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Sample records for strong protein-protein interaction

  1. 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......, are reported. The aim is to depict how the elucidation of the interplay of structures requires the interplay of methods....

  2. 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...

  3. Evolution of protein-protein interactions

    Indian Academy of Sciences (India)

    Evolution of protein-protein interactions · Our interests in protein-protein interactions · Slide 3 · Slide 4 · Slide 5 · Slide 6 · Slide 7 · Slide 8 · Slide 9 · Slide 10 · Slide 11 · Slide 12 · Slide 13 · Slide 14 · Slide 15 · Slide 16 · Slide 17 · Slide 18 · Slide 19 · Slide 20.

  4. Aquaporin Protein-Protein Interactions

    Directory of Open Access Journals (Sweden)

    Jennifer Virginia Roche

    2017-10-01

    Full Text Available Aquaporins are tetrameric membrane-bound channels that facilitate transport of water and other small solutes across cell membranes. In eukaryotes, they are frequently regulated by gating or trafficking, allowing for the cell to control membrane permeability in a specific manner. Protein–protein interactions play crucial roles in both regulatory processes and also mediate alternative functions such as cell adhesion. In this review, we summarize recent knowledge about aquaporin protein–protein interactions; dividing the interactions into three types: (1 interactions between aquaporin tetramers; (2 interactions between aquaporin monomers within a tetramer (hetero-tetramerization; and (3 transient interactions with regulatory proteins. We particularly focus on the structural aspects of the interactions, discussing the small differences within a conserved overall fold that allow for aquaporins to be differentially regulated in an organism-, tissue- and trigger-specific manner. A deep knowledge about these differences is needed to fully understand aquaporin function and regulation in many physiological processes, and may enable design of compounds targeting specific aquaporins for treatment of human disease.

  5. Ontological visualization of protein-protein interactions

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    Hill David P

    2005-02-01

    Full Text Available Abstract Background Cellular processes require the interaction of many proteins across several cellular compartments. Determining the collective network of such interactions is an important aspect of understanding the role and regulation of individual proteins. The Gene Ontology (GO is used by model organism databases and other bioinformatics resources to provide functional annotation of proteins. The annotation process provides a mechanism to document the binding of one protein with another. We have constructed protein interaction networks for mouse proteins utilizing the information encoded in the GO annotations. The work reported here presents a methodology for integrating and visualizing information on protein-protein interactions. Results GO annotation at Mouse Genome Informatics (MGI captures 1318 curated, documented interactions. These include 129 binary interactions and 125 interaction involving three or more gene products. Three networks involve over 30 partners, the largest involving 109 proteins. Several tools are available at MGI to visualize and analyze these data. Conclusions Curators at the MGI database annotate protein-protein interaction data from experimental reports from the literature. Integration of these data with the other types of data curated at MGI places protein binding data into the larger context of mouse biology and facilitates the generation of new biological hypotheses based on physical interactions among gene products.

  6. Specificity and affinity quantification of protein-protein interactions.

    Science.gov (United States)

    Yan, Zhiqiang; Guo, Liyong; Hu, Liang; Wang, Jin

    2013-05-01

    Most biological processes are mediated by the protein-protein interactions. Determination of the protein-protein structures and insight into their interactions are vital to understand the mechanisms of protein functions. Currently, compared with the isolated protein structures, only a small fraction of protein-protein structures are experimentally solved. Therefore, the computational docking methods play an increasing role in predicting the structures and interactions of protein-protein complexes. The scoring function of protein-protein interactions is the key responsible for the accuracy of the computational docking. Previous scoring functions were mostly developed by optimizing the binding affinity which determines the stability of the protein-protein complex, but they are often lack of the consideration of specificity which determines the discrimination of native protein-protein complex against competitive ones. We developed a scoring function (named as SPA-PP, specificity and affinity of the protein-protein interactions) by incorporating both the specificity and affinity into the optimization strategy. The testing results and comparisons with other scoring functions show that SPA-PP performs remarkably on both predictions of binding pose and binding affinity. Thus, SPA-PP is a promising quantification of protein-protein interactions, which can be implemented into the protein docking tools and applied for the predictions of protein-protein structure and affinity. The algorithm is implemented in C language, and the code can be downloaded from http://dl.dropbox.com/u/1865642/Optimization.cpp.

  7. Intercellular protein-protein interactions at synapses.

    Science.gov (United States)

    Yang, Xiaofei; Hou, Dongmei; Jiang, Wei; Zhang, Chen

    2014-06-01

    Chemical synapses are asymmetric intercellular junctions through which neurons send nerve impulses to communicate with other neurons or excitable cells. The appropriate formation of synapses, both spatially and temporally, is essential for brain function and depends on the intercellular protein-protein interactions of cell adhesion molecules (CAMs) at synaptic clefts. The CAM proteins link pre- and post-synaptic sites, and play essential roles in promoting synapse formation and maturation, maintaining synapse number and type, accumulating neurotransmitter receptors and ion channels, controlling neuronal differentiation, and even regulating synaptic plasticity directly. Alteration of the interactions of CAMs leads to structural and functional impairments, which results in many neurological disorders, such as autism, Alzheimer's disease and schizophrenia. Therefore, it is crucial to understand the functions of CAMs during development and in the mature neural system, as well as in the pathogenesis of some neurological disorders. Here, we review the function of the major classes of CAMs, and how dysfunction of CAMs relates to several neurological disorders.

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

    Directory of Open Access Journals (Sweden)

    Andrew Schoenrock

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

  9. Our interests in protein-protein interactions

    Indian Academy of Sciences (India)

    protein interactions. Evolution of P-P partnerships. Evolution of P-P structures. Evolutionary dynamics of P-P interactions. Dynamics of P-P interaction network. Host-pathogen interactions. CryoEM mapping of gigantic protein assemblies.

  10. 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

  11. Role for protein-protein interaction databases in human genetics.

    Science.gov (United States)

    Pattin, Kristine A; Moore, Jason H

    2009-12-01

    Proteomics and the study of protein-protein interactions are becoming increasingly important in our effort to understand human diseases on a system-wide level. Thanks to the development and curation of protein-interaction databases, up-to-date information on these interaction networks is accessible and publicly available to the scientific community. As our knowledge of protein-protein interactions increases, it is important to give thought to the different ways that these resources can impact biomedical research. In this article, we highlight the importance of protein-protein interactions in human genetics and genetic epidemiology. Since protein-protein interactions demonstrate one of the strongest functional relationships between genes, combining genomic data with available proteomic data may provide us with a more in-depth understanding of common human diseases. In this review, we will discuss some of the fundamentals of protein interactions, the databases that are publicly available and how information from these databases can be used to facilitate genome-wide genetic studies.

  12. 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.

  13. On the role of electrostatics on protein-protein interactions

    Science.gov (United States)

    Zhang, Zhe; Witham, Shawn; Alexov, Emil

    2011-01-01

    The role of electrostatics on protein-protein interactions and binding is reviewed in this article. A brief outline of the computational modeling, in the framework of continuum electrostatics, is presented and basic electrostatic effects occurring upon the formation of the complex are discussed. The role of the salt concentration and pH of the water phase on protein-protein binding free energy is demonstrated and indicates that the increase of the salt concentration tends to weaken the binding, an observation that is attributed to the optimization of the charge-charge interactions across the interface. It is pointed out that the pH-optimum (pH of optimal binding affinity) varies among the protein-protein complexes, and perhaps is a result of their adaptation to particular subcellular compartment. At the end, the similarities and differences between hetero- and homo-complexes are outlined and discussed with respect to the binding mode and charge complementarity. PMID:21572182

  14. On the role of electrostatics in protein-protein interactions

    Science.gov (United States)

    Zhang, Zhe; Witham, Shawn; Alexov, Emil

    2011-06-01

    The role of electrostatics in protein-protein interactions and binding is reviewed in this paper. A brief outline of the computational modeling, in the framework of continuum electrostatics, is presented and the basic electrostatic effects occurring upon the formation of the complex are discussed. The effect of the salt concentration and pH of the water phase on protein-protein binding free energy is demonstrated which indicates that the increase of the salt concentration tends to weaken the binding, an observation that is attributed to the optimization of the charge-charge interactions across the interface. It is pointed out that the pH-optimum (pH of optimal binding affinity) varies among the protein-protein complexes, and perhaps is a result of their adaptation to particular subcellular compartments. The similarities and differences between hetero- and homo-complexes are outlined and discussed with respect to the binding mode and charge complementarity.

  15. Can infrared spectroscopy provide information on protein-protein interactions?

    Science.gov (United States)

    Haris, Parvez I

    2010-08-01

    For most biophysical techniques, characterization of protein-protein interactions is challenging; this is especially true with methods that rely on a physical phenomenon that is common to both of the interacting proteins. Thus, for example, in IR spectroscopy, the carbonyl vibration (1600-1700 cm(-1)) associated with the amide bonds from both of the interacting proteins will overlap extensively, making the interpretation of spectral changes very complicated. Isotope-edited infrared spectroscopy, where one of the interacting proteins is uniformly labelled with (13)C or (13)C,(15)N has been introduced as a solution to this problem, enabling the study of protein-protein interactions using IR spectroscopy. The large shift of the amide I band (approx. 45 cm(-1) towards lower frequency) upon (13)C labelling of one of the proteins reveals the amide I band of the unlabelled protein, enabling it to be used as a probe for monitoring conformational changes. With site-specific isotopic labelling, structural resolution at the level of individual amino acid residues can be achieved. Furthermore, the ability to record IR spectra of proteins in diverse environments means that isotope-edited IR spectroscopy can be used to structurally characterize difficult systems such as protein-protein complexes bound to membranes or large insoluble peptide/protein aggregates. In the present article, examples of application of isotope-edited IR spectroscopy for studying protein-protein interactions are provided.

  16. Protein-protein interactions and cancer: targeting the central dogma.

    Science.gov (United States)

    Garner, Amanda L; Janda, Kim D

    2011-01-01

    Between 40,000 and 200,000 protein-protein interactions have been predicted to exist within the human interactome. As these interactions are of a critical nature in many important cellular functions and their dysregulation is causal of disease, the modulation of these binding events has emerged as a leading, yet difficult therapeutic arena. In particular, the targeting of protein-protein interactions relevant to cancer is of fundamental importance as the tumor-promoting function of several aberrantly expressed proteins in the cancerous state is directly resultant of its ability to interact with a protein-binding partner. Of significance, these protein complexes play a crucial role in each of the steps of the central dogma of molecular biology, the fundamental processes of genetic transmission. With the many important discoveries being made regarding the mechanisms of these genetic process, the identification of new chemical probes are needed to better understand and validate the druggability of protein-protein interactions related to the central dogma. In this review, we provide an overview of current small molecule-based protein-protein interaction inhibitors for each stage of the central dogma: transcription, mRNA splicing and translation. Importantly, through our analysis we have uncovered a lack of necessary probes targeting mRNA splicing and translation, thus, opening up the possibility for expansion of these fields.

  17. Oligomeric protein structure networks: insights into protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Brinda KV

    2005-12-01

    Full Text Available Abstract Background Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues with special emphasis to protein interfaces. Results A variety of interactions such as hydrogen bond, salt bridges, aromatic and hydrophobic interactions, which occur at the interfaces are identified in a consolidated manner as amino acid clusters at the interface, from this study. Moreover, the characterization of the highly connected hub-forming residues at the interfaces and their comparison with the hubs from the non-interface regions and the non-hubs in the interface regions show that there is a predominance of charged interactions at the interfaces. Further, strong and weak interfaces are identified on the basis of the interaction strength between amino acid residues and the sizes of the interface clusters, which also show that many protein interfaces are stronger than their monomeric protein cores. The interface strengths evaluated based on the interface clusters and hubs also correlate well with experimentally determined dissociation constants for known complexes. Finally, the interface hubs identified using the present method correlate very well with experimentally determined hotspots in the interfaces of protein complexes obtained from the Alanine Scanning Energetics database (ASEdb. A few predictions of interface hot

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

    Science.gov (United States)

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

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

    Science.gov (United States)

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

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

    Science.gov (United States)

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

    2002-05-01

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

  1. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Feng, Mei [Department of Physics, Institute of Quantitative Biology, Zhejiang University, Hangzhou 310027 (China); Kang, Hongsuk; Luan, Binquan [Computational Biological Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598 (United States); Yang, Zaixing [Institute of Quantitative Biology and Medicine, SRMP and RAD-X, and Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Soochow University, Suzhou 215123 (China); Zhou, Ruhong, E-mail: ruhong@us.ibm.com [Department of Physics, Institute of Quantitative Biology, Zhejiang University, Hangzhou 310027 (China); Computational Biological Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598 (United States); Department of Chemistry, Columbia University, New York, New York 10027 (United States)

    2016-06-14

    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.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

    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.

  4. Stabilization of protein-protein interaction complexes through small molecules.

    Science.gov (United States)

    Zarzycka, Barbara; Kuenemann, Mélaine A; Miteva, Maria A; Nicolaes, Gerry A F; Vriend, Gert; Sperandio, Olivier

    2016-01-01

    Most of the small molecules that have been identified thus far to modulate protein-protein interactions (PPIs) are inhibitors. Another promising way to interfere with PPI-associated biological processes is to promote PPI stabilization. Even though PPI stabilizers are still scarce, stabilization of PPIs by small molecules is gaining momentum and offers new pharmacological options. Therefore, we have performed a literature survey of PPI stabilization using small molecules. From this, we propose a classification of PPI stabilizers based on their binding mode and the architecture of the complex to facilitate the structure-based design of stabilizers. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

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    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.

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

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    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.

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

    Science.gov (United States)

    Suter, Bernhard; Zhang, Xinmin; Pesce, C Gustavo; Mendelsohn, Andrew R; Dinesh-Kumar, Savithramma P; Mao, Jian-Hua

    2015-01-01

    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.

  8. 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.

  9. Detecting protein-protein interactions in living cells

    DEFF Research Database (Denmark)

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

    2009-01-01

    -terminal of the NMDA receptor and PDZ2 of PSD-95 were fused to green fluorescent protein (GFP) and Renilla luciferase (Rluc) and expressed in COS7 cells. A robust and specific BRET signal was obtained by expression of the appropriate partner proteins and subsequently, the assay was used to evaluate a Tat......The PDZ domain mediated interaction between the NMDA receptor and its intracellular scaffolding protein, PSD-95, is a potential target for treatment of ischemic brain diseases. We have recently developed a number of peptide analogues with improved affinity for the PDZ domains of PSD-95 compared...... 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...

  10. Duchenne Muscular Dystrophy (DMD) Protein-Protein Interaction Mapping.

    Science.gov (United States)

    Rezaei Tavirani, Mostafa; OkHOVATIAN, Farshad; Zamanian Azodi, Mona; Rezaei Tavirani, Majid

    2017-01-01

    Duchenne muscular dystrophy (DMD) is one of the mortal diseases, subjected to study in terms of molecular investigation. In this study, the protein interaction map of this muscle-wasting condition was generated to gain a better knowledge of interactome profile of DMD. Applying Cytoscape and String Database, the protein-protein interaction network was constructed and the gene ontology of the constructed network was analyzed for biological process, molecular function, and cellular component annotations. Among 100 proteins related to DMD, dystrophin, utrophin, caveolin 3, and myogenic differentiation 1 play key roles in DMD network. In addition, the gene ontology analysis showed that regulation processes, kinase activity, and sarcoplasmic reticulum were the highlighted biological processes, molecular function, and cell component enrichments respectively for the proteins related to DMD. The central proteins and the enriched ontologies can be suggested as possible prominent agents in DMD; however, the validation studies may be required.

  11. Human cancer protein-protein interaction network: a structural perspective.

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    Gozde Kar

    2009-12-01

    Full Text Available Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network. The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%. We illustrate the interface related affinity properties of two cancer-related hub

  12. Exploiting amino acid composition for predicting protein-protein interactions.

    Directory of Open Access Journals (Sweden)

    Sushmita Roy

    2009-11-01

    Full Text Available Computational prediction of protein interactions typically use protein domains as classifier features because they capture conserved information of interaction surfaces. However, approaches relying on domains as features cannot be applied to proteins without any domain information. In this paper, we explore the contribution of pure amino acid composition (AAC for protein interaction prediction. This simple feature, which is based on normalized counts of single or pairs of amino acids, is applicable to proteins from any sequenced organism and can be used to compensate for the lack of domain information.AAC performed at par with protein interaction prediction based on domains on three yeast protein interaction datasets. Similar behavior was obtained using different classifiers, indicating that our results are a function of features and not of classifiers. In addition to yeast datasets, AAC performed comparably on worm and fly datasets. Prediction of interactions for the entire yeast proteome identified a large number of novel interactions, the majority of which co-localized or participated in the same processes. Our high confidence interaction network included both well-studied and uncharacterized proteins. Proteins with known function were involved in actin assembly and cell budding. Uncharacterized proteins interacted with proteins involved in reproduction and cell budding, thus providing putative biological roles for the uncharacterized proteins.AAC is a simple, yet powerful feature for predicting protein interactions, and can be used alone or in conjunction with protein domains to predict new and validate existing interactions. More importantly, AAC alone performs at par with existing, but more complex, features indicating the presence of sequence-level information that is predictive of interaction, but which is not necessarily restricted to domains.

  13. Protein-protein interaction based on pairwise similarity

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Peng Liu

    2015-01-01

    Full Text Available 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 network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

  15. The protein-protein interaction-mediated inactivation of PTEN.

    Science.gov (United States)

    De Melo, J; He, L; Tang, D

    2014-01-01

    PTEN (Phosphatase and Tensin homologue deleted on chromosome 10, 10q23.3) is the dominant phosphatase responsible for the dephosphorylation of the 3-position phosphate from the inositol ring of phosphatidylinositol 3,4,5 triphosphate (PIP3), and thereby directly antagonizes the actions mediated by Phosphatidylinositol-3 Kinase (PI3K). PI3K functions in numerous pathways and cellular processes, including tumourigenesis. Therefore, mechanisms regulating PTEN function, either positively or negatively are of great interest not only to oncogenesis but also to other aspects of human health. Since its discovery in 1997, PTEN has been one of the most-heavily studied tumour suppressors and has been the subject of numerous reviews. Most investigations and reviews center on PTEN's function and its regulation. While the regulation of PTEN function via genetic and/or epigenetic mechanisms has been extensively studied, the impact of protein-protein interaction on PTEN function remains less clear. Recent research has revealed that PTEN can be specifically inhibited by its interaction with other proteins, which are collectively termed PTEN-negative regulators (PTENNRs). This review will summarize our current understanding on the protein network that influences PTEN function with a specific focus on PTEN-NRs.

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    Melody G Campbell

    2011-01-01

    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.

  18. Targeting protein-protein interactions for parasite control.

    Directory of Open Access Journals (Sweden)

    Christina M Taylor

    2011-04-01

    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

  19. Quantifying the molecular origins of opposite solvent effects on protein-protein interactions.

    Directory of Open Access Journals (Sweden)

    Vincent Vagenende

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

  20. 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

  1. Testing strong interaction theories

    International Nuclear Information System (INIS)

    Ellis, J.

    1979-01-01

    The author discusses possible tests of the current theories of the strong interaction, in particular, quantum chromodynamics. High energy e + e - interactions should provide an excellent means of studying the strong force. (W.D.L.)

  2. Computational probing protein-protein interactions targeting small molecules.

    Science.gov (United States)

    Wang, Yong-Cui; Chen, Shi-Long; Deng, Nai-Yang; Wang, Yong

    2016-01-15

    With the booming of interactome studies, a lot of interactions can be measured in a high throughput way and large scale datasets are available. It is becoming apparent that many different types of interactions can be potential drug targets. Compared with inhibition of a single protein, inhibition of protein-protein interaction (PPI) is promising to improve the specificity with fewer adverse side-effects. Also it greatly broadens the drug target search space, which makes the drug target discovery difficult. Computational methods are highly desired to efficiently provide candidates for further experiments and hold the promise to greatly accelerate the discovery of novel drug targets. Here, we propose a machine learning method to predict PPI targets in a genomic-wide scale. Specifically, we develop a computational method, named as PrePPItar, to Predict PPIs as drug targets by uncovering the potential associations between drugs and PPIs. First, we survey the databases and manually construct a gold-standard positive dataset for drug and PPI interactions. This effort leads to a dataset with 227 associations among 63 PPIs and 113 FDA-approved drugs and allows us to build models to learn the association rules from the data. Second, we characterize drugs by profiling in chemical structure, drug ATC-code annotation, and side-effect space and represent PPI similarity by a symmetrical S-kernel based on protein amino acid sequence. Then the drugs and PPIs are correlated by Kronecker product kernel. Finally, a support vector machine (SVM), is trained to predict novel associations between drugs and PPIs. We validate our PrePPItar method on the well-established gold-standard dataset by cross-validation. We find that all chemical structure, drug ATC-code, and side-effect information are predictive for PPI target. Moreover, we can increase the PPI target prediction coverage by integrating multiple data sources. Follow-up database search and pathway analysis indicate that our new

  3. Topology-function conservation in protein-protein interaction networks.

    Science.gov (United States)

    Davis, Darren; Yaveroğlu, Ömer Nebil; Malod-Dognin, Noël; Stojmirovic, Aleksandar; Pržulj, Nataša

    2015-05-15

    Proteins underlay the functioning of a cell and the wiring of proteins in protein-protein interaction network (PIN) relates to their biological functions. Proteins with similar wiring in the PIN (topology around them) have been shown to have similar functions. This property has been successfully exploited for predicting protein functions. Topological similarity is also used to guide network alignment algorithms that find similarly wired proteins between PINs of different species; these similarities are used to transfer annotation across PINs, e.g. from model organisms to human. To refine these functional predictions and annotation transfers, we need to gain insight into the variability of the topology-function relationships. For example, a function may be significantly associated with specific topologies, while another function may be weakly associated with several different topologies. Also, the topology-function relationships may differ between different species. To improve our understanding of topology-function relationships and of their conservation among species, we develop a statistical framework that is built upon canonical correlation analysis. Using the graphlet degrees to represent the wiring around proteins in PINs and gene ontology (GO) annotations to describe their functions, our framework: (i) characterizes statistically significant topology-function relationships in a given species, and (ii) uncovers the functions that have conserved topology in PINs of different species, which we term topologically orthologous functions. We apply our framework to PINs of yeast and human, identifying seven biological process and two cellular component GO terms to be topologically orthologous for the two organisms. © The Author 2015. Published by Oxford University Press.

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

    Science.gov (United States)

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

    2011-12-01

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

  5. Categorizing Biases in High-Confidence High-Throughput Protein-Protein Interaction Data Sets*

    Science.gov (United States)

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

    2011-01-01

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

  6. Studying protein-protein interactions via blot overlay/far western blot.

    Science.gov (United States)

    Hall, Randy A

    2015-01-01

    Blot overlay is a useful method for studying protein-protein interactions. This technique involves fractionating proteins on SDS-PAGE, blotting to nitrocellulose or PVDF membrane, and then incubating with a probe of interest. The probe is typically a protein that is radiolabeled, biotinylated, or simply visualized with a specific antibody. When the probe is visualized via antibody detection, this technique is often referred to as "Far Western blot." Many different kinds of protein-protein interactions can be studied via blot overlay, and the method is applicable to screens for unknown protein-protein interactions as well as to the detailed characterization of known interactions.

  7. Studying protein-protein interactions via blot overlay or Far Western blot.

    Science.gov (United States)

    Hall, Randy A

    2004-01-01

    Blot overlay is a useful method for studying protein-protein interactions. This technique involves fractionating proteins on SDS-PAGE, blotting to nitrocellulose or PVDF membrane, and then incubating with a probe of interest. The probe is typically a protein that is radiolabeled, biotinylated, or simply visualized with a specific antibody. When the probe is visualized via antibody detection, this technique is often referred to as "Far Western blot." Many different kinds of protein-protein interactions can be studied via blot overlay, and the method is applicable to screens for unknown protein-protein interactions as well as to the detailed characterization of known interactions.

  8. Inferring domain-domain interactions from protein-protein interactions with formal concept analysis.

    Directory of Open Access Journals (Sweden)

    Susan Khor

    Full Text Available Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains.

  9. Hot-spot analysis for drug discovery targeting protein-protein interactions.

    Science.gov (United States)

    Rosell, Mireia; Fernández-Recio, Juan

    2018-04-01

    Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

  10. A simple dependence between protein evolution rate and the number of protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Hirsh Aaron E

    2003-05-01

    Full Text Available Abstract Background It has been shown for an evolutionarily distant genomic comparison that the number of protein-protein interactions a protein has correlates negatively with their rates of evolution. However, the generality of this observation has recently been challenged. Here we examine the problem using protein-protein interaction data from the yeast Saccharomyces cerevisiae and genome sequences from two other yeast species. Results In contrast to a previous study that used an incomplete set of protein-protein interactions, we observed a highly significant correlation between number of interactions and evolutionary distance to either Candida albicans or Schizosaccharomyces pombe. This study differs from the previous one in that it includes all known protein interactions from S. cerevisiae, and a larger set of protein evolutionary rates. In both evolutionary comparisons, a simple monotonic relationship was found across the entire range of the number of protein-protein interactions. In agreement with our earlier findings, this relationship cannot be explained by the fact that proteins with many interactions tend to be important to yeast. The generality of these correlations in other kingdoms of life unfortunately cannot be addressed at this time, due to the incompleteness of protein-protein interaction data from organisms other than S. cerevisiae. Conclusions Protein-protein interactions tend to slow the rate at which proteins evolve. This may be due to structural constraints that must be met to maintain interactions, but more work is needed to definitively establish the mechanism(s behind the correlations we have observed.

  11. Protein-protein interactions: impact of solvent and effects of fluorination

    OpenAIRE

    Samsonov, Sergey

    2009-01-01

    Proteins have an indispensable role in the cell. They carry out a wide variety of structural, catalytic and signaling functions in all known biological systems. To perform their biological functions, proteins establish interactions with other bioorganic molecules including other proteins. Therefore, protein-protein interactions is one of the central topics in molecular biology. My thesis is devoted to three different topics in the field of protein-protein interactions. The first one focuses o...

  12. The role of electrostatics in 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

    2014-07-07

    Understanding how protein-protein interactions depend on the choice of buffer, salt, ionic strength, and pH is needed to have better control over protein solution behavior. Here, we have characterized the pH and ionic strength dependence of protein-protein interactions in terms of an interaction parameter kD obtained from dynamic light scattering and the osmotic second virial coefficient B22 measured by static light scattering. A simplified protein-protein interaction model based on a Baxter adhesive potential and an electric double layer force is used to separate out the contributions of longer-ranged electrostatic interactions from short-ranged attractive forces. The ionic strength dependence of protein-protein interactions for solutions at pH 6.5 and below can be accurately captured using a Deryaguin-Landau-Verwey-Overbeek (DLVO) potential to describe the double layer forces. In solutions at pH 9, attractive electrostatics occur over the ionic strength range of 5-275 mM. At intermediate pH values (7.25 to 8.5), there is a crossover effect characterized by a nonmonotonic ionic strength dependence of protein-protein interactions, which can be rationalized by the competing effects of long-ranged repulsive double layer forces at low ionic strength and a shorter ranged electrostatic attraction, which dominates above a critical ionic strength. The change of interactions from repulsive to attractive indicates a concomitant change in the angular dependence of protein-protein interaction from isotropic to anisotropic. In the second part of the paper, we show how the Baxter adhesive potential can be used to predict values of kD from fitting to B22 measurements, thus providing a molecular basis for the linear correlation between the two protein-protein interaction parameters.

  13. NatalieQ: A web server for protein-protein interaction network querying

    NARCIS (Netherlands)

    El-Kebir, M.; Brandt, B.W.; Heringa, J.; Klau, G.W.

    2014-01-01

    Background Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks.

  14. NatalieQ: a web server for protein-protein interaction network querying

    NARCIS (Netherlands)

    El-Kebir, M.; Brandt, B.W.; Heringa, J.; Klau, G.W.

    2014-01-01

    Background: Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks.

  15. A scored human protein-protein interaction network to catalyze genomic interpretation

    DEFF Research Database (Denmark)

    Li, Taibo; Wernersson, Rasmus; Hansen, Rasmus B

    2017-01-01

    Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap,......Web_InBioMap, or InWeb_IM) with severalfold more interactions (>500,000) and better functional biological relevance than comparable resources. We illustrate that InWeb_InBioMap enables functional interpretation of >4,700 cancer genomes and genes involved in autism....

  16. 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.

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

    Science.gov (United States)

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

    2015-02-23

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

  18. Emergence of modularity and disassortativity in protein-protein interaction networks.

    Science.gov (United States)

    Wan, Xi; Cai, Shuiming; Zhou, Jin; Liu, Zengrong

    2010-12-01

    In this paper, we present a simple evolution model of protein-protein interaction networks by introducing a rule of small-preference duplication of a node, meaning that the probability of a node chosen to duplicate is inversely proportional to its degree, and subsequent divergence plus nonuniform heterodimerization based on some plausible mechanisms in biology. We show that our model cannot only reproduce scale-free connectivity and small-world pattern, but also exhibit hierarchical modularity and disassortativity. After comparing the features of our model with those of real protein-protein interaction networks, we believe that our model can provide relevant insights into the mechanism underlying the evolution of protein-protein interaction networks. © 2010 American Institute of Physics.

  19. 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...

  20. Analysis of protein-protein interaction networks by means of annotated graph mining algorithms

    NARCIS (Netherlands)

    Rahmani, Hossein

    2012-01-01

    This thesis discusses solutions to several open problems in Protein-Protein Interaction (PPI) networks with the aid of Knowledge Discovery. PPI networks are usually represented as undirected graphs, with nodes corresponding to proteins and edges representing interactions among protein pairs. A large

  1. 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...... 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....

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

    Science.gov (United States)

    Park, Byungkyu; Han, Kyungsook

    2010-01-18

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

  3. 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.

  4. Understanding Protein-Protein Interactions Using Local Structural Features

    DEFF Research Database (Denmark)

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

    2013-01-01

    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...

  5. Studying protein-protein interactions using peptide arrays

    NARCIS (Netherlands)

    Katz, C.; Levy-Beladev, L.; Rotem-Bamberger, S.; Rito, T.; Rudiger, S.G.D.; Friedler, A.

    2010-01-01

    Screening of arrays and libraries of compounds is well-established as a high-throughput method for detecting and analyzing interactions in both biological and chemical systems. Arrays and libraries can be composed from various types of molecules, ranging from small organic compounds to DNA, proteins

  6. Essential multimeric enzymes in kinetoplastid parasites: A host of potentially druggable protein-protein interactions.

    Science.gov (United States)

    Wachsmuth, Leah M; Johnson, Meredith G; Gavenonis, Jason

    2017-06-01

    Parasitic diseases caused by kinetoplastid parasites of the genera Trypanosoma and Leishmania are an urgent public health crisis in the developing world. These closely related species possess a number of multimeric enzymes in highly conserved pathways involved in vital functions, such as redox homeostasis and nucleotide synthesis. Computational alanine scanning of these protein-protein interfaces has revealed a host of potentially ligandable sites on several established and emerging anti-parasitic drug targets. Analysis of interfaces with multiple clustered hotspots has suggested several potentially inhibitable protein-protein interactions that may have been overlooked by previous large-scale analyses focusing solely on secondary structure. These protein-protein interactions provide a promising lead for the development of new peptide and macrocycle inhibitors of these enzymes.

  7. Deciphering peculiar protein-protein interacting modules in Deinococcus radiodurans

    Directory of Open Access Journals (Sweden)

    Barkallah Insaf

    2009-04-01

    Full Text Available Abstract Interactomes of proteins under positive selection from ionizing-radiation-resistant bacteria (IRRB might be a part of the answer to the question as to how IRRB, particularly Deinococcus radiodurans R1 (Deira, resist ionizing radiation. Here, using the Database of Interacting Proteins (DIP and the Protein Structural Interactome (PSI-base server for PSI map, we have predicted novel interactions of orthologs of the 58 proteins under positive selection in Deira and other IRRB, but which are absent in IRSB. Among these, 18 domains and their interactomes have been identified in DNA checkpoint and repair; kinases pathways; energy and nucleotide metabolisms were the important biological processes that were found to be involved. This finding provides new clues to the cellular pathways that can to be important for ionizing-radiation resistance in Deira.

  8. A Mesoscopic Model for Protein-Protein Interactions in Solution

    OpenAIRE

    Lund, Mikael; Jönsson, Bo

    2003-01-01

    Protein self-association may be detrimental in biological systems, but can be utilized in a controlled fashion for protein crystallization. It is hence of considerable interest to understand how factors like solution conditions prevent or promote aggregation. Here we present a computational model describing interactions between protein molecules in solution. The calculations are based on a molecular description capturing the detailed structure of the protein molecule using x-ray or nuclear ma...

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

    Science.gov (United States)

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

    2016-01-01

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

  10. Strong interaction and QFD

    International Nuclear Information System (INIS)

    Ebata, T.

    1981-01-01

    With an assumed weak multiplet structure for bosonic hadrons, which is consistent with the ΔI = 1/2 rule, it is shown that the strong interaction effective hamiltonian is compatible with the weak SU(2) x U(1) gauge transformation. Especially the rho-meson transforms as a triplet under SU(2)sub(w), and this is the origin of the rho-photon analogy. It is also shown that the existence of the non-vanishing Cabibbo angle is a necessary condition for the absence of the exotic hadrons. (orig.)

  11. iPPI-DB: an online database of modulators of protein-protein interactions

    NARCIS (Netherlands)

    Labbe, C.M.; Kuenemann, M.A.; Zarzycka, B.; Vriend, G.; Nicolaes, G.A.; Lagorce, D.; Miteva, M.A.; Villoutreix, B.O.; Sperandio, O.

    2016-01-01

    In order to boost the identification of low-molecular-weight drugs on protein-protein interactions (PPI), it is essential to properly collect and annotate experimental data about successful examples. This provides the scientific community with the necessary information to derive trends about

  12. 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

  13. 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.

  14. What properties characterize the hub proteins of the protein-protein interaction network of Saccharomyces cerevisiae?

    OpenAIRE

    Ekman, Diana; Light, Sara; Bj?rklund, ?sa K; Elofsson, Arne

    2006-01-01

    Background Most proteins interact with only a few other proteins while a small number of proteins (hubs) have many interaction partners. Hub proteins and non-hub proteins differ in several respects; however, understanding is not complete about what properties characterize the hubs and set them apart from proteins of low connectivity. Therefore, we have investigated what differentiates hubs from non-hubs and static hubs (party hubs) from dynamic hubs (date hubs) in the protein-protein interact...

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

    Directory of Open Access Journals (Sweden)

    Sarbottam ePiya

    2014-12-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  17. 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

    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 s...... and with independence of the partner. This information is encoded at the residue level and could be easily incorporated in the initial grid scoring for Fast Fourier Transform rigid-body docking methods.......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...

  18. Evaluation of two dependency parsers on biomedical corpus targeted at protein-protein interactions.

    Science.gov (United States)

    Pyysalo, Sampo; Ginter, Filip; Pahikkala, Tapio; Boberg, Jorma; Järvinen, Jouni; Salakoski, Tapio

    2006-06-01

    We present an evaluation of Link Grammar and Connexor Machinese Syntax, two major broad-coverage dependency parsers, on a custom hand-annotated corpus consisting of sentences regarding protein-protein interactions. In the evaluation, we apply the notion of an interaction subgraph, which is the subgraph of a dependency graph expressing a protein-protein interaction. We measure the performance of the parsers for recovery of individual dependencies, fully correct parses, and interaction subgraphs. For Link Grammar, an open system that can be inspected in detail, we further perform a comprehensive failure analysis, report specific causes of error, and suggest potential modifications to the grammar. We find that both parsers perform worse on biomedical English than previously reported on general English. While Connexor Machinese Syntax significantly outperforms Link Grammar, the failure analysis suggests specific ways in which the latter could be modified for better performance in the domain.

  19. Strong-interaction nonuniversality

    International Nuclear Information System (INIS)

    Volkas, R.R.; Foot, R.; He, X.; Joshi, G.C.

    1989-01-01

    The universal QCD color theory is extended to an SU(3) 1 direct product SU(3) 2 direct product SU(3) 3 gauge theory, where quarks of the ith generation transform as triplets under SU(3)/sub i/ and singlets under the other two factors. The usual color group is then identified with the diagonal subgroup, which remains exact after symmetry breaking. The gauge bosons associated with the 16 broken generators then form two massive octets under ordinary color. The interactions between quarks and these heavy gluonlike particles are explicitly nonuniversal and thus an exploration of their physical implications allows us to shed light on the fundamental issue of strong-interaction universality. Nonuniversality and weak flavor mixing are shown to generate heavy-gluon-induced flavor-changing neutral currents. The phenomenology of these processes is studied, as they provide the major experimental constraint on the extended theory. Three symmetry-breaking scenarios are presented. The first has color breaking occurring at the weak scale, while the second and third divorce the two scales. The third model has the interesting feature of radiatively induced off-diagonal Kobayashi-Maskawa matrix elements

  20. A Gateway-Based System for Fast Evaluation of Protein-Protein Interactions in Bacteria

    Science.gov (United States)

    Wille, Thorsten; Barlag, Britta; Jakovljevic, Vladimir; Hensel, Michael; Sourjik, Victor; Gerlach, Roman G.

    2015-01-01

    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. PMID:25856398

  1. Interaction and localization diversities of global and local hubs in human protein-protein interaction networks.

    Science.gov (United States)

    Kiran, M; Nagarajaram, H A

    2016-08-16

    Hubs, the highly connected nodes in protein-protein interaction networks (PPINs), are associated with several characteristic properties and are known to perform vital roles in cells. We defined two classes of hubs, global (housekeeping) and local (tissue-specific) hubs. These two categories of hubs are distinct from each other with respect to their abundance, structure and function. However, how distinct are the spatial expression pattern and other characteristics of their interacting partners is still not known. Our investigations revealed that the partners of the local hubs compared with those of global hubs are conserved across the tissues in which they are expressed. Partners of local hubs show diverse subcellular localizations as compared with the partners of global hubs. We examined the nature of interacting domains in both categories of hubs and found that they are promiscuous in global hubs but not so in local hubs. Deletion of some of the local and global hubs has an impact on the characteristic path length of the network indicating that those hubs are inter-modular in nature. Our present study has, therefore, shed further light on the characteristic features of the local and global hubs in human PPIN. This knowledge of different topological aspects of hubs with regard to their types and subtypes is essential as it helps in better understanding of roles of hub proteins in various cellular processes under various conditions including those caused by host-pathogen interactions and therefore useful in prioritizing targets for drug design and repositioning.

  2. Using the clustered circular layout as an informative method for visualizing protein-protein interaction networks.

    Science.gov (United States)

    Fung, David C Y; Wilkins, Marc R; Hart, David; Hong, Seok-Hee

    2010-07-01

    The force-directed layout is commonly used in computer-generated visualizations of protein-protein interaction networks. While it is good for providing a visual outline of the protein complexes and their interactions, it has two limitations when used as a visual analysis method. The first is poor reproducibility. Repeated running of the algorithm does not necessarily generate the same layout, therefore, demanding cognitive readaptation on the investigator's part. The second limitation is that it does not explicitly display complementary biological information, e.g. Gene Ontology, other than the protein names or gene symbols. Here, we present an alternative layout called the clustered circular layout. Using the human DNA replication protein-protein interaction network as a case study, we compared the two network layouts for their merits and limitations in supporting visual analysis.

  3. Detection and quantification of protein-protein interactions by far-western blotting.

    Science.gov (United States)

    Jadwin, Joshua A; Mayer, Bruce J; Machida, Kazuya

    2015-01-01

    Far-western blotting is a convenient method to characterize protein-protein interactions, in which protein samples of interest are immobilized on a membrane and then probed with a non-antibody protein. In contrast to western blotting, which uses specific antibodies to detect target proteins, far-western blotting detects proteins on the basis of the presence or absence of binding sites for the protein probe. When specific modular protein binding domains are used as probes, this approach allows characterization of protein-protein interactions involved in biological processes such as signal transduction, including interactions regulated by posttranslational modification. We here describe a rapid and simple protocol for far-western blotting, in which GST-tagged Src homology 2 (SH2) domains are used to probe cellular proteins in a phosphorylation-dependent manner. We also present a batch quantification method that allows for the direct comparison of probe binding patterns.

  4. Cell penetrating peptides to dissect host-pathogen protein-protein interactions in Theileria -transformed leukocytes

    KAUST Repository

    Haidar, Malak

    2017-09-08

    One powerful application of cell penetrating peptides is the delivery into cells of molecules that function as specific competitors or inhibitors of protein-protein interactions. Ablating defined protein-protein interactions is a refined way to explore their contribution to a particular cellular phenotype in a given disease context. Cell-penetrating peptides can be synthetically constrained through various chemical modifications that stabilize a given structural fold with the potential to improve competitive binding to specific targets. Theileria-transformed leukocytes display high PKA activity, but PKAis an enzyme that plays key roles in multiple cellular processes; consequently genetic ablation of kinase activity gives rise to a myriad of confounding phenotypes. By contrast, ablation of a specific kinase-substrate interaction has the potential to give more refined information and we illustrate this here by describing how surgically ablating PKA interactions with BAD gives precise information on the type of glycolysis performed by Theileria-transformed leukocytes. In addition, we provide two other examples of how ablating specific protein-protein interactions in Theileria-infected leukocytes leads to precise phenotypes and argue that constrained penetrating peptides have great therapeutic potential to combat infectious diseases in general.

  5. 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.

  6. A coevolution analysis for identifying protein-protein interactions by Fourier transform

    Science.gov (United States)

    Yin, Changchuan; Yau, Stephen S. -T.

    2017-01-01

    Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI). PMID:28430779

  7. A coevolution analysis for identifying protein-protein interactions by Fourier transform.

    Directory of Open Access Journals (Sweden)

    Changchuan Yin

    Full Text Available Protein-protein interactions (PPIs play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA; however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40. The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI.

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    Sun Zhirong

    2009-12-01

    Full Text Available 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 predict protein functions. Results The domain context similarity can be a useful index to predict protein function similarity. The prediction accuracy of our method in yeast is between 63%-67%, which outperforms the other methods in terms of ROC curves. Conclusion This paper presents a novel protein function prediction method that combines protein domain composition information and PPI networks. Performance evaluations show that this method outperforms existing methods.

  10. A conserved NAD+binding pocket that regulates protein-protein interactions during aging.

    Science.gov (United States)

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

    2017-03-24

    DNA repair is essential for life, yet its efficiency declines with age for reasons that are unclear. Numerous proteins possess Nudix homology domains (NHDs) that have no known function. We show that NHDs are NAD + (oxidized form of nicotinamide adenine dinucleotide) binding domains that regulate protein-protein interactions. The binding of NAD + to the NHD domain of DBC1 (deleted in breast cancer 1) prevents it from inhibiting PARP1 [poly(adenosine diphosphate-ribose) polymerase], a critical DNA repair protein. As mice age and NAD + concentrations decline, DBC1 is increasingly bound to PARP1, causing DNA damage to accumulate, a process rapidly reversed by restoring the abundance of NAD + Thus, NAD + directly regulates protein-protein interactions, the modulation of which may protect against cancer, radiation, and aging. Copyright © 2017, American Association for the Advancement of Science.

  11. A residue level protein-protein interaction model in electrolyte solutions

    Science.gov (United States)

    Song, Xueyu

    2014-03-01

    The osmotic second virial coefficients B2 are directly related to the solubility of protein molecules in electrolyte solutions and can be useful to narrow down the search parameter space of protein crystallization conditions. Using a residue level model of protein-protein interaction in electrolyte solutions B2 of bovine pancreatic trypsin inhibitor and lysozyme in various solution conditions such as salt concentration, pH and temperature are calculated using an extended Fast Multipole Methods in combination with the boundary element formulation. Overall, the calculated B2 are well correlated with the experimental observations for various solution conditions. In combination with our previous work on the binding affinity calculations of protein complexes it is demonstrated that our residue level model can be used as a reliable model to describe protein-protein interaction in solutions.

  12. High-throughput characterization of protein-protein interactions by reprogramming yeast mating.

    Science.gov (United States)

    Younger, David; Berger, Stephanie; Baker, David; Klavins, Eric

    2017-11-14

    High-throughput methods for screening protein-protein interactions enable the rapid characterization of engineered binding proteins and interaction networks. While existing approaches are powerful, none allow quantitative library-on-library characterization of protein interactions in a modifiable extracellular environment. Here, we show that sexual agglutination of Saccharomyces cerevisiae can be reprogrammed to link interaction strength with mating efficiency using synthetic agglutination (SynAg). Validation of SynAg with 89 previously characterized interactions shows a log-linear relationship between mating efficiency and protein binding strength for interactions with K d s ranging from below 500 pM to above 300 μM. Using induced chromosomal translocation to pair barcodes representing binding proteins, thousands of distinct interactions can be screened in a single pot. We demonstrate the ability to characterize protein interaction networks in a modifiable environment by introducing a soluble peptide that selectively disrupts a subset of interactions in a representative network by up to 800-fold. SynAg enables the high-throughput, quantitative characterization of protein-protein interaction networks in a fully defined extracellular environment at a library-on-library scale.

  13. 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.

  14. Distinct Mechanism Evolved for Mycobacterial RNA Polymerase and Topoisomerase I Protein-Protein Interaction.

    Science.gov (United States)

    Banda, Srikanth; Cao, Nan; Tse-Dinh, Yuk-Ching

    2017-09-15

    We report here a distinct mechanism of interaction between topoisomerase I and RNA polymerase in Mycobacterium tuberculosis and Mycobacterium smegmatis that has evolved independently from the previously characterized interaction between bacterial topoisomerase I and RNA polymerase. Bacterial DNA topoisomerase I is responsible for preventing the hyper-negative supercoiling of genomic DNA. The association of topoisomerase I with RNA polymerase during transcription elongation could efficiently relieve transcription-driven negative supercoiling. Our results demonstrate a direct physical interaction between the C-terminal domains of topoisomerase I (TopoI-CTDs) and the β' subunit of RNA polymerase of M. smegmatis in the absence of DNA. The TopoI-CTDs in mycobacteria are evolutionarily unrelated in amino acid sequence and three-dimensional structure to the TopoI-CTD found in the majority of bacterial species outside Actinobacteria, including Escherichia coli. The functional interaction between topoisomerase I and RNA polymerase has evolved independently in mycobacteria and E. coli, with distinctively different structural elements of TopoI-CTD utilized for this protein-protein interaction. Zinc ribbon motifs in E. coli TopoI-CTD are involved in the interaction with RNA polymerase. For M. smegmatis TopoI-CTD, a 27-amino-acid tail that is rich in basic residues at the C-terminal end is responsible for the interaction with RNA polymerase. Overexpression of recombinant TopoI-CTD in M. smegmatis competed with the endogenous topoisomerase I for protein-protein interactions with RNA polymerase. The TopoI-CTD overexpression resulted in decreased survival following treatment with antibiotics and hydrogen peroxide, supporting the importance of the protein-protein interaction between topoisomerase I and RNA polymerase during stress response of mycobacteria. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. 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 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)....

  16. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Beers, Eric [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Brunner, Amy [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Helm, Richard [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Dickerman, Allan [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

    2015-07-31

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

  18. Multi-level machine learning prediction of protein-protein interactions in Saccharomyces cerevisiae.

    Science.gov (United States)

    Zubek, Julian; Tatjewski, Marcin; Boniecki, Adam; Mnich, Maciej; Basu, Subhadip; Plewczynski, Dariusz

    2015-01-01

    Accurate identification of protein-protein interactions (PPI) is the key step in understanding proteins' biological functions, which are typically context-dependent. Many existing PPI predictors rely on aggregated features from protein sequences, however only a few methods exploit local information about specific residue contacts. In this work we present a two-stage machine learning approach for prediction of protein-protein interactions. We start with the carefully filtered data on protein complexes available for Saccharomyces cerevisiae in the Protein Data Bank (PDB) database. First, we build linear descriptions of interacting and non-interacting sequence segment pairs based on their inter-residue distances. Secondly, we train machine learning classifiers to predict binary segment interactions for any two short sequence fragments. The final prediction of the protein-protein interaction is done using the 2D matrix representation of all-against-all possible interacting sequence segments of both analysed proteins. The level-I predictor achieves 0.88 AUC for micro-scale, i.e., residue-level prediction. The level-II predictor improves the results further by a more complex learning paradigm. We perform 30-fold macro-scale, i.e., protein-level cross-validation experiment. The level-II predictor using PSIPRED-predicted secondary structure reaches 0.70 precision, 0.68 recall, and 0.70 AUC, whereas other popular methods provide results below 0.6 threshold (recall, precision, AUC). Our results demonstrate that multi-scale sequence features aggregation procedure is able to improve the machine learning results by more than 10% as compared to other sequence representations. Prepared datasets and source code for our experimental pipeline are freely available for download from: http://zubekj.github.io/mlppi/ (open source Python implementation, OS independent).

  19. Exploiting conformational ensembles in modeling protein-protein interactions on the proteome scale

    Science.gov (United States)

    Kuzu, Guray; Gursoy, Attila; Nussinov, Ruth; Keskin, Ozlem

    2013-01-01

    Cellular functions are performed through protein-protein interactions; therefore, identification of these interactions is crucial for understanding biological processes. Recent studies suggest that knowledge-based approaches are more useful than ‘blind’ docking for modeling at large scales. However, a caveat of knowledge-based approaches is that they treat molecules as rigid structures. The Protein Data Bank (PDB) offers a wealth of conformations. Here, we exploited ensemble of the conformations in predictions by a knowledge-based method, PRISM. We tested ‘difficult’ cases in a docking-benchmark dataset, where the unbound and bound protein forms are structurally different. Considering alternative conformations for each protein, the percentage of successfully predicted interactions increased from ~26% to 66%, and 57% of the interactions were successfully predicted in an ‘unbiased’ scenario, in which data related to the bound forms were not utilized. If the appropriate conformation, or relevant template interface, is unavailable in the PDB, PRISM could not predict the interaction successfully. The pace of the growth of the PDB promises a rapid increase of ensemble conformations emphasizing the merit of such knowledge-based ensemble strategies for higher success rates in protein-protein interaction predictions on an interactome-scale. We constructed the structural network of ERK interacting proteins as a case study. PMID:23590674

  20. PPI layouts: BioJS components for the display of Protein-Protein Interactions.

    Science.gov (United States)

    Salazar, Gustavo A; Meintjes, Ayton; Mulder, Nicola

    2014-01-01

    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. http://github.com/biojs/biojs; http://dx.doi.org/10.5281/zenodo.7753.

  1. 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.

  2. 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

    The dopamine transporter (DAT) plays a key role in regulating dopaminergic signalling in the brain by mediating rapid clearance of dopamine from the synaptic clefts. The psychostimulatory actions of cocaine and amphetamine are primarily the result of a direct interaction of these compounds with DAT...... 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...

  3. NatalieQ: a web server for protein-protein interaction network querying.

    Science.gov (United States)

    El-Kebir, Mohammed; Brandt, Bernd W; Heringa, Jaap; Klau, Gunnar W

    2014-04-01

    Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks. We recently developed Natalie, which computes high-quality network alignments via advanced methods from combinatorial optimization. Here, we present NatalieQ, a web server for topology-based alignment of a specified query protein-protein interaction network to a selected target network using the Natalie algorithm. By incorporating similarity at both the sequence and the network level, we compute alignments that allow for the transfer of functional annotation as well as for the prediction of missing interactions. We illustrate the capabilities of NatalieQ with a biological case study involving the Wnt signaling pathway. We show that topology-based network alignment can produce results complementary to those obtained by using sequence similarity alone. We also demonstrate that NatalieQ is able to predict putative interactions. The server is available at: http://www.ibi.vu.nl/programs/natalieq/.

  4. Phylogenetic tree information aids supervised learning for predicting protein-protein interaction based on distance matrices

    Directory of Open Access Journals (Sweden)

    Liao Li

    2007-01-01

    Full Text Available Abstract Background Protein-protein interactions are critical for cellular functions. Recently developed computational approaches for predicting protein-protein interactions utilize co-evolutionary information of the interacting partners, e.g., correlations between distance matrices, where each matrix stores the pairwise distances between a protein and its orthologs from a group of reference genomes. Results We proposed a novel, simple method to account for some of the intra-matrix correlations in improving the prediction accuracy. Specifically, the phylogenetic species tree of the reference genomes is used as a guide tree for hierarchical clustering of the orthologous proteins. The distances between these clusters, derived from the original pairwise distance matrix using the Neighbor Joining algorithm, form intermediate distance matrices, which are then transformed and concatenated into a super phylogenetic vector. A support vector machine is trained and tested on pairs of proteins, represented as super phylogenetic vectors, whose interactions are known. The performance, measured as ROC score in cross validation experiments, shows significant improvement of our method (ROC score 0.8446 over that of using Pearson correlations (0.6587. Conclusion We have shown that the phylogenetic tree can be used as a guide to extract intra-matrix correlations in the distance matrices of orthologous proteins, where these correlations are represented as intermediate distance matrices of the ancestral orthologous proteins. Both the unsupervised and supervised learning paradigms benefit from the explicit inclusion of these intermediate distance matrices, and particularly so in the latter case, which offers a better balance between sensitivity and specificity in the prediction of protein-protein interactions.

  5. Strong interaction phenomenology

    International Nuclear Information System (INIS)

    Giffon, M.

    1989-01-01

    A brief review of high energy hadronic data (Part I)is followed by an introduction to the standard (Weinberg Salam Glashow) model of electroweak interactions and its extension to the hadrons (Part II). Rudiments of QCD and of the parton model area given in Part III together with a quick review of the spectroscopy of heavy flavours whereas Part IV is devoted to the introduction to deep inelastic scattering and to the so-called EMC effects. (author)

  6. Macromolecular crowding enhances the binding of superoxide dismutase to xanthine oxidase: implications for protein-protein interactions in intracellular environments.

    Science.gov (United States)

    Zhou, Yu-Ling; Liao, Jun-Ming; Chen, Jie; Liang, Yi

    2006-01-01

    Physiological medium constitutes a crowded environment that serves as the field of action for protein-protein interaction in vivo. Measuring protein-protein interaction in crowded solutions can mimic this environment. Here we report the application of fluorescence spectroscopy and resonant mirror biosensor to investigate the interactions of bovine milk xanthine oxidase and bovine erythrocyte copper, zinc-superoxide dismutase in crowded solutions. Four nonspecific high molecular mass crowding agents, poly(ethylene glycol) 2000 and 20,000, Ficoll 70, and dextran 70, and one low molecular mass compound, glycerol, are used. Superoxide dismutase shows a strong and macromolecular crowding agent concentration-dependent binding affinity to xanthine oxidase. Addition of high concentrations of such high molecular mass crowding agents increases the binding constant remarkably and thus stabilizes superoxide dismutase activity, compared to those in the absence of crowding agents. In contrast, glycerol has little effect on the binding constant and decreases superoxide dismutase activity over the same concentration range. Such a pattern suggests that the enhancing effects of polymers and polysaccharides on the binding are due to macromolecular crowding. Taken together, these results indicate that macromolecular crowding enhances the binding of superoxide dismutase to xanthine oxidase and is favorable to the function of superoxide dismutase.

  7. Exploiting Expert Knowledge of Protein-Protein Interactions in a Computational Evolution System for Detecting Epistasis

    Science.gov (United States)

    Pattin, Kristine A.; Payne, Joshua L.; Hill, Douglas P.; Caldwell, Thomas; Fisher, Jonathan M.; Moore, Jason H.

    The etiology of common human disease often involves a complex genetic architecture, where numerous points of genetic variation interact to influence disease susceptibility. Automating the detection of such epistatic genetic risk factors poses a major computational challenge, as the number of possible gene-gene interactions increases combinatorially with the number of sequence variations. Previously, we addressed this challenge with the development of a computational evolution system (CES) that incorporates greater biological realism than traditional artificial evolution methods. Our results demonstrated that CES is capable of efficiently navigating these large and rugged epistatic landscapes toward the discovery of biologically meaningful genetic models of disease predisposition. Further, we have shown that the efficacy of CES is improved dramatically when the system is provided with statistical expert knowledge. We anticipate that biological expert knowledge, such as genetic regulatory or protein-protein interaction maps, will provide complementary information, and further improve the ability of CES to model the genetic architectures of common human disease. The goal of this study is to test this hypothesis, utilizing publicly available protein-protein interaction information. We show that by incorporating this source of expert knowledge, the system is able to identify functional interactions that represent more concise models of disease susceptibility with improved accuracy. Our ability to incorporate biological knowledge into learning algorithms is an essential step toward the routine use of methods such as CES for identifying genetic risk factors for common human diseases.

  8. An assessment of machine and statistical learning approaches to inferring networks of protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Browne Fiona

    2006-12-01

    Full Text Available Protein-protein interactions (PPI play a key role in many biological systems. Over the past few years, an explosion in availability of functional biological data obtained from high-throughput technologies to infer PPI has been observed. However, results obtained from such experiments show high rates of false positives and false negatives predictions as well as systematic predictive bias. Recent research has revealed that several machine and statistical learning methods applied to integrate relatively weak, diverse sources of large-scale functional data may provide improved predictive accuracy and coverage of PPI. In this paper we describe the effects of applying different computational, integrative methods to predict PPI in Saccharomyces cerevisiae. We investigated the predictive ability of combining different sets of relatively strong and weak predictive datasets. We analysed several genomic datasets ranging from mRNA co-expression to marginal essentiality. Moreover, we expanded an existing multi-source dataset from S. cerevisiae by constructing a new set of putative interactions extracted from Gene Ontology (GO- driven annotations in the Saccharomyces Genome Database. Different classification techniques: Simple Naive Bayesian (SNB, Multilayer Perceptron (MLP and K-Nearest Neighbors (KNN were evaluated. Relatively simple classification methods (i.e. less computing intensive and mathematically complex, such as SNB, have been proven to be proficient at predicting PPI. SNB produced the “highest” predictive quality obtaining an area under Receiver Operating Characteristic (ROC curve (AUC value of 0.99. The lowest AUC value of 0.90 was obtained by the KNN classifier. This assessment also demonstrates the strong predictive power of GO-driven models, which offered predictive performance above 0.90 using the different machine learning and statistical techniques. As the predictive power of single-source datasets became weaker MLP and SNB performed

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

    Directory of Open Access Journals (Sweden)

    Alexandra Traister

    2016-06-01

    Full Text Available 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: http://www.ebi.ac.uk/pride/archive/projects/PXD001053. The functional role of identified ILK interactions in cardiomyocyte function and arrhythmia were subsequently confirmed in human iPSC-cardiomyocytes.

  10. 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.

  11. Differential variation patterns between hubs and bottlenecks in human protein-protein interaction networks.

    Science.gov (United States)

    Pang, Erli; Hao, Yu; Sun, Ying; Lin, Kui

    2016-12-01

    The identification, description and understanding of protein-protein networks are important in cell biology and medicine, especially for the study of system biology where the focus concerns the interaction of biomolecules. Hubs and bottlenecks refer to the important proteins of a protein interaction network. Until now, very little attention has been paid to differentiate these two protein groups. By integrating human protein-protein interaction networks and human genome-wide variations across populations, we described the differences between hubs and bottlenecks in this study. Our findings showed that similar to interspecies, hubs and bottlenecks changed significantly more slowly than non-hubs and non-bottlenecks. To distinguish hubs from bottlenecks, we extracted their special members: hub-non-bottlenecks and non-hub-bottlenecks. The differences between these two groups represent what is between hubs and bottlenecks. We found that the variation rate of hubs was significantly lower than that of bottlenecks. In addition, we verified that stronger constraint is exerted on hubs than on bottlenecks. We further observed fewer non-synonymous sites on the domains of hubs than on those of bottlenecks and different molecular functions between them. Based on these results, we conclude that in recent human history, different variation patterns exist in hubs and bottlenecks in protein interaction networks. By revealing the difference between hubs and bottlenecks, our results might provide further insights in the relationship between evolution and biological structure.

  12. 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.

  13. NETAL: a new graph-based method for global alignment of protein-protein interaction networks.

    Science.gov (United States)

    Neyshabur, Behnam; Khadem, Ahmadreza; Hashemifar, Somaye; Arab, Seyed Shahriar

    2013-07-01

    The interactions among proteins and the resulting networks of such interactions have a central role in cell biology. Aligning these networks gives us important information, such as conserved complexes and evolutionary relationships. Although there have been several publications on the global alignment of protein networks; however, none of proposed methods are able to produce a highly conserved and meaningful alignment. Moreover, time complexity of current algorithms makes them impossible to use for multiple alignment of several large networks together. We present a novel algorithm for the global alignment of protein-protein interaction networks. It uses a greedy method, based on the alignment scoring matrix, which is derived from both biological and topological information of input networks to find the best global network alignment. NETAL outperforms other global alignment methods in terms of several measurements, such as Edge Correctness, Largest Common Connected Subgraphs and the number of common Gene Ontology terms between aligned proteins. As the running time of NETAL is much less than other available methods, NETAL can be easily expanded to multiple alignment algorithm. Furthermore, NETAL overpowers all other existing algorithms in term of performance so that the short running time of NETAL allowed us to implement it as the first server for global alignment of protein-protein interaction networks. Binaries supported on linux are freely available for download at http://www.bioinf.cs.ipm.ir/software/netal. Supplementary data are available at Bioinformatics online.

  14. 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. .

  15. 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.

  16. Detection of protein complex from protein-protein interaction network using Markov clustering

    International Nuclear Information System (INIS)

    Ochieng, P J; Kusuma, W A; Haryanto, T

    2017-01-01

    Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks. (paper)

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

    Science.gov (United States)

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

    2009-04-22

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

  18. Investigation of the pH-dependence of dye-doped protein-protein interactions.

    Science.gov (United States)

    Nudelman, Roman; Gloukhikh, Ekaterina; Rekun, Antonina; Richter, Shachar

    2016-11-01

    Proteins can dramatically change their conformation under environmental conditions such as temperature and pH. In this context, Glycoprotein's conformational determination is challenging. This is due to the variety of domains which contain rich chemical characters existing within this complex. Here we demonstrate a new, straightforward and efficient technique that uses the pH-dependent properties of dyes-doped Pig Gastric Mucin (PGM) for predicting and controlling protein-protein interaction and conformation. We utilize the PGM as natural host matrix which is capable of dynamically changing its conformational shape and adsorbing hydrophobic and hydrophilic dyes under different pH conditions and investigate and control the fluorescent properties of these composites in solution. It is shown at various pH conditions, a large variety of light emission from these complexes such as red, green and white is obtained. This phenomenon is explained by pH-dependent protein folding and protein-protein interactions that induce different emission spectra which are mediated and controlled by means of dye-dye interactions and surrounding environment. This process is used to form the technologically challenging white light-emitting liquid or solid coating for LED devices. © 2016 The Protein Society.

  19. 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.

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

    Science.gov (United States)

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

    2010-01-01

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

  1. Small-molecule stabilization of the p53 - 14-3-3 protein-protein interaction.

    Science.gov (United States)

    Doveston, Richard G; Kuusk, Ave; Andrei, Sebastian A; Leysen, Seppe; Cao, Qing; Castaldi, Maria P; Hendricks, Adam; Brunsveld, Luc; Chen, Hongming; Boyd, Helen; Ottmann, Christian

    2017-08-01

    14-3-3 proteins are positive regulators of the tumor suppressor p53, the mutation of which is implicated in many human cancers. Current strategies for targeting of p53 involve restoration of wild-type function or inhibition of the interaction with MDM2, its key negative regulator. Despite the efficacy of these strategies, the alternate approach of stabilizing the interaction of p53 with positive regulators and, thus, enhancing tumor suppressor activity, has not been explored. Here, we report the first example of small-molecule stabilization of the 14-3-3 - p53 protein-protein interaction (PPI) and demonstrate the potential of this approach as a therapeutic modality. We also observed a disconnect between biophysical and crystallographic data in the presence of a stabilizing molecule, which is unusual in 14-3-3 PPIs. © 2017 Federation of European Biochemical Societies.

  2. Single methyl groups can act as toggle switches to specify transmembrane protein-protein interactions

    DEFF Research Database (Denmark)

    He, Li; Steinocher, Helena; Shelar, Ashish

    2017-01-01

    of leucine and isoleucine (called LIL traptamers) that specifically activate the erythropoietin receptor (EPOR) in mouse cells to confer growth factor independence. We discovered that the placement of a single side chain methyl group at specific positions in a traptamer determined whether it associated......Transmembrane domains (TMDs) engage in protein-protein interactions that regulate many cellular processes, but the rules governing the specificity of these interactions are poorly understood. To discover these principles, we analyzed 26-residue model transmembrane proteins consisting exclusively...... productively with the TMD of the human EPOR, the mouse EPOR, or both receptors. Association of the traptamers with the EPOR induced EPOR oligomerization in an orientation that stimulated receptor activity. These results highlight the high intrinsic specificity of TMD interactions, demonstrate that a single...

  3. iPPI-DB: an online database of modulators of protein-protein interactions.

    Science.gov (United States)

    Labbé, Céline M; Kuenemann, Mélaine A; Zarzycka, Barbara; Vriend, Gert; Nicolaes, Gerry A F; Lagorce, David; Miteva, Maria A; Villoutreix, Bruno O; Sperandio, Olivier

    2016-01-04

    In order to boost the identification of low-molecular-weight drugs on protein-protein interactions (PPI), it is essential to properly collect and annotate experimental data about successful examples. This provides the scientific community with the necessary information to derive trends about privileged physicochemical properties and chemotypes that maximize the likelihood of promoting a given chemical probe to the most advanced stages of development. To this end we have developed iPPI-DB (freely accessible at http://www.ippidb.cdithem.fr), a database that contains the structure, some physicochemical characteristics, the pharmacological data and the profile of the PPI targets of several hundreds modulators of protein-protein interactions. iPPI-DB is accessible through a web application and can be queried according to two general approaches: using physicochemical/pharmacological criteria; or by chemical similarity to a user-defined structure input. In both cases the results are displayed as a sortable and exportable datasheet with links to external databases such as Uniprot, PubMed. Furthermore each compound in the table has a link to an individual ID card that contains its physicochemical and pharmacological profile derived from iPPI-DB data. This includes information about its binding data, ligand and lipophilic efficiencies, location in the PPI chemical space, and importantly similarity with known drugs, and links to external databases like PubChem, and ChEMBL. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  4. Extracting gene function from protein-protein interactions using Quantitative BAC InteraCtomics (QUBIC).

    Science.gov (United States)

    Hubner, Nina C; Mann, Matthias

    2011-04-01

    Large-scale proteomic screens are increasingly employed for placing genes into specific pathways. Therefore generic methods providing a physiological context for protein-protein interaction studies are of great interest. In recent years many protein-protein interactions have been determined by affinity purification followed by mass spectrometry (AP-MS). Among many different AP-MS approaches, the recently developed Quantitative BAC InteraCtomics (QUBIC) approach is particularly attractive as it uses tagged, full-length baits that are expressed under endogenous control. For QUBIC large cell line collections expressing tagged proteins from BAC transgenes or gene trap loci have been developed and are freely available. Here we describe detailed workflows on how to obtain specific protein binding partners with high confidence under physiological conditions. The methods are based on fast, streamlined and generic purification procedures followed by single run liquid chromatography-mass spectrometric analysis. Quantification is achieved either by the stable isotope labeling of amino acids in cell culture (SILAC) method or by a 'label-free' procedure. In either case data analysis is performed by using the freely available MaxQuant environment. The QUBIC approach enables biologists with access to high resolution mass spectrometry to perform small and large-scale protein interactome mappings. Copyright © 2010 Elsevier Inc. All rights reserved.

  5. 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.

  6. 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.

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

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    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.

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

    Science.gov (United States)

    Chakraborty, Sandip; Alvarez-Ponce, David

    2016-01-01

    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.

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

    Science.gov (United States)

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

    2012-07-01

    Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.

  10. Prediction of Protein-Protein Interacting Sites: How to Bridge Molecular Events to Large Scale Protein Interaction Networks

    Science.gov (United States)

    Bartoli, Lisa; Martelli, Pier Luigi; Rossi, Ivan; Fariselli, Piero; Casadio, Rita

    Most of the cellular functions are the result of the concerted action of protein complexes forming pathways and networks. For this reason, efforts were devoted to the study of protein-protein interactions. Large-scale experiments on whole genomes allowed the identification of interacting protein pairs. However residues involved in the interaction are generally not known and the majority of the interactions still lack a structural characterization. A crucial step towards the deciphering of the interaction mechanism of proteins is the recognition of their interacting surfaces, particularly in those structures for which also the most recent interaction network resources do not contain information. To this purpose, we developed a neural network-based method that is able to characterize protein complexes, by predicting amino acid residues that mediate the interactions. All the Protein Data Bank (PDB) chains, both in the unbound and in the complexed form, are predicted and the results are stored in a database of interaction surfaces (http://gpcr.biocomp.unibo.it/zenpatches). Finally, we performed a survey on the different computational methods for protein-protein interaction prediction and on their training/testing sets in order to highlight the most informative properties of protein interfaces.

  11. Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

    Science.gov (United States)

    Zhang, Mengying; Su, Qiang; Lu, Yi; Zhao, Manman; Niu, Bing

    2017-01-01

    Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed. SVM and RF are two commonly used methods. Nowadays, more researchers predict PPIs by combining more than two methods. This review presents the application of machine learning approaches in predicting PPI. Many examples of success in identification and prediction in the area of PPI prediction have been discussed, and the PPIs research is still in progress. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  12. Small-molecule stabilization of protein-protein interactions: an underestimated concept in drug discovery?

    Science.gov (United States)

    Thiel, Philipp; Kaiser, Markus; Ottmann, Christian

    2012-02-27

    The modulation of protein-protein interactions (PPIs) has been recognized as one of the most challenging tasks in drug discovery. While their systematic development has long been considered as intractable, this view has changed over the last years, with the first drug candidates undergoing clinical studies. To date, the vast majority of PPI modulators are interaction inhibitors. However, in many biological contexts a prolonged lifespan of a PPI might be desirable, calling for the complementary approach of PPI stabilization. In fact, nature offers impressive examples of this concept and some PPI-stabilizing natural products have already found application as important drugs. Moreover, directed small-molecule stabilization has recently been demonstrated. Therefore, it is time to take a closer look at the constructive side of modulating PPIs. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Integrating semantic information into multiple kernels for protein-protein interaction extraction from biomedical literatures.

    Directory of Open Access Journals (Sweden)

    Lishuang Li

    Full Text Available Protein-Protein Interaction (PPI extraction is an important task in the biomedical information extraction. Presently, many machine learning methods for PPI extraction have achieved promising results. However, the performance is still not satisfactory. One reason is that the semantic resources were basically ignored. In this paper, we propose a multiple-kernel learning-based approach to extract PPIs, combining the feature-based kernel, tree kernel and semantic kernel. Particularly, we extend the shortest path-enclosed tree kernel (SPT by a dynamic extended strategy to retrieve the richer syntactic information. Our semantic kernel calculates the protein-protein pair similarity and the context similarity based on two semantic resources: WordNet and Medical Subject Heading (MeSH. We evaluate our method with Support Vector Machine (SVM and achieve an F-score of 69.40% and an AUC of 92.00%, which show that our method outperforms most of the state-of-the-art systems by integrating semantic information.

  14. 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.

  15. Domain-Based Predictive Models for Protein-Protein Interaction Prediction

    Directory of Open Access Journals (Sweden)

    Chen Xue-Wen

    2006-01-01

    Full Text Available Protein interactions are of biological interest because they orchestrate a number of cellular processes such as metabolic pathways and immunological recognition. Recently, methods for predicting protein interactions using domain information are proposed and preliminary results have demonstrated their feasibility. In this paper, we develop two domain-based statistical models (neural networks and decision trees for protein interaction predictions. Unlike most of the existing methods which consider only domain pairs (one domain from one protein and assume that domain-domain interactions are independent of each other, the proposed methods are capable of exploring all possible interactions between domains and make predictions based on all the domains. Compared to maximum-likelihood estimation methods, our experimental results show that the proposed schemes can predict protein-protein interactions with higher specificity and sensitivity, while requiring less computation time. Furthermore, the decision tree-based model can be used to infer the interactions not only between two domains, but among multiple domains as well.

  16. 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.

  17. 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.

  18. Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

    Science.gov (United States)

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

    2012-01-01

    Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with

  19. Essential Protein Detection by Random Walk on Weighted Protein-Protein Interaction Networks.

    Science.gov (United States)

    Xu, Bin; Guan, Jihong; Wang, Yang; Wang, Zewei

    2017-05-12

    Essential proteins are critical to the development and survival of cells. Identification of essential proteins is helpful for understanding the minimal set of required genes in a living cell and for designing new drugs. To detect essential proteins, various computational methods have been proposed based on protein-protein interaction (PPI) networks. However, protein interaction data obtained by highthroughput experiments usually contain high false positives, which negatively impacts the accuracy of essential protein detection. Moreover, most existing studies focused on the local information of proteins in PPI networks, while ignoring the influence of indirect protein interactions on essentiality. In this paper, we propose a novel method, called Essentiality Ranking (EssRank in short), to boost the accuracy of essential protein detection. To deal with the inaccuracy of PPI data, confidence scores of interactions are evaluated by integrating various biological information. Weighted edge clustering coefficient (WECC), considering both interaction confidence scores and network topology, is proposed to calculate edge weights in PPI networks. The weight of each node is evaluated by the sum of WECC values of its linking edges. A random walk method, making use of both direct and indirect protein interactions, is then employed to calculate protein essentiality iteratively. Experimental results on the yeast PPI network show that EssRank outperforms most existing methods, including the most commonly-used centrality measures (SC, DC, BC, CC, IC, EC), topology based methods (DMNC and NC) and the data integrating method IEW.

  20. 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.

  1. Recent advances in protein-protein interaction prediction: experimental and computational methods.

    Science.gov (United States)

    Jessulat, Matthew; Pitre, Sylvain; Gui, Yuan; Hooshyar, Mohsen; Omidi, Katayoun; Samanfar, Bahram; Tan, Le Hoa; Alamgir, Md; Green, James; Dehne, Frank; Golshani, Ashkan

    2011-09-01

    Proteins within the cell act as part of complex networks, which allow pathways and processes to function. Therefore, understanding how proteins interact is a significant area of current research. This review aims to present an overview of key experimental techniques (yeast two-hybrid, tandem affinity purification and protein microarrays) used to discover protein-protein interactions (PPIs), as well as to briefly discuss certain computational methods for predicting protein interactions based on gene localization, phylogenetic information, 3D structural modeling or primary protein sequence data. Due to the large-scale applicability of primary sequence-based methods, the authors have chosen to focus on this strategy for our review. There is an emphasis on a recent algorithm called Protein Interaction Prediction Engine (PIPE) that can predict global PPIs. The readers will discover recent advances both in the practical determination of protein interaction and the strategies that are available to attempt to anticipate interactions without the time and costs of experimental work. Global PPI maps can help understand the biology of complex diseases and facilitate the identification of novel drug target sites. This study describes different techniques used for PPI prediction that we believe will significantly impact the development of the field in a new future. We expect to see a growing number of similar techniques capable of large-scale PPI predictions.

  2. Strong WW Interaction at LHC

    Energy Technology Data Exchange (ETDEWEB)

    Pelaez, Jose R

    1998-12-14

    We present a brief pedagogical introduction to the Effective Electroweak Chiral Lagrangians, which provide a model independent description of the WW interactions in the strong regime. When it is complemented with some unitarization or a dispersive approach, this formalism allows the study of the general strong scenario expected at the LHC, including resonances.

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

    Directory of Open Access Journals (Sweden)

    Albrecht von Brunn

    2007-05-01

    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.

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

    Science.gov (United States)

    Xie, Chao; Gao, Jin; Zhu, Run-Zhi; Yuan, Yun-Sheng; He, Hong-Lin; Huang, Qiu-Shi; Han, Wei; Yu, Yan

    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 factor β signaling pathways. We believe the use of large-scale PPI maps for integrating the information already known about the liver regeneration is a useful approach in understanding liver regeneration from the standpoint of systems biology. PMID:20653057

  5. HippDB: a database of readily targeted helical protein-protein interactions.

    Science.gov (United States)

    Bergey, Christina M; Watkins, Andrew M; Arora, Paramjit S

    2013-11-01

    HippDB catalogs every protein-protein interaction whose structure is available in the Protein Data Bank and which exhibits one or more helices at the interface. The Web site accepts queries on variables such as helix length and sequence, and it provides computational alanine scanning and change in solvent-accessible surface area values for every interfacial residue. HippDB is intended to serve as a starting point for structure-based small molecule and peptidomimetic drug development. HippDB is freely available on the web at http://www.nyu.edu/projects/arora/hippdb. The Web site is implemented in PHP, MySQL and Apache. Source code freely available for download at http://code.google.com/p/helidb, implemented in Perl and supported on Linux. arora@nyu.edu.

  6. CellMap visualizes protein-protein interactions and subcellular localization

    Science.gov (United States)

    Dallago, Christian; Goldberg, Tatyana; Andrade-Navarro, Miguel Angel; Alanis-Lobato, Gregorio; Rost, Burkhard

    2018-01-01

    Many tools visualize protein-protein interaction (PPI) networks. The tool introduced here, CellMap, adds one crucial novelty by visualizing PPI networks in the context of subcellular localization, i.e. the location in the cell or cellular component in which a PPI happens. Users can upload images of cells and define areas of interest against which PPIs for selected proteins are displayed (by default on a cartoon of a cell). Annotations of localization are provided by the user or through our in-house database. The visualizer and server are written in JavaScript, making CellMap easy to customize and to extend by researchers and developers. PMID:29497493

  7. Can understanding the packing of side chains improve the design of protein-protein interactions?

    Science.gov (United States)

    Zhou, Alice; O'Hern, Corey; Regan, Lynne

    2011-03-01

    With the long-term goal to improve the design of protein-protein interactions, we have begun extensive computational studies to understand how side-chains of key residues of binding partners geometrically fit together at protein-peptide interfaces, e.g. the tetratrico-peptide repeat protein and its cognate peptide). We describe simple atomic-scale models of hydrophobic dipeptides, which include hard-core repulsion, bond length and angle constraints, and Van der Waals attraction. By completely enumerating all minimal energy structures in these systems, we are able to reproduce important features of the probability distributions of side chain dihedral angles of hydrophic residues in the protein data bank. These results are the crucial first step in developing computational models that can predict the side chain conformations of residues at protein-peptide interfaces. CSO acknowledges support from NSF grant no. CMMT-1006527.

  8. 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. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Discovering disease-associated genes in weighted protein-protein interaction networks

    Science.gov (United States)

    Cui, Ying; Cai, Meng; Stanley, H. Eugene

    2018-04-01

    Although there have been many network-based attempts to discover disease-associated genes, most of them have not taken edge weight - which quantifies their relative strength - into consideration. We use connection weights in a protein-protein interaction (PPI) network to locate disease-related genes. We analyze the topological properties of both weighted and unweighted PPI networks and design an improved random forest classifier to distinguish disease genes from non-disease genes. We use a cross-validation test to confirm that weighted networks are better able to discover disease-associated genes than unweighted networks, which indicates that including link weight in the analysis of network properties provides a better model of complex genotype-phenotype associations.

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

    Directory of Open Access Journals (Sweden)

    Xiaomin Wang

    2011-01-01

    Full Text Available 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 uses the concepts of highest k-core and cohesion to predict protein complexes by identifying overlapping clusters. The experiments on two data sets and two benchmarks show that our algorithm has relatively high F-measure and exhibits better performance compared with some other methods.

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

    Science.gov (United States)

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

    2015-01-01

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

  12. 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.

  13. 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.

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

    Science.gov (United States)

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

    2016-01-01

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

  15. Unraveling the conundrum of seemingly discordant protein-protein interaction datasets.

    Science.gov (United States)

    Gupta, Shobhit; Wallqvist, Anders; Bondugula, Rajkumar; Ivanic, Joseph; Reifman, Jaques

    2010-01-01

    Most high-throughput experimental results of protein-protein interactions (PPIs) are seemingly inconsistent with each other. In this article, we re-evaluated these contradictions within the context of the underlying domain-domain interactions (DDIs) for two Escherichia coli and four Saccharomyces cerevisiae PPI datasets derived from high-throughput (yeast two-hybrid and tandem affinity purification) experimental platforms. For shared DDIs across pairs of compared datasets, we observed a remarkably high pair-wise correlation (Pearson correlation coefficient between 0.80 and 0.84) between datasets of the same organism derived from the same experimental platform. To a lesser degree, this concordance also held true for more general inter-platform and intra-species comparisons (Pearson correlation coefficient between 0.52 and 0.89). Thus, although varying experimental conditions can influence the ability of individual proteins to interact and, therefore, create apparent differences among PPIs, the physical nature of the underlying interactions, captured by DDIs, is the same and can be used to model and predict PPIs.

  16. Effective cell-free drug screening protocol for protein-protein interaction.

    Science.gov (United States)

    Ashkenazi, Shaked; Plotnikov, Alexander; Bahat, Anat; Dikstein, Rivka

    2017-09-01

    Specific protein-protein interaction (PPI) is an essential feature of many cellular processes however, targeting these interactions by small molecules is highly challenging due to the nature of the interaction interface. Thus, screening for PPI inhibitors requires enormous number of compounds. Here we describe a simple and improved protocol designed for a search of direct PPI inhibitors. We engineered a bacterial expression system for the split-Renilla luciferase (RL) complementation assay that monitors PPI. This enables production of large quantities of the RL fusion proteins in a simple and cost effective manner that is suitable for very large screens. Subsequently, inhibitory compounds are analyzed in a similar complementation assay in living cultured mammalian cells to select for those that can penetrate cells. We applied this method to NF-κB, a family of dimeric transcription factors that plays central roles in immune responses, cell survival and aging, and its dysregulation is linked to many pathological states. This strategy led to the identification of several direct NF-κB inhibitors. As the described protocol is very straightforward and robust it may be suitable for many pairs of interacting proteins. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Protein-protein interactions in paralogues: Electrostatics modulates specificity on a conserved steric scaffold.

    Science.gov (United States)

    Ivanov, Stefan M; Cawley, Andrew; Huber, Roland G; Bond, Peter J; Warwicker, Jim

    2017-01-01

    An improved knowledge of protein-protein interactions is essential for better understanding of metabolic and signaling networks, and cellular function. Progress tends to be based on structure determination and predictions using known structures, along with computational methods based on evolutionary information or detailed atomistic descriptions. We hypothesized that for the case of interactions across a common interface, between proteins from a pair of paralogue families or within a family of paralogues, a relatively simple interface description could distinguish between binding and non-binding pairs. Using binding data for several systems, and large-scale comparative modeling based on known template complex structures, it is found that charge-charge interactions (for groups bearing net charge) are generally a better discriminant than buried non-polar surface. This is particularly the case for paralogue families that are less divergent, with more reliable comparative modeling. We suggest that electrostatic interactions are major determinants of specificity in such systems, an observation that could be used to predict binding partners.

  18. Protein-protein interactions in paralogues: Electrostatics modulates specificity on a conserved steric scaffold.

    Directory of Open Access Journals (Sweden)

    Stefan M Ivanov

    Full Text Available An improved knowledge of protein-protein interactions is essential for better understanding of metabolic and signaling networks, and cellular function. Progress tends to be based on structure determination and predictions using known structures, along with computational methods based on evolutionary information or detailed atomistic descriptions. We hypothesized that for the case of interactions across a common interface, between proteins from a pair of paralogue families or within a family of paralogues, a relatively simple interface description could distinguish between binding and non-binding pairs. Using binding data for several systems, and large-scale comparative modeling based on known template complex structures, it is found that charge-charge interactions (for groups bearing net charge are generally a better discriminant than buried non-polar surface. This is particularly the case for paralogue families that are less divergent, with more reliable comparative modeling. We suggest that electrostatic interactions are major determinants of specificity in such systems, an observation that could be used to predict binding partners.

  19. Combined chemical shift changes and amino acid specific chemical shift mapping of protein-protein interactions

    Energy Technology Data Exchange (ETDEWEB)

    Schumann, Frank H.; Riepl, Hubert [University of Regensburg, Institute of Biophysics and Physical Biochemistry (Germany); Maurer, Till [Boehringer Ingelheim Pharma GmbH and Co. KG, Analytical Sciences Department (Germany); Gronwald, Wolfram [University of Regensburg, Institute of Biophysics and Physical Biochemistry (Germany); Neidig, Klaus-Peter [Bruker BioSpin GmbH, Software Department (Germany); Kalbitzer, Hans Robert [University of Regensburg, Institute of Biophysics and Physical Biochemistry (Germany)], E-mail: hans-robert.kalbitzer@biologie.uni-regensburg.de

    2007-12-15

    Protein-protein interactions are often studied by chemical shift mapping using solution NMR spectroscopy. When heteronuclear data are available the interaction interface is usually predicted by combining the chemical shift changes of different nuclei to a single quantity, the combined chemical shift perturbation {delta}{delta}{sub comb}. In this paper different procedures (published and non-published) to calculate {delta}{delta}{sub comb} are examined that include a variety of different functional forms and weighting factors for each nucleus. The predictive power of all shift mapping methods depends on the magnitude of the overlap of the chemical shift distributions of interacting and non-interacting residues and the cut-off criterion used. In general, the quality of the prediction on the basis of chemical shift changes alone is rather unsatisfactory but the combination of chemical shift changes on the basis of the Hamming or the Euclidian distance can improve the result. The corrected standard deviation to zero of the combined chemical shift changes can provide a reasonable cut-off criterion. As we show combined chemical shifts can also be applied for a more reliable quantitative evaluation of titration data.

  20. Molecular tweezers modulate 14-3-3 protein-protein interactions

    Science.gov (United States)

    Bier, David; Rose, Rolf; Bravo-Rodriguez, Kenny; Bartel, Maria; Ramirez-Anguita, Juan Manuel; Dutt, Som; Wilch, Constanze; Klärner, Frank-Gerrit; Sanchez-Garcia, Elsa; Schrader, Thomas; Ottmann, Christian

    2013-03-01

    Supramolecular chemistry has recently emerged as a promising way to modulate protein functions, but devising molecules that will interact with a protein in the desired manner is difficult as many competing interactions exist in a biological environment (with solvents, salts or different sites for the target biomolecule). We now show that lysine-specific molecular tweezers bind to a 14-3-3 adapter protein and modulate its interaction with partner proteins. The tweezers inhibit binding between the 14-3-3 protein and two partner proteins—a phosphorylated (C-Raf) protein and an unphosphorylated one (ExoS)—in a concentration-dependent manner. Protein crystallography shows that this effect arises from the binding of the tweezers to a single surface-exposed lysine (Lys214) of the 14-3-3 protein in the proximity of its central channel, which normally binds the partner proteins. A combination of structural analysis and computer simulations provides rules for the tweezers' binding preferences, thus allowing us to predict their influence on this type of protein-protein interactions.

  1. 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......-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...

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Adam D Hoppe

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

  4. Protein-protein interaction network and subcellular localization of the Arabidopsis thaliana ESCRT machinery

    Directory of Open Access Journals (Sweden)

    Lynn eRichardson

    2011-06-01

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

  5. SLIDER: a generic metaheuristic for the discovery of correlated motifs in protein-protein interaction networks.

    Science.gov (United States)

    Boyen, Peter; Van Dyck, Dries; Neven, Frank; van Ham, Roeland C H J; van Dijk, Aalt D J

    2011-01-01

    Correlated motif mining (cmm) is the problem of finding overrepresented pairs of patterns, called motifs, in sequences of interacting proteins. Algorithmic solutions for cmm thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a motif-driven approach where the support of candidate motif pairs is evaluated in the network. We experimentally establish the superiority of the Chi-square-based support measure over other support measures. Furthermore, we obtain that cmm is an np-hard problem for a large class of support measures (including Chi-square) and reformulate the search for correlated motifs as a combinatorial optimization problem. We then present the generic metaheuristic slider which uses steepest ascent with a neighborhood function based on sliding motifs and employs the Chi-square-based support measure. We show that slider outperforms existing motif-driven cmm methods and scales to large protein-protein interaction networks. The slider-implementation and the data used in the experiments are available on http://bioinformatics.uhasselt.be.

  6. Annotating activation/inhibition relationships to protein-protein interactions using gene ontology relations.

    Science.gov (United States)

    Yim, Soorin; Yu, Hasun; Jang, Dongjin; Lee, Doheon

    2018-04-11

    Signaling pathways can be reconstructed by identifying 'effect types' (i.e. activation/inhibition) of protein-protein interactions (PPIs). Effect types are composed of 'directions' (i.e. upstream/downstream) and 'signs' (i.e. positive/negative), thereby requiring directions as well as signs of PPIs to predict signaling events from PPI networks. Here, we propose a computational method for systemically annotating effect types to PPIs using relations between functional information of proteins. We used regulates, positively regulates, and negatively regulates relations in Gene Ontology (GO) to predict directions and signs of PPIs. These relations indicate both directions and signs between GO terms so that we can project directions and signs between relevant GO terms to PPIs. Independent test results showed that our method is effective for predicting both directions and signs of PPIs. Moreover, our method outperformed a previous GO-based method that did not consider the relations between GO terms. We annotated effect types to human PPIs and validated several highly confident effect types against literature. The annotated human PPIs are available in Additional file 2 to aid signaling pathway reconstruction and network biology research. We annotated effect types to PPIs by using regulates, positively regulates, and negatively regulates relations in GO. We demonstrated that those relations are effective for predicting not only signs, but also directions of PPIs. The usefulness of those relations suggests their potential applications to other types of interactions such as protein-DNA interactions.

  7. Domain distribution and intrinsic disorder in hubs in the human protein-protein interaction network.

    Science.gov (United States)

    Patil, Ashwini; Kinoshita, Kengo; Nakamura, Haruki

    2010-08-01

    Intrinsic disorder and distributed surface charge have been previously identified as some of the characteristics that differentiate hubs (proteins with a large number of interactions) from non-hubs in protein-protein interaction networks. In this study, we investigated the differences in the quantity, diversity, and functional nature of Pfam domains, and their relationship with intrinsic disorder, in hubs and non-hubs. We found that proteins with a more diverse domain composition were over-represented in hubs when compared with non-hubs, with the number of interactions in hubs increasing with domain diversity. Conversely, the fraction of intrinsic disorder in hubs decreased with increasing number of ordered domains. The difference in the levels of disorder was more prominent in hubs and non-hubs with fewer domains. Functional analysis showed that hubs were enriched in kinase and adaptor domains acting primarily in signal transduction and transcription regulation, whereas non-hubs had more DNA-binding domains and were involved in catalytic activity. Consistent with the differences in the functional nature of their domains, hubs with two or more domains were more likely to connect distinct functional modules in the interaction network when compared with single domain hubs. We conclude that the availability of greater number and diversity of ordered domains, in addition to the tendency to have promiscuous domains, differentiates hubs from non-hubs and provides an additional means of achieving interaction promiscuity. Further, hubs with fewer domains use greater levels of intrinsic disorder to facilitate interaction promiscuity with the prevalence of disorder decreasing with increasing number of ordered domains.

  8. Strong interaction at finite temperature

    Indian Academy of Sciences (India)

    Abstract. We review two methods discussed in the literature to determine the effective parameters of strongly interacting particles as they move through a heat bath. The first one is the general method of chiral perturbation theory, which may be readily applied to this problem. The other is the method of thermal QCD sum rules ...

  9. Investigation of the Josephin Domain protein-protein interaction by molecular dynamics.

    Directory of Open Access Journals (Sweden)

    Marco A Deriu

    Full Text Available Spinocerebellar ataxia (SCA 3, the most common form of SCA, is a neurodegenerative rare disease characterized by polyglutamine tract expansion and self-assembly of Ataxin3 (At3 misfolded proteins into highly organized fibrillar aggregates. The At3 N-terminal Josephin Domain (JD has been suggested as being responsible for mediating the initial phase of the At3 double-step fibrillogenesis. Several issues concerning the residues involved in the JD's aggregation and, more generally, the JD clumping mechanism have not been clarified yet. In this paper we present an investigation focusing on the JD protein-protein interaction by means of molecular modeling. Our results suggest possible aminoacids involved in JD contact together with local and non-local effects following JD dimerization. Surprisingly, JD conformational changes following the binding may involve ubiquitin binding sites and hairpin region even though they do not pertain to the JD interaction surfaces. Moreover, the JD binding event has been found to alter the hairpin open-like conformation toward a closed-like arrangement over the simulated timescale. Finally, our results suggest that the JD aggregation might be a multi-step process, with an initial fast JD-JD binding mainly driven by Arg101, followed by slower structural global rearrangements involving the exposure to the solvent of Leu84-Trp87, which might play a role in a second step of JD aggregation.

  10. Detection of Locally Over-Represented GO Terms in Protein-Protein Interaction Networks

    Science.gov (United States)

    LAVALLÉE-ADAM, MATHIEU; COULOMBE, BENOIT; BLANCHETTE, MATHIEU

    2015-01-01

    High-throughput methods for identifying protein-protein interactions produce increasingly complex and intricate interaction networks. These networks are extremely rich in information, but extracting biologically meaningful hypotheses from them and representing them in a human-readable manner is challenging. We propose a method to identify Gene Ontology terms that are locally over-represented in a subnetwork of a given biological network. Specifically, we propose several methods to evaluate the degree of clustering of proteins associated to a particular GO term in both weighted and unweighted PPI networks, and describe efficient methods to estimate the statistical significance of the observed clustering. We show, using Monte Carlo simulations, that our best approximation methods accurately estimate the true p-value, for random scale-free graphs as well as for actual yeast and human networks. When applied to these two biological networks, our approach recovers many known complexes and pathways, but also suggests potential functions for many subnetworks. Online Supplementary Material is available at www.liebertonline.com. PMID:20377456

  11. 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/.

  12. Structural Insights into Protein-Protein Interactions Involved in Bacterial Cell Wall Biogenesis

    Directory of Open Access Journals (Sweden)

    Federica Laddomada

    2016-04-01

    Full Text Available The bacterial cell wall is essential for survival, and proteins that participate in its biosynthesis have been the targets of antibiotic development efforts for decades. The biosynthesis of its main component, the peptidoglycan, involves the coordinated action of proteins that are involved in multi-member complexes which are essential for cell division (the “divisome” and/or cell wall elongation (the “elongasome”, in the case of rod-shaped cells. Our knowledge regarding these interactions has greatly benefitted from the visualization of different aspects of the bacterial cell wall and its cytoskeleton by cryoelectron microscopy and tomography, as well as genetic and biochemical screens that have complemented information from high resolution crystal structures of protein complexes involved in divisome or elongasome formation. This review summarizes structural and functional aspects of protein complexes involved in the cytoplasmic and membrane-related steps of peptidoglycan biosynthesis, with a particular focus on protein-protein interactions whereby disruption could lead to the development of novel antibacterial strategies.

  13. 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.

  14. A Novel Approach for Protein-Named Entity Recognition and Protein-Protein Interaction Extraction

    Directory of Open Access Journals (Sweden)

    Meijing Li

    2015-01-01

    Full Text Available Many researchers focus on developing protein-named entity recognition (Protein-NER or PPI extraction systems. However, the studies about these two topics cannot be merged well; then existing PPI extraction systems’ Protein-NER still needs to improve. In this paper, we developed the protein-protein interaction extraction system named PPIMiner based on Support Vector Machine (SVM and parsing tree. PPIMiner consists of three main models: natural language processing (NLP model, Protein-NER model, and PPI discovery model. The Protein-NER model, which is named ProNER, identifies the protein names based on two methods: dictionary-based method and machine learning-based method. ProNER is capable of identifying more proteins than dictionary-based Protein-NER model in other existing systems. The final discovered PPIs extracted via PPI discovery model are represented in detail because we showed the protein interaction types and the occurrence frequency through two different methods. In the experiments, the result shows that the performances achieved by our ProNER and PPI discovery model are better than other existing tools. PPIMiner applied this protein-named entity recognition approach and parsing tree based PPI extraction method to improve the performance of PPI extraction. We also provide an easy-to-use interface to access PPIs database and an online system for PPIs extraction and Protein-NER.

  15. In silico structure-based approaches to discover protein-protein interaction-targeting drugs.

    Science.gov (United States)

    Shin, Woong-Hee; Christoffer, Charles W; Kihara, Daisuke

    2017-12-01

    A core concept behind modern drug discovery is finding a small molecule that modulates a function of a target protein. This concept has been successfully applied since the mid-1970s. However, the efficiency of drug discovery is decreasing because the druggable target space in the human proteome is limited. Recently, protein-protein interaction (PPI) has been identified asan emerging target space for drug discovery. PPI plays a pivotal role in biological pathways including diseases. Current human interactome research suggests that the number of PPIs is between 130,000 and 650,000, and only a small number of them have been targeted as drug targets. For traditional drug targets, in silico structure-based methods have been successful in many cases. However, their performance suffers on PPI interfaces because PPI interfaces are different in five major aspects: From a geometric standpoint, they have relatively large interface regions, flat geometry, and the interface surface shape tends to fluctuate upon binding. Also, their interactions are dominated by hydrophobic atoms, which is different from traditional binding-pocket-targeted drugs. Finally, PPI targets usually lack natural molecules that bind to the target PPI interface. Here, we first summarize characteristics of PPI interfaces and their known binders. Then, we will review existing in silico structure-based approaches for discovering small molecules that bind to PPI interfaces. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Targeting protein-protein interaction between MLL1 and reciprocal proteins for leukemia therapy.

    Science.gov (United States)

    Wang, Zhi-Hui; Li, Dong-Dong; Chen, Wei-Lin; You, Qi-Dong; Guo, Xiao-Ke

    2018-01-15

    The mixed lineage leukemia protein-1 (MLL1), as a lysine methyltransferase, predominantly regulates the methylation of histone H3 lysine 4 (H3K4) and functions in hematopoietic stem cell (HSC) self-renewal. MLL1 gene fuses with partner genes that results in the generation of MLL1 fusion proteins (MLL1-FPs), which are frequently detected in acute leukemia. In the progress of leukemogenesis, a great deal of proteins cooperate with MLL1 to form multiprotein complexes serving for the dysregulation of H3K4 methylation, the overexpression of homeobox (HOX) cluster genes, and the consequent generation of leukemia. Hence, disrupting the interactions between MLL1 and the reciprocal proteins has been considered to be a new treatment strategy for leukemia. Here, we reviewed potential protein-protein interactions (PPIs) between MLL1 and its reciprocal proteins, and summarized the inhibitors to target MLL1 PPIs. The druggability of MLL1 PPIs for leukemia were also discussed. Copyright © 2017. Published by Elsevier Ltd.

  17. Influence of degree correlations on network structure and stability in protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Zimmer Ralf

    2007-08-01

    Full Text Available Abstract Background The existence of negative correlations between degrees of interacting proteins is being discussed since such negative degree correlations were found for the large-scale yeast protein-protein interaction (PPI network of Ito et al. More recent studies observed no such negative correlations for high-confidence interaction sets. In this article, we analyzed a range of experimentally derived interaction networks to understand the role and prevalence of degree correlations in PPI networks. We investigated how degree correlations influence the structure of networks and their tolerance against perturbations such as the targeted deletion of hubs. Results For each PPI network, we simulated uncorrelated, positively and negatively correlated reference networks. Here, a simple model was developed which can create different types of degree correlations in a network without changing the degree distribution. Differences in static properties associated with degree correlations were compared by analyzing the network characteristics of the original PPI and reference networks. Dynamics were compared by simulating the effect of a selective deletion of hubs in all networks. Conclusion Considerable differences between the network types were found for the number of components in the original networks. Negatively correlated networks are fragmented into significantly less components than observed for positively correlated networks. On the other hand, the selective deletion of hubs showed an increased structural tolerance to these deletions for the positively correlated networks. This results in a lower rate of interaction loss in these networks compared to the negatively correlated networks and a decreased disintegration rate. Interestingly, real PPI networks are most similar to the randomly correlated references with respect to all properties analyzed. Thus, although structural properties of networks can be modified considerably by degree

  18. 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.

    2015-01-01

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

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

    NARCIS (Netherlands)

    N. Baudendistel (Nina); T.A. Knoch (Tobias); G. Müller (Gabriele); M. Wachsmuth (Malte); T. Weidemann (Thomas); W. Waldeck (Waldemar); J. 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

  20. Utilizing Mechanistic Cross-Linking Technology to Study Protein-Protein Interactions: An Experiment Designed for an Undergraduate Biochemistry Lab

    Science.gov (United States)

    Finzel, Kara; Beld, Joris; Burkart, Michael D.; Charkoudian, Louise K.

    2017-01-01

    Over the past decade, mechanistic cross-linking probes have been used to study protein-protein interactions in natural product biosynthetic pathways. This approach is highly interdisciplinary, combining elements of protein biochemistry, organic chemistry, and computational docking. Herein, we described the development of an experiment to engage…

  1. Gateway Vectors for Simultaneous Detection of Multiple Protein-Protein Interactions in Plant Cells Using Bimolecular Fluorescence Complementation.

    Science.gov (United States)

    Kamigaki, Akane; Nito, Kazumasa; Hikino, Kazumi; Goto-Yamada, Shino; Nishimura, Mikio; Nakagawa, Tsuyoshi; Mano, Shoji

    2016-01-01

    Bimolecular fluorescence complementation (BiFC) is widely used to detect protein-protein interactions, because it is technically simple, convenient, and can be adapted for use with conventional fluorescence microscopy. We previously constructed enhanced yellow fluorescent protein (EYFP)-based Gateway cloning technology-compatible vectors. In the current study, we generated new Gateway cloning technology-compatible vectors to detect BiFC-based multiple protein-protein interactions using N- and C-terminal fragments of enhanced cyan fluorescent protein (ECFP), enhanced green fluorescent protein (EGFP), and monomeric red fluorescent protein (mRFP1). Using a combination of N- and C-terminal fragments from ECFP, EGFP and EYFP, we observed a shift in the emission wavelength, enabling the simultaneous detection of multiple protein-protein interactions. Moreover, we developed these vectors as binary vectors for use in Agrobacterium infiltration and for the generate transgenic plants. We verified that the binary vectors functioned well in tobacco cells. The results demonstrate that the BiFC vectors facilitate the design of various constructions and are convenient for the detection of multiple protein-protein interactions simultaneously in plant cells.

  2. 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...

  3. Influence of protein abundance on high-throughput protein-protein interaction detection.

    Directory of Open Access Journals (Sweden)

    Joseph Ivanic

    2009-06-01

    Full Text Available Experimental protein-protein interaction (PPI networks are increasingly being exploited in diverse ways for biological discovery. Accordingly, it is vital to discern their underlying natures by identifying and classifying the various types of deterministic (specific and probabilistic (nonspecific interactions detected. To this end, we have analyzed PPI networks determined using a range of high-throughput experimental techniques with the aim of systematically quantifying any biases that arise from the varying cellular abundances of the proteins. We confirm that PPI networks determined using affinity purification methods for yeast and Escherichia coli incorporate a correlation between protein degree, or number of interactions, and cellular abundance. The observed correlations are small but statistically significant and occur in both unprocessed (raw and processed (high-confidence data sets. In contrast, the yeast two-hybrid system yields networks that contain no such relationship. While previously commented based on mRNA abundance, our more extensive analysis based on protein abundance confirms a systematic difference between PPI networks determined from the two technologies. We additionally demonstrate that the centrality-lethality rule, which implies that higher-degree proteins are more likely to be essential, may be misleading, as protein abundance measurements identify essential proteins to be more prevalent than nonessential proteins. In fact, we generally find that when there is a degree/abundance correlation, the degree distributions of nonessential and essential proteins are also disparate. Conversely, when there is no degree/abundance correlation, the degree distributions of nonessential and essential proteins are not different. However, we show that essentiality manifests itself as a biological property in all of the yeast PPI networks investigated here via enrichments of interactions between essential proteins. These findings provide

  4. Influence of protein abundance on high-throughput protein-protein interaction detection.

    Science.gov (United States)

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

    2009-06-05

    Experimental protein-protein interaction (PPI) networks are increasingly being exploited in diverse ways for biological discovery. Accordingly, it is vital to discern their underlying natures by identifying and classifying the various types of deterministic (specific) and probabilistic (nonspecific) interactions detected. To this end, we have analyzed PPI networks determined using a range of high-throughput experimental techniques with the aim of systematically quantifying any biases that arise from the varying cellular abundances of the proteins. We confirm that PPI networks determined using affinity purification methods for yeast and Escherichia coli incorporate a correlation between protein degree, or number of interactions, and cellular abundance. The observed correlations are small but statistically significant and occur in both unprocessed (raw) and processed (high-confidence) data sets. In contrast, the yeast two-hybrid system yields networks that contain no such relationship. While previously commented based on mRNA abundance, our more extensive analysis based on protein abundance confirms a systematic difference between PPI networks determined from the two technologies. We additionally demonstrate that the centrality-lethality rule, which implies that higher-degree proteins are more likely to be essential, may be misleading, as protein abundance measurements identify essential proteins to be more prevalent than nonessential proteins. In fact, we generally find that when there is a degree/abundance correlation, the degree distributions of nonessential and essential proteins are also disparate. Conversely, when there is no degree/abundance correlation, the degree distributions of nonessential and essential proteins are not different. However, we show that essentiality manifests itself as a biological property in all of the yeast PPI networks investigated here via enrichments of interactions between essential proteins. These findings provide valuable insights

  5. Prediction and characterization of protein-protein interaction networks in swine

    Directory of Open Access Journals (Sweden)

    Wang Fen

    2012-01-01

    Full Text Available Abstract Background Studying the large-scale protein-protein interaction (PPI network is important in understanding biological processes. The current research presents the first PPI map of swine, which aims to give new insights into understanding their biological processes. Results We used three methods, Interolog-based prediction of porcine PPI network, domain-motif interactions from structural topology-based prediction of porcine PPI network and motif-motif interactions from structural topology-based prediction of porcine PPI network, to predict porcine protein interactions among 25,767 porcine proteins. We predicted 20,213, 331,484, and 218,705 porcine PPIs respectively, merged the three results into 567,441 PPIs, constructed four PPI networks, and analyzed the topological properties of the porcine PPI networks. Our predictions were validated with Pfam domain annotations and GO annotations. Averages of 70, 10,495, and 863 interactions were related to the Pfam domain-interacting pairs in iPfam database. For comparison, randomized networks were generated, and averages of only 4.24, 66.79, and 44.26 interactions were associated with Pfam domain-interacting pairs in iPfam database. In GO annotations, we found 52.68%, 75.54%, 27.20% of the predicted PPIs sharing GO terms respectively. However, the number of PPI pairs sharing GO terms in the 10,000 randomized networks reached 52.68%, 75.54%, 27.20% is 0. Finally, we determined the accuracy and precision of the methods. The methods yielded accuracies of 0.92, 0.53, and 0.50 at precisions of about 0.93, 0.74, and 0.75, respectively. Conclusion The results reveal that the predicted PPI networks are considerably reliable. The present research is an important pioneering work on protein function research. The porcine PPI data set, the confidence score of each interaction and a list of related data are available at (http://pppid.biositemap.com/.

  6. 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

  7. Strongly Interacting Light Dark Matter

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    Sebastian Bruggisser, Francesco Riva, Alfredo Urbano

    2017-09-01

    Full Text Available In the presence of approximate global symmetries that forbid relevant interactions, strongly coupled light Dark Matter (DM can appear weakly coupled at small energy and generate a sizable relic abundance. Fundamental principles like unitarity restrict these symmetries to a small class, where the leading interactions are captured by effective operators up to dimension-8. Chiral symmetry, spontaneously broken global symmetries and non-linearly realized supersymmetry are examples of this. Their DM candidates (composite fermions, pseudo Nambu-Goldstone Bosons and Goldstini are interesting targets for LHC missing-energy searches.

  8. Strongly interacting light dark matter

    International Nuclear Information System (INIS)

    Bruggisser, Sebastian; Riva, Francesco; Urbano, Alfredo

    2016-07-01

    In the presence of approximate global symmetries that forbid relevant interactions, strongly coupled light Dark Matter (DM) can appear weakly coupled at small-energy and generate a sizable relic abundance. Fundamental principles like unitarity restrict these symmetries to a small class, where the leading interactions are captured by effective operators up to dimension-8. Chiral symmetry, spontaneously broken global symmetries and non-linearly realized supersymmetry are examples of this. Their DM candidates (composite fermions, pseudo-Nambu-Goldstone Bosons and Goldstini) are interesting targets for LHC missing-energy searches.

  9. Scalar strong interaction hadron theory

    CERN Document Server

    Hoh, Fang Chao

    2015-01-01

    The scalar strong interaction hadron theory, SSI, is a first principles' and nonlocal theory at quantum mechanical level that provides an alternative to low energy QCD and Higgs related part of the standard model. The quark-quark interaction is scalar rather than color-vectorial. A set of equations of motion for mesons and another set for baryons have been constructed. This book provides an account of the present state of a theory supposedly still at its early stage of development. This work will facilitate researchers interested in entering into this field and serve as a basis for possible future development of this theory.

  10. 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.

  11. Features of protein-protein interactions that translate into potent inhibitors: topology, surface area and affinity.

    Science.gov (United States)

    Smith, Matthew C; Gestwicki, Jason E

    2012-07-26

    Protein-protein interactions (PPIs) control the assembly of multi-protein complexes and, thus, these contacts have enormous potential as drug targets. However, the field has produced a mix of both exciting success stories and frustrating challenges. Here, we review known examples and explore how the physical features of a PPI, such as its affinity, hotspots, off-rates, buried surface area and topology, might influence the chances of success in finding inhibitors. This analysis suggests that concise, tight binding PPIs are most amenable to inhibition. However, it is also clear that emerging technical methods are expanding the repertoire of 'druggable' protein contacts and increasing the odds against difficult targets. In particular, natural product-like compound libraries, high throughput screens specifically designed for PPIs and approaches that favour discovery of allosteric inhibitors appear to be attractive routes. The first group of PPI inhibitors has entered clinical trials, further motivating the need to understand the challenges and opportunities in pursuing these types of targets.

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

    Science.gov (United States)

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

    2017-03-08

    Damaged central nervous system (CNS) neurons have a poor ability to spontaneously regenerate, causing persistent functional deficits after injury. Therapies that stimulate axon growth are needed to repair CNS damage. 14-3-3 adaptors are hub proteins that are attractive targets to manipulate cell signaling. We identify a positive role for 14-3-3s in axon growth and uncover a developmental regulation of the phosphorylation and function of 14-3-3s. We show that fusicoccin-A (FC-A), a small-molecule stabilizer of 14-3-3 protein-protein interactions, stimulates axon growth in vitro and regeneration in vivo. We show that FC-A stabilizes a complex between 14-3-3 and the stress response regulator GCN1, inducing GCN1 turnover and neurite outgrowth. These findings show that 14-3-3 adaptor protein complexes are druggable targets and identify a new class of small molecules that may be further optimized for the repair of CNS damage. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Classifying protein-protein interaction articles using word and syntactic features.

    Science.gov (United States)

    Kim, Sun; Wilbur, W John

    2011-10-03

    Identifying protein-protein interactions (PPIs) from literature is an important step in mining the function of individual proteins as well as their biological network. Since it is known that PPIs have distinctive patterns in text, machine learning approaches have been successfully applied to mine these patterns. However, the complex nature of PPI description makes the extraction process difficult. Our approach utilizes both word and syntactic features to effectively capture PPI patterns from biomedical literature. The proposed method automatically identifies gene names by a Priority Model, then extracts grammar relations using a dependency parser. A large margin classifier with Huber loss function learns from the extracted features, and unknown articles are predicted using this data-driven model. For the BioCreative III ACT evaluation, our official runs were ranked in top positions by obtaining maximum 89.15% accuracy, 61.42% F1 score, 0.55306 MCC score, and 67.98% AUC iP/R score. Even though problems still remain, utilizing syntactic information for article-level filtering helps improve PPI ranking performance. The proposed system is a revision of previously developed algorithms in our group for the ACT evaluation. Our approach is valuable in showing how to use grammatical relations for PPI article filtering, in particular, with a limited training corpus. While current performance is far from satisfactory as an annotation tool, it is already useful for a PPI article search engine since users are mainly focused on highly-ranked results.

  14. Deciphering the protein-protein interaction network regulating hepatocellular carcinoma metastasis.

    Science.gov (United States)

    Qin, Guoxuan; Dang, Mengjiao; Gao, Huajun; Wang, Hao; Luo, Fengting; Chen, Ruibing

    2017-09-01

    Hepatocellular carcinoma (HCC) is one of the leading causes of mortality related to cancer all over the world. To better understand the molecular mechanisms of HCC metastasis, we analyzed the proteome of three HCC cell lines with different metastasis potentials by quantitative proteomics and bioinformatics analysis. As a result, we identified 378 cellular proteins potentially associated to HCC metastasis, and constructed a highly connected protein-protein interaction (PPI) network. Functional annotation of the network uncovered prominent pathways and key roles of these proteins, suggesting that the metabolism and cytoskeleton biological processes are greatly involved with HCC metastasis. Furthermore, the integrative network analysis revealed a rich-club organization within the PPI network, indicating a hub center of connections. The rich-club nodes include several well-known cancer-related proteins, such as proto-oncogene non-receptor tyrosine kinase (SRC) and pyruvate kinase M2 (PKM2). Moreover, the differential expressions of two identified proteins, including PKM2 and actin-related protein 2/3 complex subunit 4 (ARPC4), were validated using Western blotting. These two proteins were revealed as potential prognostic markers for HCC as shown by survival rate analysis. Copyright © 2017. Published by Elsevier B.V.

  15. Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature.

    Directory of Open Access Journals (Sweden)

    Gurusamy Murugesan

    Full Text Available Automatic extraction of protein-protein interaction (PPI pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK. DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM. Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems.

  16. Evolution versus "intelligent design": comparing the topology of protein-protein interaction networks to the Internet.

    Science.gov (United States)

    Yang, Q; Siganos, G; Faloutsos, M; Lonardi, S

    2006-01-01

    Recent research efforts have made available genome-wide, high-throughput protein-protein interaction (PPI) maps for several model organisms. This has enabled the systematic analysis of PPI networks, which has become one of the primary challenges for the system biology community. In this study, we attempt to understand better the topological structure of PPI networks by comparing them against man-made communication networks, and more specifically, the Internet. Our comparative study is based on a comprehensive set of graph metrics. Our results exhibit an interesting dichotomy. On the one hand, both networks share several macroscopic properties such as scale-free and small-world properties. On the other hand, the two networks exhibit significant topological differences, such as the cliqueishness of the highest degree nodes. We attribute these differences to the distinct design principles and constraints that both networks are assumed to satisfy. We speculate that the evolutionary constraints that favor the survivability and diversification are behind the building process of PPI networks, whereas the leading force in shaping the Internet topology is a decentralized optimization process geared towards efficient node communication.

  17. 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.

  18. Global versus local hubs in human protein-protein interaction network.

    Science.gov (United States)

    Kiran, Manjari; Nagarajaram, Hampapathalu Adimurthy

    2013-12-06

    In this study, we have constructed tissue-specific protein-protein interaction networks for 70 human tissues and have identified three types of hubs based on their expression breadths: (a) tissue-specific hubs (TSHs) (proteins that are expressed in ≤ 10 tissues and also form hubs in ≤ 10 tissues), (b) tissue-preferred hubs (TPHs) (proteins expressed in ≥ 60 tissues but are highly connected in ≤ 10 tissues), and (c) housekeeping hubs (HKHs) (proteins that are expressed in ≥ 60 tissues and also form hubs in ≥ 60 tissues). Comparative analyses revealed significant differences between TSHs and HKHs and also revealed that TPHs behave more like HKHs. TSHs are lengthier, more disordered, and also quickly evolving proteins as compared with HKHs. Despite having a similar number of binding surfaces and interacting domains, TSHs are associated with a lower degree of centrality as compared with HKHs, suggesting that TSHs are "unsaturated" with regard to their binding capability and are perhaps evolving with regard to their interactions. TSHs are less abundantly expressed as compared with HKHs and are enriched with PEST motifs, indicating their tight regulation. All of these properties of TSHs and HKHs correlate with their distinct functional roles; TSHs are involved in tissue-specific functional roles, viz., secretors, receptors, and signaling proteins, whereas HKHs are involved in core-cellular functions such as transcription, translation, and so on. Our study, therefore, brings forth a clear and distinct classification of hubs simply based on their expression breadth and further assumes significance in the light of the highly debated dichotomy of date and party hubs, which is based on the coexpression pattern of hubs with their partners.

  19. 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.

  20. 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

  1. Specific-ion effects on the aggregation mechanisms and protein-protein interactions for anti-streptavidin immunoglobulin gamma-1.

    Science.gov (United States)

    Barnett, Gregory V; Razinkov, Vladimir I; Kerwin, Bruce A; Laue, Thomas M; Woodka, Andrea H; Butler, Paul D; Perevozchikova, Tatiana; Roberts, Christopher J

    2015-05-07

    Non-native protein aggregation is common in the biopharmaceutical industry and potentially jeopardizes product shelf life, therapeutic efficacy, and patient safety. The present article focuses on the relationship(s) among protein-protein interactions, aggregate growth mechanisms, aggregate morphologies, and specific-ion effects for an anti-streptavidin (AS) immunoglobulin gamma 1 (IgG1). Aggregation mechanisms of AS-IgG1 were determined as a function of pH and NaCl concentration with sodium acetate buffer and compared to previous work with sodium citrate. Aggregate size and shape were determined using a combination of laser light scattering and small-angle neutron or X-ray scattering. Protein-protein interactions were quantified in terms of the protein-protein Kirkwood-Buff integral (G22) determined from static light scattering and in terms of the protein effective charge (Zeff) measured using electrophoretic light scattering. Changing from citrate to acetate resulted in significantly different protein-protein interactions as a function of pH for low NaCl concentrations when the protein displayed positive Zeff. Overall, the results suggest that electrostatic repulsions between proteins were lessened because of preferential accumulation of citrate anions, compared to acetate anions, at the protein surface. The predominant aggregation mechanisms correlated well with G22, indicating that ion-specific effects beyond traditional mean-field descriptions of electrostatic protein-protein interactions are important for predicting qualitative shifts in protein aggregation state diagrams. Interestingly, while solution conditions dictated which mechanisms predominated, aggregate average molecular weight and size displayed a common scaling behavior across both citrate- and acetate-based systems.

  2. LocFuse: human protein-protein interaction prediction via classifier fusion using protein localization information.

    Science.gov (United States)

    Zahiri, Javad; Mohammad-Noori, Morteza; Ebrahimpour, Reza; Saadat, Samaneh; Bozorgmehr, Joseph H; Goldberg, Tatyana; Masoudi-Nejad, Ali

    2014-12-01

    Protein-protein interaction (PPI) detection is one of the central goals of functional genomics and systems biology. Knowledge about the nature of PPIs can help fill the widening gap between sequence information and functional annotations. Although experimental methods have produced valuable PPI data, they also suffer from significant limitations. Computational PPI prediction methods have attracted tremendous attentions. Despite considerable efforts, PPI prediction is still in its infancy in complex multicellular organisms such as humans. Here, we propose a novel ensemble learning method, LocFuse, which is useful in human PPI prediction. This method uses eight different genomic and proteomic features along with four types of different classifiers. The prediction performance of this classifier selection method was found to be considerably better than methods employed hitherto. This confirms the complex nature of the PPI prediction problem and also the necessity of using biological information for classifier fusion. The LocFuse is available at: http://lbb.ut.ac.ir/Download/LBBsoft/LocFuse. The results revealed that if we divide proteome space according to the cellular localization of proteins, then the utility of some classifiers in PPI prediction can be improved. Therefore, to predict the interaction for any given protein pair, we can select the most accurate classifier with regard to the cellular localization information. Based on the results, we can say that the importance of different features for PPI prediction varies between differently localized proteins; however in general, our novel features, which were extracted from position-specific scoring matrices (PSSMs), are the most important ones and the Random Forest (RF) classifier performs best in most cases. LocFuse was developed with a user-friendly graphic interface and it is freely available for Linux, Mac OSX and MS Windows operating systems. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. Conserved cysteine residues provide a protein-protein interaction surface in dual oxidase (DUOX) proteins.

    Science.gov (United States)

    Meitzler, Jennifer L; Hinde, Sara; Bánfi, Botond; Nauseef, William M; Ortiz de Montellano, Paul R

    2013-03-08

    Intramolecular disulfide bond formation is promoted in oxidizing extracellular and endoplasmic reticulum compartments and often contributes to protein stability and function. DUOX1 and DUOX2 are distinguished from other members of the NOX protein family by the presence of a unique extracellular N-terminal region. These peroxidase-like domains lack the conserved cysteines that confer structural stability to mammalian peroxidases. Sequence-based structure predictions suggest that the thiol groups present are solvent-exposed on a single protein surface and are too distant to support intramolecular disulfide bond formation. To investigate the role of these thiol residues, we introduced four individual cysteine to glycine mutations in the peroxidase-like domains of both human DUOXs and purified the recombinant proteins. The mutations caused little change in the stabilities of the monomeric proteins, supporting the hypothesis that the thiol residues are solvent-exposed and not involved in disulfide bonds that are critical for structural integrity. However, the ability of the isolated hDUOX1 peroxidase-like domain to dimerize was altered, suggesting a role for these cysteines in protein-protein interactions that could facilitate homodimerization of the peroxidase-like domain or, in the full-length protein, heterodimeric interactions with a maturation protein. When full-length hDUOX1 was expressed in HEK293 cells, the mutations resulted in decreased H2O2 production that correlated with a decreased amount of the enzyme localized to the membrane surface rather than with a loss of activity or with a failure to synthesize the mutant proteins. These results support a role for the cysteine residues in intermolecular disulfide bond formation with the DUOX maturation factor DUOXA1.

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

    Science.gov (United States)

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

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

    Science.gov (United States)

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

    2015-01-01

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

  6. Natural products used as a chemical library for protein-protein interaction targeted drug discovery.

    Science.gov (United States)

    Jin, Xuemei; Lee, Kyungro; Kim, Nam Hee; Kim, Hyun Sil; Yook, Jong In; Choi, Jiwon; No, Kyoung Tai

    2018-01-01

    Protein-protein interactions (PPIs), which are essential for cellular processes, have been recognized as attractive therapeutic targets. Therefore, the construction of a PPI-focused chemical library is an inevitable necessity for future drug discovery. Natural products have been used as traditional medicines to treat human diseases for millennia; in addition, their molecular scaffolds have been used in diverse approved drugs and drug candidates. The recent discovery of the ability of natural products to inhibit PPIs led us to use natural products as a chemical library for PPI-targeted drug discovery. In this study, we collected natural products (NPDB) from non-commercial and in-house databases to analyze their similarities to small-molecule PPI inhibitors (iPPIs) and FDA-approved drugs by using eight molecular descriptors. Then, we evaluated the distribution of NPDB and iPPIs in the chemical space, represented by the molecular fingerprint and molecular scaffolds, to identify the promising scaffolds, which could interfere with PPIs. To investigate the ability of natural products to inhibit PPI targets, molecular docking was used. Then, we predicted a set of high-potency natural products by using the iPPI-likeness score based on a docking score-weighted model. These selected natural products showed high binding affinities to the PPI target, namely XIAP, which were validated in an in vitro experiment. In addition, the natural products with novel scaffolds might provide a promising starting point for further medicinal chemistry developments. Overall, our study shows the potency of natural products in targeting PPIs, which might help in the design of a PPI-focused chemical library for future drug discovery. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. 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.

  8. 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

  9. Targeting Protein-Protein Interactions in the Ubiquitin-Proteasome Pathway.

    Science.gov (United States)

    Gaczynska, Maria; Osmulski, Pawel A

    2018-01-01

    The ubiquitin-proteasome pathway (UPP) is a major venue for controlled intracellular protein degradation in Eukaryota. The machinery of several hundred proteins is involved in recognizing, tagging, transporting, and cleaving proteins, all in a highly regulated manner. Short-lived transcription factors, misfolded translation products, stress-damaged polypeptides, or worn-out long-lived proteins, all can be found among the substrates of UPP. Carefully choreographed protein-protein interactions (PPI) are involved in each step of the pathway. For many of the steps small-molecule inhibitors have been identified and often they directly or indirectly target PPI. The inhibitors may destabilize intracellular proteostasis and trigger apoptosis. So far this is the most explored option used as an anticancer strategy. Alternatively, substrate-specific polyubiquitination may be regulated for a precise intervention aimed at a particular metabolic pathway. This very attractive opportunity is moving close to clinical application. The best known drug target in UPP is the proteasome: the end point of the journey of a protein destined for degradation. The proteasome alone is a perfect object to study the mechanisms and roles of PPI on many levels. This giant protease is built from multisubunit modules and additionally utilizes a service from transient protein ligands, for example, delivering substrates. An elaborate set of PPI within the highest-order proteasome assembly is involved in substrate recognition and processing. Below we will outline PPI involved in the UPP and discuss the growing prospects for their utilization in pharmacological interventions. © 2018 Elsevier Inc. All rights reserved.

  10. BioPlex Display: An Interactive Suite for Large-Scale AP-MS Protein-Protein Interaction Data.

    Science.gov (United States)

    Schweppe, Devin K; Huttlin, Edward L; Harper, J Wade; Gygi, Steven P

    2018-01-05

    The development of large-scale data sets requires a new means to display and disseminate research studies to large audiences. Knowledge of protein-protein interaction (PPI) networks has become a principle interest of many groups within the field of proteomics. At the confluence of technologies, such as cross-linking mass spectrometry, yeast two-hybrid, protein cofractionation, and affinity purification mass spectrometry (AP-MS), detection of PPIs can uncover novel biological inferences at a high-throughput. Thus new platforms to provide community access to large data sets are necessary. To this end, we have developed a web application that enables exploration and dissemination of the growing BioPlex interaction network. BioPlex is a large-scale interactome data set based on AP-MS of baits from the human ORFeome. The latest BioPlex data set release (BioPlex 2.0) contains 56 553 interactions from 5891 AP-MS experiments. To improve community access to this vast compendium of interactions, we developed BioPlex Display, which integrates individual protein querying, access to empirical data, and on-the-fly annotation of networks within an easy-to-use and mobile web application. BioPlex Display enables rapid acquisition of data from BioPlex and development of hypotheses based on protein interactions.

  11. Protein Charge and Mass Contribute to the Spatio-temporal Dynamics of Protein-Protein Interactions in a Minimal Proteome

    Science.gov (United States)

    Xu, Yu; Wang, Hong; Nussinov, Ruth; Ma, Buyong

    2013-01-01

    We constructed and simulated a ‘minimal proteome’ model using Langevin dynamics. It contains 206 essential protein types which were compiled from the literature. For comparison, we generated six proteomes with randomized concentrations. We found that the net charges and molecular weights of the proteins in the minimal genome are not random. The net charge of a protein decreases linearly with molecular weight, with small proteins being mostly positively charged and large proteins negatively charged. The protein copy numbers in the minimal genome have the tendency to maximize the number of protein-protein interactions in the network. Negatively charged proteins which tend to have larger sizes can provide large collision cross-section allowing them to interact with other proteins; on the other hand, the smaller positively charged proteins could have higher diffusion speed and are more likely to collide with other proteins. Proteomes with random charge/mass populations form less stable clusters than those with experimental protein copy numbers. Our study suggests that ‘proper’ populations of negatively and positively charged proteins are important for maintaining a protein-protein interaction network in a proteome. It is interesting to note that the minimal genome model based on the charge and mass of E. Coli may have a larger protein-protein interaction network than that based on the lower organism M. pneumoniae. PMID:23420643

  12. 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. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. 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.

  14. Identification of Novel Inhibitory Peptides of Protein-Protein Interactions Involved in DNA Repair as Potential Drugs in Breast Cancer Treatment

    National Research Council Canada - National Science Library

    Beck, William

    2001-01-01

    Protein-protein interactions are critical to almost every cellular process. Disruption of these interactions would effectively interfere with the cell's functions and its ability to grow and divide normally...

  15. Identification of Naval Inhibitory Peptides of Protein-Protein Interactions Involved in DNA Repair as Potential Drugs in Breast Cancer Treatment

    National Research Council Canada - National Science Library

    Kamalakaran, Sitharthan

    2003-01-01

    Protein-protein interactions are critical to almost every cellular process. Disruption of these interactions would effectively interfere with the cell's functions and its ability to grow and divide normally...

  16. 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.

  17. Construction and analysis of protein-protein interaction network correlated with ankylosing spondylitis.

    Science.gov (United States)

    Kanwal, Attiya; Fazal, Sahar

    2018-01-05

    Ankylosing spondylitis, a systemic illness is a foundation of progressing joint swelling that for the most part influences the spine. However, it frequently causes aggravation in different joints far from the spine, and in addition organs, for example, the eyes, heart, lungs, and kidneys. It's an immune system ailment that may be activated by specific sorts of bacterial or viral diseases that initiate an invulnerable reaction that don't close off after the contamination is recuperated. The particular reason for ankylosing spondylitis is obscure, yet hereditary qualities assume a huge part in this condition. The rising apparatuses of network medicine offer a stage to investigate an unpredictable illness at framework level. In this study, we meant to recognize the key proteins and the biological regulator pathways including in AS and further investigating the molecular connectivity between these pathways by the topological examination of the Protein-protein communication (PPI) system. The extended network including of 93 nodes and have 199 interactions respectively scanned from STRING database and some separated small networks. 24 proteins with high BC at the threshold of 0.01 and 55 proteins with large degree at the threshold of 1 have been identified. CD4 with highest BC and Closeness centrality located in the centre of the network. The backbone network derived from high BC proteins presents a clear and visual overview which shows all important regulatory pathways for AS and the crosstalk between them. The finding of this research suggests that AS variation is orchestrated by an integrated PPI network centered on CD4 out of 93 nodes. Ankylosing spondylitis, a systemic disease is an establishment of advancing joint swelling that generally impacts the spine. Be that as it may, it as often as possible causes disturbance in various joints a long way from the spine, and what's more organs. It's a resistant framework affliction that might be actuated by particular sorts

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

    Science.gov (United States)

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

    2017-06-21

    For many voltage-gated ion channels (VGICs), creation of a properly functioning ion channel requires the formation of specific protein-protein interactions between the transmembrane pore-forming subunits and cystoplasmic accessory subunits. Despite the importance of such protein-protein interactions in VGIC function and assembly, their potential as sites for VGIC modulator development has been largely overlooked. Here, we develop meta-xylyl (m-xylyl) stapled peptides that target a prototypic VGIC high affinity protein-protein interaction, the interaction between the voltage-gated calcium channel (Ca V ) pore-forming subunit α-interaction domain (AID) and cytoplasmic β-subunit (Ca V β). We show using circular dichroism spectroscopy, X-ray crystallography, and isothermal titration calorimetry that the m-xylyl staples enhance AID helix formation are structurally compatible with native-like AID:Ca V β interactions and reduce the entropic penalty associated with AID binding to Ca V β. Importantly, electrophysiological studies reveal that stapled AID peptides act as effective inhibitors of the Ca V α 1 :Ca V β interaction that modulate Ca V function in an Ca V β isoform-selective manner. Together, our studies provide a proof-of-concept demonstration of the use of protein-protein interaction inhibitors to control VGIC function and point to strategies for improved AID-based Ca V modulator design.

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

    Science.gov (United States)

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

    2015-10-01

    The V1VO-ATPase (V-ATPase) is the important proton-pump in eukaryotic cells, responsible for pH-homeostasis, pH-sensing and amino acid sensing, and therefore essential for cell growths and metabolism. ATP-cleavage in the catalytic A3B3-hexamer of V1 has to be communicated via several so-called central and peripheral stalk units to the proton-pumping VO-part, which is membrane-embedded. A unique feature of V1VO-ATPase regulation is its reversible disassembly of the V1 and VO domain. Actin provides a network to hold the V1 in proximity to the VO, enabling effective V1VO-assembly to occur. Besides binding to actin, the 14-subunit V-ATPase interacts with multi-subunit machineries to form cellular sensors, which regulate the pH in cellular compartments or amino acid signaling in lysosomes. Here we describe a variety of subunit-subunit interactions within the V-ATPase enzyme during catalysis and its protein-protein assembling with key cellular machineries, essential for cellular function. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Protein-protein interactions between proteins of Citrus tristeza virus isolates.

    Science.gov (United States)

    Nchongboh, Chofong Gilbert; Wu, Guan-Wei; Hong, Ni; Wang, Guo-Ping

    2014-12-01

    Citrus tristeza virus (CTV) is one of the most devastating pathogens of citrus. Its genome is organized into 12 open reading frames (ORFs), of which ten ORFs located at the 3'-terminus of the genome have multiple biological functions. The ten genes at the 3'-terminus of the genome of a severe isolate (CTV-S4) and three ORFs (CP, CPm and p20) of three other isolates (N4, S45 and HB1) were cloned into pGBKT7 and pGADT7 yeast shuttle vectors. Yeast two-hybridization (Y2H) assays results revealed a strong self-interaction for CP and p20, and a unique interaction between the CPm of CTV-S4 (severe) and CP of CTV-N4 (mild) isolates. Bimolecular fluorescence complementation also confirmed these interactions. Analysis of the deletion mutants delineated the domains of CP and p20 self-interaction. Furthermore, the domains responsible for CP and p20 self-interactions were mapped at the CP amino acids sites 41-84 and p20 amino acids sites 1-21 by Y2H. This study provided new information on CTV protein interactions which will help for further understanding the biological functions.

  1. Strongly interacting photons and atoms

    International Nuclear Information System (INIS)

    Alge, W.

    1999-05-01

    This thesis contains the main results of the research topics I have pursued during the my PhD studies at the University of Innsbruck and partly in collaboration with the Institut d' Optique in Orsay, France. It is divided into three parts. The first and largest part discusses the possibility of using strong standing waves as a tool to cool and trap neutral atoms in optical cavities. This is very important in the field of nonlinear optics where several successful experiments with cold atoms in cavities have been performed recently. A discussion of the optical parametric oscillator in a regime where the nonlinearity dominates the evolution is the topic of the second part. We investigated mainly the statistical properties of the cavity output of the three interactive cavity modes. Very recently a system has been proposed which promises fantastic properties. It should exhibit a giant Kerr nonlinearity with negligible absorption thus leading to a photonic turnstile device based on cold atoms in cavity. We have shown that this model suffers from overly simplistic assumptions and developed several more comprehensive approaches to study the behavior of this system. Apart from the division into three parts of different contents the thesis is divided into publications, supplements and invisible stuff. The intention of the supplements is to reach researchers which work in related areas and provide them with more detailed information about the concepts and the numerical tools we used. It is written especially for diploma and PhD students to give them a chance to use the third part of our work which is actually the largest one. They consist of a large number of computer programs we wrote to investigate the behavior of the systems in parameter regions where no hope exists to solve the equations analytically. (author)

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

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    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

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

    Science.gov (United States)

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

    2015-12-01

    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 are natively

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

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    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

  5. Insight into bacterial virulence mechanisms against host immune response via the Yersinia pestis-human protein-protein interaction network.

    Science.gov (United States)

    Yang, Huiying; Ke, Yuehua; Wang, Jian; Tan, Yafang; Myeni, Sebenzile K; Li, Dong; Shi, Qinghai; Yan, Yanfeng; Chen, Hui; Guo, Zhaobiao; Yuan, Yanzhi; Yang, Xiaoming; Yang, Ruifu; Du, Zongmin

    2011-11-01

    A Yersinia pestis-human protein interaction network is reported here to improve our understanding of its pathogenesis. Up to 204 interactions between 66 Y. pestis bait proteins and 109 human proteins were identified by yeast two-hybrid assay and then combined with 23 previously published interactions to construct a protein-protein interaction network. Topological analysis of the interaction network revealed that human proteins targeted by Y. pestis were significantly enriched in the proteins that are central in the human protein-protein interaction network. Analysis of this network showed that signaling pathways important for host immune responses were preferentially targeted by Y. pestis, including the pathways involved in focal adhesion, regulation of cytoskeleton, leukocyte transendoepithelial migration, and Toll-like receptor (TLR) and mitogen-activated protein kinase (MAPK) signaling. Cellular pathways targeted by Y. pestis are highly relevant to its pathogenesis. Interactions with host proteins involved in focal adhesion and cytoskeketon regulation pathways could account for resistance of Y. pestis to phagocytosis. Interference with TLR and MAPK signaling pathways by Y. pestis reflects common characteristics of pathogen-host interaction that bacterial pathogens have evolved to evade host innate immune response by interacting with proteins in those signaling pathways. Interestingly, a large portion of human proteins interacting with Y. pestis (16/109) also interacted with viral proteins (Epstein-Barr virus [EBV] and hepatitis C virus [HCV]), suggesting that viral and bacterial pathogens attack common cellular functions to facilitate infections. In addition, we identified vasodilator-stimulated phosphoprotein (VASP) as a novel interaction partner of YpkA and showed that YpkA could inhibit in vitro actin assembly mediated by VASP.

  6. Membrane-mediated interaction between strongly anisotropic protein scaffolds.

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    Yonatan Schweitzer

    2015-02-01

    Full Text Available Specialized proteins serve as scaffolds sculpting strongly curved membranes of intracellular organelles. Effective membrane shaping requires segregation of these proteins into domains and is, therefore, critically dependent on the protein-protein interaction. Interactions mediated by membrane elastic deformations have been extensively analyzed within approximations of large inter-protein distances, small extents of the protein-mediated membrane bending and small deviations of the protein shapes from isotropic spherical segments. At the same time, important classes of the realistic membrane-shaping proteins have strongly elongated shapes with large and highly anisotropic curvature. Here we investigated, computationally, the membrane mediated interaction between proteins or protein oligomers representing membrane scaffolds with strongly anisotropic curvature, and addressed, quantitatively, a specific case of the scaffold geometrical parameters characterizing BAR domains, which are crucial for membrane shaping in endocytosis. In addition to the previously analyzed contributions to the interaction, we considered a repulsive force stemming from the entropy of the scaffold orientation. We computed this interaction to be of the same order of magnitude as the well-known attractive force related to the entropy of membrane undulations. We demonstrated the scaffold shape anisotropy to cause a mutual aligning of the scaffolds and to generate a strong attractive interaction bringing the scaffolds close to each other to equilibrium distances much smaller than the scaffold size. We computed the energy of interaction between scaffolds of a realistic geometry to constitute tens of kBT, which guarantees a robust segregation of the scaffolds into domains.

  7. 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.

  8. 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. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Genome-wide analysis of protein-protein interactions and involvement of viral proteins in SARS-CoV replication.

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    Ji'an Pan

    Full Text Available Analyses of viral protein-protein interactions are an important step to understand viral protein functions and their underlying molecular mechanisms. In this study, we adopted a mammalian two-hybrid system to screen the genome-wide intraviral protein-protein interactions of SARS coronavirus (SARS-CoV and therefrom revealed a number of novel interactions which could be partly confirmed by in vitro biochemical assays. Three pairs of the interactions identified were detected in both directions: non-structural protein (nsp 10 and nsp14, nsp10 and nsp16, and nsp7 and nsp8. The interactions between the multifunctional nsp10 and nsp14 or nsp16, which are the unique proteins found in the members of Nidovirales with large RNA genomes including coronaviruses and toroviruses, may have important implication for the mechanisms of replication/transcription complex assembly and functions of these viruses. Using a SARS-CoV replicon expressing a luciferase reporter under the control of a transcription regulating sequence, it has been shown that several viral proteins (N, X and SUD domains of nsp3, and nsp12 provided in trans stimulated the replicon reporter activity, indicating that these proteins may regulate coronavirus replication and transcription. Collectively, our findings provide a basis and platform for further characterization of the functions and mechanisms of coronavirus proteins.

  10. Mapping of protein-protein interaction sites in the plant-type [2Fe-2S] ferredoxin.

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    Haruka Kameda

    Full Text Available Knowing the manner of protein-protein interactions is vital for understanding biological events. The plant-type [2Fe-2S] ferredoxin (Fd, a well-known small iron-sulfur protein with low redox potential, partitions electrons to a variety of Fd-dependent enzymes via specific protein-protein interactions. Here we have refined the crystal structure of a recombinant plant-type Fd I from the blue green alga Aphanothece sacrum (AsFd-I at 1.46 Å resolution on the basis of the synchrotron radiation data. Incorporating the revised amino-acid sequence, our analysis corrects the 3D structure previously reported; we identified the short α-helix (67-71 near the active center, which is conserved in other plant-type [2Fe-2S] Fds. Although the 3D structures of the four molecules in the asymmetric unit are similar to each other, detailed comparison of the four structures revealed the segments whose conformations are variable. Structural comparison between the Fds from different sources showed that the distribution of the variable segments in AsFd-I is highly conserved in other Fds, suggesting the presence of intrinsically flexible regions in the plant-type [2Fe-2S] Fd. A few structures of the complexes with Fd-dependent enzymes clearly demonstrate that the protein-protein interactions are achieved through these variable regions in Fd. The results described here will provide a guide for interpreting the biochemical and mutational studies that aim at the manner of interactions with Fd-dependent enzymes.

  11. Bcl-XL-templated assembly of its own protein-protein interaction modulator from fragments decorated with thio acids and sulfonyl azides

    Science.gov (United States)

    Hu, Xiangdong; Sun, Jiazhi; Wang, Hong-Gang; Manetsch, Roman

    2008-01-01

    Protein-protein interactions have key importance in various biological processes and modulation of particular protein-protein interactions has been shown to have therapeutic effects. However, disrupting or modulating protein-protein interactions with low-molecular-weight compounds is extremely difficult due to the lack of deep binding pockets on protein surfaces. Herein we describe the development of an unprecedented lead synthesis and discovery method that generates only biologically active compounds from a library of reactive fragments. Using the protein Bcl-XL, a central regulator of programmed cell death, we demonstrated that an amidation reaction between thio acids and sulfonyl azides is applicable for Bcl-XL-templated assembly of inhibitory compounds. We have demonstrated for the first time that kinetic target-guided synthesis can be applied not only on enzymatic targets but also for the discovery of small molecules modulating protein-protein interactions. PMID:18811158

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

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    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/.

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

    Science.gov (United States)

    Browne, Fiona; Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

    2009-01-26

    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. 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. 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/.

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

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    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.

  15. PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs

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    Greenblatt Jack

    2006-07-01

    Full Text Available Abstract Background Identification of protein interaction networks has received considerable attention in the post-genomic era. The currently available biochemical approaches used to detect protein-protein interactions are all time and labour intensive. Consequently there is a growing need for the development of computational tools that are capable of effectively identifying such interactions. Results Here we explain the development and implementation of a novel Protein-Protein Interaction Prediction Engine termed PIPE. This tool is capable of predicting protein-protein interactions for any target pair of the yeast Saccharomyces cerevisiae proteins from their primary structure and without the need for any additional information or predictions about the proteins. PIPE showed a sensitivity of 61% for detecting any yeast protein interaction with 89% specificity and an overall accuracy of 75%. This rate of success is comparable to those associated with the most commonly used biochemical techniques. Using PIPE, we identified a novel interaction between YGL227W (vid30 and YMR135C (gid8 yeast proteins. This lead us to the identification of a novel yeast complex that here we term vid30 complex (vid30c. The observed interaction was confirmed by tandem affinity purification (TAP tag, verifying the ability of PIPE to predict novel protein-protein interactions. We then used PIPE analysis to investigate the internal architecture of vid30c. It appeared from PIPE analysis that vid30c may consist of a core and a secondary component. Generation of yeast gene deletion strains combined with TAP tagging analysis indicated that the deletion of a member of the core component interfered with the formation of vid30c, however, deletion of a member of the secondary component had little effect (if any on the formation of vid30c. Also, PIPE can be used to analyse yeast proteins for which TAP tagging fails, thereby allowing us to predict protein interactions that are not

  16. Revealing Two-State Protein-Protein Interaction of Calmodulin by Single-Molecule Spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Ruchuan; Hu, Dehong; Tan, Xin; Lu, H PETER.

    2006-08-09

    We report a single-molecule fluorescence resonance energy transfer (FRET) and polarization study of conformational dynamics of calmodulin (CaM) interacting with a target peptide, C28W of 28 amino-acid oligomer. The C28W peptide represents the essential binding sequence domain of the Ca-ATPase protein interacting with CaM, which is important in cellular signaling for the regulation of energy in metabolism. However, the mechanism of the CaM-C28W recognition complex formation is still unclear. The amino-terminal (N-terminal) domain of the CaM was labeled with a fluorescein-based arsenical hairpin binder (F1AsH) that enables our unambiguously probing the CaM N-terminal target-binding domain motions at a millisecond timescale without convolution of the probe-dye random motions. By analyzing the distribution of FRET efficiency between F1AsH labeled CaM and Texas Red labeled C28W and the polarization fluctuation dynamics and distributions of the CaM N-terminal domain, we reveal slow (at sub-second time scale) binding-unbinding motions of the N-terminal domain of the CaM in CaM-C28W complexes, which is a strong evidence of a two-state binding interaction of CaM-mediated cell signaling.

  17. Changing MADS-Box Transcription Factor Protein-Protein Interactions as a Mechanism for Generating Floral Morphological Diversity.

    Science.gov (United States)

    Bartlett, Madelaine E

    2017-12-01

    Flowers display fantastic morphological diversity. Despite extreme variability in form, floral organ identity is specified by a core set of deeply conserved proteins-the floral MADS-box transcription factors. This indicates that while core gene function has been maintained, MADS-box transcription factors have evolved to regulate different downstream genes. Thus, the evolution of gene regulation downstream of the MADS-box transcription factors is likely central to the evolution of floral form. Gene regulation is determined by the combination of transcriptional regulators present at a particular cis-regulatory element at a particular time. Therefore, the interactions between transcription factors can be of profound importance in determining patterns of gene regulation. Here, after a short primer on flowers and floral morphology, I discuss the centrality of protein-protein interactions to MADS-box transcription factor function, and review the evidence that the evolution of MADS-box protein-protein interactions is a key driver in the evolution of gene regulation downstream of the MADS-box genes. © The Author 2017. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

  18. InSilico Proteomics System: Integration and Application of Protein and Protein-Protein Interaction Data using Microsoft .NET

    Directory of Open Access Journals (Sweden)

    Straßer Wolfgang

    2006-12-01

    Full Text Available In the last decades, biological databases became the major knowledge resource for researchers in the field of molecular biology. The distribution of information among these databases is one of the major problems. An overview about the subject area of data access and representation of protein and protein-protein interaction data within public biological databases is described. For a comprehensive and consistent way of searching and analysing integrated protein and protein-protein interaction data, the InSilico Proteomics (ISP project has been initiated. Its three main objectives are (1 to provide an integrated knowledge pool for data investigation and global network analysis functions for a better understanding of a cell’s interactome, (2 employment of public data for plausibility analysis and validation of in-house experimental data and (3 testing the applicability of Microsoft’s .NET architecture for bioinformatics applications. Data integrated into the ISP database can be queried through the Web portal PRIMOS (PRotein Interaction and MOlecule Search which is freely available at http://biomis.fh-hagenberg.at/isp/primos.

  19. Photolytic Cross-Linking to Probe Protein-Protein and Protein-Matrix Interactions in Lyophilized Powders.

    Science.gov (United States)

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

    2015-09-08

    Protein structure and local environment in lyophilized formulations were probed using high-resolution solid-state photolytic cross-linking with mass spectrometric analysis (ssPC-MS). In order to characterize structure and microenvironment, protein-protein, protein-excipient, and protein-water interactions in lyophilized powders were identified. Myoglobin (Mb) was derivatized in solution with the heterobifunctional probe succinimidyl 4,4'-azipentanoate (SDA) and the structural integrity of the labeled protein (Mb-SDA) confirmed using CD spectroscopy and liquid chromatography/mass spectrometry (LC-MS). Mb-SDA was then formulated with and without excipients (raffinose, guanidine hydrochloride (Gdn HCl)) and lyophilized. The freeze-dried powder was irradiated with ultraviolet light at 365 nm for 30 min to produce cross-linked adducts that were analyzed at the intact protein level and after trypsin digestion. SDA-labeling produced Mb carrying up to five labels, as detected by LC-MS. Following lyophilization and irradiation, cross-linked peptide-peptide, peptide-water, and peptide-raffinose adducts were detected. The exposure of Mb side chains to the matrix was quantified based on the number of different peptide-peptide, peptide-water, and peptide-excipient adducts detected. In the absence of excipients, peptide-peptide adducts involving the CD, DE, and EF loops and helix H were common. In the raffinose formulation, peptide-peptide adducts were more distributed throughout the molecule. The Gdn HCl formulation showed more protein-protein and protein-water adducts than the other formulations, consistent with protein unfolding and increased matrix interactions. The results demonstrate that ssPC-MS can be used to distinguish excipient effects and characterize the local protein environment in lyophilized formulations with high resolution.

  20. Fluorescence Lifetime Imaging Microscopy (FLIM) as a Tool to Investigate Hypoxia-Induced Protein-Protein Interaction in Living Cells.

    Science.gov (United States)

    Schützhold, Vera; Fandrey, Joachim; Prost-Fingerle, Katrin

    2018-01-01

    Fluorescence resonance energy transfer (FRET) is widely used as a method to investigate protein-protein interactions in living cells. A FRET pair donor fluorophore in close proximity to an appropriate acceptor fluorophore transfers emission energy to the acceptor, resulting in a shorter lifetime of the donor fluorescence. When the respective FRET donor and acceptor are fused with two proteins of interest, a reduction in donor lifetime, as detected by fluorescence lifetime imaging microscopy (FLIM), can be taken as proof of close proximity between the fluorophores and therefore interaction between the proteins of interest. Here, we describe the usage of time-domain FLIM-FRET in hypoxia-related research when we record the interaction of the hypoxia-inducible factor-1 (HIF-1) subunits HIF-1α and HIF-1β in living cells in a temperature- and CO 2 -controlled environment under the microscope.

  1. 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.

  2. Structure-Based Design and Synthesis of Potent Cyclic Peptides Inhibiting the YAP-TEAD Protein-Protein Interaction.

    Science.gov (United States)

    Zhang, Zhisen; Lin, Zhaohu; Zhou, Zheng; Shen, Hong C; Yan, S Frank; Mayweg, Alexander V; Xu, Zhiheng; Qin, Ning; Wong, Jason C; Zhang, Zhenshan; Rong, Yiping; Fry, David C; Hu, Taishan

    2014-09-11

    The YAP-TEAD protein-protein interaction (PPI) mediates the oncogenic function of YAP, and inhibitors of this PPI have potential usage in treatment of YAP-involved cancers. Here we report the design and synthesis of potent cyclic peptide inhibitors of the YAP-TEAD interaction. A truncation study of YAP interface 3 peptide identified YAP(84-100) as a weak peptide inhibitor (IC50 = 37 μM), and an alanine scan revealed a beneficial mutation, D94A. Subsequent replacement of a native cation-π interaction with an optimized disulfide bridge for conformational constraint and synergistic effect between macrocyclization and modification at positions 91 and 93 greatly boosted inhibitory activity. Peptide 17 was identified with an IC50 of 25 nM, and the binding affinity (K d = 15 nM) of this 17mer peptide to TEAD1 proved to be stronger than YAP(50-171) (K d = 40 nM).

  3. Adding biological meaning to human protein-protein interactions identified by yeast two-hybrid screenings: A guide through bioinformatics tools.

    Science.gov (United States)

    Felgueiras, Juliana; Silva, Joana Vieira; Fardilha, Margarida

    2018-01-16

    "A man is known by the company he keeps" is a popular expression that perfectly fits proteins. A common approach to characterize the function of a target protein is to identify its interacting partners and thus infer its roles based on the known functions of the interactors. Protein-protein interaction networks (PPINs) have been created for several organisms, including humans, primarily as results of high-throughput screenings, such as yeast two-hybrid (Y2H). Their unequivocal use to understand events underlying human pathophysiology is promising in identifying genes and proteins associated with diseases. Therefore, numerous opportunities have emerged for PPINs as tools for clinical management of diseases: network-based disease classification systems, discovery of biomarkers and identification of therapeutic targets. Despite the great advantages of PPINs, their use is still unrecognised by several researchers who generate high-throughput data to generally characterize interactions in a certain model or to select an interaction to study in detail. We strongly believe that both approaches are not exclusive and that we can use PPINs as a complementary methodology and rich-source of information to the initial study proposal. Here, we suggest a pipeline to deal with Y2H results using bioinformatics tools freely available for academics. Yeast two-hybrid is widely-used to identify protein-protein interactions. Conventionally, the positive clones that result from a yeast two-hybrid screening are sequenced to identify the interactors of the protein of interest (also known as bait protein), and few interactions, thought as potentially relevant for the model in study, are selected for further validation using biochemical methods (e.g. co-immunoprecipitation and co-localization). The huge amount of data that is potentially lost during this conservative approach motivated us to write this tutorial-like review, so that researchers feel encouraged to take advantage of

  4. Identification of new protein-protein and protein-DNA interactions linked with wood formation in Populus trichocarpa.

    Science.gov (United States)

    Petzold, H Earl; Rigoulot, Stephen B; Zhao, Chengsong; Chanda, Bidisha; Sheng, Xiaoyan; Zhao, Mingzhe; Jia, Xiaoyan; Dickerman, Allan W; Beers, Eric P; Brunner, Amy M

    2018-03-01

    Cellular processes, such as signal transduction and cell wall deposition, are organized by macromolecule interactions. Experimentally determined protein-protein interactions (PPIs) and protein-DNA interactions (PDIs) relevant to woody plant development are sparse. To begin to develop a Populus trichocarpa Torr. & A. Gray wood interactome, we applied the yeast-two-hybrid (Y2H) assay in different ways to enable the discovery of novel PPIs and connected networks. We first cloned open reading frames (ORFs) for 361 genes markedly upregulated in secondary xylem compared with secondary phloem and performed a binary Y2H screen with these proteins. By screening a xylem cDNA library for interactors of a subset of these proteins and then recapitulating the process by using a subset of the interactors as baits, we ultimately identified 165 PPIs involving 162 different ORFs. Thirty-eight transcription factors (TFs) included in our collection of P. trichocarpa wood ORFs were used in a Y1H screen for binding to promoter regions of three genes involved in lignin biosynthesis resulting in 40 PDIs involving 20 different TFs. The network incorporating both the PPIs and PDIs included 14 connected subnetworks, with the largest having 132 members. Protein-protein interactions and PDIs validated previous reports and also identified new candidate wood formation proteins and modules through their interactions with proteins and promoters known to be involved in secondary cell wall synthesis. Selected examples are discussed including a PPI between Mps one binder (MOB1) and a mitogen-activated protein kinase kinase kinase kinase (M4K) that was further characterized by assays confirming the PPI as well as its effect on subcellular localization. Mapping of published transcriptomic data showing developmentally detailed expression patterns across a secondary stem onto the network supported that the PPIs and PDIs are relevant to wood formation, and also illustrated that wood

  5. 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

  6. Remnants of strong tidal interactions

    International Nuclear Information System (INIS)

    Mcglynn, T.A.

    1990-01-01

    This paper examines the properties of stellar systems that have recently undergone a strong tidal shock, i.e., a shock which removes a significant fraction of the particles in the system, and where the shocked system has a much smaller mass than the producer of the tidal field. N-body calculations of King models shocked in a variety of ways are performed, and the consequences of the shocks are investigated. The results confirm the prediction of Jaffe for shocked systems. Several models are also run where the tidal forces on the system are constant, simulating a circular orbit around a primary, and the development of tidal radii under these static conditions appears to be a mild process which does not dramatically affect material that is not stripped. The tidal radii are about twice as large as classical formulas would predict. Remnant density profiles are compared with a sample of elliptical galaxies, and the implications of the results for the development of stellar populations and galaxies are considered. 38 refs

  7. Analysis of hepatocellular carcinoma and metastatic hepatic carcinoma via functional modules in a protein-protein interaction network

    Directory of Open Access Journals (Sweden)

    Jun Pan

    2014-01-01

    Full Text Available Introduction: This study aims to identify protein clusters with potential functional relevance in the pathogenesis of hepatocellular carcinoma (HCC and metastatic hepatic carcinoma using network analysis. Materials and Methods: We used human protein interaction data to build a protein-protein interaction network with Cytoscape and then derived functional clusters using MCODE. Combining the gene expression profiles, we calculated the functional scores for the clusters and selected statistically significant clusters. Meanwhile, Gene Ontology was used to assess the functionality of these clusters. Finally, a support vector machine was trained on the gold standard data sets. Results: The differentially expressed genes of HCC were mainly involved in metabolic and signaling processes. We acquired 13 significant modules from the gene expression profiles. The area under the curve value based on the differentially expressed modules were 98.31%, which outweighed the classification with DEGs. Conclusions: Differentially expressed modules are valuable to screen biomarkers combined with functional modules.

  8. 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 Summary: 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. : Li et al. developed a recombinase-enhanced bimolecular luciferase complementation platform, termed ReBiL, to evaluate low-affinity protein-protein interactions (PPIs that are not detectable by other methods and to analyze PPI antagonists in living cells. ReBiL showed that small-molecule p53-Mdm2 antagonists disrupt their intended targets effectively in cells, whereas stapled peptides did not. Stapled peptides unexpectedly induced cell membrane disruption resulting in p53-independent death associated with cytoplasmic leakage. ReBiL is also valuable for high-throughput screening and for deciphering signaling mechanisms mediated by protein interactions.

  9. Analysing protein-protein interactions of the Myxococcus xanthus Dif signalling pathway using the yeast two-hybrid system.

    Science.gov (United States)

    Lancero, Hope L; Castaneda, Schryl; Caberoy, Nora B; Ma, Xiaoyuan; Garza, Anthony G; Shi, Wenyuan

    2005-05-01

    The dif operon is essential for fruiting body formation, fibril (exopolysaccharide) production and social motility of Myxococcus xanthus. The dif locus contains a gene cluster homologous to chemotaxis genes such as mcp (difA), cheW (difC), cheY (difD), cheA (difE) and cheC (difF), as well as an unknown ORF called difB. This study used yeast two-hybrid analysis to investigate possible interactions between Dif proteins, and determined that DifA, C, D and E interact in a similar fashion to chemotaxis proteins of Escherichia coli and Bacillus subtilis. It also showed that DifF interacted with DifD, and that the novel protein DifB did not interact with Dif proteins. Furthermore, DifA-F proteins were used to determine other possible protein-protein interactions in the M. xanthus genomic library. The authors not only confirmed the specific interactions among known Dif proteins, but also discovered two novel interactions between DifE and Nla19, and DifB and YidC, providing some new information about the Dif signalling pathway. Based on these findings, a model for the Dif signalling pathway is proposed.

  10. Viscosity Analysis of Dual Variable Domain Immunoglobulin Protein Solutions: Role of Size, Electroviscous Effect and Protein-Protein Interactions.

    Science.gov (United States)

    Raut, Ashlesha S; Kalonia, Devendra S

    2016-01-01

    Increased solution viscosity results in difficulties in manufacturing and delivery of therapeutic protein formulations, increasing both the time and production costs, and leading to patient inconvenience. The solution viscosity is affected by the molecular properties of both the solute and the solvent. The purpose of this work was to investigate the effect of size, charge and protein-protein interactions on the viscosity of Dual Variable Domain Immunoglobulin (DVD-Ig(TM)) protein solutions. The effect of size of the protein molecule on solution viscosity was investigated by measuring intrinsic viscosity and excluded volume calculations for monoclonal antibody (mAb) and DVD-Ig(TM) protein solutions. The role of the electrostatic charge resulting in electroviscous effects for DVD-Ig(TM) protein was assessed by measuring zeta potential. Light scattering measurements were performed to detect protein-protein interactions affecting solution viscosity. DVD-Ig(TM) protein exhibited significantly higher viscosity compared to mAb. Intrinsic viscosity and excluded volume calculations indicated that the size of the molecule affects viscosity significantly at higher concentrations, while the effect was minimal at intermediate concentrations. Electroviscous contribution to the viscosity of DVD-Ig(TM) protein varied depending on the presence or absence of ions in the solution. In buffered solutions, negative k D and B 2 values indicated the presence of attractive interactions which resulted in high viscosity for DVD-Ig(TM) protein at certain pH and ionic strength conditions. Results show that more than one factor contributes to the increased viscosity of DVD-Ig(TM) protein and interplay of these factors modulates the overall viscosity behavior of the solution, especially at higher concentrations.

  11. Bio::Homology::InterologWalk--a Perl module to build putative protein-protein interaction networks through interolog mapping.

    Science.gov (United States)

    Gallone, Giuseppe; Simpson, T Ian; Armstrong, J Douglas; Jarman, Andrew P

    2011-07-18

    Protein-protein interaction (PPI) data are widely used to generate network models that aim to describe the relationships between proteins in biological systems. The fidelity and completeness of such networks is primarily limited by the paucity of protein interaction information and by the restriction of most of these data to just a few widely studied experimental organisms. In order to extend the utility of existing PPIs, computational methods can be used that exploit functional conservation between orthologous proteins across taxa to predict putative PPIs or 'interologs'. To date most interolog prediction efforts have been restricted to specific biological domains with fixed underlying data sources and there are no software tools available that provide a generalised framework for 'on-the-fly' interolog prediction. We introduce Bio::Homology::InterologWalk, a Perl module to retrieve, prioritise and visualise putative protein-protein interactions through an orthology-walk method. The module uses orthology and experimental interaction data to generate putative PPIs and optionally collates meta-data into an Interaction Prioritisation Index that can be used to help prioritise interologs for further analysis. We show the application of our interolog prediction method to the genomic interactome of the fruit fly, Drosophila melanogaster. We analyse the resulting interaction networks and show that the method proposes new interactome members and interactions that are candidates for future experimental investigation. Our interolog prediction tool employs the Ensembl Perl API and PSICQUIC enabled protein interaction data sources to generate up to date interologs 'on-the-fly'. This represents a significant advance on previous methods for interolog prediction as it allows the use of the latest orthology and protein interaction data for all of the genomes in Ensembl. The module outputs simple text files, making it easy to customise the results by post-processing, allowing the

  12. Bio::Homology::InterologWalk - A Perl module to build putative protein-protein interaction networks through interolog mapping

    Directory of Open Access Journals (Sweden)

    Armstrong J Douglas

    2011-07-01

    Full Text Available Abstract Background Protein-protein interaction (PPI data are widely used to generate network models that aim to describe the relationships between proteins in biological systems. The fidelity and completeness of such networks is primarily limited by the paucity of protein interaction information and by the restriction of most of these data to just a few widely studied experimental organisms. In order to extend the utility of existing PPIs, computational methods can be used that exploit functional conservation between orthologous proteins across taxa to predict putative PPIs or 'interologs'. To date most interolog prediction efforts have been restricted to specific biological domains with fixed underlying data sources and there are no software tools available that provide a generalised framework for 'on-the-fly' interolog prediction. Results We introduce Bio::Homology::InterologWalk, a Perl module to retrieve, prioritise and visualise putative protein-protein interactions through an orthology-walk method. The module uses orthology and experimental interaction data to generate putative PPIs and optionally collates meta-data into an Interaction Prioritisation Index that can be used to help prioritise interologs for further analysis. We show the application of our interolog prediction method to the genomic interactome of the fruit fly, Drosophila melanogaster. We analyse the resulting interaction networks and show that the method proposes new interactome members and interactions that are candidates for future experimental investigation. Conclusions Our interolog prediction tool employs the Ensembl Perl API and PSICQUIC enabled protein interaction data sources to generate up to date interologs 'on-the-fly'. This represents a significant advance on previous methods for interolog prediction as it allows the use of the latest orthology and protein interaction data for all of the genomes in Ensembl. The module outputs simple text files, making it easy

  13. 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.

  14. Prioritization of candidate genes for cattle reproductive traits, based on protein-protein interactions, gene expression, and text-mining

    DEFF Research Database (Denmark)

    Hulsegge, Ina; Woelders, Henri; Smits, Mari

    2013-01-01

    Reproduction is of significant economic importance in dairy cattle. Improved understanding of mechanisms that control estrous behavior and other reproduction traits could help in developing strategies to improve and/or monitor these traits. The objective of this study was to predict and rank genes...... and processes in brain areas and pituitary involved in reproductive traits in cattle using information derived from three different data sources: gene expression, protein-protein interactions, and literature. We identified 59, 89, 53, 23, and 71 genes in bovine amygdala, dorsal hypothalamus, hippocampus......, pituitary, and ventral hypothalamus, respectively, potentially involved in processes underlying estrus and estrous behavior. Functional annotation of the candidate genes points to a number of tissue-specific processes of which the "neurotransmitter/ion channel/synapse" process in the amygdala, "steroid...

  15. Dynamic modular architecture of protein-protein interaction networks beyond the dichotomy of 'date' and 'party' hubs.

    Science.gov (United States)

    Chang, Xiao; Xu, Tao; Li, Yun; Wang, Kai

    2013-01-01

    The protein-protein interaction (PPI) networks are dynamically organized as modules, and are typically described by hub dichotomy: 'party' hubs act as intramodule hubs and are coexpressed with their partners, yet 'date' hubs act as coordinators among modules and are incoherently expressed with their partners. However, there remains skepticism about the existence of hub dichotomy. Since different algorithms and data sets were used in previous studies to test the model of hub classification, the conclusions may be largely influenced by the potential inherent biases. In this study, we evaluated two data sets of yeast interactome, and systematically investigated the behavior of hubs from multiple perspectives including co-expression patterns, topological roles and functional classifications. Our results revealed consistency between the two data sets, confirming the presence of hub dichotomy. Furthermore, we analyzed a human interactome data set, and demonstrated that the modular architecture of the PPI networks was more complicated than hub dichotomy.

  16. Electrostatic similarities between protein and small molecule ligands facilitate the design of protein-protein interaction inhibitors.

    Directory of Open Access Journals (Sweden)

    Arnout Voet

    Full Text Available One of the underlying principles in drug discovery is that a biologically active compound is complimentary in shape and molecular recognition features to its receptor. This principle infers that molecules binding to the same receptor may share some common features. Here, we have investigated whether the electrostatic similarity can be used for the discovery of small molecule protein-protein interaction inhibitors (SMPPIIs. We have developed a method that can be used to evaluate the similarity of electrostatic potentials between small molecules and known protein ligands. This method was implemented in a software called EleKit. Analyses of all available (at the time of research SMPPII structures indicate that SMPPIIs bear some similarities of electrostatic potential with the ligand proteins of the same receptor. This is especially true for the more polar SMPPIIs. Retrospective analysis of several successful SMPPIIs has shown the applicability of EleKit in the design of new SMPPIIs.

  17. Novel Approaches to the Characterization of Specific Protein-Protein Interactions Important in Gene Expression

    National Research Council Canada - National Science Library

    Somerville, Ronald

    1998-01-01

    .... This dimeric protein interacts with specific operator targets associated with promoters that drive the production of proteins essential for aromatic amino acid biosynthesis or transport. Like its E...

  18. 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.

  19. The protein-protein interactions between SMPI and thermolysin studied by molecular dynamics and MM/PBSA calculations.

    Science.gov (United States)

    Adekoya, Olayiwola A; Willassen, Nils-Peder; Sylte, Ingebrigt

    2005-04-01

    Thermolysin is a zinc-metalloendopeptidase secreted by the gram-positive thermophilic bacterium Bacillus thermoproteolyticus. Thermolysin belongs to the gluzinicin family of enzymes, which is selectively inhibited by Steptomyces metalloproteinase inhibitor (SMPI). Very little is known about the interaction between SMPI and thermolysin. Knowledge about the protein-protein interactions is very important for designing new thermolysin inhibitors with possible industrial or pharmaceutical applications. In the present study, two binding modes between SMPI and thermolysin were studied by 2300 picoseconds (ps) of comparative molecular dynamics (MD) simulations and calculation of the free energy of binding using the molecular mechanics-Poisson-Boltmann surface area (MM/PBSA) method. One of the positions, the 'horizontal arrow head docking' (HAHD) was similar to the previously proposed binding mode by Tate et al. (Tate, S., Ohno, A., Seeram, S. S., Hiraga, K., Oda, K., and Kainosho, M. J. Mol. Biol. 282, 435-446 (1998)). The other position, the 'vertical arrow head docking' (VAHD) was obtained by a manual docking guided by the shape and charge distribution of SMPI and the binding pocket of thermolysin. The calculations showed that SMPI had stronger interactions with thermolysin in the VAHD than in the HAHD complex, and the VAHD complex was considered more realistic than the HAHD complex. SMPI interacted with thermolysin not only at the active site but had auxiliary binding sites contributing to proper interactions. The VAHD complex can be used for designing small molecule inhibitors mimicking the SMPI-thermolysin binding interfaces.

  20. Direct protein-protein interaction between PLCγ1 and the bradykinin B2 receptor-Importance of growth conditions

    International Nuclear Information System (INIS)

    Duchene, Johan; Chauhan, Sharmila D.; Lopez, Frederic; Pecher, Christiane; Esteve, Jean-Pierre; Girolami, Jean-Pierre; Bascands, Jean-Loup; Schanstra, Joost P.

    2005-01-01

    Recently, we have described a novel protein-protein interaction between the G-protein coupled bradykinin B2 receptor and tyrosine phosphatase SHP-2 via an immunoreceptor tyrosine-based inhibition motif (ITIM) sequence located in the C-terminal part of the B2 receptor and the Src homology (SH2) domains of SHP-2. Here we show that phospholipase C (PLC)γ1, another SH2 domain containing protein, can also interact with this ITIM sequence. Using surface plasmon resonance analysis, we observed that PLCγ1 interacted with a peptide containing the phosphorylated form of the bradykinin B2 receptor ITIM sequence. In CHO cells expressing the wild-type B2 receptor, bradykinin-induced transient recruitment and activation of PLCγ1. Interestingly, this interaction was only observed in quiescent and not in proliferating cells. Mutation of the key ITIM residue abolished this interaction with and activation of PLCγ1. Finally we also identified bradykinin-induced PLCγ1 recruitment and activation in primary culture renal mesangial cells

  1. SLIDER: A Generic Metaheuristic for the Discovery of Correlated Motifs in Protein-Protein Interaction Networks

    NARCIS (Netherlands)

    Boyen, P.; Dyck, van D.; Neven, F.; Ham, van R.C.H.J.; Dijk, van A.D.J.

    2011-01-01

    Correlated motif mining (CMM) is the problem of finding overrepresented pairs of patterns, called motifs, in sequences of interacting proteins. Algorithmic solutions for CMM thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a

  2. Building protein-protein interaction networks for Leishmania species through protein structural information.

    Science.gov (United States)

    Dos Santos Vasconcelos, Crhisllane Rafaele; de Lima Campos, Túlio; Rezende, Antonio Mauro

    2018-03-06

    Systematic analysis of a parasite interactome is a key approach to understand different biological processes. It makes possible to elucidate disease mechanisms, to predict protein functions and to select promising targets for drug development. Currently, several approaches for protein interaction prediction for non-model species incorporate only small fractions of the entire proteomes and their interactions. Based on this perspective, this study presents an integration of computational methodologies, protein network predictions and comparative analysis of the protozoan species Leishmania braziliensis and Leishmania infantum. These parasites cause Leishmaniasis, a worldwide distributed and neglected disease, with limited treatment options using currently available drugs. The predicted interactions were obtained from a meta-approach, applying rigid body docking tests and template-based docking on protein structures predicted by different comparative modeling techniques. In addition, we trained a machine-learning algorithm (Gradient Boosting) using docking information performed on a curated set of positive and negative protein interaction data. Our final model obtained an AUC = 0.88, with recall = 0.69, specificity = 0.88 and precision = 0.83. Using this approach, it was possible to confidently predict 681 protein structures and 6198 protein interactions for L. braziliensis, and 708 protein structures and 7391 protein interactions for L. infantum. The predicted networks were integrated to protein interaction data already available, analyzed using several topological features and used to classify proteins as essential for network stability. The present study allowed to demonstrate the importance of integrating different methodologies of interaction prediction to increase the coverage of the protein interaction of the studied protocols, besides it made available protein structures and interactions not previously reported.

  3. Predicting protein-protein interactions from multimodal biological data sources via nonnegative matrix tri-factorization.

    Science.gov (United States)

    Wang, Hua; Huang, Heng; Ding, Chris; Nie, Feiping

    2013-04-01

    Protein interactions are central to all the biological processes and structural scaffolds in living organisms, because they orchestrate a number of cellular processes such as metabolic pathways and immunological recognition. Several high-throughput methods, for example, yeast two-hybrid system and mass spectrometry method, can help determine protein interactions, which, however, suffer from high false-positive rates. Moreover, many protein interactions predicted by one method are not supported by another. Therefore, computational methods are necessary and crucial to complete the interactome expeditiously. In this work, we formulate the problem of predicting protein interactions from a new mathematical perspective--sparse matrix completion, and propose a novel nonnegative matrix factorization (NMF)-based matrix completion approach to predict new protein interactions from existing protein interaction networks. Through using manifold regularization, we further develop our method to integrate different biological data sources, such as protein sequences, gene expressions, protein structure information, etc. Extensive experimental results on four species, Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, and Caenorhabditis elegans, have shown that our new methods outperform related state-of-the-art protein interaction prediction methods.

  4. Algebra of strong and electroweak interactions

    International Nuclear Information System (INIS)

    Bolokhov, S.V.; Vladimirov, Yu.S.

    2004-01-01

    The algebraic approach to describing the electroweak and strong interactions is considered within the frames of the binary geometrophysics, based on the principles of the Fokker-Feynman direct interparticle interaction theories of the Kaluza-Klein multidimensional geometrical models and the physical structures theory. It is shown that in this approach the electroweak and strong elementary particles interaction through the intermediate vector bosons, are characterized by the subtypes of the algebraic classification of the complex 3 x 3-matrices [ru

  5. 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.

  6. Protein-Protein Interaction on Lysozyme Crystallization Revealed by Rotational Diffusion Analysis

    OpenAIRE

    Takahashi, Daisuke; Nishimoto, Etsuko; Murase, Tadashi; Yamashita, Shoji

    2008-01-01

    Intermolecular interactions between protein molecules diffusing in various environments underlie many biological processes as well as control protein crystallization, which is a crucial step in x-ray protein structure determinations. Protein interactions were investigated through protein rotational diffusion analysis. First, it was confirmed that tetragonal lysozyme crystals containing fluorescein-tagged lysozyme were successfully formed with the same morphology as that of native protein. Usi...

  7. Prediction of protein-protein interaction sites in sequences and 3D structures by random forests.

    Directory of Open Access Journals (Sweden)

    Mile Sikić

    2009-01-01

    Full Text Available Identifying interaction sites in proteins provides important clues to the function of a protein and is becoming increasingly relevant in topics such as systems biology and drug discovery. Although there are numerous papers on the prediction of interaction sites using information derived from structure, there are only a few case reports on the prediction of interaction residues based solely on protein sequence. Here, a sliding window approach is combined with the Random Forests method to predict protein interaction sites using (i a combination of sequence- and structure-derived parameters and (ii sequence information alone. For sequence-based prediction we achieved a precision of 84% with a 26% recall and an F-measure of 40%. When combined with structural information, the prediction performance increases to a precision of 76% and a recall of 38% with an F-measure of 51%. We also present an attempt to rationalize the sliding window size and demonstrate that a nine-residue window is the most suitable for predictor construction. Finally, we demonstrate the applicability of our prediction methods by modeling the Ras-Raf complex using predicted interaction sites as target binding interfaces. Our results suggest that it is possible to predict protein interaction sites with quite a high accuracy using only sequence information.

  8. 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.

  9. Ranking support vector machine for multiple kernels output combination in protein-protein interaction extraction from biomedical literature.

    Science.gov (United States)

    Yang, Zhihao; Lin, Yuan; Wu, Jiajin; Tang, Nan; Lin, Hongfei; Li, Yanpeng

    2011-10-01

    Knowledge about protein-protein interactions (PPIs) unveils the molecular mechanisms of biological processes. However, the volume and content of published biomedical literature on protein interactions is expanding rapidly, making it increasingly difficult for interaction database curators to detect and curate protein interaction information manually. We present a multiple kernel learning-based approach for automatic PPI extraction from biomedical literature. The approach combines the following kernels: feature-based, tree, and graph and combines their output with Ranking support vector machine (SVM). Experimental evaluations show that the features in individual kernels are complementary and the kernel combined with Ranking SVM achieves better performance than those of the individual kernels, equal weight combination and optimal weight combination. Our approach can achieve state-of-the-art performance with respect to the comparable evaluations, with 64.88% F-score and 88.02% AUC on the AImed corpus. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Determining Effects of Non-synonymous SNPs on Protein-Protein Interactions using Supervised and Semi-supervised Learning

    Science.gov (United States)

    Zhao, Nan; Han, Jing Ginger; Shyu, Chi-Ren; Korkin, Dmitry

    2014-01-01

    Single nucleotide polymorphisms (SNPs) are among the most common types of genetic variation in complex genetic disorders. A growing number of studies link the functional role of SNPs with the networks and pathways mediated by the disease-associated genes. For example, many non-synonymous missense SNPs (nsSNPs) have been found near or inside the protein-protein interaction (PPI) interfaces. Determining whether such nsSNP will disrupt or preserve a PPI is a challenging task to address, both experimentally and computationally. Here, we present this task as three related classification problems, and develop a new computational method, called the SNP-IN tool (non-synonymous SNP INteraction effect predictor). Our method predicts the effects of nsSNPs on PPIs, given the interaction's structure. It leverages supervised and semi-supervised feature-based classifiers, including our new Random Forest self-learning protocol. The classifiers are trained based on a dataset of comprehensive mutagenesis studies for 151 PPI complexes, with experimentally determined binding affinities of the mutant and wild-type interactions. Three classification problems were considered: (1) a 2-class problem (strengthening/weakening PPI mutations), (2) another 2-class problem (mutations that disrupt/preserve a PPI), and (3) a 3-class classification (detrimental/neutral/beneficial mutation effects). In total, 11 different supervised and semi-supervised classifiers were trained and assessed resulting in a promising performance, with the weighted f-measure ranging from 0.87 for Problem 1 to 0.70 for the most challenging Problem 3. By integrating prediction results of the 2-class classifiers into the 3-class classifier, we further improved its performance for Problem 3. To demonstrate the utility of SNP-IN tool, it was applied to study the nsSNP-induced rewiring of two disease-centered networks. The accurate and balanced performance of SNP-IN tool makes it readily available to study the rewiring of

  11. STRING v9.1: protein-protein interaction networks, with increased coverage and integration.

    Science.gov (United States)

    Franceschini, Andrea; Szklarczyk, Damian; Frankild, Sune; Kuhn, Michael; Simonovic, Milan; Roth, Alexander; Lin, Jianyi; Minguez, Pablo; Bork, Peer; von Mering, Christian; Jensen, Lars J

    2013-01-01

    Complete knowledge of all direct and indirect interactions between proteins in a given cell would represent an important milestone towards a comprehensive description of cellular mechanisms and functions. Although this goal is still elusive, considerable progress has been made-particularly for certain model organisms and functional systems. Currently, protein interactions and associations are annotated at various levels of detail in online resources, ranging from raw data repositories to highly formalized pathway databases. For many applications, a global view of all the available interaction data is desirable, including lower-quality data and/or computational predictions. The STRING database (http://string-db.org/) aims to provide such a global perspective for as many organisms as feasible. Known and predicted associations are scored and integrated, resulting in comprehensive protein networks covering >1100 organisms. Here, we describe the update to version 9.1 of STRING, introducing several improvements: (i) we extend the automated mining of scientific texts for interaction information, to now also include full-text articles; (ii) we entirely re-designed the algorithm for transferring interactions from one model organism to the other; and (iii) we provide users with statistical information on any functional enrichment observed in their networks.

  12. 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.

  13. 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.

  14. Updates to the Integrated Protein-Protein Interaction Benchmarks : Docking Benchmark Version 5 and Affinity Benchmark Version 2

    NARCIS (Netherlands)

    Vreven, Thom; Moal, Iain H.; Vangone, Anna|info:eu-repo/dai/nl/370549694; Pierce, Brian G.; Kastritis, Panagiotis L.|info:eu-repo/dai/nl/315886668; Torchala, Mieczyslaw; Chaleil, Raphael; Jiménez-García, Brian; Bates, Paul A.; Fernandez-Recio, Juan; Bonvin, Alexandre M J J|info:eu-repo/dai/nl/113691238; Weng, Zhiping

    2015-01-01

    We present an updated and integrated version of our widely used protein-protein docking and binding affinity benchmarks. The benchmarks consist of non-redundant, high-quality structures of protein-protein complexes along with the unbound structures of their components. Fifty-five new complexes were

  15. An Integrated Docking Pipeline for the Prediction of Large-Scale Protein-Protein Interactions

    Science.gov (United States)

    2010-06-01

    their cognate chaperone. The type III secretion system ( T3SS ) used by Yersinia pestis and many other Gram- negative bacteria plays an important...the underlying binding specificity of chaperone/effector interactions and devising possible strategies for interfering with T3SS transport

  16. Protein function prediction using neighbor relativity in protein-protein interaction network.

    Science.gov (United States)

    Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

    2013-04-01

    There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

  17. Inference of a Geminivirus-Host Protein-Protein Interaction Network through Affinity Purification and Mass Spectrometry Analysis.

    Science.gov (United States)

    Wang, Liping; Ding, Xue; Xiao, Jiajing; Jiménez-Gόngora, Tamara; Liu, Renyi; Lozano-Durán, Rosa

    2017-09-25

    Viruses reshape the intracellular environment of their hosts, largely through protein-protein interactions, to co-opt processes necessary for viral infection and interference with antiviral defences. Due to genome size constraints and the concomitant limited coding capacity of viruses, viral proteins are generally multifunctional and have evolved to target diverse host proteins. Inference of the virus-host interaction network can be instrumental for understanding how viruses manipulate the host machinery and how re-wiring of specific pathways can contribute to disease. Here, we use affinity purification and mass spectrometry analysis (AP-MS) to define the global landscape of interactions between the geminivirus Tomato yellow leaf curl virus (TYLCV) and its host Nicotiana benthamiana . For this purpose, we expressed tagged versions of each of TYLCV-encoded proteins (C1/Rep, C2/TrAP, C3/REn, C4, V2, and CP) in planta in the presence of the virus. Using a quantitative scoring system, 728 high-confidence plant interactors were identified, and the interaction network of each viral protein was inferred; TYLCV-targeted proteins are more connected than average, and connect with other proteins through shorter paths, which would allow the virus to exert large effects with few interactions. Comparative analyses of divergence patterns between N. benthamiana and potato, a non-host Solanaceae , showed evolutionary constraints on TYLCV-targeted proteins. Our results provide a comprehensive overview of plant proteins targeted by TYLCV during the viral infection, which may contribute to uncovering the underlying molecular mechanisms of plant viral diseases and provide novel potential targets for anti-viral strategies and crop engineering. Interestingly, some of the TYLCV-interacting proteins appear to be convergently targeted by other pathogen effectors, which suggests a central role for these proteins in plant-pathogen interactions, and pinpoints them as potential targets to

  18. Large-scale identification of potential drug targets based on the topological features of human protein-protein interaction network.

    Science.gov (United States)

    Li, Zhan-Chao; Zhong, Wen-Qian; Liu, Zhi-Qing; Huang, Meng-Hua; Xie, Yun; Dai, Zong; Zou, Xiao-Yong

    2015-04-29

    Identifying potential drug target proteins is a crucial step in the process of drug discovery and plays a key role in the study of the molecular mechanisms of disease. Based on the fact that the majority of proteins exert their functions through interacting with each other, we propose a method to recognize target proteins by using the human protein-protein interaction network and graph theory. In the network, vertexes and edges are weighted by using the confidence scores of interactions and descriptors of protein primary structure, respectively. The novel network topological features are defined and employed to characterize protein using existing databases. A widely used minimum redundancy maximum relevance and random forests algorithm are utilized to select the optimal feature subset and construct model for the identification of potential drug target proteins at the proteome scale. The accuracies of training set and test set are 89.55% and 85.23%. Using the constructed model, 2127 potential drug target proteins have been recognized and 156 drug target proteins have been validated in the database of drug target. In addition, some new drug target proteins can be considered as targets for treating diseases of mucopolysaccharidosis, non-arteritic anterior ischemic optic neuropathy, Bernard-Soulier syndrome and pseudo-von Willebrand, etc. It is anticipated that the proposed method may became a powerful high-throughput virtual screening tool of drug target. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Complexity of the Ruminococcus flavefaciens FD-1 cellulosome reflects an expansion of family-related protein-protein interactions.

    Science.gov (United States)

    Israeli-Ruimy, Vered; Bule, Pedro; Jindou, Sadanari; Dassa, Bareket; Moraïs, Sarah; Borovok, Ilya; Barak, Yoav; Slutzki, Michal; Hamberg, Yuval; Cardoso, Vânia; Alves, Victor D; Najmudin, Shabir; White, Bryan A; Flint, Harry J; Gilbert, Harry J; Lamed, Raphael; Fontes, Carlos M G A; Bayer, Edward A

    2017-02-10

    Protein-protein interactions play a vital role in cellular processes as exemplified by assembly of the intricate multi-enzyme cellulosome complex. Cellulosomes are assembled by selective high-affinity binding of enzyme-borne dockerin modules to repeated cohesin modules of structural proteins termed scaffoldins. Recent sequencing of the fiber-degrading Ruminococcus flavefaciens FD-1 genome revealed a particularly elaborate cellulosome system. In total, 223 dockerin-bearing ORFs potentially involved in cellulosome assembly and a variety of multi-modular scaffoldins were identified, and the dockerins were classified into six major groups. Here, extensive screening employing three complementary medium- to high-throughput platforms was used to characterize the different cohesin-dockerin specificities. The platforms included (i) cellulose-coated microarray assay, (ii) enzyme-linked immunosorbent assay (ELISA) and (iii) in-vivo co-expression and screening in Escherichia coli. The data revealed a collection of unique cohesin-dockerin interactions and support the functional relevance of dockerin classification into groups. In contrast to observations reported previously, a dual-binding mode is involved in cellulosome cell-surface attachment, whereas single-binding interactions operate for cellulosome integration of enzymes. This sui generis cellulosome model enhances our understanding of the mechanisms governing the remarkable ability of R. flavefaciens to degrade carbohydrates in the bovine rumen and provides a basis for constructing efficient nano-machines applied to biological processes.

  20. Prediction of residue-residue contact matrix for protein-protein interaction with Fisher score features and deep learning.

    Science.gov (United States)

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

    2016-11-01

    Protein-protein interactions play essential roles in many biological processes. Acquiring knowledge of the residue-residue contact information of two interacting proteins is not only helpful in annotating functions for proteins, but also critical for structure-based drug design. The prediction of the protein residue-residue contact matrix of the interfacial regions is challenging. In this work, we introduced deep learning techniques (specifically, stacked autoencoders) to build deep neural network models to tackled the residue-residue contact prediction problem. In tandem with interaction profile Hidden Markov Models, which was used first to extract Fisher score features from protein sequences, stacked autoencoders were deployed to extract and learn hidden abstract features. The deep learning model showed significant improvement over the traditional machine learning model, Support Vector Machines (SVM), with the overall accuracy increased by 15% from 65.40% to 80.82%. We showed that the stacked autoencoders could extract novel features, which can be utilized by deep neural networks and other classifiers to enhance learning, out of the Fisher score features. It is further shown that deep neural networks have significant advantages over SVM in making use of the newly extracted features. Copyright © 2016. Published by Elsevier Inc.

  1. Identification of Protein-Protein Interactions Involved in Pectin Biosynthesis in the golgi Apparatus

    DEFF Research Database (Denmark)

    Lund, Christian Have

    for instance as food additives, nutraceutical, for paper and energy production. Pectin is a cell wall glycan that crucial for every plant growing on land. Pectin is said to be one of the most complex glycans on earth and it is hypothesized that at least 67 enzymatic reactions are involved in its biosynthesis...... for their ability to detect PPI inside the Golgi lumen. The first method tested was the commercially available splitubiquitin system from Dualsystems Biotech AG. This was applied to test binary interactions between proteins involved in HG and Rhamnogalacturonan I (RG-I) biosynthesis (see Manuscript II...... (Rluc-PCA) in Nicotiana benthamiana (See Manuscript IV) to perform binary interaction screening in a mid- to high-throughput manner. Mutants of gaut7 knockout grow normally (Manuscript V). This led us to hypothesize additional anchors of GAUT1 may exit. Based on subcellular localization and homology...

  2. Carbene footprinting accurately maps binding sites in protein-ligand and protein-protein interactions

    Science.gov (United States)

    Manzi, Lucio; Barrow, Andrew S.; Scott, Daniel; Layfield, Robert; Wright, Timothy G.; Moses, John E.; Oldham, Neil J.

    2016-11-01

    Specific interactions between proteins and their binding partners are fundamental to life processes. The ability to detect protein complexes, and map their sites of binding, is crucial to understanding basic biology at the molecular level. Methods that employ sensitive analytical techniques such as mass spectrometry have the potential to provide valuable insights with very little material and on short time scales. Here we present a differential protein footprinting technique employing an efficient photo-activated probe for use with mass spectrometry. Using this methodology the location of a carbohydrate substrate was accurately mapped to the binding cleft of lysozyme, and in a more complex example, the interactions between a 100 kDa, multi-domain deubiquitinating enzyme, USP5 and a diubiquitin substrate were located to different functional domains. The much improved properties of this probe make carbene footprinting a viable method for rapid and accurate identification of protein binding sites utilizing benign, near-UV photoactivation.

  3. How common is the funnel-like energy landscape in protein-protein interactions?

    Science.gov (United States)

    Tovchigrechko, Andrei; Vakser, Ilya A.

    2001-01-01

    The goal of this study is to verify the concept of the funnel-like intermolecular energy landscape in protein–protein interactions by use of a series of computational experiments. Our preliminary analysis revealed the existence of the funnel in many protein–protein interactions. However, because of the uncertainties in the modeling of these interactions and the ambiguity of the analysis procedures, the detection of the funnels requires detailed quantitative approaches to the energy landscape analysis. A number of such approaches are presented in this study. We show that the funnel detection problem is equivalent to a problem of distinguishing between distributions of low-energy intermolecular matches in the funnel and in the low-frequency landscape fluctuations. If the fluctuations are random, the decision about whether the minimum is the funnel is equivalent to determining whether this minimum is significantly different from a would-be random one. A database of 475 nonredundant cocrystallized protein–protein complexes was used to re-dock the proteins by use of smoothed potentials. To detect the funnel, we developed a set of sophisticated models of random matches. The funnel was considered detected if the binding area was more populated by the low-energy docking predictions than by the matches generated in the random models. The number of funnels detected by use of different random models varied significantly. However, the results confirmed that the funnel may be the general feature in protein–protein association. PMID:11468354

  4. The TEAD4-YAP/TAZ protein-protein interaction: expected similarities and unexpected differences.

    Science.gov (United States)

    Hau, Jean Christophe; Erdmann, Dirk; Mesrouze, Yannick; Furet, Pascal; Fontana, Patrizia; Zimmermann, Catherine; Schmelzle, Tobias; Hofmann, Francesco; Chène, Patrick

    2013-07-08

    The Hippo pathway controls cell homeostasis, and its deregulation can lead to human diseases. In this pathway, the YAP and TAZ transcriptional cofactors play a key role in stimulating gene transcription through their interaction with the TEAD transcriptional factors. Our study of YAP and TAZ peptides in biochemical and biophysical assays shows that both proteins have essentially the same affinity for TEAD. Molecular modeling and structural biology data suggest that they also bind to the same site on TEAD. However, this apparent similarity hides differences in the ways in which the two proteins interact with TEAD. The secondary structure elements of their TEAD binding site do not contribute equally to the overall affinity, and critical interactions with TEAD are made through different residues. This convergent optimization of the YAP/TAZ TEAD binding site suggests that the similarity in the affinities of binding of YAP to TEAD and of TAZ to TEAD is important for Hippo pathway functionality. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Investigating CFTR and KCa3.1 Protein/Protein Interactions.

    Directory of Open Access Journals (Sweden)

    Hélène Klein

    Full Text Available In epithelia, Cl- channels play a prominent role in fluid and electrolyte transport. Of particular importance is the cAMP-dependent cystic fibrosis transmembrane conductance regulator Cl- channel (CFTR with mutations of the CFTR encoding gene causing cystic fibrosis. The bulk transepithelial transport of Cl- ions and electrolytes needs however to be coupled to an increase in K+ conductance in order to recycle K+ and maintain an electrical driving force for anion exit across the apical membrane. In several epithelia, this K+ efflux is ensured by K+ channels, including KCa3.1, which is expressed at both the apical and basolateral membranes. We show here for the first time that CFTR and KCa3.1 can physically interact. We first performed a two-hybrid screen to identify which KCa3.1 cytosolic domains might mediate an interaction with CFTR. Our results showed that both the N-terminal fragment M1-M40 of KCa3.1 and part of the KCa3.1 calmodulin binding domain (residues L345-A400 interact with the NBD2 segment (G1237-Y1420 and C- region of CFTR (residues T1387-L1480, respectively. An association of CFTR and F508del-CFTR with KCa3.1 was further confirmed in co-immunoprecipitation experiments demonstrating the formation of immunoprecipitable CFTR/KCa3.1 complexes in CFBE cells. Co-expression of KCa3.1 and CFTR in HEK cells did not impact CFTR expression at the cell surface, and KCa3.1 trafficking appeared independent of CFTR stimulation. Finally, evidence is presented through cross-correlation spectroscopy measurements that KCa3.1 and CFTR colocalize at the plasma membrane and that KCa3.1 channels tend to aggregate consequent to an enhanced interaction with CFTR channels at the plasma membrane following an increase in intracellular Ca2+ concentration. Altogether, these results suggest 1 that the physical interaction KCa3.1/CFTR can occur early during the biogenesis of both proteins and 2 that KCa3.1 and CFTR form a dynamic complex, the formation of which

  6. The Charm and Beauty of Strong Interactions

    Science.gov (United States)

    El-Bennich, Bruno

    2018-01-01

    We briefly review common features and overlapping issues in hadron and flavor physics focussing on continuum QCD approaches to heavy bound states, their mass spectrum and weak decay constants in different strong interaction models.

  7. 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

    employ stable isotopic amino acids in cell culture (SILAC) to differentially label proteins in EGF-stimulated versus unstimulated cells. Combined cell lysates were affinity-purified over the SH2 domain of the adapter protein Grb2 (GST-SH2 fusion protein) that specifically binds phosphorylated EGFR...... and Src homologous and collagen (Shc) protein. We identified 228 proteins, of which 28 were selectively enriched upon stimulation. EGFR and Shc, which interact directly with the bait, had large differential ratios. Many signaling molecules specifically formed complexes with the activated EGFR-Shc, as did...

  8. 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

    available, identifying the most-informative RT is becoming increasingly difficult. Previous studies on the selection of RT have provided guidelines for manual taxon selection, and for eliminating closely related taxa. However, no general strategy for automatic selection of RT is currently available. Results......: 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...

  9. 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...... in rhamnogalacturonan-I biosynthesis was proved and further supported by BiFC and non-reducing gel. Finally, association among four different NSTs (AtUTr5, AtUTr5B, At5g41760 and At4g35335) was shown as both homo- and heterodimeric complexes. In conclusion, our findings point to the notion that enzymes and transporters...

  10. Beyond Competitive Inhibition: Regulation of ABC Transporters by Kinases and Protein-Protein Interactions as Potential Mechanisms of Drug-Drug Interactions.

    Science.gov (United States)

    Crawford, Rebecca R; Potukuchi, Praveen K; Schuetz, Erin G; Schuetz, John D

    2018-03-07

    ATP-binding cassette (ABC) transporters are transmembrane efflux transporters mediating the extrusion of an array of substrates ranging from amino acids and lipids to xenobiotics, and many therapeutic compounds, including anticancer drugs. The ABC transporters are also recognized as important contributors to pharmacokinetics, especially in drug-drug interactions and adverse drug effects. Drugs and xenobiotics, as well as pathological conditions, can influence the transcription of ABC transporters, or modify their activity or intracellular localization. Kinases can affect the aforementioned processes for ABC transporters as do protein interactions. In this review, we focus on the ABC transporters ABCB1, ABCB11, ABCC1, ABCC4 and ABCG2 and illustrate how kinases and protein-protein interactions affect these transporters. The clinical relevance of these factors is currently unknown, however these examples suggest that our understanding of drug-drug interactions will benefit from further knowledge of how kinases and protein-protein interactions affect ABC transporters. The American Society for Pharmacology and Experimental Therapeutics.

  11. Unraveling protein-protein interactions in clathrin assemblies via atomic force spectroscopy.

    Science.gov (United States)

    Jin, Albert J; Lafer, Eileen M; Peng, Jennifer Q; Smith, Paul D; Nossal, Ralph

    2013-03-01

    Atomic force microscopy (AFM), single molecule force spectroscopy (SMFS), and single particle force spectroscopy (SPFS) are used to characterize intermolecular interactions and domain structures of clathrin triskelia and clathrin-coated vesicles (CCVs). The latter are involved in receptor-mediated endocytosis (RME) and other trafficking pathways. Here, we subject individual triskelia, bovine-brain CCVs, and reconstituted clathrin-AP180 coats to AFM-SMFS and AFM-SPFS pulling experiments and apply novel analytics to extract force-extension relations from very large data sets. The spectroscopic fingerprints of these samples differ markedly, providing important new information about the mechanism of CCV uncoating. For individual triskelia, SMFS reveals a series of events associated with heavy chain alpha-helix hairpin unfolding, as well as cooperative unraveling of several hairpin domains. SPFS of clathrin assemblies exposes weaker clathrin-clathrin interactions that are indicative of inter-leg association essential for RME and intracellular trafficking. Clathrin-AP180 coats are energetically easier to unravel than the coats of CCVs, with a non-trivial dependence on force-loading rate. Published by Elsevier Inc.

  12. Predicting human protein subcellular locations by the ensemble of multiple predictors via protein-protein interaction network with edge clustering coefficients.

    Directory of Open Access Journals (Sweden)

    Pufeng Du

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

  13. Exploring Strong Interactions in Proteins with Quantum Chemistry and Examples of Their Applications in Drug Design.

    Directory of Open Access Journals (Sweden)

    Neng-Zhong Xie

    Full Text Available Three strong interactions between amino acid side chains (salt bridge, cation-π, and amide bridge are studied that are stronger than (or comparable to the common hydrogen bond interactions, and play important roles in protein-protein interactions.Quantum chemical methods MP2 and CCSD(T are used in calculations of interaction energies and structural optimizations.The energies of three types of amino acid side chain interactions in gaseous phase and in aqueous solutions are calculated using high level quantum chemical methods and basis sets. Typical examples of amino acid salt bridge, cation-π, and amide bridge interactions are analyzed, including the inhibitor design targeting neuraminidase (NA enzyme of influenza A virus, and the ligand binding interactions in the HCV p7 ion channel. The inhibition mechanism of the M2 proton channel in the influenza A virus is analyzed based on strong amino acid interactions.(1 The salt bridge interactions between acidic amino acids (Glu- and Asp- and alkaline amino acids (Arg+, Lys+ and His+ are the strongest residue-residue interactions. However, this type of interaction may be weakened by solvation effects and broken by lower pH conditions. (2 The cation- interactions between protonated amino acids (Arg+, Lys+ and His+ and aromatic amino acids (Phe, Tyr, Trp and His are 2.5 to 5-fold stronger than common hydrogen bond interactions and are less affected by the solvation environment. (3 The amide bridge interactions between the two amide-containing amino acids (Asn and Gln are three times stronger than hydrogen bond interactions, which are less influenced by the pH of the solution. (4 Ten of the twenty natural amino acids are involved in salt bridge, or cation-, or amide bridge interactions that often play important roles in protein-protein, protein-peptide, protein-ligand, and protein-DNA interactions.

  14. 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 ...

  15. The surprising features of the TEAD4-Vgll1 protein-protein interaction.

    Science.gov (United States)

    Mesrouze, Yannick; Hau, Jean Christophe; Erdmann, Dirk; Zimmermann, Catherine; Fontana, Patrizia; Schmelzle, Tobias; Chène, Patrick

    2014-03-03

    The Hippo signaling pathway, which controls organ size in animals, is altered in various human cancers. The TEAD transcription factors, the most downstream elements in this pathway, are regulated by different cofactors, such as the Vgll (vestigial-like) proteins. Having studied the interaction between Vgll1-derived peptides and human TEAD4, we show that, although it lacks a key secondary structure element required for tight binding by two other TEAD cofactors (YAP and TAZ), Vgll1-derived peptides bind to TEAD with nanomolar affinity. We identify a β-strand:loop:α-helix motif as the minimal Vgll binding site. Finally, we reveal an unexpected difference between mouse and human Vgll1-derived peptides. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. 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. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Machine learning based identification of protein-protein interactions using derived features of physiochemical properties and evolutionary profiles.

    Science.gov (United States)

    Tahir, Muhammad; Hayat, Maqsood

    2017-05-01

    Proteins are the central constitute of a cell or biological system. Proteins execute their functions by interacting with other molecules such as RNA, DNA and other proteins. The major functionality of protein-protein interactions (PPIs) is the execution of biochemical activities in living species. Therefore, an accurate identification of PPIs becomes a challenging and demanding task for investigators from last few decades. Various traditional and computational methods have been applied but they have not achieved quite encouraging results. In order to extend the concept of computational model by incorporating intelligent, contemporary machine learning algorithms have been utilized for identification of PPIs. In this prediction model, protein sequences are expressed by using two distinct feature extraction methods namely: physiochemical properties of amino acids and evolutionary profiles method position specific scoring matrix (PSSM). Jackknife test and numerous performance parameters namely: specificity, recall, accuracy, MCC, precision, and F-measure were employed to compute the predictive quality of proposed model. After empirical analysis, it is determined that the proposed prediction model yielded encouraging predictive outcomes compared to existing state-of-the-art models. This achievement is ascribed with PSSM because it has clearly discerned a motif of PPIs. It is realized that the proposed prediction model will lead to be a practical and very useful tool for research community. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Hubs with network motifs organize modularity dynamically in the protein-protein interaction network of yeast.

    Science.gov (United States)

    Jin, Guangxu; Zhang, Shihua; Zhang, Xiang-Sun; Chen, Luonan

    2007-11-21

    It has been recognized that modular organization pervades biological complexity. Based on network analysis, 'party hubs' and 'date hubs' were proposed to understand the basic principle of module organization of biomolecular networks. However, recent study on hubs has suggested that there is no clear evidence for coexistence of 'party hubs' and 'date hubs'. Thus, an open question has been raised as to whether or not 'party hubs' and 'date hubs' truly exist in yeast interactome. In contrast to previous studies focusing on the partners of a hub or the individual proteins around the hub, our work aims to study the network motifs of a hub or interactions among individual proteins including the hub and its neighbors. Depending on the relationship between a hub's network motifs and protein complexes, we define two new types of hubs, 'motif party hubs' and 'motif date hubs', which have the same characteristics as the original 'party hubs' and 'date hubs' respectively. The network motifs of these two types of hubs display significantly different features in spatial distribution (or cellular localizations), co-expression in microarray data, controlling topological structure of network, and organizing modularity. By virtue of network motifs, we basically solved the open question about 'party hubs' and 'date hubs' which was raised by previous studies. Specifically, at the level of network motifs instead of individual proteins, we found two types of hubs, motif party hubs (mPHs) and motif date hubs (mDHs), whose network motifs display distinct characteristics on biological functions. In addition, in this paper we studied network motifs from a different viewpoint. That is, we show that a network motif should not be merely considered as an interaction pattern but be considered as an essential function unit in organizing modules of networks.

  19. Targeting 14-3-3 adaptor protein-protein interactions to stimulate central nervous system repair

    Directory of Open Access Journals (Sweden)

    Andrew Kaplan

    2017-01-01

    Full Text Available The goal of developing treatments for central nervous system (CNS injuries is becoming more attainable with the recent identification of various drugs that can repair damaged axons. These discoveries have stemmed from screening efforts, large expression datasets and an improved understanding of the cellular and molecular biology underlying axon growth. It will be important to continue searching for new compounds that can induce axon repair. Here we describe how a family of adaptor proteins called 14-3-3s can be targeted using small molecule drugs to enhance axon outgrowth and regeneration. 14-3-3s bind to many functionally diverse client proteins to regulate their functions. We highlight the recent discovery of the axon-growth promoting activity of fusicoccin-A, a fungus-derived small molecule that stabilizes 14-3-3 interactions with their client proteins. Here we discuss how fusicoccin-A could serve as a starting point for the development of drugs to induce CNS repair.

  20. Including virtual photons in strong interactions

    International Nuclear Information System (INIS)

    Rusetsky, A.

    2003-01-01

    In the perturbative field-theoretical models we investigate the inclusion of the electromagnetic interactions into the purely strong theory that describes hadronic processes. In particular, we study the convention for splitting electromagnetic and strong interactions and the ambiguity of such a splitting. The issue of the interpretation of the parameters of the low-energy effective field theory in the presence of electromagnetic interactions is addressed, as well as the scale and gauge dependence of the effective theory couplings. We hope, that the results of these studies are relevant for the electromagnetic sector of ChPT. (orig.)

  1. 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. © 2015 Federation of European Biochemical Societies.

  2. Targeting protein-protein interactions with trimeric ligands: high affinity inhibitors of the MAGUK protein family.

    Science.gov (United States)

    Nissen, Klaus B; Haugaard-Kedström, Linda M; Wilbek, Theis S; Nielsen, Line S; Åberg, Emma; Kristensen, Anders S; Bach, Anders; Jemth, Per; Strømgaard, Kristian

    2015-01-01

    PDZ domains in general, and those of PSD-95 in particular, are emerging as promising drug targets for diseases such as ischemic stroke. We have previously shown that dimeric ligands that simultaneously target PDZ1 and PDZ2 of PSD-95 are highly potent inhibitors of PSD-95. However, PSD-95 and the related MAGUK proteins contain three consecutive PDZ domains, hence we envisioned that targeting all three PDZ domains simultaneously would lead to more potent and potentially more specific interactions with the MAGUK proteins. Here we describe the design, synthesis and characterization of a series of trimeric ligands targeting all three PDZ domains of PSD-95 and the related MAGUK proteins, PSD-93, SAP-97 and SAP-102. Using our dimeric ligands targeting the PDZ1-2 tandem as starting point, we designed novel trimeric ligands by introducing a PDZ3-binding peptide moiety via a cysteine-derivatized NPEG linker. The trimeric ligands generally displayed increased affinities compared to the dimeric ligands in fluorescence polarization binding experiments and optimized trimeric ligands showed low nanomolar inhibition towards the four MAGUK proteins, thus being the most potent inhibitors described. Kinetic experiments using stopped-flow spectrometry showed that the increase in affinity is caused by a decrease in the dissociation rate of the trimeric ligand as compared to the dimeric ligands, likely reflecting the lower probability of simultaneous dissociation of all three PDZ ligands. Thus, we have provided novel inhibitors of the MAGUK proteins with exceptionally high affinity, which can be used to further elucidate the therapeutic potential of these proteins.

  3. Computationally-guided optimization of small-molecule inhibitors of the Aurora A kinase-TPX2 protein-protein interaction.

    Science.gov (United States)

    Cole, Daniel J; Janecek, Matej; Stokes, Jamie E; Rossmann, Maxim; Faver, John C; McKenzie, Grahame J; Venkitaraman, Ashok R; Hyvönen, Marko; Spring, David R; Huggins, David J; Jorgensen, William L

    2017-08-17

    Free energy perturbation theory, in combination with enhanced sampling of protein-ligand binding modes, is evaluated in the context of fragment-based drug design, and used to design two new small-molecule inhibitors of the Aurora A kinase-TPX2 protein-protein interaction.

  4. Genetically encoded releasable photo-cross-linking strategies for studying protein-protein interactions in living cells.

    Science.gov (United States)

    Yang, Yi; Song, Haiping; He, Dan; Zhang, Shuai; Dai, Shizhong; Xie, Xiao; Lin, Shixian; Hao, Ziyang; Zheng, Huangtao; Chen, Peng R

    2017-10-01

    Although protein-protein interactions (PPIs) have crucial roles in virtually all cellular processes, the identification of more transient interactions in their biological context remains challenging. Conventional photo-cross-linking strategies can be used to identify transient interactions, but these approaches often suffer from high background due to the cross-linked bait proteins. To solve the problem, we have developed membrane-permeable releasable photo-cross-linkers that allow for prey-bait separation after protein complex isolation and can be installed in proteins of interest (POIs) as unnatural amino acids. Here we describe the procedures for using two releasable photo-cross-linkers, DiZSeK and DiZHSeC, in both living Escherichia coli and mammalian cells. A cleavage after protein photo-cross-linking (CAPP ) strategy based on the photo-cross-linker DiZSeK is described, in which the prey protein pool is released from a POI after affinity purification. Prey proteins are analyzed using mass spectrometry or 2D gel electrophoresis for global comparison of interactomes from different experimental conditions. An in situ cleavage and mass spectrometry (MS)-label transfer after protein photo-cross-linking (IMAPP) strategy based on the photo-cross-linker DiZHSeC is also described. This strategy can be used for the identification of cross-linking sites to allow detailed characterization of PPI interfaces. The procedures for photo-cross-linker incorporation, photo-cross-linking of interaction partners and affinity purification of cross-linked complexes are similar for the two photo-cross-linkers. The final section of the protocol describes prey-bait separation (for CAPP) and MS-label transfer and identification (for IMAPP). After plasmid construction, the CAPP and IMAPP strategies can be completed within 6 and 7 d, respectively.

  5. Prioritizing disease candidate proteins in cardiomyopathy-specific protein-protein interaction networks based on "guilt by association" analysis.

    Directory of Open Access Journals (Sweden)

    Wan Li

    Full Text Available The cardiomyopathies are a group of heart muscle diseases which can be inherited (familial. Identifying potential disease-related proteins is important to understand mechanisms of cardiomyopathies. Experimental identification of cardiomyophthies is costly and labour-intensive. In contrast, bioinformatics approach has a competitive advantage over experimental method. Based on "guilt by association" analysis, we prioritized candidate proteins involving in human cardiomyopathies. We first built weighted human cardiomyopathy-specific protein-protein interaction networks for three subtypes of cardiomyopathies using the known disease proteins from Online Mendelian Inheritance in Man as seeds. We then developed a method in prioritizing disease candidate proteins to rank candidate proteins in the network based on "guilt by association" analysis. It was found that most candidate proteins with high scores shared disease-related pathways with disease seed proteins. These top ranked candidate proteins were related with the corresponding disease subtypes, and were potential disease-related proteins. Cross-validation and comparison with other methods indicated that our approach could be used for the identification of potentially novel disease proteins, which may provide insights into cardiomyopathy-related mechanisms in a more comprehensive and integrated way.

  6. Analysis of Protein Phosphorylation and Its Functional Impact on Protein-Protein Interactions via Text Mining of the Scientific Literature.

    Science.gov (United States)

    Wang, Qinghua; Ross, Karen E; Huang, Hongzhan; Ren, Jia; Li, Gang; Vijay-Shanker, K; Wu, Cathy H; Arighi, Cecilia N

    2017-01-01

    Post-translational modifications (PTMs) are one of the main contributors to the diversity of proteoforms in the proteomic landscape. In particular, protein phosphorylation represents an essential regulatory mechanism that plays a role in many biological processes. Protein kinases, the enzymes catalyzing this reaction, are key participants in metabolic and signaling pathways. Their activation or inactivation dictate downstream events: what substrates are modified and their subsequent impact (e.g., activation state, localization, protein-protein interactions (PPIs)). The biomedical literature continues to be the main source of evidence for experimental information about protein phosphorylation. Automatic methods to bring together phosphorylation events and phosphorylation-dependent PPIs can help to summarize the current knowledge and to expose hidden connections. In this chapter, we demonstrate two text mining tools, RLIMS-P and eFIP, for the retrieval and extraction of kinase-substrate-site data and phosphorylation-dependent PPIs from the literature. These tools offer several advantages over a literature search in PubMed as their results are specific for phosphorylation. RLIMS-P and eFIP results can be sorted, organized, and viewed in multiple ways to answer relevant biological questions, and the protein mentions are linked to UniProt identifiers.

  7. Characterizing genes with distinct methylation patterns in the context of protein-protein interaction network: application to human brain tissues.

    Science.gov (United States)

    Li, Yongsheng; Xu, Juan; Chen, Hong; Zhao, Zheng; Li, Shengli; Bai, Jing; Wu, Aiwei; Jiang, Chunjie; Wang, Yuan; Su, Bin; Li, Xia

    2013-01-01

    DNA methylation is an essential epigenetic mechanism involved in transcriptional control. However, how genes with different methylation patterns are assembled in the protein-protein interaction network (PPIN) remains a mystery. In the present study, we systematically dissected the characterization of genes with different methylation patterns in the PPIN. A negative association was detected between the methylation levels in the brain tissues and topological centralities. By focusing on two classes of genes with considerably different methylation levels in the brain tissues, namely the low methylated genes (LMGs) and high methylated genes (HMGs), we found that their organizing principles in the PPIN are distinct. The LMGs tend to be the center of the PPIN, and attacking them causes a more deleterious effect on the network integrity. Furthermore, the LMGs express their functions in a modular pattern and substantial differences in functions are observed between the two types of genes. The LMGs are enriched in the basic biological functions, such as binding activity and regulation of transcription. More importantly, cancer genes, especially recessive cancer genes, essential genes, and aging-related genes were all found more often in the LMGs. Additionally, our analysis presented that the intra-classes communications are enhanced, but inter-classes communications are repressed. Finally, a functional complementation was revealed between methylation and miRNA regulation in the human genome. We have elucidated the assembling principles of genes with different methylation levels in the context of the PPIN, providing key insights into the complex epigenetic regulation mechanisms.

  8. A review of in silico approaches for analysis and prediction of HIV-1-human protein-protein interactions.

    Science.gov (United States)

    Bandyopadhyay, Sanghamitra; Ray, Sumanta; Mukhopadhyay, Anirban; Maulik, Ujjwal

    2015-09-01

    The computational or in silico approaches for analysing the HIV-1-human protein-protein interaction (PPI) network, predicting different host cellular factors and PPIs and discovering several pathways are gaining popularity in the field of HIV research. Although there exist quite a few studies in this regard, no previous effort has been made to review these works in a comprehensive manner. Here we review the computational approaches that are devoted to the analysis and prediction of HIV-1-human PPIs. We have broadly categorized these studies into two fields: computational analysis of HIV-1-human PPI network and prediction of novel PPIs. We have also presented a comparative assessment of these studies and proposed some methodologies for discussing the implication of their results. We have also reviewed different computational techniques for predicting HIV-1-human PPIs and provided a comparative study of their applicability. We believe that our effort will provide helpful insights to the HIV research community. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  9. Nanobody Technology: A Versatile Toolkit for Microscopic Imaging, Protein-Protein Interaction Analysis, and Protein Function Exploration.

    Science.gov (United States)

    Beghein, Els; Gettemans, Jan

    2017-01-01

    Over the last two decades, nanobodies or single-domain antibodies have found their way in research, diagnostics, and therapy. These antigen-binding fragments, derived from Camelid heavy chain only antibodies, possess remarkable characteristics that favor their use over conventional antibodies or fragments thereof, in selected areas of research. In this review, we assess the current status of nanobodies as research tools in diverse aspects of fundamental research. We discuss the use of nanobodies as detection reagents in fluorescence microscopy and focus on recent advances in super-resolution microscopy. Second, application of nanobody technology in investigating protein-protein interactions is reviewed, with emphasis on possible uses in mass spectrometry. Finally, we discuss the potential value of nanobodies in studying protein function, and we focus on their recently reported application in targeted protein degradation. Throughout the review, we highlight state-of-the-art engineering strategies that could expand nanobody versatility and we suggest future applications of the technology in the selected areas of fundamental research.

  10. CHIPMUNK: A Virtual Synthesizable Small-Molecule Library for Medicinal Chemistry, Exploitable for Protein-Protein Interaction Modulators.

    Science.gov (United States)

    Humbeck, Lina; Weigang, Sebastian; Schäfer, Till; Mutzel, Petra; Koch, Oliver

    2018-03-20

    A common issue during drug design and development is the discovery of novel scaffolds for protein targets. On the one hand the chemical space of purchasable compounds is rather limited; on the other hand artificially generated molecules suffer from a grave lack of accessibility in practice. Therefore, we generated a novel virtual library of small molecules which are synthesizable from purchasable educts, called CHIPMUNK (CHemically feasible In silico Public Molecular UNiverse Knowledge base). Altogether, CHIPMUNK covers over 95 million compounds and encompasses regions of the chemical space that are not covered by existing databases. The coverage of CHIPMUNK exceeds the chemical space spanned by the Lipinski rule of five to foster the exploration of novel and difficult target classes. The analysis of the generated property space reveals that CHIPMUNK is well suited for the design of protein-protein interaction inhibitors (PPIIs). Furthermore, a recently developed structural clustering algorithm (StruClus) for big data was used to partition the sub-libraries into meaningful subsets and assist scientists to process the large amount of data. These clustered subsets also contain the target space based on ChEMBL data which was included during clustering. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. The Prediction of Key Cytoskeleton Components Involved in Glomerular Diseases Based on a Protein-Protein Interaction Network

    Science.gov (United States)

    Ju, Wenjun; Li, Xuejuan; Li, Shao; Ding, Jie

    2016-01-01

    Maintenance of the physiological morphologies of different types of cells and tissues is essential for the normal functioning of each system in the human body. Dynamic variations in cell and tissue morphologies depend on accurate adjustments of the cytoskeletal system. The cytoskeletal system in the glomerulus plays a key role in the normal process of kidney filtration. To enhance the understanding of the possible roles of the cytoskeleton in glomerular diseases, we constructed the Glomerular Cytoskeleton Network (GCNet), which shows the protein-protein interaction network in the glomerulus, and identified several possible key cytoskeletal components involved in glomerular diseases. In this study, genes/proteins annotated to the cytoskeleton were detected by Gene Ontology analysis, and glomerulus-enriched genes were selected from nine available glomerular expression datasets. Then, the GCNet was generated by combining these two sets of information. To predict the possible key cytoskeleton components in glomerular diseases, we then examined the common regulation of the genes in GCNet in the context of five glomerular diseases based on their transcriptomic data. As a result, twenty-one cytoskeleton components as potential candidate were highlighted for consistently down- or up-regulating in all five glomerular diseases. And then, these candidates were examined in relation to existing known glomerular diseases and genes to determine their possible functions and interactions. In addition, the mRNA levels of these candidates were also validated in a puromycin aminonucleoside(PAN) induced rat nephropathy model and were also matched with existing Diabetic Nephropathy (DN) transcriptomic data. As a result, there are 15 of 21 candidates in PAN induced nephropathy model were consistent with our predication and also 12 of 21 candidates were matched with differentially expressed genes in the DN transcriptomic data. By providing a novel interaction network and prediction, GCNet

  12. The Prediction of Key Cytoskeleton Components Involved in Glomerular Diseases Based on a Protein-Protein Interaction Network.

    Science.gov (United States)

    Ding, Fangrui; Tan, Aidi; Ju, Wenjun; Li, Xuejuan; Li, Shao; Ding, Jie

    2016-01-01

    Maintenance of the physiological morphologies of different types of cells and tissues is essential for the normal functioning of each system in the human body. Dynamic variations in cell and tissue morphologies depend on accurate adjustments of the cytoskeletal system. The cytoskeletal system in the glomerulus plays a key role in the normal process of kidney filtration. To enhance the understanding of the possible roles of the cytoskeleton in glomerular diseases, we constructed the Glomerular Cytoskeleton Network (GCNet), which shows the protein-protein interaction network in the glomerulus, and identified several possible key cytoskeletal components involved in glomerular diseases. In this study, genes/proteins annotated to the cytoskeleton were detected by Gene Ontology analysis, and glomerulus-enriched genes were selected from nine available glomerular expression datasets. Then, the GCNet was generated by combining these two sets of information. To predict the possible key cytoskeleton components in glomerular diseases, we then examined the common regulation of the genes in GCNet in the context of five glomerular diseases based on their transcriptomic data. As a result, twenty-one cytoskeleton components as potential candidate were highlighted for consistently down- or up-regulating in all five glomerular diseases. And then, these candidates were examined in relation to existing known glomerular diseases and genes to determine their possible functions and interactions. In addition, the mRNA levels of these candidates were also validated in a puromycin aminonucleoside(PAN) induced rat nephropathy model and were also matched with existing Diabetic Nephropathy (DN) transcriptomic data. As a result, there are 15 of 21 candidates in PAN induced nephropathy model were consistent with our predication and also 12 of 21 candidates were matched with differentially expressed genes in the DN transcriptomic data. By providing a novel interaction network and prediction, GCNet

  13. A theory of the strong interactions

    International Nuclear Information System (INIS)

    Gross, D.J.

    1979-01-01

    The most promising candidate for a fundamental microscopic theory of the strong interactions is a gauge theory of colored quarks-Quantum Chromodynamics (QCD). There are many excellent reasons for believing in this theory. It embodies the broken symmetries, SU(3) and chiral SU(3)xSU(3), of the strong interactions and reflects the success of (albeit crude) quark models in explaining the spectrum of the observed hadrons. The hidden quantum number of color, necessary to account for the quantum numbers of the low lying hadrons, plays a fundamental role in this theory as the SU(3) color gauge vector 'gluons' are the mediators of the strong interactions. The absence of physical quark states can be 'explained' by the hypothesis of color confinement i.e. that hadrons are permanently bound in color singlet bound states. Finally this theory is unique in being asymptotically free, thus accounting for the almost free field theory behvior of quarks observed at short distances. (Auth.)

  14. 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

  15. Electroweak and Strong Interactions Phenomenology, Concepts, Models

    CERN Document Server

    Scheck, Florian

    2012-01-01

    Electroweak and Strong Interaction: Phenomenology, Concepts, Models, begins with relativistic quantum mechanics and some quantum field theory which lay the foundation for the rest of the text. The phenomenology and the physics of the fundamental interactions are emphasized through a detailed discussion of the empirical fundamentals of unified theories of strong, electromagnetic, and weak interactions. The principles of local gauge theories are described both in a heuristic and a geometric framework. The minimal standard model of the fundamental interactions is developed in detail and characteristic applications are worked out. Possible signals of physics beyond that model, notably in the physics of neutrinos are also discussed. Among the applications scattering on nucleons and on nuclei provide salient examples. Numerous exercises with solutions make the text suitable for advanced courses or individual study. This completely updated revised new edition contains an enlarged chapter on quantum chromodynamics an...

  16. Localization of protein-protein interactions among three fluorescent proteins in a single living cell: three-color FRET microscopy

    Science.gov (United States)

    Sun, Yuansheng; Booker, Cynthia F.; Day, Richard N.; Periasamy, Ammasi

    2009-02-01

    Förster resonance energy transfer (FRET) methodology has been used for over 30 years to localize protein-protein interactions in living specimens. The cloning and modification of various visible fluorescent proteins (FPs) has generated a variety of new probes that can be used as FRET pairs to investigate the protein associations in living cells. However, the spectral cross-talk between FRET donor and acceptor channels has been a major limitation to FRET microscopy. Many investigators have developed different ways to eliminate the bleedthrough signals in the FRET channel for one donor and one acceptor. We developed a novel FRET microscopy method for studying interactions among three chromophores: three-color FRET microscopy. We generated a genetic construct that directly links the three FPs - monomeric teal FP (mTFP), Venus and tandem dimer Tomato (tdTomato), and demonstrated the occurrence of mutually dependent energy transfers among the three FPs. When expressed in cells and excited with the 458 nm laser line, the mTFP-Venus-tdTomato fusion proteins yielded parallel (mTFP to Venus and mTFP to tdTomato) and sequential (mTFP to Venus and then to tdTomato) energy transfer signals. To quantify the FRET signals in the three-FP system in a single living cell, we developed an algorithm to remove all the spectral cross-talk components and also to separate different FRET signals at a same emission channel using the laser scanning spectral imaging and linear unmixing techniques on the Zeiss510 META system. Our results were confirmed with fluorescence lifetime measurements and using acceptor photobleaching FRET microscopy.

  17. Analyzing the pathways enriched in genes associated with nicotine dependence in the context of human protein-protein interaction network.

    Science.gov (United States)

    Hu, Ying; Fang, Zhonghai; Yang, Yichen; Fan, Ting; Wang, Ju

    2018-03-16

    Nicotine dependence is the primary addictive stage of cigarette smoking. Although a lot of studies have been performed to explore the molecular mechanism underlying nicotine dependence, our understanding on this disorder is still far from complete. Over the past decades, an increasing number of candidate genes involved in nicotine dependence have been identified by different technical approaches, including the genetic association analysis. In this study, we performed a comprehensive collection of candidate genes reported to be genetically associated with nicotine dependence. Then, the biochemical pathways enriched in these genes were identified by considering the gene's propensity to be related to nicotine dependence. One of the most widely used pathway enrichment analysis approach, over-representation analysis, ignores the function non-equivalence of genes in candidate gene set and may have low discriminative power in identifying some dysfunctional pathways. To overcome such drawbacks, we constructed a comprehensive human protein-protein interaction network, and then assigned a function weighting score to each candidate gene based on their network topological features. Evaluation indicated the function weighting score scheme was consistent with available evidence. Finally, the function weighting scores of the candidate genes were incorporated into pathway analysis to identify the dysfunctional pathways involved in nicotine dependence, and the interactions between pathways was detected by pathway crosstalk analysis. Compared to conventional over-representation based pathway analysis tool, the modified method exhibited improved discriminative power and detected some novel pathways potentially underlying nicotine dependence. In summary, we conducted a comprehensive collection of genes associated with nicotine dependence and then detected the biochemical pathways enriched in these genes using a modified pathway enrichment analysis approach with function weighting

  18. Target identification in Fusobacterium nucleatum by subtractive genomics approach and enrichment analysis of host-pathogen protein-protein interactions.

    Science.gov (United States)

    Kumar, Amit; Thotakura, Pragna Lakshmi; Tiwary, Basant Kumar; Krishna, Ramadas

    2016-05-12

    Fusobacterium nucleatum, a well studied bacterium in periodontal diseases, appendicitis, gingivitis, osteomyelitis and pregnancy complications has recently gained attention due to its association with colorectal cancer (CRC) progression. Treatment with berberine was shown to reverse F. nucleatum-induced CRC progression in mice by balancing the growth of opportunistic pathogens in tumor microenvironment. Intestinal microbiota imbalance and the infections caused by F. nucleatum might be regulated by therapeutic intervention. Hence, we aimed to predict drug target proteins in F. nucleatum, through subtractive genomics approach and host-pathogen protein-protein interactions (HP-PPIs). We also carried out enrichment analysis of host interacting partners to hypothesize the possible mechanisms involved in CRC progression due to F. nucleatum. In subtractive genomics approach, the essential, virulence and resistance related proteins were retrieved from RefSeq proteome of F. nucleatum by searching against Database of Essential Genes (DEG), Virulence Factor Database (VFDB) and Antibiotic Resistance Gene-ANNOTation (ARG-ANNOT) tool respectively. A subsequent hierarchical screening to identify non-human homologous, metabolic pathway-independent/pathway-specific and druggable proteins resulted in eight pathway-independent and 27 pathway-specific druggable targets. Co-aggregation of F. nucleatum with host induces proinflammatory gene expression thereby potentiates tumorigenesis. Hence, proteins from IBDsite, a database for inflammatory bowel disease (IBD) research and those involved in colorectal adenocarcinoma as interpreted from The Cancer Genome Atlas (TCGA) were retrieved to predict drug targets based on HP-PPIs with F. nucleatum proteome. Prediction of HP-PPIs exhibited 186 interactions contributed by 103 host and 76 bacterial proteins. Bacterial interacting partners were accounted as putative targets. And enrichment analysis of host interacting partners showed statistically

  19. Vector mesons in strongly interacting matter

    Indian Academy of Sciences (India)

    probes like photons, pions or protons or the heated and compressed hadronic matter generated in a heavy-ion collision. Leaving any nuclear medium without strong final-state interactions, dileptons are the optimum decay channel as they avoid any final-state distortion of the 4- momenta of the decay products entering eq.

  20. Vector mesons in strongly interacting matter

    Indian Academy of Sciences (India)

    Properties of hadrons in strongly interacting matter provide a link between quantum chromodynamics in the ... Top: Spectral function of the ρ-meson at normal nuclear matter density as a function of mass and ... directly but folded with the branching ratio ΓV →p1+p2 /Γtot into the specific final channel one is investigating.

  1. Structure-based drug design, synthesis and biological assays of P. falciparum Atg3-Atg8 protein-protein interaction inhibitors

    Science.gov (United States)

    Villa, Stefania; Legnani, Laura; Colombo, Diego; Gelain, Arianna; Lammi, Carmen; Bongiorno, Daniele; Ilboudo, Denise P.; McGee, Kellen E.; Bosch, Jürgen; Grazioso, Giovanni

    2018-01-01

    The proteins involved in the autophagy (Atg) pathway have recently been considered promising targets for the development of new antimalarial drugs. In particular, inhibitors of the protein-protein interaction (PPI) between Atg3 and Atg8 of Plasmodium falciparum retarded the blood- and liver-stages of parasite growth. In this paper, we used computational techniques to design a new class of peptidomimetics mimicking the Atg3 interaction motif, which were then synthesized by click-chemistry. Surface plasmon resonance has been employed to measure the ability of these compounds to inhibit the Atg3-Atg8 reciprocal protein-protein interaction. Moreover, P. falciparum growth inhibition in red blood cell cultures was evaluated as well as the cyto-toxicity of the compounds.

  2. Structure-based drug design, synthesis and biological assays of P. falciparum Atg3-Atg8 protein-protein interaction inhibitors

    Science.gov (United States)

    Villa, Stefania; Legnani, Laura; Colombo, Diego; Gelain, Arianna; Lammi, Carmen; Bongiorno, Daniele; Ilboudo, Denise P.; McGee, Kellen E.; Bosch, Jürgen; Grazioso, Giovanni

    2018-03-01

    The proteins involved in the autophagy (Atg) pathway have recently been considered promising targets for the development of new antimalarial drugs. In particular, inhibitors of the protein-protein interaction (PPI) between Atg3 and Atg8 of Plasmodium falciparum retarded the blood- and liver-stages of parasite growth. In this paper, we used computational techniques to design a new class of peptidomimetics mimicking the Atg3 interaction motif, which were then synthesized by click-chemistry. Surface plasmon resonance has been employed to measure the ability of these compounds to inhibit the Atg3-Atg8 reciprocal protein-protein interaction. Moreover, P. falciparum growth inhibition in red blood cell cultures was evaluated as well as the cyto-toxicity of the compounds.

  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. © The Author(s) 2016. Published by Oxford University Press.

  4. MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform.

    Science.gov (United States)

    Gupta, Surya; De Puysseleyr, Veronic; Van der Heyden, José; Maddelein, Davy; Lemmens, Irma; Lievens, Sam; Degroeve, Sven; Tavernier, Jan; Martens, Lennart

    2017-05-01

    Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments. MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT. jan.tavernier@vib-ugent.be or lennart.martens@vib-ugent.be. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

  5. Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis.

    Science.gov (United States)

    Holland, David O; Johnson, Margaret E

    2018-03-01

    Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that 'leftover' proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module

  6. Strong interaction studies with kaonic atoms

    Directory of Open Access Journals (Sweden)

    Marton J.

    2016-01-01

    Full Text Available The strong interaction of antikaons (K− with nucleons and nuclei in the low-energy regime represents an active research field connected intrinsically with few-body physics. There are important open questions like the question of antikaon nuclear bound states - the prototype system being K−pp. A unique and rather direct experimental access to the antikaon-nucleon scattering lengths is provided by precision X-ray spectroscopy of transitions in low-lying states of light kaonic atoms like kaonic hydrogen isotopes. In the SIDDHARTA experiment at the electron-positron collider DAΦNE of LNF-INFN we measured the most precise values of the strong interaction observables, i.e. the strong interaction on the 1s ground state of the electromagnetically bound K−p atom leading to a hadronic shift ϵ1s and a hadronic broadening Γ1s of the 1s state. The SIDDHARTA result triggered new theoretical work which achieved major progress in the understanding of the low-energy strong interaction with strangeness. Antikaon-nucleon scattering lengths have been calculated constrained by the SIDDHARTA data on kaonic hydrogen. For the extraction of the isospin-dependent scattering lengths a measurement of the hadronic shift and width of kaonic deuterium is necessary. Therefore, new X-ray studies with the focus on kaonic deuterium are in preparation (SIDDHARTA2. Many improvements in the experimental setup will allow to measure kaonic deuterium which is challenging due to the anticipated low X-ray yield. Especially important are the data on the X-ray yields of kaonic deuterium extracted from a exploratory experiment within SIDDHARTA.

  7. 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.

  8. Mimicking protein-protein interactions through peptide-peptide interactions: HIV-1 gp120 and CXCR4

    Directory of Open Access Journals (Sweden)

    Andrea eGross

    2013-09-01

    Full Text Available We have recently designed a soluble synthetic peptide that functionally mimics the HIV-1 coreceptor CXCR4, which is a chemokine receptor that belongs to the family of seven-transmembrane GPCRs. This CXCR4 mimetic peptide, termed CX4-M1, presents the three extracellular loops (ECLs of the receptor. In binding assays involving recombinant proteins, as well as in cellular infection assays, CX4-M1 was found to selectively recognize gp120 from HIV-1 strains that use CXCR4 for cell entry (X4 tropic HIV-1. Furthermore, anti-HIV-1 antibodies modulate this interaction in a molecular mechanism related to that of their impact on the gp120-CXCR4 interaction. We could now show that the selectivity of CX4-M1 pertains not only to gp120 from X4 tropic HIV-1, but also to synthetic peptides presenting the V3 loops of these gp120 proteins. The V3 loop is thought to be an essential part of the coreceptor binding site of gp120 that contacts the second ECL of the coreceptor. We were able to experimentally confirm this notion in binding assays using substitution analogs of CX4-M1 and the V3 loop peptides, respectively, as well as in cellular infection assays. These results indicate that interactions of the HIV-1 Env with coreceptors can be mimicked by synthetic peptides, which may be useful to explore these interactions at the molecular level in more detail.

  9. Protein-protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM.

    Science.gov (United States)

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

    2015-10-01

    Protein-protein interaction (PPI) site prediction aids to ascertain the interface residues that participate in interaction processes. Fuzzy support vector machine (F-SVM) is proposed as an effective method to solve this problem, and we have shown that the performance of the classical SVM can be enhanced with the help of an interaction-affinity based fuzzy membership function. The performances of both SVM and F-SVM on the PPI databases of the Homo sapiens and E. coli organisms are evaluated and estimated the statistical significance of the developed method over classical SVM and other fuzzy membership-based SVM methods available in the literature. Our membership function uses the residue-level interaction affinity scores for each pair of positive and negative sequence fragments. The average AUC scores in the 10-fold cross-validation experiments are measured as 79.94% and 80.48% for the Homo sapiens and E. coli organisms respectively. On the independent test datasets, AUC scores are obtained as 76.59% and 80.17% respectively for the two organisms. In almost all cases, the developed F-SVM method improves the performances obtained by the corresponding classical SVM and the other classifiers, available in the literature.

  10. Fundamental Structure of Matter and Strong Interaction

    Energy Technology Data Exchange (ETDEWEB)

    Jian-Ping Chen

    2011-11-01

    More than 99% of the visible matter in the universe are the protons and neutrons. Their internal structure is mostly governed by the strong interaction. Understanding their internal structure in terms of fundamental degrees-of-freedom is one of the most important subjects in modern physics. Worldwide efforts in the last few decades have lead to numerous surprises and discoveries, but major challenges still remain. An overview of the progress will be presented with a focus on the recent studies of the proton and neutron's electromagnetic and spin structure. Future perspectives will be discussed.

  11. Strong Interaction Studies with PANDA at FAIR

    International Nuclear Information System (INIS)

    Schönning, Karin

    2016-01-01

    The Facility for Antiproton and Ion Research (FAIR) in Darmstadt, Germany, provides unique possibilities for a new generation of nuclear-, hadron- and atomic physics experiments. The future PANDA experiment at FAIR will offer a broad physics programme with emphasis on different aspects of hadron physics. Understanding the strong interaction in the perturbative regime remains one of the greatest challenges in contemporary physics and hadrons provide several important keys. In these proceedings, PANDA will be presented along with some high-lights of the planned physics programme

  12. Strong Interactions Physics at BaBar

    Energy Technology Data Exchange (ETDEWEB)

    Pioppi, M.

    2005-03-14

    Recent results obtained by BABAR experiment and related to strong interactions physics are presented, with particular attention to the extraction of the first four hadronic-mass moments and the first three lepton-energy moments in semileptonic decays. From a simultaneous fit to the moments, the CKM element |V{sub cb}|, the inclusive B {yields} X{sub c}lv and other heavy quark parameters are derived. The second topic is the ambiguity-free measurement of cos(2{beta}) in B {yields} J/{Psi}K* decays. With approximately 88 million of B{bar B} pairs, negative solutions for cos(2{beta}) are excluded at 89%.

  13. Strong Interaction Studies with PANDA at FAIR

    Science.gov (United States)

    Schönning, Karin

    2016-10-01

    The Facility for Antiproton and Ion Research (FAIR) in Darmstadt, Germany, provides unique possibilities for a new generation of nuclear-, hadron- and atomic physics experiments. The future PANDA experiment at FAIR will offer a broad physics programme with emphasis on different aspects of hadron physics. Understanding the strong interaction in the perturbative regime remains one of the greatest challenges in contemporary physics and hadrons provide several important keys. In these proceedings, PANDA will be presented along with some high-lights of the planned physics programme.

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

    Science.gov (United States)

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

    2015-12-01

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

  15. Strong Interactive Massive Particles from a Strong Coupled Theory

    DEFF Research Database (Denmark)

    Yu. Khlopov, Maxim; Kouvaris, Christoforos

    2008-01-01

    (-2). These excessive techniparticles are all captured by $^4He$, creating \\emph{techni-O-helium} $tOHe$ ``atoms'', as soon as $^4He$ is formed in Big Bang Nucleosynthesis. The interaction of techni-O-helium with nuclei opens new paths to the creation of heavy nuclei in Big Bang Nucleosynthesis. Due...

  16. Finite temperature system of strongly interacting baryons

    Energy Technology Data Exchange (ETDEWEB)

    Bowers, R.L.; Gleeson, A.M.; Pedigo, R.D.; Wheeler, J.W.

    1976-07-01

    A fully relativistic finite temperature many body theory is constructed and used to examine the bulk properties of a system of strongly interacting baryons. The strong interactions are described by a two parameter phenomenological model fit to a simple description of nuclear matter at T = 0. The zero temperature equation of state for such a system which has already been discussed in the literature was developed to give a realistic description of nuclear matter. The model presented here is the exact finite temperature extension of that model. The effect of the inclusion of baryon pairs for T greater than or equal to 2mc/sup 2//k is discussed in detail. The phase transition identified with nuclear matter vanishes for system temperatures in excess of T/sub C/ = 1.034 x 10/sup 11/ /sup 0/K. All values of epsilon (P,T) correspond to systems that are causal in the sense that the locally determined speed of sound never exceeds the speed of light.

  17. Finite temperature system of strongly interacting baryons

    International Nuclear Information System (INIS)

    Bowers, R.L.; Gleeson, A.M.; Pedigo, R.D.; Wheeler, J.W.

    1976-07-01

    A fully relativistic finite temperature many body theory is constructed and used to examine the bulk properties of a system of strongly interacting baryons. The strong interactions are described by a two parameter phenomenological model fit to a simple description of nuclear matter at T = 0. The zero temperature equation of state for such a system which has already been discussed in the literature was developed to give a realistic description of nuclear matter. The model presented here is the exact finite temperature extension of that model. The effect of the inclusion of baryon pairs for T greater than or equal to 2mc 2 /k is discussed in detail. The phase transition identified with nuclear matter vanishes for system temperatures in excess of T/sub C/ = 1.034 x 10 11 0 K. All values of epsilon (P,T) correspond to systems that are causal in the sense that the locally determined speed of sound never exceeds the speed of light

  18. NMR identification of the binding surfaces involved in the Salmonella and Shigella Type III secretion tip-translocon protein-protein interactions.

    Science.gov (United States)

    McShan, Andrew C; Kaur, Kawaljit; Chatterjee, Srirupa; Knight, Kevin M; De Guzman, Roberto N

    2016-08-01

    The type III secretion system (T3SS) is essential for the pathogenesis of many bacteria including Salmonella and Shigella, which together are responsible for millions of deaths worldwide each year. The structural component of the T3SS consists of the needle apparatus, which is assembled in part by the protein-protein interaction between the tip and the translocon. The atomic detail of the interaction between the tip and the translocon proteins is currently unknown. Here, we used NMR methods to identify that the N-terminal domain of the Salmonella SipB translocon protein interacts with the SipD tip protein at a surface at the distal region of the tip formed by the mixed α/β domain and a portion of its coiled-coil domain. Likewise, the Shigella IpaB translocon protein and the IpaD tip protein interact with each other using similar surfaces identified for the Salmonella homologs. Furthermore, removal of the extreme N-terminal residues of the translocon protein, previously thought to be important for the interaction, had little change on the binding surface. Finally, mutations at the binding surface of SipD reduced invasion of Salmonella into human intestinal epithelial cells. Together, these results reveal the binding surfaces involved in the tip-translocon protein-protein interaction and advance our understanding of the assembly of the T3SS needle apparatus. Proteins 2016; 84:1097-1107. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  19. Convex Modeling of Interactions with Strong Heredity.

    Science.gov (United States)

    Haris, Asad; Witten, Daniela; Simon, Noah

    2016-01-01

    We consider the task of fitting a regression model involving interactions among a potentially large set of covariates, in which we wish to enforce strong heredity. We propose FAMILY, a very general framework for this task. Our proposal is a generalization of several existing methods, such as VANISH [Radchenko and James, 2010], hierNet [Bien et al., 2013], the all-pairs lasso, and the lasso using only main effects. It can be formulated as the solution to a convex optimization problem, which we solve using an efficient alternating directions method of multipliers (ADMM) algorithm. This algorithm has guaranteed convergence to the global optimum, can be easily specialized to any convex penalty function of interest, and allows for a straightforward extension to the setting of generalized linear models. We derive an unbiased estimator of the degrees of freedom of FAMILY, and explore its performance in a simulation study and on an HIV sequence data set.

  20. Strongly Interacting Matter at High Energy Density

    International Nuclear Information System (INIS)

    McLerran, L.

    2008-01-01

    This lecture concerns the properties of strongly interacting matter (which is described by Quantum Chromodynamics) at very high energy density. I review the properties of matter at high temperature, discussing the deconfinement phase transition. At high baryon density and low temperature, large N c arguments are developed which suggest that high baryonic density matter is a third form of matter, Quarkyonic Matter, that is distinct from confined hadronic matter and deconfined matter. I finally discuss the Color Glass Condensate which controls the high energy limit of QCD, and forms the low x part of a hadron wavefunction. The Glasma is introduced as matter formed by the Color Glass Condensate which eventually thermalizes into a Quark Gluon Plasma

  1. An alternative easy method for antibody purification and analysis of protein-protein interaction using GST fusion proteins immobilized onto glutathione-agarose.

    Science.gov (United States)

    Zalazar, L; Alonso, C A I; De Castro, R E; Cesari, A

    2014-01-01

    Immobilization of small proteins designed to perform protein-protein assays can be a difficult task. Often, the modification of reactive residues necessary for the interaction between the immobilized protein and the matrix compromises the interaction between the protein and its target. In these cases, glutathione-S-transferase (GST) is a valuable tag providing a long arm that makes the bait protein accessible to the mobile flow phase of the chromatography. In the present report, we used a GST fusion version of the 8-kDa protein serine protease inhibitor Kazal-type 3 (SPINK3) as the bait to purify anti-SPINK3 antibodies from a rabbit crude serum. The protocol for immobilization of GST-SPINK3 to glutathione-agarose beads was modified from previously reported protocols by using an alternative bifunctional cross-linker (dithiobis(succinimidyl propionate)) in a very simple procedure and by using simple buffers under physiological conditions. We concluded that the immobilized protein remained bound to the column after elution with low pH, allowing the reuse of the column for alternative uses, such as screening for other protein-protein interactions using SPINK3 as the bait.

  2. Toward a Strongly Interacting Scalar Higgs Particle

    International Nuclear Information System (INIS)

    Shalaby, Abouzeid M.; El-Houssieny, M.

    2008-01-01

    We calculate the vacuum energy of the non-Hermitian and PT symmetric (-gφ 4 ) 2+1 scalar field theory. Rather than the corresponding Hermitian theory and due to the asymptotic freedom property of the theory, the vacuum energy does not blow up for large energy scales which is a good sign to solve the hierarchy problem when using this model to break the U(1)xSU(2) symmetry in the standard model. The theory is strongly interacting and in fact, all the dimensionful parameters in the theory like mass and energy are finite even for very high energy scales. Moreover, relative to the vacuum energy for the Hermitian φ 4 theory, the vacuum energy of the non-Hermitian and PT symmetric (-gφ 4 ) 2+1 theory is tiny, which is a good sign toward the solution of the cosmological constant problem. Remarkably, these features of the non-Hermitian and PT symmetric (-gφ 4 ) 2+1 scalar field theory make it very plausible to be employed as a Higgs mechanism in the standard model instead of the problematic Hermitian Higgs mechanism

  3. Effects of protein-protein interactions and ligand binding on the ion permeation in KCNQ1 potassium channel.

    Science.gov (United States)

    Jalily Hasani, Horia; Ganesan, Aravindhan; Ahmed, Marawan; Barakat, Khaled H

    2018-01-01

    The voltage-gated KCNQ1 potassium ion channel interacts with the type I transmembrane protein minK (KCNE1) to generate the slow delayed rectifier (IKs) current in the heart. Mutations in these transmembrane proteins have been linked with several heart-related issues, including long QT syndromes (LQTS), congenital atrial fibrillation, and short QT syndrome. Off-target interactions of several drugs with that of KCNQ1/KCNE1 ion channel complex have been known to cause fatal cardiac irregularities. Thus, KCNQ1/KCNE1 remains an important avenue for drug-design and discovery research. In this work, we present the structural and mechanistic details of potassium ion permeation through an open KCNQ1 structural model using the combined molecular dynamics and steered molecular dynamics simulations. We discuss the processes and key residues involved in the permeation of a potassium ion through the KCNQ1 ion channel, and how the ion permeation is affected by (i) the KCNQ1-KCNE1 interactions and (ii) the binding of chromanol 293B ligand and its derivatives into the complex. The results reveal that interactions between KCNQ1 with KCNE1 causes a pore constriction in the former, which in-turn forms small energetic barriers in the ion-permeation pathway. These findings correlate with the previous experimental reports that interactions of KCNE1 dramatically slows the activation of KCNQ1. Upon ligand-binding onto the complex, the energy-barriers along ion permeation path are more pronounced, as expected, therefore, requiring higher force in our steered-MD simulations. Nevertheless, pulling the ion when a weak blocker is bound to the channel does not necessitate high force in SMD. This indicates that our SMD simulations have been able to discern between strong and week blockers and reveal their influence on potassium ion permeation. The findings presented here will have some implications in understanding the potential off-target interactions of the drugs with the KCNQ1/KCNE1 channel

  4. Fluorescence energy transfer monitoring of protein-protein interaction in human cells: the Cyclin T1-HIV1 Tat case.

    Science.gov (United States)

    Ferrari, Aldo; Cinelli, Riccardo A. G.; Pellegrini, Vittorio; Beltram, Fabio; Marcello, Alessandro; Tyagi, Mudit; Giacca, Mauro

    2001-03-01

    The human immunodeficiency virus type 1 (HIV-1) Tat protein promotes transcriptional elongation of viral RNAs. Here we show that human Cyclin T1 directly binds Tat in cultured cells. By mapping fluorescence resonance energy transfer (FRET) in different cellular compartments we shall present a quantitative analysis of this interaction. The matched tagging pair consists of two optically matched variants of the green fluorescent protein: the enhanced GFP and the blue fluorescent protein. Strong energy transfer was observed between Cyclin T1 and Tat both in the cytoplasm and in specific subnuclear regions. We shall argue that such high-resolution optical studies can provide significant new insight in molecular processes and demonstrate that, for the specific case-study presented, they lead to a model by which Tat recruits Cyclin T1 out of the nuclear compartments where the protein resides to promote transcriptional activation.

  5. 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.

  6. 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.

  7. Diversity of T cell epitopes in Plasmodium falciparum circumsporozoite protein likely due to protein-protein interactions.

    Science.gov (United States)

    Aragam, Nagesh R; Thayer, Kelly M; Nge, Nabi; Hoffman, Irving; Martinson, Francis; Kamwendo, Debbie; Lin, Feng-Chang; Sutherland, Colin; Bailey, Jeffrey A; Juliano, Jonathan J

    2013-01-01

    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.

  8. N6L pseudopeptide interferes with nucleophosmin protein-protein interactions and sensitizes leukemic cells to chemotherapy.

    Science.gov (United States)

    De Cola, A; Franceschini, M; Di Matteo, A; Colotti, G; Celani, R; Clemente, E; Ippoliti, R; Cimini, A M; Dhez, A C; Vallée, B; Raineri, F; Cascone, I; Destouches, D; De Laurenzi, V; Courty, J; Federici, L

    2018-01-01

    NPM1 is a multifunctional nucleolar protein implicated in several processes such as ribosome maturation and export, DNA damage response and apoptotic response to stress stimuli. The NPM1 gene is involved in human tumorigenesis and is found mutated in one third of acute myeloid leukemia patients, leading to the aberrant cytoplasmic localization of NPM1. Recent studies indicated that the N6L multivalent pseudopeptide, a synthetic ligand of cell-surface nucleolin, is also able to bind NPM1 with high affinity. N6L inhibits cell growth with different mechanisms and represents a good candidate as a novel anticancer drug for a number of malignancies of different histological origin. In this study we investigated whether N6L treatment could drive antitumor effect in acute myeloid leukemia cell lines. We found that N6L binds NPM1 at the N-terminal domain, co-localizes with cytoplasmic, mutated NPM1, and interferes with its protein-protein associations. N6L toxicity appears to be p53 dependent but interestingly, the leukemic cell line harbouring the mutated form of NPM1 is more resistant to treatment, suggesting that NPM1 cytoplasmic delocalization confers protection from p53 activation. Moreover, we show that N6L sensitizes AML cells to doxorubicin and cytarabine treatment. These studies suggest that N6L may be a promising option in combination therapies for acute myeloid leukemia treatment. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  9. A linear classifier based on entity recognition tools and a statistical approach to method extraction in the protein-protein interaction literature.

    Science.gov (United States)

    Lourenço, Anália; Conover, Michael; Wong, Andrew; Nematzadeh, Azadeh; Pan, Fengxia; Shatkay, Hagit; Rocha, Luis M

    2011-10-03

    We participated, as Team 81, in the Article Classification and the Interaction Method subtasks (ACT and IMT, respectively) of the Protein-Protein Interaction task of the BioCreative III Challenge. For the ACT, we pursued an extensive testing of available Named Entity Recognition and dictionary tools, and used the most promising ones to extend our Variable Trigonometric Threshold linear classifier. Our main goal was to exploit the power of available named entity recognition and dictionary tools to aid in the classification of documents relevant to Protein-Protein Interaction (PPI). For the IMT, we focused on obtaining evidence in support of the interaction methods used, rather than on tagging the document with the method identifiers. We experimented with a primarily statistical approach, as opposed to employing a deeper natural language processing strategy. In a nutshell, we exploited classifiers, simple pattern matching for potential PPI methods within sentences, and ranking of candidate matches using statistical considerations. Finally, we also studied the benefits of integrating the method extraction approach that we have used for the IMT into the ACT pipeline. For the ACT, our linear article classifier leads to a ranking and classification performance significantly higher than all the reported submissions to the challenge in terms of Area Under the Interpolated Precision and Recall Curve, Mathew's Correlation Coefficient, and F-Score. We observe that the most useful Named Entity Recognition and Dictionary tools for classification of articles relevant to protein-protein interaction are: ABNER, NLPROT, OSCAR 3 and the PSI-MI ontology. For the IMT, our results are comparable to those of other systems, which took very different approaches. While the performance is not very high, we focus on providing evidence for potential interaction detection methods. A significant majority of the evidence sentences, as evaluated by independent annotators, are relevant to PPI

  10. A membrane cell for on-line hydrogen/deuterium exchange to study protein folding and protein-protein interactions by mass spectrometry.

    Science.gov (United States)

    Astorga-Wells, Juan; Landreh, Michael; Johansson, Jan; Bergman, Tomas; Jörnvall, Hans

    2011-09-01

    A membrane cell for hydrogen and deuterium exchange on-line with mass spectrometry has been developed to monitor protein-protein interactions and protein conformations. It consists of two channels separated by a semipermeable membrane, where one channel carries the protein sample and the other deuterium oxide. The membrane allows transfer of deuterium oxide into the sample flow. The labeling time is controlled via the flow rate in the sample channel. This cell was validated against three models commonly used in hydrogen-deuterium exchange mass spectrometry: monitoring of folded and unfolded states in a protein, mapping the protein secondary structure at the peptide level, and detection of protein and antibody interactions. The system avoids the conventionally used sample dilution and handling, allowing for potential automation.

  11. A Membrane Cell for On-line Hydrogen/Deuterium Exchange to Study Protein Folding and Protein-Protein Interactions by Mass Spectrometry*

    Science.gov (United States)

    Astorga-Wells, Juan; Landreh, Michael; Johansson, Jan; Bergman, Tomas; Jörnvall, Hans

    2011-01-01

    A membrane cell for hydrogen and deuterium exchange on-line with mass spectrometry has been developed to monitor protein-protein interactions and protein conformations. It consists of two channels separated by a semipermeable membrane, where one channel carries the protein sample and the other deuterium oxide. The membrane allows transfer of deuterium oxide into the sample flow. The labeling time is controlled via the flow rate in the sample channel. This cell was validated against three models commonly used in hydrogen-deuterium exchange mass spectrometry: monitoring of folded and unfolded states in a protein, mapping the protein secondary structure at the peptide level, and detection of protein and antibody interactions. The system avoids the conventionally used sample dilution and handling, allowing for potential automation. PMID:21610101

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

    OpenAIRE

    Browne, Fiona; Wang, Haiying; Zheng, Huiru; 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...

  13. De Sitter vacua of strongly interacting QFT

    Energy Technology Data Exchange (ETDEWEB)

    Buchel, Alex [Department of Applied Mathematics, University of Western Ontario,London, Ontario N6A 5B7 (Canada); Department of Physics and Astronomy, University of Western Ontario,London, Ontario N6A 5B7 (Canada); Perimeter Institute for Theoretical Physics,Waterloo, Ontario N2J 2W9 (Canada); Karapetyan, Aleksandr [Department of Applied Mathematics, University of Western Ontario,London, Ontario N6A 5B7 (Canada)

    2017-03-22

    We use holographic correspondence to argue that Euclidean (Bunch-Davies) vacuum is a late-time attractor of the dynamical evolution of quantum gauge theories at strong coupling. The Bunch-Davies vacuum is not an adiabatic state, if the gauge theory is non-conformal — the comoving entropy production rate is nonzero. Using the N=2{sup ∗} gauge theory holography, we explore prospects of explaining current accelerated expansion of the Universe as due to the vacuum energy of a strongly coupled QFT.

  14. Relativistic rapprochement of electromagnetic and strong interactions

    International Nuclear Information System (INIS)

    Strel'tsov, V.N.

    1995-01-01

    On the basis of the Lienard-Wiechert potential and the relativistic Yukawa potential it is shown that the corresponding interactions with velocity growth increase differently (the electromagnetic one increases faster). According to preliminary estimations they are equivalent, at distances of the 'action radius' of nuclear forces, at γ≅ 960, where γ is the Lorentz factor. 2 refs

  15. Landscape mapping of functional proteins in insulin signal transduction and insulin resistance: a network-based protein-protein interaction analysis.

    Directory of Open Access Journals (Sweden)

    Chiranjib Chakraborty

    Full Text Available The type 2 diabetes has increased rapidly in recent years throughout the world. The insulin signal transduction mechanism gets disrupted sometimes and it's known as insulin-resistance. It is one of the primary causes associated with type-2 diabetes. The signaling mechanisms involved several proteins that include 7 major functional proteins such as INS, INSR, IRS1, IRS2, PIK3CA, Akt2, and GLUT4. Using these 7 principal proteins, multiple sequences alignment has been created. The scores between sequences also have been developed. We have constructed a phylogenetic tree and modified it with node and distance. Besides, we have generated sequence logos and ultimately developed the protein-protein interaction network. The small insulin signal transduction protein arrangement shows complex network between the functional proteins.

  16. Dynamic modular architecture of protein-protein interaction networks beyond the dichotomy of ‘date' and ‘party' hubs

    Science.gov (United States)

    Chang, Xiao; Xu, Tao; Li, Yun; Wang, Kai

    2013-01-01

    The protein-protein interaction (PPI) networks are dynamically organized as modules, and are typically described by hub dichotomy: ‘party' hubs act as intramodule hubs and are coexpressed with their partners, yet ‘date' hubs act as coordinators among modules and are incoherently expressed with their partners. However, there remains skepticism about the existence of hub dichotomy. Since different algorithms and data sets were used in previous studies to test the model of hub classification, the conclusions may be largely influenced by the potential inherent biases. In this study, we evaluated two data sets of yeast interactome, and systematically investigated the behavior of hubs from multiple perspectives including co-expression patterns, topological roles and functional classifications. Our results revealed consistency between the two data sets, confirming the presence of hub dichotomy. Furthermore, we analyzed a human interactome data set, and demonstrated that the modular architecture of the PPI networks was more complicated than hub dichotomy. PMID:23603706

  17. Potential of 13C and 15N Labeling for Studying Protein-Protein Interactions Using Fourier Transform Infrared Spectroscopy

    NARCIS (Netherlands)

    Haris, Parvez I.; Robillard, George T.; Dijk, Alard A. van; Chapman, Dennis

    1992-01-01

    In this study, we examine the interaction between two bacterial proteins, namely HPr and IIAmtl of the Escherichia coli phosphoenolpyruvate-dependent phosphotransferase system, using FTIR spectroscopy. In an interaction involving a 1:1 molar ratio of these two proteins, when they are unlabeled, the

  18. Amphipathic helical peptides hamper protein-protein interactions of the intrinsically disordered chromatin nuclear protein 1 (NUPR1).

    Science.gov (United States)

    Santofimia-Castaño, Patricia; Rizzuti, Bruno; Abián, Olga; Velázquez-Campoy, Adrián; Iovanna, Juan L; Neira, José L

    2018-03-09

    NUPR1 is a multifunctional intrinsically disordered protein (IDP) involved, among other functions, in chromatin remodelling, and development of pancreatic ductal adenocarcinoma (PDAC). It interacts with several biomolecules through hydrophobic patches around residues Ala33 and Thr68. The drug trifluoperazine (TFP), which hampers PDAC development in xenografted mice, also binds to those regions. Because of the large size of the hot-spot interface of NUPR1, small molecules could not be adequate to modulate its functions. We explored how amphipathic helical-designed peptides were capable of interacting with wild-type NUPR1 and the Thr68Gln mutant, inhibiting the interaction with NUPR1 protein partners. We used in vitro biophysical techniques (fluorescence, circular dichroism (CD), nuclear magnetic resonance (NMR) and isothermal titration calorimetry (ITC)), in silico studies (docking and molecular dynamics (MD)), and in cellulo protein ligation assays (PLAs) to study the interaction. Peptide dissociation constants towards wild-type NUPR1 were ~ 3 μM, whereas no interaction was observed with the Thr68Gln mutant. Peptides interacted with wild-type NUPR1 residues around Ala33 and residues at the C terminus, as shown by NMR. The computational results clarified the main determinants of the interactions, providing a mechanism for the ligand-capture that explains why peptide binding was not observed for Thr68Gln mutant. Finally, the in cellulo assays indicated that two out of four peptides inhibited the interaction of NUPR1 with the C-terminal region of the Polycomb RING protein 1 (C-RING1B). Designed peptides can be used as lead compounds to inhibit NUPR1 interactions. Peptides may be exploited as drugs to target IDPs. Copyright © 2018. Published by Elsevier B.V.

  19. System in biology leading to cell pathology: stable protein-protein interactions after covalent modifications by small molecules or in transgenic cells.

    Science.gov (United States)

    Malina, Halina Z

    2011-01-19

    The physiological processes in the cell are regulated by reversible, electrostatic protein-protein interactions. Apoptosis is such a regulated process, which is critically important in tissue homeostasis and development and leads to complete disintegration of the cell. Pathological apoptosis, a process similar to apoptosis, is associated with aging and infection. The current study shows that pathological apoptosis is a process caused by the covalent interactions between the signaling proteins, and a characteristic of this pathological network is the covalent binding of calmodulin to regulatory sequences. Small molecules able to bind covalently to the amino group of lysine, histidine, arginine, or glutamine modify the regulatory sequences of the proteins. The present study analyzed the interaction of calmodulin with the BH3 sequence of Bax, and the calmodulin-binding sequence of myristoylated alanine-rich C-kinase substrate in the presence of xanthurenic acid in primary retinal epithelium cell cultures and murine epithelial fibroblast cell lines transformed with SV40 (wild type [WT], Bid knockout [Bid-/-], and Bax-/-/Bak-/- double knockout [DKO]). Cell death was observed to be associated with the covalent binding of calmodulin, in parallel, to the regulatory sequences of proteins. Xanthurenic acid is known to activate caspase-3 in primary cell cultures, and the results showed that this activation is also observed in WT and Bid-/- cells, but not in DKO cells. However, DKO cells were not protected against death, but high rates of cell death occurred by detachment. The results showed that small molecules modify the basic amino acids in the regulatory sequences of proteins leading to covalent interactions between the modified sequences (e.g., calmodulin to calmodulin-binding sites). The formation of these polymers (aggregates) leads to an unregulated and, consequently, pathological protein network. The results suggest a mechanism for the involvement of small molecules

  20. Protein-Protein Interaction Article Classification Using a Convolutional Recurrent Neural Network with Pre-trained Word Embeddings.

    Science.gov (United States)

    Matos, Sérgio; Antunes, Rui

    2017-12-13

    Curation of protein interactions from scientific articles is an important task, since interaction networks are essential for the understanding of biological processes associated with disease or pharmacological action for example. However, the increase in the number of publications that potentially contain relevant information turns this into a very challenging and expensive task. In this work we used a convolutional recurrent neural network for identifying relevant articles for extracting information regarding protein interactions. Using the BioCreative III Article Classification Task dataset, we achieved an area under the precision-recall curve of 0.715 and a Matthew's correlation coefficient of 0.600, which represents an improvement over previous works.

  1. "Strong interaction" for particle physics laboratories

    CERN Multimedia

    2003-01-01

    A new Web site pooling the communications resources of particle physics centres all over the world has just been launched. The official launching of the new particle physics website Interactions.org during the Lepton-Proton 2003 Conference at the American laboratory Fermilab was accompanied by music and a flurry of balloons. On the initiative of Fermilab, the site was created by a collaboration of communication teams from over fifteen of the world's particle physics laboratories, including KEK, SLAC, INFN, JINR and, of course, CERN, who pooled their efforts to develop the new tool. The spectacular launching of the new particle physics website Interactions.org at Fermilab on 12 August 2003. A real gateway to particle physics, the site not only contains all the latest news from the laboratories but also offers images, graphics and a video/animation link. In addition, it provides information about scientific policies, links to the universities, a very useful detailed glossary of particle physics and astrophysic...

  2. A flow cytometry-based FRET assay to identify and analyse protein-protein interactions in living cells.

    Directory of Open Access Journals (Sweden)

    Carina Banning

    2010-02-01

    Full Text Available Försters resonance energy transfer (FRET microscopy is widely used for the analysis of protein interactions in intact cells. However, FRET microscopy is technically challenging and does not allow assessing interactions in large cell numbers. To overcome these limitations we developed a flow cytometry-based FRET assay and analysed interactions of human and simian immunodeficiency virus (HIV and SIV Nef and Vpu proteins with cellular factors, as well as HIV Rev multimer-formation.Amongst others, we characterize the interaction of Vpu with CD317 (also termed Bst-2 or tetherin, a host restriction factor that inhibits HIV release from infected cells and demonstrate that the direct binding of both is mediated by the Vpu membrane-spanning region. Furthermore, we adapted our assay to allow the identification of novel protein interaction partners in a high-throughput format.The presented combination of FRET and FACS offers the precious possibility to discover and define protein interactions in living cells and is expected to contribute to the identification of novel therapeutic targets for treatment of human diseases.

  3. ChiPPI: a novel method for mapping chimeric protein-protein interactions uncovers selection principles of protein fusion events in cancer.

    Science.gov (United States)

    Frenkel-Morgenstern, Milana; Gorohovski, Alessandro; Tagore, Somnath; Sekar, Vaishnovi; Vazquez, Miguel; Valencia, Alfonso

    2017-07-07

    Fusion proteins, comprising peptides deriving from the translation of two parental genes, are produced in cancer by chromosomal aberrations. The expressed fusion protein incorporates domains of both parental proteins. Using a methodology that treats discrete protein domains as binding sites for specific domains of interacting proteins, we have cataloged the protein interaction networks for 11 528 cancer fusions (ChiTaRS-3.1). Here, we present our novel method, chimeric protein-protein interactions (ChiPPI) that uses the domain-domain co-occurrence scores in order to identify preserved interactors of chimeric proteins. Mapping the influence of fusion proteins on cell metabolism and pathways reveals that ChiPPI networks often lose tumor suppressor proteins and gain oncoproteins. Furthermore, fusions often induce novel connections between non-interactors skewing interaction networks and signaling pathways. We compared fusion protein PPI networks in leukemia/lymphoma, sarcoma and solid tumors finding distinct enrichment patterns for each disease type. While certain pathways are enriched in all three diseases (Wnt, Notch and TGF β), there are distinct patterns for leukemia (EGFR signaling, DNA replication and CCKR signaling), for sarcoma (p53 pathway and CCKR signaling) and solid tumors (FGFR and EGFR signaling). Thus, the ChiPPI method represents a comprehensive tool for studying the anomaly of skewed cellular networks produced by fusion proteins in cancer. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  4. Supersymmetry and weak, electromagnetic and strong interactions

    International Nuclear Information System (INIS)

    Fayet, P.

    1977-01-01

    A supersymmetric theory of particle interactions is discussed. It is based on the earlier model which involves gauge (or vector) superfields, and matter (or chiral) superfields; each of them describes a vector and a Majorana spinor in the first case, or a two-component Dirac spinor and a complex scalar in the second case. The new theory suggests the possible existence of spin - 1/2 gluons and heavy spin-0 quarks, besides spin - 1 gluons and spin - 1/2 quarks. To prevent scalar particles to be exchanged in processes such as μ or β decays a new class of leptons with its own quantum number is introduced; it includes charged leptons and a ''photonic neutrino''

  5. Identification of novel protein-protein interactions of Yersinia pestis type III secretion system by yeast two hybrid system.

    Directory of Open Access Journals (Sweden)

    Huiying Yang

    Full Text Available Type III secretion system (T3SS of the plague bacterium Y. pestis encodes a syringe-like structure consisting of more than 20 proteins, which can inject virulence effectors into host cells to modulate the cellular functions. Here in this report, interactions among the possible components in T3SS of Yersinia pestis were identified using yeast mating technique. A total of 57 genes, including all the pCD1-encoded genes except those involved in plasmid replication and partition, pseudogenes, and the putative transposase genes, were subjected to yeast mating analysis. 21 pairs of interaction proteins were identified, among which 9 pairs had been previously reported and 12 novel pairs were identified in this study. Six of them were tested by GST pull down assay, and interaction pairs of YscG-SycD, YscG-TyeA, YscI-YscF, and YopN-YpCD1.09c were successfully validated, suggesting that these interactions might play potential roles in function of Yersinia T3SS. Several potential new interactions among T3SS components could help to understand the assembly and regulation of Yersinia T3SS.

  6. Protein-protein interactions as a strategy towards protein-specific drug design: the example of ataxin-1.

    Directory of Open Access Journals (Sweden)

    Cesira de Chiara

    Full Text Available A main challenge for structural biologists is to understand the mechanisms that discriminate between molecular interactions and determine function. Here, we show how partner recognition of the AXH domain of the transcriptional co-regulator ataxin-1 is fine-tuned by a subtle balance between self- and hetero-associations. Ataxin-1 is the protein responsible for the hereditary spinocerebellar ataxia type 1, a disease linked to protein aggregation and transcriptional dysregulation. Expansion of a polyglutamine tract is essential for ataxin-1 aggregation, but the sequence-wise distant AXH domain plays an important aggravating role in the process. The AXH domain is also a key element for non-aberrant function as it intervenes in interactions with multiple protein partners. Previous data have shown that AXH is dimeric in solution and forms a dimer of dimers when crystallized. By solving the structure of a complex of AXH with a peptide from the interacting transcriptional repressor CIC, we show that the dimer interface of AXH is displaced by the new interaction and that, when blocked by the CIC peptide AXH aggregation and misfolding are impaired. This is a unique example in which palindromic self- and hetero-interactions within a sequence with chameleon properties discriminate the partner. We propose a drug design strategy for the treatment of SCA1 that is based on the information gained from the AXH/CIC complex.

  7. Computational design, construction, and characterization of a set of specificity determining residues in protein-protein interactions.

    Science.gov (United States)

    Nagao, Chioko; Izako, Nozomi; Soga, Shinji; Khan, Samia Haseeb; Kawabata, Shigeki; Shirai, Hiroki; Mizuguchi, Kenji

    2012-10-01

    Proteins interact with different partners to perform different functions and it is important to elucidate the determinants of partner specificity in protein complex formation. Although methods for detecting specificity determining positions have been developed previously, direct experimental evidence for these amino acid residues is scarce, and the lack of information has prevented further computational studies. In this article, we constructed a dataset that is likely to exhibit specificity in protein complex formation, based on available crystal structures and several intuitive ideas about interaction profiles and functional subclasses. We then defined a "structure-based specificity determining position (sbSDP)" as a set of equivalent residues in a protein family showing a large variation in their interaction energy with different partners. We investigated sequence and structural features of sbSDPs and demonstrated that their amino acid propensities significantly differed from those of other interacting residues and that the importance of many of these residues for determining specificity had been verified experimentally. Copyright © 2012 Wiley Periodicals, Inc.

  8. SynSysNet: integration of experimental data on synaptic protein-protein interactions with drug-target relations

    NARCIS (Netherlands)

    von Eichborn, J.; Dunkel, M.; Gohlke, B.O.; Preissner, S.C.; Hoffmann, M.F.; Bauer, J.M.J.; Armstrong, J.D.; Schaefer, M.H.; Andrade-Navarro, M.A.; Le Novere, N.; Croning, M.D.R.; Grant, S.G.N.; van Nierop, P.; Smit, A.B.; Preissner, R.

    2013-01-01

    We created SynSysNet, available online at http://bioinformatics.charite.de/ synsysnet, to provide a platform that creates a comprehensive 4D network of synaptic interactions. Neuronal synapses are fundamental structures linking nerve cells in the brain and they are responsible for neuronal

  9. Distinct functional domains of PNMA5 mediate protein-protein interaction, nuclear localization, and apoptosis signaling in human cancer cells.

    Science.gov (United States)

    Lee, Yong Hoi; Pang, Siew Wai; Poh, Chit Laa; Tan, Kuan Onn

    2016-09-01

    Members of paraneoplastic Ma (PNMA) family have been identified as onconeuronal antigens, which aberrant expressions in cancer cells of patients with paraneoplastic disorder (PND) are closely linked to manifestation of auto-immunity, neuro-degeneration, and cancer. The purpose of present study was to determine the role of PNMA5 and its functional relationship to MOAP-1 (PNMA4) in human cancer cells. PNMA5 mutants were generated through deletion or site-directed mutagenesis and transiently expressed in human cancer cell lines to investigate their role in apoptosis, subcellular localization, and potential interaction with MOAP-1 through apoptosis assays, fluorescence microscopy, and co-immunoprecipitation studies, respectively. Over-expressed human PNMA5 exhibited nuclear localization pattern in both MCF-7 and HeLa cells. Deletion mapping and mutagenesis studies showed that C-terminus of PNMA5 is responsible for nuclear localization, while the amino acid residues (391KRRR) within the C-terminus of PNMA5 are required for nuclear targeting. Deletion mapping and co-immunoprecipitation studies showed that PNMA5 interacts with MOAP-1 and N-terminal domain of PNMA5 is required for interaction with MOAP-1. Furthermore, co-expression of PNMA5 and MOAP-1 in MCF-7 cells significantly enhanced chemo-sensitivity of MCF-7 to Etoposide treatment, indicating that PNMA5 and MOAP-1 interact synergistically to promote apoptotic signaling in MCF-7 cells. Our results show that PNMA5 promotes apoptosis signaling in HeLa and MCF-7 cells and interacts synergistically with MOAP-1 through its N-terminal domain to promote apoptosis and chemo-sensitivity in human cancer cells. The C-terminal domain of PNMA5 is required for nuclear localization; however, both N-and C-terminal domains of PNMA5 appear to be required for pro-apoptotic function.

  10. 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

  11. Redox biology of Mycobacterium tuberculosis H37Rv: protein-protein interaction between GlgB and WhiB1 involves exchange of thiol-disulfide

    Directory of Open Access Journals (Sweden)

    Kishan KV Radha

    2009-01-01

    Full Text Available Abstract Background Mycobacterium tuberculosis, an intracellular pathogen encounters redox stress throughout its life inside the host. In order to protect itself from the redox onslaughts of host immune system, M. tuberculosis appears to have developed accessory thioredoxin-like proteins which are represented by ORFs encoding WhiB-like proteins. We have earlier reported that WhiB1/Rv3219 is a thioredoxin like protein of M. tuberculosis and functions as a protein disulfide reductase. Generally thioredoxins have many substrate proteins. The current study aims to identify the substrate protein(s of M. tuberculosis WhiB1. Results Using yeast two-hybrid screen, we identified alpha (1,4-glucan branching enzyme (GlgB of M. tuberculosis as a interaction partner of WhiB1. In vitro GST pull down assay confirmed the direct physical interaction between GlgB and WhiB1. Both mass spectrometry data of tryptic digests and in vitro labeling of cysteine residues with 4-acetamido-4' maleimidyl-stilbene-2, 2'-disulfonic acid showed that in GlgB, C95 and C658 are free but C193 and C617 form an intra-molecular disulfide bond. WhiB1 has a C37XXC40 motif thus a C40S mutation renders C37 to exist as a free thiol to form a hetero-disulfide bond with the cysteine residue of substrate protein. A disulfide mediated binary complex formation between GlgB and WhiB1C40S was shown by both in-solution protein-protein interaction and thioredoxin affinity chromatography. Finally, transfer of reducing equivalent from WhiB1 to GlgB disulfide was confirmed by 4-acetamido-4' maleimidyl-stilbene-2, 2'-disulfonic acid trapping by the reduced disulfide of GlgB. Two different thioredoxins, TrxB/Rv1471 and TrxC/Rv3914 of M. tuberculosis could not perform this reaction suggesting that the reduction of GlgB by WhiB1 is specific. Conclusion We conclude that M. tuberculosis GlgB has one intra-molecular disulfide bond which is formed between C193 and C617. WhiB1, a thioredoxin like protein

  12. QCD : the theory of strong interactions Conference MT17

    CERN Multimedia

    2001-01-01

    The theory of strong interactions,Quantum Chromodynamics (QCD), predicts that the strong interaction is transmitted by the exchange of particles called gluons. Unlike the messengers of electromagnetism photons, which are electrically neutral - gluons carry a strong charge associated with the interaction they mediate. QCD predicts that the strength of the interaction between quarks and gluons becomes weaker at higher energies. LEP has measured the evolution of the strong coupling constant up to energies of 200 GeV and has confirmed this prediction.

  13. 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.

  14. GluR2 protein-protein interactions and the regulation of AMPA receptors during synaptic plasticity.

    OpenAIRE

    Duprat, Fabrice; Daw, Michael; Lim, Wonil; Collingridge, Graham; Isaac, John

    2003-01-01

    AMPA-type glutamate receptors mediate most fast excitatory synaptic transmissions in the mammalian brain. They are critically involved in the expression of long-term potentiation and long-term depression, forms of synaptic plasticity that are thought to underlie learning and memory. A number of synaptic proteins have been identified that interact with the intracellular C-termini of AMPA receptor subunits. Here, we review recent studies and present new experimental data on the roles of these i...

  15. Structure and Protein-Protein Interaction Studies on Chlamydia trachomatis Protein CT670 (YscO Homolog)

    Energy Technology Data Exchange (ETDEWEB)

    Lorenzini, Emily; Singer, Alexander; Singh, Bhag; Lam, Robert; Skarina, Tatiana; Chirgadze, Nickolay Y.; Savchenko, Alexei; Gupta, Radhey S. (Toronto); (McMaster U.); (OCI)

    2010-07-28

    Comparative genomic studies have identified many proteins that are found only in various Chlamydiae species and exhibit no significant sequence similarity to any protein in organisms that do not belong to this group. The CT670 protein of Chlamydia trachomatis is one of the proteins whose genes are in one of the type III secretion gene clusters but whose cellular functions are not known. CT670 shares several characteristics with the YscO protein of Yersinia pestis, including the neighboring genes, size, charge, and secondary structure, but the structures and/or functions of these proteins remain to be determined. Although a BLAST search with CT670 did not identify YscO as a related protein, our analysis indicated that these two proteins exhibit significant sequence similarity. In this paper, we report that the CT670 crystal, solved at a resolution of 2 {angstrom}, consists of a single coiled coil containing just two long helices. Gel filtration and analytical ultracentrifugation studies showed that in solution CT670 exists in both monomeric and dimeric forms and that the monomer predominates at lower protein concentrations. We examined the interaction of CT670 with many type III secretion system-related proteins (viz., CT091, CT665, CT666, CT667, CT668, CT669, CT671, CT672, and CT673) by performing bacterial two-hybrid assays. In these experiments, CT670 was found to interact only with the CT671 protein (YscP homolog), whose gene is immediately downstream of ct670. A specific interaction between CT670 and CT671 was also observed when affinity chromatography pull-down experiments were performed. These results suggest that CT670 and CT671 are putative homologs of the YcoO and YscP proteins, respectively, and that they likely form a chaperone-effector pair.

  16. High-Affinity, Small-Molecule Peptidomimetic Inhibitors of MLL1/WDR5 Protein-Protein Interaction

    Energy Technology Data Exchange (ETDEWEB)

    Karatas, Hacer; Townsend, Elizabeth C; Cao, Fang; Chen, Yong; Bernard, Denzil; Liu, Liu; Lei, Ming; Dou, Yali; Wang, Shaomeng [Michigan; (HHMI)

    2013-02-12

    Mixed lineage leukemia 1 (MLL1) is a histone H3 lysine 4 (H3K4) methyltransferase, and targeting the MLL1 enzymatic activity has been proposed as a novel therapeutic strategy for the treatment of acute leukemia harboring MLL1 fusion proteins. The MLL1/WDR5 protein–protein interaction is essential for MLL1 enzymatic activity. In the present study, we designed a large number of peptidomimetics to target the MLL1/WDR5 interaction based upon -CO-ARA-NH–, the minimum binding motif derived from MLL1. Our study led to the design of high-affinity peptidomimetics, which bind to WDR5 with Ki < 1 nM and function as potent antagonists of MLL1 activity in a fully reconstituted in vitro H3K4 methyltransferase assay. Determination of co-crystal structures of two potent peptidomimetics in complex with WDR5 establishes their structural basis for high-affinity binding to WDR5. Evaluation of one such peptidomimetic, MM-102, in bone marrow cells transduced with MLL1-AF9 fusion construct shows that the compound effectively decreases the expression of HoxA9 and Meis-1, two critical MLL1 target genes in MLL1 fusion protein mediated leukemogenesis. MM-102 also specifically inhibits cell growth and induces apoptosis in leukemia cells harboring MLL1 fusion proteins. Our study provides the first proof-of-concept for the design of small-molecule inhibitors of the WDR5/MLL1 protein–protein interaction as a novel therapeutic approach for acute leukemia harboring MLL1 fusion proteins.

  17. Targeting YAP/TAZ-TEAD protein-protein interactions using fragment-based and computational modeling approaches.

    Directory of Open Access Journals (Sweden)

    Hung Yi Kristal Kaan

    Full Text Available The Hippo signaling pathway, which is implicated in the regulation of organ size, has emerged as a potential target for the development of cancer therapeutics. YAP, TAZ (transcription co-activators and TEAD (transcription factor are the downstream transcriptional machinery and effectors of the pathway. Formation of the YAP/TAZ-TEAD complex leads to transcription of growth-promoting genes. Conversely, disrupting the interactions of the complex decreases cell proliferation. Herein, we screened a 1000-member fragment library using Thermal Shift Assay and identified a hit fragment. We confirmed its binding at the YAP/TAZ-TEAD interface by X-ray crystallography, and showed that it occupies the same hydrophobic pocket as a conserved phenylalanine of YAP/TAZ. This hit fragment serves as a scaffold for the development of compounds that have the potential to disrupt YAP/TAZ-TEAD interactions. Structure-activity relationship studies and computational modeling were also carried out to identify more potent compounds that may bind at this validated druggable binding site.

  18. The Hippo Pathway and YAP/TAZ-TEAD Protein-Protein Interaction as Targets for Regenerative Medicine and Cancer Treatment.

    Science.gov (United States)

    Santucci, Matteo; Vignudelli, Tatiana; Ferrari, Stefania; Mor, Marco; Scalvini, Laura; Bolognesi, Maria Laura; Uliassi, Elisa; Costi, Maria Paola

    2015-06-25

    The Hippo pathway is an important organ size control signaling network and the major regulatory mechanism of cell-contact inhibition. Yes associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ) are its targets and terminal effectors: inhibition of the pathway promotes YAP/TAZ translocation to the nucleus, where they interact with transcriptional enhancer associate domain (TEAD) transcription factors and coactivate the expression of target genes, promoting cell proliferation. Defects in the pathway can result in overgrowth phenotypes due to deregulation of stem-cell proliferation and apoptosis; members of the pathway are directly involved in cancer development. The pharmacological regulation of the pathway might be useful in cancer prevention, treatment, and regenerative medicine applications; currently, a few compounds can selectively modulate the pathway. In this review, we present an overview of the Hippo pathway, the sequence and structural analysis of YAP/TAZ, the known pharmacological modulators of the pathway, especially those targeting YAP/TAZ-TEAD interaction.

  19. Targeting YAP/TAZ-TEAD protein-protein interactions using fragment-based and computational modeling approaches.

    Science.gov (United States)

    Kaan, Hung Yi Kristal; Sim, Adelene Y L; Tan, Siew Kim Joyce; Verma, Chandra; Song, Haiwei

    2017-01-01

    The Hippo signaling pathway, which is implicated in the regulation of organ size, has emerged as a potential target for the development of cancer therapeutics. YAP, TAZ (transcription co-activators) and TEAD (transcription factor) are the downstream transcriptional machinery and effectors of the pathway. Formation of the YAP/TAZ-TEAD complex leads to transcription of growth-promoting genes. Conversely, disrupting the interactions of the complex decreases cell proliferation. Herein, we screened a 1000-member fragment library using Thermal Shift Assay and identified a hit fragment. We confirmed its binding at the YAP/TAZ-TEAD interface by X-ray crystallography, and showed that it occupies the same hydrophobic pocket as a conserved phenylalanine of YAP/TAZ. This hit fragment serves as a scaffold for the development of compounds that have the potential to disrupt YAP/TAZ-TEAD interactions. Structure-activity relationship studies and computational modeling were also carried out to identify more potent compounds that may bind at this validated druggable binding site.

  20. Maximum flow approach to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv from protein-protein interaction network.

    Science.gov (United States)

    Melak, Tilahun; Gakkhar, Sunita

    2015-12-01

    In spite of the implementations of several strategies, tuberculosis (TB) is overwhelmingly a serious global public health problem causing millions of infections and deaths every year. This is mainly due to the emergence of drug-resistance varieties of TB. The current treatment strategies for the drug-resistance TB are of longer duration, more expensive and have side effects. This highlights the importance of identification and prioritization of targets for new drugs. This study has been carried out to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv based on their flow to resistance genes. The weighted proteome interaction network of the pathogen was constructed using a dataset from STRING database. Only a subset of the dataset with interactions that have a combined score value ≥770 was considered. Maximum flow approach has been used to prioritize potential drug targets. The potential drug targets were obtained through comparative genome and network centrality analysis. The curated set of resistance genes was retrieved from literatures. Detail literature review and additional assessment of the method were also carried out for validation. A list of 537 proteins which are essential to the pathogen and non-homologous with human was obtained from the comparative genome analysis. Through network centrality measures, 131 of them were found within the close neighborhood of the centre of gravity of the proteome network. These proteins were further prioritized based on their maximum flow value to resistance genes and they are proposed as reliable drug targets of the pathogen. Proteins which interact with the host were also identified in order to understand the infection mechanism. Potential drug targets of Mycobacterium tuberculosis H37Rv were successfully prioritized based on their flow to resistance genes of existing drugs which is believed to increase the druggability of the targets since inhibition of a protein that has a maximum flow to

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

    Directory of Open Access Journals (Sweden)

    Picard-Cloutier Aude

    2007-12-01

    Full Text Available 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/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.

  2. Structure/Function Analysis of Protein-Protein Interactions and Role of Dynamic Motions in Mercuric Ion Reductase

    Energy Technology Data Exchange (ETDEWEB)

    Miller, Susan M.

    2005-05-18

    This report summarizes the activities and findings of our structure/function studies of the bacterial detoxification enzyme mercuric ion reductase. The objectives of the work were to obtain crystal structure information for the catalytic core of this enzyme, use the information to investigate the importance of specific parts of the enzyme to its function, and investigate the role of one domain of the enzyme in its function within cells. We describe the accomplishments towards these goals including many structures of the wild type and mutant forms of the enzyme that highlight its interactions with its Hg(II) substrate, elucidation of the role of the N-terminal domain in vitro and in vivo, and elucidation of the roles of at two conserved residues in the core in the mechanism of catalysis.

  3. Probing intermolecular protein-protein interactions in the calcium-sensing receptor homodimer using bioluminescence resonance energy transfer (BRET)

    DEFF Research Database (Denmark)

    Jensen, Anders A.; Hansen, Jakob L; Sheikh, Søren P

    2002-01-01

    The calcium-sensing receptor (CaR) belongs to family C of the G-protein coupled receptor superfamily. The receptor is believed to exist as a homodimer due to covalent and non-covalent interactions between the two amino terminal domains (ATDs). It is well established that agonist binding to family C...... receptors takes place at the ATD and that this causes the ATD dimer to twist. However, very little is known about the translation of the ATD dimer twist into G-protein coupling to the 7 transmembrane moieties (7TMs) of these receptor dimers. In this study we have attempted to delineate the agonist......-induced intermolecular movements in the CaR homodimer using the new bioluminescence resonance energy transfer technique, BRET2, which is based on the transference of energy from Renilla luciferase (Rluc) to the green fluorescent protein mutant GFP2. We tagged CaR with Rluc and GFP2 at different intracellular locations...

  4. Liquid-Liquid Phase Separation in a Dual Variable Domain Immunoglobulin Protein Solution: Effect of Formulation Factors and Protein-Protein Interactions.

    Science.gov (United States)

    Raut, Ashlesha S; Kalonia, Devendra S

    2015-09-08

    Dual variable domain immunoglobulin proteins (DVD-Ig proteins) are large molecules (MW ∼ 200 kDa) with increased asymmetry because of their extended Y-like shape, which results in increased formulation challenges. Liquid-liquid phase separation (LLPS) of protein solutions into protein-rich and protein-poor phases reduces solution stability at intermediate concentrations and lower temperatures, and is a serious concern in formulation development as therapeutic proteins are generally stored at refrigerated conditions. In the current work, LLPS was studied for a DVD-Ig protein molecule as a function of solution conditions by measuring solution opalescence. LLPS of the protein was confirmed by equilibrium studies and by visually observing under microscope. The protein does not undergo any structural change after phase separation. Protein-protein interactions were measured by light scattering (kD) and Tcloud (temperature that marks the onset of phase separation). There is a good agreement between kD measured in dilute solution with Tcloud measured in the critical concentration range. Results indicate that the increased complexity of the molecule (with respect to size, shape, and charge distribution on the molecule) increases contribution of specific and nonspecific interactions in solution, which are affected by formulation factors, resulting in LLPS for DVD-Ig protein.

  5. Development of bimolecular fluorescence complementation using rsEGFP2 for detection and super-resolution imaging of protein-protein interactions in live cells.

    Science.gov (United States)

    Wang, Sheng; Ding, Miao; Chen, Xuanze; Chang, Lei; Sun, Yujie

    2017-06-01

    Direct visualization of protein-protein interactions (PPIs) at high spatial and temporal resolution in live cells is crucial for understanding the intricate and dynamic behaviors of signaling protein complexes. Recently, bimolecular fluorescence complementation (BiFC) assays have been combined with super-resolution imaging techniques including PALM and SOFI to visualize PPIs at the nanometer spatial resolution. RESOLFT nanoscopy has been proven as a powerful live-cell super-resolution imaging technique. With regard to the detection and visualization of PPIs in live cells with high temporal and spatial resolution, here we developed a BiFC assay using split rsEGFP2, a highly photostable and reversibly photoswitchable fluorescent protein previously developed for RESOLFT nanoscopy. Combined with parallelized RESOLFT microscopy, we demonstrated the high spatiotemporal resolving capability of a rsEGFP2-based BiFC assay by detecting and visualizing specifically the heterodimerization interactions between Bcl-x L and Bak as well as the dynamics of the complex on mitochondria membrane in live cells.

  6. Nine steps to proteomic wisdom: A practical guide to using protein-protein interaction networks and molecular pathways as a framework for interpreting disease proteomic profiles.

    Science.gov (United States)

    Isserlin, Ruth; Emili, Andrew

    2007-09-01

    A major aim of proteomic profiling of disease is to uncover the mechanistic basis of a given pathology. High-throughput experimental techniques continue to advance rapidly, but are still plagued by high rates of false negatives, false positives, and other spurious findings. By reducing a disease profile to a subset of differentially expressed proteins and determining functional over-representation, one can often make a reasonable first-pass assessment as to what might be happening in disease. Integrating mRNA expression patterns together with prior knowledge of protein-protein interaction networks and biological pathway information goes a step further, providing clues into the core processes that are aberrant in the disease state, and indicating which cellular functions are activated or repressed as a maladaptive pathophysiological response. This multi-step framework allows one to hypothesize as to possible cause and effect of pathology, and highlights potentially instructive pathways or sub-networks for subsequent experimental validation. Indeed, efficiently exploiting data regarding the myriad of physical and genetic interactions among expressed gene products, in parallel with the systematic sampling of genetic variation among diverse human populations, promises to revolutionize our current understanding of disease action at a deeper molecular level. Copyright © 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Identification of an FHL1 protein complex containing gamma-actin and non-muscle myosin IIB by analysis of protein-protein interactions.

    Directory of Open Access Journals (Sweden)

    Lili Wang

    Full Text Available FHL1 is multifunctional and serves as a modular protein binding interface to mediate protein-protein interactions. In skeletal muscle, FHL1 is involved in sarcomere assembly, differentiation, growth, and biomechanical stress. Muscle abnormalities may play a major role in congenital clubfoot (CCF deformity during fetal development. Thus, identifying the interactions of FHL1 could provide important new insights into its functional role in both skeletal muscle development and CCF pathogenesis. Using proteins derived from rat L6GNR4 myoblastocytes, we detected FHL1 interacting proteins by immunoprecipitation. Samples were analyzed by liquid chromatography mass spectrometry (LC-MS. Dynamic gene expression of FHL1 was studied. Additionally, the expression of the possible interacting proteins gamma-actin and non-muscle myosin IIB, which were isolated from the lower limbs of E14, E15, E17, E18, E20 rat embryos or from adult skeletal muscle was analyzed. Potential interacting proteins isolated from E17 lower limbs were verified by immunoprecipitation, and co-localization in adult gastrocnemius muscle was visualized by fluorescence microscopy. FHL1 expression was associated with skeletal muscle differentiation. E17 was found to be the critical time-point for skeletal muscle differentiation in the lower limbs of rat embryos. We also identified gamma-actin and non-muscle myosin IIB as potential binding partners of FHL1, and both were expressed in adult skeletal muscle. We then demonstrated that FHL1 exists as part of a complex, which binds gamma-actin and non-muscle myosin IIB.

  8. QCD : the theory of strong interactions Exhibition LEPFest 2000

    CERN Multimedia

    2000-01-01

    The theory of strong interactions,Quantum Chromodynamics (QCD),predicts that the strong interac- tion is transmitted by the exchange of particles called glu- ons.Unlike the messengers of electromagnetism -pho- tons,which are electrically neutral -gluons carry a strong charge associated with the interaction they mediate. QCD predicts that the strength of the interaction between quarks and gluons becomes weaker at higher energies.LEP has measured the evolution of the strong coupling constant up to energies of 200 GeV and has confirmed this prediction.

  9. Interaction of liposomal formulations of meta-tetra(hydroxyphenyl)chlorin (temoporfin) with serum proteins: protein binding and liposome destruction.

    Science.gov (United States)

    Reshetov, Vadzim; Zorin, Vladimir; Siupa, Agnieszka; D'Hallewin, Marie-Ange; Guillemin, François; Bezdetnaya, Lina

    2012-01-01

    mTHPC is a non polar photosensitizer used in photodynamic therapy. To improve its solubility and pharmacokinetic properties, liposomes were proposed as drug carriers. Binding of liposomal mTHPC to serum proteins and stability of drug carriers in serum are of major importance for PDT efficacy; however, neither was reported before. We studied drug binding to human serum proteins using size-exclusion chromatography. Liposomes destruction in human serum was measured by nanoparticle tracking analysis (NTA). Inclusion of mTHPC into conventional (Foslip(®)) and PEGylated (Fospeg(®)) liposomes does not affect equilibrium serum protein binding compared with solvent-based mTHPC. At short incubation times the redistribution of mTHPC from Foslip(®) and Fospeg(®) proceeds by both drug release and liposomes destruction. At longer incubation times, the drug redistributes only by release. The release of mTHPC from PEGylated vesicles is delayed compared with conventional liposomes, alongside with greatly decreased liposomes destruction. Thus, for long-circulation times the pharmacokinetic behavior of Fospeg(®) could be influenced by a combination of protein- and liposome-bound drug. The study highlights the modes of interaction of photosensitizer-loaded nanovesicles in serum to predict optimal drug delivery and behavior in vivo in preclinical models, as well as the novel application of NTA to assess the destruction of liposomes. © 2012 Wiley Periodicals, Inc. Photochemistry and Photobiology © 2012 The American Society of Photobiology.

  10. The mitosis-regulating and protein-protein interaction activities of astrin are controlled by aurora-A-induced phosphorylation.

    Science.gov (United States)

    Chiu, Shao-Chih; Chen, Jo-Mei Maureen; Wei, Tong-You Wade; Cheng, Tai-Shan; Wang, Ya-Hui Candice; Ku, Chia-Feng; Lian, Chiao-Hsuan; Liu, Chun-Chih Jared; Kuo, Yi-Chun; Yu, Chang-Tze Ricky

    2014-09-01

    Cells display dramatic morphological changes in mitosis, where numerous factors form regulatory networks to orchestrate the complicated process, resulting in extreme fidelity of the segregation of duplicated chromosomes into two daughter cells. Astrin regulates several aspects of mitosis, such as maintaining the cohesion of sister chromatids by inactivating Separase and stabilizing spindle, aligning and segregating chromosomes, and silencing spindle assembly checkpoint by interacting with Src kinase-associated phosphoprotein (SKAP) and cytoplasmic linker-associated protein-1α (CLASP-1α). To understand how Astrin is regulated in mitosis, we report here that Astrin acts as a mitotic phosphoprotein, and Aurora-A phosphorylates Astrin at Ser(115). The phosphorylation-deficient mutant Astrin S115A abnormally activates spindle assembly checkpoint and delays mitosis progression, decreases spindle stability, and induces chromosome misalignment. Mechanistic analyses reveal that Astrin phosphorylation mimicking mutant S115D, instead of S115A, binds and induces ubiquitination and degradation of securin, which sequentially activates Separase, an enzyme required for the separation of sister chromatids. Moreover, S115A fails to bind mitosis regulators, including SKAP and CLASP-1α, which results in the mitotic defects observed in Astrin S115A-transfected cells. In conclusion, Aurora-A phosphorylates Astrin and guides the binding of Astrin to its cellular partners, which ensures proper progression of mitosis. Copyright © 2014 the American Physiological Society.

  11. An Integrative Analysis of Preeclampsia Based on the Construction of an Extended Composite Network Featuring Protein-Protein Physical Interactions and Transcriptional Relationships.

    Directory of Open Access Journals (Sweden)

    Daniel Vaiman

    Full Text Available Preeclampsia (PE is a pregnancy disorder defined by hypertension and proteinuria. This disease remains a major cause of maternal and fetal morbidity and mortality. Defective placentation is generally described as being at the root of the disease. The characterization of the transcriptome signature of the preeclamptic placenta has allowed to identify differentially expressed genes (DEGs. However, we still lack a detailed knowledge on how these DEGs impact the function of the placenta. The tools of network biology offer a methodology to explore complex diseases at a systems level. In this study we performed a cross-platform meta-analysis of seven publically available gene expression datasets comparing non-pathological and preeclamptic placentas. Using the rank product algorithm we identified a total of 369 DEGs consistently modified in PE. The DEGs were used as seeds to build both an extended physical protein-protein interactions network and a transcription factors regulatory network. Topological and clustering analysis was conducted to analyze the connectivity properties of the networks. Finally both networks were merged into a composite network which presents an integrated view of the regulatory pathways involved in preeclampsia and the crosstalk between them. This network is a useful tool to explore the relationship between the DEGs and enable hypothesis generation for functional experimentation.

  12. 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

    Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated with dis......-cells. Our results provide novel insight to the mechanisms behind type 1 diabetes pathogenesis and, thus, may provide the basis for the design of novel treatment strategies.......Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated...... with 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...

  13. Comparative Analyses of the Relative Effects of Various Mutations in Major Histocompatibility Complex I-a Way to Predict Protein-Protein Interactions.

    Science.gov (United States)

    Ali, Ananya; Biswas, Ria; Bhattacharjee, Sanchari; Nath, Prabahan; Pan, Sumanjit; Bagchi, Angshuman

    2016-09-01

    Protein-protein interactions (PPIs) play pivotal roles in most of the biological processes. PPI dysfunctions are therefore associated with disease situations. Mutations often lead to PPI dysfunctions, but there are certain other types of mutations which do not cause any appreciable abnormalities. This second type of mutations is called polymorphic mutations. So far, there are many studies that deal with the identification of PPI sites, but clear-cut analyses of the involvements of mutations in PPI dysfunctions are few and far between. We therefore made an attempt to link the appearances of mutations and PPI disruptions. We used major histocompatibility complex as our reference protein complex. We analyzed the mutations leading to the disease amyloidosis and also the other mutations that do not lead to disease conditions. We computed various biophysical parameters like relative solvent accessibility to discriminate between the two different types of mutations. Our analyses for the first time came up with a plausible explanation for the effects of different types of mutations in disease development. Our future plans are to build tools to detect the effects of mutations in disease developments by disrupting the PPIs.

  14. Prioritizing Disease Candidate Proteins in Cardiomyopathy-Specific Protein-Protein Interaction Networks Based on “Guilt by Association” Analysis

    Science.gov (United States)

    He, Weiming; Li, Weiguo; Qu, Xiaoli; Liang, Binhua; Gao, Qianping; Feng, Chenchen; Jia, Xu; Lv, Yana; Zhang, Siya; Li, Xia

    2013-01-01

    The cardiomyopathies are a group of heart muscle diseases which can be inherited (familial). Identifying potential disease-related proteins is important to understand mechanisms of cardiomyopathies. Experimental identification of cardiomyophthies is costly and labour-intensive. In contrast, bioinformatics approach has a competitive advantage over experimental method. Based on “guilt by association” analysis, we prioritized candidate proteins involving in human cardiomyopathies. We first built weighted human cardiomyopathy-specific protein-protein interaction networks for three subtypes of cardiomyopathies using the known disease proteins from Online Mendelian Inheritance in Man as seeds. We then developed a method in prioritizing disease candidate proteins to rank candidate proteins in the network based on “guilt by association” analysis. It was found that most candidate proteins with high scores shared disease-related pathways with disease seed proteins. These top ranked candidate proteins were related with the corresponding disease subtypes, and were potential disease-related proteins. Cross-validation and comparison with other methods indicated that our approach could be used for the identification of potentially novel disease proteins, which may provide insights into cardiomyopathy-related mechanisms in a more comprehensive and integrated way. PMID:23940716

  15. 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.

  16. 2P2I HUNTER: a tool for filtering orthosteric protein-protein interaction modulators via a dedicated support vector machine.

    Science.gov (United States)

    Hamon, Véronique; Bourgeas, Raphael; Ducrot, Pierre; Theret, Isabelle; Xuereb, Laura; Basse, Marie Jeanne; Brunel, Jean Michel; Combes, Sebastien; Morelli, Xavier; Roche, Philippe

    2014-01-06

    Over the last 10 years, protein-protein interactions (PPIs) have shown increasing potential as new therapeutic targets. As a consequence, PPIs are today the most screened target class in high-throughput screening (HTS). The development of broad chemical libraries dedicated to these particular targets is essential; however, the chemical space associated with this 'high-hanging fruit' is still under debate. Here, we analyse the properties of 40 non-redundant small molecules present in the 2P2I database (http://2p2idb.cnrs-mrs.fr/) to define a general profile of orthosteric inhibitors and propose an original protocol to filter general screening libraries using a support vector machine (SVM) with 11 standard Dragon molecular descriptors. The filtering protocol has been validated using external datasets from PubChem BioAssay and results from in-house screening campaigns. This external blind validation demonstrated the ability of the SVM model to reduce the size of the filtered chemical library by eliminating up to 96% of the compounds as well as enhancing the proportion of active compounds by up to a factor of 8. We believe that the resulting chemical space identified in this paper will provide the scientific community with a concrete support to search for PPI inhibitors during HTS campaigns.

  17. Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model.

    Science.gov (United States)

    Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

    2016-10-06

    Comparative analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved functional network modules across different species. Such modules typically consist of orthologous proteins with conserved interactions, which can be exploited to computationally predict the modules through network comparison. In this work, we propose a novel probabilistic framework for comparing PPI networks and effectively predicting the correspondence between proteins, represented as network nodes, that belong to conserved functional modules across the given PPI networks. The basic idea is to estimate the steady-state network flow between nodes that belong to different PPI networks based on a Markov random walk model. The random walker is designed to make random moves to adjacent nodes within a PPI network as well as cross-network moves between potential orthologous nodes with high sequence similarity. Based on this Markov random walk model, we estimate the steady-state network flow - or the long-term relative frequency of the transitions that the random walker makes - between nodes in different PPI networks, which can be used as a probabilistic score measuring their potential correspondence. Subsequently, the estimated scores can be used for detecting orthologous proteins in conserved functional modules through network alignment. Through evaluations based on multiple real PPI networks, we demonstrate that the proposed scheme leads to improved alignment results that are biologically more meaningful at reduced computational cost, outperforming the current state-of-the-art algorithms. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/CUFID .

  18. PCVMZM: Using the Probabilistic Classification Vector Machines Model Combined with a Zernike Moments Descriptor to Predict Protein-Protein Interactions from Protein Sequences.

    Science.gov (United States)

    Wang, Yanbin; You, Zhuhong; Li, Xiao; Chen, Xing; Jiang, Tonghai; Zhang, Jingting

    2017-05-11

    Protein-protein interactions (PPIs) are essential for most living organisms' process. Thus, detecting PPIs is extremely important to understand the molecular mechanisms of biological systems. Although many PPIs data have been generated by high-throughput technologies for a variety of organisms, the whole interatom is still far from complete. In addition, the high-throughput technologies for detecting PPIs has some unavoidable defects, including time consumption, high cost, and high error rate. In recent years, with the development of machine learning, computational methods have been broadly used to predict PPIs, and can achieve good prediction rate. In this paper, we present here PCVMZM, a computational method based on a Probabilistic Classification Vector Machines (PCVM) model and Zernike moments (ZM) descriptor for predicting the PPIs from protein amino acids sequences. Specifically, a Zernike moments (ZM) descriptor is used to extract protein evolutionary information from Position-Specific Scoring Matrix (PSSM) generated by Position-Specific Iterated Basic Local Alignment Search Tool (PSI-BLAST). Then, PCVM classifier is used to infer the interactions among protein. When performed on PPIs datasets of Yeast and H. Pylori , the proposed method can achieve the average prediction accuracy of 94.48% and 91.25%, respectively. In order to further evaluate the performance of the proposed method, the state-of-the-art support vector machines (SVM) classifier is used and compares with the PCVM model. Experimental results on the Yeast dataset show that the performance of PCVM classifier is better than that of SVM classifier. The experimental results indicate that our proposed method is robust, powerful and feasible, which can be used as a helpful tool for proteomics research.

  19. Prioritization of potential drug targets against P. aeruginosa by core proteomic analysis using computational subtractive genomics and Protein-Protein interaction network.

    Science.gov (United States)

    Uddin, Reaz; Jamil, Faiza

    2018-03-08

    Pseudomonas aeruginosa is an opportunistic gram-negative bacterium that has the capability to acquire resistance under hostile conditions and become a threat worldwide. It is involved in nosocomial infections. In the current study, potential novel drug targets against P. aeruginosa have been identified using core proteomic analysis and Protein-Protein Interactions (PPIs) studies. The non-redundant reference proteome of 68 strains having complete genome and latest assembly version of P. aeruginosa were downloaded from ftp NCBI RefSeq server in October 2016. The standalone CD-HIT tool was used to cluster ortholog proteins (having >=80% amino acid identity) present in all strains. The pan-proteome was clustered in 12,380 Clusters of Orthologous Proteins (COPs). By using in-house shell scripts, 3252 common COPs were extracted out and designated as clusters of core proteome. The core proteome of PAO1 strain was selected by fetching PAO1's proteome from common COPs. As a result, 1212 proteins were shortlisted that are non-homologous to the human but essential for the survival of the pathogen. Among these 1212 proteins, 321 proteins are conserved hypothetical proteins. Considering their potential as drug target, those 321 hypothetical proteins were selected and their probable functions were characterized. Based on the druggability criteria, 18 proteins were shortlisted. The interacting partners were identified by investigating the PPIs network using STRING v10 database. Subsequently, 8 proteins were shortlisted as 'hub proteins' and proposed as potential novel drug targets against P. aeruginosa. The study is interesting for the scientific community working to identify novel drug targets against MDR pathogens particularly P. aeruginosa. Copyright © 2018 Elsevier Ltd. All rights reserved.

  20. Prospects for strong interaction physics at ISABELLE. [Seven papers

    Energy Technology Data Exchange (ETDEWEB)

    Sidhu, D P; Trueman, T L

    1977-01-01

    Seven papers are presented resulting from a conference intended to stimulate thinking about how ISABELLE could be used for studying strong interactions. A separate abstract was prepared for each paper for inclusion in DOE Energy Research Abstracts (ERA). (PMA)

  1. Strongly-Interacting Fermi Gases in Reduced Dimensions

    Science.gov (United States)

    2015-11-16

    superconductivity), nuclear physics (nuclear matter), high - energy physics (effective theories of the strong interactions ), astrophysics (compact stellar objects...strongly- interacting Fermi gases confined in a standing- wave CO2 laser trap. This trap produces a periodic quasi-two-dimensional pancake geometry...predictions of the phase diagram and high temperature superfluidity. Our recent measurements reveal that pairing energy and cloud profiles can be

  2. Quark imprisonment as the origin of strong interactions

    CERN Document Server

    Amati, Daniele

    1974-01-01

    A formal scheme is suggested in which the only dynamical ingredients are weak and electro-magnetic interactions with quarks and leptons treated on the same footing. Strong interactions are generated by the requirement that quarks do not appear physically. (7 refs).

  3. 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.

  4. Nitrogen regulation of protein-protein interactions and transcript levels of GlnK PII regulator and AmtB ammonium transporter homologs in Archaea.

    Science.gov (United States)

    Pedro-Roig, Laia; Lange, Christian; Bonete, María José; Soppa, Jörg; Maupin-Furlow, Julie

    2013-10-01

    Gene homologs of GlnK PII regulators and AmtB-type ammonium transporters are often paired on prokaryotic genomes, suggesting these proteins share an ancient functional relationship. Here, we demonstrate for the first time in Archaea that GlnK associates with AmtB in membrane fractions after ammonium shock, thus, providing a further insight into GlnK-AmtB as an ancient nitrogen sensor pair. For this work, Haloferax mediterranei was advanced for study through the generation of a pyrE2-based counterselection system that was used for targeted gene deletion and expression of Flag-tagged proteins from their native promoters. AmtB1-Flag was detected in membrane fractions of cells grown on nitrate and was found to coimmunoprecipitate with GlnK after ammonium shock. Thus, in analogy to bacteria, the archaeal GlnK PII may block the AmtB1 ammonium transporter under nitrogen-rich conditions. In addition to this regulated protein-protein interaction, the archaeal amtB-glnK gene pairs were found to be highly regulated by nitrogen availability with transcript levels high under conditions of nitrogen limitation and low during nitrogen excess. While transcript levels of glnK-amtB are similarly regulated by nitrogen availability in bacteria, transcriptional regulators of the bacterial glnK promoter including activation by the two-component signal transduction proteins NtrC (GlnG, NRI) and NtrB (GlnL, NRII) and sigma factor σ(N) (σ(54) ) are not conserved in archaea suggesting a novel mechanism of transcriptional control. © 2013 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

  5. Semicalssical quantization of interacting anyons in a strong magnetic field

    International Nuclear Information System (INIS)

    Levit, S.; Sivan, N.

    1992-01-01

    We represent a semiclassical theory of charged interacting anyons in strong magnetic fields. We apply this theory to a number of few anyons systems including two interacting anyons in the presence of an impurity and three interacting anyons. We discuss the dependence of their energy levels on the statistical parameter and find regions in which this dependence follows very different patterns. The semiclassical arguments allow to correlate these patterns with the change in the character of the classical motion of the system. (author)

  6. Mixtures of Strongly Interacting Bosons in Optical Lattices

    International Nuclear Information System (INIS)

    Buonsante, P.; Penna, V.; Giampaolo, S. M.; Illuminati, F.; Vezzani, A.

    2008-01-01

    We investigate the properties of strongly interacting heteronuclear boson-boson mixtures loaded in realistic optical lattices, with particular emphasis on the physics of interfaces. In particular, we numerically reproduce the recent experimental observation that the addition of a small fraction of 41 K induces a significant loss of coherence in 87 Rb, providing a simple explanation. We then investigate the robustness against the inhomogeneity typical of realistic experimental realizations of the glassy quantum emulsions recently predicted to occur in strongly interacting boson-boson mixtures on ideal homogeneous lattices

  7. Glassy states in fermionic systems with strong disorder and interactions

    Science.gov (United States)

    Schwab, David J.; Chakravarty, Sudip

    2009-03-01

    We study the competition between interactions and disorder in two dimensions. Whereas a noninteracting system is always Anderson localized by disorder in two dimensions, a pure system can develop a Mott gap for sufficiently strong interactions. Within a simple model, with short-ranged repulsive interactions, we show that, even in the limit of strong interaction, the Mott gap is completely washed out by disorder for an infinite system for dimensions D≤2 , leading to a glassy state. Moreover, the Mott insulator cannot maintain a broken symmetry in the presence of disorder. We then show that the probability of a nonzero gap as a function of system size falls onto a universal curve, reflecting the glassy dynamics. An analytic calculation is also presented in one dimension that provides further insight into the nature of slow dynamics.

  8. New results on strong-interaction effects in antiprotonic hydrogen

    CERN Document Server

    Gotta, D; Augsburger, M A; Borchert, G L; Castelli, C M; Chatellard, D; El-Khoury, P; Egger, J P; Gorke, H; Hauser, P R; Indelicato, P J; Kirch, K; Lenz, S; Nelms, N; Rashid, K; Schult, O W B; Siems, T; Simons, L M

    1999-01-01

    Lyman and Balmer transitions of antiprotonic hydrogen and deuterium have been measured at the low-energy antiproton ring LEAR at CERN in order to determine the strong interaction effects. The X-rays were detected using charge-coupled devices (CCDs) and a reflection type crystal spectrometer. The results of the measurements support the meson-exchange models describing the medium and long range part of the nucleon-antinucleon interaction. (33 refs).

  9. New results on strong-interaction effects in antiprotonic hydrogen

    International Nuclear Information System (INIS)

    Anagnostopoulos, D. F.; Augsburger, M.; Borchert, G.; Castelli, C.; Chatellard, D.; El-Khoury, P.; Egger, J.-P.; Gorke, H.; Gotta, D.; Hauser, P.; Indelicato, P.; Kirch, K.; Lenz, S.; Nelms, N.; Rashid, K.; Schult, O. W. B.; Siems, Th.; Simons, L. M.

    1999-01-01

    Lyman and Balmer transitions of antiprotonic hydrogen and deuterium have been measured at the Low-Energy Antiproton Ring LEAR at CERN in order to determine the strong interaction effects. The X-rays were detected using Charge-Coupled Devices (CCDs) and a reflection type crystal spectrometer. The results of the measurements support the meson-exchange models describing the medium and long range part of the nucleon-antinucleon interaction

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

    Science.gov (United States)

    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; Leaman, Robert; Gonzalez, Graciela; Matos, Sergio; Kim, Sun; Wilbur, W John; Rocha, Luis; Shatkay, Hagit; Tendulkar, Ashish V; Agarwal, Shashank; Liu, Feifan; Wang, Xinglong; Rak, Rafal; Noto, Keith; Elkan, Charles; Lu, Zhiyong; Dogan, Rezarta Islamaj; Fontaine, Jean-Fred; Andrade-Navarro, Miguel A; Valencia, Alfonso

    2011-10-03

    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 interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them. A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthew's Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89% and the best AUC iP/R was 68%. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were evaluated by comparing

  11. Strong light-matter interaction in graphene - Invited talk

    DEFF Research Database (Denmark)

    Xiao, Sanshui

    of graphene with noble-metal nanostructures is currently being explored for strong light-graphene interaction. We introduce a novel hybrid graphene-metal system for studying light-matter interactions with gold-void nanostructures exhibiting resonances in the visible range[1]. The hybrid system is further......Graphene has attracted lots of attention due to its remarkable electronic and optical properties, thus providing great promise in photonics and optoelectronics. However, the performance of these devices is generally limited by the weak light-matter interaction in graphene. The combination...

  12. Discriminative deep inelastic tests of strong interaction field theories

    International Nuclear Information System (INIS)

    Glueck, M.; Reya, E.

    1979-02-01

    It is demonstrated that recent measurements of ∫ 0 1 F 2 (x, Q 2 )dx eliminate already all strong interaction field theories except QCD. A detailed study of scaling violations of F 2 (x, Q 2 ) in QCD shows their insensitivity to the gluon content of the hadron at presently measured values of Q 2 . (orig.) [de

  13. Strongly interacting mesoscopic systems of anyons in one dimension

    DEFF Research Database (Denmark)

    Zinner, N. T.

    2015-01-01

    Using the fractional statistical properties of so-called anyonic particles, we present exact solutions for up to six strongly interacting particles in one-dimensional confinement that interpolate the usual bosonic and fermionic limits. Specifically, we consider two-component mixtures of anyons...

  14. Interplay of Anderson localization and strong interaction in disordered systems

    Energy Technology Data Exchange (ETDEWEB)

    Henseler, Peter

    2010-01-15

    We study the interplay of disorder localization and strong local interactions within the Anderson-Hubbard model. Taking into account local Mott-Hubbard physics and static screening of the disorder potential, the system is mapped onto an effective single-particle Anderson model, which is studied within the self-consistent theory of electron localization. For fermions, we find rich nonmonotonic behavior of the localization length {xi}, particularly in two-dimensional systems, including an interaction-induced exponential enhancement of {xi} for small and intermediate disorders and a strong reduction of {xi} due to hopping suppression by strong interactions. In three dimensions, we identify for half filling a Mott-Hubbard-assisted Anderson localized phase existing between the metallic and the Mott-Hubbard-gapped phases. For small U there is re-entrant behavior from the Anderson localized phase to the metallic phase. For bosons, the unrestricted particle occupation number per lattice site yields a monotonic enhancement of {xi} as a function of decreasing interaction, which we assume to persist until the superfluid Bose-Einstein condensate phase is entered. Besides, we study cold atomic gases expanding, by a diffusion process, in a weak random potential. We show that the density-density correlation function of the expanding gas is strongly affected by disorder and we estimate the typical size of a speckle spot, i.e., a region of enhanced or depleted density. Both a Fermi gas and a Bose-Einstein condensate (in a mean-field approach) are considered. (orig.)

  15. Interplay of Anderson localization and strong interaction in disordered systems

    International Nuclear Information System (INIS)

    Henseler, Peter

    2010-01-01

    We study the interplay of disorder localization and strong local interactions within the Anderson-Hubbard model. Taking into account local Mott-Hubbard physics and static screening of the disorder potential, the system is mapped onto an effective single-particle Anderson model, which is studied within the self-consistent theory of electron localization. For fermions, we find rich nonmonotonic behavior of the localization length ξ, particularly in two-dimensional systems, including an interaction-induced exponential enhancement of ξ for small and intermediate disorders and a strong reduction of ξ due to hopping suppression by strong interactions. In three dimensions, we identify for half filling a Mott-Hubbard-assisted Anderson localized phase existing between the metallic and the Mott-Hubbard-gapped phases. For small U there is re-entrant behavior from the Anderson localized phase to the metallic phase. For bosons, the unrestricted particle occupation number per lattice site yields a monotonic enhancement of ξ as a function of decreasing interaction, which we assume to persist until the superfluid Bose-Einstein condensate phase is entered. Besides, we study cold atomic gases expanding, by a diffusion process, in a weak random potential. We show that the density-density correlation function of the expanding gas is strongly affected by disorder and we estimate the typical size of a speckle spot, i.e., a region of enhanced or depleted density. Both a Fermi gas and a Bose-Einstein condensate (in a mean-field approach) are considered. (orig.)

  16. A systematic study of the strong interaction with PANDA

    NARCIS (Netherlands)

    Messchendorp, J. G.; Hosaka, A; Khemchandani, K; Nagahiro, H; Nawa, K

    2011-01-01

    The theory of Quantum Chromo Dynamics (QCD) reproduces the strong interaction at distances much shorter than the size of the nucleon. At larger distance scales, the generation of hadron masses and confinement cannot yet be derived from first principles on basis of QCD. The PANDA experiment at FAIR

  17. Measurement of strong interaction parameters in antiprotonic hydrogen and deuterium

    CERN Document Server

    Augsburger, M A; Borchert, G L; Chatellard, D; Egger, J P; El-Khoury, P; Gorke, H; Gotta, D; Hauser, P R; Indelicato, P J; Kirch, K; Lenz, S; Siems, T; Simons, L M

    1999-01-01

    In the PS207 experiment at CERN, X-rays from antiprotonic hydrogen and deuterium have been measured at low pressure. The strong interaction shift and the broadening of the K/sub alpha / transition in antiprotonic hydrogen were $9 determined. Evidence was found for the individual hyperfine components of the protonium ground state. (7 refs).

  18. Emergence of junction dynamics in a strongly interacting Bose mixture

    DEFF Research Database (Denmark)

    Barfknecht, Rafael Emilio; Foerster, Angela; Zinner, Nikolaj Thomas

    We study the dynamics of a one-dimensional system composed of a bosonic background and one impurity in single- and double-well trapping geometries. In the limit of strong interactions, this system can be modeled by a spin chain where the exchange coefficients are determined by the geometry of the...

  19. Symmetry-protected collisions between strongly interacting photons.

    Science.gov (United States)

    Thompson, Jeff D; Nicholson, Travis L; Liang, Qi-Yu; Cantu, Sergio H; Venkatramani, Aditya V; Choi, Soonwon; Fedorov, Ilya A; Viscor, Daniel; Pohl, Thomas; Lukin, Mikhail D; Vuletić, Vladan

    2017-02-09

    Realizing robust quantum phenomena in strongly interacting systems is one of the central challenges in modern physical science. Approaches ranging from topological protection to quantum error correction are currently being explored across many different experimental platforms, including electrons in condensed-matter systems, trapped atoms and photons. Although photon-photon interactions are typically negligible in conventional optical media, strong interactions between individual photons have recently been engineered in several systems. Here, using coherent coupling between light and Rydberg excitations in an ultracold atomic gas, we demonstrate a controlled and coherent exchange collision between two photons that is accompanied by a π/2 phase shift. The effect is robust in that the value of the phase shift is determined by the interaction symmetry rather than the precise experimental parameters, and in that it occurs under conditions where photon absorption is minimal. The measured phase shift of 0.48(3)π is in excellent agreement with a theoretical model. These observations open a route to realizing robust single-photon switches and all-optical quantum logic gates, and to exploring novel quantum many-body phenomena with strongly interacting photons.

  20. 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

    the 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...

  1. Interaction between holo transferrin and HSA-PPIX complex in the presence of lomefloxacin: An evaluation of PPIX aggregation in protein-protein interactions

    Science.gov (United States)

    Sattar, Zohreh; Iranfar, Hediye; Asoodeh, Ahmad; Saberi, Mohammad Reza; Mazhari, Mahboobeh; Chamani, Jamshidkhan

    2012-11-01

    Human serum albumin (HSA) and holo transferrin (TF) are two serum carrier proteins that are able to interact with each other, thereby altering their binding behavior toward their ligands. During the course of this study, the interaction between HSA-PPIX and TF, in the presence and absence of lomefloxacin (LMF), was for the first time investigated using different spectroscopic and molecular modeling techniques. Fluorescence spectroscopy experiments were performed in order to study conformational changes of proteins. The RLS technique was utilized to investigate the effect of LMF on J-aggregation of PPIX, which is the first report of its kind. Our findings present clear-cut evidence for the alteration of interactions between HSA and TF in the presence of PPIX and changes in drug-binding to HSA and HSA-PPIX complex upon interaction with TF. Moreover, molecular modeling studies suggested that the binding site for LMF became switched in the presence of PPIX, and that LMF bound to the site IIA of HSA. The obtained results should give new insight into research in this field and may cast some light on the dynamics of drugs in biological systems.

  2. Roles of residues in the interface of transient protein-protein complexes before complexation

    Science.gov (United States)

    Swapna, Lakshmipuram S.; Bhaskara, Ramachandra M.; Sharma, Jyoti; Srinivasan, Narayanaswamy

    2012-01-01

    Transient protein-protein interactions play crucial roles in all facets of cellular physiology. Here, using an analysis on known 3-D structures of transient protein-protein complexes, their corresponding uncomplexed forms and energy calculations we seek to understand the roles of protein-protein interfacial residues in the unbound forms. We show that there are conformationally near invariant and evolutionarily conserved interfacial residues which are rigid and they account for ∼65% of the core interface. Interestingly, some of these residues contribute significantly to the stabilization of the interface structure in the uncomplexed form. Such residues have strong energetic basis to perform dual roles of stabilizing the structure of the uncomplexed form as well as the complex once formed while they maintain their rigid nature throughout. This feature is evolutionarily well conserved at both the structural and sequence levels. We believe this analysis has general bearing in the prediction of interfaces and understanding molecular recognition. PMID:22451863

  3. Finding strongly interacting symmetry breaking at the SSC

    International Nuclear Information System (INIS)

    Golden, M.

    1989-02-01

    Pairs of gauge bosons, W and Z, are a probe of the electroweak symmetry-breaking sector, since the numbers of two gauge boson events are much larger in strongly coupled models than weak. The doubly charged channels W + W + and W/sup /minus//W/sup/minus// are cleanest, since they do not suffer from q/bar q/ or gg fusion backgrounds. The like-charged gauge boson events are observable only if the symmetry breaking sector is strongly interacting. 19 refs., 4 figs., 2 tabs

  4. 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

  5. SpirPro: A Spirulina proteome database and web-based tools for the analysis of protein-protein interactions at the metabolic level in Spirulina (Arthrospira) platensis C1.

    Science.gov (United States)

    Senachak, Jittisak; Cheevadhanarak, Supapon; Hongsthong, Apiradee

    2015-07-29

    Spirulina (Arthrospira) platensis is the only cyanobacterium that in addition to being studied at the molecular level and subjected to gene manipulation, can also be mass cultivated in outdoor ponds for commercial use as a food supplement. Thus, encountering environmental changes, including temperature stresses, is common during the mass production of Spirulina. The use of cyanobacteria as an experimental platform, especially for photosynthetic gene manipulation in plants and bacteria, is becoming increasingly important. Understanding the mechanisms and protein-protein interaction networks that underlie low- and high-temperature responses is relevant to Spirulina mass production. To accomplish this goal, high-throughput techniques such as OMICs analyses are used. Thus, large datasets must be collected, managed and subjected to information extraction. Therefore, databases including (i) proteomic analysis and protein-protein interaction (PPI) data and (ii) domain/motif visualization tools are required for potential use in temperature response models for plant chloroplasts and photosynthetic bacteria. A web-based repository was developed including an embedded database, SpirPro, and tools for network visualization. Proteome data were analyzed integrated with protein-protein interactions and/or metabolic pathways from KEGG. The repository provides various information, ranging from raw data (2D-gel images) to associated results, such as data from interaction and/or pathway analyses. This integration allows in silico analyses of protein-protein interactions affected at the metabolic level and, particularly, analyses of interactions between and within the affected metabolic pathways under temperature stresses for comparative proteomic analysis. The developed tool, which is coded in HTML with CSS/JavaScript and depicted in Scalable Vector Graphics (SVG), is designed for interactive analysis and exploration of the constructed network. SpirPro is publicly available on the web

  6. On the strong crack-microcrack interaction problem

    Science.gov (United States)

    Gorelik, M.; Chudnovsky, A.

    1992-07-01

    The problem of the crack-microcrack interaction is examined with special attention given to the iterative procedure described by Chudnovsky and Kachanov (1983), Chudnovsky et al. (1984), and Horii and Nemat-Nasser (1983), which yields erroneous results as the crack tips become closer (i.e., for strong crack interaction). To understand the source of error, the traction distributions along the microcrack line on the n-th step of iteration representing the exact and asymptotic stress fields are compared. It is shown that the asymptotic solution gives a gross overestimation of the actual traction.

  7. Ruling out a strongly interacting standard Higgs model

    International Nuclear Information System (INIS)

    Riesselmann, K.; Willenbrock, S.

    1997-01-01

    Previous work has suggested that perturbation theory is unreliable for Higgs- and Goldstone-boson scattering, at energies above the Higgs-boson mass, for relatively small values of the Higgs quartic coupling λ(μ). By performing a summation of nonlogarithmic terms, we show that perturbation theory is in fact reliable up to relatively large coupling. This eliminates the possibility of a strongly interacting standard Higgs model at energies above the Higgs-boson mass, complementing earlier studies which excluded strong interactions at energies near the Higgs-boson mass. The summation can be formulated in terms of an appropriate scale in the running coupling, μ=√(s)/e∼√(s)/2.7, so it can be incorporated easily in renormalization-group-improved tree-level amplitudes as well as higher-order calculations. copyright 1996 The American Physical Society

  8. A connection between the strong and weak interactions

    International Nuclear Information System (INIS)

    Treiman, S.B.

    1989-01-01

    By studying weak scattering reactions (such as pion-nucleon scattering), the author and his colleague Marvin L Goldberger became renowned in the 1950s for work on dispersion relations. As a result of their collaboration a remarkable and unexpected connection was found between strong and weak interaction quantities. Agreement with experiment was good. Work by others found the same result, but via the partially conserved axial reactor current relation between the axial current divergence and the canonical pion field. (UK)

  9. Thermodynamics of strong-interaction matter from Lattice QCD

    OpenAIRE

    Ding, Heng-Tong; Karsch, Frithjof; Mukherjee, Swagato

    2015-01-01

    We review results from lattice QCD calculations on the thermodynamics of strong-interaction matter with emphasis on input these calculations can provide to the exploration of the phase diagram and properties of hot and dense matter created in heavy ion experiments. This review is organized as follows: 1) Introduction, 2) QCD thermodynamics on the lattice, 3) QCD phase diagram at high temperature, 4) Bulk thermodynamics, 5) Fluctuations of conserved charges, 6) Transport properties, 7) Open he...

  10. Development of a system for the study of protein-protein interactions in planta: characterization of a TATA-box binding protein complex in Oryza sativa.

    Science.gov (United States)

    Zhong, Jingping; Haynes, Paul A; Zhang, Shiping; Yang, Xinping; Andon, Nancy L; Eckert, Donna; Yates, John R; Wang, Xun; Budworth, Paul

    2003-01-01

    We describe a simple, rapid method for protein complex purification in planta. Using a biotin peptide as an affinity tag with TATA-box binding protein (TBP), 86 unique proteins present in the purified complex were identified by tandem mass spectrometry. We identified proteins known to be associated with TBP, and many other proteins involved in pre-mRNA processing and chromatin remodeling. The identification of these novel protein-protein associations will upon further investigations provide new insights into the mechanisms of mRNA transcription and pre-mRNA processing.

  11. The Electron-Phonon Interaction in Strongly Correlated Systems

    International Nuclear Information System (INIS)

    Castellani, C.; Grilli, M.

    1995-01-01

    We analyze the effect of strong electron-electron repulsion on the electron-phonon interaction from a Fermi-liquid point of view and show that the electron-electron interaction is responsible for vertex corrections, which generically lead to a strong suppression of the electron-phonon coupling in the v F q/ω >>1 region, while such effect is not present when v F q/ω F is the Fermi velocity and q and ω are the transferred momentum and frequency respectively. In particular the e-ph scattering is suppressed in transport properties which are dominated by low-energy-high-momentum processes. On the other hand, analyzing the stability criterion for the compressibility, which involves the effective interactions in the dynamical limit, we show that a sizable electron-phonon interaction can push the system towards a phase-separation instability. Finally a detailed analysis of these ideas is carried out using a slave-boson approach for the infinite-U three-band Hubbard model in the presence of a coupling between the local hole density and a dispersionless optical phonon. (author)

  12. Nonperturbative Dynamics of Strong Interactions from Gauge/Gravity Duality

    Energy Technology Data Exchange (ETDEWEB)

    Grigoryan, Hovhannes [Louisiana State Univ., Baton Rouge, LA (United States)

    2008-08-01

    This thesis studies important dynamical observables of strong interactions such as form factors. It is known that Quantum Chromodynamics (QCD) is a theory which describes strong interactions. For large energies, one can apply perturbative techniques to solve some of the QCD problems. However, for low energies QCD enters into the nonperturbative regime, where di erent analytical or numerical tools have to be applied to solve problems of strong interactions. The holographic dual model of QCD is such an analytical tool that allows one to solve some nonperturbative QCD problems by translating them into a dual ve-dimensional theory de ned on some warped Anti de Sitter (AdS) background. Working within the framework of the holographic dual model of QCD, we develop a formalism to calculate form factors and wave functions of vector mesons and pions. As a result, we provide predictions of the electric radius, the magnetic and quadrupole moments which can be directly veri ed in lattice calculations or even experimentally. To nd the anomalous pion form factor, we propose an extension of the holographic model by including the Chern-Simons term required to reproduce the chiral anomaly of QCD. This allows us to nd the slope of the form factor with one real and one slightly o -shell photon which appeared to be close to the experimental ndings. We also analyze the limit of large virtualities (when the photon is far o -shell) and establish that predictions of the holographic model analytically coincide with those of perturbative QCD with asymptotic pion distribution amplitude. We also study the e ects of higher dimensional terms in the AdS/QCD model and show that these terms improve the holographic description towards a more realistic scenario. We show this by calculating corrections to the vector meson form factors and corrections to the observables such as electric radii, magnetic and quadrupole moments.

  13. The hadronic standard model for strong and electroweak interactions

    Energy Technology Data Exchange (ETDEWEB)

    Raczka, R. [Soltan Inst. for Nuclear Studies, Otwock-Swierk (Poland)

    1993-12-31

    We propose a new model for strong and electro-weak interactions. First, we review various QCD predictions for hadron-hadron and lepton-hadron processes. We indicate that the present formulation of strong interactions in the frame work of Quantum Chromodynamics encounters serious conceptual and numerical difficulties in a reliable description of hadron-hadron and lepton-hadron interactions. Next we propose to replace the strong sector of Standard Model based on unobserved quarks and gluons by the strong sector based on the set of the observed baryons and mesons determined by the spontaneously broken SU(6) gauge field theory model. We analyse various properties of this model such as asymptotic freedom, Reggeization of gauge bosons and fundamental fermions, baryon-baryon and meson-baryon high energy scattering, generation of {Lambda}-polarization in inclusive processes and others. Finally we extend this model by electro-weak sector. We demonstrate a remarkable lepton and hadron anomaly cancellation and we analyse a series of important lepton-hadron and hadron-hadron processes such as e{sup +} + e{sup -} {yields} hadrons, e{sup +} + e{sup -} {yields} W{sup +} + W{sup -}, e{sup +} + e{sup -} {yields} p + anti-p, e + p {yields} e + p and p + anti-p {yields} p + anti-p processes. We obtained a series of interesting new predictions in this model especially for processes with polarized particles. We estimated the value of the strong coupling constant {alpha}(M{sub z}) and we predicted the top baryon mass M{sub {Lambda}{sub t}} {approx_equal} 240 GeV. Since in our model the proton, neutron, {Lambda}-particles, vector mesons like {rho}, {omega}, {phi}, J/{psi} ect. and leptons are elementary most of experimentally analysed lepton-hadron and hadron-hadron processes in LEP1, LEP2, LEAR, HERA, HERMES, LHC and SSC experiments may be relatively easily analysed in our model. (author). 252 refs, 65 figs, 1 tab.

  14. Emergence of junction dynamics in a strongly interacting Bose mixture

    DEFF Research Database (Denmark)

    Barfknecht, Rafael Emilio; Foerster, Angela; Zinner, Nikolaj Thomas

    We study the dynamics of a one-dimensional system composed of a bosonic background and one impurity in single- and double-well trapping geometries. In the limit of strong interactions, this system can be modeled by a spin chain where the exchange coefficients are determined by the geometry...... of the trap. We observe non-trivial dynamics when the repulsion between the impurity and the background is dominant. In this regime, the system exhibits oscillations that resemble the dynamics of a Josephson junction. Furthermore, the double-well geometry allows for an enhancement in the tunneling as compared...

  15. Strongly modified plasmon-matter interaction with mesoscopic quantum emitters

    DEFF Research Database (Denmark)

    Andersen, Mads Lykke; Stobbe, Søren; Søndberg Sørensen, Anders

    2011-01-01

    Semiconductor quantum dots (QDs) provide useful means to couple light and matter in applications such as light-harvesting1, 2 and all-solid-state quantum information processing3, 4. This coupling can be increased by placing QDs in nanostructured optical environments such as photonic crystals...... or metallic nanostructures that enable strong confinement of light and thereby enhance the light–matter interaction. It has thus far been assumed that QDs can be described in the same way as atomic photon emitters—as point sources with wavefunctions whose spatial extent can be disregarded. Here we demonstrate...

  16. Strongly interacting atom lasers in three-dimensional optical lattices.

    Science.gov (United States)

    Hen, Itay; Rigol, Marcos

    2010-10-29

    We show that the dynamical melting of a Mott insulator in a three-dimensional lattice leads to condensation at nonzero momenta, a phenomenon that can be used to generate strongly interacting atom lasers in optical lattices. For infinite on-site repulsion, the case considered here, the momenta at which bosons condense are determined analytically and found to have a simple dependence on the hopping amplitudes. The occupation of the condensates is shown to scale linearly with the total number of atoms in the initial Mott insulator. Our results are obtained by using a Gutzwiller-type mean-field approach, gauged against exact-diagonalization solutions of small systems.

  17. Ising models of strongly coupled biological networks with multivariate interactions

    Science.gov (United States)

    Merchan, Lina; Nemenman, Ilya

    2013-03-01

    Biological networks consist of a large number of variables that can be coupled by complex multivariate interactions. However, several neuroscience and cell biology experiments have reported that observed statistics of network states can be approximated surprisingly well by maximum entropy models that constrain correlations only within pairs of variables. We would like to verify if this reduction in complexity results from intricacies of biological organization, or if it is a more general attribute of these networks. We generate random networks with p-spin (p > 2) interactions, with N spins and M interaction terms. The probability distribution of the network states is then calculated and approximated with a maximum entropy model based on constraining pairwise spin correlations. Depending on the M/N ratio and the strength of the interaction terms, we observe a transition where the pairwise approximation is very good to a region where it fails. This resembles the sat-unsat transition in constraint satisfaction problems. We argue that the pairwise model works when the number of highly probable states is small. We argue that many biological systems must operate in a strongly constrained regime, and hence we expect the pairwise approximation to be accurate for a wide class of problems. This research has been partially supported by the James S McDonnell Foundation grant No.220020321.

  18. Noise in strong laser-atom interactions: Phase telegraph noise

    International Nuclear Information System (INIS)

    Eberly, J.H.; Wodkiewicz, K.; Shore, B.W.

    1984-01-01

    We discuss strong laser-atom interactions that are subjected to jump-type (random telegraph) random-phase noise. Physically, the jumps may arise from laser fluctuations, from collisions of various kinds, or from other external forces. Our discussion is carried out in two stages. First, direct and partially heuristic calculations determine the laser spectrum and also give a third-order differential equation for the average inversion of a two-level atom on resonance. At this stage a number of general features of the interaction are able to be studied easily. The optical analog of motional narrowing, for example, is clearly predicted. Second, we show that the theory of generalized Poisson processes allows laser-atom interactions in the presence of random telegraph noise of all kinds (not only phase noise) to be treated systematically, by means of a master equation first used in the context of quantum optics by Burshtein. We use the Burshtein equation to obtain an exact expression for the two-level atom's steady-state resonance fluorescence spectrum, when the exciting laser exhibits phase telegraph noise. Some comparisons are made with results obtained from other noise models. Detailed treatments of the effects ofmly jumps, or as a model of finite laser bandwidth effects, in which the laser frequency exhibits random jumps. We show that these two types of frequency noise can be distinguished in light-scattering spectra. We also discuss examples which demonstrate both temporal and spectral motional narrowing, nonexponential correlations, and non-Lorentzian spectra. Its exact solubility in finite terms makes the frequency-telegraph noise model an attractive alternative to the white-noise Ornstein-Uhlenbeck frequency noise model which has been previously applied to laser-atom interactions

  19. Towards a unified gauge theory of gravitational and strong interactions

    International Nuclear Information System (INIS)

    Hehl, F.W.; Sijacki, D.

    1980-01-01

    The space-time properties of leptons and hadrons is studied and it is found necessary to extend general relativity to the gauge theory based on the four-dimensional affine group. This group translates and deforms the tetrads of the locally Minkowskian space-time. Its conserved currents, momentum, and hypermomentum, act as sources in the two field equations of gravity. A Lagrangian quadratic in torsion and curvature allows for the propagation of two independent gauge fields: translational e-gravity mediated by the tetrad coefficients, and deformational GAMMA-gravity mediated by the connection coefficients. For macroscopic matter e-gravity coincides with general relativity up to the post-Newtonian approximation of fourth order. For microscopic matter GAMMA-gravity represents a strong Yang-Mills type interaction. In the linear approximation, for a static source, a confinement potential is found. (author)

  20. Extreme states of matter in strong interaction physics an introduction

    CERN Document Server

    Satz, Helmut

    2018-01-01

    This book is a course-tested primer on the thermodynamics of strongly interacting matter – a profound and challenging area of both theoretical and experimental modern physics. Analytical and numerical studies of statistical quantum chromodynamics provide the main theoretical tool, while in experiments, high-energy nuclear collisions are the key for extensive laboratory investigations. As such, the field straddles statistical, particle and nuclear physics, both conceptually and in the methods of investigation used. The book addresses, above all, the many young scientists starting their scientific research in this field, providing them with a general, self-contained introduction that highlights the basic concepts and ideas and explains why we do what we do. Much of the book focuses on equilibrium thermodynamics: first it presents simplified phenomenological pictures, leading to critical behavior in hadronic matter and to a quark-hadron phase transition. This is followed by elements of finite temperature latti...

  1. Ion Motion in a Plasma Interacting with Strong Magnetic Fields

    International Nuclear Information System (INIS)

    Weingarten, A.; Grabowski, C.; Chakrabarti, N.; Maron, Y.; Fruchtmant, A.

    1999-01-01

    The interaction of a plasma with strong magnetic fields takes place in many laboratory experiments and astrophysical plasmas. Applying a strong magnetic field to the plasma may result in plasma displacement, magnetization, or the formation of instabilities. Important phenomena in plasma, such as the energy transport and the momentum balance, take a different form in each case. We study this interaction in a plasma that carries a short-duration (80-ns) current pulse, generating a magnetic field of up to 17 kG. The evolution of the magnetic field, plasma density, ion velocities, and electric fields are determined before and during the current pulse. The dependence of the plasma limiting current on the plasma density and composition are studied and compared to theoretical models based on the different phenomena. When the plasma collisionality is low, three typical velocities should be taken into consideration: the proton and heavier-ion Alfven velocities (v A p and v A h , respectively) and the EMHD magnetic-field penetration velocity into the plasma (v EMHD ). If both Alfven velocities are larger than v EMHD the plasma is pushed ahead of the magnetic piston and the magnetic field energy is dissipated into ion kinetic energy. If v EMHD is the largest of three velocities, the plasma become magnetized and the ions acquire a small axial momentum only. Different ion species may drift in different directions along the current lines. In this case, the magnetic field energy is probably dissipated into electron thermal energy. When vs > V EMHD > vi, as in the case of one of our experiments, ion mass separation occurs. The protons are pushed ahead of the piston while the heavier-ions become magnetized. Since the plasma electrons are unmagnetized they cannot cross the piston, and the heavy ions are probably charge-neutralized by electrons originating from the cathode that are 'born' magnetized

  2. Discovery of a Highly Potent, Cell-Permeable Macrocyclic Peptidomimetic (MM-589) Targeting the WD Repeat Domain 5 Protein (WDR5)-Mixed Lineage Leukemia (MLL) Protein-Protein Interaction.

    Science.gov (United States)

    Karatas, Hacer; Li, Yangbing; Liu, Liu; Ji, Jiao; Lee, Shirley; Chen, Yong; Yang, Jiuling; Huang, Liyue; Bernard, Denzil; Xu, Jing; Townsend, Elizabeth C; Cao, Fang; Ran, Xu; Li, Xiaoqin; Wen, Bo; Sun, Duxin; Stuckey, Jeanne A; Lei, Ming; Dou, Yali; Wang, Shaomeng

    2017-06-22

    We report herein the design, synthesis, and evaluation of macrocyclic peptidomimetics that bind to WD repeat domain 5 (WDR5) and block the WDR5-mixed lineage leukemia (MLL) protein-protein interaction. Compound 18 (MM-589) binds to WDR5 with an IC 50 value of 0.90 nM (K i value 40 times better than the previously reported compound MM-401. Cocrystal structures of 16 and 18 complexed with WDR5 provide structural basis for their high affinity binding to WDR5. Additionally, we have developed and optimized a new AlphaLISA-based MLL HMT functional assay to facilitate the functional evaluation of these designed compounds. Compound 18 represents the most potent inhibitor of the WDR5-MLL interaction reported to date, and further optimization of 18 may yield a new therapy for acute leukemia.

  3. Model of OSBP-Mediated Cholesterol Supply to Aichi Virus RNA Replication Sites Involving Protein-Protein Interactions among Viral Proteins, ACBD3, OSBP, VAP-A/B, and SAC1.

    Science.gov (United States)

    Ishikawa-Sasaki, Kumiko; Nagashima, Shigeo; Taniguchi, Koki; Sasaki, Jun

    2018-04-15

    Positive-strand RNA viruses, including picornaviruses, utilize cellular machinery for genome replication. Previously, we reported that each of the 2B, 2BC, 2C, 3A, and 3AB proteins of Aichi virus (AiV), a picornavirus, forms a complex with the Golgi apparatus protein ACBD3 and phosphatidylinositol 4-kinase IIIβ (PI4KB) at viral RNA replication sites (replication organelles [ROs]), enhancing PI4KB-dependent phosphatidylinositol 4-phosphate (PI4P) production. Here, we demonstrate AiV hijacking of the cellular cholesterol transport system involving oxysterol-binding protein (OSBP), a PI4P-binding cholesterol transfer protein. AiV RNA replication was inhibited by silencing cellular proteins known to be components of this pathway, OSBP, the ER membrane proteins VAPA and VAPB (VAP-A/B), the PI4P-phosphatase SAC1, and PI-transfer protein β. OSBP, VAP-A/B, and SAC1 were present at RNA replication sites. We also found various previously unknown interactions among the AiV proteins (2B, 2BC, 2C, 3A, and 3AB), ACBD3, OSBP, VAP-A/B, and SAC1, and the interactions were suggested to be involved in recruiting the component proteins to AiV ROs. Importantly, the OSBP-2B interaction enabled PI4P-independent recruitment of OSBP to AiV ROs, indicating preferential recruitment of OSBP among PI4P-binding proteins. Protein-protein interaction-based OSBP recruitment has not been reported for other picornaviruses. Cholesterol was accumulated at AiV ROs, and inhibition of OSBP-mediated cholesterol transfer impaired cholesterol accumulation and AiV RNA replication. Electron microscopy showed that AiV-induced vesicle-like structures were close to ER membranes. Altogether, we conclude that AiV directly recruits the cholesterol transport machinery through protein-protein interactions, resulting in formation of membrane contact sites between the ER and AiV ROs and cholesterol supply to the ROs. IMPORTANCE Positive-strand RNA viruses utilize host pathways to modulate the lipid composition of

  4. High-energy strong interactions: from `hard' to `soft'

    Science.gov (United States)

    Ryskin, M. G.; Martin, A. D.; Khoze, V. A.

    2011-04-01

    We discuss the qualitative features of the recent data on multiparticle production observed at the LHC. The tolerable agreement with Monte Carlos based on LO DGLAP evolution indicates that there is no qualitative difference between `hard' and `soft' interactions; and that a perturbative QCD approach may be extended into the soft domain. However, in order to describe the data, these Monte Carlos need an additional infrared cutoff k min with a value k min ˜2-3 GeV which is not small, and which increases with collider energy. Here we explain the physical origin of the large k min . Using an alternative model which matches the `soft' high-energy hadron interactions smoothly on to perturbative QCD at small x, we demonstrate that this effective cutoff k min is actually due to the strong absorption of low k t partons. The model embodies the main features of the BFKL approach, including the diffusion in transverse momenta, ln k t , and an intercept consistent with resummed next-to-leading log corrections. Moreover, the model uses a two-channel eikonal framework, and includes the contributions from the multi-Pomeron exchange diagrams, both non-enhanced and enhanced. The values of a small number of physically-motivated parameters are chosen to reproduce the available total, elastic and proton dissociation cross section (pre-LHC) data. Predictions are made for the LHC, and the relevance to ultra-high-energy cosmic rays is briefly discussed. The low x inclusive integrated gluon PDF, and the diffractive gluon PDF, are calculated in this framework, using the parameters which describe the high-energy pp and pbar{p} ` soft' data. Comparison with the PDFs obtained from the global parton analyses of deep inelastic and related hard scattering data and from diffractive deep inelastic data looks encouraging.

  5. Theoretical & Experimental Research in Weak, Electromagnetic & Strong Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Nandi, Satyanarayan [Oklahoma State Univ., Stillwater, OK (United States); Babu, Kaladi [Oklahoma State Univ., Stillwater, OK (United States); Rizatdinova, Flera [Oklahoma State Univ., Stillwater, OK (United States); Khanov, Alexander [Oklahoma State Univ., Stillwater, OK (United States); Haley, Joseph [Oklahoma State Univ., Stillwater, OK (United States)

    2015-09-17

    The conducted research spans a wide range of topics in the theoretical, experimental and phenomenological aspects of elementary particle interactions. Theory projects involve topics in both the energy frontier and the intensity frontier. The experimental research involves energy frontier with the ATLAS Collaboration at the Large Hadron Collider (LHC). In theoretical research, novel ideas going beyond the Standard Model with strong theoretical motivations were proposed, and their experimental tests at the LHC and forthcoming neutrino facilities were outlined. These efforts fall into the following broad categories: (i) TeV scale new physics models for LHC Run 2, including left-right symmetry and trinification symmetry, (ii) unification of elementary particles and forces, including the unification of gauge and Yukawa interactions, (iii) supersummetry and mechanisms of supersymmetry breaking, (iv) superworld without supersymmetry, (v) general models of extra dimensions, (vi) comparing signals of extra dimensions with those of supersymmetry, (vii) models with mirror quarks and mirror leptons at the TeV scale, (viii) models with singlet quarks and singlet Higgs and their implications for Higgs physics at the LHC, (ix) new models for the dark matter of the universe, (x) lepton flavor violation in Higgs decays, (xi) leptogenesis in radiative models of neutrino masses, (xii) light mediator models of non-standard neutrino interactions, (xiii) anomalous muon decay and short baseline neutrino anomalies, (xiv) baryogenesis linked to nucleon decay, and (xv) a new model for recently observed diboson resonance at the LHC and its other phenomenological implications. The experimental High Energy Physics group has been, and continues to be, a successful and productive contributor to the ATLAS experiment at the LHC. Members of the group performed search for gluinos decaying to stop and top quarks, new heavy gauge bosons decaying to top and bottom quarks, and vector-like quarks

  6. Peptide-microgel interactions in the strong coupling regime.

    Science.gov (United States)

    Hansson, Per; Bysell, Helena; Månsson, Ronja; Malmsten, Martin

    2012-09-06

    The interaction between lightly cross-linked poly(acrylic acid) microgels and oppositely charged peptides was investigated as a function of peptide length, charge density, pH, and salt concentration, with emphasis on the strong coupling regime at high charge contrast. By micromanipulator-assisted light microscopy, the equilibrium volume response of single microgel particles upon oligolysine and oligo(lysine/alanine) absorption could be monitored in a controlled fashion. Results show that microgel deswelling, caused by peptide binding and network neutralization, increases with peptide length (3 attraction between the network chains is described using an exponential force law, and the network elasticity by the inverse Langevin theory. The model was used to calculate the composition of microgels in contact with reservoir solutions of peptides and simple electrolytes. At high electrostatic coupling, the calculated swelling curves were found to display first-order phase transition behavior. The model was demonstrated to capture pH- and electrolyte-dependent microgel swelling, as well as effects of peptide length and charge density on microgel deswelling. The analysis demonstrated that the peptide charge (length), rather than the peptide charge density, determines microgel deswelling. Furthermore, a transition between continuous and discrete network collapse was identified, consistent with experimental results in the present investigations, as well as with results from the literature on microgel deswelling caused by multivalent cations.

  7. Evolution of the Telomere-Associated Protein POT1a in Arabidopsis thaliana Is Characterized by Positive Selection to Reinforce Protein-Protein Interaction.

    Science.gov (United States)

    Beilstein, Mark A; Renfrew, Kyle B; Song, Xiangyu; Shakirov, Eugene V; Zanis, Michael J; Shippen, Dorothy E

    2015-05-01

    Gene duplication is a major driving force in genome evolution. Here, we explore the nature and origin of the POT1 gene duplication in Arabidopsis thaliana. Protection of Telomeres (POT1) is a conserved multifunctional protein that modulates telomerase activity and its engagement with telomeres. Arabidopsis thaliana encodes two divergent POT1 paralogs termed AtPOT1a and AtPOT1b. AtPOT1a positively regulates telomerase activity, whereas AtPOT1b is proposed to negatively regulate telomerase and promote chromosome end protection. Phylogenetic analysis uncovered two independent POT1 duplication events in the plant kingdom, including one at the base of Brassicaceae. Tests for positive selection implemented in PAML revealed that the Brassicaceae POT1a lineage experienced positive selection postduplication and identified three amino acid residues with signatures of positive selection. A sensitive and quantitative genetic complementation assay was developed to assess POT1a function in A. thaliana. The assay showed that AtPOT1a is functionally distinct from single-copy POT1 genes in other plants. Moreover, for two of the sites with a strong signature of positive selection, substitutions that swap the amino acids in AtPOT1a for residues found in AtPOT1b dramatically compromised AtPOT1a function in vivo. In vitro-binding studies demonstrated that all three sites under positive selection specifically enhance the AtPOT1a interaction with CTC1, a core component of the highly conserved CST (CTC1/STN1/TEN1) telomere protein complex. Our results reveal a molecular mechanism for the role of these positively selected sites in AtPOT1a. The data also provide an important empirical example to refine theories of duplicate gene retention, as the outcome of positive selection here appears to be reinforcement of an ancestral function, rather than neofunctionalization. We propose that this outcome may not be unusual when the duplicated protein is a component of a multisubunit complex whose

  8. Effective Field Theories and Strong Interactions. Final Technical Report

    International Nuclear Information System (INIS)

    Fleming, Sean

    2011-01-01

    The framework of Effective Field Theories (EFTs) allows us to describe strong interactions in terms of degrees of freedom relevant to the energy regimes of interest, in the most general way consistent with the symmetries of QCD. Observables are expanded systematically in powers of M lo /M hi , where M lo (M hi ) denotes a low-(high-)energy scale. This organizational principle is referred to as 'power counting'. Terms of increasing powers in the expansion parameter are referred to as leading order (LO), next-to-leading order (NLO), etc. Details of the QCD dynamics not included explicitly are encoded in interaction parameters, or 'low-energy constants' (LECs), which can in principle be calculated from an explicit solution of QCD - for example via lattice simulations- but can also be determined directly from experimental data. QCD has an intrinsic scale M QCD ≅ 1 GeV, at which the QCD coupling constant α s (M QCD ) becomes large and the dynamics becomes non-perturbative. As a consequence M QCD sets the scale for the masses of most hadrons, such as the nucleon mass m N ≅ 940 MeV. EFTs can roughly be divided into two categories: those that can be matched onto QCD in perturbation theory, which we call high-energy EFTs, and those that cannot be matched perturbatively, which we call low-energy EFTs. In high-energy EFTs, M QCD typically sets the low-energy scale, and all the dynamics associated with this scale reside in matrix elements of EFT operators. These non-perturbative matrix elements are the LECs and are also referred to as long-distance contributions. Each matrix element is multiplied by a short-distance coefficient, which contains the dynamics from the high scale M hi . Since M hi >> M QCD , α s (M hi ) hi ∼ M Q , the heavy-quark mass, and in addition to M QCD there are low scales associated with the typical relative momentum ∼ M Q v and energy ∼ M Q v 2 of the heavy quarks. Depending on the sizes of M Q and the heavy-quark velocity v these scales can

  9. Strongly interacting matter at high densities with a soliton model

    Science.gov (United States)

    Johnson, Charles Webster

    1998-12-01

    One of the major goals of modern nuclear physics is to explore the phase diagram of strongly interacting matter. The study of these 'extreme' conditions is the primary motivation for the construction of the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory which will accelerate nuclei to a center of mass (c.m.) energy of about 200 GeV/nucleon. From a theoretical perspective, a test of quantum chromodynamics (QCD) requires the expansion of the conditions examined from one phase point to the entire phase diagram of strongly-interacting matter. In the present work we focus attention on what happens when the density is increased, at low excitation energies. Experimental results from the Brookhaven Alternating Gradient Synchrotron (AGS) indicate that this regime may be tested in the 'full stopping' (maximum energy deposition) scenario achieved at the AGS having a c.m. collision energy of about 2.5 GeV/nucleon for two equal- mass heavy nuclei. Since the solution of QCD on nuclear length-scales is computationally prohibitive even on today's most powerful computers, progress in the theoretical description of high densities has come through the application of models incorporating some of the essential features of the full theory. The simplest such model is the MIT bag model. We use a significantly more sophisticated model, a nonlocal confining soliton model developed in part at Kent. This model has proven its value in the calculation of the properties of individual mesons and nucleons. In the present application, the many-soliton problem is addressed with the same model. We describe nuclear matter as a lattice of solitons and apply the Wigner-Seitz approximation to the lattice. This means that we consider spherical cells with one soliton centered in each, corresponding to the average properties of the lattice. The average density is then varied by changing the size of the Wigner-Seitz cell. To arrive at a solution, we need to solve a coupled set of

  10. Interaction effects in a microscopic quantum wire model with strong spin-orbit interaction

    Science.gov (United States)

    Winkler, G. W.; Ganahl, M.; Schuricht, D.; Evertz, H. G.; Andergassen, S.

    2017-06-01

    We investigate the effect of strong interactions on the spectral properties of quantum wires with strong Rashba spin-orbit (SO) interaction in a magnetic field, using a combination of matrix product state and bosonization techniques. Quantum wires with strong Rashba SO interaction and magnetic field exhibit a partial gap in one-half of the conducting modes. Such systems have attracted wide-spread experimental and theoretical attention due to their unusual physical properties, among which are spin-dependent transport, or a topological superconducting phase when under the proximity effect of an s-wave superconductor. As a microscopic model for the quantum wire we study an extended Hubbard model with SO interaction and Zeeman field. We obtain spin resolved spectral densities from the real-time evolution of excitations, and calculate the phase diagram. We find that interactions increase the pseudo gap at k = 0 and thus also enhance the Majorana-supporting phase and stabilize the helical spin order. Furthermore, we calculate the optical conductivity and compare it with the low energy spiral Luttinger liquid result, obtained from field theoretical calculations. With interactions, the optical conductivity is dominated by an excotic excitation of a bound soliton-antisoliton pair known as a breather state. We visualize the oscillating motion of the breather state, which could provide the route to their experimental detection in e.g. cold atom experiments.

  11. POTENTIAL OF C-13 AND N-15 LABELING FOR STUDYING PROTEIN-PROTEIN INTERACTIONS USING FOURIER-TRANSFORM INFRARED-SPECTROSCOPY

    NARCIS (Netherlands)

    HARIS, PI; ROBILLARD, GT; VANDIJK, AA; CHAPMAN, D

    1992-01-01

    In this study, we examine the interaction between two bacterial proteins, namely HPr and IIA(mtl) of the Escherichia coli phosphoenolpyruvate-dependent phosphotransferase system, using FTIR spectroscopy. In an interaction involving a 1:1 molar ratio of these two proteins, when they are unlabeled,

  12. The colours of strong interaction; L`interaction forte sous toutes ses couleurs

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-12-31

    The aim of this session is to draw a consistent framework about the different ways to consider strong interaction. A large part is dedicated to theoretical work and the latest experimental results obtained at the first electron collider HERA are discussed. (A.C.)

  13. Study of protein-protein interactions in under saturated and supersaturated lysozyme solutions in heavy water as a function of temperature

    International Nuclear Information System (INIS)

    Gripon, C.; Legrand, L.; Rosenman, I.; Vidal, O.; Robert, M.C.; Boue, F.

    1996-01-01

    We have studied freshly prepared lysozyme solutions in heavy water for two NaCl concentrations as a function of temperature. Lysozyme solubilities in this solvent are determined by static light scattering. By small angle neutron scattering, we evidence that interactions between lysozyme molecules are characterized by a second virial coefficient A 2 whether the solution is under-saturated or supersaturated. From the variation of A 2 as a function of temperature we have evaluated the enthalpy corresponding to the interaction between lysozyme molecules. We show that the interactions between protein molecules are higher in heavy water than in light water. (authors). 13 refs., 3 figs

  14. 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

    2016-02-03

    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.

  15. SOcK, MiSTs, MASK and STicKs: the GCKIII (germinal centre kinase III) kinases and their heterologous protein-protein interactions.

    Science.gov (United States)

    Sugden, Peter H; McGuffin, Liam J; Clerk, Angela

    2013-08-15

    The GCKIII (germinal centre kinase III) subfamily of the mammalian Ste20 (sterile 20)-like group of serine/threonine protein kinases comprises SOK1 (Ste20-like/oxidant-stress-response kinase 1), MST3 (mammalian Ste20-like kinase 3) and MST4. Initially, GCKIIIs were considered in the contexts of the regulation of mitogen-activated protein kinase cascades and apoptosis. More recently, their participation in multiprotein heterocomplexes has become apparent. In the present review, we discuss the structure and phosphorylation of GCKIIIs and then focus on their interactions with other proteins. GCKIIIs possess a highly-conserved, structured catalytic domain at the N-terminus and a less-well conserved C-terminal regulatory domain. GCKIIIs are activated by tonic autophosphorylation of a T-loop threonine residue and their phosphorylation is regulated primarily through protein serine/threonine phosphatases [especially PP2A (protein phosphatase 2A)]. The GCKIII regulatory domains are highly disorganized, but can interact with more structured proteins, particularly the CCM3 (cerebral cavernous malformation 3)/PDCD10 (programmed cell death 10) protein. We explore the role(s) of GCKIIIs (and CCM3/PDCD10) in STRIPAK (striatin-interacting phosphatase and kinase) complexes and their association with the cis-Golgi protein GOLGA2 (golgin A2; GM130). Recently, an interaction of GCKIIIs with MO25 has been identified. This exhibits similarities to the STRADα (STE20-related kinase adaptor α)-MO25 interaction (as in the LKB1-STRADα-MO25 heterotrimer) and, at least for MST3, the interaction may be enhanced by cis-autophosphorylation of its regulatory domain. In these various heterocomplexes, GCKIIIs associate with the Golgi apparatus, the centrosome and the nucleus, as well as with focal adhesions and cell junctions, and are probably involved in cell migration, polarity and proliferation. Finally, we consider the association of GCKIIIs with a number of human diseases, particularly

  16. 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

    on the 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....

  17. The Structure of Herpesvirus Fusion Glycoprotein B-Bilayer Complex Reveals the Protein-Membrane and Lateral Protein-Protein Interaction

    NARCIS (Netherlands)

    Maurer, Ulrike E.; Zeev-Ben-Mordehai, Tzviya; Pandurangan, Arun Prasad; Cairns, Tina M.; Hannah, Brian P.; Whitbeck, J. Charles; Eisenberg, Roselyn J.; Cohen, Gary H.; Topf, Maya; Huiskonen, Juha T.; Gruenewald, Kay

    2013-01-01

    Glycoprotein B (gB) is a key component of the complex herpesvirus fusion machinery. We studied membrane interaction of two gB ectodomain forms and present an electron cryotomography structure of the gB-bilayer complex. The two forms differed in presence or absence of the membrane proximal region

  18. Expression Patterns and Identified Protein-Protein Interactions Suggest That Cassava CBL-CIPK Signal Networks Function in Responses to Abiotic Stresses.

    Science.gov (United States)

    Mo, Chunyan; Wan, Shumin; Xia, Youquan; Ren, Ning; Zhou, Yang; Jiang, Xingyu

    2018-01-01

    Cassava is an energy crop that is tolerant of multiple abiotic stresses. It has been reported that the interaction between Calcineurin B-like (CBL) protein and CBL-interacting protein kinase (CIPK) is implicated in plant development and responses to various stresses. However, little is known about their functions in cassava. Herein, 8 CBL ( MeCBL ) and 26 CIPK ( MeCIPK ) genes were isolated from cassava by genome searching and cloning of cDNA sequences of Arabidopsis CBL s and CIPK s. Reverse-transcriptase polymerase chain reaction (RT-PCR) analysis showed that the expression levels of MeCBL and MeCIPK genes were different in different tissues throughout the life cycle. The expression patterns of 7 CBL and 26 CIPK genes in response to NaCl, PEG, heat and cold stresses were analyzed by quantitative real-time PCR (qRT-PCR), and it was found that the expression of each was induced by multiple stimuli. Furthermore, we found that many pairs of CBLs and CIPKs could interact with each other via investigating the interactions between 8 CBL and 25 CIPK proteins using a yeast two-hybrid system. Yeast cells co-transformed with cassava MeCIPK24, MeCBL10 , and Na + /H + antiporter MeSOS1 genes exhibited higher salt tolerance compared to those with one or two genes. These results suggest that the cassava CBL-CIPK signal network might play key roles in response to abiotic stresses.

  19. Expression Patterns and Identified Protein-Protein Interactions Suggest That Cassava CBL-CIPK Signal Networks Function in Responses to Abiotic Stresses

    Directory of Open Access Journals (Sweden)

    Chunyan Mo

    2018-03-01

    Full Text Available Cassava is an energy crop that is tolerant of multiple abiotic stresses. It has been reported that the interaction between Calcineurin B-like (CBL protein and CBL-interacting protein kinase (CIPK is implicated in plant development and responses to various stresses. However, little is known about their functions in cassava. Herein, 8 CBL (MeCBL and 26 CIPK (MeCIPK genes were isolated from cassava by genome searching and cloning of cDNA sequences of Arabidopsis CBLs and CIPKs. Reverse-transcriptase polymerase chain reaction (RT-PCR analysis showed that the expression levels of MeCBL and MeCIPK genes were different in different tissues throughout the life cycle. The expression patterns of 7 CBL and 26 CIPK genes in response to NaCl, PEG, heat and cold stresses were analyzed by quantitative real-time PCR (qRT-PCR, and it was found that the expression of each was induced by multiple stimuli. Furthermore, we found that many pairs of CBLs and CIPKs could interact with each other via investigating the interactions between 8 CBL and 25 CIPK proteins using a yeast two-hybrid system. Yeast cells co-transformed with cassava MeCIPK24, MeCBL10, and Na+/H+ antiporter MeSOS1 genes exhibited higher salt tolerance compared to those with one or two genes. These results suggest that the cassava CBL-CIPK signal network might play key roles in response to abiotic stresses.

  20. Free-Propagator Reweighting Integrator for Single-Particle Dynamics in Reaction-Diffusion Models of Heterogeneous Protein-Protein Interaction Systems

    Directory of Open Access Journals (Sweden)

    Margaret E. Johnson

    2014-09-01

    Full Text Available 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.

  1. Interaction of neutral particles with strong laser fields

    Energy Technology Data Exchange (ETDEWEB)

    Meuren, Sebastian; Keitel, Christoph H.; Di Piazza, Antonino [Max-Planck-Institut fuer Kernphysik, Saupfercheckweg 1, D-69117 Heidelberg (Germany)

    2013-07-01

    Since the invention of the laser in the 1960s the experimentally available field strengths have continuously increased. The current peak intensity record is 2 x 10{sup 22} W/cm{sup 2} and next generation facilities such as ELI, HiPER and XCELS plan to reach even intensities of the order of 10{sup 24} W/cm{sup 2}. Thus, modern laser facilities are a clean source for very strong external electromagnetic fields and promise new and interesting high-energy physics experiments. In particular, strong laser fields could be used to test non-linear effects in quantum field theory. Earlier we have investigated how radiative corrections modify the coupling of a charged particle inside a strong plane-wave electromagnetic background field. However, a charged particle couples already at tree level to electromagnetic radiation. Therefore, we have now analyzed how the coupling between neutral particles and radiation is affected by a very strong plane-wave electromagnetic background field, when loop corrections are taken into account. In particular, the case of neutrinos is discussed.

  2. Intensities and strong interaction attenuation of kaonic x-rays

    CERN Document Server

    Backenstoss, Gerhard; Koch, H; Povel, H P; Schwitter, A; Tauscher, Ludwig

    1974-01-01

    Relative intensities of numerous kaonic X-ray transitions have been measured for the elements C, P, S, and Cl, from which level widths due to the strong K-nucleus absorption have been determined. From these and earlier published data, optical potential parameters have been derived and possible consequences on the nuclear matter distribution are discussed. (10 refs).

  3. Construction of high-quality Caco-2 three-frame cDNA library and its application to yeast two-hybrid for the human astrovirus protein-protein interaction.

    Science.gov (United States)

    Zhao, Wei; Li, Xin; Liu, Wen-Hui; Zhao, Jian; Jin, Yi-Ming; Sui, Ting-Ting

    2014-09-01

    Human epithelial colorectal adenocarcinoma (Caco-2) cells are widely used as an in vitro model of the human small intestinal mucosa. Caco-2 cells are host cells of the human astrovirus (HAstV) and other enteroviruses. High quality cDNA libraries are pertinent resources and critical tools for protein-protein interaction research, but are currently unavailable for Caco-2 cells. To construct a three-open reading frame, full length-expression cDNA library from the Caco-2 cell line for application to HAstV protein-protein interaction screening, total RNA was extracted from Caco-2 cells. The switching mechanism at the 5' end of the RNA transcript technique was used for cDNA synthesis. Double-stranded cDNA was digested by Sfi I and ligated to reconstruct a pGADT7-Sfi I three-frame vector. The ligation mixture was transformed into Escherichia coli HST08 premium electro cells by electroporation to construct the primary cDNA library. The library capacity was 1.0×10(6)clones. Gel electrophoresis results indicated that the fragments ranged from 0.5kb to 4.2kb. Randomly picked clones show that the recombination rate was 100%. The three-frame primary cDNA library plasmid mixture (5×10(5)cfu) was also transformed into E. coli HST08 premium electro cells, and all clones were harvested to amplify the cDNA library. To detect the sufficiency of the cDNA library, HAstV capsid protein as bait was screened and tested against the Caco-2 cDNA library by a yeast two-hybrid (Y2H) system. A total of 20 proteins were found to interact with the capsid protein. These results showed that a high-quality three-frame cDNA library from Caco-2 cells was successfully constructed. This library was efficient for the application to the Y2H system, and could be used for future research. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. Molecular screening of compounds to the predicted Protein-Protein Interaction site of Rb1-E7 with p53- E6 in HPV.

    Science.gov (United States)

    Shaikh, Faraz; Sanehi, Parvish; Rawal, Rakesh

    2012-01-01

    Cervical cancer is malignant neoplasm of the cervix uteri or cervical area. Human Papillomaviruses (HPVs) which are heterogeneous groups of small double stranded DNA viruses are considered as the primary cause of cervical cancer, involved in 90% of all Cervical Cancers. Two early HPV genes, E6 and E7, are known to play crucial role in tumor formation. E6 binds with p53 and prevents its translocation and thereby inhibit the ability of p53 to activate or repress target genes. E7 binds to hypophosphorylated Rb and thereby induces cells to enter into premature S-phase by disrupting Rb-E2F complexes. The strategy of the research work was to target the site of interaction of Rb1 -E7 & p53-E6. A total of 88 compounds were selected for molecular screening, based on comprehensive literature survey for natural compounds with anti-cancer activity. Molecular docking analysis was carried out with Molegro Virtual Docker, to screen the 88 chosen compounds and rank them according to their binding affinity towards the site of interaction of the viral oncoproteins and human tumor suppressor proteins. The docking result revealed that Nicandrenone a member of Withanolides family of chemical compounds as the most likely molecule that can be used as a candidate drug against HPV induced cervical cancer. HPV - Human Papiloma Virus, HTSP - Human Tumor Suppressor Proteins, VOP - Viral oncoproteins.

  5. Comparing side chain packing in soluble proteins, protein-protein interfaces, and transmembrane proteins.

    Science.gov (United States)

    Gaines, J C; Acebes, S; Virrueta, A; Butler, M; Regan, L; O'Hern, C S

    2018-05-01

    We compare side chain prediction and packing of core and non-core regions of soluble proteins, protein-protein interfaces, and transmembrane proteins. We first identified or created comparable databases of high-resolution crystal structures of these 3 protein classes. We show that the solvent-inaccessible cores of the 3 classes of proteins are equally densely packed. As a result, the side chains of core residues at protein-protein interfaces and in the membrane-exposed regions of transmembrane proteins can be predicted by the hard-sphere plus stereochemical constraint model with the same high prediction accuracies (>90%) as core residues in soluble proteins. We also find that for all 3 classes of proteins, as one moves away from the solvent-inaccessible core, the packing fraction decreases as the solvent accessibility increases. However, the side chain predictability remains high (80% within 30°) up to a relative solvent accessibility, rSASA≲0.3, for all 3 protein classes. Our results show that ≈40% of the interface regions in protein complexes are "core", that is, densely packed with side chain conformations that can be accurately predicted using the hard-sphere model. We propose packing fraction as a metric that can be used to distinguish real protein-protein interactions from designed, non-binding, decoys. Our results also show that cores of membrane proteins are the same as cores of soluble proteins. Thus, the computational methods we are developing for the analysis of the effect of hydrophobic core mutations in soluble proteins will be equally applicable to analyses of mutations in membrane proteins. © 2018 Wiley Periodicals, Inc.

  6. 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

    cells. It is concluded that the heterodimeric complex of the P1/P2 proteins is formed preferentially. Formation of homodimers (P1/P1 and P2/P2) can also be observed, though with much less efficiency. Regarding that, we propose to describe the double heterodimeric complex as a protein configuration which......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 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...

  7. Dynamical fermion mass generation by a strong Yukawa interaction

    Czech Academy of Sciences Publication Activity Database

    Brauner, Tomáš; Hošek, Jiří

    2005-01-01

    Roč. 72, č. 4 (2005), 045007 ISSN 0556-2821 R&D Projects: GA MŠk LA 080; GA ČR(CZ) GD202/05/H003 Institutional research plan: CEZ:AV0Z10480505 Keywords : dynamical mass generation * Yukawa interaction Subject RIV: BF - Elementary Particles and High Energy Physics Impact factor: 4.852, year: 2005

  8. Gauge theories of weak, electromagnetic and strong interactions

    International Nuclear Information System (INIS)

    Boehm, M.; Joos, H.

    1978-05-01

    This 10 lectures are devided into the chapters: Phenomenological basis of the quantum chromodynamics, phenomenology of weak interactions, quantum electrodynamics and gauge invariance, from the fermimodel to the quantum flavor dynamics, on the quantum theory of yang-mills-fields, spontaneous symmetry breaking - the Higgs-Kibble-mechanism, the Salam-Weinberg-model, asymptotic freedom, quark confinement and charmonium. (WL) [de

  9. Physics Performance Report for PANDA : Strong Interaction Studies with Antiprotons

    NARCIS (Netherlands)

    Erni, W.; Keshelashvili, I.; Krusche, B.; Steinacher, M.; Heng, Y.; Liu, Z.; Liu, H.; Shen, X.; Wang, O.; Xu, H.; Becker, J.; Feldbauer, F.; Heinsius, F. -H.; Held, T.; Koch, H.; Kopf, B.; Pelizaeus, M.; Schroeder, T.; Steinke, M.; Wiedner, U.; Zhong, J.; Bianconi, A.; Bragadireanu, M.; Pantea, D.; Tudorache, A.; Tudorache, V.; De Napoli, M.; Giacoppo, F.; Raciti, G.; Rapisarda, E.; Sfienti, C.; Bialkowski, E.; Budzanowski, A.; Czech, B.; Kistryn, M.; Kliczewski, S.; Kozela, A.; Kulessa, P.; Pysz, K.; Schaefer, W.; Siudak, R.; Szczurek, A.; Czy. zycki, W.; Domagala, M.; Hawryluk, M.; Lisowski, E.; Lisowski, F.; Wojnar, L.; Gil, D.; Hawranek, P.; Kamys, B.; Kistryn, St.; Korcyl, K.; Krzemien, W.; Magiera, A.; Moskal, P.; Rudy, Z.; Salabura, P.; Smyrski, J.; Wronska, A.; Al-Turany, M.; Augustin, I.; Deppe, H.; Flemming, H.; Gerl, J.; Goetzen, K.; Hohler, R.; Lehmann, D.; Lewandowski, B.; Luehning, J.; Maas, F.; Mishra, D.; Orth, H.; Peters, K.; Saito, T.; Schepers, G.; Schmidt, C. J.; Schmitt, L.; Schwarz, C.; Voss, B.; Wieczorek, P.; Wilms, A.; Brinkmann, K. -T.; Freiesleben, H.; Jaekel, R.; Kliemt, R.; Wuerschig, T.; Zaunick, H. -G.; Abazov, V. M.; Alexeev, G.; Arefiev, A.; Astakhov, V. I.; Barabanov, M. Yu.; Batyunya, B. V.; Davydov, Yu. I.; Dodokhov, V. Kh.; Efremov, A. A.; Fedunov, A. G.; Feshchenko, A. A.; Galoyan, A. S.; Grigoryan, S.; Karmokov, A.; Koshurnikov, E. K.; Kudaev, V. Ch.; Lobanov, V. I.; Lobanov, Yu. Yu.; Makarov, A. F.; Malinina, L. V.; Malyshev, V. L.; Mustafaev, G. A.; Olshevski, A.; . Pasyuk, M. A.; Perevalova, E. A.; Piskun, A. A.; Pocheptsov, T. A.; Pontecorvo, G.; Rodionov, V. K.; Rogov, Yu. N.; Salmin, R. A.; Samartsev, A. G.; Sapozhnikov, M. G.; Shabratova, A.; Shabratova, G. S.; Skachkova, A. N.; Skachkov, N. B.; Strokovsky, E. A.; Suleimanov, M. K.; Teshev, R. Sh.; Tokmenin, V. V.; Uzhinsky, V. V.; Vodopianov, A. S.; Zaporozhets, S. A.; Zhuravlev, N. I.; Zorin, A. G.; Branford, D.; Foehl, K.; Glazier, D.; Watts, D.; Woods, P.; Eyrich, W.; Lehmann, A.; Teufel, A.; Dobbs, S.; Metreveli, Z.; Seth, K.; Tann, B.; Tomaradze, A.; Bettoni, D.; Carassiti, V.; Cecchi, A.; Dalpiaz, P.; Fioravanti, E.; Garzia, I.; Negrini, M.; Savri`e, M.; Stancari, G.; Dulach, B.; Gianotti, P.; Guaraldo, C.; Lucherini, V.; Pace, E.; Bersani, A.; Macri, M.; Marinelli, M.; Parodi, R. F.; Brodski, I.; Doering, W.; Drexler, P.; Dueren, M.; Gagyi-Palffy, Z.; Hayrapetyan, A.; Kotulla, M.; Kuehn, W.; Lange, S.; Liu, M.; Metag, V.; Nanova, M.; Novotny, R.; Salz, C.; Schneider, J.; Schoenmeier, P.; Schubert, R.; Spataro, S.; Stenzel, H.; Strackbein, C.; Thiel, M.; Thoering, U.; Yang, S.; Clarkson, T.; Cowie, E.; Downie, E.; Hill, G.; Hoek, M.; Ireland, D.; Kaiser, R.; Keri, T.; Lehmann, I.; Livingston, K.; Lumsden, S.; MacGregor, D.; McKinnon, B.; Murray, M.; Protopopescu, D.; Rosner, G.; Seitz, B.; Yang, G.; Babai, M.; Biegun, A. K.; Bubak, A.; Guliyev, E.; Suyam Jothi, Vanniarajan; Kavatsyuk, M.; Loehner, H.; Messchendorp, J.; Smit, H.; van der Weele, J. C.; Garcia, F.; Riska, D. -O.; Buescher, M.; Dosdall, R.; Dzhygadlo, R.; Gillitzer, A.; Grunwald, D.; Jha, V.; Kemmerling, G.; Kleines, H.; Lehrach, A.; Maier, R.; Mertens, M.; Ohm, H.; Prasuhn, D.; Randriamalala, T.; Ritman, J.; Roeder, M.; Stockmanns, T.; Wintz, P.; Wuestner, P.; Kisiel, J.; Li, S.; Li, Z.; Sun, Z.; Xu, H.; Fissum, S.; Hansen, K.; Isaksson, L.; Lundin, M.; Schroeder, B.; Achenbach, P.; Mora Espi, M. C.; Pochodzalla, J.; Sanchez, S.; Sanchez-Lorente, A.; Dormenev, V. I.; Fedorov, A. A.; Korzhik, M. V.; Missevitch, O. V.; Balanutsa, V.; Chernetsky, V.; Demekhin, A.; Dolgolenko, A.; Fedorets, P.; Gerasimov, A.; Goryachev, V.; Boukharov, A.; Malyshev, O.; Marishev, I.; Semenov, A.; Hoeppner, C.; Ketzer, B.; Konorov, I.; Mann, A.; Neubert, S.; Paul, S.; Weitzel, Q.; Khoukaz, A.; Rausmann, T.; Taeschner, A.; Wessels, J.; Varma, R.; Baldin, E.; Kotov, K.; Peleganchuk, S.; Tikhonov, Yu.; Boucher, J.; Hennino, T.; Kunne, R.; Ong, S.; Pouthas, J.; Ramstein, B.; Rosier, P.; Sudol, M.; Van de Wiele, J.; Zerguerras, T.; Dmowski, K.; Korzeniewski, R.; Przemyslaw, D.; Slowinski, B.; Boca, G.; Braghieri, A.; Costanza, S.; Fontana, A.; Genova, P.; Lavezzi, L.; Montagna, P.; Rotondi, A.; Belikov, N. I.; Davidenko, A. M.; Derevschikov, A. A.; Goncharenko, Y. M.; Grishin, V. N.; Kachanov, V. A.; Konstantinov, D. A.; Kormilitsin, V. A.; Kravtsov, V. I.; Matulenko, Y. A.; Melnik, Y. M.; Meschanin, A. P.; Minaev, N. G.; Mochalov, V. V.; Morozov, D. A.; Nogach, L. V.; Nurushev, S. B.; Ryazantsev, A. V.; Semenov, P. A.; Soloviev, L. F.; Uzunian, A. V.; Vasiliev, A. N.; Yakutin, A. E.; Baeck, T.; Cederwall, B.; Bargholtz, C.; Geren, L.; Tegner, P. E.; Belostotski, S.; Gavrilov, G.; Itzotov, A.; Kisselev, A.; Kravchenko, P.; Manaenkov, S.; Miklukho, O.; Naryshkin, Y.; Veretennikov, D.; Vikhrov, V.; Zhadanov, A.; Fava, L.; Panzieri, D.; Alberto, D.; Amoroso, A.; Botta, E.; Bressani, T.; Bufalino, S.; Bussa, M. P.; Busso, L.; De Mori, F.; Destefanis, M.; Ferrero, L.; Grasso, A.; Greco, M.; Kugathasan, T.; Maggiora, M.; Marcello, S.; Serbanut, G.; Sosio, S.; Bertini, R.; Calvo, D.; Coli, S.; De Remigis, P.; Feliciello, A.; Filippi, A.; Giraudo, G.; Mazza, G.; Rivetti, A.; Szymanska, K.; Tosello, F.; Wheadon, R.; Morra, O.; Agnello, M.; Iazzi, F.; Szymanska, K.; Birsa, R.; Bradamante, F.; Bressan, A.; Martin, A.; Clement, H.; Ekstroem, C.; Calen, H.; Grape, S.; Hoeistad, B.; Johansson, T.; Kupsc, A.; Marciniewski, P.; Thome, E.; Zlomanczuk, J.; Diaz, J.; Ortiz, A.; Borsuk, S.; Chlopik, A.; Guzik, Z.; Kopec, J.; Kozlowski, T.; Melnychuk, D.; Plominski, M.; Szewinski, J.; Traczyk, K.; Zwieglinski, B.; Buehler, P.; Gruber, A.; Kienle, P.; Marton, J.; Widmann, E.; Zmeskal, J.; Lutz, M. F. M.; Pire, B.; Scholten, O.; Timmermans, R.

    To study fundamental questions of hadron and nuclear physics in interactions of antiprotons with nucleons and nuclei, the universal PANDA detector will be built. Gluonic excitations, the physics of strange and charm quarks and nucleon structure studies will be performed with unprecedented accuracy

  10. Coulomb plus strong interaction bound states - momentum space numerical solutions

    International Nuclear Information System (INIS)

    Heddle, D.P.; Tabakin, F.

    1985-01-01

    The levels and widths of hadronic atoms are calculated in momentum space using an inverse algorithm for the eigenvalue problem. The Coulomb singularity is handled by the Lande substraction method. Relativistic, nonlocal, complex hadron-nucleus interactions are incorporated as well as vacuum polarization and finite size effects. Coordinate space wavefunctions are obtained by employing a Fourier Bessel transformation. (orig.)

  11. A positive-strand RNA virus uses alternative protein-protein interactions within a viral protease/cofactor complex to switch between RNA replication and virion morphogenesis

    Science.gov (United States)

    Rey, Félix A.

    2017-01-01

    The viruses of the family Flaviviridae possess a positive-strand RNA genome and express a single polyprotein which is processed into functional proteins. Initially, the nonstructural (NS) proteins, which are not part of the virions, form complexes capable of genome replication. Later on, the NS proteins also play a critical role in virion formation. The molecular basis to understand how the same proteins form different complexes required in both processes is so far unknown. For pestiviruses, uncleaved NS2-3 is essential for virion morphogenesis while NS3 is required for RNA replication but is not functional in viral assembly. Recently, we identified two gain of function mutations, located in the C-terminal region of NS2 and in the serine protease domain of NS3 (NS3 residue 132), which allow NS2 and NS3 to substitute for uncleaved NS2-3 in particle assembly. We report here the crystal structure of pestivirus NS3-4A showing that the NS3 residue 132 maps to a surface patch interacting with the C-terminal region of NS4A (NS4A-kink region) suggesting a critical role of this contact in virion morphogenesis. We show that destabilization of this interaction, either by alanine exchanges at this NS3/4A-kink interface, led to a gain of function of the NS3/4A complex in particle formation. In contrast, RNA replication and thus replicase assembly requires a stable association between NS3 and the NS4A-kink region. Thus, we propose that two variants of NS3/4A complexes exist in pestivirus infected cells each representing a basic building block required for either RNA replication or virion morphogenesis. This could be further corroborated by trans-complementation studies with a replication-defective NS3/4A double mutant that was still functional in viral assembly. Our observations illustrate the presence of alternative overlapping surfaces providing different contacts between the same proteins, allowing the switch from RNA replication to virion formation. PMID:28151973

  12. A positive-strand RNA virus uses alternative protein-protein interactions within a viral protease/cofactor complex to switch between RNA replication and virion morphogenesis.

    Directory of Open Access Journals (Sweden)

    Danilo Dubrau

    2017-02-01

    Full Text Available The viruses of the family Flaviviridae possess a positive-strand RNA genome and express a single polyprotein which is processed into functional proteins. Initially, the nonstructural (NS proteins, which are not part of the virions, form complexes capable of genome replication. Later on, the NS proteins also play a critical role in virion formation. The molecular basis to understand how the same proteins form different complexes required in both processes is so far unknown. For pestiviruses, uncleaved NS2-3 is essential for virion morphogenesis while NS3 is required for RNA replication but is not functional in viral assembly. Recently, we identified two gain of function mutations, located in the C-terminal region of NS2 and in the serine protease domain of NS3 (NS3 residue 132, which allow NS2 and NS3 to substitute for uncleaved NS2-3 in particle assembly. We report here the crystal structure of pestivirus NS3-4A showing that the NS3 residue 132 maps to a surface patch interacting with the C-terminal region of NS4A (NS4A-kink region suggesting a critical role of this contact in virion morphogenesis. We show that destabilization of this interaction, either by alanine exchanges at this NS3/4A-kink interface, led to a gain of function of the NS3/4A complex in particle formation. In contrast, RNA replication and thus replicase assembly requires a stable association between NS3 and the NS4A-kink region. Thus, we propose that two variants of NS3/4A complexes exist in pestivirus infected cells each representing a basic building block required for either RNA replication or virion morphogenesis. This could be further corroborated by trans-complementation studies with a replication-defective NS3/4A double mutant that was still functional in viral assembly. Our observations illustrate the presence of alternative overlapping surfaces providing different contacts between the same proteins, allowing the switch from RNA replication to virion formation.

  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. Uses of Phage Display in Agriculture: A Review of Food-Related Protein-Protein Interactions Discovered by Biopanning over Diverse Baits

    Directory of Open Access Journals (Sweden)

    Rekha Kushwaha

    2013-01-01

    Full Text Available This review highlights discoveries made using phage display that impact the use of agricultural products. The contribution phage display made to our fundamental understanding of how various protective molecules serve to safeguard plants and seeds from herbivores and microbes is discussed. The utility of phage display for directed evolution of enzymes with enhanced capacities to degrade the complex polymers of the cell wall into molecules useful for biofuel production is surveyed. Food allergies are often directed against components of seeds; this review emphasizes how phage display has been employed to determine the seed component(s contributing most to the allergenic reaction and how it has played a central role in novel approaches to mitigate patient response. Finally, an overview of the use of phage display in identifying the mature seed proteome protection and repair mechanisms is provided. The identification of specific classes of proteins preferentially bound by such protection and repair proteins leads to hypotheses concerning the importance of safeguarding the translational apparatus from damage during seed quiescence and environmental perturbations during germination. These examples, it is hoped, will spur the use of phage display in future plant science examining protein-ligand interactions.

  15. Sedimentation velocity analysis of heterogeneous protein-protein interactions: sedimentation coefficient distributions c(s) and asymptotic boundary profiles from Gilbert-Jenkins theory.

    Science.gov (United States)

    Dam, Julie; Schuck, Peter

    2005-07-01

    Interacting proteins in rapid association equilibrium exhibit coupled migration under the influence of an external force. In sedimentation, two-component systems can exhibit bimodal boundaries, consisting of the undisturbed sedimentation of a fraction of the population of one component, and the coupled sedimentation of a mixture of both free and complex species in the reaction boundary. For the theoretical limit of diffusion-free sedimentation after infinite time, the shapes of the reaction boundaries and the sedimentation velocity gradients have been predicted by Gilbert and Jenkins. We compare these asymptotic gradients with sedimentation coefficient distributions, c(s), extracted from experimental sedimentation profiles by direct modeling with superpositions of Lamm equation solutions. The overall shapes are qualitatively consistent and the amplitudes and weight-average s-values of the different boundary components are quantitatively in good agreement. We propose that the concentration dependence of the area and weight-average s-value of the c(s) peaks can be modeled by isotherms based on Gilbert-Jenkins theory, providing a robust approach to exploit the bimodal structure of the reaction boundary for the analysis of experimental data. This can significantly improve the estimates for the determination of binding constants and hydrodynamic parameters of the complexes.

  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. Quantum memory with strong and controllable Rydberg-level interactions.

    Science.gov (United States)

    Li, Lin; Kuzmich, A

    2016-11-21

    Realization of distributed quantum systems requires fast generation and long-term storage of quantum states. Ground atomic states enable memories with storage times in the range of a minute, however their relatively weak interactions do not allow fast creation of non-classical collective states. Rydberg atomic systems feature fast preparation of singly excited collective states and their efficient mapping into light, but storage times in these approaches have not yet exceeded a few microseconds. Here we demonstrate a system that combines fast quantum state generation and long-term storage. An initially prepared coherent state of an atomic memory is transformed into a non-classical collective atomic state by Rydberg-level interactions in less than a microsecond. By sheltering the quantum state in the ground atomic levels, the storage time is increased by almost two orders of magnitude. This advance opens a door to a number of quantum protocols for scalable generation and distribution of entanglement.

  18. Hadron yields and the phase diagram of strongly interacting matter

    CERN Document Server

    Floris, Michele

    2014-01-01

    This paper presents a brief review of the interpretation of measurements of hadron yields in hadronic interactions within the framework of thermal models, over a broad energy range (from SIS to LHC energies, $\\sqrt{s_{NN}} \\simeq$ 2.5 GeV -- 5 TeV). Recent experimental results and theoretical developments are reported, with an emphasis on topics discussed during the Quark Matter 2014 conference.

  19. Theoretical studies in weak, electromagnetic and strong interactions. Attachments

    International Nuclear Information System (INIS)

    Nandi, S.

    1999-01-01

    The project covered a wide area of current research in theoretical high-energy physics. This included Standard Model (SM) as well as physics beyond the Standard Model. Specific topics included supersymmetry (SUSY), perturbative quantum chromodynamics (QCD), a new weak interaction for the third family (called topflavor), neutrino masses and mixings, topcolor model, Pade approximation, and its application to perturbative QCD and other physical processes

  20. First evidence for substrate channeling between proline catabolic enzymes: a validation of domain fusion analysis for predicting protein-protein interactions.

    Science.gov (United States)

    Sanyal, Nikhilesh; Arentson, Benjamin W; Luo, Min; Tanner, John J; Becker, Donald F

    2015-01-23

    Proline dehydrogenase (PRODH) and Δ(1)-pyrroline-5-carboxylate (P5C) dehydrogenase (P5CDH) catalyze the four-electron oxidation of proline to glutamate via the intermediates P5C and l-glutamate-γ-semialdehyde (GSA). In Gram-negative bacteria, PRODH and P5CDH are fused together in the bifunctional enzyme proline utilization A (PutA) whereas in other organisms PRODH and P5CDH are expressed as separate monofunctional enzymes. Substrate channeling has previously been shown for bifunctional PutAs, but whether the monofunctional enzymes utilize an analogous channeling mechanism has not been examined. Here, we report the first evidence of substrate channeling in a PRODH-P5CDH two-enzyme pair. Kinetic data for the coupled reaction of PRODH and P5CDH from Thermus thermophilus are consistent with a substrate channeling mechanism, as the approach to steady-state formation of NADH does not fit a non-channeling two-enzyme model. Furthermore, inactive P5CDH and PRODH mutants inhibit NADH production and increase trapping of the P5C intermediate in coupled assays of wild-type PRODH-P5CDH enzyme pairs, indicating that the mutants disrupt PRODH-P5CDH channeling interactions. A dissociation constant of 3 μm was estimated for a putative PRODH-P5CDH complex by surface plasmon resonance (SPR). Interestingly, P5CDH binding to PRODH was only observed when PRODH was immobilized with the top face of its (βα)8 barrel exposed. Using the known x-ray crystal structures of PRODH and P5CDH from T. thermophilus, a model was built for a proposed PRODH-P5CDH enzyme channeling complex. The structural model predicts that the core channeling pathway of bifunctional PutA enzymes is conserved in monofunctional PRODH-P5CDH enzyme pairs. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  1. Muons probe strong hydrogen interactions with defective graphene.

    Science.gov (United States)

    Riccò, Mauro; Pontiroli, Daniele; Mazzani, Marcello; Choucair, Mohammad; Stride, John A; Yazyev, Oleg V

    2011-11-09

    Here, we present the first muon spectroscopy investigation of graphene, focused on chemically produced, gram-scale samples, appropriate to the large muon penetration depth. We have observed an evident muon spin precession, usually the fingerprint of magnetic order, but here demonstrated to originate from muon-hydrogen nuclear dipolar interactions. This is attributed to the formation of CHMu (analogous to CH(2)) groups, stable up to 1250 K where the signal still persists. The relatively large signal amplitude demonstrates an extraordinary hydrogen capture cross section of CH units. These results also rule out the formation of ferromagnetic or antiferromagnetic order in chemically synthesized graphene samples.

  2. Interaction of Azobenzene and Benzalaniline with Strong Amido Bases.

    Science.gov (United States)

    Kornev, Alexander N; Sushev, Vyacheslav V; Zolotareva, Natalia V; Baranov, Evgenii V; Fukin, Georgy K; Abakumov, Gleb A

    2015-12-18

    The interaction of azobenzene with lithium dicyclohexylamide (Cy2NLi) in THF or Et2O afforded the ion-radical salt of azobenzene (1) structurally characterized for the first time and dicyclohexylaminyl radical, which begins a novel chain of transformations leading eventually to the imino-enamido lithium complex (3). Benzalaniline, being a relative of azobenzene, reacted with Cy2NLi without electron transfer by a proton-abstraction mechanism to form the dilithium salt of N(1),N(2),1,2-tetraphenylethene-1,2-diamine quantitatively.

  3. Spin effects in strong-field laser-electron interactions

    International Nuclear Information System (INIS)

    Ahrens, S; Bauke, H; Müller, T-O; Villalba-Chávez, S; Müller, C

    2013-01-01

    The electron spin degree of freedom can play a significant role in relativistic scattering processes involving intense laser fields. In this contribution we discuss the influence of the electron spin on (i) Kapitza-Dirac scattering in an x-ray laser field of high intensity, (ii) photo-induced electron-positron pair production in a strong laser wave and (iii) multiphoton electron-positron pair production on an atomic nucleus. We show that in all cases under consideration the electron spin can have a characteristic impact on the process properties and their total probabilities. To this end, spin-resolved calculations based on the Dirac equation in the presence of an intense laser field are performed. The predictions from Dirac theory are also compared with the corresponding results from the Klein-Gordon equation.

  4. Strongly-interacting mirror fermions at the LHC

    Directory of Open Access Journals (Sweden)

    Triantaphyllou George

    2017-01-01

    Full Text Available The introduction of mirror fermions corresponding to an interchange of leftwith right-handed fermion quantum numbers of the Standard Model can lead to a model according to which the BEH mechanism is just an effective manifestation of a more fundamental theory while the recently-discovered Higgs-like particle is composite. This is achieved by a non-abelian gauge symmetry encompassing three mirror-fermion families strongly coupled at energies near 1 TeV. The corresponding non-perturbative dynamics lead to dynamical mirror-fermion masses between 0.14 - 1.2 TeV. Furthermore, one expects the formation of composite states, i.e. “mirror mesons”, with masses between 0.1 and 3 TeV. The number and properties of the resulting new degrees of freedom lead to a rich and interesting phenomenology, part of which is analyzed in the present work.

  5. A non-linear theory of strong interactions

    International Nuclear Information System (INIS)

    Skyrme, T.H.R.

    1994-01-01

    A non-linear theory of mesons, nucleons and hyperons is proposed. The three independent fields of the usual symmetrical pseudo-scalar pion field are replaced by the three directions of a four-component field vector of constant length, conceived in an Euclidean four-dimensional isotopic spin space. This length provides the universal scaling factor, all other constants being dimensionless; the mass of the meson field is generated by a φ 4 term; this destroys the continuous rotation group in the iso-space, leaving a 'cubic' symmetry group. Classification of states by this group introduces quantum numbers corresponding to isotopic spin and to 'strangeness'; one consequences is that, at least in elementary interactions, charge is only conserved module 4. Furthermore, particle states have not a well-defined parity, but parity is effectively conserved for meson-nucleon interactions. A simplified model, using only two dimensions of space and iso-space, is considered further; the non-linear meson field has solutions with particle character, and an indication is given of the way in which the particle field variables might be introduced as collective co-ordinates describing the dynamics of these particular solutions of the meson field equations, suggesting a unified theory based on the meson field alone. (author). 7 refs

  6. Magnetic dynamics of weakly and strongly interacting hematite nanoparticles