPGRIP1 binding to RPGR affects the interaction with PDEδ, the cargo shuttling factor for prenylated ciliary proteins. RPGRIP1-RID is a C2 domain with a canonical β sandwich structure that does not bind Ca2+ and/or phospholipids and thus constitutes a unique type of protein-protein interaction module. Judging from the large number of C2 domains in most of the ciliary transition zone proteins identified thus far, the structure presented here seems to constitute a cilia-specific module that is present in multiprotein transition zone complexes.

  12. SNAPPI-DB: a database and API of Structures, iNterfaces and Alignments for Protein-Protein Interactions.

    Science.gov (United States)

    Jefferson, Emily R; Walsh, Thomas P; Roberts, Timothy J; Barton, Geoffrey J

    2007-01-01

    SNAPPI-DB, a high performance database of Structures, iNterfaces and Alignments of Protein-Protein Interactions, and its associated Java Application Programming Interface (API) is described. SNAPPI-DB contains structural data, down to the level of atom co-ordinates, for each structure in the Protein Data Bank (PDB) together with associated data including SCOP, CATH, Pfam, SWISSPROT, InterPro, GO terms, Protein Quaternary Structures (PQS) and secondary structure information. Domain-domain interactions are stored for multiple domain definitions and are classified by their Superfamily/Family pair and interaction interface. Each set of classified domain-domain interactions has an associated multiple structure alignment for each partner. The API facilitates data access via PDB entries, domains and domain-domain interactions. Rapid development, fast database access and the ability to perform advanced queries without the requirement for complex SQL statements are provided via an object oriented database and the Java Data Objects (JDO) API. SNAPPI-DB contains many features which are not available in other databases of structural protein-protein interactions. It has been applied in three studies on the properties of protein-protein interactions and is currently being employed to train a protein-protein interaction predictor and a functional residue predictor. The database, API and manual are available for download at: http://www.compbio.dundee.ac.uk/SNAPPI/downloads.jsp. PMID:17202171

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

    Directory of Open Access Journals (Sweden)

    Murilo S. Alves

    2014-03-01

    Full Text Available 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.

  14. Novel protein-protein interactions between Entamoeba histolyticad-phosphoglycerate dehydrogenase and phosphoserine aminotransferase.

    Science.gov (United States)

    Mishra, Vibhor; Kumar, Ashutosh; Ali, Vahab; Nozaki, Tomoyoshi; Zhang, Kam Y J; Bhakuni, Vinod

    2012-08-01

    Physical interactions between d-phosphoglycerate dehydrogenase (EhPGDH) and phosphoserine aminotransferase (EhPSAT) from an enteric human parasite Entamoeba histolytica was observed by pull-down assay, gel filtration chromatography, chemical cross-linking, emission anisotropy, molecular docking and molecular dynamic simulations. The protein-protein complex had a 1:1 stochiometry with a dissociation constant of 3.453 × 10(-7) M. Ionic interactions play a significant role in complex formation and stability. Analysis of the energy minimized average simulated model of the protein complex show that the nucleotide binding domain of EhPGDH specifically interacts with EhPSAT. Denaturation studies suggest that the nucleotide binding domain (Nbd) and substrate binding domain (Sbd) of EhPGDH are independent folding/unfolding units. Thus the Nbd-EhPGDH was separately cloned over-expressed and purified to homogeneity. Fluorescence anisotropy study show that the purified Nbd interacts with EhPSAT. Forward enzyme catalyzed reaction for the EhPGDH-PSAT complex showed efficient Km values for 3-phosphoglyceric acid as compared to only EhPGDH suggesting a possibility of substrate channelling in the protein complex. PMID:22386871

  15. Predicting protein-protein interactions in unbalanced data using the primary structure of proteins

    Directory of Open Access Journals (Sweden)

    Chou Lih-Ching

    2010-04-01

    Full Text Available Abstract Background Elucidating protein-protein interactions (PPIs is essential to constructing protein interaction networks and facilitating our understanding of the general principles of biological systems. Previous studies have revealed that interacting protein pairs can be predicted by their primary structure. Most of these approaches have achieved satisfactory performance on datasets comprising equal number of interacting and non-interacting protein pairs. However, this ratio is highly unbalanced in nature, and these techniques have not been comprehensively evaluated with respect to the effect of the large number of non-interacting pairs in realistic datasets. Moreover, since highly unbalanced distributions usually lead to large datasets, more efficient predictors are desired when handling such challenging tasks. Results This study presents a method for PPI prediction based only on sequence information, which contributes in three aspects. First, we propose a probability-based mechanism for transforming protein sequences into feature vectors. Second, the proposed predictor is designed with an efficient classification algorithm, where the efficiency is essential for handling highly unbalanced datasets. Third, the proposed PPI predictor is assessed with several unbalanced datasets with different positive-to-negative ratios (from 1:1 to 1:15. This analysis provides solid evidence that the degree of dataset imbalance is important to PPI predictors. Conclusions Dealing with data imbalance is a key issue in PPI prediction since there are far fewer interacting protein pairs than non-interacting ones. This article provides a comprehensive study on this issue and develops a practical tool that achieves both good prediction performance and efficiency using only protein sequence information.

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

    Science.gov (United States)

    Lin, Peng-Lin; Yu, Ya-Wen; Chung, Ren-Hua

    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

  17. An improved method for scoring protein-protein interactions using semantic similarity within the gene ontology

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    Jain Shobhit

    2010-11-01

    Full Text Available Abstract Background Semantic similarity measures are useful to assess the physiological relevance of protein-protein interactions (PPIs. They quantify similarity between proteins based on their function using annotation systems like the Gene Ontology (GO. Proteins that interact in the cell are likely to be in similar locations or involved in similar biological processes compared to proteins that do not interact. Thus the more semantically similar the gene function annotations are among the interacting proteins, more likely the interaction is physiologically relevant. However, most semantic similarity measures used for PPI confidence assessment do not consider the unequal depth of term hierarchies in different classes of cellular location, molecular function, and biological process ontologies of GO and thus may over-or under-estimate similarity. Results We describe an improved algorithm, Topological Clustering Semantic Similarity (TCSS, to compute semantic similarity between GO terms annotated to proteins in interaction datasets. Our algorithm, considers unequal depth of biological knowledge representation in different branches of the GO graph. The central idea is to divide the GO graph into sub-graphs and score PPIs higher if participating proteins belong to the same sub-graph as compared to if they belong to different sub-graphs. Conclusions The TCSS algorithm performs better than other semantic similarity measurement techniques that we evaluated in terms of their performance on distinguishing true from false protein interactions, and correlation with gene expression and protein families. We show an average improvement of 4.6 times the F1 score over Resnik, the next best method, on our Saccharomyces cerevisiae PPI dataset and 2 times on our Homo sapiens PPI dataset using cellular component, biological process and molecular function GO annotations.

  18. Inferring the Brassica rapa Interactome Using Protein-Protein Interaction Data from Arabidopsis thaliana.

    Science.gov (United States)

    Yang, Jianhua; Osman, Kim; Iqbal, Mudassar; Stekel, Dov J; Luo, Zewei; Armstrong, Susan J; Franklin, F Chris H

    2012-01-01

    Following successful completion of the Brassica rapa sequencing project, the next step is to investigate functions of individual genes/proteins. For Arabidopsis thaliana, large amounts of protein-protein interaction (PPI) data are available from the major PPI databases (DBs). It is known that Brassica crop species are closely related to A. thaliana. This provides an opportunity to infer the B. rapa interactome using PPI data available from A. thaliana. In this paper, we present an inferred B. rapa interactome that is based on the A. thaliana PPI data from two resources: (i) A. thaliana PPI data from three major DBs, BioGRID, IntAct, and TAIR. (ii) ortholog-based A. thaliana PPI predictions. Linking between B. rapa and A. thaliana was accomplished in three complementary ways: (i) ortholog predictions, (ii) identification of gene duplication based on synteny and collinearity, and (iii) BLAST sequence similarity search. A complementary approach was also applied, which used known/predicted domain-domain interaction data. Specifically, since the two species are closely related, we used PPI data from A. thaliana to predict interacting domains that might be conserved between the two species. The predicted interactome was investigated for the component that contains known A. thaliana meiotic proteins to demonstrate its usability. PMID:23293649

  19. Inferring the Brassica rapa interactome using protein-protein interaction data from Arabidopsis thaliana

    Directory of Open Access Journals (Sweden)

    Jianhua eYang

    2013-01-01

    Full Text Available Following successful completion of the Brassica rapa sequencing project, the next step is to investigate functions of individual genes/proteins. For Arabidopsis thaliana, large amounts of protein-protein interaction (PPI data are available from the major PPI databases. It is known that Brassica crop species are closely related to A. thaliana. This provides an opportunity to infer the B. rapa interactome using PPI data available from A. thaliana. In this paper, we present an inferred B. rapa interactome that is based on the A. thaliana PPI data from two resources: (i A. thaliana PPI data from three major databases, BioGRID, IntAct and TAIR. (ii ortholog-based A. thaliana PPI predictions. Linking between B. rapa and A. thaliana was accomplished in three complementary ways: (i ortholog predictions, (ii identification of gene duplication based on synteny and collinearity, and (iii BLAST sequence similarity search. A complementary approach was also applied, which used known/predicted domain-domain interaction data. Specifically, since the two species are closely related, we used PPI data from A. thaliana to predict interacting domains that might be conserved between the two species. The predicted interactome was investigated for the component that contains known A. thaliana meiotic proteins to demonstrate its usability.

  20. Interplay between binding affinity and kinetics in protein-protein interactions.

    Science.gov (United States)

    Cao, Huaiqing; Huang, Yongqi; Liu, Zhirong

    2016-07-01

    To clarify the interplay between the binding affinity and kinetics of protein-protein interactions, and the possible role of intrinsically disordered proteins in such interactions, molecular simulations were carried out on 20 protein complexes. With bias potential and reweighting techniques, the free energy profiles were obtained under physiological affinities, which showed that the bound-state valley is deep with a barrier height of 12 - 33 RT. From the dependence of the affinity on interface interactions, the entropic contribution to the binding affinity is approximated to be proportional to the interface area. The extracted dissociation rates based on the Arrhenius law correlate reasonably well with the experimental values (Pearson correlation coefficient R = 0.79). For each protein complex, a linear free energy relationship between binding affinity and the dissociation rate was confirmed, but the distribution of the slopes for intrinsically disordered proteins showed no essential difference with that observed for ordered proteins. A comparison with protein folding was also performed. Proteins 2016; 84:920-933. © 2016 Wiley Periodicals, Inc. PMID:27018856

  1. A miniaturized sandwich immunoassay platform for the detection of protein-protein interactions

    Directory of Open Access Journals (Sweden)

    He Wei

    2010-10-01

    Full Text Available Abstract Background Analysis of protein-protein interactions (PPIs is a valuable approach for the characterization of huge networks of protein complexes or proteins of unknown function. Co-immunoprecipitation (coIP using affinity resins coupled to protein A/G is the most widely used method for PPI detection. However, this traditional large scale resin-based coIP is too laborious and time consuming. To overcome this problem, we developed a miniaturized sandwich immunoassay platform (MSIP by combining antibody array technology and coIP methods. Results Based on anti-FLAG antibody spotted aldehyde slides, MSIP enables simple, rapid and large scale detection of PPIs by fluorescent labeling anti-myc antibody. By analyzing well-known interacting and non-interacting protein pairs, MSIP was demonstrated to be highly accurate and reproducible. Compared to traditional resin-based coIP, MSIP results in higher sensitivity and enhanced throughput, with the additional benefit of digital read-outs. In addition, MSIP was shown to be a highly useful validation platform to confirm PPI candidates that have been identified from yeast two hybrid systems. Conclusions In conclusion, MSIP is proved to be a simple, cost-saving and highly efficient technique for the comprehensive study of PPIs.

  2. Comparative Analysis of Protein-Protein Interactions in Cancer-Associated Genes 25

    Institute of Scientific and Technical Information of China (English)

    Purnima Guda; Sridar V. Chittur; Chittibabu Guda

    2009-01-01

    Protein-protein interactions (PPIs) have been widely studied to understand the bi-ological processes or molecular functions associated with different disease systems like cancer. While focused studies on individual cancers have generated valuable in-formation, global and comparative analysis of datasets from different cancer types has not been done. In this work, we carried out bioinformatic analysis of PPIs corresponding to differentially expressed genes from microarrays of various tumor tissues (belonging to bladder, colon, kidney and thyroid cancers) and compared their associated biological processes and molecular functions (based on Gene On-tology terms). We identified a set of processes or functions that are common to all these cancers, as well as those that are specific to only one or partial cancer types. Similarly, protein interaction networks in nucleic acid metabolism were compared to identify the common/specific clusters of proteins across different cancer types. Our results provide a basis for further experimental investigations to study protein interaction networks associated with cancer. The methodology developed in this work can also be applied to study similar disease systems.

  3. AlphaSpace: Fragment-Centric Topographical Mapping To Target Protein-Protein Interaction Interfaces.

    Science.gov (United States)

    Rooklin, David; Wang, Cheng; Katigbak, Joseph; Arora, Paramjit S; Zhang, Yingkai

    2015-08-24

    Inhibition of protein-protein interactions (PPIs) is emerging as a promising therapeutic strategy despite the difficulty in targeting such interfaces with drug-like small molecules. PPIs generally feature large and flat binding surfaces as compared to typical drug targets. These features pose a challenge for structural characterization of the surface using geometry-based pocket-detection methods. An attractive mapping strategy--that builds on the principles of fragment-based drug discovery (FBDD)--is to detect the fragment-centric modularity at the protein surface and then characterize the large PPI interface as a set of localized, fragment-targetable interaction regions. Here, we introduce AlphaSpace, a computational analysis tool designed for fragment-centric topographical mapping (FCTM) of PPI interfaces. Our approach uses the alpha sphere construct, a geometric feature of a protein's Voronoi diagram, to map out concave interaction space at the protein surface. We introduce two new features--alpha-atom and alpha-space--and the concept of the alpha-atom/alpha-space pair to rank pockets for fragment-targetability and to facilitate the evaluation of pocket/fragment complementarity. The resulting high-resolution interfacial map of targetable pocket space can be used to guide the rational design and optimization of small molecule or biomimetic PPI inhibitors. PMID:26225450

  4. Coordination of Pancreatic HCO3- Secretion by Protein-Protein Interaction between Membrane Transporters

    Directory of Open Access Journals (Sweden)

    Lee MG

    2001-07-01

    Full Text Available Increasing evidence suggests that protein-protein interaction is essential in many biological processes including epithelial transport. In this report, we discuss the significance of protein interactions to HCO(3(- secretion in pancreatic duct cells. In pancreatic ducts HCO(3(- secretion is mediated by cystic fibrosis transmembrane conductance regulator (CFTR activated luminal Cl(-/HCO(3(- exchange activity and HCO(3(- absorption is achieved by Na(+-dependent mechanisms including Na(+/H(+ exchanger 3 (NHE3. We found biochemical and functional association between CFTR and NHE3. In addition, protein binding through PDZ modules is needed for this regulatory interaction. CFTR affected NHE3 activities in two ways. Acutely, CFTR augmented the cAMP-dependent inhibition of NHE3. In a chronic mechanism, CFTR increases the luminal expression of Na(+/H(+ exchange in pancreatic duct cells. These findings reveal that protein complexes in the plasma membrane of pancreatic duct cells are highly organized for efficient HCO(3(- secretion.

  5. Protein-protein interactions in a crowded environment: an analysis via cross-docking simulations and evolutionary information.

    Directory of Open Access Journals (Sweden)

    Anne Lopes

    Full Text Available Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information showing that the combination of the two improves partner identification. On the other hand, since protein interactions usually occur in crowded environments with several competing partners, we realized a thorough analysis of the interactions of proteins with true partners but also with non-partners to evaluate whether proteins in the environment, competing with the true partner, affect its identification. We found three populations of proteins: strongly competing, never competing, and interacting with different levels of strength. Populations and levels of strength are numerically characterized and provide a signature for the behavior of a protein in the crowded environment. We showed that partner identification, to some extent, does not depend on the competing partners present in the environment, that certain biochemical classes of proteins are intrinsically easier to analyze than others, and that small proteins are not more promiscuous than large ones. Our approach brings to light that the knowledge of the binding site can be used to reduce the high computational cost of docking simulations with no consequence in the quality of the results, demonstrating the possibility to apply coarse-grain docking to datasets made of thousands of proteins. Comparison with all available large-scale analyses aimed to partner predictions is realized. We release the complete decoys set issued by coarse-grain docking simulations of both true and false interacting partners, and

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

    Science.gov (United States)

    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. PMID:27434096

  7. Modulating non-native aggregation and electrostatic protein-protein interactions with computationally designed single-point mutations.

    Science.gov (United States)

    O'Brien, C J; Blanco, M A; Costanzo, J A; Enterline, M; Fernandez, E J; Robinson, A S; Roberts, C J

    2016-06-01

    Non-native protein aggregation is a ubiquitous challenge in the production, storage and administration of protein-based biotherapeutics. This study focuses on altering electrostatic protein-protein interactions as a strategy to modulate aggregation propensity in terms of temperature-dependent aggregation rates, using single-charge variants of human γ-D crystallin. Molecular models were combined to predict amino acid substitutions that would modulate protein-protein interactions with minimal effects on conformational stability. Experimental protein-protein interactions were quantified by the Kirkwood-Buff integrals (G22) from laser scattering, and G22 showed semi-quantitative agreement with model predictions. Experimental initial-rates for aggregation showed that increased (decreased) repulsive interactions led to significantly increased (decreased) aggregation resistance, even based solely on single-point mutations. However, in the case of a particular amino acid (E17), the aggregation mechanism was altered by substitution with R or K, and this greatly mitigated improvements in aggregation resistance. The results illustrate that predictions based on native protein-protein interactions can provide a useful design target for engineering aggregation resistance; however, this approach needs to be balanced with consideration of how mutations can impact aggregation mechanisms. PMID:27160179

  8. PPI finder: a mining tool for human protein-protein interactions.

    Directory of Open Access Journals (Sweden)

    Min He

    Full Text Available BACKGROUND: The exponential increase of published biomedical literature prompts the use of text mining tools to manage the information overload automatically. One of the most common applications is to mine protein-protein interactions (PPIs from PubMed abstracts. Currently, most tools in mining PPIs from literature are using co-occurrence-based approaches or rule-based approaches. Hybrid methods (frame-based approaches by combining these two methods may have better performance in predicting PPIs. However, the predicted PPIs from these methods are rarely evaluated by known PPI databases and co-occurred terms in Gene Ontology (GO database. METHODOLOGY/PRINCIPAL FINDINGS: We here developed a web-based tool, PPI Finder, to mine human PPIs from PubMed abstracts based on their co-occurrences and interaction words, followed by evidences in human PPI databases and shared terms in GO database. Only 28% of the co-occurred pairs in PubMed abstracts appeared in any of the commonly used human PPI databases (HPRD, BioGRID and BIND. On the other hand, of the known PPIs in HPRD, 69% showed co-occurrences in the literature, and 65% shared GO terms. CONCLUSIONS: PPI Finder provides a useful tool for biologists to uncover potential novel PPIs. It is freely accessible at http://liweilab.genetics.ac.cn/tm/.

  9. Prediction of Protein-Protein Interaction By Metasample-Based Sparse Representation

    Directory of Open Access Journals (Sweden)

    Xiuquan Du

    2015-01-01

    Full Text Available Protein-protein interactions (PPIs play key roles in many cellular processes such as transcription regulation, cell metabolism, and endocrine function. Understanding these interactions takes a great promotion to the pathogenesis and treatment of various diseases. A large amount of data has been generated by experimental techniques; however, most of these data are usually incomplete or noisy, and the current biological experimental techniques are always very time-consuming and expensive. In this paper, we proposed a novel method (metasample-based sparse representation classification, MSRC for PPIs prediction. A group of metasamples are extracted from the original training samples and then use the l1-regularized least square method to express a new testing sample as the linear combination of these metasamples. PPIs prediction is achieved by using a discrimination function defined in the representation coefficients. The MSRC is applied to PPIs dataset; it achieves 84.9% sensitivity, and 94.55% specificity, which is slightly lower than support vector machine (SVM and much higher than naive Bayes (NB, neural networks (NN, and k-nearest neighbor (KNN. The result shows that the MSRC is efficient for PPIs prediction.

  10. Femtosecond UV-laser pulses to unveil protein-protein interactions in living cells.

    Science.gov (United States)

    Itri, Francesco; Monti, Daria M; Della Ventura, Bartolomeo; Vinciguerra, Roberto; Chino, Marco; Gesuele, Felice; Lombardi, Angelina; Velotta, Raffaele; Altucci, Carlo; Birolo, Leila; Piccoli, Renata; Arciello, Angela

    2016-02-01

    A hallmark to decipher bioprocesses is to characterize protein-protein interactions in living cells. To do this, the development of innovative methodologies, which do not alter proteins and their natural environment, is particularly needed. Here, we report a method (LUCK, Laser UV Cross-linKing) to in vivo cross-link proteins by UV-laser irradiation of living cells. Upon irradiation of HeLa cells under controlled conditions, cross-linked products of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were detected, whose yield was found to be a linear function of the total irradiation energy. We demonstrated that stable dimers of GAPDH were formed through intersubunit cross-linking, as also observed when the pure protein was irradiated by UV-laser in vitro. We proposed a defined patch of aromatic residues located at the enzyme subunit interface as the cross-linking sites involved in dimer formation. Hence, by this technique, UV-laser is able to photofix protein surfaces that come in direct contact. Due to the ultra-short time scale of UV-laser-induced cross-linking, this technique could be extended to weld even transient protein interactions in their native context. PMID:26265182

  11. Radioresistance related genes screened by protein-protein interaction network analysis in nasopharyngeal carcinoma

    International Nuclear Information System (INIS)

    Objective: To discover radioresistance associated molecular biomarkers and its mechanism in nasopharyngeal carcinoma by protein-protein interaction network analysis. Methods: Whole genome expression microarray was applied to screen out differentially expressed genes in two cell lines CNE-2R and CNE-2 with different radiosensitivity. Four differentially expressed genes were randomly selected for further verification by the semi-quantitative RT-PCR analysis with self-designed primers. The common differentially expressed genes from two experiments were analyzed with the SNOW online database in order to find out the central node related to the biomarkers of nasopharyngeal carcinoma radioresistance. The expression of STAT1 in CNE-2R and CNE-2 cells was measured by Western blot. Results: Compared with CNE-2 cells, 374 genes in CNE-2R cells were differentially expressed while 197 genes showed significant differences. Four randomly selected differentially expressed genes were verified by RT-PCR and had same change trend in consistent with the results of chip assay. Analysis with the SNOW database demonstrated that those 197 genes could form a complicated interaction network where STAT1 and JUN might be two key nodes. Indeed, the STAT1-α expression in CNE-2R was higher than that in CNE-2 (t=4.96, P<0.05). Conclusions: The key nodes of STAT1 and JUN may be the molecular biomarkers leading to radioresistance in nasopharyngeal carcinoma, and STAT1-α might have close relationship with radioresistance. (authors)

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

    Science.gov (United States)

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

    2015-10-01

    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

  13. Interaction preferences across protein-protein interfaces of obligatory and non-obligatory components are different

    Directory of Open Access Journals (Sweden)

    Srinivasan N

    2005-08-01

    Full Text Available Abstract Background A polypeptide chain of a protein-protein complex is said to be obligatory if it is bound to another chain throughout its functional lifetime. Such a chain might not adopt the native fold in the unbound form. A non-obligatory polypeptide chain associates with another chain and dissociates upon molecular stimulus. Although conformational changes at the interaction interface are expected, the overall 3-D structure of the non-obligatory chain is unaltered. The present study focuses on protein-protein complexes to understand further the differences between obligatory and non-obligatory interfaces. Results A non-obligatory chain in a complex of known 3-D structure is recognized by its stable existence with same fold in the bound and unbound forms. On the contrary, an obligatory chain is detected by its existence only in the bound form with no evidence for the native-like fold of the chain in the unbound form. Various interfacial properties of a large number of complexes of known 3-D structures thus classified are comparatively analyzed with an aim to identify structural descriptors that distinguish these two types of interfaces. We report that the interaction patterns across the interfaces of obligatory and non-obligatory components are different and contacts made by obligatory chains are predominantly non-polar. The obligatory chains have a higher number of contacts per interface (20 ± 14 contacts per interface than non-obligatory chains (13 ± 6 contacts per interface. The involvement of main chain atoms is higher in the case of obligatory chains (16.9 % compared to non-obligatory chains (11.2 %. The β-sheet formation across the subunits is observed only among obligatory protein chains in the dataset. Apart from these, other features like residue preferences and interface area produce marginal differences and they may be considered collectively while distinguishing the two types of interfaces. Conclusion These results can be

  14. Painting Proteins Blue: β-(1-Azulenyl)-L-Alanine as a Probe for Studying Protein-Protein Interactions

    Science.gov (United States)

    Moroz, Yurii S.; Binder, Wolfgang; Nygren, Patrik; Caputo, Gregory A.; Korendovych, Ivan V.

    2013-01-01

    We demonstrated that β-(1-Azulenyl)-L-Alanine, a fluorescent pseudoisosteric analog of tryptophan, exhibits weak environmental dependence and thus allows for using weak intrinsic quenchers, such as methionines, to monitor protein-protein interactions while not perturbing them. PMID:23207368

  15. InterMitoBase: An annotated database and analysis platform of protein-protein interactions for human mitochondria

    OpenAIRE

    Zhang Chenyu; Xu Hua; Wang Junling; Gong Ming; Gao Song; Li Jie; Gu Zuguang; Wang Jin

    2011-01-01

    Abstract Background The mitochondrion is an essential organelle which plays important roles in diverse biological processes, such as metabolism, apoptosis, signal transduction and cell cycle. Characterizing protein-protein interactions (PPIs) that execute mitochondrial functions is fundamental in understanding the mechanisms underlying biological functions and diseases associated with mitochondria. Investigations examining mitochondria are expanding to the system level because of the accumula...

  16. Design and modular parallel synthesis of a MCR derived α-helix mimetic protein-protein interaction inhibitor scaffold

    NARCIS (Netherlands)

    Antuch, Walfrido; Menon, Sanjay; Chen, Quin-Zene; Lu, Yingchun; Sakamuri, Sukumar; Beck, Barbara; Schauer-Vukašinović, Vesna; Agarwal, Seema; Hess, Sibylle; Dömling, Alexander

    2006-01-01

    A terphenyl α-helix mimetic scaffold recognized to be capable of disrupting protein-protein interactions was structurally morphed into an easily amenable and versatile multicomponent reaction (MCR) backbone. The design, modular in-parallel library synthesis, initial cell based biological data, and p

  17. Light-regulated stapled peptides to inhibit protein-protein interactions involved in clathrin-mediated endocytosis.

    Science.gov (United States)

    Nevola, Laura; Martín-Quirós, Andrés; Eckelt, Kay; Camarero, Núria; Tosi, Sébastien; Llobet, Artur; Giralt, Ernest; Gorostiza, Pau

    2013-07-22

    Control of membrane traffic: Photoswitchable inhibitors of protein-protein interactions were applied to photoregulate clathrin-mediated endocytosis (CME) in living cells. Traffic light (TL) peptides acting as "stop" and "go" signals for membrane traffic can be used to dissect the role of CME in receptor internalization and in cell growth, division, and differentiation. PMID:23775788

  18. Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

    OpenAIRE

    Morrell-Falvey, J. L.; Qi, H.; Doktycz, M. J.; Venkatraman, S.

    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 ...

  19. Structural deformation upon protein-protein interaction: A structural alphabet approach

    OpenAIRE

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

    2008-01-01

    Abstract Background In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding. Results In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backb...

  20. A domain-based approach to predict protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Resat Haluk

    2007-06-01

    Full Text Available Abstract Background Knowing which proteins exist in a certain organism or cell type and how these proteins interact with each other are necessary for the understanding of biological processes at the whole cell level. The determination of the protein-protein interaction (PPI networks has been the subject of extensive research. Despite the development of reasonably successful methods, serious technical difficulties still exist. In this paper we present DomainGA, a quantitative computational approach that uses the information about the domain-domain interactions to predict the interactions between proteins. Results DomainGA is a multi-parameter optimization method in which the available PPI information is used to derive a quantitative scoring scheme for the domain-domain pairs. Obtained domain interaction scores are then used to predict whether a pair of proteins interacts. Using the yeast PPI data and a series of tests, we show the robustness and insensitivity of the DomainGA method to the selection of the parameter sets, score ranges, and detection rules. Our DomainGA method achieves very high explanation ratios for the positive and negative PPIs in yeast. Based on our cross-verification tests on human PPIs, comparison of the optimized scores with the structurally observed domain interactions obtained from the iPFAM database, and sensitivity and specificity analysis; we conclude that our DomainGA method shows great promise to be applicable across multiple organisms. Conclusion We envision the DomainGA as a first step of a multiple tier approach to constructing organism specific PPIs. As it is based on fundamental structural information, the DomainGA approach can be used to create potential PPIs and the accuracy of the constructed interaction template can be further improved using complementary methods. Explanation ratios obtained in the reported test case studies clearly show that the false prediction rates of the template networks constructed

  1. Stabilization of Protein-Protein Interactions in chemical biology and drug discovery.

    Science.gov (United States)

    Bier, David; Thiel, Philipp; Briels, Jeroen; Ottmann, Christian

    2015-10-01

    More than 300,000 Protein-Protein Interactions (PPIs) can be found in human cells. This number is significantly larger than the number of single proteins, which are the classical targets for pharmacological intervention. Hence, specific and potent modulation of PPIs by small, drug-like molecules would tremendously enlarge the "druggable genome" enabling novel ways of drug discovery for essentially every human disease. This strategy is especially promising in diseases with difficult targets like intrinsically disordered proteins or transcription factors, for example neurodegeneration or metabolic diseases. Whereas the potential of PPI modulation has been recognized in terms of the development of inhibitors that disrupt or prevent a binary protein complex, the opposite (or complementary) strategy to stabilize PPIs has not yet been realized in a systematic manner. This fact is rather surprising given the number of impressive natural product examples that confer their activity by stabilizing specific PPIs. In addition, in recent years more and more examples of synthetic molecules are being published that work as PPI stabilizers, despite the fact that in the majority they initially have not been designed as such. Here, we describe examples from both the natural products as well as the synthetic molecules advocating for a stronger consideration of the PPI stabilization approach in chemical biology and drug discovery. PMID:26093250

  2. Dynamic protein-protein interaction subnetworks of lung cancer in cases with smoking history

    Directory of Open Access Journals (Sweden)

    Wei Yu

    2013-02-01

    Full Text Available Smoking is the primary cause of lung cancer and is linked to 85% of lung cancer cases. However, how lung cancer develops in patients with smoking history remains unclear. Systems approaches that combine human protein-protein interaction (PPI networks and gene expression data are superior to traditional methods. We performed these systems to determine the role that smoking plays in lung cancer development and used the support vector machine (SVM model to predict PPIs. By defining expression variance (EV, we found 520 dynamic proteins (EV>0.4 using data from the Human Protein Reference Database and Gene Expression Omnibus Database, and built 7 dynamic PPI subnetworks of lung cancer in patients with smoking history. We also determined the primary functions of each subnetwork: signal transduction, apoptosis, and cell migration and adhesion for subnetwork A; cell-sustained angiogenesis for subnetwork B; apoptosis for subnetwork C; and, finally, signal transduction and cell replication and proliferation for subnetworks D-G. The probability distribution of the degree of dynamic protein and static protein differed, clearly showing that the dynamic proteins were not the core proteins which widely connected with their neighbor proteins. There were high correlations among the dynamic proteins, suggesting that the dynamic proteins tend to form specific dynamic modules. We also found that the dynamic proteins were only correlated with the expression of selected proteins but not all neighbor proteins when cancer occurred.

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

    Science.gov (United States)

    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. PMID:23112006

  4. Inference of gene-phenotype associations via protein-protein interaction and orthology.

    Directory of Open Access Journals (Sweden)

    Panwen Wang

    Full Text Available One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.

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

    Science.gov (United States)

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

    2015-01-01

    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. PMID:26490033

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

    Science.gov (United States)

    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. Identification of Candidate Genes related to Bovine Marbling using Protein-Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Dajeong Lim, Nam-Kuk Kim, Hye-Sun Park, Seung-Hwan Lee, Yong-Min Cho, Sung Jong Oh, Tae-Hun Kim, Heebal Kim

    2011-01-01

    Full Text Available Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The present study systemically analyzed genes associated with bovine marbling score and identified their relationships. The candidate nodes were obtained using MedScan text-mining tools and linked by protein-protein interaction (PPI from the Human Protein Reference Database (HPRD. To determine key node of marbling, the degree and betweenness centrality (BC were used. The hub nodes and biological pathways of our network are consistent with the previous reports about marbling traits, and also suggest unknown candidate genes associated with intramuscular fat. Five nodes were identified as hub genes, which was consistent with the network analysis using quantitative reverse-transcription PCR (qRT-PCR. Key nodes of the PPI network have positive roles (PPARγ, C/EBPα, and RUNX1T1 and negative roles (RXRA, CAMK2A in the development of intramuscular fat by several adipogenesis-related pathways. This study provides genetic information for identifying candidate genes for the marbling trait in bovine.

  8. The many faces of protein-protein interactions: A compendium of interface geometry.

    Directory of Open Access Journals (Sweden)

    Wan Kyu Kim

    2006-09-01

    Full Text Available A systematic classification of protein-protein interfaces is a valuable resource for understanding the principles of molecular recognition and for modelling protein complexes. Here, we present a classification of domain interfaces according to their geometry. Our new algorithm uses a hybrid approach of both sequential and structural features. The accuracy is evaluated on a hand-curated dataset of 416 interfaces. Our hybrid procedure achieves 83% precision and 95% recall, which improves the earlier sequence-based method by 5% on both terms. We classify virtually all domain interfaces of known structure, which results in nearly 6,000 distinct types of interfaces. In 40% of the cases, the interacting domain families associate in multiple orientations, suggesting that all the possible binding orientations need to be explored for modelling multidomain proteins and protein complexes. In general, hub proteins are shown to use distinct surface regions (multiple faces for interactions with different partners. Our classification provides a convenient framework to query genuine gene fusion, which conserves binding orientation in both fused and separate forms. The result suggests that the binding orientations are not conserved in at least one-third of the gene fusion cases detected by a conventional sequence similarity search. We show that any evolutionary analysis on interfaces can be skewed by multiple binding orientations and multiple interaction partners. The taxonomic distribution of interface types suggests that ancient interfaces common to the three major kingdoms of life are enriched by symmetric homodimers. The classification results are online at http://www.scoppi.org.

  9. Screening of Small-Molecule Inhibitors of Protein-Protein Interaction with Capillary Electrophoresis Frontal Analysis.

    Science.gov (United States)

    Xu, Mei; Liu, Chao; Zhou, Mi; Li, Qing; Wang, Renxiao; Kang, Jingwu

    2016-08-16

    A simple and effective method for identifying inhibitors of protein-protein interactions (PPIs) was developed by using capillary electrophoresis frontal analysis (CE-FA). Antiapoptotic B-cell-2 (Bcl-2) family member Bcl-XL protein, a 5-carboxyfluorescein labeled peptide truncated from the BH3 domain of Bid (F-Bid) as the ligand, and a known Bcl-XL-Bid interaction inhibitor ABT-263 were employed as an experimental model for the proof of concept. In CE-FA, the free ligand is separated from the protein and protein-ligand complex to permit the measurement of the equilibrium concentration of the ligand, hence the dissociation constant of the protein-ligand complex. In the presence of inhibitors, formation of the protein-ligand complex is hindered, thereby the inhibition can be easily identified by the raised plateau height of the ligand and the decayed plateau of the complex. Further, we proposed an equation used to convert the IC50 value into the inhibition constant Ki value, which is more useful than the former for comparison. In addition, the sample pooling strategy was employed to improve the screening throughput more than 10 times. A small chemical library composed of synthetic compounds and natural extracts were screened with the method, two natural products, namely, demethylzeylasteral and celastrol, were identified as new inhibitors to block the Bcl-XL-Bid interaction. Cell-based assay was performed to validate the activity of the identified compounds. The result demonstrated that CE-FA represents a straightforward and robust technique for screening of PPI inhibitors. PMID:27425825

  10. Functional mapping of protein-protein interactions in an enzyme complex by directed evolution.

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    Kathrin Roderer

    Full Text Available The shikimate pathway enzyme chorismate mutase converts chorismate into prephenate, a precursor of Tyr and Phe. The intracellular chorismate mutase (MtCM of Mycobacterium tuberculosis is poorly active on its own, but becomes >100-fold more efficient upon formation of a complex with the first enzyme of the shikimate pathway, 3-deoxy-d-arabino-heptulosonate-7-phosphate synthase (MtDS. The crystal structure of the enzyme complex revealed involvement of C-terminal MtCM residues with the MtDS interface. Here we employed evolutionary strategies to probe the tolerance to substitution of the C-terminal MtCM residues from positions 84-90. Variants with randomized positions were subjected to stringent selection in vivo requiring productive interactions with MtDS for survival. Sequence patterns identified in active library members coincide with residue conservation in natural chorismate mutases of the AroQδ subclass to which MtCM belongs. An Arg-Gly dyad at positions 85 and 86, invariant in AroQδ sequences, was intolerant to mutation, whereas Leu88 and Gly89 exhibited a preference for small and hydrophobic residues in functional MtCM-MtDS complexes. In the absence of MtDS, selection under relaxed conditions identifies positions 84-86 as MtCM integrity determinants, suggesting that the more C-terminal residues function in the activation by MtDS. Several MtCM variants, purified using a novel plasmid-based T7 RNA polymerase gene expression system, showed that a diminished ability to physically interact with MtDS correlates with reduced activatability and feedback regulatory control by Tyr and Phe. Mapping critical protein-protein interaction sites by evolutionary strategies may pinpoint promising targets for drugs that interfere with the activity of protein complexes.

  11. Comparing human-Salmonella with plant-Salmonella protein-protein interaction predictions

    Directory of Open Access Journals (Sweden)

    Sylvia eSchleker

    2015-01-01

    Full Text Available Salmonellosis is the most frequent food-borne disease world-wide and can be transmitted to humans by a variety of routes, especially via animal and plant products. Salmonella bacteria are believed to use not only animal and human but also plant hosts despite their evolutionary distance. This raises the question if Salmonella employs similar mechanisms in infection of these diverse hosts. Given that most of our understanding comes from its interaction with human hosts, we investigate here to what degree knowledge of Salmonella-human interactions can be transferred to the Salmonella-plant system. Reviewed are recent publications on analysis and prediction of Salmonella-host interactomes. Putative protein-protein interactions (PPIs between Salmonella and its human and Arabidopsis hosts were retrieved utilizing purely interolog-based approaches in which predictions were inferred based on available sequence and domain information of known PPIs, and machine learning approaches that integrate a larger set of useful information from different sources. Transfer learning is an especially suitable machine learning technique to predict plant host targets from the knowledge of human host targets. A comparison of the prediction results with transcriptomic data shows a clear overlap between the host proteins predicted to be targeted by PPIs and their gene ontology enrichment in both host species and regulation of gene expression. In particular, the cellular processes Salmonella interferes with in plants and humans are catabolic processes. The details of how these processes are targeted, however, are quite different between the two organisms, as expected based on their evolutionary and habitat differences. Possible implications of this observation on evolution of host-pathogen communication are discussed.

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

    Science.gov (United States)

    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

  13. Identifying novel protein phenotype annotations by hybridizing protein-protein interactions and protein sequence similarities.

    Science.gov (United States)

    Chen, Lei; Zhang, Yu-Hang; Huang, Tao; Cai, Yu-Dong

    2016-04-01

    Studies of protein phenotypes represent a central challenge of modern genetics in the post-genome era because effective and accurate investigation of protein phenotypes is one of the most critical procedures to identify functional biological processes in microscale, which involves the analysis of multifactorial traits and has greatly contributed to the development of modern biology in the post genome era. Therefore, we have developed a novel computational method that identifies novel proteins associated with certain phenotypes in yeast based on the protein-protein interaction network. Unlike some existing network-based computational methods that identify the phenotype of a query protein based on its direct neighbors in the local network, the proposed method identifies novel candidate proteins for a certain phenotype by considering all annotated proteins with this phenotype on the global network using a shortest path (SP) algorithm. The identified proteins are further filtered using both a permutation test and their interactions and sequence similarities to annotated proteins. We compared our method with another widely used method called random walk with restart (RWR). The biological functions of proteins for each phenotype identified by our SP method and the RWR method were analyzed and compared. The results confirmed a large proportion of our novel protein phenotype annotation, and the RWR method showed a higher false positive rate than the SP method. Our method is equally effective for the prediction of proteins involving in all the eleven clustered yeast phenotypes with a quite low false positive rate. Considering the universality and generalizability of our supporting materials and computing strategies, our method can further be applied to study other organisms and the new functions we predicted can provide pertinent instructions for the further experimental verifications. PMID:26728152

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

    Science.gov (United States)

    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. PMID:26646257

  15. Evolutionary Dynamics of Floral Homeotic Transcription Factor Protein-Protein Interactions.

    Science.gov (United States)

    Bartlett, Madelaine; Thompson, Beth; Brabazon, Holly; Del Gizzi, Robert; Zhang, Thompson; Whipple, Clinton

    2016-06-01

    Protein-protein interactions (PPIs) have widely acknowledged roles in the regulation of development, but few studies have addressed the timing and mechanism of shifting PPIs over evolutionary history. The B-class MADS-box transcription factors, PISTILLATA (PI) and APETALA3 (AP3) are key regulators of floral development. PI-like (PI(L)) and AP3-like (AP3(L)) proteins from a number of plants, including Arabidopsis thaliana (Arabidopsis) and the grass Zea mays (maize), bind DNA as obligate heterodimers. However, a PI(L) protein from the grass relative Joinvillea can bind DNA as a homodimer. To ascertain whether Joinvillea PI(L) homodimerization is an anomaly or indicative of broader trends, we characterized PI(L) dimerization across the Poales and uncovered unexpected evolutionary lability. Both obligate B-class heterodimerization and PI(L) homodimerization have evolved multiple times in the order, by distinct molecular mechanisms. For example, obligate B-class heterodimerization in maize evolved very recently from PI(L) homodimerization. A single amino acid change, fixed during domestication, is sufficient to toggle one maize PI(L) protein between homodimerization and obligate heterodimerization. We detected a signature of positive selection acting on residues preferentially clustered in predicted sites of contact between MADS-box monomers and dimers, and in motifs that mediate MADS PPI specificity in Arabidopsis. Changing one positively selected residue can alter PI(L) dimerization activity. Furthermore, ectopic expression of a Joinvillea PI(L) homodimer in Arabidopsis can homeotically transform sepals into petals. Our results provide a window into the evolutionary remodeling of PPIs, and show that novel interactions have the potential to alter plant form in a context-dependent manner. PMID:26908583

  16. Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer

    OpenAIRE

    H Billur Engin; Emre Guney; Ozlem Keskin; Baldo Oliva; Attila Gursoy

    2013-01-01

    Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer H. Billur Engin1, Emre Guney2, Ozlem Keskin1, Baldo Oliva2, Attila Gursoy1* 1 Center for Computational Biology and Bioinformatics and College of Engineering, Koc University, Istanbul, Turkey, 2 Structural Bioinformatics Group (GRIB), Universitat Pompeu Fabra Abstract Blocking specific protein interactions can lead to human diseases. Accordingly, protein i...

  17. ModuleRole: A Tool for Modulization, Role Determination and Visualization in Protein-Protein Interaction Networks

    OpenAIRE

    Guipeng Li; Ming Li; Yiwei Zhang; Dong Wang; Rong Li; Roger Guimerà; Juntao Tony Gao; Zhang, Michael Q

    2014-01-01

    Rapidly increasing amounts of (physical and genetic) protein-protein interaction (PPI) data are produced by various high-throughput techniques, and interpretation of these data remains a major challenge. In order to gain insight into the organization and structure of the resultant large complex networks formed by interacting molecules, using simulated annealing, a method based on the node connectivity, we developed ModuleRole, a user-friendly web server tool which finds modules in PPI network...

  18. Integrating structure to protein-protein interaction networks that drive metastasis to brain and lung in breast cancer

    OpenAIRE

    Engin, H Billur; G??ney, Emre, 1983-; Keskin, Ozlem; Oliva Miguel, Baldomero; Gursoy, Attila

    2013-01-01

    Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer H. Billur Engin1, Emre Guney2, Ozlem Keskin1, Baldo Oliva2, Attila Gursoy1* 1 Center for Computational Biology and Bioinformatics and College of Engineering, Koc University, Istanbul, Turkey, 2 Structural Bioinformatics Group (GRIB), Universitat Pompeu Fabra Abstract Blocking specific protein interactions can lead to human diseases. Accordingly, protein i...

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

    Science.gov (United States)

    He, Yi-Ming; Ma, Bin-Guang

    2016-05-01

    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.

  20. InterMitoBase: An annotated database and analysis platform of protein-protein interactions for human mitochondria

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    Zhang Chenyu

    2011-06-01

    Full Text Available Abstract Background The mitochondrion is an essential organelle which plays important roles in diverse biological processes, such as metabolism, apoptosis, signal transduction and cell cycle. Characterizing protein-protein interactions (PPIs that execute mitochondrial functions is fundamental in understanding the mechanisms underlying biological functions and diseases associated with mitochondria. Investigations examining mitochondria are expanding to the system level because of the accumulation of mitochondrial proteomes and human interactome. Consequently, the development of a database that provides the entire protein interaction map of the human mitochondrion is urgently required. Results InterMitoBase provides a comprehensive interactome of human mitochondria. It contains the PPIs in biological pathways mediated by mitochondrial proteins, the PPIs between mitochondrial proteins and non-mitochondrial proteins as well as the PPIs between mitochondrial proteins. The current version of InterMitoBase covers 5,883 non-redundant PPIs of 2,813 proteins integrated from a wide range of resources including PubMed, KEGG, BioGRID, HPRD, DIP and IntAct. Comprehensive curations have been made on the interactions derived from PubMed. All the interactions in InterMitoBase are annotated according to the information collected from their original sources, GenBank and GO. Additionally, InterMitoBase features a user-friendly graphic visualization platform to present functional and topological analysis of PPI networks identified. This should aid researchers in the study of underlying biological properties. Conclusions InterMitoBase is designed as an integrated PPI database which provides the most up-to-date PPI information for human mitochondria. It also works as a platform by integrating several on-line tools for the PPI analysis. As an analysis platform and as a PPI database, InterMitoBase will be an important database for the study of mitochondria biochemistry

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

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    Hao Wu

    Full Text Available 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.

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

    Science.gov (United States)

    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. PMID:24642838

  3. A comprehensive benchmark of kernel methods to extract protein-protein interactions from literature.

    Directory of Open Access Journals (Sweden)

    Domonkos Tikk

    Full Text Available The most important way of conveying new findings in biomedical research is scientific publication. Extraction of protein-protein interactions (PPIs reported in scientific publications is one of the core topics of text mining in the life sciences. Recently, a new class of such methods has been proposed - convolution kernels that identify PPIs using deep parses of sentences. However, comparing published results of different PPI extraction methods is impossible due to the use of different evaluation corpora, different evaluation metrics, different tuning procedures, etc. In this paper, we study whether the reported performance metrics are robust across different corpora and learning settings and whether the use of deep parsing actually leads to an increase in extraction quality. Our ultimate goal is to identify the one method that performs best in real-life scenarios, where information extraction is performed on unseen text and not on specifically prepared evaluation data. We performed a comprehensive benchmarking of nine different methods for PPI extraction that use convolution kernels on rich linguistic information. Methods were evaluated on five different public corpora using cross-validation, cross-learning, and cross-corpus evaluation. Our study confirms that kernels using dependency trees generally outperform kernels based on syntax trees. However, our study also shows that only the best kernel methods can compete with a simple rule-based approach when the evaluation prevents information leakage between training and test corpora. Our results further reveal that the F-score of many approaches drops significantly if no corpus-specific parameter optimization is applied and that methods reaching a good AUC score often perform much worse in terms of F-score. We conclude that for most kernels no sensible estimation of PPI extraction performance on new text is possible, given the current heterogeneity in evaluation data. Nevertheless, our study

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

    Science.gov (United States)

    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

  5. Prediction of protein motions from amino acid sequence and its application to protein-protein interaction

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    Wako Hiroshi

    2010-07-01

    Full Text Available Abstract Background Structural flexibility is an important characteristic of proteins because it is often associated with their function. The movement of a polypeptide segment in a protein can be broken down into two types of motions: internal and external ones. The former is deformation of the segment itself, but the latter involves only rotational and translational motions as a rigid body. Normal Model Analysis (NMA can derive these two motions, but its application remains limited because it necessitates the gathering of complete structural information. Results In this work, we present a novel method for predicting two kinds of protein motions in ordered structures. The prediction uses only information from the amino acid sequence. We prepared a dataset of the internal and external motions of segments in many proteins by application of NMA. Subsequently, we analyzed the relation between thermal motion assessed from X-ray crystallographic B-factor and internal/external motions calculated by NMA. Results show that attributes of amino acids related to the internal motion have different features from those related to the B-factors, although those related to the external motion are correlated strongly with the B-factors. Next, we developed a method to predict internal and external motions from amino acid sequences based on the Random Forest algorithm. The proposed method uses information associated with adjacent amino acid residues and secondary structures predicted from the amino acid sequence. The proposed method exhibited moderate correlation between predicted internal and external motions with those calculated by NMA. It has the highest prediction accuracy compared to a naïve model and three published predictors. Conclusions Finally, we applied the proposed method predicting the internal motion to a set of 20 proteins that undergo large conformational change upon protein-protein interaction. Results show significant overlaps between the

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

    Science.gov (United States)

    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

    2016-01-01

    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. PMID:27447450

  7. An approach to improve kernel-based Protein-Protein Interaction extraction by learning from large-scale network data.

    Science.gov (United States)

    Li, Lishuang; Guo, Rui; Jiang, Zhenchao; Huang, Degen

    2015-07-15

    Protein-Protein Interaction extraction (PPIe) from biomedical literatures is an important task in biomedical text mining and has achieved desirable results on the annotated datasets. However, the traditional machine learning methods on PPIe suffer badly from vocabulary gap and data sparseness, which weakens classification performance. In this work, an approach capturing external information from the web-based data is introduced to address these problems and boost the existing methods. The approach involves three kinds of word representation techniques: distributed representation, vector clustering and Brown clusters. Experimental results show that our method outperforms the state-of-the-art methods on five publicly available corpora. Our code and data are available at: http://chaoslog.com/improving-kernel-based-protein-protein-interaction-extraction-by-unsupervised-word-representation-codes-and-data.html. PMID:25864936

  8. Using the theory of coevolution to predict protein-protein interactions in non-small cell lung cancer

    OpenAIRE

    Meng Zhang; Man-Him Chan; Wen-Jian Tu; Li-Ran He; Chak-Man Lee; Miao He

    2013-01-01

    Systems biology has become an effective approach for understanding the molecular mechanisms underlying the development of lung cancer. In this study, sequences of 100 non-small cell lung cancer (NSCLC)-related proteins were downloaded from the National Center for Biotechnology Information (NCBI) databases. The Theory of Coevolution was then used to build a protein-protein interaction (PPI) network of NSCLC. Adopting the reverse thinking approach, we analyzed the NSCLC proteins one at a time. ...

  9. A new essential protein discovery method based on the integration of protein-protein interaction and gene expression data

    Directory of Open Access Journals (Sweden)

    Li Min

    2012-03-01

    Full Text Available Abstract Background Identification of essential proteins is always a challenging task since it requires experimental approaches that are time-consuming and laborious. With the advances in high throughput technologies, a large number of protein-protein interactions are available, which have produced unprecedented opportunities for detecting proteins' essentialities from the network level. There have been a series of computational approaches proposed for predicting essential proteins based on network topologies. However, the network topology-based centrality measures are very sensitive to the robustness of network. Therefore, a new robust essential protein discovery method would be of great value. Results In this paper, we propose a new centrality measure, named PeC, based on the integration of protein-protein interaction and gene expression data. The performance of PeC is validated based on the protein-protein interaction network of Saccharomyces cerevisiae. The experimental results show that the predicted precision of PeC clearly exceeds that of the other fifteen previously proposed centrality measures: Degree Centrality (DC, Betweenness Centrality (BC, Closeness Centrality (CC, Subgraph Centrality (SC, Eigenvector Centrality (EC, Information Centrality (IC, Bottle Neck (BN, Density of Maximum Neighborhood Component (DMNC, Local Average Connectivity-based method (LAC, Sum of ECC (SoECC, Range-Limited Centrality (RL, L-index (LI, Leader Rank (LR, Normalized α-Centrality (NC, and Moduland-Centrality (MC. Especially, the improvement of PeC over the classic centrality measures (BC, CC, SC, EC, and BN is more than 50% when predicting no more than 500 proteins. Conclusions We demonstrate that the integration of protein-protein interaction network and gene expression data can help improve the precision of predicting essential proteins. The new centrality measure, PeC, is an effective essential protein discovery method.

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

    OpenAIRE

    Yi-Ming He; Bin-Guang Ma

    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 thermophil...

  11. Discovery of a Potent Inhibitor of Replication Protein A Protein-Protein Interactions Using a Fragment Linking Approach

    OpenAIRE

    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.

    2013-01-01

    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 sensitize cancer cells to DNA-damaging agents without affecting other functions of RPA. To discover a potent, selective...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Lai, Hsien-Tsung; Chiang, Cheng-Ming

    2016-01-01

    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

  14. Identification of Candidate Genes related to Bovine Marbling using Protein-Protein Interaction Networks

    OpenAIRE

    Lim, Dajeong; Kim, Nam-Kuk; Park, Hye-Sun; Lee, Seung-Hwan; Cho, Yong-Min; Oh, Sung Jong; Kim, Tae-Hun; Kim, Heebal

    2011-01-01

    Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The present study systemically analyzed genes associated with bovine marbling score and identified their relationships. The candidate nodes were obtained using MedScan text-mining tools and linked by protein-protein intera...

  15. Tuning protein-protein interactions using cosolvents: specific effects of ionic and non-ionic additives on protein phase behavior.

    Science.gov (United States)

    Hansen, Jan; Platten, Florian; Wagner, Dana; Egelhaaf, Stefan U

    2016-04-21

    Cosolvents are routinely used to modulate the (thermal) stability of proteins and, hence, their interactions with proteins have been studied intensely. However, less is known about their specific effects on protein-protein interactions, which we characterize in terms of the protein phase behavior. We analyze the phase behavior of lysozyme solutions in the presence of sodium chloride (NaCl), guanidine hydrochloride (GuHCl), glycerol, and dimethyl sulfoxide (DMSO). We experimentally determined the crystallization boundary (XB) and, in combination with data on the cloud-point temperatures (CPTs), the crystallization gap. In agreement with other studies, our data indicate that the additives might affect the protein phase behavior through electrostatic screening and additive-specific contributions. At high salt concentrations, where electrostatic interactions are screened, both the CPT and the XB are found to be linear functions of the additive concentration. Their slopes quantify the additive-specific changes of the phase behavior and thus of the protein-protein interactions. While the specific effect of NaCl is to induce attractions between proteins, DMSO, glycerol and GuHCl (with increasing strength) weaken attractions and/or induce repulsions. Except for DMSO, changes of the CPT are stronger than those of the XB. Furthermore, the crystallization gap widens in the case of GuHCl and glycerol and narrows in the case of NaCl. We relate these changes to colloidal interaction models, namely square-well and patchy interactions. PMID:27020538

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

    Directory of Open Access Journals (Sweden)

    Jessica B Hostetler

    2015-12-01

    Full Text Available 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.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 suggesting that the proteins

  17. Vectors for multi-color bimolecular fluorescence complementation to investigate protein-protein interactions in living plant cells

    Directory of Open Access Journals (Sweden)

    Kuang Lin-Yun

    2008-10-01

    Full Text Available Abstract Background The investigation of protein-protein interactions is important for characterizing protein function. Bimolecular fluorescence complementation (BiFC has recently gained interest as a relatively easy and inexpensive method to visualize protein-protein interactions in living cells. BiFC uses "split YFP" tags on proteins to detect interactions: If the tagged proteins interact, they may bring the two split fluorophore components together such that they can fold and reconstitute fluorescence. The sites of interaction can be monitored using epifluorescence or confocal microscopy. However, "conventional" BiFC can investigate interactions only between two proteins at a time. There are instances when one may wish to offer a particular "bait" protein to several "prey" proteins simultaneously. Preferential interaction of the bait protein with one of the prey proteins, or different sites of interaction between the bait protein and multiple prey proteins, may thus be observed. Results We have constructed a series of gene expression vectors, based upon the pSAT series of vectors, to facilitate the practice of multi-color BiFC. The bait protein is tagged with the C-terminal portion of CFP (cCFP, and prey proteins are tagged with the N-terminal portions of either Venus (nVenus or Cerulean (nCerulean. Interaction of cCFP-tagged proteins with nVenus-tagged proteins generates yellow fluorescence, whereas interaction of cCFP-tagged proteins with nCerulean-tagged proteins generates blue fluorescence. Additional expression of mCherry indicates transfected cells and sub-cellular structures. Using this system, we have determined in both tobacco BY-2 protoplasts and in onion epidermal cells that Agrobacterium VirE2 protein interacts with the Arabidopsis nuclear transport adapter protein importin α-1 in the cytoplasm, whereas interaction of VirE2 with a different importin α isoform, importin α-4, occurs predominantly in the nucleus. Conclusion Multi

  18. Toward a rigorous network of protein-protein interactions of the model sulfate reducer Desulfovibrio vulgaris Hildenborough

    Energy Technology Data Exchange (ETDEWEB)

    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.

  19. Investigating the importance of Delaunay-based definition of atomic interactions in scoring of protein-protein docking results.

    Science.gov (United States)

    Jafari, Rahim; Sadeghi, Mehdi; Mirzaie, Mehdi

    2016-05-01

    The approaches taken to represent and describe structural features of the macromolecules are of major importance when developing computational methods for studying and predicting their structures and interactions. This study attempts to explore the significance of Delaunay tessellation for the definition of atomic interactions by evaluating its impact on the performance of scoring protein-protein docking prediction. Two sets of knowledge-based scoring potentials are extracted from a training dataset of native protein-protein complexes. The potential of the first set is derived using atomic interactions extracted from Delaunay tessellated structures. The potential of the second set is calculated conventionally, that is, using atom pairs whose interactions were determined by their separation distances. The scoring potentials were tested against two different docking decoy sets and their performances were compared. The results show that, if properly optimized, the Delaunay-based scoring potentials can achieve higher success rate than the usual scoring potentials. These results and the results of a previous study on the use of Delaunay-based potentials in protein fold recognition, all point to the fact that Delaunay tessellation of protein structure can provide a more realistic definition of atomic interaction, and therefore, if appropriately utilized, may be able to improve the accuracy of pair potentials. PMID:27060891

  20. Conformational Selection in a Protein-Protein Interaction Revealed by Dynamic Pathway Analysis

    Directory of Open Access Journals (Sweden)

    Kalyan S. Chakrabarti

    2016-01-01

    Full Text Available 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 nuclear magnetic resonance (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. Protein dynamics in free recoverin limits the overall rate of binding.

  1. Conformational Selection in a Protein-Protein Interaction Revealed by Dynamic Pathway Analysis.

    Science.gov (United States)

    Chakrabarti, Kalyan S; Agafonov, Roman V; Pontiggia, Francesco; Otten, Renee; Higgins, Matthew K; Schertler, Gebhard F X; Oprian, Daniel D; Kern, Dorothee

    2016-01-01

    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 nuclear magnetic resonance (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. Protein dynamics in free recoverin limits the overall rate of binding. PMID:26725117

  2. Structural deformation upon protein-protein interaction: A structural alphabet approach

    Directory of Open Access Journals (Sweden)

    Lecornet Hélène

    2008-02-01

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

  3. GRIP: A web-based system for constructing Gold Standard datasets for protein-protein interaction prediction

    Directory of Open Access Journals (Sweden)

    Zheng Huiru

    2009-01-01

    Full Text Available Abstract Background Information about protein interaction networks is fundamental to understanding protein function and cellular processes. Interaction patterns among proteins can suggest new drug targets and aid in the design of new therapeutic interventions. Efforts have been made to map interactions on a proteomic-wide scale using both experimental and computational techniques. Reference datasets that contain known interacting proteins (positive cases and non-interacting proteins (negative cases are essential to support computational prediction and validation of protein-protein interactions. Information on known interacting and non interacting proteins are usually stored within databases. Extraction of these data can be both complex and time consuming. Although, the automatic construction of reference datasets for classification is a useful resource for researchers no public resource currently exists to perform this task. Results GRIP (Gold Reference dataset constructor from Information on Protein complexes is a web-based system that provides researchers with the functionality to create reference datasets for protein-protein interaction prediction in Saccharomyces cerevisiae. Both positive and negative cases for a reference dataset can be extracted, organised and downloaded by the user. GRIP also provides an upload facility whereby users can submit proteins to determine protein complex membership. A search facility is provided where a user can search for protein complex information in Saccharomyces cerevisiae. Conclusion GRIP is developed to retrieve information on protein complex, cellular localisation, and physical and genetic interactions in Saccharomyces cerevisiae. Manual construction of reference datasets can be a time consuming process requiring programming knowledge. GRIP simplifies and speeds up this process by allowing users to automatically construct reference datasets. GRIP is free to access at http://rosalind.infj.ulst.ac.uk/GRIP/.

  4. Prediction of protein-protein interactions in dengue virus coat proteins guided by low resolution cryoEM structures

    Directory of Open Access Journals (Sweden)

    Srinivasan Narayanaswamy

    2010-06-01

    Full Text Available Abstract 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.

  5. In vivo characterization of protein-protein interactions in the AP1 system with fluorescence correlation spectroscopy (FCS).

    OpenAIRE

    Baudendistel, Nina; Knoch, Tobias; Müller, Gabriele; Wachsmuth, Malte; Weidemann, Thomas; Waldeck, Waldemar; Langowski, Jörg

    2002-01-01

    textabstractThe aim of these studies is the quantitative investigation of protein-protein interactions in the AP1 system in vivo. First results of FCS measurements show an exchange in the nucleus of the proteins Fos-CFP and Jun-YFP in the stably mono-transfected HeLa-Cells. This is also shown by fitting the bleaching curves measured in the nucleus with an appropriate model. We obtained dissociation times between 10 and 20 seconds in the nucleus. In the autocorrelation function a free and an o...

  6. A bacterial two-hybrid system that utilizes Gateway cloning for rapid screening of protein-protein interactions.

    Science.gov (United States)

    Karna, S L Rajasekhar; Zogaj, Xhavit; Barker, Jeffrey R; Seshu, Janakiram; Dove, Simon L; Klose, Karl E

    2010-11-01

    Comprehensive clone sets representing the entire genome now exist for a large number of organisms. The Gateway entry clone sets are a particularly useful means to study gene function, given the ease of introduction into any Gateway-suitable destination vector. We have adapted a bacterial two-hybrid system for use with Gateway entry clone sets, such that potential interactions between proteins encoded within these clone sets can be determined by new destination vectors. We show that utilizing the Gateway clone sets for Francisella tularensis and Vibrio cholerae, known interactions between F. tularensis IglA and IglB and V. cholerae VipA and VipB could be confirmed with these destination vectors. Moreover, the introduction of unique tags into each vector allowed for visualization of the expressed hybrid proteins via Western immunoblot. This Gateway-suitable bacterial two-hybrid system provides a new tool for rapid screening of protein-protein interactions. PMID:21091448

  7. Engineering of soybean mosaic virus as a versatile tool for studying protein-protein interactions in soybean.

    Science.gov (United States)

    Seo, Jang-Kyun; Choi, Hong-Soo; Kim, Kook-Hyung

    2016-01-01

    Transient gene expression approaches are valuable tools for rapid introduction of genes of interest and characterization of their functions in plants. Although agroinfiltration is the most effectively and routinely used method for transient expression of multiple genes in various plant species, this approach has been largely unsuccessful in soybean. In this study, we engineered soybean mosaic virus (SMV) as a dual-gene delivery vector to simultaneously deliver and express two genes in soybean cells. We further show the application of the SMV-based dual vector for a bimolecular fluorescence complementation assay to visualize in vivo protein-protein interactions in soybean and for a co-immunoprecipitation assay to identify cellular proteins interacting with SMV helper component protease. This approach provides a rapid and cost-effective tool for transient introduction of multiple traits into soybean and for in vivo characterization of the soybean cellular protein interaction network. PMID:26926710

  8. Sample Preparation for Mass Spectrometry Analysis of Protein-Protein Interactions in Cancer Cell Lines and Tissues.

    Science.gov (United States)

    Beigbeder, Alice; Vélot, Lauriane; James, D Andrew; Bisson, Nicolas

    2016-01-01

    A precisely controlled network of protein-protein interactions constitutes the basis for functional signaling pathways. This equilibrium is more often than not disrupted in cancer cells, by the aberrant expression or activation of oncogenic proteins. Therefore, the analysis of protein interaction networks in cancer cells has become crucial to expand our comprehension of the molecular underpinnings of tumor formation and progression. This protocol describes a sample preparation method for the analysis of signaling complexes by mass spectrometry (MS), following the affinity purification of a protein of interest from a cancer cell line or a solid tumor. In particular, we provide a spin tip-based protease digestion procedure that offers a more rapid and controlled alternative to other gel-based and gel-free methods. This sample preparation protocol represents a useful strategy to identify protein interactions and to gain insight into the molecular mechanisms that contribute to a given cancer phenotype. PMID:27581032

  9. Arabidopsis mRNA polyadenylation machinery: comprehensive analysis of protein-protein interactions and gene expression profiling

    Directory of Open Access Journals (Sweden)

    Mo Min

    2008-05-01

    Full Text Available Abstract Background The polyadenylation of mRNA is one of the critical processing steps during expression of almost all eukaryotic genes. It is tightly integrated with transcription, particularly its termination, as well as other RNA processing events, i.e. capping and splicing. The poly(A tail protects the mRNA from unregulated degradation, and it is required for nuclear export and translation initiation. In recent years, it has been demonstrated that the polyadenylation process is also involved in the regulation of gene expression. The polyadenylation process requires two components, the cis-elements on the mRNA and a group of protein factors that recognize the cis-elements and produce the poly(A tail. Here we report a comprehensive pairwise protein-protein interaction mapping and gene expression profiling of the mRNA polyadenylation protein machinery in Arabidopsis. Results By protein sequence homology search using human and yeast polyadenylation factors, we identified 28 proteins that may be components of Arabidopsis polyadenylation machinery. To elucidate the protein network and their functions, we first tested their protein-protein interaction profiles. Out of 320 pair-wise protein-protein interaction assays done using the yeast two-hybrid system, 56 (~17% showed positive interactions. 15 of these interactions were further tested, and all were confirmed by co-immunoprecipitation and/or in vitro co-purification. These interactions organize into three distinct hubs involving the Arabidopsis polyadenylation factors. These hubs are centered around AtCPSF100, AtCLPS, and AtFIPS. The first two are similar to complexes seen in mammals, while the third one stands out as unique to plants. When comparing the gene expression profiles extracted from publicly available microarray datasets, some of the polyadenylation related genes showed tissue-specific expression, suggestive of potential different polyadenylation complex configurations. Conclusion An

  10. Topological and organizational properties of the products of house-keeping and tissue-specific genes in protein-protein interaction networks

    OpenAIRE

    Liu Wei-chung; Lin Wen-hsien; Hwang Ming-jing

    2009-01-01

    Abstract Background Human cells of various tissue types differ greatly in morphology despite having the same set of genetic information. Some genes are expressed in all cell types to perform house-keeping functions, while some are selectively expressed to perform tissue-specific functions. In this study, we wished to elucidate how proteins encoded by human house-keeping genes and tissue-specific genes are organized in human protein-protein interaction networks. We constructed protein-protein ...

  11. AraPPISite: a database of fine-grained protein-protein interaction site annotations for Arabidopsis thaliana.

    Science.gov (United States)

    Li, Hong; Yang, Shiping; Wang, Chuan; Zhou, Yuan; Zhang, Ziding

    2016-09-01

    Knowledge about protein interaction sites provides detailed information of protein-protein interactions (PPIs). To date, nearly 20,000 of PPIs from Arabidopsis thaliana have been identified. Nevertheless, the interaction site information has been largely missed by previously published PPI databases. Here, AraPPISite, a database that presents fine-grained interaction details for A. thaliana PPIs is established. First, the experimentally determined 3D structures of 27 A. thaliana PPIs are collected from the Protein Data Bank database and the predicted 3D structures of 3023 A. thaliana PPIs are modeled by using two well-established template-based docking methods. For each experimental/predicted complex structure, AraPPISite not only provides an interactive user interface for browsing interaction sites, but also lists detailed evolutionary and physicochemical properties of these sites. Second, AraPPISite assigns domain-domain interactions or domain-motif interactions to 4286 PPIs whose 3D structures cannot be modeled. In this case, users can easily query protein interaction regions at the sequence level. AraPPISite is a free and user-friendly database, which does not require user registration or any configuration on local machines. We anticipate AraPPISite can serve as a helpful database resource for the users with less experience in structural biology or protein bioinformatics to probe the details of PPIs, and thus accelerate the studies of plant genetics and functional genomics. AraPPISite is available at http://systbio.cau.edu.cn/arappisite/index.html . PMID:27338257

  12. Binding specificity and in vivo targets of the EH domain, a novel protein-protein interaction module

    DEFF Research Database (Denmark)

    Salcini, A E; Confalonieri, S; Doria, M;

    1997-01-01

    EH is a recently identified protein-protein interaction domain found in the signal transducers Eps15 and Eps15R and several other proteins of yeast nematode. We show that EH domains from Eps15 and Eps15R bind in vitro to peptides containing an asparagine-proline-phenylalanine (NPF) motif. Direct...... screening of expression libraries with EH domains yielded a number of putative EH interactors, all of which possessed NPF motifs that were shown to be responsible for the interaction. Among these interactors were the human homolog of NUMB, a developmentally reguated gene of Drosophila, and RAB, the cellular...... cofactor of the HIV REV protein. We demonstrated coimmunoprecipitation of Eps15 with NUMB and RAB. Finally, in vitro binding of NPF-containing peptides to cellular proteins and EST database screening established the existence of a family of EH-containing proteins in mammals. Based on the characteristics of...

  13. A quantitative approach to analyzing genome reductive evolution using protein-protein interaction networks: A case study ofMycobacterium leprae

    Directory of Open Access Journals (Sweden)

    Richard O Akinola

    2016-03-01

    Full Text Available The advance in high-throughput sequencing technologies has yielded complete genome sequences of several organisms, including complete bacterial genomes. The growing number of these available sequenced genomes has enabled analyses of their dynamics, as well as the molecular and evolutionary processes which these organisms are under. Comparative genomics of different bacterial genomes have highlighted their genome size and gene content in association with lifestyles and adaptation to various environments and have contributed to enhancing our understanding of the mechanisms of their evolution. Protein-protein functional interactions mediate many essential processes for maintaining the stability of the biological systems under changing environmental conditions. Thus, these interactions play crucial roles in the evolutionary processes of different organisms, especially for obligate intracellular bacteria, proven to generally have reduced genome sizes compared to their nearest free-living relatives. In this study, we used the approach based on the Renormalization Group (RG analysis technique and the Maximum-Excluded-Mass-Burning (MEMB model to investigate the evolutionary process of genome reduction in relation to the organization of functional networks of two organisms. Using a Mycobacterium leprae (MLP network in comparison with a Mycobacterium tuberculosis (MTB network as a case study, we show that reductive evolution in MLP was as a result of removal of important proteins from neighbours of corresponding orthologous MTB proteins. While each orthologous MTB protein had an increase in number of interacting partners in most instances, the corresponding MLP protein had lost some of them. This work provides a quantitative model for mapping reductive evolution and protein-protein functional interaction network organization in terms of roles played by different proteins in the network structure.

  14. Cell-free Protein Synthesis in an Autoinduction System for NMR Studies of Protein-Protein Interactions

    International Nuclear Information System (INIS)

    Cell-free protein synthesis systems provide facile access to proteins in a nascent state that enables formation of soluble, native protein-protein complexes even if one of the protein components is prone to self-aggregation and precipitation. Combined with selective isotope-labeling, this allows the rapid analysis of protein-protein interactions with few 15N-HSQC spectra. The concept is demonstrated with binary and ternary complexes between the χ, ψ and γ subunits of Escherichia coli DNA polymerase III: nascent, selectively 15N-labeled ψ produced in the presence of χ resulted in a soluble, correctly folded χ-ψ complex, whereas ψ alone precipitated irrespective of whether γ was present or not. The 15N-HSQC spectra showed that the N-terminal segment of ψ is mobile in the χ-ψ complex, yet important for its binding to γ. The sample preparation was greatly enhanced by an autoinduction strategy, where the T7 RNA polymerase needed for transcription of a gene in a T7-promoter vector was produced in situ

  15. Discovering Protein-Protein Interactions within the Programmed Cell Death Network Using a Protein-Fragment Complementation Screen

    Directory of Open Access Journals (Sweden)

    Yuval Gilad

    2014-08-01

    Full Text Available Apoptosis and autophagy are distinct biological processes, each driven by a different set of protein-protein interactions, with significant crosstalk via direct interactions among apoptotic and autophagic proteins. To measure the global profile of these interactions, we adapted the Gaussia luciferase protein-fragment complementation assay (GLuc PCA, which monitors binding between proteins fused to complementary fragments of a luciferase reporter. A library encompassing 63 apoptotic and autophagic proteins was constructed for the analysis of ∼3,600 protein-pair combinations. This generated a detailed landscape of the apoptotic and autophagic modules and points of interface between them, identifying 46 previously unknown interactions. One of these interactions, between DAPK2, a Ser/Thr kinase that promotes autophagy, and 14-3-3τ, was further investigated. We mapped the region responsible for 14-3-3τ binding and proved that this interaction inhibits DAPK2 dimerization and activity. This proof of concept underscores the power of the GLuc PCA platform for the discovery of biochemical pathways within the cell death network.

  16. Bimolecular Fluorescence Complementation (BiFC) Analysis of Protein-Protein Interactions and Assessment of Subcellular Localization in Live Cells.

    Science.gov (United States)

    Pratt, Evan P S; Owens, Jake L; Hockerman, Gregory H; Hu, Chang-Deng

    2016-01-01

    Bimolecular fluorescence complementation (BiFC) is a fluorescence imaging technique used to visualize protein-protein interactions (PPIs) in live cells and animals. One unique application of BiFC is to reveal subcellular localization of PPIs. The superior signal-to-noise ratio of BiFC in comparison with fluorescence resonance energy transfer or bioluminescence resonance energy transfer enables its wide applications. Here, we describe how confocal microscopy can be used to detect and quantify PPIs and their subcellular localization. We use basic leucine zipper transcription factor proteins as an example to provide a step-by-step BiFC protocol using a Nikon A1 confocal microscope and NIS-Elements imaging software. The protocol given below can be readily adapted for use with other confocal microscopes or imaging software. PMID:27515079

  17. Changes in flexibility upon binding: Application of the self-consistent pair contact probability method to protein-protein interactions

    Science.gov (United States)

    Canino, Lawrence S.; Shen, Tongye; McCammon, J. Andrew

    2002-12-01

    We extend the self-consistent pair contact probability method to the evaluation of the partition function for a protein complex at thermodynamic equilibrium. Specifically, we adapt the method for multichain models and introduce a parametrization for amino acid-specific pairwise interactions. This method is similar to the Gaussian network model but allows for the adjusting of the strengths of native state contacts. The method is first validated on a high resolution x-ray crystal structure of bovine Pancreatic Phospholipase A2 by comparing calculated B-factors with reported values. We then examine binding-induced changes in flexibility in protein-protein complexes, comparing computed results with those obtained from x-ray crystal structures and molecular dynamics simulations. In particular, we focus on the mouse acetylcholinesterase:fasciculin II and the human α-thrombin:thrombomodulin complexes.

  18. A split horseradish peroxidase for the detection of intercellular protein-protein interactions and sensitive visualization of synapses.

    Science.gov (United States)

    Martell, Jeffrey D; Yamagata, Masahito; Deerinck, Thomas J; Phan, Sébastien; Kwa, Carolyn G; Ellisman, Mark H; Sanes, Joshua R; Ting, Alice Y

    2016-07-01

    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 techniques have insufficient sensitivity and/or specificity. Here we report a split horseradish peroxidase (sHRP) as a sensitive and specific tool for the 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 cleft, 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 to studying mechanisms of communication between a variety of cell types. PMID:27240195

  19. The TRPC2 channel forms protein-protein interactions with Homer and RTP in the rat vomeronasal organ

    Directory of Open Access Journals (Sweden)

    Brann Jessica H

    2010-05-01

    Full Text Available Abstract Background The signal transduction cascade operational in the vomeronasal organ (VNO of the olfactory system detects odorants important for prey localization, mating, and social recognition. While the protein machinery transducing these external cues has been individually well characterized, little attention has been paid to the role of protein-protein interactions among these molecules. Development of an in vitro expression system for the transient receptor potential 2 channel (TRPC2, which establishes the first electrical signal in the pheromone transduction pathway, led to the discovery of two protein partners that couple with the channel in the native VNO. Results Homer family proteins were expressed in both male and female adult VNO, particularly Homer 1b/c and Homer 3. In addition to this family of scaffolding proteins, the chaperones receptor transporting protein 1 (RTP1 and receptor expression enhancing protein 1 (REEP1 were also expressed. RTP1 was localized broadly across the VNO sensory epithelium, goblet cells, and the soft palate. Both Homer and RTP1 formed protein-protein interactions with TRPC2 in native reciprocal pull-down assays and RTP1 increased surface expression of TRPC2 in in vitro assays. The RTP1-dependent TRPC2 surface expression was paralleled with an increase in ATP-stimulated whole-cell current in an in vitro patch-clamp electrophysiological assay. Conclusions TRPC2 expression and channel activity is regulated by chaperone- and scaffolding-associated proteins, which could modulate the transduction of chemosignals. The developed in vitro expression system, as described here, will be advantageous for detailed investigations into TRPC2 channel activity and cell signalling, for a channel protein that was traditionally difficult to physiologically assess.

  20. Prediction of Protein-Protein Interaction Sites Based on Naive Bayes Classifier

    OpenAIRE

    Haijiang Geng; Tao Lu; Xiao Lin; Yu Liu; Fangrong Yan

    2015-01-01

    Protein functions through interactions with other proteins and biomolecules and these interactions occur on the so-called interface residues of the protein sequences. Identifying interface residues makes us better understand the biological mechanism of protein interaction. Meanwhile, information about the interface residues contributes to the understanding of metabolic, signal transduction networks and indicates directions in drug designing. In recent years, researchers have focused on develo...

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

    OpenAIRE

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

    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 ...

  2. Improved silicon nanowire field-effect transistors for fast protein-protein interaction screening.

    Science.gov (United States)

    Lin, Ti-Yu; Li, Bor-Ran; Tsai, Sheng-Ta; Chen, Chien-Wei; Chen, Chung-Hsuan; Chen, Yit-Tsong; Pan, Chien-Yuan

    2013-02-21

    Understanding how proteins interact with each other is the basis for studying the biological mechanisms behind various physiological activities. Silicon nanowire field-effect transistors (SiNW-FETs) are sensitive sensors used to detect biomolecular interactions in real-time. However, the majority of the applications that use SiNW-FETs are for known interactions between different molecules. To explore the capability of SiNW-FETs as fast screening devices to identify unknown interacting molecules, we applied mass spectrometry (MS) to analyze molecules reversibly bound to the SiNW-FETs. Calmodulin (CaM) is a Ca(2+)-sensing protein that is ubiquitously expressed in cells and its interaction with target molecules is Ca(2+)-dependent. By modifying the SiNW-FET surface with glutathione, glutathione S-transferase (GST)-tagged CaM binds reversibly to the SiNW-FET. We first verified the Ca(2+)-dependent interaction between GST-CaM and purified troponin I, which is involved in muscle contraction, through the conductance changes of the SiNW-FET. Furthermore, the cell lysate containing overexpressed Ca(2+)/CaM-dependent protein kinase IIα induced a conductance change in the GST-CaM-modified SiNW-FET. The bound proteins were eluted and subsequently identified by MS as CaM and kinase. In another example, candidate proteins from neuronal cell lysates interacting with calneuron I (CalnI), a CaM-like protein, were captured with a GST-CalnI-modified SiNW-FET. The proteins that interacted with CalnI were eluted and verified by MS. The Ca(2+)-dependent interaction between GST-CalnI and one of the candidates, heat shock protein 70, was re-confirmed via the SiNW-FET measurement. Our results demonstrate the effectiveness of combining MS with SiNW-FETs to quickly screen interacting molecules from cell lysates. PMID:23235921

  3. PreBIND and Textomy – mining the biomedical literature for protein-protein interactions using a support vector machine

    Directory of Open Access Journals (Sweden)

    Baskin Berivan

    2003-03-01

    Full Text Available Abstract Background The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational methods. The Biomolecular interaction network database (BIND seeks to capture these data in a machine-readable format. We hypothesized that the formidable task-size of backfilling the database could be reduced by using Support Vector Machine technology to first locate interaction information in the literature. We present an information extraction system that was designed to locate protein-protein interaction data in the literature and present these data to curators and the public for review and entry into BIND. Results Cross-validation estimated the support vector machine's test-set precision, accuracy and recall for classifying abstracts describing interaction information was 92%, 90% and 92% respectively. We estimated that the system would be able to recall up to 60% of all non-high throughput interactions present in another yeast-protein interaction database. Finally, this system was applied to a real-world curation problem and its use was found to reduce the task duration by 70% thus saving 176 days. Conclusions Machine learning methods are useful as tools to direct interaction and pathway database back-filling; however, this potential can only be realized if these techniques are coupled with human review and entry into a factual database such as BIND. The PreBIND system described here is available to the public at http://bind.ca. Current capabilities allow searching for human, mouse and yeast protein-interaction information.

  4. Detecting Protein-Protein Interactions with a Novel Matrix-Based Protein Sequence Representation and Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Zhu-Hong You

    2015-01-01

    Full Text Available Proteins and their interactions lie at the heart of most underlying biological processes. Consequently, correct detection of protein-protein interactions (PPIs is of fundamental importance to understand the molecular mechanisms in biological systems. Although the convenience brought by high-throughput experiment in technological advances makes it possible to detect a large amount of PPIs, the data generated through these methods is unreliable and may not be completely inclusive of all possible PPIs. Targeting at this problem, this study develops a novel computational approach to effectively detect the protein interactions. This approach is proposed based on a novel matrix-based representation of protein sequence combined with the algorithm of support vector machine (SVM, which fully considers the sequence order and dipeptide information of the protein primary sequence. When performed on yeast PPIs datasets, the proposed method can reach 90.06% prediction accuracy with 94.37% specificity at the sensitivity of 85.74%, indicating that this predictor is a useful tool to predict PPIs. Achieved results also demonstrate that our approach can be a helpful supplement for the interactions that have been detected experimentally.

  5. Large-scale protein-protein interaction analysis in Arabidopsis mesophyll protoplasts by split firefly luciferase complementation.

    Directory of Open Access Journals (Sweden)

    Jian-Feng Li

    Full Text Available Protein-protein interactions (PPIs constitute the regulatory network that coordinates diverse cellular functions. There are growing needs in plant research for creating protein interaction maps behind complex cellular processes and at a systems biology level. However, only a few approaches have been successfully used for large-scale surveys of PPIs in plants, each having advantages and disadvantages. Here we present split firefly luciferase complementation (SFLC as a highly sensitive and noninvasive technique for in planta PPI investigation. In this assay, the separate halves of a firefly luciferase can come into close proximity and transiently restore its catalytic activity only when their fusion partners, namely the two proteins of interest, interact with each other. This assay was conferred with quantitativeness and high throughput potential when the Arabidopsis mesophyll protoplast system and a microplate luminometer were employed for protein expression and luciferase measurement, respectively. Using the SFLC assay, we could monitor the dynamics of rapamycin-induced and ascomycin-disrupted interaction between Arabidopsis FRB and human FKBP proteins in a near real-time manner. As a proof of concept for large-scale PPI survey, we further applied the SFLC assay to testing 132 binary PPIs among 8 auxin response factors (ARFs and 12 Aux/IAA proteins from Arabidopsis. Our results demonstrated that the SFLC assay is ideal for in vivo quantitative PPI analysis in plant cells and is particularly powerful for large-scale binary PPI screens.

  6. No simple dependence between protein evolution rate and the number of protein-protein interactions: only the most prolific interactors tend to evolve slowly

    Directory of Open Access Journals (Sweden)

    Koonin Eugene V

    2003-01-01

    Full Text Available Abstract Background It has been suggested that rates of protein evolution are influenced, to a great extent, by the proportion of amino acid residues that are directly involved in protein function. In agreement with this hypothesis, recent work has shown a negative correlation between evolutionary rates and the number of protein-protein interactions. However, the extent to which the number of protein-protein interactions influences evolutionary rates remains unclear. Here, we address this question at several different levels of evolutionary relatedness. Results Manually curated data on the number of protein-protein interactions among Saccharomyces cerevisiae proteins was examined for possible correlation with evolutionary rates between S. cerevisiae and Schizosaccharomyces pombe orthologs. Only a very weak negative correlation between the number of interactions and evolutionary rate of a protein was observed. Furthermore, no relationship was found between a more general measure of the evolutionary conservation of S. cerevisiae proteins, based on the taxonomic distribution of their homologs, and the number of protein-protein interactions. However, when the proteins from yeast were assorted into discrete bins according to the number of interactions, it turned out that 6.5% of the proteins with the greatest number of interactions evolved, on average, significantly slower than the rest of the proteins. Comparisons were also performed using protein-protein interaction data obtained with high-throughput analysis of Helicobacter pylori proteins. No convincing relationship between the number of protein-protein interactions and evolutionary rates was detected, either for comparisons of orthologs from two completely sequenced H. pylori strains or for comparisons of H. pylori and Campylobacter jejuni orthologs, even when the proteins were classified into bins by the number of interactions. Conclusion The currently available comparative-genomic data do not

  7. Probability-based model of protein-protein interactions on biological timescales

    Directory of Open Access Journals (Sweden)

    Bates Paul A

    2006-12-01

    Full Text Available Abstract Background Simulation methods can assist in describing and understanding complex networks of interacting proteins, providing fresh insights into the function and regulation of biological systems. Recent studies have investigated such processes by explicitly modelling the diffusion and interactions of individual molecules. In these approaches, two entities are considered to have interacted if they come within a set cutoff distance of each other. Results In this study, a new model of bimolecular interactions is presented that uses a simple, probability-based description of the reaction process. This description is well-suited to simulations on timescales relevant to biological systems (from seconds to hours, and provides an alternative to the previous description given by Smoluchowski. In the present approach (TFB the diffusion process is explicitly taken into account in generating the probability that two freely diffusing chemical entities will interact within a given time interval. It is compared to the Smoluchowski method, as modified by Andrews and Bray (AB. Conclusion When implemented, the AB & TFB methods give equivalent results in a variety of situations relevant to biology. Overall, the Smoluchowski method as modified by Andrews and Bray emerges as the most simple, robust and efficient method for simulating biological diffusion-reaction processes currently available.

  8. Kinetic Measurements Reveal Enhanced Protein-Protein Interactions at Intercellular Junctions.

    Science.gov (United States)

    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

  9. A feature-based approach to modeling protein-protein interaction hot spots.

    Science.gov (United States)

    Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

    2009-05-01

    Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions. PMID:19273533

  10. Computational Approaches for Prediction of Pathogen-Host Protein-Protein Interactions

    Directory of Open Access Journals (Sweden)

    Esmaeil eNourani

    2015-02-01

    Full Text Available Infectious diseases are still among the major and prevalent health problems, mostly because of the drug resistance of novel variants of pathogens. Molecular interactions between pathogens and their hosts are the key part of the infection mechanisms. Novel antimicrobial therapeutics to fight drug resistance is only possible in case of a thorough understanding of pathogen-host interaction (PHI systems. Existing databases, which contain experimentally verified PHI data, suffer from scarcity of reported interactions due to the technically challenging and time consuming process of experiments. This has motivated many researchers to address the problem by proposing computational approaches for analysis and prediction of PHIs. The computational methods primarily utilize sequence information, protein structure and known interactions. Classic machine learning techniques are used when there are sufficient known interactions to be used as training data. On the opposite case, transfer and multi task learning methods are preferred. Here, we present an overview of these computational approaches for PHI prediction, discussing their weakness and abilities, with future directions.

  11. Inhibition of CDC25B Phosphatase Through Disruption of Protein-Protein Interaction

    Energy Technology Data Exchange (ETDEWEB)

    Lund, George; Dudkin, Sergii; Borkin, Dmitry; Ni, Wendi; Grembecka, Jolanta; Cierpicki, Tomasz [Michigan

    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.

  12. Stimulation of DNA Glycosylase Activities by XPC Protein Complex: Roles of Protein-Protein Interactions

    Directory of Open Access Journals (Sweden)

    Yuichiro Shimizu

    2010-01-01

    Full Text Available We showed that XPC complex, which is a DNA damage detector for nucleotide excision repair, stimulates activity of thymine DNA glycosylase (TDG that initiates base excision repair. XPC appeared to facilitate the enzymatic turnover of TDG by promoting displacement from its own product abasic site, although the precise mechanism underlying this stimulation has not been clarified. Here we show that XPC has only marginal effects on the activity of E. coli TDG homolog (EcMUG, which remains bound to the abasic site like human TDG but does not significantly interacts with XPC. On the contrary, XPC significantly stimulates the activities of sumoylated TDG and SMUG1, both of which exhibit quite different enzymatic kinetics from unmodified TDG but interact with XPC. These results point to importance of physical interactions for stimulation of DNA glycosylases by XPC and have implications in the molecular mechanisms underlying mutagenesis and carcinogenesis in XP-C patients.

  13. Protein-protein interactions in the plant Golgi apparatus, studied with FRET acceptor photobleaching technique

    DEFF Research Database (Denmark)

    Poulsen, Christian Peter

    The focus of this Ph.D. study has primarily been to utilize and adapt the acceptor photobleaching technique for measuring of Förster resonance energy transfer (FRET) to tudy proteinprotein interactions (PPIs) among glycosyltranseferases (GTs) and nucleotide ugar transporters (NSTs) localized to the...... plant Golgi apparatus and involved mainly in arabinogalactan protein (AGP) biosynthesis. Co-expression analysis identified 4 GTs and 4 NSTs possibly involved in AGP biosynthesis. As part of the method development, the cytoskeleton-acting agent Cytochalasin D was tested as an inhibitor of the......GALT31A, which remarkably enhanced the nzymatic activity specifically towards the β-(1→6)-galactan side chain elongation of AGP. No interaction was found between AtGALT31A and AtGlcAT14A. In addition, the interaction between the putative arabinosyltransferases, ARAD1 and ARAD2, involved in...

  14. Automatic selection of reference taxa for protein-protein interaction prediction with phylogenetic profiling

    DEFF Research Database (Denmark)

    Simonsen, Martin; Maetschke, S.R.; Ragan, M.A.

    2012-01-01

    Motivation: Phylogenetic profiling methods can achieve good accuracy in predicting protein–protein interactions, especially in prokaryotes. Recent studies have shown that the choice of reference taxa (RT) is critical for accurate prediction, but with more than 2500 fully sequenced taxa publicly......: We present three novel methods for automating the selection of RT, using machine learning based on known protein–protein interaction networks. One of these methods in particular, Tree-Based Search, yields greatly improved prediction accuracies. We further show that different methods for constituting...

  15. A magnetic nanoparticles relaxation sensor for protein-protein interaction detection at ultra-low magnetic field.

    Science.gov (United States)

    Wang, Wei; Ma, Peixiang; Dong, Hui; Krause, Hans-Joachim; Zhang, Yi; Willbold, Dieter; Offenhaeusser, Andreas; Gu, Zhongwei

    2016-06-15

    Functionalized magnetic nanoparticles (MNPs) can serve as magnetic relaxation sensors (MRSs) to detect different biological targets, because the clustering of magnetic particle may cause the spin-spin relaxation time (T2) decrease of the surrounding water protons. However, the application of MNPs in clinical NMR systems faces the challenge of poor stability at magnetic field strengths in the order of tesla. The recently developed ultra-low field (ULF) NMR technique working at microtesla (μT) range then becomes a candidate. Herein, we incorporated superconducting quantum interference device (SQUID) as the detector in the ultra-low field system to enhance the sensitivity. We functionalized the Fe3O4 nanoparticles with the gama-aminobutyrate type A receptor-associated proteins (GABARAP), which specifically interact with calreticulin (CRT). As a result of the interaction between GABARAP and CRT, the clustering of the functionalized MNPs generates local magnetic fields, which accelerate the dephasing of the water protons in the vicinity. We analyzed the relation between T2 values and the CRT concentrations at 211μT and the low detection limit for CRT is 10pg/ml, which is superior to the immunoblot system. The high sensitivity of the ULF NMR system for protein-protein interaction detection demonstrates the potential to use this inexpensive, portable system for quick biochemical and clinical assays. PMID:26914374

  16. PROTEIN-PROTEIN INTERACTIONS IN CASEIN PRECIPITATED BY PRESSURIZED CARBON DIOXIDE (C02 CASEIN)

    Science.gov (United States)

    Despite much research on the casein micelles, the colloidal calcium-phosphate complexes of skim milk, the molecular interactions involved in the casein micelles remain elusive. We investigate casein precipitated by pressurized carbon dioxide (CO2 casein) to elucidate the mechanism of the formation o...

  17. Interfacial Protein-Protein Associations

    OpenAIRE

    Langdon, Blake B.; Kastantin, Mark; Walder, Robert; Schwartz, Daniel K.

    2013-01-01

    While traditional models of protein adsorption focus primarily on direct protein-surface interactions, recent findings suggest that protein-protein interactions may play a central role. Using high-throughput intermolecular resonance energy transfer (RET) tracking, we directly observed dynamic, protein-protein associations of bovine serum albumin on poly(ethylene glycol) modified surfaces. The associations were heterogeneous and reversible, and associating molecules resided on the surface for ...

  18. The role of residue stability in transient protein-protein interactions involved in enzymatic phosphate hydrolysis. A computational study.

    Science.gov (United States)

    Bonet, Jaume; Caltabiano, Gianluigi; Khan, Abdul Kareem; Johnston, Michael A; Corbí, Carles; Gómez, Alex; Rovira, Xavier; Teyra, Joan; Villà-Freixa, Jordi

    2006-04-01

    Finding why protein-protein interactions (PPIs) are so specific can provide a valuable tool in a variety of fields. Statistical surveys of so-called transient complexes (like those relevant for signal transduction mechanisms) have shown a tendency of polar residues to participate in the interaction region. Following this scheme, residues in the unbound partners have to compete between interacting with water or interacting with other residues of the protein. On the other hand, several works have shown that the notion of active site electrostatic preorganization can be used to interpret the high efficiency in enzyme reactions. This preorganization can be related to the instability of the residues important for catalysis. In some enzymes, in addition, conformational changes upon binding to other proteins lead to an increase in the activity of the enzymatic partner. In this article the linear response approximation version of the semimacroscopic protein dipoles Langevin dipoles (PDLD/S-LRA) model is used to evaluate the stability of several residues in two phosphate hydrolysis enzymes upon complexation with their activating partners. In particular, the residues relevant for PPI and for phosphate hydrolysis in the CDK2/Cyclin A and Ras/GAP complexes are analyzed. We find that the evaluation of the stability of residues in these systems can be used to identify not only active site regions but it can also be used as a guide to locate "hot spots" for PPIs. We also show that conformational changes play a major role in positioning interfacing residues in a proper "energetic" orientation, ready to interact with the residues in the partner protein surface. Thus, we extend the preorganization theory to PPIs, extrapolating the results we obtained from the above-mentioned complexes to a more general case. We conclude that the correlation between stability of a residue in the surface and the likelihood that it participates in the interaction can be a general fact for transient

  19. Prioritizing cancer-related genes with aberrant methylation based on a weighted protein-protein interaction network

    Directory of Open Access Journals (Sweden)

    Lv Jie

    2011-10-01

    Full Text Available Abstract Background As an important epigenetic modification, DNA methylation plays a crucial role in the development of mammals and in the occurrence of complex diseases. Genes that interact directly or indirectly may have the same or similar functions in the biological processes in which they are involved and together contribute to the related disease phenotypes. The complicated relations between genes can be clearly represented using network theory. A protein-protein interaction (PPI network offers a platform from which to systematically identify disease-related genes from the relations between genes with similar functions. Results We constructed a weighted human PPI network (WHPN using DNA methylation correlations based on human protein-protein interactions. WHPN represents the relationships of DNA methylation levels in gene pairs for four cancer types. A cancer-associated subnetwork (CASN was obtained from WHPN by selecting genes associated with seed genes which were known to be methylated in the four cancers. We found that CASN had a more densely connected network community than WHPN, indicating that the genes in CASN were much closer to seed genes. We prioritized 154 potential cancer-related genes with aberrant methylation in CASN by neighborhood-weighting decision rule. A function enrichment analysis for GO and KEGG indicated that the optimized genes were mainly involved in the biological processes of regulating cell apoptosis and programmed cell death. An analysis of expression profiling data revealed that many of the optimized genes were expressed differentially in the four cancers. By examining the PubMed co-citations, we found 43 optimized genes were related with cancers and aberrant methylation, and 10 genes were validated to be methylated aberrantly in cancers. Of 154 optimized genes, 27 were as diagnostic markers and 20 as prognostic markers previously identified in literature for cancers and other complex diseases by searching Pub

  20. Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource

    OpenAIRE

    Schuette, Scott; Piatkowski, Brian; Corley, Aaron; Lang, Daniel; Geisler, Matt

    2015-01-01

    Background Physcomitrella patens, a haploid dominant plant, is fast becoming a useful molecular genetics and bioinformatics tool due to its key phylogenetic position as a bryophyte in the post-genomic era. Genome sequences from select reference species were compared bioinformatically to Physcomitrella patens using reciprocal blasts with the InParanoid software package. A reference protein interaction database assembled using MySQL by compiling BioGrid, BIND, DIP, and Intact databases was quer...

  1. A computational framework for boosting confidence in high-throughput protein-protein interaction datasets

    OpenAIRE

    Hosur, R.; Peng, J.; A Vinayagam; Stelzl, U.; Xu, J.; Perrimon, N; Bienkowska, J.; Berger, B.

    2012-01-01

    Improving the quality and coverage of the protein interactome is of tantamount importance for biomedical research, particularly given the various sources of uncertainty in high-throughput techniques. We introduce a structure-based framework, Coev2Net, for computing a single confidence score that addresses both false-positive and false-negative rates. Coev2Net is easily applied to thousands of binary protein interactions and has superior predictive performance over existing methods. We experim...

  2. Comparative analysis of protein-protein interactions in the defense response of rice and wheat

    OpenAIRE

    Cantu, Dario; Yang, Baoju; Ruan, Randy; LI, Kun; Menzo, Virginia; Fu, Daolin; Chern, Mawsheng; Ronald, Pamela C; Dubcovsky, Jorge

    2013-01-01

    Abstract Background Despite the importance of wheat as a major staple crop and the negative impact of diseases on its production worldwide, the genetic mechanisms and gene interactions involved in the resistance response in wheat are still poorly understood. The complete sequence of the rice genome has provided an extremely useful parallel road map for genetic and genomics studies in wheat. The recent construction of a defense response interactome in ...

  3. Comparative analysis of protein-protein interactions in the defense response of rice and wheat

    OpenAIRE

    Cantu, Dario; Yang, Baoju; Ruan, Randy; LI, Kun; Menzo, Virginia; Fu, Daolin; Chern, Mawsheng; Ronald, Pamela C; Dubcovsky, Jorge

    2013-01-01

    Background Despite the importance of wheat as a major staple crop and the negative impact of diseases on its production worldwide, the genetic mechanisms and gene interactions involved in the resistance response in wheat are still poorly understood. The complete sequence of the rice genome has provided an extremely useful parallel road map for genetic and genomics studies in wheat. The recent construction of a defense response interactome in rice has the potential to further enhance the trans...

  4. Comparative analysis of protein-protein interactions in the defense response of rice and wheat

    OpenAIRE

    Cantu, D.; Yang, B.; Ruan, R.; Li, K.; Menzo, V; Fu, D.; Chern, M; Ronald, PC; Dubcovsky, J.

    2013-01-01

    Background: Despite the importance of wheat as a major staple crop and the negative impact of diseases on its production worldwide, the genetic mechanisms and gene interactions involved in the resistance response in wheat are still poorly understood. The complete sequence of the rice genome has provided an extremely useful parallel road map for genetic and genomics studies in wheat. The recent construction of a defense response interactome in rice has the potential to further enhance the tran...

  5. Protein-protein interactions in a higher-order structure direct lambda site-specific recombination.

    Science.gov (United States)

    Thompson, J F; de Vargas, L M; Skinner, S E; Landy, A

    1987-06-01

    The highly directional site-specific recombination of bacteriophage lambda is tightly regulated by the binding of three different proteins to a complex array of sites. The manner in which these reactions are both stimulated and inhibited by co-operative binding of proteins to specific sites on the P arm of attP and AttR has been elucidated by correlation of nuclease protection with recombination studies of both wild-type and mutant DNAs. In addition to co-operative forces, there is a specific competitive interaction that allows the protein-DNA complex to serve as a "biological switch". This switch does not depend upon the simple occlusion of DNA binding sites by neighboring proteins; but, rather, the outcome of this competition is dependent on long-range interactions that vary between the higher-order structures of attP and attR. These higher-order structures are dependent on cooperative interactions involving three proteins binding to five or more sites. PMID:2958633

  6. Exploring of protein - protein interactions at the solid - aqueous interface by means of contact angle measurements.

    Science.gov (United States)

    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. PMID:26918510

  7. PROTEIN-PROTEIN INTERACTIONS OF THE FLAVONOID BIOSYNTHETIC ENZYMES IN ARABIDOPSIS THALIANA

    OpenAIRE

    Xiang, Jiale

    2014-01-01

    Flavonoids are a group of secondary metabolites, which are not only important for plants’ survival, but also have been found to have medicinal properties for human health. Several enzymes are involved in the flavonoid biosynthesis. It is thought that these enzymes work together and may form enzymatic complexes. But the way of these enzymes interact with each other is still not clear. In arabidopsis, the number of gene family members that encode these enzymes is less than in other model plan...

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

    CERN Document Server

    Buijsman, Wouter

    2012-01-01

    Various biological sensory systems exhibit a response to the relative change of the stimulus, often reffered to as fold-change detection. Here, we present a mechanism consisting of two interacting proteins, able to detect a fold-change effectively. This mechanism, in contrast to other proposed mechanisms, does not consume chemical energy and is not subject to transcriptional and translational noise. We show by analytical and numerical calculations that the mechanism can have a fast, precise and efficient response for parameters that are relevant to eukaryotic cells.

  9. Small-Molecule Stabilization of the 14-3-3/Gab2 Protein-Protein Interaction (PPI) Interface.

    Science.gov (United States)

    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. PMID:26644359

  10. Protein-protein interaction network construction for cancer using a new L1/2-penalized Net-SVM model.

    Science.gov (United States)

    Chai, H; Huang, H H; Jiang, H K; Liang, Y; Xia, L Y

    2016-01-01

    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. PMID:27525863

  11. Revisiting topological properties and models of protein-protein interaction networks from the perspective of dataset evolution.

    Science.gov (United States)

    Shao, Mingyu; Zhou, Shuigeng; Guan, Jihong

    2015-08-01

    Protein-protein interaction (PPI) networks are crucial for organisms. Many research efforts have thus been devoted to the study on the topological properties and models of PPI networks. However, existing studies did not always report consistent results on the topological properties of PPI networks. Although a number of PPI network models have been introduced, yet in the literature there is no convincing conclusion on which model is best for describing PPI networks. This situation is primarily caused by the incompleteness of current PPI datasets. To solve this problem, in this study, the authors propose to revisit the topological properties and models of PPI networks from the perspective of PPI dataset evolution. Concretely, they used 12 PPI datasets of Arabidopsis thaliana and 10 PPI datasets of Saccharomyces cerevisiae from different Biological General Repository for Interaction Datasets (BioGRID) database versions, and compared the topological properties of these datasets and the fitting capabilities of five typical PPI network models over these datasets. PMID:26243826

  12. Enabling systematic interrogation of protein-protein interactions in live cells with a versatile ultra-high-throughput biosensor platform.

    Science.gov (United States)

    Mo, Xiu-Lei; Luo, Yin; Ivanov, Andrei A; Su, Rina; Havel, Jonathan J; Li, Zenggang; Khuri, Fadlo R; Du, Yuhong; Fu, Haian

    2016-06-01

    Large-scale genomics studies have generated vast resources for in-depth understanding of vital biological and pathological processes. A rising challenge is to leverage such enormous information to rapidly decipher the intricate protein-protein interactions (PPIs) for functional characterization and therapeutic interventions. While a number of powerful technologies have been employed to detect PPIs, a singular PPI biosensor platform with both high sensitivity and robustness in a mammalian cell environment remains to be established. Here we describe the development and integration of a highly sensitive NanoLuc luciferase-based bioluminescence resonance energy transfer technology, termed BRET(n), which enables ultra-high-throughput (uHTS) PPI detection in live cells with streamlined co-expression of biosensors in a miniaturized format. We further demonstrate the application of BRET(n) in uHTS format in chemical biology research, including the discovery of chemical probes that disrupt PRAS40 dimerization and pathway connectivity profiling among core members of the Hippo signaling pathway. Such hippo pathway profiling not only confirmed previously reported PPIs, but also revealed two novel interactions, suggesting new mechanisms for regulation of Hippo signaling. Our BRET(n) biosensor platform with uHTS capability is expected to accelerate systematic PPI network mapping and PPI modulator-based drug discovery. PMID:26578655

  13. Virtual Screening and Experimental Validation Identify Novel Inhibitors of the Plasmodium falciparum Atg8-Atg3 Protein-Protein Interaction.

    Science.gov (United States)

    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. PMID:26748931

  14. A Versatile Platform to Analyze Low-Affinity and Transient Protein-Protein Interactions in Living Cells in Real Time

    Directory of Open Access Journals (Sweden)

    Yao-Cheng Li

    2014-12-01

    Full Text Available Protein-protein interactions (PPIs play central roles in orchestrating biological processes. While some PPIs are stable, many important ones are transient and hard to detect with conventional approaches. We developed ReBiL, a recombinase enhanced bimolecular luciferase complementation platform, to enable detection of weak PPIs in living cells. ReBiL readily identified challenging transient interactions between an E3 ubiquitin ligase and an E2 ubiquitin-conjugating enzyme. ReBiL’s ability to rapidly interrogate PPIs in diverse conditions revealed that some stapled α-helical peptides, a class of PPI antagonists, induce target-independent cytosolic leakage and cytotoxicity that is antagonized by serum. These results explain the requirement for serum-free conditions to detect stapled peptide activity, and define a required parameter to evaluate for peptide antagonist approaches. ReBiL’s ability to expedite PPI analysis, assess target specificity and cell permeability, and reveal off-target effects of PPI modifiers should facilitate the development of effective, cell-permeable PPI therapeutics and the elaboration of diverse biological mechanisms.

  15. Probing the Small-Molecule Inhibition of an Anticancer Therapeutic Protein-Protein Interaction Using a Solid-State Nanopore.

    Science.gov (United States)

    Kwak, Dong-Kyu; Chae, Hongsik; Lee, Mi-Kyung; Ha, Ji-Hyang; Goyal, Gaurav; Kim, Min Jun; Kim, Ki-Bum; Chi, Seung-Wook

    2016-05-01

    Nanopore sensing is an emerging technology for the single-molecule-based detection of various biomolecules. In this study, we probed the anticancer therapeutic p53 transactivation domain (p53TAD)/MDM2 interaction and its inhibition with a small-molecule MDM2 antagonist, Nutlin-3, using low-noise solid-state nanopores. Although the translocation of positively charged MDM2 through a nanopore was detected at the applied negative voltage, this MDM2 translocation was almost completely blocked upon formation of the MDM2/GST-p53TAD complex owing to charge conversion. In combination with NMR data, the nanopore measurements showed that the addition of Nutlin-3 rescued MDM2 translocation, indicating that Nutlin-3 disrupted the MDM2/GST-p53TAD complex, thereby releasing MDM2. Taken together, our results reveal that solid-state nanopores can be a valuable platform for the ultrasensitive, picomole-scale screening of small-molecule drugs against protein-protein interaction (PPI) targets. PMID:27038437

  16. Characterization of Ca2+-Dependent Protein-Protein Interactions within the Ca2+ Release Units of Cardiac Sarcoplasmic Reticulum

    Science.gov (United States)

    Rani, Shilpa; Park, Chang Sik; Sreenivasaiah, Pradeep Kumar; Kim, Do Han

    2016-01-01

    In the heart, excitation-contraction (E-C) coupling is mediated by Ca2+ release from sarcoplasmic reticulum (SR) through the interactions of proteins forming the Ca2+ release unit (CRU). Among them, calsequestrin (CSQ) and histidine-rich Ca2+ binding protein (HRC) are known to bind the charged luminal region of triadin (TRN) and thus directly or indirectly regulate ryanodine receptor 2 (RyR2) activity. However, the mechanisms of CSQ and HRC mediated regulation of RyR2 activity through TRN have remained unclear. We first examined the minimal KEKE motif of TRN involved in the interactions with CSQ2, HRC and RyR2 using TRN deletion mutants and in vitro binding assays. The results showed that CSQ2, HRC and RyR2 share the same KEKE motif region on the distal part of TRN (aa 202–231). Second, in vitro binding assays were conducted to examine the Ca2+ dependence of protein-protein interactions (PPI). The results showed that TRN-HRC interaction had a bell-shaped Ca2+ dependence, which peaked at pCa4, whereas TRN-CSQ2 or TRN-RyR2 interaction did not show such Ca2+ dependence pattern. Third, competitive binding was conducted to examine whether CSQ2, HRC, or RyR2 affects the TRN-HRC or TRN-CSQ2 binding at pCa4. Among them, only CSQ2 or RyR2 competitively inhibited TRN-HRC binding, suggesting that HRC can confer functional refractoriness to CRU, which could be beneficial for reloading of Ca2+ into SR at intermediate Ca2+ concentrations. PMID:26674963

  17. Protein-protein Interaction Between Domains of PDZ and BAR from PICK1

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Two DNA fragments encoding PDZ domain(21-110 residues) and BAR domain( 150-360 residues) from PICK1 (1-416 residues) were amplified by PCR and then introduced into vectors, pET-32M and pMAL-c2X respectively to generate recombinant plasmids, pE-pdz and pM-bar. Having been separately transferred into the hosts E. coli BL21 and E. coli JM109, these two strains can express fusion proteins: His-tagged PDZ (PDZ domain) and maltose binding protein-BAR( MBP-BAR domain) respectively, as confirmed by both SDS-PAGE and Western blotting. The interaction between these two domains is dose-dependence, as identified by a pull-down test. Moreover, it has been shown from the ELISA analysis that the actual amount of PDZ bound to MBP-BAR-amylose beads reaches ( 16 ±0. 5 )%, as calculated by the molar ratio of PDZ to MBP-BAR. In addition, the interaction between BAR(bait) and PDZ(prey) in vivo was also examined with a yeast two-hybrid system.

  18. Peptides interfering with protein-protein interactions in the ethylene signaling pathway delay tomato fruit ripening.

    Science.gov (United States)

    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

  19. Targeting Protein-Protein Interactions with Trimeric Ligands: High Affinity Inhibitors of the MAGUK Protein Family

    DEFF Research Database (Denmark)

    Nissen, Klaus B; Kedström, Linda Maria Haugaard; Wilbek, Theis S;

    2015-01-01

    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...

  20. [small beta]-Turn mimetic-based stabilizers of protein-protein interactions for the study of the non-canonical roles of leucyl-tRNA synthetase

    DEFF Research Database (Denmark)

    Kim, Chanwoo; Jung, Jinjoo; Thanh Tung, Truong;

    2016-01-01

    For the systematic perturbation of protein-protein interactions, we designed and synthesized tetra-substituted hexahydro-4H-pyrazino[2,1-c][1,2,4]triazine-4,7(6H)-diones as [small beta]-turn mimetics. We then devised a new synthetic route to obtain [small beta]-turn mimetic scaffolds via tandem N...

  1. Identification of novel type 1 diabetes candidate genes by integrating genome-wide association data, protein-protein interactions, and human pancreatic islet gene expression

    DEFF Research Database (Denmark)

    Bergholdt, Regine; Brorsson, Caroline; Palleja, Albert;

    2012-01-01

    disease, and they do not typically inform the broader context in which the disease genes operate. Here, we integrated type 1 diabetes GWAS data with protein-protein interactions to construct biological networks of relevance for disease. A total of 17 networks were identified. To prioritize and...

  2. Prediction of protein-protein interactions from amino acid sequences using a novel multi-scale continuous and discontinuous feature set

    OpenAIRE

    You, Zhu-Hong; Zhu, Lin; Zheng, Chun-Hou; Yu, Hong-Jie; Deng, Su-Ping; Ji, Zhen

    2014-01-01

    Background Identifying protein-protein interactions (PPIs) is essential for elucidating protein functions and understanding the molecular mechanisms inside the cell. However, the experimental methods for detecting PPIs are both time-consuming and expensive. Therefore, computational prediction of protein interactions are becoming increasingly popular, which can provide an inexpensive way of predicting the most likely set of interactions at the entire proteome scale, and can be used to compleme...

  3. Protein-protein interaction studies revealed genes associated with plant disease resistance and drought tolerance (abstract)

    International Nuclear Information System (INIS)

    Under natural conditions, plants are frequently subjected to biotic and abiotic constraints that cause considerable damage and limit plant productivity worldwide. Biotic and abiotic stresses results in the accumulation of Reactive Oxygen Species, ROS (H/sub 2/O/sub 2/, O/sub 2/), Nitric oxide (NO) and cytosolic calcium (Ca/sup 2), indicating that plant responses to diseases and drought may operate, at least in part, through common molecular pathways. Additionally, stress-inducible genes have been categorized in two different groups: (a) genes that directly protect against environmental stresses and (b) genes that encode protein kinases intriguingly, protein kinases are also involved in disease resistance since many resistance genes (R genes) are in fact kinases. Here, we describe an interactor hunt using the bacterial virulent gene, VirPphA as a bait to screen an Arabidopsis thaliana cDNA prey library. VirPpha shares sequence similarity with another type III effector protein. AvrPtoB. The screen, originally designed to search for key signaling components involved in disease resistance, identified several putative and promising interactors (2-cys peroxiredoxin-like protein, kinase-like protein and ER6 protein, which is a universal stress protein) that might be involved in both biotic and abiotic stress responses. Simultaneously, another screen using AvrPtoB as a bait was conducted searching the same library for common interactors. Fibrillin (Fibri, At4g04020) was identified in both screens indicating a possible involvement in plant disease resistance through its influence on the plant cytoskeleton, which has been implicated in localized defence response. Furthermore, At4g04020 is 82% similar to the Rice fibrillin, At4g22240, which was recently shown to interact the, rice SGT1 (OsSGT1). SGT1 is a gene that is required for multiple R-gene function. Using the yeast two-hybrid system, fibrillin was found to interact strongly with all VirPphA homologues identified in

  4. Ultra-High-Throughput Structure-Based Virtual Screening for Small-Molecule Inhibitors of Protein-Protein Interactions.

    Science.gov (United States)

    Johnson, David K; Karanicolas, John

    2016-02-22

    Protein-protein interactions play important roles in virtually all cellular processes, making them enticing targets for modulation by small-molecule therapeutics: specific examples have been well validated in diseases ranging from cancer and autoimmune disorders, to bacterial and viral infections. Despite several notable successes, however, overall these remain a very challenging target class. Protein interaction sites are especially challenging for computational approaches, because the target protein surface often undergoes a conformational change to enable ligand binding: this confounds traditional approaches for virtual screening. Through previous studies, we demonstrated that biased "pocket optimization" simulations could be used to build collections of low-energy pocket-containing conformations, starting from an unbound protein structure. Here, we demonstrate that these pockets can further be used to identify ligands that complement the protein surface. To do so, we first build from a given pocket its "exemplar": a perfect, but nonphysical, pseudoligand that would optimally match the shape and chemical features of the pocket. In our previous studies, we used these exemplars to quantitatively compare protein surface pockets to one another. Here, we now introduce this exemplar as a template for pharmacophore-based screening of chemical libraries. Through a series of benchmark experiments, we demonstrate that this approach exhibits comparable performance as traditional docking methods for identifying known inhibitors acting at protein interaction sites. However, because this approach is predicated on ligand/exemplar overlays, and thus does not require explicit calculation of protein-ligand interactions, exemplar screening provides a tremendous speed advantage over docking: 6 million compounds can be screened in about 15 min on a single 16-core, dual-GPU computer. The extreme speed at which large compound libraries can be traversed easily enables screening against

  5. De novo design of protein-protein interactions through modification of inter-molecular helix-helix interface residues.

    Science.gov (United States)

    Yagi, Sota; Akanuma, Satoshi; Yamagishi, Manami; Uchida, Tatsuya; Yamagishi, Akihiko

    2016-05-01

    For de novo design of protein-protein interactions (PPIs), information on the shape and chemical complementarity of their interfaces is generally required. Recent advances in computational PPI design have allowed for de novo design of protein complexes, and several successful examples have been reported. In addition, a simple and easy-to-use approach has also been reported that arranges leucines on a solvent-accessible region of an α-helix and places charged residues around the leucine patch to induce interactions between the two helical peptides. For this study, we adopted this approach to de novo design a new PPI between the helical bundle proteins sulerythrin and LARFH. A non-polar patch was created on an α-helix of LARFH around which arginine residues were introduced to retain its solubility. The strongest interaction found was for the LARFH variant cysLARFH-IV-3L3R and the sulerythrin mutant 6L6D (KD=0.16 μM). This artificial protein complex is maintained by hydrophobic and ionic interactions formed by the inter-molecular helical bundle structure. Therefore, by the simple and easy-to-use approach to create de novo interfaces on the α-helices, we successfully generated an artificial PPI. We also created a second LARFH variant with the non-polar patch surrounded by positively charged residues at each end. Upon mixing this LARFH variant with 6L6D, mesh-like fibrous nanostructures were observed by atomic force microscopy. Our method may, therefore, also be applicable to the de novo design of protein nanostructures. PMID:26867971

  6. Analysis of phosphorylation-dependent protein-protein interactions of histone h3.

    Science.gov (United States)

    Klingberg, Rebecca; Jost, Jan Oliver; Schümann, Michael; Gelato, Kathy Ann; Fischle, Wolfgang; Krause, Eberhard; Schwarzer, Dirk

    2015-01-16

    Multiple posttranslational modifications (PTMs) of histone proteins including site-specific phosphorylation of serine and threonine residues govern the accessibility of chromatin. According to the histone code theory, PTMs recruit regulatory proteins or block their access to chromatin. Here, we report a general strategy for simultaneous analysis of both of these effects based on a SILAC MS scheme. We applied this approach for studying the biochemical role of phosphorylated S10 of histone H3. Differential pull-down experiments with H3-tails synthesized from l- and d-amino acids uncovered that histone acetyltransferase 1 (HAT1) and retinoblastoma-binding protein 7 (RBBP7) are part of the protein network, which interacts with the unmodified H3-tail. An additional H3-derived bait containing the nonhydrolyzable phospho-serine mimic phosphonomethylen-alanine (Pma) at S10 recruited several isoforms of the 14-3-3 family and blocked the recruitment of HAT1 and RBBP7 to the unmodified H3-tail. Our observations provide new insights into the many functions of H3S10 phosphorylation. In addition, the outlined methodology is generally applicable for studying specific binding partners of unmodified histone tails. PMID:25330109

  7. Fuzzy regions in an intrinsically disordered protein impair protein-protein interactions.

    Science.gov (United States)

    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. PMID:26684000

  8. Analysis of transient phosphorylation-dependent protein-protein interactions in living mammalian cells using split-TEV

    Directory of Open Access Journals (Sweden)

    Botvinnik Anna

    2008-07-01

    Full Text Available Abstract Background Regulated protein-protein interactions (PPIs are pivotal molecular switches that are important for the regulation of signaling processes within eukaryotic cells. Cellular signaling is altered in various disease conditions and offers interesting options for pharmacological interventions. Constitutive PPIs are usually mediated by large interaction domains. In contrast, stimulus-regulated PPIs often depend on small post-translational modifications and are thus better suited targets for drug development. However, the detection of modification-dependent PPIs with biochemical methods still remains a labour- and material-intensive task, and many pivotal PPIs that are potentially suited for pharmacological intervention most likely remain to be identified. The availability of methods to easily identify and quantify stimulus-dependent, potentially also transient interaction events, is therefore essential. The assays should be applicable to intact mammalian cells, optimally also to primary cells in culture. Results In this study, we adapted the split-TEV system to quantify phosphorylation-dependent and transient PPIs that occur at the membrane and in the cytosol of living mammalian cells. Split-TEV is based on a PPI-induced functional complementation of two inactive TEV protease fragments fused to interaction partners of choice. Genetically encoded transcription-coupled and proteolysis-only TEV reporter systems were used to convert the TEV activity into an easily quantifiable readout. We measured the phosphorylation-dependent interaction between the pro-apoptotic protein Bad and the adapter proteins 14-3-3ε and ζ in NIH-3T3 fibroblasts and in primary cultured neurons. Using split-TEV assays, we show that Bad specifically interacts with 14-3-3 isoforms when phosphorylated by protein kinase Akt-1/PKB at Ser136. We also measured the phosphorylation-dependent Bad/14-3-3 interactions mediated by endogenous and transient Akt-1 activity. We

  9. Lateral Protein-Protein Interactions at Hydrophobic and Charged Surfaces as a Function of pH and Salt Concentration.

    Science.gov (United States)

    Hladílková, Jana; Callisen, Thomas H; Lund, Mikael

    2016-04-01

    Surface adsorption of Thermomyces lanuginosus lipase (TLL)-a widely used industrial biocatalyst-is studied experimentally and theoretically at different pH and salt concentrations. The maximum achievable surface coverage on a hydrophobic surface occurs around the protein isoelectric point and adsorption is reduced when either increasing or decreasing pH, indicating that electrostatic protein-protein interactions in the adsorbed layer play an important role. Using Metropolis Monte Carlo (MC) simulations, where proteins are coarse grained to the amino acid level, we estimate the protein isoelectric point in the vicinity of charged surfaces as well as the lateral osmotic pressure in the adsorbed monolayer. Good agreement with available experimental data is achieved and we further make predictions of the protein orientation at hydrophobic and charged surfaces. Finally, we present a perturbation theory for predicting shifts in the protein isoelectric point due to close proximity to charged surfaces. Although this approximate model requires only single protein properties (mean charge and its variance), excellent agreement is found with MC simulations. PMID:26815664

  10. Identification of Lung-Cancer-Related Genes with the Shortest Path Approach in a Protein-Protein Interaction Network

    Directory of Open Access Journals (Sweden)

    Bi-Qing Li

    2013-01-01

    Full Text Available Lung cancer is one of the leading causes of cancer mortality worldwide. The main types of lung cancer are small cell lung cancer (SCLC and nonsmall cell lung cancer (NSCLC. In this work, a computational method was proposed for identifying lung-cancer-related genes with a shortest path approach in a protein-protein interaction (PPI network. Based on the PPI data from STRING, a weighted PPI network was constructed. 54 NSCLC- and 84 SCLC-related genes were retrieved from associated KEGG pathways. Then the shortest paths between each pair of these 54 NSCLC genes and 84 SCLC genes were obtained with Dijkstra’s algorithm. Finally, all the genes on the shortest paths were extracted, and 25 and 38 shortest genes with a permutation P value less than 0.05 for NSCLC and SCLC were selected for further analysis. Some of the shortest path genes have been reported to be related to lung cancer. Intriguingly, the candidate genes we identified from the PPI network contained more cancer genes than those identified from the gene expression profiles. Furthermore, these genes possessed more functional similarity with the known cancer genes than those identified from the gene expression profiles. This study proved the efficiency of the proposed method and showed promising results.

  11. Optimizing Protein-Protein van der Waals Interactions for the AMBER ff9x/ff12 Force Field.

    Science.gov (United States)

    Chapman, Dail E; Steck, Jonathan K; Nerenberg, Paul S

    2014-01-14

    The quality of molecular dynamics (MD) simulations relies heavily on the accuracy of the underlying force field. In recent years, considerable effort has been put into developing more accurate dihedral angle potentials for MD force fields, but relatively little work has focused on the nonbonded parameters, many of which are two decades old. In this work, we assess the accuracy of protein-protein van der Waals interactions in the AMBER ff9x/ff12 force field. Across a test set of 44 neat organic liquids containing the moieties present in proteins, we find root-mean-square (RMS) errors of 1.26 kcal/mol in enthalpy of vaporization and 0.36 g/cm(3) in liquid densities. We then optimize the van der Waals radii and well depths for all of the relevant atom types using these observables, which lowers the RMS errors in enthalpy of vaporization and liquid density of our validation set to 0.59 kcal/mol (53% reduction) and 0.019 g/cm(3) (46% reduction), respectively. Limitations in our parameter optimization were evident for certain atom types, however, and we discuss the implications of these observations for future force field development. PMID:26579910

  12. Development of bispecific molecules for the in situ detection of protein-protein interactions and protein phosphorylation.

    Science.gov (United States)

    van Dieck, Jan; Schmid, Volker; Heindl, Dieter; Dziadek, Sebastian; Schraeml, Michael; Gerg, Michael; Massoner, Petra; Engel, Alfred M; Tiefenthaler, Georg; Vural, Serhat; Stritt, Simon; Tetzlaff, Fabian; Soukupova, Monika; Kopetzki, Erhard; Bossenmaier, Birgit; Thomas, Marlene; Klein, Christian; Mertens, Alfred; Heller, Astrid; Tacke, Michael

    2014-03-20

    Investigation of protein-protein interactions (PPIs) and protein phosphorylation in clinical tissue samples can offer valuable information about the activation status and function of proteins involved in disease progression. However, existing antibody-based methods for phosphorylation detection have been found to lack specificity, and methods developed for examining PPIs in vitro cannot be easily adapted for tissues samples. In this study, we eliminated some of these limitations by developing a specific immunohistochemical staining method that uses "dual binders" (DBs), which are bispecific detection agents consisting of two Fab fragment molecules joined by a flexible linker, to detect PPIs and protein phosphorylation. We engineered DBs by selecting Fab fragments with fast off-rate kinetics, which allowed us to demonstrate that stable target binding was achieved only upon simultaneous, cooperative binding to both epitopes. We show that DBs specifically detect the activated HER2/HER3 complex in formalin-fixed, paraffin-embedded cancer cells and exhibit superior detection specificity for phospho-HER3 compared to the corresponding monoclonal antibody. Overall, the performance of DBs makes them attractive tools for future development for clinical applications. PMID:24529991

  13. Prediction of Protein-Protein Interaction Sites with Machine-Learning-Based Data-Cleaning and Post-Filtering Procedures.

    Science.gov (United States)

    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. PMID:26563228

  14. Analysis of protein-protein interactions in MCF-7 and MDA-MB-231 cell lines using phthalic acid chemical probes.

    Science.gov (United States)

    Liang, Shih-Shin; Wang, Tsu-Nai; Tsai, Eing-Mei

    2014-01-01

    Phthalates are a class of plasticizers that have been characterized as endocrine disrupters, and are associated with genital diseases, cardiotoxicity, hepatotoxicity, and nephrotoxicity in the GeneOntology gene/protein database. In this study, we synthesized phthalic acid chemical probes and demonstrated differing protein-protein interactions between MCF-7 cells and MDA-MB-231 breast cancer cell lines. Phthalic acid chemical probes were synthesized using silicon dioxide particle carriers, which were modified using the silanized linker 3-aminopropyl triethoxyslane (APTES). Incubation with cell lysates from breast cancer cell lines revealed interactions between phthalic acid and cellular proteins in MCF-7 and MDA-MB-231 cells. Subsequent proteomics analyses indicated 22 phthalic acid-binding proteins in both cell types, including heat shock cognate 71-kDa protein, ATP synthase subunit beta, and heat shock protein HSP 90-beta. In addition, 21 MCF-7-specific and 32 MDA-MB-231 specific phthalic acid-binding proteins were identified, including related proteasome proteins, heat shock 70-kDa protein, and NADPH dehydrogenase and ribosomal correlated proteins, ras-related proteins, and members of the heat shock protein family, respectively. PMID:25402641

  15. Rational design of selective small-molecule inhibitors for β-catenin/B-cell lymphoma 9 protein-protein interactions.

    Science.gov (United States)

    Hoggard, Logan R; Zhang, Yongqiang; Zhang, Min; Panic, Vanja; Wisniewski, John A; Ji, Haitao

    2015-09-30

    Selective inhibition of α-helix-mediated protein-protein interactions (PPIs) with small organic molecules provides great potential for the discovery of chemical probes and therapeutic agents. Protein Data Bank data mining using the HippDB database indicated that (1) the side chains of hydrophobic projecting hot spots at positions i, i + 3, and i + 7 of an α-helix had few orientations when interacting with the second protein and (2) the hot spot pockets of PPI complexes had different sizes, shapes, and chemical groups when interacting with the same hydrophobic projecting hot spots of α-helix. On the basis of these observations, a small organic molecule, 4'-fluoro-N-phenyl-[1,1'-biphenyl]-3-carboxamide, was designed as a generic scaffold that itself directly mimics the binding mode of the side chains of hydrophobic projecting hot spots at positions i, i + 3, and i + 7 of an α-helix. Convenient decoration of this generic scaffold led to the selective disruption of α-helix-mediated PPIs. A series of small-molecule inhibitors selective for β-catenin/B-cell lymphoma 9 (BCL9) over β-catenin/cadherin PPIs was designed and synthesized. The binding mode of new inhibitors was characterized by site-directed mutagenesis and structure-activity relationship studies. This new class of inhibitors can selectively disrupt β-catenin/BCL9 over β-catenin/cadherin PPIs, suppress the transactivation of canonical Wnt signaling, downregulate the expression of Wnt target genes, and inhibit the growth of Wnt/β-catenin-dependent cancer cells. PMID:26352795

  16. Molecular Dynamics Simulations and Structural Analysis of Giardia duodenalis 14-3-3 Protein-Protein Interactions.

    Science.gov (United States)

    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. PMID:26551337

  17. Setting up a Bioluminescence Resonance Energy Transfer high throughput screening assay to search for protein/protein interaction inhibitors in mammalian cells.

    Directory of Open Access Journals (Sweden)

    Cyril eCouturier

    2012-09-01

    Full Text Available Each step of the cell life and its response or adaptation to its environment are mediated by a network of protein/protein interactions termed interactome. Our knowledge of this network keeps growing due to the development of sensitive techniques devoted to study these interactions. The bioluminescence resonance energy transfer (BRET technique was primarily developed to allow the dynamic monitoring of protein-protein interactions in living cells, and has widely been used to study receptor activation by intra- or extra-molecular conformational changes within receptors and activated complexes in mammal cells. Some interactions are described as crucial in human pathological processes, and a new class of drugs targeting them has recently emerged. The BRET method is well suited to identify inhibitors of protein-protein interactions and here is described why and how to set up and optimize a High Throughput Screening assay based on BRET to search for such inhibitory compounds. The different parameters to take into account when developing such BRET assays in mammal cells are reviewed to give general guidelines: considerations on the targeted interaction, choice of BRET version, inducibility of the interaction, kinetic of the monitored interaction, and of the BRET reading, influence substrate concentration, number of cells and medium composition used on the Z’ factor, and expected interferences for colored or fluorescent compounds.

  18. An efficient heuristic method for active feature acquisition and its application to protein-protein interaction prediction

    Directory of Open Access Journals (Sweden)

    Thahir Mohamed

    2012-11-01

    Full Text Available Abstract Background Machine learning approaches for classification learn the pattern of the feature space of different classes, or learn a boundary that separates the feature space into different classes. The features of the data instances are usually available, and it is only the class-labels of the instances that are unavailable. For example, to classify text documents into different topic categories, the words in the documents are features and they are readily available, whereas the topic is what is predicted. However, in some domains obtaining features may be resource-intensive because of which not all features may be available. An example is that of protein-protein interaction prediction, where not only are the labels ('interacting' or 'non-interacting' unavailable, but so are some of the features. It may be possible to obtain at least some of the missing features by carrying out a few experiments as permitted by the available resources. If only a few experiments can be carried out to acquire missing features, which proteins should be studied and which features of those proteins should be determined? From the perspective of machine learning for PPI prediction, it would be desirable that those features be acquired which when used in training the classifier, the accuracy of the classifier is improved the most. That is, the utility of the feature-acquisition is measured in terms of how much acquired features contribute to improving the accuracy of the classifier. Active feature acquisition (AFA is a strategy to preselect such instance-feature combinations (i.e. protein and experiment combinations for maximum utility. The goal of AFA is the creation of optimal training set that would result in the best classifier, and not in determining the best classification model itself. Results We present a heuristic method for active feature acquisition to calculate the utility of acquiring a missing feature. This heuristic takes into account the change in

  19. Polyamine biosynthesis inhibitors alter protein-protein interactions involving estrogen receptor in MCF-7 breast cancer cells.

    Science.gov (United States)

    Thomas, T; Shah, N; Klinge, C M; Faaland, C A; Adihkarakunnathu, S; Gallo, M A; Thomas, T J

    1999-04-01

    We investigated the effects of polyamine biosynthesis inhibition on the estrogenic signaling pathway of MCF-7 breast cancer cells using a protein-protein interaction system. Estrogen receptor (ER) linked to glutathione-S-transferase (GST) was used to examine the effects of two polyamine biosynthesis inhibitors, difluoromethylornithine (DFMO) and CGP 48664. ER was specifically associated with a 45 kDa protein in control cells. In cells treated with estradiol, nine proteins were associated with ER. Cells treated with polyamine biosynthesis inhibitors in the absence of estradiol retained the binding of their ER with a 45 kDa protein and the ER also showed low-affinity interactions with a number of cellular proteins; however, these associations were decreased by the presence of estradiol and the inhibitors. When samples from the estradiol+DFMO treatment group were incubated with spermidine prior to GST-ER pull down assay, an increased association of several proteins with ER was detected. The intensity of the ER-associated 45 kDa protein increased by 10-fold in the presence of 1000 microM spermidine. These results indicate a specific role for spermidine in ER association of proteins. Western blot analysis of samples eluted from GST-ER showed the presence of chicken ovalbumin upstream promoter-transcription factor, an orphan nuclear receptor, and the endogenous full-length ER. These results show that multiple proteins associate with ER and that the binding of some of these proteins is highly sensitive to intracellular polyamine concentrations. Overall, our results indicate the importance of the polyamine pathway in the gene regulatory function of estradiol in breast cancer cells. PMID:10194516

  20. Network analysis and cross species comparison of protein-protein interaction networks of human, mouse and rat cytochrome P450 proteins that degrade xenobiotics.

    Science.gov (United States)

    Karthikeyan, Bagavathy Shanmugam; Akbarsha, Mohammad Abdulkader; Parthasarathy, Subbiah

    2016-06-21

    Cytochrome P450 (CYP) enzymes that degrade xenobiotics play a critical role in the metabolism and biotransformation of drugs and xenobiotics in humans as well as experimental animal models such as mouse and rat. These proteins function as a network collectively as well as independently. Though there are several reports on the organization, regulation and functionality of various CYP enzymes at the molecular level, the understanding of organization and functionality of these proteins at the holistic level remain unclear. The objective of this study is to understand the organization and functionality of xenobiotic degrading CYP enzymes of human, mouse and rat using network theory approaches and to study species differences that exist among them at the holistic level. For our analysis, a protein-protein interaction (PPI) network for CYP enzymes of human, mouse and rat was constructed using the STRING database. Topology, centrality, modularity and robustness analyses were performed for our predicted CYP PPI networks that were then validated by comparison with randomly generated network models. Network centrality analyses of CYP PPI networks reveal the central/hub proteins in the network. Modular analysis of the CYP PPI networks of human, mouse and rat resulted in functional clusters. These clusters were subjected to ontology and pathway enrichment analysis. The analyses show that the cluster of the human CYP PPI network is enriched with pathways principally related to xenobiotic/drug metabolism. Endo-xenobiotic crosstalk dominated in mouse and rat CYP PPI networks, and they were highly enriched with endogenous metabolic and signaling pathways. Thus, cross-species comparisons and analyses of human, mouse and rat CYP PPI networks gave insights about species differences that existed at the holistic level. More investigations from both reductionist and holistic perspectives can help understand CYP metabolism and species extrapolation in a much better way. PMID:27194593

  1. ModuleRole: a tool for modulization, role determination and visualization in protein-protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Guipeng Li

    Full Text Available Rapidly increasing amounts of (physical and genetic protein-protein interaction (PPI data are produced by various high-throughput techniques, and interpretation of these data remains a major challenge. In order to gain insight into the organization and structure of the resultant large complex networks formed by interacting molecules, using simulated annealing, a method based on the node connectivity, we developed ModuleRole, a user-friendly web server tool which finds modules in PPI network and defines the roles for every node, and produces files for visualization in Cytoscape and Pajek. For given proteins, it analyzes the PPI network from BioGRID database, finds and visualizes the modules these proteins form, and then defines the role every node plays in this network, based on two topological parameters Participation Coefficient and Z-score. This is the first program which provides interactive and very friendly interface for biologists to find and visualize modules and roles of proteins in PPI network. It can be tested online at the website http://www.bioinfo.org/modulerole/index.php, which is free and open to all users and there is no login requirement, with demo data provided by "User Guide" in the menu Help. Non-server application of this program is considered for high-throughput data with more than 200 nodes or user's own interaction datasets. Users are able to bookmark the web link to the result page and access at a later time. As an interactive and highly customizable application, ModuleRole requires no expert knowledge in graph theory on the user side and can be used in both Linux and Windows system, thus a very useful tool for biologist to analyze and visualize PPI networks from databases such as BioGRID.ModuleRole is implemented in Java and C, and is freely available at http://www.bioinfo.org/modulerole/index.php. Supplementary information (user guide, demo data is also available at this website. API for ModuleRole used for this

  2. Identification of a novel protein-protein interaction motif mediating interaction of GPCR-associated sorting proteins with G protein-coupled receptors

    DEFF Research Database (Denmark)

    Bornert, Olivier; Møller, Thor Christian; Boeuf, Julien;

    2013-01-01

    degradation pathway. This protein belongs to the recently identified GPCR-associated sorting proteins (GASPs) family that comprises ten members for which structural and functional details are poorly documented. We present here a detailed structure-function relationship analysis of the molecular interaction...... GPCRs and highlight the presence within GASPs of a novel protein-protein interaction motif that might represent a new target to investigate the involvement of GASPs in the modulation of the activity of GPCRs.......GPCR desensitization and down-regulation are considered key molecular events underlying the development of tolerance in vivo. Among the many regulatory proteins that are involved in these complex processes, GASP-1 have been shown to participate to the sorting of several receptors toward the...

  3. BioC-compatible full-text passage detection for protein-protein interactions using extended dependency graph.

    Science.gov (United States)

    Peng, Yifan; Arighi, Cecilia; Wu, Cathy H; Vijay-Shanker, K

    2016-01-01

    There has been a large growth in the number of biomedical publications that report experimental results. Many of these results concern detection of protein-protein interactions (PPI). In BioCreative V, we participated in the BioC task and developed a PPI system to detect text passages with PPIs in the full-text articles. By adopting the BioC format, the output of the system can be seamlessly added to the biocuration pipeline with little effort required for the system integration. A distinctive feature of our PPI system is that it utilizes extended dependency graph, an intermediate level of representation that attempts to abstract away syntactic variations in text. As a result, we are able to use only a limited set of rules to extract PPI pairs in the sentences, and additional rules to detect additional passages for PPI pairs. For evaluation, we used the 95 articles that were provided for the BioC annotation task. We retrieved the unique PPIs from the BioGRID database for these articles and show that our system achieves a recall of 83.5%. In order to evaluate the detection of passages with PPIs, we further annotated Abstract and Results sections of 20 documents from the dataset and show that an f-value of 80.5% was obtained. To evaluate the generalizability of the system, we also conducted experiments on AIMed, a well-known PPI corpus. We achieved an f-value of 76.1% for sentence detection and an f-value of 64.7% for unique PPI detection.Database URL: http://proteininformationresource.org/iprolink/corpora. PMID:27170286

  4. HADDOCK2P2I : A biophysical model for predicting the binding affinity of protein-protein interaction inhibitors

    NARCIS (Netherlands)

    Kastritis, Panagiotis L.; Garcia Lopes Maia Rodrigues, João; Bonvin, Alexandre M J J

    2014-01-01

    The HADDOCK score, a scoring function for both protein-protein and protein-nucleic acid modeling, has been successful in selecting near-native docking poses in a variety of cases, including those of the CAPRI blind prediction experiment. However, it has yet to be optimized for small molecules, and i

  5. Using the theory of coevolution to predict protein-protein interactions in non-small cell lung cancer.

    Science.gov (United States)

    Zhang, Meng; Chan, Man-Him; Tu, Wen-Jian; He, Li-Ran; Lee, Chak-Man; He, Miao

    2013-02-01

    Systems biology has become an effective approach for understanding the molecular mechanisms underlying the development of lung cancer. In this study, sequences of 100 non-small cell lung cancer (NSCLC)-related proteins were downloaded from the National Center for Biotechnology Information (NCBI) databases. The Theory of Coevolution was then used to build a protein-protein interaction (PPI) network of NSCLC. Adopting the reverse thinking approach, we analyzed the NSCLC proteins one at a time. Fifteen key proteins were identified and categorized into a special protein family F(K), which included Cyclin D1 (CCND1), E-cadherin (CDH1), Cyclin-dependent kinase inhibitor 2A (CDKN2A), chemokine (C-X-C motif) ligand 12 (CXCL12), epidermal growth factor (EGF), epidermal growth factor receptor (EGFR), TNF receptor superfamily, member 6(FAS), FK506 binding protein 12-rapamycin associated protein 1 (FRAP1), O-6-methylguanine-DNA methyltransferase (MGMT), parkinson protein 2, E3 ubiquitin protein ligase (PARK2), phosphatase and tensin homolog (PTEN), calcium channel voltage-dependent alpha 2/delta subunit 2 (CACNA2D2), tubulin beta class I (TUBB), SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a, member 2 (SMARCA2), and wingless-type MMTV integration site family, member 7A (WNT7A). Seven key nodes of the sub-network were identified, which included PARK2, WNT7A, SMARCA2, FRAP1, CDKN2A, CCND1, and EGFR. The PPI predictions of EGFR-EGF, PARK2-FAS, PTEN-FAS, and CACNA2D2-CDH1 were confirmed experimentally by retrieving the Biological General Repository for Interaction Datasets (BioGRID) and PubMed databases. We proposed that the 7 proteins could serve as potential diagnostic molecular markers for NSCLC. In accordance with the developmental mode of lung cancer established by Sekine et al., we assumed that the occurrence and development of lung cancer were linked not only to gene loss in the 3p region (WNT7A, 3p25) and genetic mutations in the 9p

  6. Using the theory of coevolution to predict protein-protein interactions in non-small cell lung cancer

    Institute of Scientific and Technical Information of China (English)

    Meng Zhang; Man-Him Chan; Wen-Jian Tu; Li-Ran He; Chak-Man Lee; Miao He

    2013-01-01

    Systems biology has become an effective approach for understanding the molecular mechanisms underlying the development of lung cancer.In this study,sequences of 100 non-small cell lung cancer (NSCLC)-related proteins were downloaded from the National Center for Biotechnology Information (NCBI) databases.The Theory of Coevolution was then used to build a protein-protein interaction (PPI) network of NSCLC.Adopting the reverse thinking approach,we analyzed the NSCLC proteins one at a time.Fifteen key proteins were identified and categorized into a special protein family F (K),which included Cyclin D1 (CCND1),E-cadherin (CDH1),Cyclin-dependent kinase inhibitor 2A (CDKN2A),chemokine (C-X-C motif) ligand 12 (CXCL12),epidermal growth factor (EGF),epidermal growth factor receptor (EGFR),TNF receptor superfamily,member 6 (FAS),FK506 binding protein 12-rapamycin associated protein 1 (FRAP1),O-6-methylguanine-DNA methyltransferase (MGMT),parkinson protein 2,E3 ubiquitin protein ligase (PARK2),phosphatase and tensin homolog (PTEN),calcium channel voltage-dependent alpha 2/delta subunit 2 (CACNA2D2),tubulin beta class I (TUBB),SWl/SNF-related,matrix-associated,actin-dependent regulator of chromatin,subfamily a,member 2 (SMARCA2),and wingless-type MMTV integration site family,member 7A (WNT7A).Seven key nodes of the sub-network were identified,which included PARK2,WNT7A,SMARCA2,FRAP1,CDKN2A,CCND1,and EGFR.The PPI predictions of EGFR-EGF,PARK2-FAS,PTEN-FAS,and CACNA2D2-CDH1 were confirmed experimentally by retrieving the Biological General Repository for Interaction Datasets (BioGRID) and PubMed databases.We proposed that the 7 proteins could serve as potential diagnostic molecular markers for NSCLC.In accordance with the developmental mode of lung cancer established by Sekine et al.,we assumed that the occurrence and development of lung cancer were linked not only to gene loss in the 3p region (WNT7A,3p25) and genetic mutations in the 9p region but also to similar events in the

  7. Global De Novo Protein-Protein Interactome Elucidates Interactions of Drought-Responsive Proteins in Horse Gram (Macrotyloma uniflorum).

    Science.gov (United States)

    Bhardwaj, Jyoti; Gangwar, Indu; Panzade, Ganesh; Shankar, Ravi; Yadav, Sudesh Kumar

    2016-06-01

    Inspired by the availability of de novo transcriptome of horse gram (Macrotyloma uniflorum) and recent developments in systems biology studies, the first ever global protein-protein interactome (PPI) map was constructed for this highly drought-tolerant legume. Large-scale studies of PPIs and the constructed database would provide rationale behind the interplay at cascading translational levels for drought stress-adaptive mechanisms in horse gram. Using a bidirectional approach (interolog and domain-based), a high-confidence interactome map and database for horse gram was constructed. Available transcriptomic information for shoot and root tissues of a sensitive (M-191; genotype 1) and a drought-tolerant (M-249; genotype 2) genotype of horse gram was utilized to draw comparative PPI subnetworks under drought stress. High-confidence 6804 interactions were predicted among 1812 proteins covering about one-fourth of the horse gram proteome. The highest number of interactions (33.86%) in horse gram interactome matched with Arabidopsis PPI data. The top five hub nodes mostly included ubiquitin and heat-shock-related proteins. Higher numbers of PPIs were found to be responsive in shoot tissue (416) and root tissue (2228) of genotype 2 compared with shoot tissue (136) and root tissue (579) of genotype 1. Characterization of PPIs using gene ontology analysis revealed that kinase and transferase activities involved in signal transduction, cellular processes, nucleocytoplasmic transport, protein ubiquitination, and localization of molecules were most responsive to drought stress. Hence, these could be framed in stress adaptive mechanisms of horse gram. Being the first legume global PPI map, it would provide new insights into gene and protein regulatory networks for drought stress tolerance mechanisms in horse gram. Information compiled in the form of database (MauPIR) will provide the much needed high-confidence systems biology information for horse gram genes, proteins, and

  8. Targeting the K-Ras/PDEδ protein-protein interaction: the solution for Ras-driven cancers or just another therapeutic mirage?

    Science.gov (United States)

    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. PMID:23939923

  9. Enabling systematic interrogation of protein-protein interactions in live cells with a versatile ultra-high-throughput biosensor platform | Office of Cancer Genomics

    Science.gov (United States)

    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.

  10. The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

    OpenAIRE

    Krallinger, Martin; Vazquez, Miguel; Leitner, Florian; Salgado, David; Chatr-aryamontri, Andrew; Winter, Andrew; Perfetto, Livia; Briganti, Leonardo; Licata, Luana; Iannuccelli, Marta; Castagnoli, Luisa; Cesareni, Gianni; Tyers, Mike; Schneider, Gerold; Rinaldi, Fabio

    2011-01-01

    Background Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretat...

  11. A unique insertion of low complexity amino acid sequence underlies protein-protein interaction in human malaria parasite orotate phosphoribosyltransferase and orotidine 5'-monophosphate decarboxylase

    Institute of Scientific and Technical Information of China (English)

    Waranya Imprasittichai; Sittiruk Roytrakul; Sudaratana R Krungkrai; Jerapan Krungkrai

    2014-01-01

    Objective:To investigate the multienzyme complex formation of human malaria parasite Plasmodium falciparum(P. falciparum) orotate phosphoribosyltransferase(OPRT) and orotidine 5'-monophosphate decarboxylase(OMPDC), the fifth and sixth enzyme of the de novo pyrimidine biosynthetic pathway.Previously, we have clearly established that the two enzymes in the malaria parasite exist physically as a heterotetrameric(OPRT)2(OMPDC)2 complex containing two subunits each ofOPRT andOMPDC, and that the complex have catalytic kinetic advantages over the monofunctional enzyme.Methods:Both enzymes were cloned and expressed as recombinant proteins.The protein-protein interaction in the enzyme complex was identified using bifunctional chemical cross-linker, liquid chromatography-mass spectrometric analysis and homology modeling.Results:The unique insertions of low complexity region at the α2 and α5 helices of the parasiteOMPDC, characterized by single amino acid repeat sequence which was not found in homologous proteins from other organisms, was located on theOPRT-OMPDC interface.The structural models for the protein-protein interaction of the heterotetrameric(OPRT)2(OMPDC)2 multienzyme complex were proposed.Conclusions:Based on the proteomic data and structural modeling, it is surmised that the human malaria parasite low complexity region is responsible for theOPRT-OMPDC interaction.The structural complex of the parasite enzymes, thus, represents an efficient functional kinetic advantage, which in line with co-localization principles of evolutional origin, and allosteric control in protein-protein-interactions.

  12. Online multi-channel microfluidic chip-mass spectrometry and its application for quantifying noncovalent protein-protein interactions.

    Science.gov (United States)

    Liu, Wu; Chen, Qiushui; Lin, Xuexia; Lin, Jin-Ming

    2015-03-01

    To establish an automatic and online microfluidic chip-mass spectrometry (chip-MS) system, a device was designed and fabricated for microsampling by a hybrid capillary. The movement of the capillary was programmed by a computer to aspirate samples from different microfluidic channels in the form of microdroplets (typically tens of nanoliters in volume), which were separated by air plugs. The droplets were then directly analyzed by MS via paper spray ionization without any pretreatment. The feasibility and performance were demonstrated by a concentration gradient experiment. Furthermore, after eliminating the effect of nonuniform response factors by an internal standard method, determination of the association constant within a noncovalent protein-protein complex was successfully accomplished with the MS-based titration indicating the versatility and the potential of this novel platform for widespread applications. PMID:25597452

  13. PARPs database: A LIMS systems for protein-protein interaction data mining or laboratory information management system

    Science.gov (United States)

    Droit, Arnaud; Hunter, Joanna M; Rouleau, Michèle; Ethier, Chantal; Picard-Cloutier, Aude; Bourgais, David; Poirier, Guy G

    2007-01-01

    Background In the "post-genome" era, mass spectrometry (MS) has become an important method for the analysis of proteins and the rapid advancement of this technique, in combination with other proteomics methods, results in an increasing amount of proteome data. This data must be archived and analysed using specialized bioinformatics tools. Description We herein describe "PARPs database," a data analysis and management pipeline for liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics. PARPs database is a web-based tool whose features include experiment annotation, protein database searching, protein sequence management, as well as data-mining of the peptides and proteins identified. Conclusion Using this pipeline, we have successfully identified several interactions of biological significance between PARP-1 and other proteins, namely RFC-1, 2, 3, 4 and 5. PMID:18093328

  14. Protein-protein interaction between CRIPT and human galanin receptor 2%CRIPT与人甘丙肽2型受体的相互作用

    Institute of Scientific and Technical Information of China (English)

    路雅静; 宫夏霓; 孟斐; 杨予涛; 徐志卿

    2012-01-01

    Objective To get insight into the molecular mechanisms of signaling and trafficking of galanin receptor 2 ( GalR2) , and to investigate the interaction between human galanin receptor 2 (hCalR2) and cytoplasmic adapter proteins. Methods Yeast two-hybrid method was used to find which proteins interact with the C terminal of hGalR2. Then yeast co-transformation system and co-immunoprecipitation were applied to confirm the protein-protein interaction. Results Cyste-ine-rich PDZ-binding protein ( CRIFT) was found interact with the C terminal of hGalR2. The protein-protein interaction was confirmed by yeast co-transformation system and co-immunoprecipitation. Conclusion CRIFT interacts with GalR2 and this protein-protein interaction may be involved in trafficking and signaling of GalR2.%目的 通过寻找与人甘丙肽2型受体(hGalR2)C端相互作用的蛋白,以进一步探讨hGalR2转运和信号传导机制.方法 利用酵母双杂交实验寻找可以与hGalR2 C端相互作用的蛋白,并通过酵母双转验证和免疫共沉淀实验验证受体和目标蛋白之间的相互作用.结果 酵母双杂交方法结合免疫共沉淀实验发现和证实hGalR2与蛋白Cysteine-rich PDZ-binding protein(CRIPT)之间存在相互作用.结论 CRIPT可以与hGalR2结合而发生相互作用并可能因此参与hGalR2的转运或信号传导.

  15. Computational Simulations to Predict Creatine Kinase-Associated Factors: Protein-Protein Interaction Studies of Brain and Muscle Types of Creatine Kinases

    Directory of Open Access Journals (Sweden)

    Wei-Jiang Hu

    2011-01-01

    Full Text Available Creatine kinase (CK; EC 2.7.3.2 is related to several skin diseases such as psoriasis and dermatomyositis. CK is important in skin energy homeostasis because it catalyzes the reversible transfer of a phosphoryl group from MgATP to creatine. In this study, we predicted CK binding proteins via the use of bioinformatic tools such as protein-protein interaction (PPI mappings and suggest the putative hub proteins for CK interactions. We obtained 123 proteins for brain type CK and 85 proteins for muscle type CK in the interaction networks. Among them, several hub proteins such as NFKB1, FHL2, MYOC, and ASB9 were predicted. Determination of the binding factors of CK can further promote our understanding of the roles of CK in physiological conditions.

  16. Combining random gene fission and rational gene fusion to discover near-infrared fluorescent protein fragments that report on protein-protein interactions.

    Science.gov (United States)

    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. PMID:25265085

  17. Single-step protease cleavage elution for identification of protein-protein interactions from GST pull-down and mass spectrometry.

    Science.gov (United States)

    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. PMID:24259493

  18. Protein-protein complexation in bioluminescence

    OpenAIRE

    Titushin, Maxim S.; Feng, Yingang; Lee, John; Vysotski, Eugene S.; Liu, Zhi-jie

    2011-01-01

    In this review we summarize the progress made towards understanding the role of protein-protein interactions in the function of various bioluminescence systems of marine organisms, including bacteria, jellyfish and soft corals, with particular focus on methodology used to detect and characterize these interactions. In some bioluminescence systems, protein-protein interactions involve an “accessory protein” whereby a stored substrate is efficiently delivered to the bioluminescent enzyme lucife...

  19. Characterization of the Shigella and Salmonella Type III Secretion System Tip-Translocon Protein-Protein Interaction by Paramagnetic Relaxation Enhancement.

    Science.gov (United States)

    Kaur, Kawaljit; Chatterjee, Srirupa; De Guzman, Roberto N

    2016-04-15

    Many Gram-negative pathogens, such as Shigella and Salmonella, assemble the type III secretion system (T3SS) to inject virulence proteins directly into eukaryotic cells to initiate infectious diseases. The needle apparatus of the T3SS consists of a base, an extracellular needle, a tip protein complex, and a translocon. The atomic structure of the assembled tip complex and the translocon is unknown. Here, we show by NMR paramagnetic relaxation enhancement (PRE) that the mixed α-β domain at the distal region of the Shigella and Salmonella tip proteins interacts with the N-terminal ectodomain of their major translocon proteins. Our results reveal the binding surfaces involved in the tip-translocon protein-protein interaction and provide insights about the assembly of the needle apparatus of the T3SS. PMID:26749041

  20. GRIP: A web-based system for constructing Gold Standard datasets for protein-protein interaction prediction

    OpenAIRE

    Zheng Huiru; Wang Haiying; Browne Fiona; Azuaje Francisco

    2009-01-01

    Abstract Background Information about protein interaction networks is fundamental to understanding protein function and cellular processes. Interaction patterns among proteins can suggest new drug targets and aid in the design of new therapeutic interventions. Efforts have been made to map interactions on a proteomic-wide scale using both experimental and computational techniques. Reference datasets that contain known interacting proteins (positive cases) and non-interacting proteins (negativ...

  1. ABA Signaling in Guard Cells Entails a Dynamic Protein-Protein Interaction Relay from the PYL-RCAR Family Receptors to Ion Channels

    Institute of Scientific and Technical Information of China (English)

    Sung Chul Lee; Chae Woo Lim; Wenzhi Lan; Kai He; Sheng Luan

    2013-01-01

    Plant hormone abscisic acid (ABA) serves as an integrator of environmental stresses such as drought to trigger stomatal closure by regulating specific ion channels in guard cells.We previously reported that SLACl,an outward anion channel required for stomatal closure,was regulated via reversible protein phosphorylation events involving ABA signaling components,including protein phosphatase 2C members and a SnRK2-type kinase (OST1).In this study,we reconstituted the ABA signaling pathway as a protein-protein interaction relay from the PYL/RCAR-type receptors,to the PP2C-SnRK2 phosphatase-kinase pairs,to the ion channel SLACl.The ABA receptors interacted with and inhibited PP2C phosphatase activity against the SnRK2-type kinase,releasing active SnRK2 kinase to phosphorylate,and activate the SLACl channel,leading to reduced guard cell turgor and stomatal closure.Both yeast two-hybrid and bimolecular fluorescence complementation assays were used to verify the interactions among the components in the pathway.These biochemical assays demonstrated activity modifications of phosphatases and kinases by their interaction partners.The SLACl channel activity was used as an endpoint readout for the strength of the signaling pathway,depending on the presence of different combinations of signaling components.Further study using transgenic plants overexpressing one of the ABA receptors demonstrated that changing the relative level of interacting partners would change ABA sensitivity.

  2. PreBIND and Textomy – mining the biomedical literature for protein-protein interactions using a support vector machine

    OpenAIRE

    Baskin Berivan; Zhang Shudong; Tuekam Brigitte; Lay Vicki; Wolting Cheryl; de Bruijn Berry; Martin Joel; Donaldson Ian; Bader Gary D; Michalickova Katerina; Pawson Tony; Hogue Christopher WV

    2003-01-01

    Abstract Background The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational methods. The Biomolecular interaction network database (BIND) seeks to capture these data in a machine-readable format. We hypothesized that the formidable task-size of backfilling the database could be reduced by using Support Vector Machine technology to first locate inte...

  3. IntNetDB v1.0: an integrated protein-protein interaction network database generated by a probabilistic model

    Directory of Open Access Journals (Sweden)

    Han Jing-Dong J

    2006-11-01

    Full Text Available Abstract Background Although protein-protein interaction (PPI networks have been explored by various experimental methods, the maps so built are still limited in coverage and accuracy. To further expand the PPI network and to extract more accurate information from existing maps, studies have been carried out to integrate various types of functional relationship data. A frequently updated database of computationally analyzed potential PPIs to provide biological researchers with rapid and easy access to analyze original data as a biological network is still lacking. Results By applying a probabilistic model, we integrated 27 heterogeneous genomic, proteomic and functional annotation datasets to predict PPI networks in human. In addition to previously studied data types, we show that phenotypic distances and genetic interactions can also be integrated to predict PPIs. We further built an easy-to-use, updatable integrated PPI database, the Integrated Network Database (IntNetDB online, to provide automatic prediction and visualization of PPI network among genes of interest. The networks can be visualized in SVG (Scalable Vector Graphics format for zooming in or out. IntNetDB also provides a tool to extract topologically highly connected network neighborhoods from a specific network for further exploration and research. Using the MCODE (Molecular Complex Detections algorithm, 190 such neighborhoods were detected among all the predicted interactions. The predicted PPIs can also be mapped to worm, fly and mouse interologs. Conclusion IntNetDB includes 180,010 predicted protein-protein interactions among 9,901 human proteins and represents a useful resource for the research community. Our study has increased prediction coverage by five-fold. IntNetDB also provides easy-to-use network visualization and analysis tools that allow biological researchers unfamiliar with computational biology to access and analyze data over the internet. The web interface of

  4. Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Eric A Yen

    2014-05-01

    Full Text Available 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

  5. Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

    Science.gov (United States)

    Yen, Eric A; Tsay, Aaron; Waldispuhl, Jerome; Vogel, Jackie

    2014-05-01

    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

  6. One-Pot N2C/C2C/N2N Ligation To Trap Weak Protein-Protein Interactions.

    Science.gov (United States)

    Zhao, Lei; Ehrt, Christiane; Koch, Oliver; Wu, Yao-Wen

    2016-07-01

    Weak transient protein-protein interactions (PPIs) play an essential role in cellular dynamics. However, it is challenging to obtain weak protein complexes owing to their short lifetime. Herein we present a general and facile method for trapping weak PPIs in an unbiased manner using proximity-induced ligations. To expand the chemical ligation spectrum, we developed novel N2N (N-terminus to N-terminus) and C2C (C-terminus to C-terminus) ligation approaches. By using N2C (N-terminus to C-terminus), N2N, and C2C ligations in one pot, the interacting proteins were linked. The weak Ypt1:GDI interaction drove C2C ligation with t1/2 of 4.8 min and near quantitative conversion. The Ypt1-GDI conjugate revealed that binding of Ypt1 G-domain causes opening of the lipid-binding site of GDI, which can accommodate one prenyl group, giving insights into Rab membrane recycling. Moreover, we used this strategy to trap the KRas homodimer, which plays an important role in Ras signaling. PMID:27213482

  7. PARPs database: A LIMS systems for protein-protein interaction data mining or laboratory information management system

    OpenAIRE

    Picard-Cloutier Aude; Ethier Chantal; Rouleau Michèle; Hunter Joanna M; Droit Arnaud; Bourgais David; Poirier Guy G

    2007-01-01

    Abstract Background In the "post-genome" era, mass spectrometry (MS) has become an important method for the analysis of proteins and the rapid advancement of this technique, in combination with other proteomics methods, results in an increasing amount of proteome data. This data must be archived and analysed using specialized bioinformatics tools. Description We herein describe "PARPs database," a data analysis and management pipeline for liquid chromatography tandem mass spectrometry (LC-MS/...

  8. Adding 3D-structural context to protein-protein interaction data from high-throughput experiments

    OpenAIRE

    Jüttemann, Thomas

    2011-01-01

    In the past decade, automatisation has led to an immense increase of data in biology. Next generation sequencing techniques will produce a vast amount of sequences across all species in the coming years. In many cases, identifying the function and biological role of a protein from its sequence can be a complicated and time-intensive task. The identification of a protein's interaction partners is a tremendous help for understanding the biological context in which it is involved. In order to fu...

  9. Three-Dimensional Reconstruction of Three-Way FRET Microscopy Improves Imaging of Multiple Protein-Protein Interactions

    Science.gov (United States)

    Scott, Brandon L.; Hoppe, Adam D.

    2016-01-01

    Fluorescence resonance energy transfer (FRET) microscopy is a powerful tool for imaging the interactions between fluorescently tagged proteins in two-dimensions. For FRET microscopy to reach its full potential, it must be able to image more than one pair of interacting molecules and image degradation from out-of-focus light must be reduced. Here we extend our previous work on the application of maximum likelihood methods to the 3-dimensional reconstruction of 3-way FRET interactions within cells. We validated the new method (3D-3Way FRET) by simulation and fluorescent protein test constructs expressed in cells. In addition, we improved the computational methods to create a 2-log reduction in computation time over our previous method (3DFSR). We applied 3D-3Way FRET to image the 3D subcellular distributions of HIV Gag assembly. Gag fused to three different FPs (CFP, YFP, and RFP), assembled into viral-like particles and created punctate FRET signals that become visible on the cell surface when 3D-3Way FRET was applied to the data. Control experiments in which YFP-Gag, RFP-Gag and free CFP were expressed, demonstrated localized FRET between YFP and RFP at sites of viral assembly that were not associated with CFP. 3D-3Way FRET provides the first approach for quantifying multiple FRET interactions while improving the 3D resolution of FRET microscopy data without introducing bias into the reconstructed estimates. This method should allow improvement of widefield, confocal and superresolution FRET microscopy data. PMID:27023704

  10. Coev2Net: a computational framework for boosting confidence in high-throughput protein-protein interaction datasets

    OpenAIRE

    Hosur, Raghavendra; Peng, Jian; Vinayagam, Arunachalam; Stelzl, Ulrich; Xu, Jinbo; Perrimon, Norbert; Bienkowska, Jadwiga R.; Berger, Bonnie

    2012-01-01

    Improving the quality and coverage of the protein interactome is of tantamount importance for biomedical research, particularly given the various sources of uncertainty in high-throughput techniques. We introduce a structure-based framework, Coev2Net, for computing a single confidence score that addresses both false-positive and false-negative rates. Coev2Net is easily applied to thousands of binary protein interactions and has superior predictive performance over existing methods. We experim...

  11. iWRAP: An interface threading approach with application to prediction of cancer related protein-protein interactions

    OpenAIRE

    Hosur, R.; Xu, J.; Bienkowska, J.; Berger, B.

    2010-01-01

    Current homology modeling methods for predicting protein–protein interactions (PPIs) have difficulty in the “twilight zone” (< 40%) of sequence identities. Threading methods extend coverage further into the twilight zone by aligning primary sequences for a pair of proteins to a best-fit template complex to predict an entire three-dimensional structure. We introduce a threading approach, iWRAP, which focuses only on the protein interface. Our approach combines a novel linear programming formul...

  12. Discovery of a Potent Inhibitor of Replication Protein A Protein-Protein Interactions Using a Fragment-Linking Approach

    Energy Technology Data Exchange (ETDEWEB)

    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. [Vanderbilt; (Vanderbilt-MED)

    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.

  13. A comparative approach expands the protein-protein interaction node of the immune receptor XA21 in wheat and rice

    OpenAIRE

    Yang, Baoju; Ruan, Randy; Cantu, Dario; Wang, Xiaodong; Ji, Wanquan; Ronald, Pamela C; Dubcovsky, Jorge

    2013-01-01

    The rice (Oryza sativa) OsXA21 receptor kinase is a well-studied immune receptor that initiates a signal transduction pathway leading to resistance to Xanthomonas oryzae pv. oryzae. Two homologs of OsXA21 were identified in wheat (Triticum aestivum): TaXA21-like1 located in a syntenic region with OsXA21, and TaXA21-like2 located in a non-syntenic region. Proteins encoded by these two wheat genes interact with four wheat orthologs of known OsXA21 interactors. In this study, we screened a wheat...

  14. Characterizing alpha helical properties of Ebola viral proteins as potential targets for inhibition of alpha-helix mediated protein-protein interactions.

    Science.gov (United States)

    Chakraborty, Sandeep; Rao, Basuthkar J; Asgeirsson, Bjarni; Dandekar, Abhaya

    2014-01-01

    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

  15. Protein-protein interactions indicate composition of a 480 kDa SELMA complex in the second outermost membrane of diatom complex plastids.

    Science.gov (United States)

    Lau, Julia B; Stork, Simone; Moog, Daniel; Schulz, Julian; Maier, Uwe G

    2016-04-01

    Most secondary plastids of red algal origin are surrounded by four membranes and nucleus-encoded plastid proteins have to traverse these barriers. Translocation across the second outermost plastid membrane, the periplastidal membrane (PPM), is facilitated by a ERAD-(ER-associated degradation) derived machinery termed SELMA (symbiont-specific ERAD-like machinery). In the last years, important subunits of this translocator have been identified, which clearly imply compositional similarities between SELMA and ERAD. Here we investigated, via protein-protein interaction studies, if the composition of SELMA is comparable to the known ERAD complex. As a result, our data suggest that the membrane proteins of SELMA, the derlin proteins, are linked to the soluble sCdc48 complex via the UBX protein sUBX. This is similar to the ERAD machinery whereas the additional SELMA components, sPUB und a second Cdc48 copy might indicate the influence of functional constraints in developing a translocation machinery from ERAD-related factors. In addition, we show for the first time that a rhomboid protease is a central interaction partner of the membrane proteins of the SELMA system in complex plastids. PMID:26712034

  16. SOX2 O-GlcNAcylation alters its protein-protein interactions and genomic occupancy to modulate gene expression in pluripotent cells.

    Science.gov (United States)

    Myers, Samuel A; Peddada, Sailaja; Chatterjee, Nilanjana; Friedrich, Tara; Tomoda, Kiichrio; Krings, Gregor; Thomas, Sean; Maynard, Jason; Broeker, Michael; Thomson, Matthew; Pollard, Katherine; Yamanaka, Shinya; Burlingame, Alma L; Panning, Barbara

    2016-01-01

    The transcription factor SOX2 is central in establishing and maintaining pluripotency. The processes that modulate SOX2 activity to promote pluripotency are not well understood. Here, we show SOX2 is O-GlcNAc modified in its transactivation domain during reprogramming and in mouse embryonic stem cells (mESCs). Upon induction of differentiation SOX2 O-GlcNAcylation at serine 248 is decreased. Replacing wild type with an O-GlcNAc-deficient SOX2 (S248A) increases reprogramming efficiency. ESCs with O-GlcNAc-deficient SOX2 exhibit alterations in gene expression. This change correlates with altered protein-protein interactions and genomic occupancy of the O-GlcNAc-deficient SOX2 compared to wild type. In addition, SOX2 O-GlcNAcylation impairs the SOX2-PARP1 interaction, which has been shown to regulate ESC self-renewal. These findings show that SOX2 activity is modulated by O-GlcNAc, and provide a novel regulatory mechanism for this crucial pluripotency transcription factor. PMID:26949256

  17. Diversity of T cell epitopes in Plasmodium falciparum circumsporozoite protein likely due to protein-protein interactions.

    Directory of Open Access Journals (Sweden)

    Nagesh R Aragam

    Full Text Available Circumsporozoite protein (CS is a leading vaccine antigen for falciparum malaria, but is highly polymorphic in natural parasite populations. The factors driving this diversity are unclear, but non-random assortment of the T cell epitopes TH2 and TH3 has been observed in a Kenyan parasite population. The recent publication of the crystal structure of the variable C terminal region of the protein allows the assessment of the impact of diversity on protein structure and T cell epitope assortment. Using data from the Gambia (55 isolates and Malawi (235 isolates, we evaluated the patterns of diversity within and between epitopes in these two distantly-separated populations. Only non-synonymous mutations were observed with the vast majority in both populations at similar frequencies suggesting strong selection on this region. A non-random pattern of T cell epitope assortment was seen in Malawi and in the Gambia, but structural analysis indicates no intramolecular spatial interactions. Using the information from these parasite populations, structural analysis reveals that polymorphic amino acids within TH2 and TH3 colocalize to one side of the protein, surround, but do not involve, the hydrophobic pocket in CS, and predominately involve charge switches. In addition, free energy analysis suggests residues forming and behind the novel pocket within CS are tightly constrained and well conserved in all alleles. In addition, free energy analysis shows polymorphic residues tend to be populated by energetically unfavorable amino acids. In combination, these findings suggest the diversity of T cell epitopes in CS may be primarily an evolutionary response to intermolecular interactions at the surface of the protein potentially counteracting antibody-mediated immune recognition or evolving host receptor diversity.

  18. IDEA: Interactive Display for Evolutionary Analyses

    Directory of Open Access Journals (Sweden)

    Carlton Jane M

    2008-12-01

    Full Text Available Abstract Background The availability of complete genomic sequences for hundreds of organisms promises to make obtaining genome-wide estimates of substitution rates, selective constraints and other molecular evolution variables of interest an increasingly important approach to addressing broad evolutionary questions. Two of the programs most widely used for this purpose are codeml and baseml, parts of the PAML (Phylogenetic Analysis by Maximum Likelihood suite. A significant drawback of these programs is their lack of a graphical user interface, which can limit their user base and considerably reduce their efficiency. Results We have developed IDEA (Interactive Display for Evolutionary Analyses, an intuitive graphical input and output interface which interacts with PHYLIP for phylogeny reconstruction and with codeml and baseml for molecular evolution analyses. IDEA's graphical input and visualization interfaces eliminate the need to edit and parse text input and output files, reducing the likelihood of errors and improving processing time. Further, its interactive output display gives the user immediate access to results. Finally, IDEA can process data in parallel on a local machine or computing grid, allowing genome-wide analyses to be completed quickly. Conclusion IDEA provides a graphical user interface that allows the user to follow a codeml or baseml analysis from parameter input through to the exploration of results. Novel options streamline the analysis process, and post-analysis visualization of phylogenies, evolutionary rates and selective constraint along protein sequences simplifies the interpretation of results. The integration of these functions into a single tool eliminates the need for lengthy data handling and parsing, significantly expediting access to global patterns in the data.

  19. Protein-Protein and Peptide-Protein Interactions of NudE-Like 1 (Ndel1): A Protein Involved in Schizophrenia.

    Science.gov (United States)

    Hayashi, M A F; Felicori, L F; Fresqui, M A C; Yonamine, C M

    2015-01-01

    Schizophrenia (SCZ) is a devastating chronic mental disease determined by genetic and environmental factors, which susceptibility may involve an impaired neural migration during the neurodevelopmental process. Several candidate risk genes potentially associated with SCZ were related to the formation of protein complexes that ultimately mediate alterations in the neuroplasticity. The most studied SCZ risk gene is the Disrupted-in-Schizophrenia 1 (DISC1) gene, which functions seem to depend on the binding with cytoskeleton proteins, as the Nuclear-distribution gene E homolog like-1 (Ndel1) protein among others. Interestingly, Ndel1 is the only binding partner of DISC1 proteins with oligopeptidase activity, besides playing roles in multiple processes, including cytoskeletal organization, cell signaling, neuron migration, and neurite outgrowth. It is still not clear if the protein-protein interaction between Ndel1 and DISC1 is enough to explain all cellular functions attributed to these proteins, but there are several lines of evidence suggesting the importance of the catalytic activity of Ndel1 for the neurite outgrowth and neuron migration during embryogenesis. Recent works of the group have demonstrated the modulation of Ndel1 activity by DISC1, which is hypothetically impaired in SCZ patients. In fact, more recently, we also showed a lower Ndel1 activity in the plasma of SCZ patients compared to control health subjects, but the physiopathological significance of this feature is still unknown. Here we discuss Ndel1 ligands involved in protein-protein complex formations related to neurodevelopmental diseases, as (1) lissencephaly or Miller-Dieker Syndrome (MDS), which is characterized by the typical craniofacial features and abnormal smooth cerebral surface, and as (2) SCZ, since they both seem to be determined by defects in neuronal migration. Although impaired lissencephaly protein Lis1 complex formation with Ndel1 is the leading cause of lissencephaly, this

  20. Interrogation of the protein-protein interactions between human BRCA2 BRC repeats and RAD51 reveals atomistic determinants of affinity.

    Science.gov (United States)

    Cole, Daniel J; Rajendra, Eeson; Roberts-Thomson, Meredith; Hardwick, Bryn; McKenzie, Grahame J; Payne, Mike C; Venkitaraman, Ashok R; Skylaris, Chris-Kriton

    2011-07-01

    analysis of protein-protein interactions for chemical biology and molecular therapeutics. PMID:21789034

  1. Interrogation of the protein-protein interactions between human BRCA2 BRC repeats and RAD51 reveals atomistic determinants of affinity.

    Directory of Open Access Journals (Sweden)

    Daniel J Cole

    2011-07-01

    experimental tools for the analysis of protein-protein interactions for chemical biology and molecular therapeutics.

  2. The Use of Protein-Protein Interactions for the Analysis of the Associations between PM2.5 and Some Diseases.

    Science.gov (United States)

    Zhang, Qing; Zhang, Pei-Wei; Cai, Yu-Dong

    2016-01-01

    Nowadays, pollution levels are rapidly increasing all over the world. One of the most important pollutants is PM2.5. It is known that the pollution environment may cause several problems, such as greenhouse effect and acid rain. Among them, the most important problem is that pollutants can induce a number of serious diseases. Some studies have reported that PM2.5 is an important etiologic factor for lung cancer. In this study, we extensively investigate the associations between PM2.5 and 22 disease classes recommended by Goh et al., such as respiratory diseases, cardiovascular diseases, and gastrointestinal diseases. The protein-protein interactions were used to measure the linkage between disease genes and genes that have been reported to be modulated by PM2.5. The results suggest that some diseases, such as diseases related to ear, nose, and throat and gastrointestinal, nutritional, renal, and cardiovascular diseases, are influenced by PM2.5 and some evidences were provided to confirm our results. For example, a total of 18 genes related to cardiovascular diseases are identified to be closely related to PM2.5, and cardiovascular disease relevant gene DSP is significantly related to PM2.5 gene JUP. PMID:27243032

  3. Mixed-Isotope Labeling with LC-IMS-MS for Characterization of Protein-Protein Interactions by Chemical Cross-Linking

    Energy Technology Data Exchange (ETDEWEB)

    Merkley, Eric D.; Baker, Erin Shammel; Crowell, Kevin L.; Orton, Daniel J.; Taverner, Thomas; Ansong, Charles; Ibrahim, Yehia M.; Burnet, Meagan C.; Cort, John R.; Anderson, Gordon A.; Smith, Richard D.; Adkins, Joshua N.

    2013-02-20

    Chemical cross-linking of proteins followed by proteolysis and mass spectrometric analysis of the resulting cross-linked peptides can provide insights into protein structure and protein-protein interactions. However, cross-linked peptides are by necessity of low stoichometry and have different physicochemical properties than linear peptides, routine unambiguous identification of the cross-linked peptides has remained difficult. To address this challenge, we demonstrated the use of liquid chromatography and ion mobility separations coupled with mass spectrometry in combination with a heavy-isotope labeling method. The combination of mixed-isotope cross-linking and ion mobility provided unique and easily interpretable spectral multiplet features for the intermolecular cross-linked peptides. Application of the method to two different homodimeric proteins ‒ SrfN, a virulence factor from Salmonella Typhimurium and SO_2176, a protein of unknown function from Shewanella oneidensis‒ revealed several cross-linked peptides from both proteins that were identified with a low false discovery rate (estimated using a decoy approach). A greater number of cross-linked peptides were identified using ion mobility drift time information in the analysis than when the data were summed across the drift time dimension before analysis. The identified cross-linked peptides migrated more quickly in the ion mobility drift tube than the unmodified peptides.

  4. Developing an Acidic Residue Reactive and Sulfoxide-Containing MS-Cleavable Homobifunctional Cross-Linker for Probing Protein-Protein Interactions.

    Science.gov (United States)

    Gutierrez, Craig B; Yu, Clinton; Novitsky, Eric J; Huszagh, Alexander S; Rychnovsky, Scott D; Huang, Lan

    2016-08-16

    Cross-linking mass spectrometry (XL-MS) has become a powerful strategy for defining protein-protein interactions and elucidating architectures of large protein complexes. However, one of the inherent challenges in MS analysis of cross-linked peptides is their unambiguous identification. To facilitate this process, we have previously developed a series of amine-reactive sulfoxide-containing MS-cleavable cross-linkers. These MS-cleavable reagents have allowed us to establish a common robust XL-MS workflow that enables fast and accurate identification of cross-linked peptides using multistage tandem mass spectrometry (MS(n)). Although amine-reactive reagents targeting lysine residues have been successful, it remains difficult to characterize protein interaction interfaces with little or no lysine residues. To expand the coverage of protein interaction regions, we present here the development of a new acidic residue-targeting sulfoxide-containing MS-cleavable homobifunctional cross-linker, dihydrazide sulfoxide (DHSO). We demonstrate that DHSO cross-linked peptides display the same predictable and characteristic fragmentation pattern during collision induced dissociation as amine-reactive sulfoxide-containing MS-cleavable cross-linked peptides, thus permitting their simplified analysis and unambiguous identification by MS(n). Additionally, we show that DHSO can provide complementary data to amine-reactive reagents. Collectively, this work not only enlarges the range of the application of XL-MS approaches but also further demonstrates the robustness and applicability of sulfoxide-based MS-cleavability in conjunction with various cross-linking chemistries. PMID:27417384

  5. Protein-protein interactions in the β-oxidation part of the phenylacetate utilization pathway: crystal structure of the PaaF-PaaG hydratase-isomerase complex.

    Science.gov (United States)

    Grishin, Andrey M; Ajamian, Eunice; Zhang, Linhua; Rouiller, Isabelle; Bostina, Mihnea; Cygler, Miroslaw

    2012-11-01

    Microbial anaerobic and so-called hybrid pathways for degradation of aromatic compounds contain β-oxidation-like steps. These reactions convert the product of the opening of the aromatic ring to common metabolites. The hybrid phenylacetate degradation pathway is encoded in Escherichia coli by the paa operon containing genes for 10 enzymes. Previously, we have analyzed protein-protein interactions among the enzymes catalyzing the initial oxidation steps in the paa pathway (Grishin, A. M., Ajamian, E., Tao, L., Zhang, L., Menard, R., and Cygler, M. (2011) J. Biol. Chem. 286, 10735-10743). Here we report characterization of interactions between the remaining enzymes of this pathway and show another stable complex, PaaFG, an enoyl-CoA hydratase and enoyl-Coa isomerase, both belonging to the crotonase superfamily. These steps are biochemically similar to the well studied fatty acid β-oxidation, which can be catalyzed by individual monofunctional enzymes, multifunctional enzymes comprising several domains, or enzymatic complexes such as the bacterial fatty acid β-oxidation complex. We have determined the structure of the PaaFG complex and determined that although individually PaaF and PaaG are similar to enzymes from the fatty acid β-oxidation pathway, the structure of the complex is dissimilar from bacterial fatty acid β-oxidation complexes. The PaaFG complex has a four-layered structure composed of homotrimeric discs of PaaF and PaaG. The active sites of PaaF and PaaG are adapted to accept the intermediary components of the Paa pathway, different from those of the fatty acid β-oxidation. The association of PaaF and PaaG into a stable complex might serve to speed up the steps of the pathway following the conversion of phenylacetyl-CoA to a toxic and unstable epoxide-CoA by PaaABCE monooxygenase. PMID:22961985

  6. Immobilized Cytochrome P450 2C9 (CYP2C9): Applications for Metabolite Generation, Monitoring Protein-Protein Interactions, and Improving In-vivo Predictions Using Enhanced In-vitro Models

    Science.gov (United States)

    Wollenberg, Lance A.

    Cytochrome P450 (P450) enzymes are a family of oxoferroreductase enzymes containing a heme moiety and are well known to be involved in the metabolism of a wide variety of endogenous and xenobiotic materials. It is estimated that roughly 75% of all pharmaceutical compounds are metabolized by these enzymes. Traditional reconstituted in-vitro incubation studies using recombinant P450 enzymes are often used to predict in-vivo kinetic parameters of a drug early in development. However, in many cases, these reconstituted incubations are prone to aggregation which has been shown to affect the catalytic activity of an enzyme. Moreover, the presence of other isoforms of P450 enzymes present in a metabolic incubation, as is the case with microsomal systems, may affect the catalytic activity of an enzyme through isoform-specific protein-protein interactions. Both of these effects may result in inaccurate prediction of in-vivo drug metabolism using in-vitro experiments. Here we described the development of immobilized P450 constructs designed to elucidate the effects of aggregation and protein-protein interactions between P450 isoforms on catalytic activities. The long term objective of this project is to develop a system to control the oligomeric state of Cytochrome P450 enzymes to accurately elucidate discrepancies between in vitro reconstituted systems and actual in vivo drug metabolism for the precise prediction of metabolic activity. This approach will serve as a system to better draw correlations between in-vivo and in-vitro drug metabolism data. The central hypothesis is that Cytochrome P450 enzymes catalytic activity can be altered by protein-protein interactions occurring between Cytochrome P450 enzymes involved in drug metabolism, and is dependent on varying states of protein aggregation. This dissertation explains the details of the construction and characterization of a nanostructure device designed to control the state of aggregation of a P450 enzyme. Moreover

  7. High-Affinity Small-Molecule Inhibitors of the Menin-Mixed Lineage Leukemia (MLL) Interaction Closely Mimic a Natural Protein-Protein Interaction

    Energy Technology Data Exchange (ETDEWEB)

    He, Shihan; Senter, Timothy J.; Pollock, Jonathan; Han, Changho; Upadhyay, Sunil Kumar; Purohit, Trupta; Gogliotti, Rocco D.; Lindsley, Craig W.; Cierpicki, Tomasz; Stauffer, Shaun R.; Grembecka, Jolanta [Michigan; (Vanderbilt); (Vanderbilt-MED)

    2014-10-02

    The protein–protein interaction (PPI) between menin and mixed lineage leukemia (MLL) plays a critical role in acute leukemias, and inhibition of this interaction represents a new potential therapeutic strategy for MLL leukemias. We report development of a novel class of small-molecule inhibitors of the menin–MLL interaction, the hydroxy- and aminomethylpiperidine compounds, which originated from HTS of ~288000 small molecules. We determined menin–inhibitor co-crystal structures and found that these compounds closely mimic all key interactions of MLL with menin. Extensive crystallography studies combined with structure-based design were applied for optimization of these compounds, resulting in MIV-6R, which inhibits the menin–MLL interaction with IC50 = 56 nM. Treatment with MIV-6 demonstrated strong and selective effects in MLL leukemia cells, validating specific mechanism of action. Our studies provide novel and attractive scaffold as a new potential therapeutic approach for MLL leukemias and demonstrate an example of PPI amenable to inhibition by small molecules.

  8. Mutational analysis of STE5 in the yeast Saccharomyces cerevisiae: Application of a differential interaction trap assay for examining protein-protein interactions

    Energy Technology Data Exchange (ETDEWEB)

    Inouye, C.; Dhillon, N.; Durfee, T. [Univ. of California, Berkeley, CA (United States)] [and others

    1997-10-01

    Ste5 is essential for the yeast mating pheromone response pathway and is thought to function as a scaffold that organized the components of the mitogen-activated protein kinase (MAKP) cascade. A new method was developed to isolate missense mutations in Ste5 that differentially affect the ability of Ste5 to interact with either of two MAPK cascade constituents, the MEKK (Ste11) and the MEK (Ste7). Mutations that affect association with Ste7 or with Ste11 delineate discrete regions of Ste5 that are critical for each interaction. Co-immunoprecipitation analysis, examining the binding in vitro of Ste5 to Ste11, Ste7, Ste4 (G protein {beta} subunit), and Fus3 (MAPK), confirmed that each mutation specifically affects the interaction of Ste5 with only one protein. When expressed in a ste5{delta} cell, mutant Ste5 proteins that are defective in their ability to interact with either Ste11 or Ste7 result in a markedly reduced mating proficiency. One mutation that clearly weakened (but did not eliminate) interaction of Ste5 with Ste7 permitted mating at wild-type efficiency, indicating that an efficacious signal is generated even when Ste5 associates with only a small fraction of (or only transiently with) Ste7. Ste5 mutants defective in association with Ste11 or Ste7 showed strong interallelic complementation when co-expressed, suggesting that the functional form of Ste5 in vivo is an oligomer. 69 refs., 6 figs., 3 tabs.

  9. PPI layouts: BioJS components for the display of Protein-Protein Interactions [v1; ref status: indexed, http://f1000r.es/2u5

    Directory of Open Access Journals (Sweden)

    Gustavo A. Salazar

    2014-02-01

    Full Text Available Summary: We present two web-based components for the display of Protein-Protein Interaction networks using different self-organizing layout methods: force-directed and circular. These components conform to the BioJS standard and can be rendered in an HTML5-compliant browser without the need for third-party plugins. We provide examples of interaction networks and how the components can be used to visualize them, and refer to a more complex tool that uses these components. Availability: http://github.com/biojs/biojs; http://dx.doi.org/10.5281/zenodo.7753

  10. A Cross-Species Study of PI3K Protein-Protein Interactions Reveals the Direct Interaction of P85 and SHP2.

    Science.gov (United States)

    Breitkopf, Susanne B; Yang, Xuemei; Begley, Michael J; Kulkarni, Meghana; Chiu, Yu-Hsin; Turke, Alexa B; Lauriol, Jessica; Yuan, Min; Qi, Jie; Engelman, Jeffrey A; Hong, Pengyu; Kontaridis, Maria I; Cantley, Lewis C; Perrimon, Norbert; Asara, John M

    2016-01-01

    Using a series of immunoprecipitation (IP)-tandem mass spectrometry (LC-MS/MS) experiments and reciprocal BLAST, we conducted a fly-human cross-species comparison of the phosphoinositide-3-kinase (PI3K) interactome in a drosophila S2R+ cell line and several NSCLC and human multiple myeloma cell lines to identify conserved interacting proteins to PI3K, a critical signaling regulator of the AKT pathway. Using H929 human cancer cells and drosophila S2R+ cells, our data revealed an unexpected direct binding of Corkscrew, the drosophila ortholog of the non-receptor protein tyrosine phosphatase type II (SHP2) to the Pi3k21B (p60) regulatory subunit of PI3K (p50/p85 human ortholog) but no association with Pi3k92e, the human ortholog of the p110 catalytic subunit. The p85-SHP2 association was validated in human cell lines, and formed a ternary regulatory complex with GRB2-associated-binding protein 2 (GAB2). Validation experiments with knockdown of GAB2 and Far-Western blots proved the direct interaction of SHP2 with p85, independent of adaptor proteins and transfected FLAG-p85 provided evidence that SHP2 binding on p85 occurred on the SH2 domains. A disruption of the SHP2-p85 complex took place after insulin/IGF1 stimulation or imatinib treatment, suggesting that the direct SHP2-p85 interaction was both independent of AKT activation and positively regulates the ERK signaling pathway. PMID:26839216

  11. A Cross-Species Study of PI3K Protein-Protein Interactions Reveals the Direct Interaction of P85 and SHP2

    Science.gov (United States)

    Breitkopf, Susanne B.; Yang, Xuemei; Begley, Michael J.; Kulkarni, Meghana; Chiu, Yu-Hsin; Turke, Alexa B.; Lauriol, Jessica; Yuan, Min; Qi, Jie; Engelman, Jeffrey A.; Hong, Pengyu; Kontaridis, Maria I.; Cantley, Lewis C.; Perrimon, Norbert; Asara, John M.

    2016-02-01

    Using a series of immunoprecipitation (IP) - tandem mass spectrometry (LC-MS/MS) experiments and reciprocal BLAST, we conducted a fly-human cross-species comparison of the phosphoinositide-3-kinase (PI3K) interactome in a drosophila S2R+ cell line and several NSCLC and human multiple myeloma cell lines to identify conserved interacting proteins to PI3K, a critical signaling regulator of the AKT pathway. Using H929 human cancer cells and drosophila S2R+ cells, our data revealed an unexpected direct binding of Corkscrew, the drosophila ortholog of the non-receptor protein tyrosine phosphatase type II (SHP2) to the Pi3k21B (p60) regulatory subunit of PI3K (p50/p85 human ortholog) but no association with Pi3k92e, the human ortholog of the p110 catalytic subunit. The p85-SHP2 association was validated in human cell lines, and formed a ternary regulatory complex with GRB2-associated-binding protein 2 (GAB2). Validation experiments with knockdown of GAB2 and Far-Western blots proved the direct interaction of SHP2 with p85, independent of adaptor proteins and transfected FLAG-p85 provided evidence that SHP2 binding on p85 occurred on the SH2 domains. A disruption of the SHP2-p85 complex took place after insulin/IGF1 stimulation or imatinib treatment, suggesting that the direct SHP2-p85 interaction was both independent of AKT activation and positively regulates the ERK signaling pathway.

  12. Extending pathways and processes using molecular interaction networks to analyse cancer genome data

    Directory of Open Access Journals (Sweden)

    Krasnogor Natalio

    2010-12-01

    Full Text Available Abstract Background Cellular processes and pathways, whose deregulation may contribute to the development of cancers, are often represented as cascades of proteins transmitting a signal from the cell surface to the nucleus. However, recent functional genomic experiments have identified thousands of interactions for the signalling canonical proteins, challenging the traditional view of pathways as independent functional entities. Combining information from pathway databases and interaction networks obtained from functional genomic experiments is therefore a promising strategy to obtain more robust pathway and process representations, facilitating the study of cancer-related pathways. Results We present a methodology for extending pre-defined protein sets representing cellular pathways and processes by mapping them onto a protein-protein interaction network, and extending them to include densely interconnected interaction partners. The added proteins display distinctive network topological features and molecular function annotations, and can be proposed as putative new components, and/or as regulators of the communication between the different cellular processes. Finally, these extended pathways and processes are used to analyse their enrichment in pancreatic mutated genes. Significant associations between mutated genes and certain processes are identified, enabling an analysis of the influence of previously non-annotated cancer mutated genes. Conclusions The proposed method for extending cellular pathways helps to explain the functions of cancer mutated genes by exploiting the synergies of canonical knowledge and large-scale interaction data.

  13. The characterisation and prediction of protein-protein interfaces.

    OpenAIRE

    Kabir, T.

    2004-01-01

    Understanding how proteins interact with each other is of fundamental importance and is one of the most important goals of molecular biology. In order to study the characteristics of protein-protein interaction sites datasets of non-homologous protein-complexes have been compiled. These datasets include 142 obligate homocomplexes, 20 obligate hetero-complexes, 20 enzyme-inhibitor complexes, 15 antibody-antigen complexes, and 10 signaling complexes. Overall, the protein-protein interfaces of o...

  14. The fluorescent two-hybrid assay to screen for protein-protein interaction inhibitors in live cells: targeting the interaction of p53 with Mdm2 and Mdm4.

    Science.gov (United States)

    Yurlova, Larisa; Derks, Maarten; Buchfellner, Andrea; Hickson, Ian; Janssen, Marc; Morrison, Denise; Stansfield, Ian; Brown, Christopher J; Ghadessy, Farid J; Lane, David P; Rothbauer, Ulrich; Zolghadr, Kourosh; Krausz, Eberhard

    2014-04-01

    Protein-protein interactions (PPIs) are attractive but challenging targets for drug discovery. To overcome numerous limitations of the currently available cell-based PPI assays, we have recently established a fully reversible microscopy-assisted fluorescent two-hybrid (F2H) assay. The F2H assay offers a fast and straightforward readout: an interaction-dependent co-localization of two distinguishable fluorescent signals at a defined spot in the nucleus of mammalian cells. We developed two reversible F2H assays for the interactions between the tumor suppressor p53 and its negative regulators, Mdm2 and Mdm4. We then performed a pilot F2H screen with a subset of compounds, including small molecules (such as Nutlin-3) and stapled peptides. We identified five cell-penetrating compounds as potent p53-Mdm2 inhibitors. However, none exhibited intracellular activity on p53-Mdm4. Live cell data generated by the F2H assays enable the characterization of stapled peptides based on their ability to penetrate cells and disrupt p53-Mdm2 interaction as well as p53-Mdm4 interaction. Here, we show that the F2H assays enable side-by-side analysis of substances' dual Mdm2-Mdm4 activity. In addition, they are suitable for testing various types of compounds (e.g., small molecules and peptidic inhibitors) and concurrently provide initial data on cellular toxicity. Furthermore, F2H assays readily allow real-time visualization of PPI dynamics in living cells. PMID:24476585

  15. Conserved transmembrane glycine residues in the Shigella flexneri polysaccharide co-polymerase protein WzzB influence protein-protein interactions.

    Science.gov (United States)

    Papadopoulos, Magdalene; Tran, Elizabeth Ngoc Hoa; Murray, Gerald Laurence; Morona, Renato

    2016-06-01

    The O antigen (Oag) component of lipopolysaccharides (LPS) is crucial for virulence and Oag chain-length regulation is controlled by the polysaccharide co-polymerase class 1 (PCP1) proteins. Crystal structure analyses indicate that structural conservation among PCP1 proteins is highly maintained, however the mechanism of Oag modal-chain-length control remains to be fully elucidated. Shigella flexneri PCP1 protein WzzBSF confers a modal-chain length of 10-17 Oag repeat units (RUs), whereas the Salmonella enterica Typhimurium PCP1 protein WzzBST confers a modal-chain length of ~16-28 Oag RUs. Both proteins share >70 % overall sequence identity and contain two transmembrane (TM1 and TM2) regions, whereby a conserved proline-glycine-rich motif overlapping the TM2 region is identical in both proteins. Conserved glycine residues within TM2 are functionally important, as glycine to alanine substitutions at positions 305 and 311 confer very short Oag modal-chain length (~2-6 Oag RUs). In this study, WzzBSF was co-expressed with WzzBST in S. flexneri and a single intermediate modal-chain length of ~11-21 Oag RUs was observed, suggesting the presence of Wzz:Wzz interactions. Interestingly, co-expression of WzzBSF with WzzBG305A/G311A conferred a bimodal LPS Oag chain length (despite over 99 % protein sequence identity), and we hypothesized that the proteins fail to interact. Co-purification assays detected His6-WzzBSF co-purifying with FLAG-tagged WzzBST but not with FLAG-tagged WzzBG305A/G311A, supporting our hypothesis. These data indicate that the conserved glycine residues in TM2 are involved in Wzz:Wzz interactions, and provide insight into key interactions that drive Oag modal length control. PMID:27028755

  16. Investigation of Protein - Protein Interactions by Surface Plasmon Resonance%表面等离子体共振技术在蛋白质-蛋白质相互作用研究中的应用

    Institute of Scientific and Technical Information of China (English)

    杨彦; 戴宗; 邹小勇

    2009-01-01

    The technique of surface plasmon resonance(SPR) has been rapidly developed to investigate the interactions of biomolecules in recent years due to its exceptional capabilities with respects to label-free, specificity, sensitivity, sample dosage, real-time and online detection. Recently, the applications of SPR have been extended to immunology, proteomic, drug screening, cellular signal transduction, ligand/receptor fishing and so on. In this paper, the principle and the experimental design of biosensor chip technology of SPR biosensors was firstly briefly described. Its application on protein - protein interaction, including dynamic study by measuring the equilibrium binding constants , the association - dissociation rates, structure - function study, mutation and fragment analysis, and signal transduction were reviewed. In addition, several key techniques of SPR technology used in protein - protein interaction study, including surface modification of the sensor chip, methods to resist non-specific adsorption and surface regeneration, were discussed. When coupled with other spectral, electrochemical techniques, SPR biosensors can extend the capability to obtain more specific interfacing properties during the protein - protein interaction process.%表面等离子共振(SPR)近年来迅速发展为用于分析生物分子相互作用的一项技术.该技术无需标记、特异性强、灵敏度高、样品用量小,可实现在线连续实时检测.目前SPR已被广泛应用于免疫学、蛋白质组学、药物筛选、细胞信号转导、受体/配体垂钓等领域.该文阐述了基于表面等离子体共振技术生物传感器的基本原理和技术流程,综述了SPR在蛋白质-蛋白质相互作用动力学研究、蛋白质结构及功能研究、蛋白质突变和碎片分析、信号转导中的应用以及SPR在蛋白质-蛋白质相互作用研究中的多项关键技术.指出SPR通过与光谱、电化学等多技术联用后,可以获得更加详实的信息.

  17. The distribution of ligand-binding pockets around protein-protein interfaces suggests a general mechanism for pocket formation

    OpenAIRE

    Gao, Mu; Skolnick, Jeffrey

    2012-01-01

    Protein-protein and protein-ligand interactions are ubiquitous in a biological cell. Here, we report a comprehensive study of the distribution of protein-ligand interaction sites, namely ligand-binding pockets, around protein-protein interfaces where protein-protein interactions occur. We inspected a representative set of 1,611 representative protein-protein complexes and identified pockets with a potential for binding small molecule ligands. The majority of these pockets are within a 6 Å dis...

  18. Participation Gestalt: Analysing Participatory Qualities of Interaction in Public Space

    DEFF Research Database (Denmark)

    Dalsgaard, Peter; Halskov, Kim; Iversen, Ole Sejer

    2016-01-01

    We introduce a participation gestalt framework for analysing participation in public interactive installations. Building on the concept of interaction gestalt, we define the participation gestalt as the unified perception and experience of participatory qualities as they unfold through interaction...... five qualities provide a vocabulary for analyzing an interactive installation. Combined, the five qualities constitute a participation gestalt framework by which HCI researchers can qualify how a certain forms of participation emerge in public installations. We exemplify the framework by analyzing four...... public installations in different socio-cultural contexts and examining their participation gestalt....

  19. Analysing effects of spatiotemporally distributed species interactions in Maculinea systems

    OpenAIRE

    Singer, Alexander

    2007-01-01

    We analyse effects of species-interaction and spatiotemporal host distribution on persistence of Maculinea populations at isolated habitat sites. Maculinea butterflies are parasites of Myrmica ants. The butterfly caterpillars infest host ant nest in the vicinity of their initial oviposition plant. Thus, spatial distribution of initial host plants (oviposition plants), implies a spatial distribution of parasitism. We develop a ...

  20. Interrogation of the protein-protein interactions between human BRCA2 BRC repeats and RAD51 reveals atomistic determinants of affinity

    OpenAIRE

    Cole, Daniel J.; Eeson Rajendra; Meredith Roberts-Thomson; Bryn Hardwick; Grahame J. McKenzie; Payne, Mike C.; Ashok R Venkitaraman; Chris-Kriton Skylaris

    2011-01-01

    The breast cancer suppressor BRCA2 controls the recombinase RAD51 in the reactions that mediate homologous DNA recombination, an essential cellular process required for the error-free repair of DNA double-stranded breaks. The primary mode of interaction between BRCA2 and RAD51 is through the BRC repeats, which are ~35 residue peptide motifs that interact directly with RAD51 in vitro. Human BRCA2, like its mammalian orthologues, contains 8 BRC repeats whose sequence and spacing are evolutionar...

  1. The Citrus transcription factor, CitERF13, regulates citric acid accumulation via a protein-protein interaction with the vacuolar proton pump, CitVHA-c4.

    Science.gov (United States)

    Li, Shao-jia; Yin, Xue-ren; Xie, Xiu-lan; Allan, Andrew C; Ge, Hang; Shen, Shu-ling; Chen, Kun-song

    2016-01-01

    Organic acids are essential to fruit flavor. The vacuolar H(+) transporting adenosine triphosphatase (V-ATPase) plays an important role in organic acid transport and accumulation. However, less is known of V-ATPase interacting proteins and their relationship with organic acid accumulation. The relationship between V-ATPase and citric acid was investigated, using the citrus tangerine varieties 'Ordinary Ponkan (OPK)' and an early maturing mutant 'Zaoshu Ponkan (ZPK)'. Five V-ATPase genes (CitVHA) were predicted as important to citric acid accumulation. Among the genes, CitVHA-c4 was observed, using a yeast two-hybrid screen, to interact at the protein level with an ethylene response factor, CitERF13. This was verified using bimolecular fluorescence complementation assays. A similar interaction was also observed between Arabidopsis AtERF017 (a CitERF13 homolog) and AtVHA-c4 (a CitVHA-c4 homolog). A synergistic effect on citric acid levels was observed between V-ATPase proteins and interacting ERFs when analyzed using transient over-expression in tobacco and Arabidopsis mutants. Furthermore, the transcript abundance of CitERF13 was concomitant with CitVHA-c4. CitERF13 or AtERF017 over-expression leads to significant citric acid accumulation. This accumulation was abolished in an AtVHA-c4 mutant background. ERF-VHA interactions appear to be involved in citric acid accumulation, which was observed in both citrus and Arabidopsis. PMID:26837571

  2. Identification of protein-protein interactions between the TatB and TatC subunits of the twin-arginine translocase system and respiratory enzyme specific chaperones.

    Science.gov (United States)

    Kuzniatsova, Lalita; Winstone, Tara M L; Turner, Raymond J

    2016-04-01

    The Twin-arginine translocation (Tat) pathway serves for translocation of fully folded proteins across the cytoplasmic membrane in bacterial and chloroplast thylakoid membranes. The Escherichia coli Tat system consists of three core components: TatA, TatB, and TatC. The TatB and TatC subunits form the receptor complex for Tat dependent proteins. The TatB protein is composed of a single transmembrane helix and cytoplasmic domain. The structure of TatC revealed six transmembrane helices. Redox Enzyme Maturation Proteins (REMPs) are system specific chaperones, which play roles in the maturation of Tat dependent respiratory enzymes. Here we applied the in vivo bacterial two-hybrid technique to investigate interaction of REMPs with the TatBC proteins, finding that all but the formate dehydrogenase REMP dock to TatB or TatC. We focused on the NarJ subfamily, where DmsD--the REMP for dimethyl sulfoxide reductase in E. coli--was previously shown to interact with TatB and TatC. We found that these REMPs interact with TatC cytoplasmic loops 1, 2 and 4, with the exception of NarJ, that only interacts with 1 and 4. An in vitro isothermal titration calorimetry study was applied to confirm the evidence of interactions between TatC fragments and DmsD chaperone. Using a peptide overlapping array, it was shown that the different NarJ subfamily REMPs interact with different regions of the TatB cytoplasmic domains. The results demonstrate a role of REMP chaperones in targeting respiratory enzymes to the Tat system. The data suggests that the different REMPs may have different mechanisms for this task. PMID:26826271

  3. Small-Molecule Inhibitors of the MDM2-p53 Protein-Protein Interaction to Reactivate p53 Function: A Novel Approach for Cancer Therapy

    OpenAIRE

    Shangary, Sanjeev; Wang, Shaomeng

    2009-01-01

    Tumor suppressor p53 is an attractive cancer therapeutic target because it can be functionally activated to eradicate tumors. Direct gene alterations in p53 or interaction between p53 and MDM2 proteins are two alternative mechanisms for the inactivation of p53 function. Designing small molecules to block the MDM2-p53 interaction and reactivate the p53 function is a promising therapeutic strategy for the treatment of cancers retaining wild-type p53. This review will highlight recent advances i...

  4. Interrogation of the Protein-Protein Interactions between Human BRCA2 BRC Repeats and RAD51 Reveals Atomistic Determinants of Affinity

    OpenAIRE

    Cole, Daniel J.; Rajendra, Eeson; Roberts-Thomson, Meredith; Hardwick, Bryn; Grahame J. McKenzie; Payne, Mike C.; Ashok R Venkitaraman; Skylaris, Chris-Kriton

    2011-01-01

    The breast cancer suppressor BRCA2 controls the recombinase RAD51 in the reactions that mediate homologous DNA recombination, an essential cellular process required for the error-free repair of DNA double-stranded breaks. The primary mode of interaction between BRCA2 and RAD51 is through the BRC repeats, which are ∼35 residue peptide motifs that interact directly with RAD51 in vitro. Human BRCA2, like its mammalian orthologues, contains 8 BRC repeats whose sequence and spacing are evolutionar...

  5. Analysis of the protein-protein interactions between the human acidic ribosomal P-proteins: evaluation by the two hybrid system

    DEFF Research Database (Denmark)

    Tchórzewski, M; Boldyreff, B; Issinger, O;

    2000-01-01

    function of these proteins, we are the first to have precisely analyzed mutual interactions among human P-proteins, employing the two hybrid system. The human acidic ribosomal P-proteins, (P1 or P2,) were fused to the GAL4 binding domain (BD) as well as the activation domain (AD), and analyzed in yeast...... forms the 60 S ribosomal stalk: P0-(P1/P2)(2). Additionally, mutual interactions among human and yeast P-proteins were analyzed. Heterodimer formation could be observed between human P2 and yeast P1 proteins.......The surface acidic ribosomal proteins (P-proteins), together with ribosomal core protein P0 form a multimeric lateral protuberance on the 60 S ribosomal subunit. This structure, also called stalk, is important for efficient translational activity of the ribosome. In order to shed more light on the...

  6. Free-Propagator Reweighting Integrator for Single-Particle Dynamics in Reaction-Diffusion Models of Heterogeneous Protein-Protein Interaction Systems

    Science.gov (United States)

    Johnson, Margaret E.; Hummer, Gerhard

    2014-07-01

    We present a new algorithm for simulating reaction-diffusion equations at single-particle resolution. Our algorithm is designed to be both accurate and simple to implement, and to be applicable to large and heterogeneous systems, including those arising in systems biology applications. We combine the use of the exact Green's function for a pair of reacting particles with the approximate free-diffusion propagator for position updates to particles. Trajectory reweighting in our free-propagator reweighting (FPR) method recovers the exact association rates for a pair of interacting particles at all times. FPR simulations of many-body systems accurately reproduce the theoretically known dynamic behavior for a variety of different reaction types. FPR does not suffer from the loss of efficiency common to other path-reweighting schemes, first, because corrections apply only in the immediate vicinity of reacting particles and, second, because by construction the average weight factor equals one upon leaving this reaction zone. FPR applications include the modeling of pathways and networks of protein-driven processes where reaction rates can vary widely and thousands of proteins may participate in the formation of large assemblies. With a limited amount of bookkeeping necessary to ensure proper association rates for each reactant pair, FPR can account for changes to reaction rates or diffusion constants as a result of reaction events. Importantly, FPR can also be extended to physical descriptions of protein interactions with long-range forces, as we demonstrate here for Coulombic interactions.

  7. The Citrus transcription factor, CitERF13, regulates citric acid accumulation via a protein-protein interaction with the vacuolar proton pump, CitVHA-c4

    OpenAIRE

    Shao-jia Li; Xue-ren Yin; Xiu-lan Xie; Andrew C. Allan; Hang Ge; Shu-ling Shen; Kun-song Chen

    2016-01-01

    Organic acids are essential to fruit flavor. The vacuolar H+ transporting adenosine triphosphatase (V-ATPase) plays an important role in organic acid transport and accumulation. However, less is known of V-ATPase interacting proteins and their relationship with organic acid accumulation. The relationship between V-ATPase and citric acid was investigated, using the citrus tangerine varieties ‘Ordinary Ponkan (OPK)’ and an early maturing mutant ‘Zaoshu Ponkan (ZPK)’. Five V-ATPase genes (CitVHA...

  8. Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

    OpenAIRE

    Romina Oliva; Edrisse Chermak; Luigi Cavallo

    2015-01-01

    In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a ...

  9. Characterizing alpha helical properties of Ebola viral proteins as potential targets for inhibition of alpha-helix mediated protein-protein interactions [v3; ref status: indexed, http://f1000r.es/50u

    Directory of Open Access Journals (Sweden)

    Sandeep Chakraborty

    2015-01-01

    Full Text Available 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.

  10. Deletion mutagenesis of the Escherichia coli UvrA protein localizes domains for DNA binding, damage recognition, and protein-protein interactions

    International Nuclear Information System (INIS)

    The UvrA protein is the DNA binding and damage recognition subunit of the damage-specific UvrABC endonuclease. In addition, it is an ATPase/GTPase, and the binding energy of ATP is linked to dimerization of the UvrA protein. Furthermore, the UvrA protein interacts with the UvrB protein to modulate its activities, both in solution and in association with DNA, where the UvrAB complex possesses a helicase activity. The domains of the UvrA protein that sponsor each of these activities were localized within the protein by studying the in vitro properties of a set of purified deletion mutants of the UvrA protein. A region located within the first 230 amino acids was found to contain the minimal region necessary for interactions with UvrB, the UvrA dimerization interface was localized to within the first 680 amino acids, and the DNA binding domain lies within the first 900 amino acids of the 940-amino acid UvrA protein. Two damage recognition domains were detected. The first domain, which coincides with the DNA binding region, is required to detect the damage. The second domain, located on or near the C-terminal 40 amino acids, stabilizes the protein-DNA complex when damage is encountered

  11. Structures of Neuroligin-1 And the Neuroligin-1/Neurexin-1beta Complex Reveal Specific Protein-Protein And Protein-Ca**2+ Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Arac, D.; Boucard, A.A.; Ozkan, E.A; Strop, P.; Newell, E.; Sudhof, T.C.; Brunger, A.T.

    2009-05-28

    Neurexins and neuroligins provide trans-synaptic connectivity by the Ca{sup 2+}-dependent interaction of their alternatively spliced extracellular domains. Neuroligins specify synapses in an activity-dependent manner, presumably by binding to neurexins. Here, we present the crystal structures of neuroligin-1 in isolation and in complex with neurexin-1{beta}. Neuroligin-1 forms a constitutive dimer, and two neurexin-1{beta} monomers bind to two identical surfaces on the opposite faces of the neuroligin-1 dimer to form a heterotetramer. The neuroligin-1/neurexin-1{beta} complex exhibits a nanomolar affinity and includes a large binding interface that contains bound Ca{sup 2+}. Alternatively spliced sites in neurexin-1{beta} and in neuroligin-1 are positioned nearby the binding interface, explaining how they regulate the interaction. Structure-based mutations of neuroligin-1 at the interface disrupt binding to neurexin-1{beta}, but not the folding of neuroligin-1 and confirm the validity of the binding interface of the neuroligin-1/neurexin-1{beta} complex. Our results provide molecular insights for understanding the role of cell-adhesion proteins in synapse function.

  12. Structures of Neuroligin-1 And the Neuroligin-1/Neurexin-1 Beta Complex Reveal Specific Protein-Protein And Protein-Ca2+ Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Demet, Arac; Boucard, A.A.; Ozkan, E.A; Strop, P.; Newell, E.; Sudhof, T.C.; Brunger, A.T.

    2009-06-01

    Neurexins and neuroligins provide trans-synaptic connectivity by the Ca{sup 2+}-dependent interaction of their alternatively spliced extracellular domains. Neuroligins specify synapses in an activity-dependent manner, presumably by binding to neurexins. Here, we present the crystal structures of neuroligin-1 in isolation and in complex with neurexin-1{beta}. Neuroligin-1 forms a constitutive dimer, and two neurexin-1{beta} monomers bind to two identical surfaces on the opposite faces of the neuroligin-1 dimer to form a heterotetramer. The neuroligin-1/neurexin-1{beta} complex exhibits a nanomolar affinity and includes a large binding interface that contains bound Ca{sup 2+}. Alternatively spliced sites in neurexin-1{beta} and in neuroligin-1 are positioned nearby the binding interface, explaining how they regulate the interaction. Structure-based mutations of neuroligin-1 at the interface disrupt binding to neurexin-1{beta}, but not the folding of neuroligin-1 and confirm the validity of the binding interface of the neuroligin-1/neurexin-1{beta} complex. Our results provide molecular insights for understanding the role of cell-adhesion proteins in synapse function.

  13. Structural basis of regulation and substrate specificity of protein kinase CK2 deduced from the modeling of protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Srinivasan N

    2003-05-01

    Full Text Available Abstract Background Protein Kinase Casein Kinase 2 (PKCK2 is an ubiquitous Ser/Thr kinase expressed in all eukaryotes. It phosphorylates a number of proteins involved in various cellular processes. PKCK2 holoenzyme is catalytically active tetramer, composed of two homologous or identical and constitutively active catalytic (α and two identical regulatory (β subunits. The tetramer cannot phosphorylate some substrates that can be phosphorylated by PKCK2α in isolation. The present work explores the structural basis of this feature using computational analysis and modeling. Results We have initially built a model of PKCK2α bound to a substrate peptide with a conformation identical to that of the substrates in the available crystal structures of other kinases complexed with the substrates/ pseudosubstrates. In this model however, the fourth acidic residue in the consensus pattern of the substrate, S/T-X-X-D/E where S/T is the phosphorylation site, did not result in interaction with the active form of PKCK2α and is highly solvent exposed. Interaction of the acidic residue is observed if the substrate peptide adopts conformations as seen in β turn, α helix, or 310 helices. This type of conformation is observed and accommodated well by PKCK2α in calmodulin where the phosphorylation site is at the central helix. PP2A carries sequence patterns for PKCK2α phosphorylation. While the possibility of PP2A being phosphorylated by PKCK2 has been raised in the literature we use the model of PP2A to generate a model of PP2A-PKCK2α complex. PKCK2β undergoes phosphorylation by holoenzyme at the N-terminal region, and is accommodated very well in the limited space available at the substrate-binding site of the holoenzyme while the space is insufficient to accommodate the binding of PP2A or calmodulin in the holoenzyme. Conclusion Charge and shape complimentarity seems to play a role in substrate recognition and binding to PKCK2α, along with the consensus

  14. Activation of anthocyanin biosynthesis in Gerbera hybrida (Asteraceae) suggests conserved protein-protein and protein-promoter interactions between the anciently diverged monocots and eudicots.

    Science.gov (United States)

    Elomaa, Paula; Uimari, Anne; Mehto, Merja; Albert, Victor A; Laitinen, Roosa A E; Teeri, Teemu H

    2003-12-01

    We have identified an R2R3-type MYB factor, GMYB10, from Gerbera hybrida (Asteraceae) that shares high sequence homology to and is phylogenetically grouped together with the previously characterized regulators of anthocyanin pigmentation in petunia (Petunia hybrida) and Arabidopsis. GMYB10 is able to induce anthocyanin pigmentation in transgenic tobacco (Nicotiana tabacum), especially in vegetative parts and anthers. In G. hybrida, GMYB10 is involved in activation of anthocyanin biosynthesis in leaves, floral stems, and flowers. In flowers, its expression is restricted to petal epidermal cell layers in correlation with the anthocyanin accumulation pattern. We have shown, using yeast (Saccharomyces cerevisiae) two-hybrid assay, that GMYB10 interacts with the previously isolated bHLH factor GMYC1. Particle bombardment analysis was used to show that GMYB10 is required for activation of a late anthocyanin biosynthetic gene promoter, PGDFR2. cis-Analysis of the target PGDFR2 revealed a sequence element with a key role in activation by GMYB10/GMYC1. This element shares high homology with the anthocyanin regulatory elements characterized in maize (Zea mays) anthocyanin promoters, suggesting that the regulatory mechanisms involved in activation of anthocyanin biosynthesis have been conserved for over 125 million years not only at the level of transcriptional regulators but also at the level of the biosynthetic gene promoters. PMID:14605235

  15. Gene Prioritization by Integrated Analysis of Protein Structural and Network Topological Properties for the Protein-Protein Interaction Network of Neurological Disorders

    Directory of Open Access Journals (Sweden)

    Yashna Paul

    2016-01-01

    Full Text Available Neurological disorders are known to show similar phenotypic manifestations like anxiety, depression, and cognitive impairment. There is a need to identify shared genetic markers and molecular pathways in these diseases, which lead to such comorbid conditions. Our study aims to prioritize novel genetic markers that might increase the susceptibility of patients affected with one neurological disorder to other diseases with similar manifestations. Identification of pathways involving common candidate markers will help in the development of improved diagnosis and treatments strategies for patients affected with neurological disorders. This systems biology study for the first time integratively uses 3D-structural protein interface descriptors and network topological properties that characterize proteins in a neurological protein interaction network, to aid the identification of genes that are previously not known to be shared between these diseases. Results of protein prioritization by machine learning have identified known as well as new genetic markers which might have direct or indirect involvement in several neurological disorders. Important gene hubs have also been identified that provide an evidence for shared molecular pathways in the neurological disease network.

  16. Elicitin-induced distal systemic resistance in plants is mediated through the protein-protein interactions influenced by selected lysine residues

    Directory of Open Access Journals (Sweden)

    Hana eUhlíková

    2016-02-01

    Full Text Available Elicitins are a family of small proteins with sterol-binding activity that are secreted by Phytophthora and Pythium spp. classified as oomycete PAMPs. Although alfa- and beta-elicitins bind with the same affinity to one high affinity binding site on the plasma membrane, beta-elicitins (possessing 6-7 lysine residues are generally 50- to 100-fold more active at inducing distal HR and systemic resistance than the alfa-isoforms (with only 1-3 lysine residues.To examine the role of lysine residues in elicitin biological activity, we employed site-directed mutagenesis to prepare a series of beta-elicitin cryptogein variants with mutations on specific lysine residues. In contrast to direct infiltration of protein into leaves, application to the stem revealed a rough correlation between protein’s charge and biological activity, resulting in protection against Phytophthora parasitica. A detailed analysis of proteins’ movement in plants showed no substantial differences in distribution through phloem indicating differences in consequent apoplastic or symplastic transport. In this process, an important role of homodimer formation together with the ability to form a heterodimer with potential partner represented by endogenous plants LTPs is suggested. Our work demonstrates a key role of selected lysine residues in these interactions and stresses the importance of processes preceding elicitin recognition responsible for induction of distal systemic resistance.

  17. Elicitin-Induced Distal Systemic Resistance in Plants is Mediated Through the Protein-Protein Interactions Influenced by Selected Lysine Residues.

    Science.gov (United States)

    Uhlíková, Hana; Obořil, Michal; Klempová, Jitka; Šedo, Ondrej; Zdráhal, Zbyněk; Kašparovský, Tomáš; Skládal, Petr; Lochman, Jan

    2016-01-01

    Elicitins are a family of small proteins with sterol-binding activity that are secreted by Phytophthora and Pythium sp. classified as oomycete PAMPs. Although α- and β-elicitins bind with the same affinity to one high affinity binding site on the plasma membrane, β-elicitins (possessing 6-7 lysine residues) are generally 50- to 100-fold more active at inducing distal HR and systemic resistance than the α-isoforms (with only 1-3 lysine residues). To examine the role of lysine residues in elicitin biological activity, we employed site-directed mutagenesis to prepare a series of β-elicitin cryptogein variants with mutations on specific lysine residues. In contrast to direct infiltration of protein into leaves, application to the stem revealed a rough correlation between protein's charge and biological activity, resulting in protection against Phytophthora parasitica. A detailed analysis of proteins' movement in plants showed no substantial differences in distribution through phloem indicating differences in consequent apoplastic or symplastic transport. In this process, an important role of homodimer formation together with the ability to form a heterodimer with potential partner represented by endogenous plants LTPs is suggested. Our work demonstrates a key role of selected lysine residues in these interactions and stresses the importance of processes preceding elicitin recognition responsible for induction of distal systemic resistance. PMID:26904041

  18. Protein-protein interactions during high-moisture extrusion for fibrous meat analogues and comparison of protein solubility methods using different solvent systems.

    Science.gov (United States)

    Liu, KeShun; Hsieh, Fu-Hung

    2008-04-23

    Soy protein, mixed with gluten and starch, was extruded into fibrous meat analogues under high-moisture and high-temperature conditions. The protein solubility of samples collected at different extruder zones and extrudates made with different moistures was determined by 11 extraction solutions consisting of 6 selective reagents and their combinations: phosphate salts, urea, DTT, thiourea, Triton X-100, and CHAPS. Protein solubility by most extractants showed decreasing patterns as the material passed through the extruder, but the solution containing all 6 reagents, known as isoelectric focus (IEF) buffer, solubilized the highest levels and equal amounts of proteins in all samples, indicating that there are no other covalent bonds involved besides disulfide bonds. With regard to relative importance between disulfide bonds and non-covalent interactions, different conclusions could be made from protein solubility patterns, depending on the type of extracting systems and a baseline used for comparison. The observation points out pitfalls and limitation of current protein solubility methodology and explains why controversy exists in the literature. Using the IEF buffer system with omission of one or more selective reagents is considered to be the right methodology to conduct protein solubility study and thus recommended. Results obtained with this system indicate that disulfide bonding plays a more important role than non-covalent bonds in not only holding the rigid structure of extrudates but also forming fibrous texture. The sharpest decrease in protein solubility occurred when the mix passed through the intermediate section of the extruder barrel, indicating formation of new disulfide bonds during the stage of dramatic increase in both temperature and moisture. After this stage, although the physical form of the product might undergo change and fiber formation might occur as it passed through the cooling die, the chemical nature of the product did not change

  19. Glyceraldehyde-3-Phosphate Dehydrogenase (GAPDH) Protein-Protein Interaction Inhibitor Reveals a Non-catalytic Role for GAPDH Oligomerization in Cell Death.

    Science.gov (United States)

    Qvit, Nir; Joshi, Amit U; Cunningham, Anna D; Ferreira, Julio C B; Mochly-Rosen, Daria

    2016-06-24

    Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), an important glycolytic enzyme, has a non-catalytic (thus a non-canonical) role in inducing mitochondrial elimination under oxidative stress. We recently demonstrated that phosphorylation of GAPDH by δ protein kinase C (δPKC) inhibits this GAPDH-dependent mitochondrial elimination. δPKC phosphorylation of GAPDH correlates with increased cell injury following oxidative stress, suggesting that inhibiting GAPDH phosphorylation should decrease cell injury. Using rational design, we identified pseudo-GAPDH (ψGAPDH) peptide, an inhibitor of δPKC-mediated GAPDH phosphorylation that does not inhibit the phosphorylation of other δPKC substrates. Unexpectedly, ψGAPDH decreased mitochondrial elimination and increased cardiac damage in an animal model of heart attack. Either treatment with ψGAPDH or direct phosphorylation of GAPDH by δPKC decreased GAPDH tetramerization, which corresponded to reduced GAPDH glycolytic activity in vitro and ex vivo Taken together, our study identified the potential mechanism by which oxidative stress inhibits the protective GAPDH-mediated elimination of damaged mitochondria. Our study also identified a pharmacological tool, ψGAPDH peptide, with interesting properties. ψGAPDH peptide is an inhibitor of the interaction between δPKC and GAPDH and of the resulting phosphorylation of GAPDH by δPKC. ψGAPDH peptide is also an inhibitor of GAPDH oligomerization and thus an inhibitor of GAPDH glycolytic activity. Finally, we found that ψGAPDH peptide is an inhibitor of the elimination of damaged mitochondria. We discuss how this unique property of increasing cell damage following oxidative stress suggests a potential use for ψGAPDH peptide-based therapy. PMID:27129213

  20. Seismic Soil-Structure Interaction Analyses of a Deeply Embedded Model Reactor – SASSI Analyses

    Energy Technology Data Exchange (ETDEWEB)

    Nie J.; Braverman J.; Costantino, M.

    2013-10-31

    This report summarizes the SASSI analyses of a deeply embedded reactor model performed by BNL and CJC and Associates, as part of the seismic soil-structure interaction (SSI) simulation capability project for the NEAMS (Nuclear Energy Advanced Modeling and Simulation) Program of the Department of Energy. The SASSI analyses included three cases: 0.2 g, 0.5 g, and 0.9g, all of which refer to nominal peak accelerations at the top of the bedrock. The analyses utilized the modified subtraction method (MSM) for performing the seismic SSI evaluations. Each case consisted of two analyses: input motion in one horizontal direction (X) and input motion in the vertical direction (Z), both of which utilized the same in-column input motion. Besides providing SASSI results for use in comparison with the time domain SSI results obtained using the DIABLO computer code, this study also leads to the recognition that the frequency-domain method should be modernized so that it can better serve its mission-critical role for analysis and design of nuclear power plants.

  1. Viscosity of high concentration protein formulations of monoclonal antibodies of the IgG1 and IgG4 subclass - Prediction of viscosity through protein-protein interaction measurements

    DEFF Research Database (Denmark)

    Neergaard, Martin S; Kalonia, Devendra S; Parshad, Henrik;

    2013-01-01

    The purpose of this work was to explore the relation between protein-protein interactions (PPIs) and solution viscosity at high protein concentration using three monoclonal antibodies (mAbs), two of the IgG4 subclass and one of the IgG1 subclass. A range of methods was used to quantify the PPI...... low or high protein concentration determined using DLS. The PPI measurements were correlated with solution viscosity (measured by DLS using polystyrene nanospheres and ultrasonic shear rheology) as a function of pH (4-9) and ionic strength (10, 50 and 150mM). Our measurements showed that the highest...... solution viscosity was observed under conditions with the most negative kD, the highest apparent radius and the lowest net charge. An increase in ionic strength resulted in a change in the nature of the PPI at low pH from repulsive to attractive. In the neutral to alkaline pH region the mAbs behaved...

  2. Cooperative long range protein-protein dynamics in Purple Membrane

    OpenAIRE

    Rheinstadter, Maikel; Schmalzl, Karin; Wood, Kathleen; Strauch, Dieter

    2008-01-01

    We present experimental evidence for a long-range protein-protein interaction in purple membrane (PM). The interprotein dynamics were quantified by measuring the spectrum of the acoustic phonons in the 2D bacteriorhodopsin (BR) protein lattice using inelastic neutron scattering. Phonon energies of about 1 meV were determined. The data are compared to an analytical model, and the effective spring constant for the interaction between neighboring protein trimers are determined to be k=53 N/m. Ad...

  3. Procurement and execution of PCB analyses: Customer-analyst interactions

    Energy Technology Data Exchange (ETDEWEB)

    Erickson, M.D.

    1993-03-01

    The practical application of PCB (polychlorinated biphenyl) analyses begins with a request for the analysis and concludes with provision of the requested analysis. The key to successful execution of this iteration is timely, professional communication between the requester and the analyst. Often PCB analyses are not satisfactorily executed, either because the requester failed to give adequate instructions or because the analyst simply ``did what he/she was told.`` The request for and conduct of a PCB analysis represents a contract for the procurement of a product (information about the sample); if both parties recognize and abide by this contractual relationship, the process generally proceeds smoothly. Requesters may be corporate purchasing agents working from a scope of work, a sample management office, a field team leader, a project manager, a physician`s office, or the analyst himself. The analyst with whom the requester communicates may be a laboratory supervisor, a sample-receiving department, a salesperson for the laboratory, or the analyst himself. The analyst conducting the analysis is often a team, with custody of the sample being passed from sample receiving to the extraction laboratory, to the cleanup laboratory, to the gas chromatography (GC) laboratory, to the data reduction person, to the package preparation person, to the quality control (QC) department for verification, to shipping. Where a team of analysts is involved, the requester needs a central point of contact to minimize confusion and frustration. For the requester-analyst interface to work smoothly, it must function as if it is a one-to-one interaction. This article addresses the pitfalls of the requester-analyst interaction and provides suggestions for improving the quality of the analytical product through the requester-analyst interface.

  4. Procurement and execution of PCB analyses: Customer-analyst interactions

    International Nuclear Information System (INIS)

    The practical application of PCB (polychlorinated biphenyl) analyses begins with a request for the analysis and concludes with provision of the requested analysis. The key to successful execution of this iteration is timely, professional communication between the requester and the analyst. Often PCB analyses are not satisfactorily executed, either because the requester failed to give adequate instructions or because the analyst simply ''did what he/she was told.'' The request for and conduct of a PCB analysis represents a contract for the procurement of a product (information about the sample); if both parties recognize and abide by this contractual relationship, the process generally proceeds smoothly. Requesters may be corporate purchasing agents working from a scope of work, a sample management office, a field team leader, a project manager, a physician's office, or the analyst himself. The analyst with whom the requester communicates may be a laboratory supervisor, a sample-receiving department, a salesperson for the laboratory, or the analyst himself. The analyst conducting the analysis is often a team, with custody of the sample being passed from sample receiving to the extraction laboratory, to the cleanup laboratory, to the gas chromatography (GC) laboratory, to the data reduction person, to the package preparation person, to the quality control (QC) department for verification, to shipping. Where a team of analysts is involved, the requester needs a central point of contact to minimize confusion and frustration. For the requester-analyst interface to work smoothly, it must function as if it is a one-to-one interaction. This article addresses the pitfalls of the requester-analyst interaction and provides suggestions for improving the quality of the analytical product through the requester-analyst interface

  5. Grafting of protein-protein binding sites

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    A strategy for grafting protein-protein binding sites is described. Firstly, key interaction residues at the interface of ligand protein to be grafted are identified and suitable positions in scaffold protein for grafting these key residues are sought. Secondly, the scaffold proteins are superposed onto the ligand protein based on the corresponding Ca and Cb atoms. The complementarity between the scaffold protein and the receptor protein is evaluated and only matches with high score are accepted. The relative position between scaffold and receptor proteins is adjusted so that the interface has a reasonable packing density. Then the scaffold protein is mutated to corresponding residues in ligand protein at each candidate position. And the residues having bad steric contacts with the receptor proteins, or buried charged residues not involved in the formation of any salt bridge are mutated. Finally, the mutated scaffold protein in complex with receptor protein is co-minimized by Charmm. In addition, we deduce a scoring function to evaluate the affinity between mutated scaffold protein and receptor protein by statistical analysis of rigid binding data sets.

  6. HomPPI: a class of sequence homology based protein-protein interface prediction methods

    Directory of Open Access Journals (Sweden)

    Dobbs Drena

    2011-06-01

    Full Text Available Abstract Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i NPS-HomPPI (Non partner-specific HomPPI, which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii PS-HomPPI (Partner-specific HomPPI, which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of

  7. Yeast two hybrid analyses reveal novel binary interactions between human cytomegalovirus-encoded virion proteins.

    Directory of Open Access Journals (Sweden)

    Aaron To

    Full Text Available Human cytomegalovirus (HCMV is the largest human herpesvirus and its virion contains many viral encoded proteins found in the capsid, tegument, and envelope. In this study, we carried out a yeast two-hybrid (YTH analysis to study potential binary interactions among 56 HCMV-encoded virion proteins. We have tested more than 3,500 pairwise combinations for binary interactions in the YTH analysis, and identified 79 potential interactions that involve 37 proteins. Forty five of the 79 interactions were also identified in human cells expressing the viral proteins by co-immunoprecipitation (co-IP experiments. To our knowledge, 58 of the 79 interactions revealed by YTH analysis, including those 24 that were also identified in co-IP experiments, have not been reported before. Novel potential interactions were found between viral capsid proteins and tegument proteins, between tegument proteins, between tegument proteins and envelope proteins, and between envelope proteins. Furthermore, both the YTH and co-IP experiments have identified 9, 7, and 5 interactions that were involved with UL25, UL24, and UL89, respectively, suggesting that these "hub" proteins may function as the organizing centers for connecting multiple virion proteins in the mature virion and for recruiting other virion proteins during virion maturation and assembly. Our study provides a framework to study potential interactions between HCMV proteins and investigate the roles of protein-protein interactions in HCMV virion formation or maturation process.

  8. Sequence and structural features of binding site residues in protein-protein complexes: comparison with protein-nucleic acid complexes

    OpenAIRE

    Selvaraj S; Jayaram B; Saranya N; Gromiha M; Fukui Kazuhiko

    2011-01-01

    Abstract Background Protein-protein interactions are important for several cellular processes. Understanding the mechanism of protein-protein recognition and predicting the binding sites in protein-protein complexes are long standing goals in molecular and computational biology. Methods We have developed an energy based approach for identifying the binding site residues in protein–protein complexes. The binding site residues have been analyzed with sequence and structure based parameters such...

  9. A protein-protein binding assay using coated microtitre plates: increased throughput, reproducibility and speed compared to bead-based assays.

    Science.gov (United States)

    Craig, Tim J; Ciufo, Leonora F; Morgan, Alan

    2004-07-30

    Protein-protein interactions, and the factors affecting them, are of fundamental importance to all biological systems. Surface plasmon resonance (SPR) and isothermal titration calorimetry (ITR) are powerful methods for assaying such interactions, but are expensive to implement. In contrast, bead-based pull-down assays using affinity tags such as glutathione-S-transferase (GST), require no specialist equipment. As a result, such assays are the most popular method for analysing protein-protein interactions, despite being time-consuming and prone to variability. In respect of these problems, we have modified this form of binding assay, using glutathione-coated 96-well plates rather than glutathione-Sepharose beads to bind the primary bait protein. Quantitation of bound protein utilises ELISA for purified proteins and scintillation counting for in vitro translated proteins, rather than the SDS-PAGE-based detection methods used in traditional bead-based assays. These modifications result in an approximately 10-fold increase in the number of samples that can be assayed daily, and allow results to be obtained within hours as opposed to days. We validate the modified assay by analysing the equilibrium binding of Munc18 and syntaxin, and also demonstrate that association and dissociation kinetics may be measured using this approach. The method we describe is generally applicable to any protein-protein interaction assay based on affinity tags and is amenable to automation, and so should benefit a wide range of biochemical research. PMID:15236910

  10. Statistical analyses of hydrophobic interactions: A mini-review

    CERN Document Server

    Pratt, L R; Rempe, Susan B

    2016-01-01

    This review focuses on the striking recent progress in solving for hydrophobic interactions between small inert molecules. We discuss several new understandings. Firstly, the _inverse _temperature phenomenology of hydrophobic interactions, _i.e., strengthening of hydrophobic bonds with increasing temperature, is decisively exhibited by hydrophobic interactions between atomic-scale hard sphere solutes in water. Secondly, inclusion of attractive interactions associated with atomic-size hydrophobic reference cases leads to substantial, non-trivial corrections to reference results for purely repulsive solutes. Hydrophobic bonds are _weakened by adding solute dispersion forces to treatment of reference cases. The classic statistical mechanical theory for those corrections is not accurate in this application, but molecular quasi-chemical theory shows promise. Finally, because of the masking roles of excluded volume and attractive interactions, comparisons that do not discriminate the different possibilities face an...

  11. Scenario evolution: Interaction between event tree construction and numerical analyses

    International Nuclear Information System (INIS)

    Construction of well-posed scenarios for the range of conditions possible at any proposed repository site is a critical first step to assessing total system performance. Even tree construction is the method that is being used to develop potential failure scenarios for the proposed nuclear waste repository at Yucca Mountain. An event tree begins with an initial event or condition. Subsequent events are listed in a sequence, leading eventually to release of radionuclides to the accessible environment. Ensuring the validity of the scenarios requires iteration between problems constructed using scenarios contained in the event tree sequence, experimental results, and numerical analyses. Details not adequately captured within the tree initially may become more apparent as a result of analyses. To illustrate this process, we discuss the iterations used to develop numerical analyses for PACE-90 using basaltic igneous activity and human-intrusion event trees

  12. Scenario evolution: Interaction between event tree construction and numerical analyses

    International Nuclear Information System (INIS)

    Construction of well-posed scenarios for the range of conditions possible at any proposed repository site is a critical first step to assessing total system performance. Event tree construction is the method that is being used to develop potential failure scenarios for the proposed nuclear waste repository at Yucca Mountain. An event tree begins with an initial event or condition. Subsequent events are listed in a sequence, leading eventually to release of radionuclides to the accessible environment. Ensuring the validity of the scenarios requires iteration between problems constructed using scenarios contained in the event tree sequence, experimental results, and numerical analyses. Details not adequately captured within the tree initially may become more apparent as a result of analyses. To illustrate this process, the authors discuss the iterations used to develop numerical analyses for PACE-90 (Performance Assessment Calculational Exercises) using basaltic igneous activity and human-intrusion event trees

  13. Measuring musical interaction: analysing communication in embodied musical behaviour

    OpenAIRE

    Moran, Nicola

    2007-01-01

    This thesis addresses the ubiquity and necessity of embodied interaction to musical activity, using video analysis to observe communication in musical events. Through the specific study of classical North Indian instrumental duo performance, the thesis examines how processes of social interaction may inform human musical activity, using a combined methodology of ethnographic study and quantitative data analysis of original video-recordings. Proposing a pragmatic approach to the study of the m...

  14. Magneto-nanosensor platform for probing low-affinity protein-protein interactions and identification of a low-affinity PD-L1/PD-L2 interaction.

    Science.gov (United States)

    Lee, Jung-Rok; Bechstein, Daniel J B; Ooi, Chin Chun; Patel, Ashka; Gaster, Richard S; Ng, Elaine; Gonzalez, Lino C; Wang, Shan X

    2016-01-01

    Substantial efforts have been made to understand the interactions between immune checkpoint receptors and their ligands targeted in immunotherapies against cancer. To carefully characterize the complete network of interactions involved and the binding affinities between their extracellular domains, an improved kinetic assay is needed to overcome limitations with surface plasmon resonance (SPR). Here, we present a magneto-nanosensor platform integrated with a microfluidic chip that allows measurement of dissociation constants in the micromolar-range. High-density conjugation of magnetic nanoparticles with prey proteins allows multivalent receptor interactions with sensor-immobilized bait proteins, more closely mimicking natural-receptor clustering on cells. The platform has advantages over traditional SPR in terms of insensitivity of signal responses to pH and salinity, less consumption of proteins and better sensitivities. Using this platform, we characterized the binding affinities of the PD-1-PD-L1/PD-L2 co-inhibitory receptor system, and discovered an unexpected interaction between the two known PD-1 ligands, PD-L1 and PD-L2. PMID:27447090

  15. BWR Mark II ex-vessel corium interaction analyses

    International Nuclear Information System (INIS)

    This report describes the results of a series of studies conducted to investigate the behavior of core debris within a BWR Mark II containment. These studies focused on the interaction of core debris with concrete and steel structures (downcomers and inpedestal floor drains) within the drywell, the transport of debris through these drains and downcomers into the wetwell, and on debris-water reactions within the wetwell. Estimates of the conditions under which debris would penetrate the in-pedestal drain lines, the time-dependent behavior of the debris within the drain lines, and the amount of debris which might enter the suppression pool via these drain lines are provided. An assessment of the conditions under which the upper lip of the downcomers would be expected to fail (i.e. melt) due to exposure to hot core debris is presented. Finally, the unique characteristics of debris water interactions in Mark II containments are discussed, the existing knowledge base regarding core-concrete debris-water interactions is summarized, and an evaluation of the applicability of the MELCOR 1.80 code's debris-water interaction model to BWR Mark II's is presented

  16. Directed Evolution of a Cyclized Peptoid-Peptide Chimera against a Cell-Free Expressed Protein and Proteomic Profiling of the Interacting Proteins to Create a Protein-Protein Interaction Inhibitor.

    Science.gov (United States)

    Kawakami, Takashi; Ogawa, Koji; Hatta, Tomohisa; Goshima, Naoki; Natsume, Tohru

    2016-06-17

    N-alkyl amino acids are useful building blocks for the in vitro display evolution of ribosomally synthesized peptides because they can increase the proteolytic stability and cell permeability of these peptides. However, the translation initiation substrate specificity of nonproteinogenic N-alkyl amino acids has not been investigated. In this study, we screened various N-alkyl amino acids and nonamino carboxylic acids for translation initiation with an Escherichia coli reconstituted cell-free translation system (PURE system) and identified those that efficiently initiated translation. Using seven of these efficiently initiating acids, we next performed in vitro display evolution of cyclized peptidomimetics against an arbitrarily chosen model human protein (β-catenin) cell-free expressed from its cloned cDNA (HUPEX) and identified a novel β-catenin-binding cyclized peptoid-peptide chimera. Furthermore, by a proteomic approach using direct nanoflow liquid chromatography-tandem mass spectrometry (DNLC-MS/MS), we successfully identified which protein-β-catenin interaction is inhibited by the chimera. The combination of in vitro display evolution of cyclized N-alkyl peptidomimetics and in vitro expression of human proteins would be a powerful approach for the high-speed discovery of diverse human protein-targeted cyclized N-alkyl peptidomimetics. PMID:27010125

  17. Toward a unified method for analysing and teaching Human Robot Interaction

    DEFF Research Database (Denmark)

    Dinesen, Jens Vilhelm

    This abstract aims to present key aspect of a future paper, which outlines the ongoing development ofa unified method for analysing and teaching Human-Robot-Interaction. The paper will propose a novel method for analysing both HRI, interaction with other forms of technologies and fellow humans...

  18. The complex becomes more complex: protein-protein interactions of SnRK1 with DUF581 family proteins provide a framework for cell- and stimulus type-specific SnRK1 signaling in plants

    Directory of Open Access Journals (Sweden)

    Madlen eNietzsche

    2014-02-01

    Full Text Available In plants, SNF1-related kinase (SnRK1 responds to the availability of carbohydrates as well as to environmental stresses by down-regulating ATP consuming biosynthetic processes, while stimulating energy-generating catabolic reactions through gene expression and post-transcriptional regulation. The functional SnRK1 complex is a heterotrimer where the catalytic alpha subunit associates with a regulatory beta subunit and an activating gamma subunit. Several different metabolites as well as the hormone abscisic acid (ABA have been shown to modulate SnRK1 activity in a cell- and stimulus-type specific manner. It has been proposed that tissue- or stimulus-specific expression of adapter proteins mediating SnRK1 regulation can at least partly explain the differences observed in SnRK1 signaling. By using yeast two-hybrid and in planta bi-molecular fluorescence complementation assays we were able to demonstrate that proteins containing the domain of unknown function (DUF 581 could interact with both isoforms of the SnRK1 alpha subunit (AKIN10/11 of Arabidopsis. A structure/function analysis suggests that the DUF581 is a generic SnRK1 interaction module and co-expression with DUF581 proteins in plant cells leads to reallocation of the kinase to specific regions within the nucleus. Yeast two-hybrid analyses suggest that SnRK1 and DUF581 proteins can share common interaction partners inside the nucleus. The analysis of available microarray data implies that expression of the 19 members of the DUF581 encoding gene family in Arabidopsis is differentially regulated by hormones and environmental cues, indicating specialized functions of individual family members. We hypothesize that DUF581 proteins could act as mediators conferring tissue- and stimulus-type specific differences in SnRK1 regulation.

  19. Bound water at protein-protein interfaces: partners, roles and hydrophobic bubbles as a conserved motif.

    Directory of Open Access Journals (Sweden)

    Mostafa H Ahmed

    Full Text Available BACKGROUND: There is a great interest in understanding and exploiting protein-protein associations as new routes for treating human disease. However, these associations are difficult to structurally characterize or model although the number of X-ray structures for protein-protein complexes is expanding. One feature of these complexes that has received little attention is the role of water molecules in the interfacial region. METHODOLOGY: A data set of 4741 water molecules abstracted from 179 high-resolution (≤ 2.30 Å X-ray crystal structures of protein-protein complexes was analyzed with a suite of modeling tools based on the HINT forcefield and hydrogen-bonding geometry. A metric termed Relevance was used to classify the general roles of the water molecules. RESULTS: The water molecules were found to be involved in: a (bridging interactions with both proteins (21%, b favorable interactions with only one protein (53%, and c no interactions with either protein (26%. This trend is shown to be independent of the crystallographic resolution. Interactions with residue backbones are consistent for all classes and account for 21.5% of all interactions. Interactions with polar residues are significantly more common for the first group and interactions with non-polar residues dominate the last group. Waters interacting with both proteins stabilize on average the proteins' interaction (-0.46 kcal mol(-1, but the overall average contribution of a single water to the protein-protein interaction energy is unfavorable (+0.03 kcal mol(-1. Analysis of the waters without favorable interactions with either protein suggests that this is a conserved phenomenon: 42% of these waters have SASA ≤ 10 Å(2 and are thus largely buried, and 69% of these are within predominantly hydrophobic environments or "hydrophobic bubbles". Such water molecules may have an important biological purpose in mediating protein-protein interactions.

  20. Structural basis of a rationally rewired protein-protein interface critical to bacterial signaling.

    Science.gov (United States)

    Podgornaia, Anna I; Casino, Patricia; Marina, Alberto; Laub, Michael T

    2013-09-01

    Two-component signal transduction systems typically involve a sensor histidine kinase that specifically phosphorylates a single, cognate response regulator. This protein-protein interaction relies on molecular recognition via a small set of residues in each protein. To better understand how these residues determine the specificity of kinase-substrate interactions, we rationally rewired the interaction interface of a Thermotoga maritima two-component system, HK853-RR468, to match that found in a different two-component system, Escherichia coli PhoR-PhoB. The rewired proteins interacted robustly with each other, but no longer interacted with the parent proteins. Analysis of the crystal structures of the wild-type and mutant protein complexes and a systematic mutagenesis study reveal how individual mutations contribute to the rewiring of interaction specificity. Our approach and conclusions have implications for studies of other protein-protein interactions and protein evolution and for the design of novel protein interfaces. PMID:23954504

  1. Computational Study for Protein-Protein Docking Using Global Optimization and Empirical Potentials

    Directory of Open Access Journals (Sweden)

    Kyoungrim Lee

    2008-01-01

    Full Text Available Protein-protein interactions are important for biochemical processes in biological systems. The 3D structure of the macromolecular complex resulting from the protein-protein association is a very useful source to understand its specific functions. This work focuses on computational study for protein-protein docking, where the individually crystallized structures of interacting proteins are treated as rigid, and the conformational space generated by the two interacting proteins is explored extensively. The energy function consists of intermolecular electrostatic potential, desolvation free energy represented by empirical contact potential, and simple repulsive energy terms. The conformational space is six dimensional, represented by translational vectors and rotational angles formed between two interacting proteins. The conformational sampling is carried out by the search algorithms such as simulated annealing (SA, conformational space annealing (CSA, and CSA combined with SA simulations (combined CSA/SA. Benchmark tests are performed on a set of 18 protein-protein complexes selected from various protein families to examine feasibility of these search methods coupled with the energy function above for protein docking study.

  2. Sequence and structural features of binding site residues in protein-protein complexes: comparison with protein-nucleic acid complexes

    Directory of Open Access Journals (Sweden)

    Selvaraj S

    2011-10-01

    Full Text Available Abstract Background Protein-protein interactions are important for several cellular processes. Understanding the mechanism of protein-protein recognition and predicting the binding sites in protein-protein complexes are long standing goals in molecular and computational biology. Methods We have developed an energy based approach for identifying the binding site residues in protein–protein complexes. The binding site residues have been analyzed with sequence and structure based parameters such as binding propensity, neighboring residues in the vicinity of binding sites, conservation score and conformational switching. Results We observed that the binding propensities of amino acid residues are specific for protein-protein complexes. Further, typical dipeptides and tripeptides showed high preference for binding, which is unique to protein-protein complexes. Most of the binding site residues are highly conserved among homologous sequences. Our analysis showed that 7% of residues changed their conformations upon protein-protein complex formation and it is 9.2% and 6.6% in the binding and non-binding sites, respectively. Specifically, the residues Glu, Lys, Leu and Ser changed their conformation from coil to helix/strand and from helix to coil/strand. Leu, Ser, Thr and Val prefer to change their conformation from strand to coil/helix. Conclusions The results obtained in this study will be helpful for understanding and predicting the binding sites in protein-protein complexes.

  3. Insights into protein-protein interaction by free energy calculation for human MCL-1 with its BH3 α-helix complex%MCL-1及其BH3螺旋结合自由能计算研究蛋白-蛋白相互作用原理

    Institute of Scientific and Technical Information of China (English)

    刘广; 李良; 赵润宁; 陈杭; 李丹; 韩聚广

    2012-01-01

    MCL-1蛋白是细胞增殖和分化的一个关键调控因子.使用MM-PBSA方法预测MCL-1蛋白与其野生型和碳氢化合物钉子修饰的BH3多肽形成的2个复合物的结合自由能.结果表明,碳氢化合物钉子对多肽与MCL-1的亲和力影响有限;并利用自由能分解(BFED)计算部分残基的能量贡献.疏水效应是稳定复合物结构的主要因素,它同时被额外的静电相互作用强化.该研究在原子水平上探究蛋白-蛋白相互作用机理,提供了新的癌症治疗候选药物.%MM-PBSA approach is applied to evaluate the binding affinities for the MCL-1 complexes with the wild-type and hydrocarbon-stapled MCL-1 BH3 peptides.The hydrophobic effect is the main contribution to the stabilization. Moreover, the interactions are reinforced by additional electrostatic interactions.This study gives insight into protein-protein interaction mechanism at the atomic level.

  4. SPR and electrochemical analyses of interactions between CYP3A4 or 3A5 and cytochrome b5

    Science.gov (United States)

    Gnedenko, O. V.; Yablokov, E. O.; Usanov, S. A.; Mukha, D. V.; Sergeev, G. V.; Bulko, T. V.; Kuzikov, A. V.; Moskaleva, N. E.; Shumyantseva, V. V.; Ivanov, A. S.; Archakov, A. I.

    2014-02-01

    The combination of SPR biosensor with electrochemical analysis was used for the study of protein-protein interaction between cytochromes CYP3A4 or 3А5 and cytochromes b5: the microsomal, mitochondrial forms of this protein, and 2 ≪chimeric≫ proteins. Kinetic constants of CYP3A4 and CYP3А5 complex formation with cytochromes b5 were determined by the SPR biosensor. Essential distinction between CYP3A4 and CYP3A5 was observed upon their interactions with mitochondrial cytochrome b5. The electrochemical analysis of CYP3A4, CYP3A5, and cytochromes b5 immobilized on screen printed graphite electrodes modified with membranous matrix revealed that these proteins have very close reduction potentials -0.435 to -0.350 V (vs. Ag/AgCl).

  5. Immunoassay for Visualization of Protein-Protein Interactions on Ni-Nitrilotriacetate Support: Example of a Laboratory Exercise with Recombinant Heterotrimeric G[alpha][subscript i2][beta][subscript 1[gamma]2] Tagged by Hexahistidine from sf9 Cells

    Science.gov (United States)

    Bavec, Aljosa

    2004-01-01

    We have developed an "in vitro assay" for following the interaction between the [alpha][subscript i2] subunit and [beta][subscript 1[gamma]2] dimer from sf9 cells. This method is suitable for education purposes because it is easy, reliable, nonexpensive, can be applied for a big class of 20 students, and avoid the commonly used kinetic approach,…

  6. Exploring the Interaction Natures in Plutonyl (VI) Complexes with Topological Analyses of Electron Density.

    Science.gov (United States)

    Du, Jiguang; Sun, Xiyuan; Jiang, Gang

    2016-01-01

    The interaction natures between Pu and different ligands in several plutonyl (VI) complexes are investigated by performing topological analyses of electron density. The geometrical structures in both gaseous and aqueous phases are obtained with B3LYP functional, and are generally in agreement with available theoretical and experimental results when combined with all-electron segmented all-electron relativistic contracted (SARC) basis set. The Pu- O y l bond orders show significant linear dependence on bond length and the charge of oxygen atoms in plutonyl moiety. The closed-shell interactions were identified for Pu-Ligand bonds in most complexes with quantum theory of atoms in molecules (QTAIM) analyses. Meanwhile, we found that some Pu-Ligand bonds, like Pu-OH(-), show weak covalent. The interactive nature of Pu-ligand bonds were revealed based on the interaction quantum atom (IQA) energy decomposition approach, and our results indicate that all Pu-Ligand interactions is dominated by the electrostatic attraction interaction as expected. Meanwhile it is also important to note that the quantum mechanical exchange-correlation contributions can not be ignored. By means of the non-covalent interaction (NCI) approach it has been found that some weak and repulsion interactions existed in plutonyl(VI) complexes, which can not be distinguished by QTAIM, can be successfully identified. PMID:27077844

  7. Exploring the Interaction Natures in Plutonyl (VI Complexes with Topological Analyses of Electron Density

    Directory of Open Access Journals (Sweden)

    Jiguang Du

    2016-04-01

    Full Text Available The interaction natures between Pu and different ligands in several plutonyl (VI complexes are investigated by performing topological analyses of electron density. The geometrical structures in both gaseous and aqueous phases are obtained with B3LYP functional, and are generally in agreement with available theoretical and experimental results when combined with all-electron segmented all-electron relativistic contracted (SARC basis set. The Pu– O y l bond orders show significant linear dependence on bond length and the charge of oxygen atoms in plutonyl moiety. The closed-shell interactions were identified for Pu-Ligand bonds in most complexes with quantum theory of atoms in molecules (QTAIM analyses. Meanwhile, we found that some Pu–Ligand bonds, like Pu–OH−, show weak covalent. The interactive nature of Pu–ligand bonds were revealed based on the interaction quantum atom (IQA energy decomposition approach, and our results indicate that all Pu–Ligand interactions is dominated by the electrostatic attraction interaction as expected. Meanwhile it is also important to note that the quantum mechanical exchange-correlation contributions can not be ignored. By means of the non-covalent interaction (NCI approach it has been found that some weak and repulsion interactions existed in plutonyl(VI complexes, which can not be distinguished by QTAIM, can be successfully identified.

  8. DECK: Distance and environment-dependent, coarse-grained, knowledge-based potentials for protein-protein docking

    Directory of Open Access Journals (Sweden)

    Vakser Ilya A

    2011-07-01

    Full Text Available Abstract Background Computational approaches to protein-protein docking typically include scoring aimed at improving the rank of the near-native structure relative to the false-positive matches. Knowledge-based potentials improve modeling of protein complexes by taking advantage of the rapidly increasing amount of experimentally derived information on protein-protein association. An essential element of knowledge-based potentials is defining the reference state for an optimal description of the residue-residue (or atom-atom pairs in the non-interaction state. Results The study presents a new Distance- and Environment-dependent, Coarse-grained, Knowledge-based (DECK potential for scoring of protein-protein docking predictions. Training sets of protein-protein matches were generated based on bound and unbound forms of proteins taken from the DOCKGROUND resource. Each residue was represented by a pseudo-atom in the geometric center of the side chain. To capture the long-range and the multi-body interactions, residues in different secondary structure elements at protein-protein interfaces were considered as different residue types. Five reference states for the potentials were defined and tested. The optimal reference state was selected and the cutoff effect on the distance-dependent potentials investigated. The potentials were validated on the docking decoys sets, showing better performance than the existing potentials used in scoring of protein-protein docking results. Conclusions A novel residue-based statistical potential for protein-protein docking was developed and validated on docking decoy sets. The results show that the scoring function DECK can successfully identify near-native protein-protein matches and thus is useful in protein docking. In addition to the practical application of the potentials, the study provides insights into the relative utility of the reference states, the scope of the distance dependence, and the coarse-graining of

  9. Identification of AML-1 and the (8;21) translocation protein (AML-1/ETO) as sequence-specific DNA-binding proteins: the runt homology domain is required for DNA binding and protein-protein interactions.

    OpenAIRE

    Meyers, S; Downing, J R; Hiebert, S W

    1993-01-01

    The AML1 gene on chromosome 21 is disrupted in the (8;21)(q22;q22) translocation associated with acute myelogenous leukemia and encodes a protein with a central 118-amino-acid domain with 69% homology to the Drosophila pair-rule gene, runt. We demonstrate that AML-1 is a DNA-binding protein which specifically interacts with a sequence belonging to the group of enhancer core motifs, TGT/cGGT. Electrophoretic mobility shift analysis of cell extracts identified two AML-1-containing protein-DNA c...

  10. Regulation of ryanodine receptor RyR2 by protein-protein interactions: prediction of a PKA binding site on the N-terminal domain of RyR2 and its relation to disease causing mutations [v1; ref status: indexed, http://f1000r.es/4tw

    Directory of Open Access Journals (Sweden)

    Belinda Nazan Walpoth

    2015-01-01

    Full Text Available Protein-protein interactions are the key processes responsible for signaling and function in complex networks. Determining the correct binding partners and predicting the ligand binding sites in the absence of experimental data require predictive models. Hybrid models that combine quantitative atomistic calculations with statistical thermodynamics formulations are valuable tools for bioinformatics predictions. We present a hybrid prediction and analysis model for determining putative binding partners and interpreting the resulting correlations in the yet functionally uncharacterized interactions of the ryanodine RyR2 N-terminal domain. Using extensive docking calculations and libraries of hexameric peptides generated from regulator proteins of the RyR2 channel, we show that the residues 318-323 of protein kinase A, PKA, have a very high affinity for the N-terminal of RyR2. Using a coarse grained Elastic Net Model, we show that the binding site lies at the end of a pathway of evolutionarily conserved residues in RyR2. The two disease causing mutations are also on this path. The program for the prediction of the energetically responsive residues by the Elastic Net Model is freely available on request from the corresponding author.

  11. 4,6-Diphenylpyridines as Promising Novel Anti-Influenza Agents Targeting the PA-PB1 Protein-Protein Interaction: Structure-Activity Relationships Exploration with the Aid of Molecular Modeling.

    Science.gov (United States)

    Trist, Iuni M L; Nannetti, Giulio; Tintori, Cristina; Fallacara, Anna Lucia; Deodato, Davide; Mercorelli, Beatrice; Palù, Giorgio; Wijtmans, Maikel; Gospodova, Tzveta; Edink, Ewald; Verheij, Mark; de Esch, Iwan; Viteva, Lilia; Loregian, Arianna; Botta, Maurizio

    2016-03-24

    Influenza is an infectious disease that represents an important public health burden, with high impact on the global morbidity, mortality, and economy. The poor protection and the need of annual updating of the anti-influenza vaccine, added to the rapid emergence of viral strains resistant to current therapy make the need for antiviral drugs with novel mechanisms of action compelling. In this regard, the viral RNA polymerase is an attractive target that allows the design of selective compounds with reduced risk of resistance. In previous studies we showed that the inhibition of the polymerase acidic protein-basic protein 1 (PA-PB1) interaction is a promising strategy for the development of anti-influenza agents. Starting from the previously identified 3-cyano-4,6-diphenyl-pyridines, we chemically modified this scaffold and explored its structure-activity relationships. Noncytotoxic compounds with both the ability of disrupting the PA-PB1 interaction and antiviral activity were identified, and their mechanism of target binding was clarified with molecular modeling simulations. PMID:26924568

  12. A Framework for Analysing Driver Interactions with Semi-Autonomous Vehicles

    Directory of Open Access Journals (Sweden)

    Siraj Shaikh

    2012-12-01

    Full Text Available Semi-autonomous vehicles are increasingly serving critical functions in various settings from mining to logistics to defence. A key characteristic of such systems is the presence of the human (drivers in the control loop. To ensure safety, both the driver needs to be aware of the autonomous aspects of the vehicle and the automated features of the vehicle built to enable safer control. In this paper we propose a framework to combine empirical models describing human behaviour with the environment and system models. We then analyse, via model checking, interaction between the models for desired safety properties. The aim is to analyse the design for safe vehicle-driver interaction. We demonstrate the applicability of our approach using a case study involving semi-autonomous vehicles where the driver fatigue are factors critical to a safe journey.

  13. 基于蛋白质互作知识的生物学通路扩充新方法%A novel biological pathway expansion method based on the knowledge of protein-protein interactions

    Institute of Scientific and Technical Information of China (English)

    赵小蕾; 左晓宇; 覃继恒; 梁岩; 张乃尊; 栾奕昭; 饶绍奇

    2014-01-01

    生物学通路被广泛应用于基因功能学研究,但现有的生物学通路知识并不完善,仍需进一步扩充.生物信息学预测为通路扩充提供了一种有效且经济的途径.文章提出了一种融合蛋白质-蛋白质互作知识以及Gene Ontology(GO)数据库信息进行基因通路预测的新方法.首先选取目标基因在蛋白质-蛋白质互作层面上的邻居所在的Kyoto Encyclopedia of Genes and Genomes(KEGG)通路为候选通路,然后通过检验候选通路中的基因是否在与目标基因关联的GO节点富集来判断目标基因的通路归属.分别利用Human Protein Reference Database(HPRD)和Biological General Repository for Interaction Datasets(BioGRID)数据库中的蛋白质-蛋白质互作信息进行预测.结果表明,在两套数据中,随着互作邻居个数的增加,预测的平均准确率(在所有目标基因注释的通路中被成功预测的比例)及相对准确率(在至少有一个注释通路被成功预测的基因集中,所有注释通路均被预测正确的基因所占的比例)均呈现上升趋势.当互作邻居个数达到22时,预测的平均准确率分别达到96.2%(HPRD)和96.3%(BioGRID),而相对准确率分别为93.3%(HPRD)和84.1%(BioGRID).进一步利用新版数据库对旧版数据库中被更新的89个基因进行验证,至少有一个更新通路被预测正确的基因有50个,其中43个基因的更新通路被完全正确预测,相对准确率为86.0%.这些结果显示该方法是一种可靠且有效的通路扩充方法.

  14. A frame signature matrix for analysing and comparing interaction design behaviour

    OpenAIRE

    Blyth, Richard; Schadewitz, Nicole; Sharp, Helen; Woodroffe, Mark; Rajah, Dino; Turugare, Ranganai

    2012-01-01

    Protocol studies are an established method to investigate design behaviour. In the context of a project to investigate novice interaction design (ID) behaviour across protocols and cultures, we found that existing design behaviour analysis frameworks did not provide reliable results. This paper describes the development of a new approach to analyse and compare ID behaviour using verbal protocols. We augment Schön’s basic design and reflection cycle with construction of a frame signature matri...

  15. PPIRank - an advanced method for ranking protein-protein interations in TAP/MS data

    OpenAIRE

    Sun, Xiaoyun; Hong, Pengyu; Kulkarni, Meghana; Kwon, Young; Perrimon, Norbert

    2013-01-01

    Background: Tandem affinity purification coupled with mass-spectrometry (TAP/MS) analysis is a popular method for the identification of novel endogenous protein-protein interactions (PPIs) in large-scale. Computational analysis of TAP/MS data is a critical step, particularly for high-throughput datasets, yet it remains challenging due to the noisy nature of TAP/MS data. Results: We investigated several major TAP/MS data analysis methods for identifying PPIs, and developed an advanced method, ...

  16. Computational modelling of protein/protein and protein/DNA docking.

    OpenAIRE

    Moont, G.

    2005-01-01

    The docking problem is to start with unbound conformations for the components of a complex, and computationally model a near-native structure for the complex. This thesis describes work in developing computer programs to tackle both protein/protein and protein/DNA docking. Empirical pair potential functions are generated from datasets of residue/residue interactions. A scoring function was parameterised and then used to screen possible complexes, generated by the global search computer algori...

  17. Unintended consequences? Water molecules at biological and crystallographic protein-protein interfaces.

    Science.gov (United States)

    Ahmed, Mostafa H; Habtemariam, Mesay; Safo, Martin K; Scarsdale, J Neel; Spyrakis, Francesca; Cozzini, Pietro; Mozzarelli, Andrea; Kellogg, Glen E

    2013-12-01

    The importance of protein-protein interactions (PPIs) is becoming increasingly appreciated, as these interactions lie at the core of virtually every biological process. Small molecule modulators that target PPIs are under exploration as new therapies. One of the greatest obstacles faced in crystallographically determining the 3D structures of proteins is coaxing the proteins to form "artificial" PPIs that lead to uniform crystals suitable for X-ray diffraction. This work compares interactions formed naturally, i.e., "biological", with those artificially formed under crystallization conditions or "non-biological". In particular, a detailed analysis of water molecules at the interfaces of high-resolution (≤2.30 Å) X-ray crystal structures of protein-protein complexes, where 140 are biological protein-protein complex structures and 112 include non-biological protein-protein interfaces, was carried out using modeling tools based on the HINT forcefield. Surprisingly few and relatively subtle differences were observed between the two types of interfaces: (i) non-biological interfaces are more polar than biological interfaces, yet there is better organized hydrogen bonding at the latter; (ii) biological associations rely more on water-mediated interactions with backbone atoms compared to non-biological associations; (iii) aromatic/planar residues play a larger role in biological associations with respect to water, and (iv) Lys has a particularly large role at non-biological interfaces. A support vector machines (SVMs) classifier using descriptors from this study was devised that was able to correctly classify 84% of the two interface types. PMID:24076743

  18. Mathematical Analyses for the Influence of Soil Conditions and Nutrient Interactions on Cotton Yields

    Institute of Scientific and Technical Information of China (English)

    ZHANGJIANHUI; HUCHANGQING; 等

    1996-01-01

    The influence of soil chemical properties and soil nutrition on cotton yields was studied by means of establishing mathematical models.The nultivarate quadratic regression equations developed by a stepwise regression method not only presented the single effect of soil factors but also displayed the interaction(synergistic or antagonistic) of soil nutrients.The effect of individual factor and the way of nutrient interaction were further analysed by the path analysis method.The results showed that among major factors affecting cotton yields,there existed the interactions between macronutrients(available P× available K),and between macronutrients and microelements(N×Zn,P×Mo,P×Cu,P×Zn,K×Mo)besides the single effect of soil pH,total P ,available Cu and available Zn.

  19. Protein-Protein Interactions at the Adrenergic Receptors

    OpenAIRE

    Cotecchia, Susanna; Stanasila, Laura; Diviani, Dario

    2012-01-01

    The adrenergic receptors are among the best characterized G protein-coupled receptors (GPCRs) and knowledge on this receptor family has provided several important paradigms about GPCR function and regulation. One of the most recent paradigms initially supported by studies on adrenergic receptors is that both βarrestins and G protein-coupled receptors themselves can act as scaffolds binding a variety of proteins and this can result in growing complexity of the receptor-mediated cellular effect...

  20. Targeting FAK using inhibitors of Protein-Protein Interactions

    OpenAIRE

    Philippe Rond?

    2015-01-01

    The Focal Adhesion Kinase (FAK) is involved in many aspects of the metastatic process including adhesion, migration, and invasion. Indeed, overexpression, hyperphosphorylation and/or elevated activity of FAK have been described in a variety of human cancers. Thus, the development of FAK antagonists as anti-cancer therapy, led to several small inhibitors of FAK kinase function that are currently undergoing clinical trials. FAK is a ubiquitously expressed non-receptor cytoplasmic tyrosine kinas...

  1. Modulation of opioid receptor function by protein-protein interactions

    OpenAIRE

    Alfaras-Melainis, Konstantinos; Gomes, Ivone; Rozenfeld, Raphael; Zachariou, Venetia; Devi, Lakshmi,

    2009-01-01

    Opioid receptors, MORP, DORP and KORP, belong to the family A of G protein coupled receptors (GPCR), and have been found to modulate a large number of physiological functions, including mood, stress, appetite, nociception and immune responses. Exogenously applied opioid alkaloids produce analgesia, hedonia and addiction. Addiction is linked to alterations in function and responsiveness of all three opioid receptors in the brain. Over the last few years, a large number of studies identified pr...

  2. PROTEIN-PROTEIN INTERACTIONS IN CASEIN MICELLE STRUCTURE

    Science.gov (United States)

    Historically, the central dogma of structural biology is the Anfinsen hypothesis: the linear primary sequence of amino acids of a protein codes for specific secondary structural elements which in turn lead to tertiary structural elements through protein folding and complex higher order systems throu...

  3. Protein-Protein Interfaces Mimics and Inhibitors Design for Cancers Caused by the disruption of HDAC-3

    Directory of Open Access Journals (Sweden)

    K. Rajaganapathy

    2015-03-01

    Full Text Available Protein-Protein interactions are deregulated or disrupted; it’s a new target for an anti-cancer agent development. In this work, the protein-protein interfaces mimics on a small molecule inhibitors of a molecular combinatorial ligand library (as a similar structure of protein-protein interfaces was designed for disruption of NcoRSIN3- HDAC3 complexes. And molecular docking study was performed with Schrodinger-Maestro-9.3.5-Version, the designed five Ligands was shown good binding interactions and their docking score was around -11.9, As a result of five ligand of a novel analogue is showing superior anti- cancerous histone deacetylase inhibitor caused by the disruption of HDAC-3.

  4. Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

    KAUST Repository

    Oliva, Romina

    2015-07-01

    In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

  5. Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

    Directory of Open Access Journals (Sweden)

    Romina Oliva

    2015-07-01

    Full Text Available In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

  6. Geomechanical analyses to investigate wellbore/mine interactions in the Potash Enclave of Southeastern New Mexico.

    Energy Technology Data Exchange (ETDEWEB)

    Ehgartner, Brian L.; Bean, James E. (Sandia Staffing Alliance, LLC, Albuquerque, NM); Arguello, Jose Guadalupe, Jr.; Stone, Charles Michael

    2010-04-01

    Geomechanical analyses have been performed to investigate potential mine interactions with wellbores that could occur in the Potash Enclave of Southeastern New Mexico. Two basic models were used in the study; (1) a global model that simulates the mechanics associated with mining and subsidence and (2) a wellbore model that examines the resulting interaction impacts on the wellbore casing. The first model is a 2D approximation of a potash mine using a plane strain idealization for mine depths of 304.8 m (1000 ft) and 609.6 m (2000 ft). A 3D wellbore model then considers the impact of bedding plane slippage across single and double cased wells cemented through the Salado formation. The wellbore model establishes allowable slippage to prevent casing yield.

  7. Site response - a critical problem in soil-structure interaction analyses for embedded structures

    International Nuclear Information System (INIS)

    Soil-structure interaction analyses for embedded structures must necessarily be based on a knowledge of the manner in which the soil would behave in the absence of any structure - that is on a knowledge and understanding of the spatial distribution of motions in the ground within the depth of embedment of the structure. The nature of these spatial variations is discussed and illustrated by examples of recorded motions. It is shown that both the amplitude of peak acceleration and the form of the acceleration response spectrum for earthquake motions will necessarily vary with depth and failure to take these variations into account may introduce an unwarranted degree of conservatism into the soil-structure interaction analysis procedure

  8. Composition of Overlapping Protein-Protein and Protein-Ligand Interfaces.

    Directory of Open Access Journals (Sweden)

    Ruzianisra Mohamed

    Full Text Available Protein-protein interactions (PPIs play a major role in many biological processes and they represent an important class of targets for therapeutic intervention. However, targeting PPIs is challenging because often no convenient natural substrates are available as starting point for small-molecule design. Here, we explored the characteristics of protein interfaces in five non-redundant datasets of 174 protein-protein (PP complexes, and 161 protein-ligand (PL complexes from the ABC database, 436 PP complexes, and 196 PL complexes from the PIBASE database and a dataset of 89 PL complexes from the Timbal database. In all cases, the small molecule ligands must bind at the respective PP interface. We observed similar amino acid frequencies in all three datasets. Remarkably, also the characteristics of PP contacts and overlapping PL contacts are highly similar.

  9. Quaternary re-arrangement analysed by spectral enhancement: the interaction of a sporulation repressor with its antagonist.

    Science.gov (United States)

    Scott, D J; Leejeerajumnean, S; Brannigan, J A; Lewis, R J; Wilkinson, A J; Hoggett, J G

    1999-11-12

    The protein/protein interaction between SinI and SinR has been studied by analytical ultracentrifugation and gel electrophoresis in an attempt to understand how these proteins contribute to developmental control of sporulation in Bacillus subtilis. SinR was found to be tetrameric, while SinI was found to exist as monomers and dimers in a rapidly reversible equilibrium. Labelling of SinR by incorporating the tryptophan analogue 7-azatryptophan (7AW) into the protein in place of tryptophan shifts the UV absorbance spectrum, thus allowing selective monitoring of 7AWSinR at 315 nm using the UV absorption optics of the analytical ultracentrifuge. Selective monitoring of SinR in mixtures of SinR and SinI enables the binding and stoichiometry of the interaction to be investigated quantitatively and unambiguously. We demonstrate that the oligomeric forms of SinR and SinI re-arrange to form a tight 1:1 SinR:SinI complex, with no stable intermediate species. A fragment of SinR, SinR(1-69), which contains only the DNA-binding domain, was found to be monomeric, showing that the protein appears not to oligomerise in a similar manner to the Cro repressor, a protein with which it shares a marked structural similarity. PMID:10547280

  10. The application of fluid structure interaction techniques within finite element analyses of water filled transport flasks

    International Nuclear Information System (INIS)

    Historically, finite-element (FE) analyses of water-filled transport flasks and their payloads have been carried out assuming a dry environment, mainly due to lack of robust fluid structure interaction (FSI) modelling techniques. Recent years have seen significant improvements in FSI techniques. These FSI techniques have been used to investigate the effects of assuming a wet environment for the regulatory drop test within a recent Rolls-Royce Naval Marine licence renewal application. This paper will present the FSI capabilities available within various FE codes. The required structural aspects of the FE codes will also be discussed, in particular material models, as these also influence the final code selection. Two explicit dynamic FE codes were finally identified, LS-DYNA, which was used in the extant dry analyses, and RADIOSS, which was used to provided additional confidence in the FSI calculations. Fluid flow and pressure vary significantly during an impact and the effects on the contents become complex when water is incorporated into the flask analyses. Therefore, a verification and validation (V and V) exercise was undertaken to underpin the FSI techniques eventually used. Modelling a fluid environment within the entire flask to capture the explicit effects of fluid on a complex structure is impractical. A good understanding of the FSI techniques and assumptions regarding the fluid boundaries is therefore required for a representative FSI model. A number of V and V problems are presented which test key features required for analysing the payload in a water environment. In conclusion the paper will discuss FSI technology, lessons learnt, limitations of FSI techniques and further possible applications. (author)

  11. Yeast Interacting Proteins Database: YJL199C, YJL199C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available d in closely related Saccharomyces species; protein detected in large-scale protein-protein interaction studies...cies; protein detected in large-scale protein-protein interaction studies Rows with this prey as prey (4) Ro...n; not conserved in closely related Saccharomyces species; protein detected in large-scale protein-protein interaction studies... species; protein detected in large-scale protein-protein interaction studies Rows with this prey as prey Ro

  12. Analysing Buyers' and Sellers' Strategic Interactions in Marketplaces: An Evolutionary Game Theoretic Approach

    Science.gov (United States)

    Vytelingum, Perukrishnen; Cliff, Dave; Jennings, Nicholas R.

    We develop a new model to analyse the strategic behaviour of buyers and sellers in market mechanisms. In particular, we wish to understand how the different strategies they adopt affect their economic efficiency in the market and to understand the impact of these choices on the overall efficiency of the marketplace. To this end, we adopt a two-population evolutionary game theoretic approach, where we consider how the behaviours of both buyers and sellers evolve in marketplaces. In so doing, we address the shortcomings of the previous state-of-the-art analytical model that assumes that buyers and sellers have to adopt the same mixed strategy in the market. Finally, we apply our model in one of the most common market mechanisms, the Continuous Double Auction, and demonstrate how it allows us to provide new insights into the strategic interactions of such trading agents.

  13. Comparing of Normal Stress Distribution in Static and Dynamic Soil-Structure Interaction Analyses

    Science.gov (United States)

    Kholdebarin, Alireza; Massumi, Ali; Davoodi, Mohammad; Tabatabaiefar, Hamid Reza

    2008-07-01

    It is important to consider the vertical component of earthquake loading and inertia force in soil-structure interaction analyses. In most circumstances, design engineers are primarily concerned about the analysis of behavior of foundations subjected to earthquake-induced forces transmitted from the bedrock. In this research, a single rigid foundation with designated geometrical parameters located on sandy-clay soil has been modeled in FLAC software with Finite Different Method and subjected to three different vertical components of earthquake records. In these cases, it is important to evaluate effect of footing on underlying soil and to consider normal stress in soil with and without footing. The distribution of normal stress under the footing in static and dynamic states has been studied and compared. This Comparison indicated that, increasing in normal stress under the footing caused by vertical component of ground excitations, has decreased dynamic vertical settlement in comparison with static state.

  14. The simulation of man-machine interaction in NPPs: the system response analyser project

    International Nuclear Information System (INIS)

    In this paper, the ongoing research at Joint Research Centre-Ispra on the simulation of man-machine interaction is reviewed with reference to the past experience of system modelling and to the advances of the technological world. These require the coalescence of mixed disciplines covering the fields of engineering, psychology and sociology. In particular, the complexity of man-machine systems with respect to safety analysis is depicted. The developments and issues in modelling humans and machines are discussed: the possibility of combining them through the System Response Analyser methodology is presented as a balanced to be applied when the objective is the study of safety of systems during abnormal sequences. The three analytical tools which constitute the body of system response analysis namely a quasi-classical simulation of the actual plant, a cognitive model of the operator activities and a driver model, are described. (author)

  15. Analysing context-dependent deviations in interacting with safety-critical systems

    International Nuclear Information System (INIS)

    Mobile technology is penetrating many areas of human life. This implies that the context of use can vary in many respects. We present a method that aims to support designers in managing the complex design space when considering applications with varying contexts and help them to identify solutions that support users in performing their activities while preserving usability and safety. The method is a novel combination of an analysis of both potential deviations in task performance and most suitable information representations based on distributed cognition. The originality of the contribution is in providing a conceptual tool for better understanding the impact of context of use on user interaction in safety-critical domains. In order to present our approach we provide an example in which the implications of introducing new support through mobile devices in a safety-critical system are identified and analysed in terms of potential hazards

  16. Analysing change in music therapy interactions of children with communication difficulties

    Science.gov (United States)

    2016-01-01

    Music therapy has been found to improve communicative behaviours and joint attention in children with autism, but it is unclear what in the music therapy sessions drives those changes. We developed an annotation protocol and tools to accumulate large datasets of music therapy, for analysis of interaction dynamics. Analysis of video recordings of improvisational music therapy sessions focused on simple, unambiguous individual and shared behaviours: movement and facing behaviours, rhythmic activity and musical structures and the relationships between them. To test the feasibility of the protocol, early and late sessions of five client–therapist pairs were annotated and analysed to track changes in behaviours. To assess the reliability and validity of the protocol, inter-rater reliability of the annotation tiers was calculated, and the therapists provided feedback about the relevance of the analyses and results. This small-scale study suggests that there are both similarities and differences in the profiles of client–therapist sessions. For example, all therapists faced the clients most of the time, while the clients did not face back so often. Conversely, only two pairs had an increase in regular pulse from early to late sessions. More broadly, similarity across pairs at a general level is complemented by variation in the details. This perhaps goes some way to reconciling client- and context-specificity on one hand and generalizability on the other. Behavioural characteristics seem to influence each other. For instance, shared rhythmic pulse alternated with mutual facing and the occurrence of shared pulse was found to relate to the musical structure. These observations point towards a framework for looking at change in music therapy that focuses on networks of variables or broader categories. The results suggest that even when starting with simple behaviours, we can trace aspects of interaction and change in music therapy, which are seen as relevant by therapists

  17. Analysing change in music therapy interactions of children with communication difficulties.

    Science.gov (United States)

    Spiro, Neta; Himberg, Tommi

    2016-05-01

    Music therapy has been found to improve communicative behaviours and joint attention in children with autism, but it is unclear what in the music therapy sessions drives those changes. We developed an annotation protocol and tools to accumulate large datasets of music therapy, for analysis of interaction dynamics. Analysis of video recordings of improvisational music therapy sessions focused on simple, unambiguous individual and shared behaviours: movement and facing behaviours, rhythmic activity and musical structures and the relationships between them. To test the feasibility of the protocol, early and late sessions of five client-therapist pairs were annotated and analysed to track changes in behaviours. To assess the reliability and validity of the protocol, inter-rater reliability of the annotation tiers was calculated, and the therapists provided feedback about the relevance of the analyses and results. This small-scale study suggests that there are both similarities and differences in the profiles of client-therapist sessions. For example, all therapists faced the clients most of the time, while the clients did not face back so often. Conversely, only two pairs had an increase in regular pulse from early to late sessions. More broadly, similarity across pairs at a general level is complemented by variation in the details. This perhaps goes some way to reconciling client- and context-specificity on one hand and generalizability on the other. Behavioural characteristics seem to influence each other. For instance, shared rhythmic pulse alternated with mutual facing and the occurrence of shared pulse was found to relate to the musical structure. These observations point towards a framework for looking at change in music therapy that focuses on networks of variables or broader categories. The results suggest that even when starting with simple behaviours, we can trace aspects of interaction and change in music therapy, which are seen as relevant by therapists

  18. Understanding the Flow Physics of Shock Boundary-Layer Interactions Using CFD and Numerical Analyses

    Science.gov (United States)

    Friedlander, David J.

    2013-01-01

    Computational fluid dynamic (CFD) analyses of the University of Michigan (UM) Shock/Boundary-Layer Interaction (SBLI) experiments were performed as an extension of the CFD SBLI Workshop held at the 48th AIAA Aerospace Sciences Meeting in 2010. In particular, the UM Mach 2.75 Glass Tunnel with a semi-spanning 7.75deg wedge was analyzed in attempts to explore key physics pertinent to SBLI's, including thermodynamic and viscous boundary conditions as well as turbulence modeling. Most of the analyses were 3D CFD simulations using the OVERFLOW flow solver, with additional quasi-1D simulations performed with an in house MATLAB code interfacing with the NIST REFPROP code to explore perfect verses non-ideal air. A fundamental exploration pertaining to the effects of particle image velocimetry (PIV) on post-processing data is also shown. Results from the CFD simulations showed an improvement in agreement with experimental data with key contributions including adding a laminar zone upstream of the wedge and the necessity of mimicking PIV particle lag for comparisons. Results from the quasi-1D simulation showed that there was little difference between perfect and non-ideal air for the configuration presented.

  19. Elastoplastic pipe-soil interaction analyses of partially-supported jointed water mains

    Institute of Scientific and Technical Information of China (English)

    Yu SHAO; Tu-qiao ZHANG

    2008-01-01

    Water distribution networks are essential components of water supply systems.The combination of pipe structural deterioration and mechanics leads to the failure of pipelines.A physical model for estimating the pipe failure must include both the pipe deterioration model and mechanics model.Winkler pipe-soil interaction(WPSI),an analytical mechanics model developed by Rajani and Tesfamariam(2004),takes external and internal loads,temperature changes,loss of bedding support,and the elastoplastic effect of soil into consideration.Based on the WPSI model,a method to evaluate the elastic and plastic areas was proposed in the present study.An FEM model based on pipe-soil interaction(PSI)element was used to verify the analytical model.Sensitivity analyses indicate that the soft soil,long pipe and high temperature induced the axial plastic deformation more likely,which,however,may not occur in normal scenarios.The soft soil,pipes in small diameters,long unsupported bedding are prone to form flexural plastic area.The results show that the pipes subjected to the same loads have smaller stresses in the elastoplastic analysis than elastic analysis.The difference,however,is slight.

  20. A unified set-based test with adaptive filtering for gene-environment interaction analyses.

    Science.gov (United States)

    Liu, Qianying; Chen, Lin S; Nicolae, Dan L; Pierce, Brandon L

    2016-06-01

    In genome-wide gene-environment interaction (GxE) studies, a common strategy to improve power is to first conduct a filtering test and retain only the SNPs that pass the filtering in the subsequent GxE analyses. Inspired by two-stage tests and gene-based tests in GxE analysis, we consider the general problem of jointly testing a set of parameters when only a few are truly from the alternative hypothesis and when filtering information is available. We propose a unified set-based test that simultaneously considers filtering on individual parameters and testing on the set. We derive the exact distribution and approximate the power function of the proposed unified statistic in simplified settings, and use them to adaptively calculate the optimal filtering threshold for each set. In the context of gene-based GxE analysis, we show that although the empirical power function may be affected by many factors, the optimal filtering threshold corresponding to the peak of the power curve primarily depends on the size of the gene. We further propose a resampling algorithm to calculate P-values for each gene given the estimated optimal filtering threshold. The performance of the method is evaluated in simulation studies and illustrated via a genome-wide gene-gender interaction analysis using pancreatic cancer genome-wide association data. PMID:26496228