WorldWideScience

Sample records for binary protein-protein binding

  1. Grafting of protein-protein binding sites

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    A strategy for grafting protein-protein binding sites is described. Firstly, key interaction residues at the interface of ligand protein to be grafted are identified and suitable positions in scaffold protein for grafting these key residues are sought. Secondly, the scaffold proteins are superposed onto the ligand protein based on the corresponding Ca and Cb atoms. The complementarity between the scaffold protein and the receptor protein is evaluated and only matches with high score are accepted. The relative position between scaffold and receptor proteins is adjusted so that the interface has a reasonable packing density. Then the scaffold protein is mutated to corresponding residues in ligand protein at each candidate position. And the residues having bad steric contacts with the receptor proteins, or buried charged residues not involved in the formation of any salt bridge are mutated. Finally, the mutated scaffold protein in complex with receptor protein is co-minimized by Charmm. In addition, we deduce a scoring function to evaluate the affinity between mutated scaffold protein and receptor protein by statistical analysis of rigid binding data sets.

  2. A binary logistic regression model for discriminating real protein-protein interface

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    The selection and study of descriptive variables of protein-protein complex interface is a major question that many biologists come across when the research of protein-protein recognition is concerned. Several variables have been proposed to understand the structural or energetic features of complex interfaces. Here a systematic study of some of these "traditional" variables, as well as a few new ones, is introduced. With the values of these variables extracted from 42 PDB samples with real or false complex interfaces, a binary logistic regression analysis is performed, which results in an effective empirical model for the evaluation of binding probabilities of protein-protein interfaces. The model is validated with 12 samples, and satisfactory results are obtained for both the training and validation sets. Meanwhile, three potential dimeric interfaces of staphylokinase have been investigated and one with the best suitability to our model is proposed.

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

    Directory of Open Access Journals (Sweden)

    Bernhard eSuter

    2015-12-01

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

  4. Predicting where small molecules bind at protein-protein interfaces.

    Directory of Open Access Journals (Sweden)

    Peter Walter

    Full Text Available Small molecules that bind at protein-protein interfaces may either block or stabilize protein-protein interactions in cells. Thus, some of these binding interfaces may turn into prospective targets for drug design. Here, we collected 175 pairs of protein-protein (PP complexes and protein-ligand (PL complexes with known three-dimensional structures for which (1 one protein from the PP complex shares at least 40% sequence identity with the protein from the PL complex, and (2 the interface regions of these proteins overlap at least partially with each other. We found that those residues of the interfaces that may bind the other protein as well as the small molecule are evolutionary more conserved on average, have a higher tendency of being located in pockets and expose a smaller fraction of their surface area to the solvent than the remaining protein-protein interface region. Based on these findings we derived a statistical classifier that predicts patches at binding interfaces that have a higher tendency to bind small molecules. We applied this new prediction method to more than 10,000 interfaces from the protein data bank. For several complexes related to apoptosis the predicted binding patches were in direct contact to co-crystallized small molecules.

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

    NARCIS (Netherlands)

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

    2008-01-01

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

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

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    Craescu Constantin T

    2011-05-01

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

  7. Sequence and structural features of binding site residues in protein-protein complexes: comparison with protein-nucleic acid complexes

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    Selvaraj S

    2011-10-01

    Full Text Available Abstract Background Protein-protein interactions are important for several cellular processes. Understanding the mechanism of protein-protein recognition and predicting the binding sites in protein-protein complexes are long standing goals in molecular and computational biology. Methods We have developed an energy based approach for identifying the binding site residues in protein–protein complexes. The binding site residues have been analyzed with sequence and structure based parameters such as binding propensity, neighboring residues in the vicinity of binding sites, conservation score and conformational switching. Results We observed that the binding propensities of amino acid residues are specific for protein-protein complexes. Further, typical dipeptides and tripeptides showed high preference for binding, which is unique to protein-protein complexes. Most of the binding site residues are highly conserved among homologous sequences. Our analysis showed that 7% of residues changed their conformations upon protein-protein complex formation and it is 9.2% and 6.6% in the binding and non-binding sites, respectively. Specifically, the residues Glu, Lys, Leu and Ser changed their conformation from coil to helix/strand and from helix to coil/strand. Leu, Ser, Thr and Val prefer to change their conformation from strand to coil/helix. Conclusions The results obtained in this study will be helpful for understanding and predicting the binding sites in protein-protein complexes.

  8. SONAR Discovers RNA-Binding Proteins from Analysis of Large-Scale Protein-Protein Interactomes.

    Science.gov (United States)

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

    2016-10-20

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

  9. Structural Perspectives on the Evolutionary Expansion of Unique Protein-Protein Binding Sites.

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    Goncearenco, Alexander; Shaytan, Alexey K; Shoemaker, Benjamin A; Panchenko, Anna R

    2015-09-15

    Structures of protein complexes provide atomistic insights into protein interactions. Human proteins represent a quarter of all structures in the Protein Data Bank; however, available protein complexes cover less than 10% of the human proteome. Although it is theoretically possible to infer interactions in human proteins based on structures of homologous protein complexes, it is still unclear to what extent protein interactions and binding sites are conserved, and whether protein complexes from remotely related species can be used to infer interactions and binding sites. We considered biological units of protein complexes and clustered protein-protein binding sites into similarity groups based on their structure and sequence, which allowed us to identify unique binding sites. We showed that the growth rate of the number of unique binding sites in the Protein Data Bank was much slower than the growth rate of the number of structural complexes. Next, we investigated the evolutionary roots of unique binding sites and identified the major phyletic branches with the largest expansion in the number of novel binding sites. We found that many binding sites could be traced to the universal common ancestor of all cellular organisms, whereas relatively few binding sites emerged at the major evolutionary branching points. We analyzed the physicochemical properties of unique binding sites and found that the most ancient sites were the largest in size, involved many salt bridges, and were the most compact and least planar. In contrast, binding sites that appeared more recently in the evolution of eukaryotes were characterized by a larger fraction of polar and aromatic residues, and were less compact and more planar, possibly due to their more transient nature and roles in signaling processes.

  10. Interactome-Wide Prediction of Protein-Protein Binding Sites Reveals Effects of Protein Sequence Variation in Arabidopsis thaliana

    NARCIS (Netherlands)

    Valentim, F.L.; Neven, F.; Boyen, P.; Dijk, van A.D.J.

    2012-01-01

    The specificity of protein-protein interactions is encoded in those parts of the sequence that compose the binding interface. Therefore, understanding how changes in protein sequence influence interaction specificity, and possibly the phenotype, requires knowing the location of binding sites in thos

  11. Protein-protein binding detection with nanoparticle photonic crystal enhanced microscopy (NP-PCEM).

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    Zhuo, Yue; Tian, Limei; Chen, Weili; Yu, Hojeong; Singamaneni, Srikanth; Cunningham, Brian T

    2014-01-01

    We demonstrate a novel microscopy-based biosensing approach that utilizes a photonic crystal (PC) surface to detect protein-protein binding with the functionalized nanoparticles as tags. This imaging approach utilizes the measurement of localized shifts in the resonant wavelength and resonant reflection magnitude from the PC biosensor in the presence of individual nanoparticles. Moreover, it substantially increases the sensitivity of the imaging approach through tunable localized surface plasmon resonant frequency of the nanoparticle matching with the resonance of the PC biosensor. Experimental demonstrations of photonic crystal enhanced microscopy (PCEM) imaging with single nanoparticle resolution are supported by Finite-Difference Time-Domain (FDTD) computer simulations. The ability to detect the surface adsorption of individual nanoparticles as tags offers a route to single molecule biosensing with photonic crystal biosensor in the future.

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

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    Cao, Huaiqing; Huang, Yongqi; Liu, Zhirong

    2016-07-01

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

  13. Theoretical studies of protein-protein and protein-DNA binding rates

    Science.gov (United States)

    Alsallaq, Ramzi A.

    Proteins are folded chains of amino acids. Some of the amino acids (e.g. Lys, Arg, His, Asp, and Glu) carry charges under physiological conditions. Proteins almost always function through binding to other proteins or ligands, for example barnase is a ribonuclease protein, found in the bacterium Bacillus amyloliquefaceus. Barnase degrades RNA by hydrolysis. For the bacterium to inhibit the potentially lethal action of Barnase within its own cell it co-produces another protein called barstar which binds quickly, and tightly, to barnase. The biological function of this binding is to block the active site of barnase. The speeds (rates) at which proteins associate are vital to many biological processes. They span a wide range (from less than 103 to 108 M-1s-1 ). Rates greater than ˜ 106 M -1s-1 are typically found to be manifestations of enhancements by long-range electrostatic interactions between the associating proteins. A different paradigm appears in the case of protein binding to DNA. The rate in this case is enhanced through attractive surface potential that effectively reduces the dimensionality of the available search space for the diffusing protein. This thesis presents computational and theoretical models on the rate of association of ligands/proteins to other proteins or DNA. For protein-protein association we present a general strategy for computing protein-protein rates of association. The main achievements of this strategy is the ability to obtain a stringent reaction criteria based on the landscape of short-range interactions between the associating proteins, and the ability to compute the effect of the electrostatic interactions on the rates of association accurately using the best known solvers for Poisson-Boltzmann equation presently available. For protein-DNA association we present a mathematical model for proteins targeting specific sites on a circular DNA topology. The main achievements are the realization that a linear DNA with reflecting ends

  14. 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...

  15. Discovery of binding proteins for a protein target using protein-protein docking-based virtual screening.

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

    2014-10-01

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

  16. Bovine peptidoglycan recognition protein-S: antimicrobial activity, localization, secretion, and binding properties.

    Science.gov (United States)

    Tydell, C Chace; Yuan, Jun; Tran, Patti; Selsted, Michael E

    2006-01-15

    Peptidoglycan (PGN) recognition proteins (PGRPs) are pattern recognition molecules of innate immunity that are conserved from insects to humans. Various PGRPs are reported to have diverse functions: they bind bacterial molecules, digest PGN, and are essential to the Toll pathway in Drosophila. One family member, bovine PGN recognition protein-S (bPGRP-S), has been found to bind and kill microorganisms in a PGN-independent manner, raising questions about the identity of the bPGRP-S ligand. Addressing this, we have determined the binding and microbicidal properties of bPGRP-S in a range of solutions approximating physiologic conditions. In this study we show that bPGRP-S interacts with other bacterial components, including LPS and lipoteichoic acid, with higher affinities than for PCP, as determined by their abilities to inhibit bPGRP-S-mediated killing of bacteria. Where and how PGRPs act in vivo is not yet clear. Using Immunogold electron microscopy, PGRP-S was localized to the dense/large granules of naive neutrophils, which contain the oxygen-independent bactericidal proteins of these cells, and to the neutrophil phagolysosome. In addition, Immunogold staining and secretion studies demonstrate that neutrophils secrete PGRP-S when exposed to bacteria. Bovine PGRP-S can mediate direct lysis of heat-killed bacteria; however, PGRP-S-mediated killing of bacteria is independent of this activity. Evidence that bPGRP-S has multiple activities and affinity to several bacterial molecules challenges the assumption that the PGRP family of proteins recapitulates the evolution of TLRs. Mammalian PGRPs do not have a single antimicrobial activity against a narrow range of target organisms; rather, they are generalists in their affinity and activity.

  17. Interactome-wide prediction of protein-protein binding sites reveals effects of protein sequence variation in Arabidopsis thaliana.

    Directory of Open Access Journals (Sweden)

    Felipe Leal Valentim

    Full Text Available The specificity of protein-protein interactions is encoded in those parts of the sequence that compose the binding interface. Therefore, understanding how changes in protein sequence influence interaction specificity, and possibly the phenotype, requires knowing the location of binding sites in those sequences. However, large-scale detection of protein interfaces remains a challenge. Here, we present a sequence- and interactome-based approach to mine interaction motifs from the recently published Arabidopsis thaliana interactome. The resultant proteome-wide predictions are available via www.ab.wur.nl/sliderbio and set the stage for further investigations of protein-protein binding sites. To assess our method, we first show that, by using a priori information calculated from protein sequences, such as evolutionary conservation and residue surface accessibility, we improve the performance of interface prediction compared to using only interactome data. Next, we present evidence for the functional importance of the predicted sites, which are under stronger selective pressure than the rest of protein sequence. We also observe a tendency for compensatory mutations in the binding sites of interacting proteins. Subsequently, we interrogated the interactome data to formulate testable hypotheses for the molecular mechanisms underlying effects of protein sequence mutations. Examples include proteins relevant for various developmental processes. Finally, we observed, by analysing pairs of paralogs, a correlation between functional divergence and sequence divergence in interaction sites. This analysis suggests that large-scale prediction of binding sites can cast light on evolutionary processes that shape protein-protein interaction networks.

  18. Protein-protein interactions: general trends in the relationship between binding affinity and interfacial buried surface area.

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    Chen, Jieming; Sawyer, Nicholas; Regan, Lynne

    2013-04-01

    Protein-protein interactions play key roles in many cellular processes and their affinities and specificities are finely tuned to the functions they perform. Here, we present a study on the relationship between binding affinity and the size and chemical nature of protein-protein interfaces. Our analysis focuses on heterodimers and includes curated structural and thermodynamic data for 113 complexes. We observe a direct correlation between binding affinity and the amount of surface area buried at the interface. For a given amount of surface area buried, the binding affinity spans four orders of magnitude in terms of the dissociation constant (Kd ). Across the entire dataset, we observe no obvious relationship between binding affinity and the chemical composition of the interface. We also calculate the free energy per unit surface area buried, or "surface energy density," of each heterodimer. For interfacial surface areas between 500 and 2000 Å(2) , the surface energy density decreases as the buried surface area increases. As the buried surface area increases beyond about 2000 Å(2) , the surface energy density levels off to a constant value. We believe that these analyses and data will be useful for researchers with an interest in understanding, designing or inhibiting protein-protein interfaces.

  19. Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles.

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    Brender, Jeffrey R; Zhang, Yang

    2015-10-01

    The formation of protein-protein complexes is essential for proteins to perform their physiological functions in the cell. Mutations that prevent the proper formation of the correct complexes can have serious consequences for the associated cellular processes. Since experimental determination of protein-protein binding affinity remains difficult when performed on a large scale, computational methods for predicting the consequences of mutations on binding affinity are highly desirable. We show that a scoring function based on interface structure profiles collected from analogous protein-protein interactions in the PDB is a powerful predictor of protein binding affinity changes upon mutation. As a standalone feature, the differences between the interface profile score of the mutant and wild-type proteins has an accuracy equivalent to the best all-atom potentials, despite being two orders of magnitude faster once the profile has been constructed. Due to its unique sensitivity in collecting the evolutionary profiles of analogous binding interactions and the high speed of calculation, the interface profile score has additional advantages as a complementary feature to combine with physics-based potentials for improving the accuracy of composite scoring approaches. By incorporating the sequence-derived and residue-level coarse-grained potentials with the interface structure profile score, a composite model was constructed through the random forest training, which generates a Pearson correlation coefficient >0.8 between the predicted and observed binding free-energy changes upon mutation. This accuracy is comparable to, or outperforms in most cases, the current best methods, but does not require high-resolution full-atomic models of the mutant structures. The binding interface profiling approach should find useful application in human-disease mutation recognition and protein interface design studies.

  20. Direct protein-protein interactions and substrate channeling between cellular retinoic acid binding proteins and CYP26B1.

    Science.gov (United States)

    Nelson, Cara H; Peng, Chi-Chi; Lutz, Justin D; Yeung, Catherine K; Zelter, Alex; Isoherranen, Nina

    2016-08-01

    Cellular retinoic acid binding proteins (CRABPs) bind all-trans-retinoic acid (atRA) tightly. This study aimed to determine whether atRA is channeled directly to cytochrome P450 (CYP) CYP26B1 by CRABPs, and whether CRABPs interact directly with CYP26B1. atRA bound to CRABPs (holo-CRABP) was efficiently metabolized by CYP26B1. Isotope dilution experiments showed that delivery of atRA to CYP26B1 in solution was similar with or without CRABP. Holo-CRABPs had higher affinity for CYP26B1 than free atRA, but both apo-CRABPs inhibited the formation of 4-OH-RA by CYP26B1. Similar protein-protein interactions between soluble binding proteins and CYPs may be important for other lipophilic CYP substrates.

  1. Protein-protein binding before and after photo-modification of albumin

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    Rozinek, Sarah C.; Glickman, Randolph D.; Thomas, Robert J.; Brancaleon, Lorenzo

    2016-03-01

    Bioeffects of directed-optical-energy encompass a wide range of applications. One aspect of photochemical interactions involves irradiating a photosensitizer with visible light in order to induce protein unfolding and consequent changes in function. In the past, irradiation of several dye-protein combinations has revealed effects on protein structure. Beta lactoglobulin, human serum albumin (HSA) and tubulin have all been photo-modified with meso-tetrakis(4- sulfonatophenyl)porphyrin (TSPP) bound, but only in the case of tubulin has binding caused a verified loss of biological function (loss of ability to form microtubules) as a result of this light-induced structural change. The current work questions if the photo-induced structural changes that occur to HSA, are sufficient to disable its biological function of binding to osteonectin. The albumin-binding protein, osteonectin, is about half the molecular weight of HSA, so the two proteins and their bound product can be separated and quantified by size exclusion high performance liquid chromatography. TSPP was first bound to HSA and irradiated, photo-modifying the structure of HSA. Then native HSA or photo-modified HSA (both with TSPP bound) were compared, to assess loss in HSA's innate binding ability as a result of light-induced structure modification.

  2. 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...... results were compared with a residue-pair potential scoring function (RPScore) and an atomic-detailed scoring function (Zrank). We have combined knowledge-based potentials to score protein-protein poses of decoys of complexes classified either as transient or as permanent protein-protein interactions...

  3. Structural basis of heparin binding to camel peptidoglycan recognition protein-S

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    Sharma, Pradeep; Dube, Divya; Sinha, Mau; Dey, Sharmistha; Kaur, Punit; Sharma, Sujata; Singh, Tej P.

    2012-01-01

    Short peptidoglycan recognition protein (PGRP-S) is a member of the innate immunity system in mammals. PGRP-S from Camelus dromedarius (CPGRP-S) is found to be highly potent against bacterial infections. It is capable of binding to a wide range of pathogen-associated molecular patterns (PAMPs) including lipopolysaccharide (LPS), lipoteichoic acid (LTA) and peptidoglycan (PGN). The heparin-like polysaccharides have also been observed in some bacteria such as the capsule of K5 Escherichia coli thus making them relevant for determining the nature of their interactions with CPGRP-S. The binding studies of CPGRP-S with heparin disaccharide in solution using surface plasmon resonance gave a value 3.3×10-7 M for the dissociation constant (Kd). The structure of the heparin bound CPGRP-S determined at 2.8Å resolution revealed the presence of a bound heparin molecule in the binding pocket of CPGRP-S. It was found anchored tightly to the protein with the help of several ionic and hydrogen bonded interactions. Three sulphate groups of heparin S1, S2 and S3 have been found to interact with residues, Arg-31, Lys-90, Thr- 97, Asn-99 Asn-140, Gln-150 and Arg-170 of CPGRP-S. The binding site includes two subsites, S-I and S-II with cleft-like structures. Heparin disaccharide is bound in subsite S-I. Previously determined structures of the complexes of CPGRP-S with LPS, LTA and PGN also showed that their glycan moieties were also held in subsite S-I indicating that heparin disaccharide also represents an important element for the recognition by CPGRP-S. PMID:22509483

  4. The ubiquitous octamer-binding protein(s) is sufficient for transcription of immunoglobulin genes.

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    Johnson, D G; Carayannopoulos, L; Capra, J D; Tucker, P W; Hanke, J H

    1990-03-01

    All immunoglobulin genes contain a conserved octanucleotide promoter element, ATGCAAAT, which has been shown to be required for their normal B-cell-specific transcription. Proteins that bind this octamer have been purified, and cDNAs encoding octamer-binding proteins have been cloned. Some of these proteins (referred to as OTF-2) are lymphoid specific, whereas at least one other, and possibly more (referred to as OTF-1), is found ubiquitously in all cell types. The exact role of these different proteins in directing the tissue-specific expression of immunoglobulin genes is unclear. We have identified two human pre-B-cell lines that contain extremely low levels of OTF-2 yet still express high levels of steady-state immunoglobulin heavy-chain mRNA in vivo and efficiently transcribe an immunoglobulin gene in vitro. Addition of a highly enriched preparation of OTF-1 made from one of these pre-B cells or from HeLa cells specifically stimulated in vitro transcription of an immunoglobulin gene. Furthermore, OFT-1 appeared to have approximately the same transactivation ability as OTF-2 when normalized for binding activity. These results suggest that OTF-1, without OTF-2, is sufficient for transcription of immunoglobulin genes and that OTF-2 alone is not responsible for the B-cell-specific regulation of immunoglobulin gene expression.

  5. The ubiquitous octamer-binding protein(s) is sufficient for transcription of immunoglobulin genes

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, D.G.; Carayannopoulos, L.; Capra, J.D.; Tucker, P.W. (Dept. of Microbiology, Southwestern Medical Center at Dallas, Dallas, TX (US)); Hanke, J.H. (Central Research, Dept. of Molecular Genetics, Pfizer, Inc., Groton, CT (US))

    1990-03-01

    All immunoglobulin genes contain a conserved octanucleotide promoter element, ATGCAAAT, which has been shown to be required for their normal B-cell-specific transcription. Proteins that bind this octamer have been purified, and cDNAs encoding octamer-binding proteins have been cloned. Some of these proteins (referred to as OTF-2) are lymphoid specific, whereas at least one other, and possibly more (referred to as OTF-1), is found ubiquitously in all cell types. The exact role of these different proteins in directing the tissue-specific expression of immunoglobulin genes is unclear. The authors have identified two human pre-B-cell lines that contain extremely low levels of OTF-2 yet still express high levels of steady-state immunoglobulin heavy-chain mRNA in vivo and efficiently transcribe an immunoglobulin gene in vitro. Addition of a highly enriched preparation of OTF-1 made from one of these pre-B cells or from HeLa cells specifically stimulated in vitro transcription of an immunoglobulin gene. Furthermore, OFT-1 appeared to have approximately the same transactivation ability as OTF-2 when normalized for binding activity. These results suggest that OTF-1, without OTF-2, is sufficient for transcription of immunoglobulin genes and that OTF-2 alone is not responsible for the B-cell-specific regulation of immunoglobulin gene expression.

  6. 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.

  7. Insights into cellulase-lignin non-specific binding revealed by computational redesign of the surface of green fluorescent protein: Protein Redesign to Lower Protein-lignin Binding

    Energy Technology Data Exchange (ETDEWEB)

    Haarmeyer, Carolyn N. [Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing Michigan 48824; Smith, Matthew D. [Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing Michigan 48824; Chundawat, Shishir P. S. [Great Lakes Bioenergy Research Center (GLBRC), Michigan State University, East Lansing Michigan; Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway New Jersey; Sammond, Deanne [Biosciences Center, National Renewable Energy Laboratory, Golden Colorado; Whitehead, Timothy A. [Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing Michigan 48824; Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing Michigan 48824

    2016-11-07

    Biological-mediated conversion of pretreated lignocellulosic biomass to biofuels and biochemicals is a promising avenue towards energy sustainability. However, a critical impediment to the commercialization of cellulosic biofuel production is the high cost of cellulase enzymes needed to deconstruct biomass into fermentable sugars. One major factor driving cost is cellulase adsorption and inactivation in the presence of lignin, yet we currently have a poor understanding of the protein structure-function relationships driving this adsorption. In this work, we have systematically investigated the role of protein surface potential on lignin adsorption using a model monomeric fluorescent protein. We have designed and experimentally characterized 16 model protein variants spanning the physiological range of net charge (-24 to +16 total charges) and total charge density (0.28 to 0.40 charges per sequence length) typical for natural proteins. Protein designs were expressed, purified, and subjected to in silico and in vitro biophysical measurements to evaluate the relationship between protein surface potential and lignin adsorption properties. The designs were comparable to model fluorescent protein in terms of thermostability and heterologous expression yield, although the majority of the designs unexpectedly formed homodimers. Protein adsorption to lignin was studied at two different temperatures using Quartz Crystal Microbalance with Dissipation Monitoring and a subtractive mass balance assay. We found a weak correlation between protein net charge and protein-binding capacity to lignin. No other single characteristic, including apparent melting temperature and 2nd virial coefficient, showed correlation with lignin binding. Analysis of an unrelated cellulase dataset with mutations localized to a family I carbohydrate-binding module showed a similar correlation between net charge and lignin binding capacity. Overall, our study provides strategies to identify highly active

  8. Understanding Protein-Protein Interactions Using Local Structural Features

    DEFF Research Database (Denmark)

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

    2013-01-01

    Protein-protein interactions (PPIs) play a relevant role among the different functions of a cell. Identifying the PPI network of a given organism (interactome) is useful to shed light on the key molecular mechanisms within a biological system. In this work, we show the role of structural features...... (loops and domains) to comprehend the molecular mechanisms of PPIs. A paradox in protein-protein binding is to explain how the unbound proteins of a binary complex recognize each other among a large population within a cell and how they find their best docking interface in a short timescale. We use...

  9. SCOWLP update: 3D classification of protein-protein, -peptide, -saccharide and -nucleic acid interactions, and structure-based binding inferences across folds

    Directory of Open Access Journals (Sweden)

    Schreiber Sven

    2011-10-01

    Full Text Available Abstract Background Protein interactions are essential for coordinating cellular functions. Proteomic studies have already elucidated a huge amount of protein-protein interactions that require detailed functional analysis. Understanding the structural basis of each individual interaction through their structural determination is necessary, yet an unfeasible task. Therefore, computational tools able to predict protein binding regions and recognition modes are required to rationalize putative molecular functions for proteins. With this aim, we previously created SCOWLP, a structural classification of protein binding regions at protein family level, based on the information obtained from high-resolution 3D protein-protein and protein-peptide complexes. Description We present here a new version of SCOWLP that has been enhanced by the inclusion of protein-nucleic acid and protein-saccharide interactions. SCOWLP takes interfacial solvent into account for a detailed characterization of protein interactions. In addition, the binding regions obtained per protein family have been enriched by the inclusion of predicted binding regions, which have been inferred from structurally related proteins across all existing folds. These inferences might become very useful to suggest novel recognition regions and compare structurally similar interfaces from different families. Conclusions The updated SCOWLP has new functionalities that allow both, detection and comparison of protein regions recognizing different types of ligands, which include other proteins, peptides, nucleic acids and saccharides, within a solvated environment. Currently, SCOWLP allows the analysis of predicted protein binding regions based on structure-based inferences across fold space. These predictions may have a unique potential in assisting protein docking, in providing insights into protein interaction networks, and in guiding rational engineering of protein ligands. The newly designed

  10. Structure-activity relationship of the peptide binding-motif mediating the BRCA2:RAD51 protein-protein interaction.

    Science.gov (United States)

    Scott, Duncan E; Marsh, May; Blundell, Tom L; Abell, Chris; Hyvönen, Marko

    2016-04-01

    RAD51 is a recombinase involved in the homologous recombination of double-strand breaks in DNA. RAD51 forms oligomers by binding to another molecule of RAD51 via an 'FxxA' motif, and the same recognition sequence is similarly utilised to bind BRCA2. We have tabulated the effects of mutation of this sequence, across a variety of experimental methods and from relevant mutations observed in the clinic. We use mutants of a tetrapeptide sequence to probe the binding interaction, using both isothermal titration calorimetry and X-ray crystallography. Where possible, comparison between our tetrapeptide mutational study and the previously reported mutations is made, discrepancies are discussed and the importance of secondary structure in interpreting alanine scanning and mutational data of this nature is considered.

  11. The First Residue of the PWWP Motif Modulates HATH Domain Binding, Stability, and Protein-Protein Interaction.

    Science.gov (United States)

    Hung, Yi-Lin; Lee, Hsia-Ju; Jiang, Ingjye; Lin, Shang-Chi; Lo, Wei-Cheng; Lin, Yi-Jan; Sue, Shih-Che

    2015-07-01

    Hepatoma-derived growth factor (hHDGF) and HDGF-related proteins (HRPs) contain conserved N-terminal HATH domains with a characteristic structural motif, namely the PWWP motif. The HATH domain has attracted attention because of its ability to bind with heparin/heparan sulfate, DNA, and methylated histone peptide. Depending on the sequence of the PWWP motif, HRP HATHs are classified into P-type (Pro-His-Trp-Pro) and A-type (Ala-His-Trp-Pro) forms. A-type HATH is highly unstable and tends to precipitate in solution. We replaced the Pro residue in P-type HATHHDGF with Ala and evaluated the influence on structure, dynamics, and ligand binding. Nuclear magnetic resonance (NMR) hydrogen/deuterium exchange and circular dichroism (CD) measurements revealed reduced stability. Analysis of NMR backbone (15)N relaxations (R1, R2, and nuclear Overhauser effect) revealed additional backbone dynamics in the interface between the β-barrel and the C-terminal helix bundle. The β1-β2 loop, where the AHWP sequence is located, has great structural flexibility, which aids HATH-HATH interaction through the loop. A-type HATH, therefore, shows a stronger tendency to aggregate when binding with heparin and DNA oligomers. This study defines the role of the first residue of the PWWP motif in modulating HATH domain stability and oligomer formation in binding.

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

    Institute of Scientific and Technical Information of China (English)

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

    2011-01-01

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

  13. Binding of Solvent Molecules to a Protein Surface in Binary Mixtures Follows a Competitive Langmuir Model.

    Science.gov (United States)

    Kulschewski, Tobias; Pleiss, Jürgen

    2016-09-06

    The binding of solvent molecules to a protein surface was modeled by molecular dynamics simulations of of Candida antarctica (C. antarctica) lipase B in binary mixtures of water, methanol, and toluene. Two models were analyzed: a competitive Langmuir model which assumes identical solvent binding sites with a different affinity toward water (KWat), methanol (KMet), and toluene (KTol) and a competitive Langmuir model with an additional interaction between free water and already bound water (KWatWat). The numbers of protein-bound molecules of both components of a binary mixture were determined for different compositions as a function of their thermodynamic activities in the bulk phase, and the binding constants were simultaneously fitted to the six binding curves (two components of three different mixtures). For both Langmuir models, the values of KWat, KMet, and KTol were highly correlated. The highest binding affinity was found for methanol, which was almost 4-fold higher than the binding affinities of water and toluene (KMet ≫ KWat ≈ KTol). Binding of water was dominated by the water-water interaction (KWatWat). Even for the three protein surface patches of highest water affinity, the binding affinity of methanol was 2-fold higher than water and 8-fold higher than toluene (KMet > KWat > KTol). The Langmuir model provides insights into the protein destabilizing mechanism of methanol which has a high binding affinity toward the protein surface. Thus, destabilizing solvents compete with intraprotein interactions and disrupt the tertiary structure. In contrast, benign solvents such as water or toluene have a low affinity toward the protein surface. Water is a special solvent: only few water molecules bind directly to the protein; most water molecules bind to already bound water molecules thus forming water patches. A quantitative mechanistic model of protein-solvent interactions that includes competition and miscibility of the components contributes a robust basis

  14. 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....

  15. Disruption of protein-protein interactions: design of a synthetic receptor that blocks the binding of cytochrome c to cytochrome c peroxidase.

    Science.gov (United States)

    Wei, Y; McLendon, G L; Hamilton, A D; Case, M A; Purring, C B; Lin, Q; Park, H S; Lee, C S; Yu, T

    2001-09-07

    Synthetic receptor 1 has been found via fluorescence titration to compete effectively with cytochrome c peroxidase for binding cytochrome c (Cc), forming 1:1 Cc:1 complex with a binding constant of (3 +/- 1) x 10(8) M-1, and to disrupt Cc: Apaf-1 complex, a key adduct in apoptosis.

  16. Phage phi 29 regulatory protein p4 stabilizes the binding of the RNA polymerase to the late promoter in a process involving direct protein-protein contacts.

    Science.gov (United States)

    Nuez, B; Rojo, F; Salas, M

    1992-12-01

    Transcription from the late promoter, PA3, of Bacillus subtilis phage phi 29 is activated by the viral regulatory protein p4. A kinetic analysis of the activation process has revealed that the role of protein p4 is to stabilize the binding of RNA polymerase to the promoter as a closed complex without significantly affecting further steps of the initiation process. Electrophoretic band-shift assays performed with a DNA fragment spanning only the protein p4 binding site showed that RNA polymerase could efficiently retard the complex formed by protein p4 bound to the DNA. Similarly, when a DNA fragment containing only the RNA polymerase-binding region of PA3 was used, p4 greatly stimulated the binding of RNA polymerase to the DNA. These results strongly suggest that p4 and RNA polymerase contact each other at the PA3 promoter. In the light of current knowledge of the p4 activation mechanism, we propose that direct contacts between the two proteins participate in the activation process.

  17. Reticulomics: Protein-Protein Interaction Studies with Two Plasmodesmata-Localized Reticulon Family Proteins Identify Binding Partners Enriched at Plasmodesmata, Endoplasmic Reticulum, and the Plasma Membrane.

    Science.gov (United States)

    Kriechbaumer, Verena; Botchway, Stanley W; Slade, Susan E; Knox, Kirsten; Frigerio, Lorenzo; Oparka, Karl; Hawes, Chris

    2015-11-01

    The endoplasmic reticulum (ER) is a ubiquitous organelle that plays roles in secretory protein production, folding, quality control, and lipid biosynthesis. The cortical ER in plants is pleomorphic and structured as a tubular network capable of morphing into flat cisternae, mainly at three-way junctions, and back to tubules. Plant reticulon family proteins (RTNLB) tubulate the ER by dimerization and oligomerization, creating localized ER membrane tensions that result in membrane curvature. Some RTNLB ER-shaping proteins are present in the plasmodesmata (PD) proteome and may contribute to the formation of the desmotubule, the axial ER-derived structure that traverses primary PD. Here, we investigate the binding partners of two PD-resident reticulon proteins, RTNLB3 and RTNLB6, that are located in primary PD at cytokinesis in tobacco (Nicotiana tabacum). Coimmunoprecipitation of green fluorescent protein-tagged RTNLB3 and RTNLB6 followed by mass spectrometry detected a high percentage of known PD-localized proteins as well as plasma membrane proteins with putative membrane-anchoring roles. Förster resonance energy transfer by fluorescence lifetime imaging microscopy assays revealed a highly significant interaction of the detected PD proteins with the bait RTNLB proteins. Our data suggest that RTNLB proteins, in addition to a role in ER modeling, may play important roles in linking the cortical ER to the plasma membrane.

  18. Conductometric monitoring of protein-protein interactions.

    Science.gov (United States)

    Spera, Rosanna; Festa, Fernanda; Bragazzi, Nicola L; Pechkova, Eugenia; LaBaer, Joshua; Nicolini, Claudio

    2013-12-06

    Conductometric monitoring of protein-protein and protein-sterol interactions is here proved feasible by coupling quartz crystal microbalance with dissipation monitoring (QCM_D) to nucleic acid programmable protein arrays (NAPPA). The conductance curves measured in NAPPA microarrays printed on quartz surface allowed the identification of binding events between the immobilized proteins and the query. NAPPA allows the immobilization on the quartz surface of a wide range of proteins and can be easily adapted to generate innumerous types of biosensors. Indeed multiple proteins on the same quartz crystal have been tested and envisaged proving the possibility of analyzing the same array for several distinct interactions. Two examples of NAPPA-based conductometer applications with clinical relevance are presented herein, the interaction between the transcription factors Jun and ATF2 and the interaction between Cytochrome P540scc and cholesterol.

  19. Protein docking prediction using predicted protein-protein interface

    Directory of Open Access Journals (Sweden)

    Li Bin

    2012-01-01

    Full Text Available Abstract Background Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. Results We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm, is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. Conclusion We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

  20. 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......Years of meticulous curation of scientific literature and increasingly reliable computational predictions have resulted in creation of vast databases of protein interaction data. Over the years, these repositories have become a basic framework in which experiments are analyzed and new directions...

  1. Anchored design of protein-protein interfaces.

    Directory of Open Access Journals (Sweden)

    Steven M Lewis

    Full Text Available BACKGROUND: Few existing protein-protein interface design methods allow for extensive backbone rearrangements during the design process. There is also a dichotomy between redesign methods, which take advantage of the native interface, and de novo methods, which produce novel binders. METHODOLOGY: Here, we propose a new method for designing novel protein reagents that combines advantages of redesign and de novo methods and allows for extensive backbone motion. This method requires a bound structure of a target and one of its natural binding partners. A key interaction in this interface, the anchor, is computationally grafted out of the partner and into a surface loop on the design scaffold. The design scaffold's surface is then redesigned with backbone flexibility to create a new binding partner for the target. Careful choice of a scaffold will bring experimentally desirable characteristics into the new complex. The use of an anchor both expedites the design process and ensures that binding proceeds against a known location on the target. The use of surface loops on the scaffold allows for flexible-backbone redesign to properly search conformational space. CONCLUSIONS AND SIGNIFICANCE: This protocol was implemented within the Rosetta3 software suite. To demonstrate and evaluate this protocol, we have developed a benchmarking set of structures from the PDB with loop-mediated interfaces. This protocol can recover the correct loop-mediated interface in 15 out of 16 tested structures, using only a single residue as an anchor.

  2. A general scheme for the estimation of oxygen binding energies on binary transition metal surface alloys

    DEFF Research Database (Denmark)

    Greeley, Jeffrey Philip; Nørskov, Jens Kehlet

    2005-01-01

    A simple scheme for the estimation of oxygen binding energies on transition metal surface alloys is presented. It is shown that a d-band center model of the alloy surfaces is a convenient and appropriate basis for this scheme; variations in chemical composition, strain effects, and ligand effects...... for the estimation of oxygen binding energies on a wide variety of transition metal alloys. (c) 2005 Elsevier B.V. All rights reserved....

  3. Models for the Binary Complex of Bacteriophage T4 Gp59 Helicase Loading Protein. GP32 Single-Stranded DNA-Binding Protein and Ternary Complex with Pseudo-Y Junction DNA

    Energy Technology Data Exchange (ETDEWEB)

    Hinerman, Jennifer M. [Univ. of Toledo, OH (United States); Dignam, J. David [Univ. of Toledo, OH (United States); Mueser, Timothy C. [Univ. of Toledo, OH (United States)

    2012-04-05

    The bacteriophage T4 gp59 helicase assembly protein (gp59) is required for loading of gp41 replicative helicase onto DNA protected by gp32 single-stranded DNA-binding protein. The gp59 protein recognizes branched DNA structures found at replication and recombination sites. Binding of gp32 protein (full-length and deletion constructs) to gp59 protein measured by isothermal titration calorimetry demonstrates that the gp32 protein C-terminal A-domain is essential for protein-protein interaction in the absence of DNA. Sedimentation velocity experiments with gp59 protein and gp32ΔB protein (an N-terminal B-domain deletion) show that these proteins are monomers but form a 1:1 complex with a dissociation constant comparable with that determined by isothermal titration calorimetry. Small angle x-ray scattering (SAXS) studies indicate that the gp59 protein is a prolate monomer, consistent with the crystal structure and hydrodynamic properties determined from sedimentation velocity experiments. SAXS experiments also demonstrate that gp32ΔB protein is a prolate monomer with an elongated A-domain protruding from the core. Moreover, fitting structures of gp59 protein and the gp32 core into the SAXS-derived molecular envelope supports a model for the gp59 protein-gp32ΔB protein complex. Our earlier work demonstrated that gp59 protein attracts full-length gp32 protein to pseudo-Y junctions. A model of the gp59 protein-DNA complex, modified to accommodate new SAXS data for the binary complex together with mutational analysis of gp59 protein, is presented in the accompanying article (Dolezal, D., Jones, C. E., Lai, X., Brister, J. R., Mueser, T. C., Nossal, N. G., and Hinton, D. M. (2012) J. Biol. Chem. 287, 18596–18607).

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

    Science.gov (United States)

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

    2015-01-01

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

  5. Regulation of ryanodine receptor RyR2 by protein-protein interactions: prediction of a PKA binding site on the N-terminal domain of RyR2 and its relation to disease causing mutations [v1; ref status: indexed, http://f1000r.es/4tw

    Directory of Open Access Journals (Sweden)

    Belinda Nazan Walpoth

    2015-01-01

    Full Text Available Protein-protein interactions are the key processes responsible for signaling and function in complex networks. Determining the correct binding partners and predicting the ligand binding sites in the absence of experimental data require predictive models. Hybrid models that combine quantitative atomistic calculations with statistical thermodynamics formulations are valuable tools for bioinformatics predictions. We present a hybrid prediction and analysis model for determining putative binding partners and interpreting the resulting correlations in the yet functionally uncharacterized interactions of the ryanodine RyR2 N-terminal domain. Using extensive docking calculations and libraries of hexameric peptides generated from regulator proteins of the RyR2 channel, we show that the residues 318-323 of protein kinase A, PKA, have a very high affinity for the N-terminal of RyR2. Using a coarse grained Elastic Net Model, we show that the binding site lies at the end of a pathway of evolutionarily conserved residues in RyR2. The two disease causing mutations are also on this path. The program for the prediction of the energetically responsive residues by the Elastic Net Model is freely available on request from the corresponding author.

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

    Energy Technology Data Exchange (ETDEWEB)

    Ozawa, Kiyoshi; Jergic, Slobodan; Crowther, Jeffrey A.; Thompson, Phillip R. [Australian National University, Research School of Chemistry (Australia); Wijffels, Gene [Queensland Bioscience Precinct, CSIRO Livestock Industries (Australia); Otting, Gottfried; Dixon, Nicholas A. [Australian National University, Research School of Chemistry (Australia)], E-mail: dixon@rsc.anu.edu.au

    2005-07-15

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

  7. Scaffolds for blocking protein-protein interactions.

    Science.gov (United States)

    Hershberger, Stefan J; Lee, Song-Gil; Chmielewski, Jean

    2007-01-01

    Due to the pivotal roles that protein-protein interactions play in a plethora of biological processes, the design of therapeutic agents targeting these interactions has become an attractive and important area of research. The development of such agents is faced with a variety of challenges. Nevertheless, considerable progress has been made in the design of proteomimetics capable of disrupting protein-protein interactions. Those inhibitors based on molecular scaffold designs hold considerable interest because of the ease of variation in regard to their displayed functionality. In particular, protein surface mimetics, alpha-helical mimetics, beta-sheet/beta-strand mimetics, as well as beta-turn mimetics have successfully modulated protein-protein interactions involved in such diseases as cancer and HIV. In this review, current progress in the development of molecular scaffolds designed for the disruption of protein-protein interactions will be discussed with an emphasis on those active against biological targets.

  8. 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.

  9. Uranyl(VI) nitrate salts: modeling thermodynamic properties using the binding mean spherical approximation theory and determination of "fictive" binary data.

    Science.gov (United States)

    Ruas, Alexandre; Bernard, Olivier; Caniffi, Barbara; Simonin, Jean-Pierre; Turq, Pierre; Blum, Lesser; Moisy, Philippe

    2006-02-23

    This work is aimed at a description of the thermodynamic properties of highly concentrated aqueous solutions of uranyl nitrate at 25 degrees C. A new resolution of the binding mean spherical approximation (BIMSA) theory, taking into account 1-1 and also 1-2 complex formation, is developed and used to reproduce, from a simple procedure, experimental uranyl nitrate osmotic coefficient variation with concentration. For better consistency of the theory, binary uranyl perchlorate and chloride osmotic coefficients are also calculated. Comparison of calculated and experimental values is made. The possibility of regarding the ternary system UO(2)(NO(3))(2)/HNO(3)/H(2)O as a "simple" solution (in the sense of Zdanovskii, Stokes, and Robinson) is examined from water activity and density measurements. Also, an analysis of existing uranyl nitrate binary data is proposed and compared with our obtained data. On the basis of the concept of "simple" solution, values for density and water activity for the binary system UO(2)(NO(3))(2)/H(2)O are proposed in a concentration range on which uranyl nitrate precipitates from measurements on concentrated solutions of the ternary system UO(2)(NO(3))(2)/HNO(3)/H(2)O. This new set of binary data is "fictive" in the sense that the real binary system is not stable chemically. Finally, a new, interesting predictive capability of the BIMSA theory is shown.

  10. A holistic molecular docking approach for predicting protein-protein complex structure

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    A holistic protein-protein molecular docking approach,HoDock,was established,composed of such steps as binding site prediction,initial complex structure sampling,refined complex structure sampling,structure clustering,scoring and final structure selection.This article explains the detailed steps and applications for CAPRI Target 39.The CAPRI result showed that three predicted binding site residues,A191HIS,B512ARG and B531ARG,were correct,and there were five submitted structures with a high fraction of correct receptor-ligand interface residues,indicating that this docking approach may improve prediction accuracy for protein-protein complex structures.

  11. SwarmDock and the Use of Normal Modes in Protein-Protein Docking

    Directory of Open Access Journals (Sweden)

    Paul A. Bates

    2010-09-01

    Full Text Available Here is presented an investigation of the use of normal modes in protein-protein docking, both in theory and in practice. Upper limits of the ability of normal modes to capture the unbound to bound conformational change are calculated on a large test set, with particular focus on the binding interface, the subset of residues from which the binding energy is calculated. Further, the SwarmDock algorithm is presented, to demonstrate that the modelling of conformational change as a linear combination of normal modes is an effective method of modelling flexibility in protein-protein docking.

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

    Directory of Open Access Journals (Sweden)

    Amin R Mazloom

    2011-12-01

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

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

    Science.gov (United States)

    Kandel, Sylvie E; Lampe, Jed N

    2014-09-15

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

  14. Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin.

    Directory of Open Access Journals (Sweden)

    Julian E Fuchs

    Full Text Available Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm "dynamics govern specificity" might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design.

  15. Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin.

    Science.gov (United States)

    Fuchs, Julian E; Huber, Roland G; Waldner, Birgit J; Kahler, Ursula; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R

    2015-01-01

    Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm "dynamics govern specificity" might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design.

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

    Science.gov (United States)

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

    2011-06-01

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

  17. Uranyl(VI) nitrate salts: Modeling thermodynamic properties using the binding mean spherical approximation theory and determination of 'fictive' binary data

    Energy Technology Data Exchange (ETDEWEB)

    Ruas, Alexandre; Bernard, Olivier; Caniffi, Barbara; Simonin, Jean-Pierre; Turq, Pierre; Blum, Lesser; Moisy, Philippe [CEA-Valrho Marcoule, DEN/DRCP/SCPS/LCA, Bat 399, BP 17171, 30207 Bagnols-sur-Ceze Cedex (France); Laboratoire LI2C (UMR 7612), Universite P. M. Curie, Boite No. 51, 4 Place Jussieu, 75252 Paris Cedex 05 (France); Department of Physics, POB 23343, University of Puerto Rico, Rio Pedras, Puerto Rico 00931-3343 (United States)

    2006-07-01

    This work is aimed at a description of the thermodynamic properties of highly concentrated aqueous solutions of uranyl nitrate at 25 degrees C. A new resolution of the binding mean spherical approximation (BIMSA) theory, taking into account 1-1 and also 1-2 complex formation, is developed and used to reproduce, from a simple procedure, experimental uranyl nitrate osmotic coefficient variation with concentration. For better consistency of the theory, binary uranyl perchlorate and chloride osmotic coefficients are also calculated. Comparison of calculated and experimental values is made. The possibility of regarding the ternary system UO{sub 2}(NO{sub 3}){sub 2}/HNO{sub 3}/H{sub 2}O as a 'simple' solution (in the sense of Zdanovskii, Stokes, and Robinson) is examined from water activity and density measurements. Also, an analysis of existing uranyl nitrate binary data is proposed and compared with our obtained data. On the basis of the concept of 'simple' solution, values for density and water activity for the binary system UO{sub 2}(NO{sub 3}){sub 2}/H{sub 2}O are proposed in a concentration range on which uranyl nitrate precipitates from measurements on concentrated solutions of the ternary System UO{sub 2}(NO{sub 3}){sub 2}/HNO{sub 3}/H{sub 2}O. This new set of binary data is 'fictive' in the sense that the real binary system is not stable chemically. Finally, a new, interesting predictive capability of the BIMSA theory is shown. (authors)

  18. Pathogen mimicry of host protein-protein interfaces modulates immunity.

    Science.gov (United States)

    Guven-Maiorov, Emine; Tsai, Chung-Jung; Nussinov, Ruth

    2016-10-01

    Signaling pathways shape and transmit the cell's reaction to its changing environment; however, pathogens can circumvent this response by manipulating host signaling. To subvert host defense, they beat it at its own game: they hijack host pathways by mimicking the binding surfaces of host-encoded proteins. For this, it is not necessary to achieve global protein homology; imitating merely the interaction surface is sufficient. Different protein folds often interact via similar protein-protein interface architectures. This similarity in binding surfaces permits the pathogenic protein to compete with a host target protein. Thus, rather than binding a host-encoded partner, the host protein hub binds the pathogenic surrogate. The outcome can be dire: rewiring or repurposing the host pathways, shifting the cell signaling landscape and consequently the immune response. They can also cause persistent infections as well as cancer by modulating key signaling pathways, such as those involving Ras. Mapping the rewired host-pathogen 'superorganism' interaction network - along with its structural details - is critical for in-depth understanding of pathogenic mechanisms and developing efficient therapeutics. Here, we overview the role of molecular mimicry in pathogen host evasion as well as types of molecular mimicry mechanisms that emerged during evolution.

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

    Directory of Open Access Journals (Sweden)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-01-01

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

  1. Evolvability of yeast protein-protein interaction interfaces.

    Science.gov (United States)

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

    2012-06-22

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

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

    Institute of Scientific and Technical Information of China (English)

    Mahmood A. Mahdavi; Yen-Han Lin

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Melody G Campbell

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

  4. Interface-resolved network of protein-protein interactions.

    Directory of Open Access Journals (Sweden)

    Margaret E Johnson

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

  5. Spectroscopic and nano-molecular modeling investigation on the binary and ternary bindings of colchicine and lomefloxacin to Human serum albumin with the viewpoint of multi-drug therapy

    Energy Technology Data Exchange (ETDEWEB)

    Chamani, J., E-mail: Chamani@ibb.ut.ac.i [Department of Biology, Faculty of Sciences, Islamic Azad University-Mashhad Branch, Mashhad (Iran, Islamic Republic of); Asoodeh, A. [Department of Chemistry, Faculty of Sciences, Ferdowsi University of Mashhad, Mashhad (Iran, Islamic Republic of); Homayoni-Tabrizi, M. [Department of Biology, Faculty of Sciences, Islamic Azad University-Mashhad Branch, Mashhad (Iran, Islamic Republic of); Amiri Tehranizadeh, Z.; Baratian, A.; Saberi, M.R. [Medical Chemistry Department, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad (Iran, Islamic Republic of); Gharanfoli, M. [Department of Development Biology, Culture and Science University, Tehran (Iran, Islamic Republic of)

    2010-12-15

    Combination of several drugs is often necessary especially during long-term therapy. The competitive binding drugs can cause a decrease in the amount of drug bound to protein and increase the biological active fraction of the drug. The aim of this study is to analyze the interactions of Lomefloxacin (LMF) and Colchicine (COL) with human serum albumin (HSA) and to evaluate the mechanism of simultaneous binding of LMF and COL to protein. Fluorescence analysis was used to estimate the effect of drugs on the protein fluorescence and to define the binding and quenching properties of drugs-HSA complexes. The binding sites for LMF and COL were identified in tertiary structure of HSA with the use of spectrofluorescence analysis. The analysis of fluorescence quenching of HSA in the binary and ternary systems show that LMF does not affect the complex formed between COL and HSA. On the contrary, COL decreases the interaction between LMF and HSA. The results of synchronous fluorescence, resonance light scattering and circular dichroism spectra of binary and ternary systems show that binding of LMF and COL to HSA can induce micro-environmental and conformational changes in HSA. The simultaneous presence of LMF and COL in binding to HSA should be taken into account in the multi-drug therapy, and necessity of using a monitoring therapy owning to the possible increase of the uncontrolled toxic effects. Molecular modeling of the possible binding sites of LMF and COL in binary and ternary systems to HSA confirms the spectroscopic results.

  6. Experimental determination of water activity for binary aqueous cerium(III) ionic solutions: application to an assessment of the predictive capability of the binding mean spherical approximation model.

    Science.gov (United States)

    Ruas, Alexandre; Simonin, Jean-Pierre; Turq, Pierre; Moisy, Philippe

    2005-12-08

    This work is aimed at a description of the thermodynamic properties of actinide salt solutions at high concentration. The predictive capability of the binding mean spherical approximation (BIMSA) theory to describe the thermodynamic properties of electrolytes is assessed in the case of aqueous solutions of lanthanide(III) nitrate and chloride salts. Osmotic coefficients of cerium(III) nitrate and chloride were calculated from other lanthanide(III) salts properties. In parallel, concentrated binary solutions of cerium nitrate were prepared in order to measure experimentally its water activity and density as a function of concentration, at 25 degrees C. Water activities of several binary solutions of cerium chloride were also measured to check existing data on this salt. Then, the properties of cerium chloride and cerium nitrate solutions were compared within the BIMSA model. Osmotic coefficient values for promethium nitrate and promethium chloride given by this theory are proposed. Finally, water activity measurements were made to examine the fact that the ternary system Ce(NO3)3/HNO3/H2O and the quaternary system Ce(NO3)3/HNO3/N2H5NO3/H2O may be regarded as "simple solutions" (in the sense of Zdanovskii and Mikulin).

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

    Science.gov (United States)

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

    2015-01-05

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

  8. Protopia: a protein-protein interaction tool

    Science.gov (United States)

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

    2009-01-01

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

  9. Alternative protein-protein interfaces are frequent exceptions.

    Directory of Open Access Journals (Sweden)

    Tobias Hamp

    Full Text Available The intricate molecular details of protein-protein interactions (PPIs are crucial for function. Therefore, measuring the same interacting protein pair again, we expect the same result. This work measured the similarity in the molecular details of interaction for the same and for homologous protein pairs between different experiments. All scores analyzed suggested that different experiments often find exceptions in the interfaces of similar PPIs: up to 22% of all comparisons revealed some differences even for sequence-identical pairs of proteins. The corresponding number for pairs of close homologs reached 68%. Conversely, the interfaces differed entirely for 12-29% of all comparisons. All these estimates were calculated after redundancy reduction. The magnitude of interface differences ranged from subtle to the extreme, as illustrated by a few examples. An extreme case was a change of the interacting domains between two observations of the same biological interaction. One reason for different interfaces was the number of copies of an interaction in the same complex: the probability of observing alternative binding modes increases with the number of copies. Even after removing the special cases with alternative hetero-interfaces to the same homomer, a substantial variability remained. Our results strongly support the surprising notion that there are many alternative solutions to make the intricate molecular details of PPIs crucial for function.

  10. 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......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...

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

    Directory of Open Access Journals (Sweden)

    Fernández-Recio Juan

    2008-10-01

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

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

    Science.gov (United States)

    Peri, Claudio; Morra, Giulia; Colombo, Giorgio

    2016-04-01

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

  13. Composition of Overlapping Protein-Protein and Protein-Ligand Interfaces.

    Directory of Open Access Journals (Sweden)

    Ruzianisra Mohamed

    Full Text Available Protein-protein interactions (PPIs play a major role in many biological processes and they represent an important class of targets for therapeutic intervention. However, targeting PPIs is challenging because often no convenient natural substrates are available as starting point for small-molecule design. Here, we explored the characteristics of protein interfaces in five non-redundant datasets of 174 protein-protein (PP complexes, and 161 protein-ligand (PL complexes from the ABC database, 436 PP complexes, and 196 PL complexes from the PIBASE database and a dataset of 89 PL complexes from the Timbal database. In all cases, the small molecule ligands must bind at the respective PP interface. We observed similar amino acid frequencies in all three datasets. Remarkably, also the characteristics of PP contacts and overlapping PL contacts are highly similar.

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

    Institute of Scientific and Technical Information of China (English)

    代启国; 郭茂祖; 刘晓燕; 滕志霞; 王春宇

    2014-01-01

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

  15. From the Cover: Toward a protein-protein interaction map of the budding yeast: A comprehensive system to examine two-hybrid interactions in all possible combinations between the yeast proteins

    Science.gov (United States)

    Ito, Takashi; Tashiro, Kosuke; Muta, Shigeru; Ozawa, Ritsuko; Chiba, Tomoko; Nishizawa, Mayumi; Yamamoto, Kiyoshi; Kuhara, Satoru; Sakaki, Yoshiyuki

    2000-02-01

    Protein-protein interactions play pivotal roles in various aspects of the structural and functional organization of the cell, and their complete description is indispensable to thorough understanding of the cell. As an approach toward this goal, here we report a comprehensive system to examine two-hybrid interactions in all of the possible combinations between proteins of Saccharomyces cerevisiae. We cloned all of the yeast ORFs individually as a DNA-binding domain fusion ("bait") in a MATa strain and as an activation domain fusion ("prey") in a MATα strain, and subsequently divided them into pools, each containing 96 clones. These bait and prey clone pools were systematically mated with each other, and the transformants were subjected to strict selection for the activation of three reporter genes followed by sequence tagging. Our initial examination of ≈4 × 106 different combinations, constituting ≈10% of the total to be tested, has revealed 183 independent two-hybrid interactions, more than half of which are entirely novel. Notably, the obtained binary data allow us to extract more complex interaction networks, including the one that may explain a currently unsolved mechanism for the connection between distinct steps of vesicular transport. The approach described here thus will provide many leads for integration of various cellular functions and serve as a major driving force in the completion of the protein-protein interaction map.

  16. Measuring protein-protein and protein-nucleic Acid interactions by biolayer interferometry.

    Science.gov (United States)

    Sultana, Azmiri; Lee, Jeffrey E

    2015-01-01

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

  17. New approach for predicting protein-protein interactions

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

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

  18. 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. .

  19. A Bayesian Estimator of Protein-Protein Association Probabilities

    Energy Technology Data Exchange (ETDEWEB)

    Gilmore, Jason M.; Auberry, Deanna L.; Sharp, Julia L.; White, Amanda M.; Anderson, Kevin K.; Daly, Don S.

    2008-07-01

    The Bayesian Estimator of Protein-Protein Association Probabilities (BEPro3) is a software tool for estimating probabilities of protein-protein association between bait and prey protein pairs using data from multiple-bait, multiple-replicate, protein pull-down LC-MS assay experiments. BEPro3 is open source software that runs on both Windows XP and Mac OS 10.4 or newer versions, and is freely available from http://www.pnl.gov/statistics/BEPro3.

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

    Science.gov (United States)

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

    2011-01-01

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

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

    Science.gov (United States)

    Dukare, Sandeep; Klempnauer, Karl-Heinz

    2016-07-01

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

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

    DEFF Research Database (Denmark)

    Lund, Christian Have

    GALACTURONOSYLTRANSFERASE1 (GAUT1) and GAUT7 has beesn identified and is essential for pectin biosynthesis. Interestingly, GAUT1 has been shown to be proteolytic processed from its transmembrane anchor domain and its catalytic domain is retained by GAUT7, thus ensuring biosynthesis of HG in the Golgi apparatus. Many...... methods exist in identifying protein-protein interaction (PPI) but many of these are developed for other organisms than plants and are most applicable for PPI detection in other organelles than the Golgi apparatus where pectin biosynthesis occurs. In this work, different PPI detection methods are examined...... 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...

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

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

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

  4. A second-generation protein-protein interaction network of Helicobacter pylori.

    Science.gov (United States)

    Häuser, Roman; Ceol, Arnaud; Rajagopala, Seesandra V; Mosca, Roberto; Siszler, Gabriella; Wermke, Nadja; Sikorski, Patricia; Schwarz, Frank; Schick, Matthias; Wuchty, Stefan; Aloy, Patrick; Uetz, Peter

    2014-05-01

    Helicobacter pylori infections cause gastric ulcers and play a major role in the development of gastric cancer. In 2001, the first protein interactome was published for this species, revealing over 1500 binary protein interactions resulting from 261 yeast two-hybrid screens. Here we roughly double the number of previously published interactions using an ORFeome-based, proteome-wide yeast two-hybrid screening strategy. We identified a total of 1515 protein-protein interactions, of which 1461 are new. The integration of all the interactions reported in H. pylori results in 3004 unique interactions that connect about 70% of its proteome. Excluding interactions of promiscuous proteins we derived from our new data a core network consisting of 908 interactions. We compared our data set to several other bacterial interactomes and experimentally benchmarked the conservation of interactions using 365 protein pairs (interologs) of E. coli of which one third turned out to be conserved in both species.

  5. 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

  6. Bayesian Estimator of Protein-Protein Association Probabilities

    Energy Technology Data Exchange (ETDEWEB)

    2008-05-28

    The Bayesian Estimator of Protein-Protein Association Probabilities (BEPro3) is a software tool for estimating probabilities of protein-protein association between bait and prey protein pairs using data from multiple-bait, multiple-replicate, protein LC-MS/MS affinity isolation experiments. BEPro3 is public domain software, has been tested on Windows XP and version 10.4 or newer of the Mac OS 10.4, and is freely available. A user guide, example dataset with analysis and additional documentation are included with the BEPro3 download.

  7. 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

    2015-01-01

    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.

  8. Characterization of Protein-Protein Interfaces through a Protein Contact Network Approach.

    Science.gov (United States)

    Di Paola, Luisa; Platania, Chiara Bianca Maria; Oliva, Gabriele; Setola, Roberto; Pascucci, Federica; Giuliani, Alessandro

    2015-01-01

    Anthrax toxin comprises three different proteins, jointly acting to exert toxic activity: a non-toxic protective agent (PA), toxic edema factor (EF), and lethal factor (LF). Binding of PA to anthrax receptors promotes oligomerization of PA, binding of EF and LF, and then endocytosis of the complex. Homomeric forms of PA, complexes of PA bound to LF and to the endogenous receptor capillary morphogenesis gene 2 (CMG2) were analyzed. In this work, we characterized protein-protein interfaces (PPIs) and identified key residues at PPIs of complexes, by means of a protein contact network (PCN) approach. Flexibility and global and local topological properties of each PCN were computed. The vulnerability of each PCN was calculated using different node removal strategies, with reference to specific PCN topological descriptors, such as participation coefficient, contact order, and degree. The participation coefficient P, the topological descriptor of the node's ability to intervene in protein inter-module communication, was the key descriptor of PCN vulnerability of all structures. High P residues were localized both at PPIs and other regions of complexes, so that we argued an allosteric mechanism in protein-protein interactions. The identification of residues, with key role in the stability of PPIs, has a huge potential in the development of new drugs, which would be designed to target not only PPIs but also residues localized in allosteric regions of supramolecular complexes.

  9. The Development and Characterization of Protein-Based Stationary Phases for Studying Drug-Protein and Protein-Protein Interactions

    OpenAIRE

    Sanghvi, Mitesh; Moaddel, Ruin; Wainer, Irving W.

    2011-01-01

    Protein-based liquid chromatography stationary phases are used in bioaffinity chromatography for studying drug-protein interactions, the determination of binding affinities, competitive and allosteric interactions, as well as for studying protein-protein interactions. This review addresses the development and characterization of protein-based stationary phase, and the application of these phases using frontal and zonal chromatography techniques. The approach will be illustrated using immobili...

  10. Coarse-grain modelling of protein-protein interactions

    NARCIS (Netherlands)

    Baaden, Marc; Marrink, Siewert J.

    2013-01-01

    Here, we review recent advances towards the modelling of protein-protein interactions (PPI) at the coarse-grained (CG) level, a technique that is now widely used to understand protein affinity, aggregation and self-assembly behaviour. PPI models of soluble proteins and membrane proteins are separate

  11. Detecting protein-protein interactions in living cells

    DEFF Research Database (Denmark)

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

    2009-01-01

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

  12. 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.

  13. 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

  14. Mapping Protein-Protein Interactions by Quantitative Proteomics

    DEFF Research Database (Denmark)

    Dengjel, Joern; Kratchmarova, Irina; Blagoev, Blagoy

    2010-01-01

    spectrometry (MS)-based proteomics in combination with affinity purification protocols has become the method of choice to map and track the dynamic changes in protein-protein interactions, including the ones occurring during cellular signaling events. Different quantitative MS strategies have been used...

  15. A Statistical Analysis of Protein-Protein Interaction with Knowledge-Based Potential at Residue Level

    Institute of Scientific and Technical Information of China (English)

    林巍; 孙飞; 饶子和

    2003-01-01

    Protein-protein recognition is an important step in biological processes, which still largely remains elusive.The inter-residue contact potential, CPij, describes the propensity of contact between two types of residue.In this study, several different CPij variants were examined with the objective of discriminating the binding potential of surface pairs.Using solvent mediated inter-molecule contact potential (SM-IMCPij), an evaluation model was deduced and tested.Using the evaluation model it was found that the SM-IMCPij gives a better performance than either residue mediated IMCPij(RM-IMCPij) or folding-residue contact potential (FCPij).The results suggest that the evaluation model provides a fast, effective, and discriminative method for the evaluation of proposed binding interfaces.

  16. Understanding and Manipulating Electrostatic Fields at the Protein-Protein Interface Using Vibrational Spectroscopy and Continuum Electrostatics Calculations.

    Science.gov (United States)

    Ritchie, Andrew W; Webb, Lauren J

    2015-11-05

    Biological function emerges in large part from the interactions of biomacromolecules in the complex and dynamic environment of the living cell. For this reason, macromolecular interactions in biological systems are now a major focus of interest throughout the biochemical and biophysical communities. The affinity and specificity of macromolecular interactions are the result of both structural and electrostatic factors. Significant advances have been made in characterizing structural features of stable protein-protein interfaces through the techniques of modern structural biology, but much less is understood about how electrostatic factors promote and stabilize specific functional macromolecular interactions over all possible choices presented to a given molecule in a crowded environment. In this Feature Article, we describe how vibrational Stark effect (VSE) spectroscopy is being applied to measure electrostatic fields at protein-protein interfaces, focusing on measurements of guanosine triphosphate (GTP)-binding proteins of the Ras superfamily binding with structurally related but functionally distinct downstream effector proteins. In VSE spectroscopy, spectral shifts of a probe oscillator's energy are related directly to that probe's local electrostatic environment. By performing this experiment repeatedly throughout a protein-protein interface, an experimental map of measured electrostatic fields generated at that interface is determined. These data can be used to rationalize selective binding of similarly structured proteins in both in vitro and in vivo environments. Furthermore, these data can be used to compare to computational predictions of electrostatic fields to explore the level of simulation detail that is necessary to accurately predict our experimental findings.

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

    Science.gov (United States)

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

    2010-01-01

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

  19. Interacting binaries

    CERN Document Server

    Shore, S N; van den Heuvel, EPJ

    1994-01-01

    This volume contains lecture notes presented at the 22nd Advanced Course of the Swiss Society for Astrophysics and Astronomy. The contributors deal with symbiotic stars, cataclysmic variables, massive binaries and X-ray binaries, in an attempt to provide a better understanding of stellar evolution.

  20. Crystal structure of shrimp arginine kinase in binary complex with arginine-a molecular view of the phosphagen precursor binding to the enzyme.

    Science.gov (United States)

    López-Zavala, Alonso A; García-Orozco, Karina D; Carrasco-Miranda, Jesús S; Sugich-Miranda, Rocio; Velázquez-Contreras, Enrique F; Criscitiello, Michael F; Brieba, Luis G; Rudiño-Piñera, Enrique; Sotelo-Mundo, Rogerio R

    2013-12-01

    Arginine kinase (AK) is a key enzyme for energetic balance in invertebrates. Although AK is a well-studied system that provides fast energy to invertebrates using the phosphagen phospho-arginine, the structural details on the AK-arginine binary complex interaction remain unclear. Herein, we determined two crystal structures of the Pacific whiteleg shrimp (Litopenaeus vannamei) arginine kinase, one in binary complex with arginine (LvAK-Arg) and a ternary transition state analog complex (TSAC). We found that the arginine guanidinium group makes ionic contacts with Glu225, Cys271 and a network of ordered water molecules. On the zwitterionic side of the amino acid, the backbone amide nitrogens of Gly64 and Val65 coordinate the arginine carboxylate. Glu314, one of proposed acid-base catalytic residues, did not interact with arginine in the binary complex. This residue is located in the flexible loop 310-320 that covers the active site and only stabilizes in the LvAK-TSAC. This is the first binary complex crystal structure of a guanidine kinase in complex with the guanidine substrate and could give insights into the nature of the early steps of phosphagen biosynthesis.

  1. Information-driven structural modelling of protein-protein interactions.

    Science.gov (United States)

    Rodrigues, João P G L M; Karaca, Ezgi; Bonvin, Alexandre M J J

    2015-01-01

    Protein-protein docking aims at predicting the three-dimensional structure of a protein complex starting from the free forms of the individual partners. As assessed in the CAPRI community-wide experiment, the most successful docking algorithms combine pure laws of physics with information derived from various experimental or bioinformatics sources. Of these so-called "information-driven" approaches, HADDOCK stands out as one of the most successful representatives. In this chapter, we briefly summarize which experimental information can be used to drive the docking prediction in HADDOCK, and then focus on the docking protocol itself. We discuss and illustrate with a tutorial example a "classical" protein-protein docking prediction, as well as more recent developments for modelling multi-body systems and large conformational changes.

  2. 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

    2016-01-01

    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 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.

  3. Optimization and dynamics of protein-protein complexes using B-splines.

    Science.gov (United States)

    Gillilan, Richard E; Lilien, Ryan H

    2004-10-01

    A moving-grid approach for optimization and dynamics of protein-protein complexes is introduced, which utilizes cubic B-spline interpolation for rapid energy and force evaluation. The method allows for the efficient use of full electrostatic potentials joined smoothly to multipoles at long distance so that multiprotein simulation is possible. Using a recently published benchmark of 58 protein complexes, we examine the performance and quality of the grid approximation, refining cocrystallized complexes to within 0.68 A RMSD of interface atoms, close to the optimum 0.63 A produced by the underlying MMFF94 force field. We quantify the theoretical statistical advantage of using minimization in a stochastic search in the case of two rigid bodies, and contrast it with the underlying cost of conjugate gradient minimization using B-splines. The volumes of conjugate gradient minimization basins of attraction in cocrystallized systems are generally orders of magnitude larger than well volumes based on energy thresholds needed to discriminate native from nonnative states; nonetheless, computational cost is significant. Molecular dynamics using B-splines is doubly efficient due to the combined advantages of rapid force evaluation and large simulation step sizes. Large basins localized around the native state and other possible binding sites are identifiable during simulations of protein-protein motion. In addition to providing increased modeling detail, B-splines offer new algorithmic possibilities that should be valuable in refining docking candidates and studying global complex behavior.

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

    Science.gov (United States)

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

    2017-04-01

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

  5. Relative quantification of protein-protein interactions using a dual luciferase reporter pull-down assay system.

    Directory of Open Access Journals (Sweden)

    Shuaizheng Jia

    Full Text Available The identification and quantitative analysis of protein-protein interactions are essential to the functional characterization of proteins in the post-proteomics era. The methods currently available are generally time-consuming, technically complicated, insensitive and/or semi-quantitative. The lack of simple, sensitive approaches to precisely quantify protein-protein interactions still prevents our understanding of the functions of many proteins. Here, we develop a novel dual luciferase reporter pull-down assay by combining a biotinylated Firefly luciferase pull-down assay with a dual luciferase reporter assay. The biotinylated Firefly luciferase-tagged protein enables rapid and efficient isolation of a putative Renilla luciferase-tagged binding protein from a relatively small amount of sample. Both of these proteins can be quantitatively detected using the dual luciferase reporter assay system. Protein-protein interactions, including Fos-Jun located in the nucleus; MAVS-TRAF3 in cytoplasm; inducible IRF3 dimerization; viral protein-regulated interactions, such as MAVS-MAVS and MAVS-TRAF3; IRF3 dimerization; and protein interaction domain mapping, are studied using this novel assay system. Herein, we demonstrate that this dual luciferase reporter pull-down assay enables the quantification of the relative amounts of interacting proteins that bind to streptavidin-coupled beads for protein purification. This study provides a simple, rapid, sensitive, and efficient approach to identify and quantify relative protein-protein interactions. Importantly, the dual luciferase reporter pull-down method will facilitate the functional determination of proteins.

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

    Indian Academy of Sciences (India)

    Bimlesh Ojha; Cirantan Kar; Gopal Das

    2013-03-01

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

  7. Protein-spanning water networks and implications for prediction of protein-protein interactions mediated through hydrophobic effects.

    Science.gov (United States)

    Cui, Di; Ou, Shuching; Patel, Sandeep

    2014-12-01

    Hydrophobic effects, often conflated with hydrophobic forces, are implicated as major determinants in biological association and self-assembly processes. Protein-protein interactions involved in signaling pathways in living systems are a prime example where hydrophobic effects have profound implications. In the context of protein-protein interactions, a priori knowledge of relevant binding interfaces (i.e., clusters of residues involved directly with binding interactions) is difficult. In the case of hydrophobically mediated interactions, use of hydropathy-based methods relying on single residue hydrophobicity properties are routinely and widely used to predict propensities for such residues to be present in hydrophobic interfaces. However, recent studies suggest that consideration of hydrophobicity for single residues on a protein surface require accounting of the local environment dictated by neighboring residues and local water. In this study, we use a method derived from percolation theory to evaluate spanning water networks in the first hydration shells of a series of small proteins. We use residue-based water density and single-linkage clustering methods to predict hydrophobic regions of proteins; these regions are putatively involved in binding interactions. We find that this simple method is able to predict with sufficient accuracy and coverage the binding interface residues of a series of proteins. The approach is competitive with automated servers. The results of this study highlight the importance of accounting of local environment in determining the hydrophobic nature of individual residues on protein surfaces.

  8. 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.

  9. Exposing the Alkanesulfonate Monooxygenase Protein-Protein Interaction Sites.

    Science.gov (United States)

    Dayal, Paritosh V; Singh, Harsimran; Busenlehner, Laura S; Ellis, Holly R

    2015-12-29

    The alkanesulfonate monooxygenase enzymes (SsuE and SsuD) catalyze the desulfonation of diverse alkanesulfonate substrates. The SsuE enzyme is an NADPH-dependent FMN reductase that provides reduced flavin to the SsuD monooxygenase enzyme. Previous studies have highlighted the presence of protein-protein interactions between SsuE and SsuD thought to be important in the flavin transfer event, but the putative interaction sites have not been identified. Protected sites on specific regions of SsuE and SsuD were identified by hydrogen-deuterium exchange mass spectrometry. An α-helix on SsuD containing conserved charged amino acids showed a decrease in percent deuteration in the presence of SsuE. The α-helical region of SsuD is part of an insertion sequence and is adjacent to the active site opening. A SsuD variant containing substitutions of the charged residues showed a 4-fold decrease in coupled assays that included SsuE to provide reduced FMN, but there was no activity observed with an SsuD variant containing a deletion of the α-helix under similar conditions. Desulfonation by the SsuD deletion variant was only observed with an increase in enzyme and substrate concentrations. Although activity was observed under certain conditions, there were no protein-protein interactions observed with the SsuD variants and SsuE in pull-down assays and fluorimetric titrations. The results from these studies suggest that optimal transfer of reduced flavin from SsuE to SsuD requires defined protein-protein interactions, but diffusion can occur under specified conditions. A basis is established for further studies to evaluate the structural features of the alkanesulfonate monooxygenase enzymes that promote desulfonation.

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

    Science.gov (United States)

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

    2013-10-01

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

  11. Sentence Simplification Aids Protein-Protein Interaction Extraction

    CERN Document Server

    Jonnalagadda, Siddhartha

    2010-01-01

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

  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. Beauty is in the eye of the beholder: proteins can recognize binding sites of homologous proteins in more than one way.

    Directory of Open Access Journals (Sweden)

    Juliette Martin

    2010-06-01

    Full Text Available Understanding the mechanisms of protein-protein interaction is a fundamental problem with many practical applications. The fact that different proteins can bind similar partners suggests that convergently evolved binding interfaces are reused in different complexes. A set of protein complexes composed of non-homologous domains interacting with homologous partners at equivalent binding sites was collected in 2006, offering an opportunity to investigate this point. We considered 433 pairs of protein-protein complexes from the ABAC database (AB and AC binary protein complexes sharing a homologous partner A and analyzed the extent of physico-chemical similarity at the atomic and residue level at the protein-protein interface. Homologous partners of the complexes were superimposed using Multiprot, and similar atoms at the interface were quantified using a five class grouping scheme and a distance cut-off. We found that the number of interfacial atoms with similar properties is systematically lower in the non-homologous proteins than in the homologous ones. We assessed the significance of the similarity by bootstrapping the atomic properties at the interfaces. We found that the similarity of binding sites is very significant between homologous proteins, as expected, but generally insignificant between the non-homologous proteins that bind to homologous partners. Furthermore, evolutionarily conserved residues are not colocalized within the binding sites of non-homologous proteins. We could only identify a limited number of cases of structural mimicry at the interface, suggesting that this property is less generic than previously thought. Our results support the hypothesis that different proteins can interact with similar partners using alternate strategies, but do not support convergent evolution.

  14. Human carotid atherosclerotic plaque protein(s) change HDL protein(s) composition and impair HDL anti-oxidant activity.

    Science.gov (United States)

    Cohen, Elad; Aviram, Michael; Khatib, Soliman; Volkova, Nina; Vaya, Jacob

    2016-01-01

    High density lipoprotein (HDL) anti-atherogenic functions are closely associated with cardiovascular disease risk factor, and are dictated by its composition, which is often affected by environmental factors. The present study investigates the effects of the human carotid plaque constituents on HDL composition and biological functions. To this end, human carotid plaques were homogenized and incubated with HDL. Results showed that after incubation, most of the apolipoprotein A1 (Apo A1) protein was released from the HDL, and HDL diameter increased by an average of approximately 2 nm. In parallel, HDL antioxidant activity was impaired. In response to homogenate treatment HDL could not prevent the accelerated oxidation of LDL caused by the homogenate. Boiling of the homogenate prior to its incubation with HDL abolished its effects on HDL composition changes. Moreover, tryptophan fluorescence quenching assay revealed an interaction between plaque component(s) and HDL, an interaction that was reduced by 50% upon using pre-boiled homogenate. These results led to hypothesize that plaque protein(s) interacted with HDL-associated Apo A1 and altered the HDL composition. Immuno-precipitation of Apo A1 that was released from the HDL after its incubation with the homogenate revealed a co-precipitation of three isomers of actin. However, beta-actin alone did not significantly affect the HDL composition, and yet the active protein within the plaque was elusive. In conclusion then, protein(s) in the homogenate interact with HDL protein(s), leading to release of Apo A1 from the HDL particle, a process that was associated with an increase in HDL diameter and with impaired HDL anti-oxidant activity.

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

    Science.gov (United States)

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

    2016-06-14

    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.

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

    Science.gov (United States)

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

    2016-06-01

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

  17. A machine learning approach for ranking clusters of docked protein-protein complexes by pairwise cluster comparison.

    Science.gov (United States)

    Pfeiffenberger, Erik; Chaleil, Raphael A G; Moal, Iain H; Bates, Paul A

    2017-03-01

    Reliable identification of near-native poses of docked protein-protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein-protein interactions is challenging for traditional biophysical or knowledge based potentials and the identification of many false positive binding sites is not unusual. Often, ranking protocols are based on initial clustering of docked poses followed by the application of an energy function to rank each cluster according to its lowest energy member. Here, we present an approach of cluster ranking based not only on one molecular descriptor (e.g., an energy function) but also employing a large number of descriptors that are integrated in a machine learning model, whereby, an extremely randomized tree classifier based on 109 molecular descriptors is trained. The protocol is based on first locally enriching clusters with additional poses, the clusters are then characterized using features describing the distribution of molecular descriptors within the cluster, which are combined into a pairwise cluster comparison model to discriminate near-native from incorrect clusters. The results show that our approach is able to identify clusters containing near-native protein-protein complexes. In addition, we present an analysis of the descriptors with respect to their power to discriminate near native from incorrect clusters and how data transformations and recursive feature elimination can improve the ranking performance. Proteins 2017; 85:528-543. © 2016 Wiley Periodicals, Inc.

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

    Science.gov (United States)

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

    2016-05-19

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

  19. Analysis of protein-protein docking decoys using interaction fingerprints: application to the reconstruction of CaM-ligand complexes

    Directory of Open Access Journals (Sweden)

    Uchikoga Nobuyuki

    2010-05-01

    Full Text Available Abstract Background Protein-protein docking for proteins with large conformational changes was analyzed by using interaction fingerprints, one of the scales for measuring similarities among complex structures, utilized especially for searching near-native protein-ligand or protein-protein complex structures. Here, we have proposed a combined method for analyzing protein-protein docking by taking large conformational changes into consideration. This combined method consists of ensemble soft docking with multiple protein structures, refinement of complexes, and cluster analysis using interaction fingerprints and energy profiles. Results To test for the applicability of this combined method, various CaM-ligand complexes were reconstructed from the NMR structures of unbound CaM. For the purpose of reconstruction, we used three known CaM-ligands, namely, the CaM-binding peptides of cyclic nucleotide gateway (CNG, CaM kinase kinase (CaMKK and the plasma membrane Ca2+ ATPase pump (PMCA, and thirty-one structurally diverse CaM conformations. For each ligand, 62000 CaM-ligand complexes were generated in the docking step and the relationship between their energy profiles and structural similarities to the native complex were analyzed using interaction fingerprint and RMSD. Near-native clusters were obtained in the case of CNG and CaMKK. Conclusions The interaction fingerprint method discriminated near-native structures better than the RMSD method in cluster analysis. We showed that a combined method that includes the interaction fingerprint is very useful for protein-protein docking analysis of certain cases.

  20. Piezo dispensed microarray of multivalent chelating thiols for dissecting complex protein-protein interactions.

    Science.gov (United States)

    Klenkar, Goran; Valiokas, Ramûnas; Lundström, Ingemar; Tinazli, Ali; Tampé, Robert; Piehler, Jacob; Liedberg, Bo

    2006-06-01

    The fabrication of a novel biochip, designed for dissection of multiprotein complex formation, is reported. An array of metal chelators has been produced by piezo dispensing of a bis-nitrilotriacetic acid (bis-NTA) thiol on evaporated gold thin films, prestructured with a microcontact printed grid of eicosanethiols. The bis-NTA thiol is mixed in various proportions with an inert, tri(ethylene glycol) hexadecane thiol, and the thickness and morphological homogeneity of the dispensed layers are characterized by imaging ellipsometry before and after back-filling with the same inert thiol and subsequent rinsing. It is found that the dispensed areas display a monotonic increase in thickness with increasing molar fraction of bis-NTA in the dispensing solution, and they are consistently a few Angströms thicker than those prepared at the same molar fraction by solution self-assembly under equilibrium-like conditions. The bulkiness of the bis-NTA tail group and the short period of time available for chemisorption and in-plane organization of the dispensed thiols are most likely responsible for the observed difference in thickness. Moreover, the functional properties of this biochip are demonstrated by studying multiple protein-protein interactions using imaging surface plasmon resonance. The subunits of the type I interferon receptor are immobilized as a composition array determined by the surface concentration of bis-NTA in the array elements. Ligand dissociation kinetics depends on the receptor surface concentration, which is ascribed to the formation of a ternary complex by simultaneous interaction of the ligand with the two receptor subunits. Thus, multiplexed monitoring of binding phenomena at various compositions (receptor densities) offers a powerful tool to dissect protein-protein interactions.

  1. Identification of protein-protein interactions by standard gal4p-based yeast two-hybrid screening.

    Science.gov (United States)

    Wagemans, Jeroen; Lavigne, Rob

    2015-01-01

    Yeast two-hybrid (Y2H) screening permits identification of completely new protein interaction partners for a protein of interest, in addition to confirming binary protein-protein interactions. After discussing the general advantages and drawbacks of Y2H and existing alternatives, this chapter provides a detailed protocol for traditional Gal4p-based Y2H library screens in Saccharomyces cerevisiae AH109. This includes bait transformation, bait auto-activation testing, prey library transformation, Y2H evaluation, and subsequent identification of the prey plasmids. Moreover, a one-on-one mating protocol to confirm interactions between suspected partners is given. Finally, a quantitative α-galactosidase assay protocol to compare interaction strengths is provided.

  2. Protein-protein interaction predictions using text mining methods.

    Science.gov (United States)

    Papanikolaou, Nikolas; Pavlopoulos, Georgios A; Theodosiou, Theodosios; Iliopoulos, Ioannis

    2015-03-01

    It is beyond any doubt that proteins and their interactions play an essential role in most complex biological processes. The understanding of their function individually, but also in the form of protein complexes is of a great importance. Nowadays, despite the plethora of various high-throughput experimental approaches for detecting protein-protein interactions, many computational methods aiming to predict new interactions have appeared and gained interest. In this review, we focus on text-mining based computational methodologies, aiming to extract information for proteins and their interactions from public repositories such as literature and various biological databases. We discuss their strengths, their weaknesses and how they complement existing experimental techniques by simultaneously commenting on the biological databases which hold such information and the benchmark datasets that can be used for evaluating new tools.

  3. 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.

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

    Science.gov (United States)

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

    2012-01-15

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

  5. Evolution of Binary Stars in Multiple-Population Globular Clusters

    CERN Document Server

    Hong, Jongsuk; Sollima, Antonio; McMillan, Stephen L W; D'Antona, Franca; D'Ercole, Annibale

    2015-01-01

    The discovery of multiple stellar populations in globular clusters has implications for all the aspects of the study of these stellar systems. In this paper, by means of N-body simulations, we study the evolution of binary stars in multiple-population clusters and explore the implications of the initial differences in the spatial distribution of different stellar populations for the evolution and survival of their binary stars. Our simulations show that initial differences between the spatial distribution of first-generation (FG) and second-generation (SG) stars can leave a fingerprint in the current properties of the binary population. SG binaries are disrupted more efficiently than those of the FG population resulting in a global SG binary fraction smaller than that of the FG. As for surviving binaries, dynamical evolution produces a difference between the SG and the FG binary binding energy distribution with the SG population characterized by a larger fraction of high binding energy (more bound) binaries. ...

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

    Institute of Scientific and Technical Information of China (English)

    SUN Jingchun; XU Jinlin; LI Yixue; SHI Tieliu

    2005-01-01

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

  7. 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

  8. Comprehensive peptidomimetic libraries targeting protein-protein interactions.

    Science.gov (United States)

    Whitby, Landon R; Boger, Dale L

    2012-10-16

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

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

    Science.gov (United States)

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

    2014-02-17

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

  10. 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.

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Carmen Sánchez Claros

    Full Text Available 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. 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.

  14. 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

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

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    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.

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

    NARCIS (Netherlands)

    Somireddy Venkata, Bharat Kumar Reddy

    2012-01-01

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

  17. 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 (In...

  18. Imaging beads-retained prey assay for rapid and quantitative protein-protein interaction.

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    Yan Zhou

    Full Text Available Conventional Western blot based pull-down methods involve lengthy and laborious work and the results are generally not quantitative. Here, we report the imaging beads-retained prey (IBRP assay that is rapid and quantitative in studying protein-protein interactions. In this assay, the bait is immobilized onto beads and the prey is fused with a fluorescence protein. The assay takes advantage of the fluorescence of prey and directly quantifies the amount of prey binding to the immobilized bait under a microscope. We validated the assay using previously well studied interactions and found that the amount of prey retained on beads could have a relative linear relationship to both the inputs of bait and prey. IBRP assay provides a universal, fast, quantitative and economical method to study protein interactions and it could be developed to a medium- or high-throughput compatible method. With the availability of fluorescence tagged whole genome ORFs in several organisms, we predict IBRP assay should have wide applications.

  19. Mapping of protein-protein interactions within the DNA-dependent protein kinase complex.

    Science.gov (United States)

    Gell, D; Jackson, S P

    1999-01-01

    In mammalian cells, the Ku and DNA-dependent protein kinase catalytic subunit (DNA-PKcs) proteins are required for the correct and efficient repair of DNA double-strand breaks. Ku comprises two tightly-associated subunits of approximately 69 and approximately 83 kDa, which are termed Ku70 and Ku80 (or Ku86), respectively. Previously, a number of regions of both Ku subunits have been demonstrated to be involved in their interaction, but the molecular mechanism of this interaction remains unknown. We have identified a region in Ku70 (amino acid residues 449-578) and a region in Ku80 (residues 439-592) that participate in Ku subunit interaction. Sequence analysis reveals that these interaction regions share sequence homology and suggests that the Ku subunits are structurally related. On binding to a DNA double-strand break, Ku is able to interact with DNA-PKcs, but how this interaction is mediated has not been defined. We show that the extreme C-terminus of Ku80, specifically the final 12 amino acid residues, mediates a highly specific interaction with DNA-PKcs. Strikingly, these residues appear to be conserved only in Ku80 sequences from vertebrate organisms. These data suggest that Ku has evolved to become part of the DNA-PK holo-enzyme by acquisition of a protein-protein interaction motif at the C-terminus of Ku80. PMID:10446239

  20. Predictions of hot spot residues at protein-protein interfaces using support vector machines.

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    Stefano Lise

    Full Text Available Protein-protein interactions are critically dependent on just a few 'hot spot' residues at the interface. Hot spots make a dominant contribution to the free energy of binding and they can disrupt the interaction if mutated to alanine. Here, we present HSPred, a support vector machine(SVM-based method to predict hot spot residues, given the structure of a complex. HSPred represents an improvement over a previously described approach (Lise et al, BMC Bioinformatics 2009, 10:365. It achieves higher accuracy by treating separately predictions involving either an arginine or a glutamic acid residue. These are the amino acid types on which the original model did not perform well. We have therefore developed two additional SVM classifiers, specifically optimised for these cases. HSPred reaches an overall precision and recall respectively of 61% and 69%, which roughly corresponds to a 10% improvement. An implementation of the described method is available as a web server at http://bioinf.cs.ucl.ac.uk/hspred. It is free to non-commercial users.

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

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    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/.

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

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    Lee MG

    2001-07-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2010-01-01

    Förster (or Fluorescence) resonance energy transfer (FRET) is a physical process in which energy is transferred nonradiatively from an excited fluorophore, serving as a donor, to another chromophore (acceptor). Among the techniques related to fluorescence microscopy, FRET is unique in providing signals sensitive to intra- and intermolecular distances in the 1-10 nm range. Because of its potency, FRET is increasingly used to visualize and quantify the dynamics of protein-protein interaction in living cells, with high spatio-temporal resolution. Here we describe the physical bases of FRET, detailing the principal methods applied: (1) measurement of signal intensity and (2) analysis of fluorescence lifetime (FLIM). Although several technical complications must be carefully considered, both methods can be applied fruitfully to specific fields. For example, FRET based on intensity detection is more suitable to follow biological phenomena at a finely tuned spatial and temporal scale. Furthermore, a specific fluorescence signal occurring close to the plasma membrane (advantage of the discovery and use of spontaneously fluorescent proteins, like the green fluorescent protein (GFP). Until now, FRET has been widely used to analyze the structural characteristics of several proteins, including integrins and ion channels. More recently, this method has been applied to clarify the interaction dynamics of these classes of membrane proteins with cytosolic signaling proteins. We report two examples in which the interaction dynamics between integrins and ion channels have been studied with FRET methods. Using fluorescent antibodies and applying FRET-FLIM, the direct interaction of beta1 integrin with the receptor for Epidermal Growth Factor (EGF-R) has been proved in living endothelial cells. A different approach, based on TIRFM measurement of the FRET intensity of fluorescently labeled recombinant proteins, suggests that a direct interaction also occurs between integrins and the

  5. Inferring high-confidence human protein-protein interactions

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    Yu Xueping

    2012-05-01

    Full Text Available Abstract Background As numerous experimental factors drive the acquisition, identification, and interpretation of protein-protein interactions (PPIs, aggregated assemblies of human PPI data invariably contain experiment-dependent noise. Ascertaining the reliability of PPIs collected from these diverse studies and scoring them to infer high-confidence networks is a non-trivial task. Moreover, a large number of PPIs share the same number of reported occurrences, making it impossible to distinguish the reliability of these PPIs and rank-order them. For example, for the data analyzed here, we found that the majority (>83% of currently available human PPIs have been reported only once. Results In this work, we proposed an unsupervised statistical approach to score a set of diverse, experimentally identified PPIs from nine primary databases to create subsets of high-confidence human PPI networks. We evaluated this ranking method by comparing it with other methods and assessing their ability to retrieve protein associations from a number of diverse and independent reference sets. These reference sets contain known biological data that are either directly or indirectly linked to interactions between proteins. We quantified the average effect of using ranked protein interaction data to retrieve this information and showed that, when compared to randomly ranked interaction data sets, the proposed method created a larger enrichment (~134% than either ranking based on the hypergeometric test (~109% or occurrence ranking (~46%. Conclusions From our evaluations, it was clear that ranked interactions were always of value because higher-ranked PPIs had a higher likelihood of retrieving high-confidence experimental data. Reducing the noise inherent in aggregated experimental PPIs via our ranking scheme further increased the accuracy and enrichment of PPIs derived from a number of biologically relevant data sets. These results suggest that using our high

  6. Protein-protein interaction network of celiac disease

    Science.gov (United States)

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

    2016-01-01

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

  7. Targeting protein-protein interactions for parasite control.

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    Christina M Taylor

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

  8. Discovering functional interaction patterns in protein-protein interaction networks

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    Can Tolga

    2008-06-01

    Full Text Available Abstract Background In recent years, a considerable amount of research effort has been directed to the analysis of biological networks with the availability of genome-scale networks of genes and/or proteins of an increasing number of organisms. A protein-protein interaction (PPI network is a particular biological network which represents physical interactions between pairs of proteins of an organism. Major research on PPI networks has focused on understanding the topological organization of PPI networks, evolution of PPI networks and identification of conserved subnetworks across different species, discovery of modules of interaction, use of PPI networks for functional annotation of uncharacterized proteins, and improvement of the accuracy of currently available networks. Results In this article, we map known functional annotations of proteins onto a PPI network in order to identify frequently occurring interaction patterns in the functional space. We propose a new frequent pattern identification technique, PPISpan, adapted specifically for PPI networks from a well-known frequent subgraph identification method, gSpan. Existing module discovery techniques either look for specific clique-like highly interacting protein clusters or linear paths of interaction. However, our goal is different; instead of single clusters or pathways, we look for recurring functional interaction patterns in arbitrary topologies. We have applied PPISpan on PPI networks of Saccharomyces cerevisiae and identified a number of frequently occurring functional interaction patterns. Conclusion With the help of PPISpan, recurring functional interaction patterns in an organism's PPI network can be identified. Such an analysis offers a new perspective on the modular organization of PPI networks. The complete list of identified functional interaction patterns is available at http://bioserver.ceng.metu.edu.tr/PPISpan/.

  9. Synthesis, characterization and thermal studies of binary and/or mixed ligand complexes of Cd(II), Cu(II), Ni(II) and Co(III) based on 2-(Hydroxybenzylidene) thiosemicarbazone: DNA binding affinity of binary Cu(II) complex.

    Science.gov (United States)

    Saif, M; Mashaly, Mahmoud M; Eid, Mohamed F; Fouad, R

    2012-06-15

    A new series of metal complexes of Cd(II), Cu(II), Ni(II) and Co(III) with Schiff base ligand, H(2)L, 2-(Hydroxybenzylidene) thiosemicarbazone were synthesized. The mixed ligand complexes were prepared by using glycine (Gly), 2-aminopyridine (2-Ampy) and 1,10-phenanthroline (Phen) as secondary ligands. The structure of these complexes was identified and confirmed by elemental analysis, molar conductivity, UV-Vis, FT-IR and (1)H NMR spectroscopy and magnetic moment measurements as well as TG-DSC technique. The discussions of the prepared complexes indicate that the ligand behaves as a monoanionic tridentate ligand through ONS donor sites. Thermal studies suggested a mechanism for the degradation of the metal complexes as a function of temperature supporting the chelation modes and showed the possibility of obtaining new complexes pyrolytically in the solid state which cannot be synthesized from the solution. The absorption studies support that the binary Cu(II) complex exhibits a significant binding affinity to HS-DNA through intercalative mode.

  10. Binary effectivity rules

    DEFF Research Database (Denmark)

    Keiding, Hans; Peleg, Bezalel

    2006-01-01

    is binary if it is rationalized by an acyclic binary relation. The foregoing result motivates our definition of a binary effectivity rule as the effectivity rule of some binary SCR. A binary SCR is regular if it satisfies unanimity, monotonicity, and independence of infeasible alternatives. A binary...... effectivity rule is regular if it is the effectivity rule of some regular binary SCR. We characterize completely the family of regular binary effectivity rules. Quite surprisingly, intrinsically defined von Neumann-Morgenstern solutions play an important role in this characterization...

  11. Bioluminescent indicator for determining protein-protein interactions using intramolecular complementation of split click beetle luciferase.

    Science.gov (United States)

    Kim, Sung Bae; Otani, Yosuke; Umezawa, Yoshio; Tao, Hiroaki

    2007-07-01

    Click beetle luciferase (CBLuc) is insensitive to pH, temperature, and heavy metals, and emits a stable, highly tissue-transparent red light with luciferin in physiological circumstances. Thus, the luminescence signal is optimal for a bioanalytical index reporting the magnitude of a signal transduction of interest. Here, we validated a single-molecule-format complementation system of split CBLuc to study signal-controlled protein-protein (peptide) interactions. First, we generated 10 pairs of N- and C-terminal fragments of CBLuc to examine respectively whether a significant recovery of the activity occurs through the intramolecular complementation. The ligand binding domain of androgen receptor (AR LBD) was connected to a functional peptide sequence through a flexible linker. The fusion protein was then sandwiched between the dissected N- and C-terminal fragments of CBLuc. Androgen induces the association between AR LBD and a functional peptide and the subsequent complementation of N- and C-terminal fragments of split CBLuc inside the single-molecule-format probe, which restores the activities of CBLuc. The examination about the dissection sites of CBLuc revealed that the dissection positions next to the amino acids D412 and I439 admit a stable recovery of CBLuc activity through an intramolecular complementation. The ligand sensitivity and kinetics of the single molecular probe with split CBLuc were discussed in various cell lines and in different protein-peptide binding models. The probe is applicable to developing biotherapeutic agents on the AR signaling and for screening adverse chemicals that possibly influence the signal transduction of proteins in living cells or animals.

  12. Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors

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    Rushikesh Sable

    2015-06-01

    Full Text Available Blocking protein-protein interactions (PPI using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers.

  13. Insight into structural organization and protein-protein interaction of non structural 3 (NS3) proteins from dengue serotypes.

    Science.gov (United States)

    Parida, Pratap; Yadav, R N S; Sarma, Kishore

    2014-01-01

    Dengue infections produce a distinct character of virus-induced intracellular membrane alterations which are associated with the viral replication machinery. Currently, the NS3 protein is being targeted for antiviral therapy against dengue. NS3 protein of dengue virus interacts with nuclear receptor binding protein (NRBP) of human causing cell trafficking between the Endoplasmic Reticulum (ER) and Golgi, which interacts with Rac3, a member of the Rho-GTPase family. No crystal structure of the NRBP is available for any species, thus limiting the complete understanding of structure- function relationships of this protein. The present study deals with the molecular modeling of the viral protein (NS3 of DENV1-4), the host protein (NRBP) and their interactions through protein-protein docking study. Theoretical threedimensional structures of the NRBP and NS3 were modeled using the Modeller 9v8, and the evaluated models were docked using GRAMM-X to study the mode of protein-protein interaction (NRBP as receptor and NS3 as ligand). The docked docking complexes were further evaluated for interaction analysis by the RosettaDock Server. Suface and interface residues were observed along with hydrogen and hydrophobic interaction. The conserved residues forming hydrogen interaction of NRBP with DENV1-4 serotypes were found to be GLN 305, SER 363 and GLN 379.

  14. 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.

  15. Application of Enhanced Sampling Monte Carlo Methods for High-Resolution Protein-Protein Docking in Rosetta.

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    Zhe Zhang

    Full Text Available The high-resolution refinement of docked protein-protein complexes can provide valuable structural and mechanistic insight into protein complex formation complementing experiment. Monte Carlo (MC based approaches are frequently applied to sample putative interaction geometries of proteins including also possible conformational changes of the binding partners. In order to explore efficiency improvements of the MC sampling, several enhanced sampling techniques, including temperature or Hamiltonian replica exchange and well-tempered ensemble approaches, have been combined with the MC method and were evaluated on 20 protein complexes using unbound partner structures. The well-tempered ensemble method combined with a 2-dimensional temperature and Hamiltonian replica exchange scheme (WTE-H-REMC was identified as the most efficient search strategy. Comparison with prolonged MC searches indicates that the WTE-H-REMC approach requires approximately 5 times fewer MC steps to identify near native docking geometries compared to conventional MC searches.

  16. Community-wide Evaluation of Methods for Predicting the Effect of Mutations on Protein-Protein Interactions

    Science.gov (United States)

    Moretti, Rocco; Fleishman, Sarel J.; Agius, Rudi; Torchala, Mieczyslaw; Bates, Paul A.; Kastritis, Panagiotis L.; Rodrigues, João P. G. L. M.; Trellet, Mikaël; Bonvin, Alexandre M. J. J.; Cui, Meng; Rooman, Marianne; Gillis, Dimitri; Dehouck, Yves; Moal, Iain; Romero-Durana, Miguel; Perez-Cano, Laura; Pallara, Chiara; Jimenez, Brian; Fernandez-Recio, Juan; Flores, Samuel; Pacella, Michael; Kilambi, Krishna Praneeth; Gray, Jeffrey J.; Popov, Petr; Grudinin, Sergei; Esquivel-Rodríguez, Juan; Kihara, Daisuke; Zhao, Nan; Korkin, Dmitry; Zhu, Xiaolei; Demerdash, Omar N. A.; Mitchell, Julie C.; Kanamori, Eiji; Tsuchiya, Yuko; Nakamura, Haruki; Lee, Hasup; Park, Hahnbeom; Seok, Chaok; Sarmiento, Jamica; Liang, Shide; Teraguchi, Shusuke; Standley, Daron M.; Shimoyama, Hiromitsu; Terashi, Genki; Takeda-Shitaka, Mayuko; Iwadate, Mitsuo; Umeyama, Hideaki; Beglov, Dmitri; Hall, David R.; Kozakov, Dima; Vajda, Sandor; Pierce, Brian G.; Hwang, Howook; Vreven, Thom; Weng, Zhiping; Huang, Yangyu; Li, Haotian; Yang, Xiufeng; Ji, Xiaofeng; Liu, Shiyong; Xiao, Yi; Zacharias, Martin; Qin, Sanbo; Zhou, Huan-Xiang; Huang, Sheng-You; Zou, Xiaoqin; Velankar, Sameer; Janin, Joël; Wodak, Shoshana J.; Baker, David

    2014-01-01

    Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side chain sampling and backbone relaxation, and evaluated packing, electrostatic and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of methodological improvement. PMID:23843247

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

    Science.gov (United States)

    Park, Byungkyu; Han, Kyungsook

    2010-02-01

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

  18. Quantitative Analysis of Spatial Protein-protein Proximity in Fluorescence Confocal Microscopy

    Science.gov (United States)

    Wu, Yong; Liu, Yi-Kuang; Eghbali, Mansoureh; Stefani, Enrico

    2009-02-01

    To quantify spatial protein-protein proximity (colocalization) in fluorescence microscopic images, cross-correlation and autocorrelation functions were decomposed into fast and slowly decaying components. The fast component results from clusters of proteins specifically labeled and the slow one from background/image heterogeneity. We show that the calculation of the protein-protein proximity index and the correlation coefficient are more reliably determined by extracting the fast-decaying component.

  19. Stabilized helical peptides: a strategy to target protein-protein interactions.

    Science.gov (United States)

    Klein, Mark A

    2014-08-14

    Protein-protein interactions are critical for cell proliferation, differentiation, and function. Peptides hold great promise for clinical applications focused on targeting protein-protein interactions. Advantages of peptides include a large chemical space and potential diversity of sequences and structures. However, peptides do present well-known challenges for drug development. Progress has been made in the development of stabilizing alpha helices for potential therapeutic applications. Advantages and disadvantages of different methods of helical peptide stabilization are discussed.

  20. Thioflavin S (NSC71948) interferes with Bcl-2-associated athanogene (BAG-1)-mediated protein-protein interactions.

    Science.gov (United States)

    Sharp, Adam; Crabb, Simon J; Johnson, Peter W M; Hague, Angela; Cutress, Ramsey; Townsend, Paul A; Ganesan, A; Packham, Graham

    2009-11-01

    The C-terminal BAG domain is thought to play a key role in BAG-1-induced survival and proliferation by mediating protein-protein interactions, for example, with heat shock proteins HSC70 and HSP70, and with RAF-1 kinase. Here, we have identified thioflavin S (NSC71948) as a potential small-molecule chemical inhibitor of these interactions. NSC71948 inhibited the interaction of BAG-1 and HSC70 in vitro and decreased BAG-1:HSC70 and BAG-1:HSP70 binding in intact cells. NSC71948 also reduced binding between BAG-1 and RAF-1, but had no effect on the interaction between two unrelated proteins, BIM and MCL-1. NSC71948 functionally reversed the ability of BAG-1 to promote vitamin D3 receptor-mediated transactivation, an activity of BAG-1 that depends on HSC70/HSP70 binding, and reduced phosphorylation of p44/42 mitogen-activate protein kinase. NSC71948 can be used to stain amyloid fibrils; however, structurally related compounds, thioflavin T and BTA-1, had no effect on BAG-1:HSC70 binding, suggesting that structural features important for amyloid fibril binding and inhibition of BAG-1:HSC70 binding may be separable. We demonstrated that NSC71948 inhibited the growth of BAG-1 expressing human ZR-75-1 breast cancer cells and wild-type, but not BAG-1-deficient, mouse embryo fibroblasts. Taken together, these data suggest that NSC71948 may be a useful molecule to investigate the functional significance of BAG-1 C-terminal protein interactions. However, it is important to recognize that NSC71948 may exert additional "off-target" effects. Inhibition of BAG-1 function may be an attractive strategy to inhibit the growth of BAG-1-overexpressing cancers, and further screens of additional compound collections may be warranted.

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

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, C; Zemla, A

    2009-02-25

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

  2. 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.

  3. Development of a novel molecular sensor for imaging estrogen receptor-coactivator protein-protein interactions.

    Directory of Open Access Journals (Sweden)

    Madryn C Lake

    Full Text Available Anti-estrogens, in particular tissue selective anti-estrogens, have been the bedrock of adjuvant therapy for patients with estrogen receptor alpha (ERα positive breast cancer. Though current therapies have greatly enhanced patient prognosis, there continues to be an impetus for the development of improved anti-estrogens. ERα is a nuclear receptor transcription factor which activates gene expression through the recruitment of transcriptional coactivator proteins. The SRC family of coactivators, which includes AIB1, has been shown to be of particular importance for ERα mediated transcription. ERα-AIB1 interactions are indicative of gene expression and are inhibited by anti-estrogen treatment. We have exploited the interaction between ERα and AIB1 as a novel method for imaging ERα activity using a split luciferase molecular sensor. By producing a range of ERα ligand binding domain (ER-LBD and AIB1 nuclear receptor interacting domain (AIB-RID N- and C-terminal firefly luciferase fragment fusion proteins, constructs which exhibited more than a 10-fold increase in luciferase activity with E2 stimulation were identified. The specificity of the E2-stimulated luciferase activity to ERα-AIB1 interaction was validated through Y537S and L539/540A ER-LBD fusion protein mutants. The primed nature of the split luciferase assay allowed changes in ERα activity, with respect to the protein-protein interactions preceding transcription, to be assessed soon after drug treatment. The novel assay split luciferase detailed in this report enabled modulation of ERα activity to be sensitively imaged in vitro and in living subjects and potentially holds much promise for imaging the efficacy of novel ERα specific therapies.

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

    Directory of Open Access Journals (Sweden)

    Swapna Lakshmipuram S

    2012-12-01

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

  5. Designing coarse grained-and atom based-potentials for protein-protein docking

    Directory of Open Access Journals (Sweden)

    Tobi Dror

    2010-11-01

    Full Text Available Abstract Background Protein-protein docking is a challenging computational problem in functional genomics, particularly when one or both proteins undergo conformational change(s upon binding. The major challenge is to define a scoring function soft enough to tolerate these changes and specific enough to distinguish between near-native and "misdocked" conformations. Results Using a linear programming (LP technique, we developed two types of potentials: (i Side chain-based and (ii Heavy atom-based. To achieve this we considered a set of 161 transient complexes and generated a large set of putative docked structures (decoys, based on a shape complementarity criterion, for each complex. The demand on the potentials was to yield, for the native (correctly docked structure, a potential energy lower than those of any of the non-native (misdocked structures. We show that the heavy atom-based potentials were able to comply with this requirement but not the side chain-based one. Thus, despite the smaller number of parameters, the capability of heavy atom-based potentials to discriminate between native and "misdocked" conformations is improved relative to those of the side chain-based potentials. The performance of the atom-based potentials was evaluated by a jackknife test on a set of 50 complexes taken from the Zdock2.3 decoys set. Conclusions Our results show that, using the LP approach, we were able to train our potentials using a dataset of transient complexes only the newly developed potentials outperform three other known potentials in this test.

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

    Science.gov (United States)

    Goodfellow, Ian; Bailey, Dalan

    2014-01-01

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

  7. Evaluation of protein-protein docking model structures using all-atom molecular dynamics simulations combined with the solution theory in the energy representation.

    Science.gov (United States)

    Takemura, Kazuhiro; Guo, Hao; Sakuraba, Shun; Matubayasi, Nobuyuki; Kitao, Akio

    2012-12-07

    We propose a method to evaluate binding free energy differences among distinct protein-protein complex model structures through all-atom molecular dynamics simulations in explicit water using the solution theory in the energy representation. Complex model structures are generated from a pair of monomeric structures using the rigid-body docking program ZDOCK. After structure refinement by side chain optimization and all-atom molecular dynamics simulations in explicit water, complex models are evaluated based on the sum of their conformational and solvation free energies, the latter calculated from the energy distribution functions obtained from relatively short molecular dynamics simulations of the complex in water and of pure water based on the solution theory in the energy representation. We examined protein-protein complex model structures of two protein-protein complex systems, bovine trypsin/CMTI-1 squash inhibitor (PDB ID: 1PPE) and RNase SA/barstar (PDB ID: 1AY7), for which both complex and monomer structures were determined experimentally. For each system, we calculated the energies for the crystal complex structure and twelve generated model structures including the model most similar to the crystal structure and very different from it. In both systems, the sum of the conformational and solvation free energies tended to be lower for the structure similar to the crystal. We concluded that our energy calculation method is useful for selecting low energy complex models similar to the crystal structure from among a set of generated models.

  8. 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.

  9. 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.

  10. Eclipsing binaries in open clusters

    DEFF Research Database (Denmark)

    Southworth, John; Clausen, J.V.

    2006-01-01

    Stars: fundamental parameters - Stars : binaries : eclipsing - Stars: Binaries: spectroscopic - Open clusters and ass. : general Udgivelsesdato: 5 August......Stars: fundamental parameters - Stars : binaries : eclipsing - Stars: Binaries: spectroscopic - Open clusters and ass. : general Udgivelsesdato: 5 August...

  11. Deducing topology of protein-protein interaction networks from experimentally measured sub-networks

    Directory of Open Access Journals (Sweden)

    MacLellan W Robb

    2008-07-01

    Full Text Available Abstract Background Protein-protein interaction networks are commonly sampled using yeast two hybrid approaches. However, whether topological information reaped from these experimentally-measured sub-networks can be extrapolated to complete protein-protein interaction networks is unclear. Results By analyzing various experimental protein-protein interaction datasets, we found that they are not random samples of the parent networks. Based on the experimental bait-prey behaviors, our computer simulations show that these non-random sampling features may affect the topological information. We tested the hypothesis that a core sub-network exists within the experimentally sampled network that better maintains the topological characteristics of the parent protein-protein interaction network. We developed a method to filter the experimentally sampled network to result in a core sub-network that more accurately reflects the topology of the parent network. These findings have fundamental implications for large-scale protein interaction studies and for our understanding of the behavior of cellular networks. Conclusion The topological information from experimental measured networks network as is may not be the correct source for topological information about the parent protein-protein interaction network. We define a core sub-network that more accurately reflects the topology of the parent network.

  12. Real-time single-molecule coimmunoprecipitation of weak protein-protein interactions.

    Science.gov (United States)

    Lee, Hong-Won; Ryu, Ji Young; Yoo, Janghyun; Choi, Byungsan; Kim, Kipom; Yoon, Tae-Young

    2013-10-01

    Coimmunoprecipitation (co-IP) analysis is a useful method for studying protein-protein interactions. It currently involves electrophoresis and western blotting, which are not optimized for detecting weak and transient interactions. In this protocol we describe an advanced version of co-IP analysis that uses real-time, single-molecule fluorescence imaging as its detection scheme. Bait proteins are pulled down onto the imaging plane of a total internal reflection (TIR) microscope. With unpurified cells or tissue extracts kept in reaction chambers, we observe single protein-protein interactions between the surface-immobilized bait and the fluorescent protein-labeled prey proteins in real time. Such direct recording provides an improvement of five orders of magnitude in the time resolution of co-IP analysis. With the single-molecule sensitivity and millisecond time resolution, which distinguish our method from other methods for measuring weak protein-protein interactions, it is possible to quantify the interaction kinetics and active fraction of native, unlabeled bait proteins. Real-time single-molecule co-IP analysis, which takes ∼4 h to complete from lysate preparation to kinetic analysis, provides a general avenue for revealing the rich kinetic picture of target protein-protein interactions, and it can be used, for example, to investigate the molecular lesions that drive individual cancers at the level of protein-protein interactions.

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

    Science.gov (United States)

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

    2015-01-01

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

  14. Lectin receptor kinases participate in protein-protein interactions to mediate plasma membrane-cell wall adhesions in Arabidopsis.

    Science.gov (United States)

    Gouget, Anne; Senchou, Virginie; Govers, Francine; Sanson, Arnaud; Barre, Annick; Rougé, Pierre; Pont-Lezica, Rafael; Canut, Hervé

    2006-01-01

    Interactions between plant cell walls and plasma membranes are essential for cells to function properly, but the molecules that mediate the structural continuity between wall and membrane are unknown. Some of these interactions, which are visualized upon tissue plasmolysis in Arabidopsis (Arabidopsis thaliana), are disrupted by the RGD (arginine-glycine-aspartic acid) tripeptide sequence, a characteristic cell adhesion motif in mammals. In planta induced-O (IPI-O) is an RGD-containing protein from the plant pathogen Phytophthora infestans that can disrupt cell wall-plasma membrane adhesions through its RGD motif. To identify peptide sequences that specifically bind the RGD motif of the IPI-O protein and potentially play a role in receptor recognition, we screened a heptamer peptide library displayed in a filamentous phage and selected two peptides acting as inhibitors of the plasma membrane RGD-binding activity of Arabidopsis. Moreover, the two peptides also disrupted cell wall-plasma membrane adhesions. Sequence comparison of the RGD-binding peptides with the Arabidopsis proteome revealed 12 proteins containing amino acid sequences in their extracellular domains common with the two RGD-binding peptides. Eight belong to the receptor-like kinase family, four of which have a lectin-like extracellular domain. The lectin domain of one of these, At5g60300, recognized the RGD motif both in peptides and proteins. These results imply that lectin receptor kinases are involved in protein-protein interactions with RGD-containing proteins as potential ligands, and play a structural and signaling role at the plant cell surfaces.

  15. Lectin Receptor Kinases Participate in Protein-Protein Interactions to Mediate Plasma Membrane-Cell Wall Adhesions in Arabidopsis1

    Science.gov (United States)

    Gouget, Anne; Senchou, Virginie; Govers, Francine; Sanson, Arnaud; Barre, Annick; Rougé, Pierre; Pont-Lezica, Rafael; Canut, Hervé

    2006-01-01

    Interactions between plant cell walls and plasma membranes are essential for cells to function properly, but the molecules that mediate the structural continuity between wall and membrane are unknown. Some of these interactions, which are visualized upon tissue plasmolysis in Arabidopsis (Arabidopsis thaliana), are disrupted by the RGD (arginine-glycine-aspartic acid) tripeptide sequence, a characteristic cell adhesion motif in mammals. In planta induced-O (IPI-O) is an RGD-containing protein from the plant pathogen Phytophthora infestans that can disrupt cell wall-plasma membrane adhesions through its RGD motif. To identify peptide sequences that specifically bind the RGD motif of the IPI-O protein and potentially play a role in receptor recognition, we screened a heptamer peptide library displayed in a filamentous phage and selected two peptides acting as inhibitors of the plasma membrane RGD-binding activity of Arabidopsis. Moreover, the two peptides also disrupted cell wall-plasma membrane adhesions. Sequence comparison of the RGD-binding peptides with the Arabidopsis proteome revealed 12 proteins containing amino acid sequences in their extracellular domains common with the two RGD-binding peptides. Eight belong to the receptor-like kinase family, four of which have a lectin-like extracellular domain. The lectin domain of one of these, At5g60300, recognized the RGD motif both in peptides and proteins. These results imply that lectin receptor kinases are involved in protein-protein interactions with RGD-containing proteins as potential ligands, and play a structural and signaling role at the plant cell surfaces. PMID:16361528

  16. Binary mask programmable hologram.

    Science.gov (United States)

    Tsang, P W M; Poon, T-C; Zhou, Changhe; Cheung, K W K

    2012-11-19

    We report, for the first time, the concept and generation of a novel Fresnel hologram called the digital binary mask programmable hologram (BMPH). A BMPH is comprised of a static, high resolution binary grating that is overlaid with a lower resolution binary mask. The reconstructed image of the BMPH can be programmed to approximate a target image (including both intensity and depth information) by configuring the pattern of the binary mask with a simple genetic algorithm (SGA). As the low resolution binary mask can be realized with less stringent display technology, our method enables the development of simple and economical holographic video display.

  17. Quantitative Determination of Spatial Protein-protein Proximity in Fluorescence Confocal Microscopy

    CERN Document Server

    Wu, Yong; Ou, Jimmy; Li, Min; Toro, Ligia; Stefani, Enrico

    2009-01-01

    To quantify spatial protein-protein proximity (colocalization) in fluorescence microscopic images, cross-correlation and autocorrelation functions were decomposed into fast and slowly decaying components. The fast component results from clusters of proteins specifically labeled and the slow one from background/image heterogeneity. We show that the calculation of the protein-protein proximity index and the correlation coefficient are more reliably determined by extracting the fast-decaying component. This new method is illustrated by analyzing colocalization in both simulated and biological images.

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

    Institute of Scientific and Technical Information of China (English)

    LIU Xiang; WANG Yifei

    2007-01-01

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

  19. Structures of the Ultra-High-Affinity Protein-Protein Complexes of Pyocins S2 and AP41 and Their Cognate Immunity Proteins from Pseudomonas aeruginosa.

    Science.gov (United States)

    Joshi, Amar; Grinter, Rhys; Josts, Inokentijs; Chen, Sabrina; Wojdyla, Justyna A; Lowe, Edward D; Kaminska, Renata; Sharp, Connor; McCaughey, Laura; Roszak, Aleksander W; Cogdell, Richard J; Byron, Olwyn; Walker, Daniel; Kleanthous, Colin

    2015-08-28

    How ultra-high-affinity protein-protein interactions retain high specificity is still poorly understood. The interaction between colicin DNase domains and their inhibitory immunity (Im) proteins is an ultra-high-affinity interaction that is essential for the neutralisation of endogenous DNase catalytic activity and for protection against exogenous DNase bacteriocins. The colicin DNase-Im interaction is a model system for the study of high-affinity protein-protein interactions. However, despite the fact that closely related colicin-like bacteriocins are widely produced by Gram-negative bacteria, this interaction has only been studied using colicins from Escherichia coli. In this work, we present the first crystal structures of two pyocin DNase-Im complexes from Pseudomonas aeruginosa, pyocin S2 DNase-ImS2 and pyocin AP41 DNase-ImAP41. These structures represent divergent DNase-Im subfamilies and are important in extending our understanding of protein-protein interactions for this important class of high-affinity protein complex. A key finding of this work is that mutations within the immunity protein binding energy hotspot, helix III, are tolerated by complementary substitutions at the DNase-Immunity protein binding interface. Im helix III is strictly conserved in colicins where an Asp forms polar interactions with the DNase backbone. ImAP41 contains an Asp-to-Gly substitution in helix III and our structures show the role of a co-evolved substitution where Pro in DNase loop 4 occupies the volume vacated and removes the unfulfilled hydrogen bond. We observe the co-evolved mutations in other DNase-Immunity pairs that appear to underpin the split of this family into two distinct groups.

  20. pH-selective mutagenesis of protein-protein interfaces: in silico design of therapeutic antibodies with prolonged half-life.

    Science.gov (United States)

    Spassov, Velin Z; Yan, Lisa

    2013-04-01

    Understanding the effects of mutation on pH-dependent protein binding affinity is important in protein design, especially in the area of protein therapeutics. We propose a novel method for fast in silico mutagenesis of protein-protein complexes to calculate the effect of mutation as a function of pH. The free energy differences between the wild type and mutants are evaluated from a molecular mechanics model, combined with calculations of the equilibria of proton binding. The predicted pH-dependent energy profiles demonstrate excellent agreement with experimentally measured pH-dependency of the effect of mutations on the dissociation constants for the complex of turkey ovomucoid third domain (OMTKY3) and proteinase B. The virtual scanning mutagenesis identifies all hotspots responsible for pH-dependent binding of immunoglobulin G (IgG) to neonatal Fc receptor (FcRn) and the results support the current understanding of the salvage mechanism of the antibody by FcRn based on pH-selective binding. The method can be used to select mutations that change the pH-dependent binding profiles of proteins and guide the time consuming and expensive protein engineering experiments. As an application of this method, we propose a computational strategy to search for mutations that can alter the pH-dependent binding behavior of IgG to FcRn with the aim of improving the half-life of therapeutic antibodies in the target organism.

  1. The Epc-N domain: a predicted protein-protein interaction domain found in select chromatin associated proteins

    Directory of Open Access Journals (Sweden)

    Perry Jason

    2006-01-01

    Full Text Available Abstract Background An underlying tenet of the epigenetic code hypothesis is the existence of protein domains that can recognize various chromatin structures. To date, two major candidates have emerged: (i the bromodomain, which can recognize certain acetylation marks and (ii the chromodomain, which can recognize certain methylation marks. Results The Epc-N (Enhancer of Polycomb-N-terminus domain is formally defined herein. This domain is conserved across eukaryotes and is predicted to form a right-handed orthogonal four-helix bundle with extended strands at both termini. The types of amino acid residues that define the Epc-N domain suggest a role in mediating protein-protein interactions, possibly specifically in the context of chromatin binding, and the types of proteins in which it is found (known components of histone acetyltransferase complexes strongly suggest a role in epigenetic structure formation and/or recognition. There appear to be two major Epc-N protein families that can be divided into four unique protein subfamilies. Two of these subfamilies (I and II may be related to one another in that subfamily I can be viewed as a plant-specific expansion of subfamily II. The other two subfamilies (III and IV appear to be related to one another by duplication events in a primordial fungal-metazoan-mycetozoan ancestor. Subfamilies III and IV are further defined by the presence of an evolutionarily conserved five-center-zinc-binding motif in the loop connecting the second and third helices of the four-helix bundle. This motif appears to consist of a PHD followed by a mononuclear Zn knuckle, followed by a PHD-like derivative, and will thus be referred to as the PZPM. All non-Epc-N proteins studied thus far that contain the PZPM have been implicated in histone methylation and/or gene silencing. In addition, an unusual phyletic distribution of Epc-N-containing proteins is observed. Conclusion The data suggest that the Epc-N domain is a protein-protein

  2. Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods

    Directory of Open Access Journals (Sweden)

    Pontil Massimiliano

    2009-10-01

    Full Text Available Abstract Background Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual amino-acids are systematically mutated to alanine and changes in free energy of binding (ΔΔG measured. Several experiments have shown that protein-protein interactions are critically dependent on just a few residues ("hot spots" at the interface. Hot spots make a dominant contribution to the free energy of binding and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there is a need for accurate and reliable computational methods. Such methods would also add to our understanding of the determinants of affinity and specificity in protein-protein recognition. Results We present a novel computational strategy to identify hot spot residues, given the structure of a complex. We consider the basic energetic terms that contribute to hot spot interactions, i.e. van der Waals potentials, solvation energy, hydrogen bonds and Coulomb electrostatics. We treat them as input features and use machine learning algorithms such as Support Vector Machines and Gaussian Processes to optimally combine and integrate them, based on a set of training examples of alanine mutations. We show that our approach is effective in predicting hot spots and it compares favourably to other available methods. In particular we find the best performances using Transductive Support Vector Machines, a semi-supervised learning scheme. When hot spots are defined as those residues for which ΔΔG ≥ 2 kcal/mol, our method achieves a precision and a recall respectively of 56% and 65%. Conclusion We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-09-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-12-01

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

  5. Identifying functional modules in protein-protein interaction networks: An integrated exact approach

    NARCIS (Netherlands)

    Dittrich, M.; Klau, G.W.; Rosenwald, A.; Dandekar, T.; et al, not CWI

    2008-01-01

    Motivation: With the exponential growth of expression and protein-protein interaction (PPI) data, the frontier of research in system biology shifts more and more to the integrated analysis of these large datasets. Of particular interest is the identification of functional modules in PPI networks, sh

  6. Mining minimal motif pair sets maximally covering interactions in a protein-protein interaction network

    NARCIS (Netherlands)

    Boyen, P.; Neven, F.; Valentim, F.L.; Dijk, van A.D.J.

    2013-01-01

    Correlated motif covering (CMC) is the problem of finding a set of motif pairs, i.e., pairs of patterns, in the sequences of proteins from a protein-protein interaction network (PPI-network) that describe the interactions in the network as concisely as possible. In other words, a perfect solution fo

  7. 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

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

    Science.gov (United States)

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

    2015-04-01

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

  9. Analysis of MADS box protein-protein interactions in living plant cells

    NARCIS (Netherlands)

    Immink, R.G.H.; Gadella, T.W.J.; Ferrario, S.I.T.; Busscher, M.; Angenent, G.C.

    2002-01-01

    Over the last decade, the yeast two-hybrid system has become the tool to use for the identification of protein-protein interactions and recently, even complete interactomes were elucidated by this method. Nevertheless, it is an artificial system that is sensitive to errors resulting in the identific

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

    Science.gov (United States)

    Zhang, Shu-Bo; Tang, Qiang-Rong

    2016-07-21

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

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

    DEFF Research Database (Denmark)

    Hartmann-Petersen, Rasmus; Gordon, Colin

    2005-01-01

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

  12. In silico identification of essential proteins in Corynebacterium pseudotuberculosis based on protein-protein interaction networks

    DEFF Research Database (Denmark)

    Folador, Edson Luiz; de Carvalho, Paulo Vinícius Sanches Daltro; Silva, Wanderson Marques;

    2016-01-01

    and decreased production of meat, wool, and milk. Current diagnosis or treatment protocols are not fully effective and, thus, require further research of Cp pathogenesis. RESULTS: Here, we mapped known protein-protein interactions (PPI) from various species to nine Cp strains to reconstruct parts...

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

    Institute of Scientific and Technical Information of China (English)

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

    2003-01-01

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

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

    Science.gov (United States)

    2011-01-01

    Interactions Functional Diversity in Protein Interaction Data Sets—Al- though genomic-scale protein-protein interaction detection campaigns are by design...mapped out in Fig. 2 show that the different data sets covered distinct parts of the interaction space, with some FIG. 1. Functional diversity among

  15. Enabling large-scale design, synthesis and validation of small molecule protein-protein antagonists

    NARCIS (Netherlands)

    Koes, David; Khoury, Kareem; Huang, Yijun; Wang, Wei; Bista, Michal; Popowicz, Grzegorz M; Wolf, Siglinde; Holak, Tad A; Dömling, Alexander; Camacho, Carlos J

    2012-01-01

    Although there is no shortage of potential drug targets, there are only a handful known low-molecular-weight inhibitors of protein-protein interactions (PPIs). One problem is that current efforts are dominated by low-yield high-throughput screening, whose rigid framework is not suitable for the dive

  16. 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.

  17. High content screening biosensor assay to identify disruptors of p53-hDM2 protein-protein interactions.

    Science.gov (United States)

    Hua, Yun; Strock, Christopher J; Johnston, Paul A

    2015-01-01

    This chapter describes the implementation of the p53-hDM2 protein-protein interaction (PPI) biosensor (PPIB) HCS assay to identify disruptors of p53-hDM2 PPIs. Recombinant adenovirus expression constructs were generated bearing the individual p53-GFP and hDM2-RFP PPI partners. The N-terminal p53 transactivating domain that contains the binding site for hDM2 is expressed as a GFP fusion protein that is targeted and anchored in the nucleolus of infected cells by a nuclear localization (NLS) sequence. The p53-GFP biosensor is localized to the nucleolus to enhance and facilitate the image acquisition and analysis of the PPIs. The N-terminus of hDM2 encodes the domain for binding to the transactivating domain of p53, and is expressed as a RFP fusion protein that includes both an NLS and a nuclear export sequence (NES). In U-2 OS cells co-infected with both adenovirus constructs, the binding interactions between hDM2 and p53 result in both biosensors becoming co-localized within the nucleolus. Upon disruption of the p53-hDM2 PPIs, the p53-GFP biosensor remains in the nucleolus while the shuttling hDM2-RFP biosensor redistributes into the cytoplasm. p53-hDM2 PPIs are measured by acquiring fluorescent images of cells co-infected with both adenovirus biosensors on an automated HCS imaging platform and using an image analysis algorithm to quantify the relative distribution of the hDM2-RFP shuttling component of the biosensor between the cytoplasm and nuclear regions of compound treated cells.

  18. Interacting binary stars

    CERN Document Server

    Sahade, Jorge; Ter Haar, D

    1978-01-01

    Interacting Binary Stars deals with the development, ideas, and problems in the study of interacting binary stars. The book consolidates the information that is scattered over many publications and papers and gives an account of important discoveries with relevant historical background. Chapters are devoted to the presentation and discussion of the different facets of the field, such as historical account of the development in the field of study of binary stars; the Roche equipotential surfaces; methods and techniques in space astronomy; and enumeration of binary star systems that are studied

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

    Energy Technology Data Exchange (ETDEWEB)

    Weiss, Shimon

    2006-08-30

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

  20. InterEvDock: a docking server to predict the structure of protein-protein interactions using evolutionary information.

    Science.gov (United States)

    Yu, Jinchao; Vavrusa, Marek; Andreani, Jessica; Rey, Julien; Tufféry, Pierre; Guerois, Raphaël

    2016-07-01

    The structural modeling of protein-protein interactions is key in understanding how cell machineries cross-talk with each other. Molecular docking simulations provide efficient means to explore how two unbound protein structures interact. InterEvDock is a server for protein docking based on a free rigid-body docking strategy. A systematic rigid-body docking search is performed using the FRODOCK program and the resulting models are re-scored with InterEvScore and SOAP-PP statistical potentials. The InterEvScore potential was specifically designed to integrate co-evolutionary information in the docking process. InterEvDock server is thus particularly well suited in case homologous sequences are available for both binding partners. The server returns 10 structures of the most likely consensus models together with 10 predicted residues most likely involved in the interface. In 91% of all complexes tested in the benchmark, at least one residue out of the 10 predicted is involved in the interface, providing useful guidelines for mutagenesis. InterEvDock is able to identify a correct model among the top10 models for 49% of the rigid-body cases with evolutionary information, making it a unique and efficient tool to explore structural interactomes under an evolutionary perspective. The InterEvDock web interface is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock/.

  1. A novel immuno-competitive capture mass spectrometry strategy for protein-protein interaction profiling reveals that LATS kinases regulate HCV replication through NS5A phosphorylation.

    Science.gov (United States)

    Meistermann, Hélène; Gao, Junjun; Golling, Sabrina; Lamerz, Jens; Le Pogam, Sophie; Tzouros, Manuel; Sankabathula, Sailaja; Gruenbaum, Lore; Nájera, Isabel; Langen, Hanno; Klumpp, Klaus; Augustin, Angélique

    2014-11-01

    Mapping protein-protein interactions is essential to fully characterize the biological function of a protein and improve our understanding of diseases. Affinity purification coupled to mass spectrometry (AP-MS) using selective antibodies against a target protein has been commonly applied to study protein complexes. However, one major limitation is a lack of specificity as a substantial part of the proposed binders is due to nonspecific interactions. Here, we describe an innovative immuno-competitive capture mass spectrometry (ICC-MS) method to allow systematic investigation of protein-protein interactions. ICC-MS markedly increases the specificity of classical immunoprecipitation (IP) by introducing a competition step between free and capturing antibody prior to IP. Instead of comparing only one experimental sample with a control, the methodology generates a 12-concentration antibody competition profile. Label-free quantitation followed by a robust statistical analysis of the data is then used to extract the cellular interactome of a protein of interest and to filter out background proteins. We applied this new approach to specifically map the interactome of hepatitis C virus (HCV) nonstructural protein 5A (NS5A) in a cellular HCV replication system and uncovered eight new NS5A-interacting protein candidates along with two previously validated binding partners. Follow-up biological validation experiments revealed that large tumor suppressor homolog 1 and 2 (LATS1 and LATS2, respectively), two closely related human protein kinases, are novel host kinases responsible for NS5A phosphorylation at a highly conserved position required for optimal HCV genome replication. These results are the first illustration of the value of ICC-MS for the analysis of endogenous protein complexes to identify biologically relevant protein-protein interactions with high specificity.

  2. Structural analysis of protein-protein interactions in type I polyketide synthases.

    Science.gov (United States)

    Xu, Wei; Qiao, Kangjian; Tang, Yi

    2013-01-01

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

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

    Science.gov (United States)

    Yang, Lei; Zhao, Xudong; Tang, Xianglong

    2014-01-01

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

  4. Discovery of protein-protein interactions using a combination of linguistic, statistical and graphical information

    Directory of Open Access Journals (Sweden)

    Kershenbaum Aaron

    2005-06-01

    Full Text Available Abstract Background The rapid publication of important research in the biomedical literature makes it increasingly difficult for researchers to keep current with significant work in their area of interest. Results This paper reports a scalable method for the discovery of protein-protein interactions in Medline abstracts, using a combination of text analytics, statistical and graphical analysis, and a set of easily implemented rules. Applying these techniques to 12,300 abstracts, a precision of 0.61 and a recall of 0.97 were obtained, (f = 0.74 and when allowing for two-hop and three-hop relations discovered by graphical analysis, the precision was 0.74 (f = 0.83. Conclusion This combination of linguistic and statistical approaches appears to provide the highest precision and recall thus far reported in detecting protein-protein relations using text analytic approaches.

  5. 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.

  6. Determining effects of non-synonymous SNPs on protein-protein interactions using supervised and semi-supervised learning.

    Directory of Open Access Journals (Sweden)

    Nan Zhao

    2014-05-01

    Full Text Available 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

  7. 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.

  8. Analysis of signaling networks distributed over intracellular compartments based on protein-protein interactions

    OpenAIRE

    2014-01-01

    BackgroundBiological processes are usually distributed over various intracellular compartments. Proteins from diverse cellular compartments are often involved in similar signaling networks. However, the difference in the reaction rates between similar proteins among different compartments is usually quite high. We suggest that the estimation of frequency of intracompartmental as well as intercompartmental protein-protein interactions is an appropriate approach to predict the efficiency of a p...

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

    OpenAIRE

    Meijing Li; Tsendsuren Munkhdalai; Xiuming Yu; Keun Ho Ryu

    2015-01-01

    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 mod...

  10. Cross-species Virus-host Protein-Protein Interactions Inhibiting Innate Immunity

    Science.gov (United States)

    2016-07-01

    SUBJECTTERMS viral pathogen, zoonotic, arenavirus, host tropism, protein - protein interactions, RIG-I, Z protein , CARD domain, MAVS 16. SECURITY...individually subcloned into Checkmate M2H System (Promega) bait and prey reporter plasmids. The genes encoding the viral Z proteins were synthesized... viral proteins were calculated with PhyML. While several residue positions are highly conserved across Z proteins (Figure 8), significant sequence

  11. A Shortest Dependency Path Based Convolutional Neural Network for Protein-Protein Relation Extraction

    OpenAIRE

    2016-01-01

    The state-of-the-art methods for protein-protein interaction (PPI) extraction are primarily based on kernel methods, and their performances strongly depend on the handcraft features. In this paper, we tackle PPI extraction by using convolutional neural networks (CNN) and propose a shortest dependency path based CNN (sdpCNN) model. The proposed method (1) only takes the sdp and word embedding as input and (2) could avoid bias from feature selection by using CNN. We performed experiments on sta...

  12. Mergers of binary neutron stars with realistic spin

    CERN Document Server

    Bernuzzi, Sebastiano; Tichy, Wolfgang; Bruegmann, Bernd

    2013-01-01

    Simulations of binary neutron stars have seen great advances in terms of physical detail and numerical quality. However, the spin of the neutron stars, one of the simplest global parameters of binaries, remains mostly unstudied. We present the first, fully nonlinear general relativistic dynamical evolutions of the last three orbits for constraint satisfying initial data of spinning neutron star binaries, with astrophysically realistic spins aligned and anti-aligned to the orbital angular momentum. The initial data is computed with the constant rotational velocity approach. The dynamics of the systems is analyzed in terms of gauge-invariant binding energy vs. orbital angular momentum curves. By comparing to a binary black hole configuration we can estimate the different tidal and spin contributions to the binding energy for the first time. First results on the gravitational wave forms are presented. The phase evolution during the orbital motion is significantly affected by spin-orbit interactions, leading to d...

  13. Identifying Protein-Protein Associations at the Nuclear Envelope with BioID.

    Science.gov (United States)

    Kim, Dae In; Jensen, Samuel C; Roux, Kyle J

    2016-01-01

    The nuclear envelope (NE) is a critical cellular structure whose constituents and roles in a myriad of cellular processes seem ever expanding. To determine the underlying mechanisms by which the NE constituents participate in various cellular events, it is necessary to understand the nature of their protein-protein associations. BioID (proximity-dependent biotin identification) is a recently established method to generate a history of protein-protein associations as they occur over time in living cells. BioID is based on fusion of a bait protein to a promiscuous biotin ligase. Expression of the BioID fusion protein in a relevant cellular environment enables biotinylation of vicinal and interacting proteins of the bait protein, permitting isolation and identification by conventional biotin-affinity capture and mass-spec analysis. In this way, BioID provides unique capabilities to identify protein-protein associations at the NE. In this chapter we provide a detailed protocol for the application of BioID to the study of NE proteins.

  14. 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.

  15. PathFinder: mining signal transduction pathway segments from protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Yang Jiong

    2007-09-01

    Full Text Available Abstract Background A Signal transduction pathway is the chain of processes by which a cell converts an extracellular signal into a response. In most unicellular organisms, the number of signal transduction pathways influences the number of ways the cell can react and respond to the environment. Discovering signal transduction pathways is an arduous problem, even with the use of systematic genomic, proteomic and metabolomic technologies. These techniques lead to an enormous amount of data and how to interpret and process this data becomes a challenging computational problem. Results In this study we present a new framework for identifying signaling pathways in protein-protein interaction networks. Our goal is to find biologically significant pathway segments in a given interaction network. Currently, protein-protein interaction data has excessive amount of noise, e.g., false positive and false negative interactions. First, we eliminate false positives in the protein-protein interaction network by integrating the network with microarray expression profiles, protein subcellular localization and sequence information. In addition, protein families are used to repair false negative interactions. Then the characteristics of known signal transduction pathways and their functional annotations are extracted in the form of association rules. Conclusion Given a pair of starting and ending proteins, our methodology returns candidate pathway segments between these two proteins with possible missing links (recovered false negatives. In our study, S. cerevisiae (yeast data is used to demonstrate the effectiveness of our method.

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

    Science.gov (United States)

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

    2006-04-01

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

  17. 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.

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

    Science.gov (United States)

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

    2015-09-09

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

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

    Directory of Open Access Journals (Sweden)

    Thorsten Wille

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

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

    Institute of Scientific and Technical Information of China (English)

    Thanigaimani Rajarathinam; Yen-Han Lin

    2006-01-01

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

  1. Predicting protein-protein interactions in Arabidopsis thaliana through integration of orthology, gene ontology and co-expression

    Directory of Open Access Journals (Sweden)

    Vandepoele Klaas

    2009-06-01

    Full Text Available Abstract Background Large-scale identification of the interrelationships between different components of the cell, such as the interactions between proteins, has recently gained great interest. However, unraveling large-scale protein-protein interaction maps is laborious and expensive. Moreover, assessing the reliability of the interactions can be cumbersome. Results In this study, we have developed a computational method that exploits the existing knowledge on protein-protein interactions in diverse species through orthologous relations on the one hand, and functional association data on the other hand to predict and filter protein-protein interactions in Arabidopsis thaliana. A highly reliable set of protein-protein interactions is predicted through this integrative approach making use of existing protein-protein interaction data from yeast, human, C. elegans and D. melanogaster. Localization, biological process, and co-expression data are used as powerful indicators for protein-protein interactions. The functional repertoire of the identified interactome reveals interactions between proteins functioning in well-conserved as well as plant-specific biological processes. We observe that although common mechanisms (e.g. actin polymerization and components (e.g. ARPs, actin-related proteins exist between different lineages, they are active in specific processes such as growth, cancer metastasis and trichome development in yeast, human and Arabidopsis, respectively. Conclusion We conclude that the integration of orthology with functional association data is adequate to predict protein-protein interactions. Through this approach, a high number of novel protein-protein interactions with diverse biological roles is discovered. Overall, we have predicted a reliable set of protein-protein interactions suitable for further computational as well as experimental analyses.

  2. Protein-RNA and Protein-Protein Recognition by Dual KH1/2 Domains of the Neuronal Splicing Factor Nova-1

    Energy Technology Data Exchange (ETDEWEB)

    M Teplova; L Malinina; J Darnell; J Song; M Lu; R Abagyan; K Musunuru; A Teplov; S Burley; et al.

    2011-12-31

    Nova onconeural antigens are neuron-specific RNA-binding proteins implicated in paraneoplastic opsoclonus-myoclonus-ataxia (POMA) syndrome. Nova harbors three K-homology (KH) motifs implicated in alternate splicing regulation of genes involved in inhibitory synaptic transmission. We report the crystal structure of the first two KH domains (KH1/2) of Nova-1 bound to an in vitro selected RNA hairpin, containing a UCAG-UCAC high-affinity binding site. Sequence-specific intermolecular contacts in the complex involve KH1 and the second UCAC repeat, with the RNA scaffold buttressed by interactions between repeats. Whereas the canonical RNA-binding surface of KH2 in the above complex engages in protein-protein interactions in the crystalline state, the individual KH2 domain can sequence-specifically target the UCAC RNA element in solution. The observed antiparallel alignment of KH1 and KH2 domains in the crystal structure of the complex generates a scaffold that could facilitate target pre-mRNA looping on Nova binding, thereby potentially explaining Nova's functional role in splicing regulation.

  3. Kuiper Binary Object Formation

    CERN Document Server

    Nazzario, R C; Covington, C; Kagan, D; Hyde, T W

    2005-01-01

    It has been observed that binary Kuiper Belt Objects (KBOs) exist contrary to theoretical expectations. Their creation presents problems to most current models. However, the inclusion of a third body (for example, one of the outer planets) may provide the conditions necessary for the formation of these objects. The presence of a third massive body not only helps to clear the primordial Kuiper Belt but can also result in long lived binary Kuiper belt objects. The gravitational interaction between the KBOs and the third body causes one of four effects; scattering into the Oort cloud, collisions with the growing protoplanets, formation of binary pairs, or creation of a single Kuiper belt object. Additionally, the initial location of the progenitors of the Kuiper belt objects also has a significant effect on binary formation.

  4. Kuiper Binary Object Formation

    OpenAIRE

    Nazzario, R. C.; Orr, K.; Covington, C.; Kagan, D.; Hyde, T. W.

    2005-01-01

    It has been observed that binary Kuiper Belt Objects (KBOs) exist contrary to theoretical expectations. Their creation presents problems to most current models. However, the inclusion of a third body (for example, one of the outer planets) may provide the conditions necessary for the formation of these objects. The presence of a third massive body not only helps to clear the primordial Kuiper Belt but can also result in long lived binary Kuiper belt objects. The gravitational interaction betw...

  5. Pore-forming activity of clostridial binary toxins.

    Science.gov (United States)

    Knapp, O; Benz, R; Popoff, M R

    2016-03-01

    Clostridial binary toxins (Clostridium perfringens Iota toxin, Clostridium difficile transferase, Clostridium spiroforme toxin, Clostridium botulinum C2 toxin) as Bacillus binary toxins, including Bacillus anthracis toxins consist of two independent proteins, one being the binding component which mediates the internalization into cell of the intracellularly active component. Clostridial binary toxins induce actin cytoskeleton disorganization through mono-ADP-ribosylation of globular actin and are responsible for enteric diseases. Clostridial and Bacillus binary toxins share structurally and functionally related binding components which recognize specific cell receptors, oligomerize, form pores in endocytic vesicle membrane, and mediate the transport of the enzymatic component into the cytosol. Binding components retain the global structure of pore-forming toxins (PFTs) from the cholesterol-dependent cytotoxin family such as perfringolysin. However, their pore-forming activity notably that of clostridial binding components is more related to that of heptameric PFT family including aerolysin and C. perfringens epsilon toxin. This review focuses upon pore-forming activity of clostridial binary toxins compared to other related PFTs. This article is part of a Special Issue entitled: Pore-Forming Toxins edited by Mauro Dalla Serra and Franco Gambale.

  6. Eclipsing Binary Pulsars

    CERN Document Server

    Freire, P C C

    2004-01-01

    The first eclipsing binary pulsar, PSR B1957+20, was discovered in 1987. Since then, 13 other eclipsing low-mass binary pulsars have been found, 12 of these are in globular clusters. In this paper we list the known eclipsing binary pulsars and their properties, with special attention to the eclipsing systems in 47 Tuc. We find that there are two fundamentally different groups of eclipsing binary pulsars; separated by their companion masses. The less massive systems (M_c ~ 0.02 M_sun) are a product of predictable stellar evolution in binary pulsars. The systems with more massive companions (M_c ~ 0.2 M_sun) were formed by exchange encounters in globular clusters, and for that reason are exclusive to those environments. This class of systems can be used to learn about the neutron star recycling fraction in the globular clusters actively forming pulsars. We suggest that most of these binary systems are undetectable at radio wavelengths.

  7. The presence of phosphate-binding protein in inner mitochondrial membrane

    Directory of Open Access Journals (Sweden)

    Hatase,Osamu

    1976-06-01

    Full Text Available Phosphate-binding protein(s was found in the inner mitochondrial membrane of calf heart by Sephadex G-200 and G-25 gel filtration. The binding activity was inhibited by N-ethylmaleimide and competed by a large amount of cold phosphate. The amount of phosphate bound to the fraction was 29 nmoles per mg of protein. Affinity chromatography with phosphate-bound Sepharose 4B confirmed the presence of phosphate-binding protein(s in the active fraction of mitochondrial membrane fractionated by gel filtration.

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

    Directory of Open Access Journals (Sweden)

    Malina Halina Z

    2011-01-01

    Full Text Available Abstract Background 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. Results 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. Conclusions 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

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

    Institute of Scientific and Technical Information of China (English)

    路雅静; 宫夏霓; 孟斐; 杨予涛; 徐志卿

    2012-01-01

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

  10. DECK: Distance and environment-dependent, coarse-grained, knowledge-based potentials for protein-protein docking

    Directory of Open Access Journals (Sweden)

    Vakser Ilya A

    2011-07-01

    Full Text Available Abstract Background Computational approaches to protein-protein docking typically include scoring aimed at improving the rank of the near-native structure relative to the false-positive matches. Knowledge-based potentials improve modeling of protein complexes by taking advantage of the rapidly increasing amount of experimentally derived information on protein-protein association. An essential element of knowledge-based potentials is defining the reference state for an optimal description of the residue-residue (or atom-atom pairs in the non-interaction state. Results The study presents a new Distance- and Environment-dependent, Coarse-grained, Knowledge-based (DECK potential for scoring of protein-protein docking predictions. Training sets of protein-protein matches were generated based on bound and unbound forms of proteins taken from the DOCKGROUND resource. Each residue was represented by a pseudo-atom in the geometric center of the side chain. To capture the long-range and the multi-body interactions, residues in different secondary structure elements at protein-protein interfaces were considered as different residue types. Five reference states for the potentials were defined and tested. The optimal reference state was selected and the cutoff effect on the distance-dependent potentials investigated. The potentials were validated on the docking decoys sets, showing better performance than the existing potentials used in scoring of protein-protein docking results. Conclusions A novel residue-based statistical potential for protein-protein docking was developed and validated on docking decoy sets. The results show that the scoring function DECK can successfully identify near-native protein-protein matches and thus is useful in protein docking. In addition to the practical application of the potentials, the study provides insights into the relative utility of the reference states, the scope of the distance dependence, and the coarse-graining of

  11. Interrogation of the protein-protein interactions between human BRCA2 BRC repeats and RAD51 reveals atomistic determinants of affinity.

    Directory of Open Access Journals (Sweden)

    Daniel J Cole

    2011-07-01

    Full Text Available The breast cancer suppressor BRCA2 controls the recombinase RAD51 in the reactions that mediate homologous DNA recombination, an essential cellular process required for the error-free repair of DNA double-stranded breaks. The primary mode of interaction between BRCA2 and RAD51 is through the BRC repeats, which are ∼35 residue peptide motifs that interact directly with RAD51 in vitro. Human BRCA2, like its mammalian orthologues, contains 8 BRC repeats whose sequence and spacing are evolutionarily conserved. Despite their sequence conservation, there is evidence that the different human BRC repeats have distinct capacities to bind RAD51. A previously published crystal structure reports the structural basis of the interaction between human BRC4 and the catalytic core domain of RAD51. However, no structural information is available regarding the binding of the remaining seven BRC repeats to RAD51, nor is it known why the BRC repeats show marked variation in binding affinity to RAD51 despite only subtle sequence variation. To address these issues, we have performed fluorescence polarisation assays to indirectly measure relative binding affinity, and applied computational simulations to interrogate the behaviour of the eight human BRC-RAD51 complexes, as well as a suite of BRC cancer-associated mutations. Our computational approaches encompass a range of techniques designed to link sequence variation with binding free energy. They include MM-PBSA and thermodynamic integration, which are based on classical force fields, and a recently developed approach to computing binding free energies from large-scale quantum mechanical first principles calculations with the linear-scaling density functional code onetep. Our findings not only reveal how sequence variation in the BRC repeats directly affects affinity with RAD51 and provide significant new insights into the control of RAD51 by human BRCA2, but also exemplify a palette of computational and

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

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    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

  13. DrugScorePPI knowledge-based potentials used as scoring and objective function in protein-protein docking.

    Directory of Open Access Journals (Sweden)

    Dennis M Krüger

    Full Text Available The distance-dependent knowledge-based DrugScore(PPI potentials, previously developed for in silico alanine scanning and hot spot prediction on given structures of protein-protein complexes, are evaluated as a scoring and objective function for the structure prediction of protein-protein complexes. When applied for ranking "unbound perturbation" ("unbound docking" decoys generated by Baker and coworkers a 4-fold (1.5-fold enrichment of acceptable docking solutions in the top ranks compared to a random selection is found. When applied as an objective function in FRODOCK for bound protein-protein docking on 97 complexes of the ZDOCK benchmark 3.0, DrugScore(PPI/FRODOCK finds up to 10% (15% more high accuracy solutions in the top 1 (top 10 predictions than the original FRODOCK implementation. When used as an objective function for global unbound protein-protein docking, fair docking success rates are obtained, which improve by ∼ 2-fold to 18% (58% for an at least acceptable solution in the top 10 (top 100 predictions when performing knowledge-driven unbound docking. This suggests that DrugScore(PPI balances well several different types of interactions important for protein-protein recognition. The results are discussed in view of the influence of crystal packing and the type of protein-protein complex docked. Finally, a simple criterion is provided with which to estimate a priori if unbound docking with DrugScore(PPI/FRODOCK will be successful.

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

    Science.gov (United States)

    Buijsman, W.; Sheinman, M.

    2014-02-01

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

  15. 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.

  16. 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)....

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

    DEFF Research Database (Denmark)

    Andersen, Tonni Grube; Nintemann, Sebastian; Marek, Magdalena;

    2016-01-01

    into the widely used split ubiquitin-, bimolecular fluorescence complementation (BiFC)- and Forster resonance energy transfer (FRET)-based methods and investigated different protein-protein interactions in yeast and plants. We demonstrate the functionality of this concept by the analysis of weakly interacting...... proteins from specialized metabolism in the model plant Arabidopsis thaliana. Our results illustrate that chemically induced dimerization can function as a built-in control for split-based systems that is easily implemented and allows for direct evaluation of functionality....

  18. Assessing protein-protein interactions based on the semantic similarity of interacting proteins.

    Science.gov (United States)

    Cui, Guangyu; Kim, Byungmin; Alguwaizani, Saud; Han, Kyungsook

    2015-01-01

    The Gene Ontology (GO) has been used in estimating the semantic similarity of proteins since it has the largest and reliable vocabulary of gene products and characteristics. We developed a new method which can assess Protein-Protein Interactions (PPI) using the branching factor and information content of the common ancestor of interacting proteins in the GO hierarchy. We performed a comparative evaluation of the measure with other GO-based similarity measures and evaluation results showed that our method outperformed others in most GO domains.

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

    Science.gov (United States)

    Buijsman, W; Sheinman, M

    2014-02-01

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

  20. HomPPI: a class of sequence homology based protein-protein interface prediction methods

    Directory of Open Access Journals (Sweden)

    Dobbs Drena

    2011-06-01

    Full Text Available Abstract Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i NPS-HomPPI (Non partner-specific HomPPI, which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii PS-HomPPI (Partner-specific HomPPI, which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of

  1. Analysis of origin and protein-protein interaction maps suggests distinct oncogenic role of nuclear EGFR during cancer evolution

    Science.gov (United States)

    Sharip, Ainur; Abdukhakimova, Diyora; Wang, Xiao; Kim, Alexey; Kim, Yevgeniy; Sharip, Aigul; Orakov, Askarbek; Miao, Lixia; Sun, Qinglei; Chen, Yue; Chen, Zhenbang; Xie, Yingqiu

    2017-01-01

    Receptor tyrosine kinase EGFR usually is localized on plasma membrane to induce progression of many cancers including cancers in children (Bodey et al. In Vivo. 2005, 19:931-41), but it contains a nuclear localization signal (NLS) that mediates EGFR nuclear translocation (Lin et al. Nat Cell Biol. 2001, 3:802-8). Here we report that NLS of EGFR has its old evolutionary origin. Protein-protein interaction maps suggests that nEGFR pathways are different from membrane EGFR and EGF is not found in nEGFR network while androgen receptor (AR) is found, which suggests the evolution of prostate cancer, a well-known AR driven cancer, through changes in androgen- or EGF-dependence. Database analysis suggests that nEGFR correlates with the tumor grades especially in prostate cancer patients. Structural predication analysis suggests that NLS can compromise the differential protein binding to EGFR through stretch linkers with evolutionary mutation from N to V. In experiment, elevation of nEGFR but not membrane EGFR was found in castration resistant prostate cancer cells. Finally, systems analysis of NLS and transmembrane domain (TM) suggests that NLS has old origin while NLS neighboring domain of TM has been undergone accelerated evolution. Thus nEGFR has an old origin resembling the cancer evolution but TM may interfere with NLS driven signaling for natural selection of survival to evade NLS induced aggressive cancers. Our data suggest NLS is a dynamic inducer of EGFR oncogenesis during evolution for advanced cancers. Our model provides novel insights into the evolutionary role of NLS of oncogenic kinases in cancers.

  2. Binary Masking & Speech Intelligibility

    DEFF Research Database (Denmark)

    Boldt, Jesper

    The purpose of this thesis is to examine how binary masking can be used to increase intelligibility in situations where hearing impaired listeners have difficulties understanding what is being said. The major part of the experiments carried out in this thesis can be categorized as either experime...... mask using a directional system and a method for correcting errors in the target binary mask. The last part of the thesis, proposes a new method for objective evaluation of speech intelligibility.......The purpose of this thesis is to examine how binary masking can be used to increase intelligibility in situations where hearing impaired listeners have difficulties understanding what is being said. The major part of the experiments carried out in this thesis can be categorized as either...... experiments under ideal conditions or as experiments under more realistic conditions useful for real-life applications such as hearing aids. In the experiments under ideal conditions, the previously defined ideal binary mask is evaluated using hearing impaired listeners, and a novel binary mask -- the target...

  3. Skewed Binary Search Trees

    DEFF Research Database (Denmark)

    Brodal, Gerth Stølting; Moruz, Gabriel

    2006-01-01

    It is well-known that to minimize the number of comparisons a binary search tree should be perfectly balanced. Previous work has shown that a dominating factor over the running time for a search is the number of cache faults performed, and that an appropriate memory layout of a binary search tree...... can reduce the number of cache faults by several hundred percent. Motivated by the fact that during a search branching to the left or right at a node does not necessarily have the same cost, e.g. because of branch prediction schemes, we in this paper study the class of skewed binary search trees....... For all nodes in a skewed binary search tree the ratio between the size of the left subtree and the size of the tree is a fixed constant (a ratio of 1/2 gives perfect balanced trees). In this paper we present an experimental study of various memory layouts of static skewed binary search trees, where each...

  4. Binary Neutron Star Mergers

    Directory of Open Access Journals (Sweden)

    Joshua A. Faber

    2012-07-01

    Full Text Available We review the current status of studies of the coalescence of binary neutron star systems. We begin with a discussion of the formation channels of merging binaries and we discuss the most recent theoretical predictions for merger rates. Next, we turn to the quasi-equilibrium formalisms that are used to study binaries prior to the merger phase and to generate initial data for fully dynamical simulations. The quasi-equilibrium approximation has played a key role in developing our understanding of the physics of binary coalescence and, in particular, of the orbital instability processes that can drive binaries to merger at the end of their lifetimes. We then turn to the numerical techniques used in dynamical simulations, including relativistic formalisms, (magneto-hydrodynamics, gravitational-wave extraction techniques, and nuclear microphysics treatments. This is followed by a summary of the simulations performed across the field to date, including the most recent results from both fully relativistic and microphysically detailed simulations. Finally, we discuss the likely directions for the field as we transition from the first to the second generation of gravitational-wave interferometers and while supercomputers reach the petascale frontier.

  5. 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.

  6. 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.

  7. Direct and Propagated Effects of Small Molecules on Protein-Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Laura C Cesa

    2015-08-01

    Full Text Available Networks of protein-protein interactions (PPIs link all aspects of cellular biology. Dysfunction in the assembly or dynamics of PPI networks is a hallmark of human disease, and as such, there is growing interest in the discovery of small molecules that either promote or inhibit PPIs. Protein-protein interactions were once considered undruggable because of their relatively large buried surface areas and difficult topologies. Despite these challenges, recent advances in chemical screening methodologies, combined with improvements in structural and computational biology have made some of these targets more tractable. In this review, we highlight developments that have opened the door to potent chemical modulators. We focus on how allostery is being used to produce surprisingly robust changes in PPIs, even for the most challenging targets. We also discuss how interfering with one PPI can propagate changes through the broader web of interactions. Through this analysis, it is becoming clear that a combination of direct and propagated effects on PPI networks is ultimately how small molecules re-shape biology.

  8. A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces

    Science.gov (United States)

    Melo, Rita; Fieldhouse, Robert; Melo, André; Correia, João D. G.; Cordeiro, Maria Natália D. S.; Gümüş, Zeynep H.; Costa, Joaquim; Bonvin, Alexandre M. J. J.; Moreira, Irina S.

    2016-01-01

    Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous published Machine Learning (ML) techniques. Our model is trained on a large number of complexes and on a significantly larger number of different structural- and evolutionary sequence-based features. In particular, we added interface size, type of interaction between residues at the interface of the complex, number of different types of residues at the interface and the Position-Specific Scoring Matrix (PSSM), for a total of 79 features. We used twenty-seven algorithms from a simple linear-based function to support-vector machine models with different cost functions. The best model was achieved by the use of the conditional inference random forest (c-forest) algorithm with a dataset pre-processed by the normalization of features and with up-sampling of the minor class. The method has an overall accuracy of 0.80, an F1-score of 0.73, a sensitivity of 0.76 and a specificity of 0.82 for the independent test set. PMID:27472327

  9. 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.

  10. PPLook: an automated data mining tool for protein-protein interaction

    Directory of Open Access Journals (Sweden)

    Xia Li

    2010-06-01

    Full Text Available Abstract Background Extracting and visualizing of protein-protein interaction (PPI from text literatures are a meaningful topic in protein science. It assists the identification of interactions among proteins. There is a lack of tools to extract PPI, visualize and classify the results. Results We developed a PPI search system, termed PPLook, which automatically extracts and visualizes protein-protein interaction (PPI from text. Given a query protein name, PPLook can search a dataset for other proteins interacting with it by using a keywords dictionary pattern-matching algorithm, and display the topological parameters, such as the number of nodes, edges, and connected components. The visualization component of PPLook enables us to view the interaction relationship among the proteins in a three-dimensional space based on the OpenGL graphics interface technology. PPLook can also provide the functions of selecting protein semantic class, counting the number of semantic class proteins which interact with query protein, counting the literature number of articles appearing the interaction relationship about the query protein. Moreover, PPLook provides heterogeneous search and a user-friendly graphical interface. Conclusions PPLook is an effective tool for biologists and biosystem developers who need to access PPI information from the literature. PPLook is freely available for non-commercial users at http://meta.usc.edu/softs/PPLook.

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

    Institute of Scientific and Technical Information of China (English)

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

    2007-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

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

  14. Features of protein-protein interactions in two-component signaling deduced from genomic libraries.

    Science.gov (United States)

    White, Robert A; Szurmant, Hendrik; Hoch, James A; Hwa, Terence

    2007-01-01

    As more and more sequence data become available, new approaches for extracting information from these data become feasible. This chapter reports on one such method that has been applied to elucidate protein-protein interactions in bacterial two-component signaling pathways. The method identifies residues involved in the interaction through an analysis of over 2500 functionally coupled proteins and a precise determination of the substitutional constraints placed on one protein by its signaling mate. Once identified, a simple log-likelihood scoring procedure is applied to these residues to build a predictive tool for assigning signaling mates. The ability to apply this method is based on a proliferation of related domains within multiple organisms. Paralogous evolution through gene duplication and divergence of two-component systems has commonly resulted in tens of closely related interacting pairs within one organism with a roughly one-to-one correspondence between signal and response. This provides us with roughly an order of magnitude more protein pairs than there are unique, fully sequenced bacterial species. Consequently, this chapter serves as both a detailed exposition of the method that has provided more depth to our knowledge of bacterial signaling and a look ahead to what would be possible on a more widespread scale, that is, to protein-protein interactions that have only one example per genome, as the number of genomes increases by a factor of 10.

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

    Science.gov (United States)

    Kodama, Yutaka; Suetsugu, Noriyuki; Wada, Masamitsu

    2011-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Zhang Aidong

    2006-12-01

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

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

    Science.gov (United States)

    K, Muhammed Jamsheer; Laxmi, Ashverya

    2014-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2013-01-01

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

  19. 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.

  20. A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces

    Directory of Open Access Journals (Sweden)

    Rita Melo

    2016-07-01

    Full Text Available Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS in protein-protein interfaces from their native complex structure compared to previous published Machine Learning (ML techniques. Our model is trained on a large number of complexes and on a significantly larger number of different structural- and evolutionary sequence-based features. In particular, we added interface size, type of interaction between residues at the interface of the complex, number of different types of residues at the interface and the Position-Specific Scoring Matrix (PSSM, for a total of 79 features. We used twenty-seven algorithms from a simple linear-based function to support-vector machine models with different cost functions. The best model was achieved by the use of the conditional inference random forest (c-forest algorithm with a dataset pre-processed by the normalization of features and with up-sampling of the minor class. The method has an overall accuracy of 0.80, an F1-score of 0.73, a sensitivity of 0.76 and a specificity of 0.82 for the independent test set.

  1. 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.

  2. Prediction of Protein-protein Interactions on the Basis of Evolutionary Conservation of Protein Functions

    Directory of Open Access Journals (Sweden)

    Ekaterina Kotelnikova

    2007-01-01

    Full Text Available Motivation: Although a great deal of progress is being made in the development of fast and reliable experimental techniques to extract genome-wide networks of protein-protein and protein-DNA interactions, the sequencing of new genomes proceeds at an even faster rate. That is why there is a considerable need for reliable methods of in-silico prediction of protein interaction based solely on sequence similarity information and known interactions from well-studied organisms. This problem can be solved if a dependency exists between sequence similarity and the conservation of the proteins’ functions.Results: In this paper, we introduce a novel probabilistic method for prediction of protein-protein interactions using a new empirical probabilistic formula describing the loss of interactions between homologous proteins during the course of evolution. This formula describes an evolutional process quite similar to the process of the Earth’s population growth. In addition, our method favors predictions confi rmed by several interacting pairs over predictions coming from a single interacting pair. Our approach is useful in working with “noisy” data such as those coming from high-throughput experiments. We have generated predictions for fi ve “model” organisms: H. sapiens, D. melanogaster, C. elegans, A. thaliana, and S. cerevisiae and evaluated the quality of these predictions.

  3. Binary and Millisecond Pulsars

    Directory of Open Access Journals (Sweden)

    Lorimer Duncan R.

    2008-11-01

    Full Text Available We review the main properties, demographics and applications of binary and millisecond radio pulsars. Our knowledge of these exciting objects has greatly increased in recent years, mainly due to successful surveys which have brought the known pulsar population to over 1800. There are now 83 binary and millisecond pulsars associated with the disk of our Galaxy, and a further 140 pulsars in 26 of the Galactic globular clusters. Recent highlights include the discovery of the young relativistic binary system PSR J1906+0746, a rejuvination in globular cluster pulsar research including growing numbers of pulsars with masses in excess of 1.5M_⊙, a precise measurement of relativistic spin precession in the double pulsar system and a Galactic millisecond pulsar in an eccentric (e = 0.44 orbit around an unevolved companion.

  4. Binary Popldation Synthcsis Study

    Institute of Scientific and Technical Information of China (English)

    HAN Zhanwen

    2011-01-01

    Binary population synthesis (BPS), an approach to evolving millions of stars (including binaries) simultaneously, plays a crucial role in our understanding of stellar physics, the structure and evolution of galaxies, and cosmology. We proposed and developed a BPS approach, and used it to investigate the formation of many peculiar stars such as hot subdwarf stars, progenitors of type la supernovae, barium stars, CH stars, planetary nebulae, double white dwarfs, blue stragglers, contact binaries, etc. We also established an evolution population synthesis (EPS) model, the Yunnan Model, which takes into account binary interactions for the first time. We applied our model for the origin of hot subdwarf stars in the study of elliptical galaxies and explained their far-UV radiation.

  5. Eclipsing Binary Update, No. 2.

    Science.gov (United States)

    Williams, D. B.

    1996-01-01

    Contents: 1. Wrong again! The elusive period of DHK 41. 2. Stars observed and not observed. 3. Eclipsing binary chart information. 4. Eclipsing binary news and notes. 5. A note on SS Arietis. 6. Featured star: TX Ursae Majoris.

  6. Protein-protein docking using region-based 3D Zernike descriptors

    Directory of Open Access Journals (Sweden)

    Sael Lee

    2009-12-01

    Full Text Available Abstract Background Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. Results We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-αRMSD ≤ 2.5 Å within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. Conclusion We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for

  7. Compressing Binary Decision Diagrams

    DEFF Research Database (Denmark)

    Hansen, Esben Rune; Satti, Srinivasa Rao; Tiedemann, Peter

    2008-01-01

    The paper introduces a new technique for compressing Binary Decision Diagrams in those cases where random access is not required. Using this technique, compression and decompression can be done in linear time in the size of the BDD and compression will in many cases reduce the size of the BDD to 1...

  8. Compressing Binary Decision Diagrams

    DEFF Research Database (Denmark)

    Rune Hansen, Esben; Srinivasa Rao, S.; Tiedemann, Peter

    The paper introduces a new technique for compressing Binary Decision Diagrams in those cases where random access is not required. Using this technique, compression and decompression can be done in linear time in the size of the BDD and compression will in many cases reduce the size of the BDD to 1...

  9. Orbits for sixteen binaries

    Directory of Open Access Journals (Sweden)

    Cvetković Z.

    2006-01-01

    Full Text Available In this paper orbits for 13 binaries are recalculated and presented. The reason is that recent observations show higher residuals than the corresponding ephemerides calculated by using the orbital elements given in the Sixth Catalog of Orbits of Visual Binary Stars. The binaries studied were: WDS 00182+7257 = A 803, WDS 00335+4006 = HO 3, WDS 00583+2124 = BU 302, WDS 01011+6022 = A 926, WDS 01014+1155 = BU 867, WDS 01112+4113 = A 655, WDS 01361−2954 + HJ 3447, WDS 02333+5219 = STT 42 AB,WDS 04362+0814 = A 1840 AB,WDS 08017−0836 = A 1580, WDS 08277−0425 = A 550, WDS 17471+1742 = STF 2215 and WDS 18025+4414 = BU 1127 Aa-B. In addition, for three binaries - WDS 01532+1526 = BU 260, WDS 02563+7253 = STF 312 AB and WDS 05003+3924 = STT 92 AB - the orbital elements are calculated for the first time. In this paper the authors present not only the orbital elements, but the masses dynamical parallaxes, absolute magnitudes and ephemerides for the next five years, as well.

  10. Equational binary decision diagrams

    NARCIS (Netherlands)

    Groote, J.F.; Pol, J.C. van de

    2000-01-01

    We incorporate equations in binary decision diagrams (BDD). The resulting objects are called EQ-BDDs. A straightforward notion of ordered EQ-BDDs (EQ-OBDD) is defined, and it is proved that each EQ-BDD is logically equivalent to an EQ-OBDD. Moreover, on EQ-OBDDs satisfiability and tautology checkin

  11. High-sensitivity real-time imaging of dual protein-protein interactions in living subjects using multicolor luciferases.

    Directory of Open Access Journals (Sweden)

    Naoki Hida

    Full Text Available Networks of protein-protein interactions play key roles in numerous important biological processes in living subjects. An effective methodology to assess protein-protein interactions in living cells of interest is protein-fragment complement assay (PCA. Particularly the assays using fluorescent proteins are powerful techniques, but they do not directly track interactions because of its irreversibility or the time for chromophore formation. By contrast, PCAs using bioluminescent proteins can overcome these drawbacks. We herein describe an imaging method for real-time analysis of protein-protein interactions using multicolor luciferases with different spectral characteristics. The sensitivity and signal-to-background ratio were improved considerably by developing a carboxy-terminal fragment engineered from a click beetle luciferase. We demonstrate its utility in spatiotemporal characterization of Smad1-Smad4 and Smad2-Smad4 interactions in early developing stages of a single living Xenopus laevis embryo. We also describe the value of this method by application of specific protein-protein interactions in cell cultures and living mice. This technique supports quantitative analyses and imaging of versatile protein-protein interactions with a selective luminescence wavelength in opaque or strongly auto-fluorescent living subjects.

  12. Construction of a cancer-perturbed protein-protein interaction network for discovery of apoptosis drug targets

    Directory of Open Access Journals (Sweden)

    Chen Bor-Sen

    2008-06-01

    Full Text Available Abstract Background Cancer is caused by genetic abnormalities, such as mutations of oncogenes or tumor suppressor genes, which alter downstream signal transduction pathways and protein-protein interactions. Comparisons of the interactions of proteins in cancerous and normal cells can shed light on the mechanisms of carcinogenesis. Results We constructed initial networks of protein-protein interactions involved in the apoptosis of cancerous and normal cells by use of two human yeast two-hybrid data sets and four online databases. Next, we applied a nonlinear stochastic model, maximum likelihood parameter estimation, and Akaike Information Criteria (AIC to eliminate false-positive protein-protein interactions in our initial protein interaction networks by use of microarray data. Comparisons of the networks of apoptosis in HeLa (human cervical carcinoma cells and in normal primary lung fibroblasts provided insight into the mechanism of apoptosis and allowed identification of potential drug targets. The potential targets include BCL2, caspase-3 and TP53. Our comparison of cancerous and normal cells also allowed derivation of several party hubs and date hubs in the human protein-protein interaction networks involved in caspase activation. Conclusion Our method allows identification of cancer-perturbed protein-protein interactions involved in apoptosis and identification of potential molecular targets for development of anti-cancer drugs.

  13. Open source tool for prediction of genome wide protein-protein interaction network based on ortholog information

    Directory of Open Access Journals (Sweden)

    Pedamallu Chandra Sekhar

    2010-08-01

    Full Text Available Abstract Background Protein-protein interactions are crucially important for cellular processes. Knowledge of these interactions improves the understanding of cell cycle, metabolism, signaling, transport, and secretion. Information about interactions can hint at molecular causes of diseases, and can provide clues for new therapeutic approaches. Several (usually expensive and time consuming experimental methods can probe protein - protein interactions. Data sets, derived from such experiments make the development of prediction methods feasible, and make the creation of protein-protein interaction network predicting tools possible. Methods Here we report the development of a simple open source program module (OpenPPI_predictor that can generate a putative protein-protein interaction network for target genomes. This tool uses the orthologous interactome network data from a related, experimentally studied organism. Results Results from our predictions can be visualized using the Cytoscape visualization software, and can be piped to downstream processing algorithms. We have employed our program to predict protein-protein interaction network for the human parasite roundworm Brugia malayi, using interactome data from the free living nematode Caenorhabditis elegans. Availability The OpenPPI_predictor source code is available from http://tools.neb.com/~posfai/.

  14. Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

    KAUST Repository

    Oliva, Romina

    2015-07-01

    In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

  15. Black holes in binary stars

    NARCIS (Netherlands)

    Wijers, R.A.M.J.

    1996-01-01

    Introduction Distinguishing neutron stars and black holes Optical companions and dynamical masses X-ray signatures of the nature of a compact object Structure and evolution of black-hole binaries High-mass black-hole binaries Low-mass black-hole binaries Low-mass black holes Formation of black holes

  16. Insight into the intermolecular recognition mechanism between Keap1 and IKKβ combining homology modelling, protein-protein docking, molecular dynamics simulations and virtual alanine mutation.

    Directory of Open Access Journals (Sweden)

    Zheng-Yu Jiang

    Full Text Available Degradation of certain proteins through the ubiquitin-proteasome pathway is a common strategy taken by the key modulators responsible for stress responses. Kelch-like ECH-associated protein-1(Keap1, a substrate adaptor component of the Cullin3 (Cul3-based ubiquitin E3 ligase complex, mediates the ubiquitination of two key modulators, NF-E2-related factor 2 (Nrf2 and IκB kinase β (IKKβ, which are involved in the redox control of gene transcription. However, compared to the Keap1-Nrf2 protein-protein interaction (PPI, the intermolecular recognition mechanism of Keap1 and IKKβ has been poorly investigated. In order to explore the binding pattern between Keap1 and IKKβ, the PPI model of Keap1 and IKKβ was investigated. The structure of human IKKβ was constructed by means of the homology modeling method and using reported crystal structure of Xenopus laevis IKKβ as the template. A protein-protein docking method was applied to develop the Keap1-IKKβ complex model. After the refinement and visual analysis of docked proteins, the chosen pose was further optimized through molecular dynamics simulations. The resulting structure was utilized to conduct the virtual alanine mutation for the exploration of hot-spots significant for the intermolecular interaction. Overall, our results provided structural insights into the PPI model of Keap1-IKKβ and suggest that the substrate specificity of Keap1 depend on the interaction with the key tyrosines, namely Tyr525, Tyr574 and Tyr334. The study presented in the current project may be useful to design molecules that selectively modulate Keap1. The selective recognition mechanism of Keap1 with IKKβ or Nrf2 will be helpful to further know the crosstalk between NF-κB and Nrf2 signaling.

  17. Insight into the intermolecular recognition mechanism between Keap1 and IKKβ combining homology modelling, protein-protein docking, molecular dynamics simulations and virtual alanine mutation.

    Science.gov (United States)

    Jiang, Zheng-Yu; Chu, Hong-Xi; Xi, Mei-Yang; Yang, Ting-Ting; Jia, Jian-Min; Huang, Jing-Jie; Guo, Xiao-Ke; Zhang, Xiao-Jin; You, Qi-Dong; Sun, Hao-Peng

    2013-01-01

    Degradation of certain proteins through the ubiquitin-proteasome pathway is a common strategy taken by the key modulators responsible for stress responses. Kelch-like ECH-associated protein-1(Keap1), a substrate adaptor component of the Cullin3 (Cul3)-based ubiquitin E3 ligase complex, mediates the ubiquitination of two key modulators, NF-E2-related factor 2 (Nrf2) and IκB kinase β (IKKβ), which are involved in the redox control of gene transcription. However, compared to the Keap1-Nrf2 protein-protein interaction (PPI), the intermolecular recognition mechanism of Keap1 and IKKβ has been poorly investigated. In order to explore the binding pattern between Keap1 and IKKβ, the PPI model of Keap1 and IKKβ was investigated. The structure of human IKKβ was constructed by means of the homology modeling method and using reported crystal structure of Xenopus laevis IKKβ as the template. A protein-protein docking method was applied to develop the Keap1-IKKβ complex model. After the refinement and visual analysis of docked proteins, the chosen pose was further optimized through molecular dynamics simulations. The resulting structure was utilized to conduct the virtual alanine mutation for the exploration of hot-spots significant for the intermolecular interaction. Overall, our results provided structural insights into the PPI model of Keap1-IKKβ and suggest that the substrate specificity of Keap1 depend on the interaction with the key tyrosines, namely Tyr525, Tyr574 and Tyr334. The study presented in the current project may be useful to design molecules that selectively modulate Keap1. The selective recognition mechanism of Keap1 with IKKβ or Nrf2 will be helpful to further know the crosstalk between NF-κB and Nrf2 signaling.

  18. Artificial septal targeting of Bacillus subtilis cell division proteins in Escherichia coli: an interspecies approach to the study of protein-protein interactions in multiprotein complexes.

    Science.gov (United States)

    Robichon, Carine; King, Glenn F; Goehring, Nathan W; Beckwith, Jon

    2008-09-01

    Bacterial cell division is mediated by a set of proteins that assemble to form a large multiprotein complex called the divisome. Recent studies in Bacillus subtilis and Escherichia coli indicate that cell division proteins are involved in multiple cooperative binding interactions, thus presenting a technical challenge to the analysis of these interactions. We report here the use of an E. coli artificial septal targeting system for examining the interactions between the B. subtilis cell division proteins DivIB, FtsL, DivIC, and PBP 2B. This technique involves the fusion of one of the proteins (the "bait") to ZapA, an E. coli protein targeted to mid-cell, and the fusion of a second potentially interacting partner (the "prey") to green fluorescent protein (GFP). A positive interaction between two test proteins in E. coli leads to septal localization of the GFP fusion construct, which can be detected by fluorescence microscopy. Using this system, we present evidence for two sets of strong protein-protein interactions between B. subtilis divisomal proteins in E. coli, namely, DivIC with FtsL and DivIB with PBP 2B, that are independent of other B. subtilis cell division proteins and that do not disturb the cytokinesis process in the host cell. Our studies based on the coexpression of three or four of these B. subtilis cell division proteins suggest that interactions among these four proteins are not strong enough to allow the formation of a stable four-protein complex in E. coli in contrast to previous suggestions. Finally, our results demonstrate that E. coli artificial septal targeting is an efficient and alternative approach for detecting and characterizing stable protein-protein interactions within multiprotein complexes from other microorganisms. A salient feature of our approach is that it probably only detects the strongest interactions, thus giving an indication of whether some interactions suggested by other techniques may either be considerably weaker or due to

  19. Learning to assign binary weights to binary descriptor

    Science.gov (United States)

    Huang, Zhoudi; Wei, Zhenzhong; Zhang, Guangjun

    2016-10-01

    Constructing robust binary local feature descriptors are receiving increasing interest due to their binary nature, which can enable fast processing while requiring significantly less memory than their floating-point competitors. To bridge the performance gap between the binary and floating-point descriptors without increasing the computational cost of computing and matching, optimal binary weights are learning to assign to binary descriptor for considering each bit might contribute differently to the distinctiveness and robustness. Technically, a large-scale regularized optimization method is applied to learn float weights for each bit of the binary descriptor. Furthermore, binary approximation for the float weights is performed by utilizing an efficient alternatively greedy strategy, which can significantly improve the discriminative power while preserve fast matching advantage. Extensive experimental results on two challenging datasets (Brown dataset and Oxford dataset) demonstrate the effectiveness and efficiency of the proposed method.

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

    Science.gov (United States)

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

    2015-01-01

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

  1. Quantitative analysis of protein-protein interactions by split firefly luciferase complementation in plant protoplasts.

    Science.gov (United States)

    Li, Jian-Feng; Zhang, Dandan

    2014-07-01

    This unit describes the split firefly luciferase complementation (SFLC) assay, a high-throughput quantitative method that can be used to investigate protein-protein interactions (PPIs) in plant mesophyll protoplasts. In SFLC, the two proteins to be tested for interaction are expressed as chimeric proteins, each fused to a different half of firefly luciferase. If the proteins interact, a functional luciferase can be transitorily reconstituted, and is detected using the cell-permeable substrate D-luciferin. An advantage of the SFLC assay is that dynamic changes in PPIs in a cell can be detected in a near real-time manner. Another advantage is the unusually high DNA co-transfection and protein expression efficiencies that can be achieved in plant protoplasts, thereby enhancing the throughput of the method.

  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...... leading to attenuated dopamine clearance and for amphetamine even increased dopamine release. In the last decade, intensive efforts have been directed towards understanding the molecular and cellular mechanisms governing the activity and availability of DAT in the plasma membrane of the pre...... 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. Prediction and systematic study of protein-protein interaction networks of Leptospira interrogans

    Institute of Scientific and Technical Information of China (English)

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

    2006-01-01

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

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

    CERN Document Server

    Zhang, Xizhe; Yang, Yunyi

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-10-01

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

  6. A Shortest Dependency Path Based Convolutional Neural Network for Protein-Protein Relation Extraction

    Directory of Open Access Journals (Sweden)

    Lei Hua

    2016-01-01

    Full Text Available The state-of-the-art methods for protein-protein interaction (PPI extraction are primarily based on kernel methods, and their performances strongly depend on the handcraft features. In this paper, we tackle PPI extraction by using convolutional neural networks (CNN and propose a shortest dependency path based CNN (sdpCNN model. The proposed method (1 only takes the sdp and word embedding as input and (2 could avoid bias from feature selection by using CNN. We performed experiments on standard Aimed and BioInfer datasets, and the experimental results demonstrated that our approach outperformed state-of-the-art kernel based methods. In particular, by tracking the sdpCNN model, we find that sdpCNN could extract key features automatically and it is verified that pretrained word embedding is crucial in PPI task.

  7. A Shortest Dependency Path Based Convolutional Neural Network for Protein-Protein Relation Extraction.

    Science.gov (United States)

    Hua, Lei; Quan, Chanqin

    2016-01-01

    The state-of-the-art methods for protein-protein interaction (PPI) extraction are primarily based on kernel methods, and their performances strongly depend on the handcraft features. In this paper, we tackle PPI extraction by using convolutional neural networks (CNN) and propose a shortest dependency path based CNN (sdpCNN) model. The proposed method (1) only takes the sdp and word embedding as input and (2) could avoid bias from feature selection by using CNN. We performed experiments on standard Aimed and BioInfer datasets, and the experimental results demonstrated that our approach outperformed state-of-the-art kernel based methods. In particular, by tracking the sdpCNN model, we find that sdpCNN could extract key features automatically and it is verified that pretrained word embedding is crucial in PPI task.

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    Matej Zábrady

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

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    Baoman Wang

    2015-01-01

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

  12. ATTRACT and PTools: open source programs for protein-protein docking.

    Science.gov (United States)

    Schneider, Sebastian; Saladin, Adrien; Fiorucci, Sébastien; Prévost, Chantal; Zacharias, Martin

    2012-01-01

    The prediction of the structure of protein-protein complexes based on structures or structural models of isolated partners is of increasing importance for structural biology and bioinformatics. The ATTRACT program can be used to perform systematic docking searches based on docking energy minimization. It is part of the object-oriented PTools library written in Python and C++. The library contains various routines to manipulate protein structures, to prepare and perform docking searches as well as analyzing docking results. It also intended to facilitate further methodological developments in the area of macromolecular docking that can be easily integrated. Here, we describe the application of PTools to perform systematic docking searches and to analyze the results. In addition, the possibility to perform multi-component docking will also be presented.

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

    Science.gov (United States)

    Jia, Jianhua; Xiao, Xuan; Liu, Bingxiang

    2016-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Sylvain Lacomble

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

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

    CERN Document Server

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

    2007-01-01

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

  16. Protein-protein interactions: a supra-structural phenomenon demanding trans-disciplinary biophysical approaches.

    Science.gov (United States)

    Byron, Olwyn; Vestergaard, Bente

    2015-12-01

    Responsive formation of protein:protein interaction (PPI) upon diverse stimuli is a fundament of cellular function. As a consequence, PPIs are complex, adaptive entities, and exist in structurally heterogeneous interplays defined by the energetic states of the free and complexed protomers. The biophysical and structural investigations of PPIs consequently demand hybrid approaches, implementing orthogonal methods and strategies for global data analysis. Currently, impressive developments in hardware and software within several methodologies define a new era for the biostructural community. Data can be obtained at increasing resolution, at relevant time-scales and under increasingly relevant experimental conditions, intricate data are interpreted reliably, and the questions posed and answered grow in complexity. With this review, highlights from the study of PPIs using a multitude of biophysical methods, are reported. The aim is to depict how the elucidation of the interplay of structures requires the interplay of methods.

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

    Science.gov (United States)

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

    2014-01-01

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

  18. Protein-protein interactions visualized by bimolecular fluorescence complementation in tobacco protoplasts and leaves.

    Science.gov (United States)

    Schweiger, Regina; Schwenkert, Serena

    2014-03-09

    Many proteins interact transiently with other proteins or are integrated into multi-protein complexes to perform their biological function. Bimolecular fluorescence complementation (BiFC) is an in vivo method to monitor such interactions in plant cells. In the presented protocol the investigated candidate proteins are fused to complementary halves of fluorescent proteins and the respective constructs are introduced into plant cells via agrobacterium-mediated transformation. Subsequently, the proteins are transiently expressed in tobacco leaves and the restored fluorescent signals can be detected with a confocal laser scanning microscope in the intact cells. This allows not only visualization of the interaction itself, but also the subcellular localization of the protein complexes can be determined. For this purpose, marker genes containing a fluorescent tag can be coexpressed along with the BiFC constructs, thus visualizing cellular structures such as the endoplasmic reticulum, mitochondria, the Golgi apparatus or the plasma membrane. The fluorescent signal can be monitored either directly in epidermal leaf cells or in single protoplasts, which can be easily isolated from the transformed tobacco leaves. BiFC is ideally suited to study protein-protein interactions in their natural surroundings within the living cell. However, it has to be considered that the expression has to be driven by strong promoters and that the interaction partners are modified due to fusion of the relatively large fluorescence tags, which might interfere with the interaction mechanism. Nevertheless, BiFC is an excellent complementary approach to other commonly applied methods investigating protein-protein interactions, such as coimmunoprecipitation, in vitro pull-down assays or yeast-two-hybrid experiments.

  19. Dynamics of protein-protein encounter: a Langevin equation approach with reaction patches.

    Science.gov (United States)

    Schluttig, Jakob; Alamanova, Denitsa; Helms, Volkhard; Schwarz, Ulrich S

    2008-10-21

    We study the formation of protein-protein encounter complexes with a Langevin equation approach that considers direct, steric, and thermal forces. As three model systems with distinctly different properties we consider the pairs barnase:barstar, cytochrome c-cytochrome c peroxidase, and p53:MDM2. In each case, proteins are modeled either as spherical particles, as dipolar spheres, or as collection of several small beads with one dipole. Spherical reaction patches are placed on the model proteins according to the known experimental structures of the protein complexes. In the computer simulations, concentration is varied by changing box size. Encounter is defined as overlap of the reaction patches and the corresponding first passage times are recorded together with the number of unsuccessful contacts before encounter. We find that encounter frequency scales linearly with protein concentration, thus proving that our microscopic model results in a well-defined macroscopic encounter rate. The number of unsuccessful contacts before encounter decreases with increasing encounter rate and ranges from 20 to 9000. For all three models, encounter rates are obtained within one order of magnitude of the experimentally measured association rates. Electrostatic steering enhances association up to 50-fold. If diffusional encounter is dominant (p53:MDM2) or similarly important as electrostatic steering (barnase:barstar), then encounter rate decreases with decreasing patch radius. More detailed modeling of protein shapes decreases encounter rates by 5%-95%. Our study shows how generic principles of protein-protein association are modulated by molecular features of the systems under consideration. Moreover it allows us to assess different coarse-graining strategies for the future modeling of the dynamics of large protein complexes.

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

    Science.gov (United States)

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

    2011-06-01

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

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

    Science.gov (United States)

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

    2004-11-01

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

  2. 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

  3. 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.

  4. 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.

  5. 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

    proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives. RESULTS: Here we describe an annotated reconstruction of the protein-protein interactions around four key nutrient......-sensing and metabolic regulatory signal transduction pathways (STP) operating in Saccharomyces cerevisiae. The reconstructed STP network includes a full protein-protein interaction network including the key nodes Snf1, Tor1, Hog1 and Pka1. The network includes a total of 623 structural open reading frames (ORFs......) and for all the interactions between them (edges). The annotated information is readily available utilizing the functionalities of network modelling tools such as Cytoscape and CellDesigner. CONCLUSIONS: The reported fully annotated interaction model serves as a platform for integrated systems biology studies...

  6. Evolution of a derived protein-protein interaction between HoxA11 and Foxo1a in mammals caused by changes in intramolecular regulation.

    Science.gov (United States)

    Brayer, Kathryn J; Lynch, Vincent J; Wagner, Günter P

    2011-08-09

    Current models of developmental evolution suggest changes in gene regulation underlie the evolution of morphology. Despite the fact that protein complexes regulate gene expression, the evolution of regulatory protein complexes is rarely studied. Here, we investigate the evolution of a protein-protein interaction (PPI) between Homeobox A11 (HoxA11) and Forkhead box 01A (Foxo1a). Using extant and "resurrected" ancestral proteins, we show that the physical interaction between HoxA11 and Foxo1a originated in the mammalian stem lineage. Functional divergence tests and coimmunoprecipitation with heterologous protein pairs indicate that the evolution of interaction was attributable to changes in HoxA11, and deletion studies demonstrate that the interaction interface is located in the homeodomain region of HoxA11. However, there are no changes in amino acid sequence in the homeodomain region during this time period, indicating that the origin of the derived PPI was attributable to changes outside the binding interface. We infer that the amino acid substitutions in HoxA11 altered Foxo1a's access to the conserved binding interface at the HoxA11 homeodomain. We also found an expansion in the number of paired Hox/Fox binding sites in the genomes of mammalian lineage species suggesting the complex has a biological function. Our data indicate that the physical interaction between HoxA11 and Foxo1a evolved through noninterface changes that facilitate the PPI, which prevents inappropriate interactions, rather than through the evolution of a novel binding interface. We speculate that evolutionary changes of intramolecular regulation have limited pleiotropic effects compared with changes to interaction domains themselves.

  7. Lupin Peptides Modulate the Protein-Protein Interaction of PCSK9 with the Low Density Lipoprotein Receptor in HepG2 Cells

    Science.gov (United States)

    Lammi, Carmen; Zanoni, Chiara; Aiello, Gilda; Arnoldi, Anna; Grazioso, Giovanni

    2016-07-01

    Proprotein convertase subtilisin/kexin type 9 (PCSK9) has been recently identified as a new useful target for hypercholesterolemia treatment. This work demonstrates that natural peptides, deriving from the hydrolysis of lupin protein and absorbable at intestinal level, are able to inhibit the protein-protein interaction between PCSK9 and the low density lipoprotein receptor (LDLR). In order to sort out the best potential inhibitors among these peptides, a refined in silico model of the PCSK9/LDLR interaction was developed. Docking, molecular dynamics (MD) simulations and peptide binding energy estimations, by MM-GBSA approach, permitted to select the two best candidates among tested peptides that were synthesized and evaluated for their inhibitory activity. The most active was P5 that induced a concentration dependent inhibition of the PCSK9-LDLR binding, with an IC50 value equal to 1.6 ± 0.33 μM. Tested at a 10 μM concentration, this peptide increased by 66 ± 21.4% the ability of HepG2 cells to take up LDL from the extracellular environment.

  8. The development of protein microarrays and their applications in DNA-protein and protein-protein interaction analyses of Arabidopsis transcription factors.

    Science.gov (United States)

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

    2008-01-01

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

  9. A systematic molecular dynamics approach to the study of peptide Keap1-Nrf2 protein-protein interaction inhibitors and its application to p62 peptides.

    Science.gov (United States)

    Lu, Meng-Chen; Yuan, Zhen-Wei; Jiang, Yong-Lin; Chen, Zhi-Yun; You, Qi-Dong; Jiang, Zheng-Yu

    2016-04-01

    Protein-protein interactions (PPIs) as drug targets have been gaining growing interest, though developing drug-like small molecule PPI inhibitors remains challenging. Peptide PPI inhibitors, which can provide informative data on the PPI interface, are good starting points to develop small molecule modulators. Computational methods combining molecular dynamics simulations and binding energy calculations could give both the structural and the energetic perspective of peptide PPI inhibitors. Herein, we set up a computational workflow to investigate Keap1-Nrf2 peptide PPI inhibitors and predict the activity of novel sequences. Furthermore, we applied this method to investigate p62 peptides as PPI inhibitors of Keap1-Nrf2 and explored the activity change induced by the phosphorylation of serine. Our results showed that because of the unfavorable solvation effects, the binding affinity of the phosphorylated p62 peptide is lower than the Nrf2 ETGE peptide. Our research results not only provide a useful method to investigate the Keap1-Nrf2 peptide inhibitors, but also give a good example to show how to incorporate computational methods into the study of peptide PPI inhibitors. Besides, applying this method to p62 peptides provides a detailed explanation for the expression of cytoprotective Nrf2 targets induced by p62 phosphorylation, which may benefit the further study of the crosstalk between the Keap1-Nrf2 pathway and p62-mediated selective autophagy.

  10. The Binary Garrote

    CERN Document Server

    Kappen, H J

    2011-01-01

    In this paper, I present a new model and solution method for sparse regression. The model introduces binary selector variables $s_i$ for the features $i$ in a way that is similar to Breiman's Garrote model. I refer to this method as the binary Garrote (BG). The posterior probability for $s_i$ is computed in the variational approximation. The BG is compared numerically with the Lasso method and with ridge regression. Numerical results on synthetic data show that the BG yields more accurate predictions and more accurately reconstructs the true model than the other methods. The naive implementation of the BG requires the inversion of a modified covariance matrix which scales cubic in the number of features. We indicate how for sparse problem the solution can be computed linear in the number of features.

  11. Binary Tetrahedral Flavor Symmetry

    CERN Document Server

    Eby, David A

    2013-01-01

    A study of the T' Model and its variants utilizing Binary Tetrahedral Flavor Symmetry. We begin with a description of the historical context and motivations for this theory, together with some conceptual background for added clarity, and an account of our theory's inception in previous works. Our model endeavors to bridge two categories of particles, leptons and quarks, a unification made possible by the inclusion of additional Higgs particles, shared between the two fermion sectors and creating a single coherent system. This is achieved through the use of the Binary Tetrahedral symmetry group and an investigation of the Tribimaximal symmetry evidenced by neutrinos. Our work details perturbations and extensions of this T' Model as we apply our framework to neutrino mixing, quark mixing, unification, and dark matter. Where possible, we evaluate model predictions against experimental results and find excellent matching with the atmospheric and reactor neutrino mixing angles, an accurate prediction of the Cabibb...

  12. Binary Love Relations

    CERN Document Server

    Yagi, Kent

    2015-01-01

    When in a tight binary, the mutual tidal deformations of neutron stars imprint onto observables, encoding information about their internal structure at supranuclear densities and gravity in the extreme-gravity regime. Gravitational wave observations of their late binary inspiral may serve as a tool to extract the individual tidal deformabilities, but this is made difficult by degeneracies between them in the gravitational wave model. We here resolve this problem by discovering approximately universal relations between dimensionless combinations of the individual tidal deformabilities. We show that these relations break degeneracies in the gravitational wave model, allowing for the accurate extraction of both deformabilities. Such measurements can be used to better differentiate between equation-of-state models, and improve tests of General Relativity and cosmology.

  13. Binary Love relations

    Science.gov (United States)

    Yagi, Kent; Yunes, Nicolás

    2016-07-01

    When in a tight binary, the mutual tidal deformations of neutron stars get imprinted onto observables, encoding information about their internal structure at supranuclear densities and gravity in the extreme-gravity regime. Gravitational wave (GW) observations of their late binary inspiral may serve as a tool to extract the individual tidal deformabilities, but this is made difficult by degeneracies between them in the GW model. We here resolve this problem by discovering approximately equation-of-state (EoS)-insensitive relations between dimensionless combinations of the individual tidal deformabilities. We show that these relations break degeneracies in the GW model, allowing for the accurate extraction of both deformabilities. Such measurements can be used to better differentiate between EoS models, and improve tests of general relativity and cosmology.

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

    Institute of Scientific and Technical Information of China (English)

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

    2013-01-01

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

  15. Protein-protein interaction domains of Bacillus subtilis DivIVA

    NARCIS (Netherlands)

    S. van Baarle; I.N. Celik; K.G. Kaval; M. Bramkamp; L.W. Hamoen; S. Halbedel

    2012-01-01

    DivIVA proteins are curvature sensitive membrane binding proteins that recruit other proteins to the poles and the division septum. They consist of a conserved N-terminal lipid binding domain fused to a less conserved C-terminal domain. DivIVA homologues interact with different proteins involved in

  16. Protein-protein interaction domains of Bacillus subtilis DivIVA

    NARCIS (Netherlands)

    van Baarle, S.; Celik, I.N.; Kaval, K.G.; Bramkamp, M.; Hamoen, L.W.; Halbedel, S.

    2013-01-01

    DivIVA proteins are curvature sensitive membrane binding proteins that recruit other proteins to the poles and the division septum. They consist of a conserved N-terminal lipid binding domain fused to a less conserved C-terminal domain. DivIVA homologues interact with different proteins involved in

  17. Binary-Signal Recovery

    Science.gov (United States)

    Griebeler, Elmer L.

    2011-01-01

    Binary communication through long cables, opto-isolators, isolating transformers, or repeaters can become distorted in characteristic ways. The usual solution is to slow the communication rate, change to a different method, or improve the communication media. It would help if the characteristic distortions could be accommodated at the receiving end to ease the communication problem. The distortions come from loss of the high-frequency content, which adds slopes to the transitions from ones to zeroes and zeroes to ones. This weakens the definition of the ones and zeroes in the time domain. The other major distortion is the reduction of low frequency, which causes the voltage that defines the ones or zeroes to drift out of recognizable range. This development describes a method for recovering a binary data stream from a signal that has been subjected to a loss of both higher-frequency content and low-frequency content that is essential to define the difference between ones and zeroes. The method makes use of the frequency structure of the waveform created by the data stream, and then enhances the characteristics related to the data to reconstruct the binary switching pattern. A major issue is simplicity. The approach taken here is to take the first derivative of the signal and then feed it to a hysteresis switch. This is equivalent in practice to using a non-resonant band pass filter feeding a Schmitt trigger. Obviously, the derivative signal needs to be offset to halfway between the thresholds of the hysteresis switch, and amplified so that the derivatives reliably exceed the thresholds. A transition from a zero to a one is the most substantial, fastest plus movement of voltage, and therefore will create the largest plus first derivative pulse. Since the quiet state of the derivative is sitting between the hysteresis thresholds, the plus pulse exceeds the plus threshold, switching the hysteresis switch plus, which re-establishes the data zero to one transition

  18. Massive Black Hole Binary Evolution

    Directory of Open Access Journals (Sweden)

    Merritt David

    2005-11-01

    Full Text Available Coalescence of binary supermassive black holes (SBHs would constitute the strongest sources of gravitational waves to be observed by LISA. While the formation of binary SBHs during galaxy mergers is almost inevitable, coalescence requires that the separation between binary components first drop by a few orders of magnitude, due presumably to interaction of the binary with stars and gas in a galactic nucleus. This article reviews the observational evidence for binary SBHs and discusses how they would evolve. No completely convincing case of a bound, binary SBH has yet been found, although a handful of systems (e.g. interacting galaxies; remnants of galaxy mergers are now believed to contain two SBHs at projected separations of <~ 1kpc. N-body studies of binary evolution in gas-free galaxies have reached large enough particle numbers to reproduce the slow, “diffusive” refilling of the binary’s loss cone that is believed to characterize binary evolution in real galactic nuclei. While some of the results of these simulations - e.g. the binary hardening rate and eccentricity evolution - are strongly N-dependent, others - e.g. the “damage” inflicted by the binary on the nucleus - are not. Luminous early-type galaxies often exhibit depleted cores with masses of ~ 1-2 times the mass of their nuclear SBHs, consistent with the predictions of the binary model. Studies of the interaction of massive binaries with gas are still in their infancy, although much progress is expected in the near future. Binary coalescence has a large influence on the spins of SBHs, even for mass ratios as extreme as 10:1, and evidence of spin-flips may have been observed.

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

    Science.gov (United States)

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

    2013-03-01

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

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

    NARCIS (Netherlands)

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

    2006-01-01

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

  1. 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

    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...

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

    Science.gov (United States)

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

    2016-05-23

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

  3. Visual binary stars: data to investigate formation of binaries

    Science.gov (United States)

    Kovaleva,, D.; Malkov,, O.; Yungelson, L.; Chulkov, D.

    Statistics of orbital parameters of binary stars as well as statistics of their physical characteristics bear traces of star formation history. However, statistical investigations of binaries are complicated by incomplete or missing observational data and by a number of observational selection effects. Visual binaries are the most common type of observed binary stars, with the number of pairs exceeding 130 000. The most complete list of presently known visual binary stars was compiled by cross-matching objects and combining data of the three largest catalogues of visual binaries. This list was supplemented by the data on parallaxes, multicolor photometry, and spectral characteristics taken from other catalogues. This allowed us to compensate partly for the lack of observational data for these objects. The combined data allowed us to check the validity of observational values and to investigate statistics of the orbital and physical parameters of visual binaries. Corrections for incompleteness of observational data are discussed. The datasets obtained, together with modern distributions of binary parameters, will be used to reconstruct the initial distributions and parameters of the function of star formation for binary systems.

  4. 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.

  5. Analysis of protein-protein interactions involved in the activation of the Shc/Grb-2 pathway by the ErbB-2 kinase.

    Science.gov (United States)

    Ricci, A; Lanfrancone, L; Chiari, R; Belardo, G; Pertica, C; Natali, P G; Pelicci, P G; Segatto, O

    1995-10-19

    In murine fibroblasts activation of the Shc/Grb-2 pathway by the ErbB-2 kinase involves tyrosine phosphorylation of Shc products and the formation of Shc/ErbB-2, Shc/Grb-2 and Grb-2/ErbB-2 complexes. Tyr 1139 of ErbB-2 bound to the Grb-2 SH2 domain in vitro as well as in intact cells. Tyr 1221 and 1248 are binding sites of gp185ErbB-2 for Shc SH2 domain in vitro whereas Tyr 1196 and 1248 are major binding sites of ErbB-2 for Shc PTB domain. Inhibition of Shc/ErbB-2 complex formation in intact cells was obtained by simultaneous mutational inactivation of Shc SH2 and Shc PTB binding sites of gp185ErbB-2. Shc/ErbB-2 complexes are formed upon activation of the ErbB-2 kinase and tyrosine phosphorylation of Shc proteins; they are located in both cytosol and cellular membranes. ErbB-2 activation induces also translocation of Grb-2 from cytosol to membranes. This network of protein-protein interactions may reflect the ability of the Shc/Grb-2 pathway to act as a molecular switch controlling different cellular functions regulated by RTK activation. In fact the Ras GDP exchanger mSOS was recruited in Grb-2/ErbB-2 complexes; furthermore besides mSOS, other polypeptides present in either cytosolic or membrane preparations were able to complex in vitro with Grb-2 SH3 domains.

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

    Science.gov (United States)

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

    2014-08-01

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

  7. Statistically Inferring Protein-Protein Assocations with Affinity isolation LC-MS/MS assays

    Energy Technology Data Exchange (ETDEWEB)

    Sharp, Julia L. [Montana State University; Anderson, Kevin K. [Pacific Northwest National Laboratory (PNNL); Hurst, Gregory {Greg} B [ORNL; Daly, Don S. [Pacific Northwest National Laboratory (PNNL); Pelletier, Dale A [ORNL; Cannon, Bill [Pacific Northwest National Laboratory (PNNL); Auberry, Deanna L [ORNL; Schmoyer, Denise D [ORNL; McDonald, W Hayes [ORNL; White, Amanda M. [Pacific Northwest National Laboratory (PNNL); Hooker, Brian [Pacific Northwest National Laboratory (PNNL); Victry, Kristin D [Pacific Northwest National Laboratory (PNNL); Buchanan, Michelle V [ORNL; Kerry, Vladimir [Pacific Northwest National Laboratory (PNNL); Wiley, Steven [Pacific Northwest National Laboratory (PNNL); Doktycz, Mitchel John [ORNL

    2007-01-01

    Affinity isolation of protein complexes followed by protein identification by LC-MS/MS is an increasingly popular approach for mapping protein interactions. However, systematic and random assay errors from multiple sources must be considered to confidently infer authentic protein-protein interactions. To address this issue, we developed a general, robust statistical method for inferring authentic interactions from protein prey-by-bait frequency tables using a binomial-based likelihood ratio test (LRT) coupled with Bayes' Odds estimation. We then applied our LRT-Bayes' algorithm experimentally using data from protein complexes isolated from Rhodopseudomonas palustris. Our algorithm, in conjunction with the experimental protocol, inferred with high confidence authentic interacting proteins from abundant, stable complexes, but few or no authentic interactions for lower-abundance complexes. We conclude that the experimental protocol including the LRT-Bayes' algorithm produces results with high confidence but moderate sensitivity. We also found that Monte Carlo simulation is a feasible tool for checking modeling assumptions, estimating parameters, and evaluating the significance of results in protein association studies.

  8. Statistically Inferring Protein-Protein Associations with Affinity Isolation LC-MS/MS Assays

    Energy Technology Data Exchange (ETDEWEB)

    Sharp, Julia L. [Montana State University; Anderson, Kevin K. [Pacific Northwest National Laboratory (PNNL); Daly, Don S. [Pacific Northwest National Laboratory (PNNL); Pelletier, Dale A [ORNL; Hurst, Gregory {Greg} B [ORNL; Cannon, Bill [Pacific Northwest National Laboratory (PNNL); Auberry, Deanna L [ORNL; Schmoyer, Denise D [ORNL; McDonald, W Hayes [ORNL; White, Amanda M. [Pacific Northwest National Laboratory (PNNL); Hooker, Brian [Pacific Northwest National Laboratory (PNNL); Victry, Kristin D [Pacific Northwest National Laboratory (PNNL); Buchanan, Michelle V [ORNL; Kerry, Vladimir [Pacific Northwest National Laboratory (PNNL); Wiley, Steven [Pacific Northwest National Laboratory (PNNL)

    2007-01-01

    Affinity isolation of protein complexes followed by protein identification by LC-MS/MS is an increasingly popular approach for mapping protein interactions. However, systematic and random assay errors from multiple sources must be considered to confidently infer authentic protein-protein interactions. To address this issue, we developed a general, robust statistical method for inferring authentic interactions from protein prey-by-bait frequency tables using a binomial-based likelihood ratio test (LRT) coupled with Bayes Odds estimation. We then applied our LRT-Bayes algorithm experimentally using data from protein complexes isolated from Rhodopseudomonas palustris. Our algorithm, in conjunction with the experimental protocol, inferred with high confidence authentic interacting proteins from abundant, stable complexes, but few or no authentic interactions for lower-abundance complexes. We conclude that the experimental protocol including the LRT-Bayes algorithm produces results with high confidence but moderate sensitivity. We also found that Monte Carlo simulation is a feasible tool for checking modeling assumptions, estimating parameters, and evaluating the significance of results in protein association studies.

  9. Statistically Inferring Protein-Protein Asociations with Affinity Isolation LC-MS/MS Assays

    Energy Technology Data Exchange (ETDEWEB)

    Sharp, Julia L.; Anderson, Kevin K.; Hurst, G. B.; Daly, Don S.; Pelletier, Dale A.; Cannon, William R.; Auberry, Deanna L.; Schmoyer, Denise D.; McDonald, W. Hayes; White, Amanda M.; Hooker, Brian S.; Victry, Kristin D.; Buchanan, M. V.; Kery, Vladimir; Wiley, H. S.

    2007-09-30

    Affinity isolation of protein complexes followed by protein identification by LC-MS/MS is an increasingly popular approach for mapping protein interactions. However, systematic and random assay errors from multiple sources must be considered to confidently infer authentic protein-protein interactions. To address this issue, we developed a general, robust statistical method for inferring authentic interactions from protein prey-by-bait frequency tables using a binomial-based likelihood ratio test (LRT) coupled with Bayes’ Odds estimation. We then applied our LRT-Bayes’ algorithm experimentally using data from protein complexes isolated from Rhodopseudomonas palustris. Our algorithm, in conjunction with the experimental protocol, inferred with high confidence authentic interacting proteins from abundant, stable complexes, but few or no authentic interactions for lower-abundance complexes. The algorithm can discriminate against a background of prey proteins that are detected in association with a large number of baits as an artifact of the measurement. We conclude that the experimental protocol including the LRT-Bayes’ algorithm produces results with high confidence but moderate sensitivity. We also found that Monte Carlo simulation is a feasible tool for checking modeling assumptions, estimating parameters, and evaluating the significance of results in protein association studies.

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Science.gov (United States)

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

    2015-10-22

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

  13. 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.

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

    Science.gov (United States)

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

    2008-07-01

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

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

    Science.gov (United States)

    Chen, T Scott; Keating, Amy E

    2012-07-01

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

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

    Science.gov (United States)

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

    2010-03-01

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

  17. The polarity sub-network in the yeast network of protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Luca Paris

    2011-12-01

    Full Text Available Rare, but highly connected, hub proteins subdivide hierarchically global networks of interacting proteins into modular clusters. Most biological research, however, focuses on functionally defined sub-networks. Thus, it is important to know whether the sub-networks retain the same topology of the global networks, from which they derive. To address this issue, we have analyzed the protein-protein interaction sub-network that participates in the polarized growth of the budding yeast Saccharomyces cerevisiae and that is derived from the global network of this model organism. We have observed that, in contrast to global networks, the distribution of connectivity k (i.e., the number of interactions per protein does not follow a power law, but decays exponentially, which reflects the local absence of hub proteins. Nonetheless, far from being randomly organized, the polarity sub-network can be subdivided into functional modules. In addition, most non-hub connector proteins, besides ensuring communications among modules, are linked mutually and contribute to the formation of the polarisome, a structure that coordinates actin assembly with polarized growth. These findings imply that identifying critical proteins within sub-networks (e.g., for the aim of targeted therapy requires searching not only for hubs but also for key non-hub connectors, which might remain otherwise unnoticed due to their relatively low connectivity.

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

    Directory of Open Access Journals (Sweden)

    Kyunghyun Park

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

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

    Science.gov (United States)

    Stone, Tracy A; Deber, Charles M

    2017-04-01

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

  20. High throughput protein-protein interaction data: clues for the architecture of protein complexes

    Directory of Open Access Journals (Sweden)

    Pang Chi

    2008-11-01

    Full Text Available Abstract Background High-throughput techniques are becoming widely used to study protein-protein interactions and protein complexes on a proteome-wide scale. Here we have explored the potential of these techniques to accurately determine the constituent proteins of complexes and their architecture within the complex. Results Two-dimensional representations of the 19S and 20S proteasome, mediator, and SAGA complexes were generated and overlaid with high quality pairwise interaction data, core-module-attachment classifications from affinity purifications of complexes and predicted domain-domain interactions. Pairwise interaction data could accurately determine the members of each complex, but was unexpectedly poor at deciphering the topology of proteins in complexes. Core and module data from affinity purification studies were less useful for accurately defining the member proteins of these complexes. However, these data gave strong information on the spatial proximity of many proteins. Predicted domain-domain interactions provided some insight into the topology of proteins within complexes, but was affected by a lack of available structural data for the co-activator complexes and the presence of shared domains in paralogous proteins. Conclusion The constituent proteins of complexes are likely to be determined with accuracy by combining data from high-throughput techniques. The topology of some proteins in the complexes will be able to be clearly inferred. We finally suggest strategies that can be employed to use high throughput interaction data to define the membership and understand the architecture of proteins in novel complexes.

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

    Science.gov (United States)

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

    2014-10-31

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

  2. 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.

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    Shun Koyabu

    2015-01-01

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

  5. A least square method based model for identifying protein complexes in protein-protein interaction network.

    Science.gov (United States)

    Dai, Qiguo; Guo, Maozu; Guo, Yingjie; Liu, Xiaoyan; Liu, Yang; Teng, Zhixia

    2014-01-01

    Protein complex formed by a group of physical interacting proteins plays a crucial role in cell activities. Great effort has been made to computationally identify protein complexes from protein-protein interaction (PPI) network. However, the accuracy of the prediction is still far from being satisfactory, because the topological structures of protein complexes in the PPI network are too complicated. This paper proposes a novel optimization framework to detect complexes from PPI network, named PLSMC. The method is on the basis of the fact that if two proteins are in a common complex, they are likely to be interacting. PLSMC employs this relation to determine complexes by a penalized least squares method. PLSMC is applied to several public yeast PPI networks, and compared with several state-of-the-art methods. The results indicate that PLSMC outperforms other methods. In particular, complexes predicted by PLSMC can match known complexes with a higher accuracy than other methods. Furthermore, the predicted complexes have high functional homogeneity.

  6. 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.

  7. 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.

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

    Science.gov (United States)

    Yang, Lei; Tang, Xianglong

    2014-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  10. 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.

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

    Science.gov (United States)

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

    2015-01-01

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

  12. Tree kernel-based protein-protein interaction extraction from biomedical literature.

    Science.gov (United States)

    Qian, Longhua; Zhou, Guodong

    2012-06-01

    There is a surge of research interest in protein-protein interaction (PPI) extraction from biomedical literature. While most of the state-of-the-art PPI extraction systems focus on dependency-based structured information, the rich structured information inherent in constituent parse trees has not been extensively explored for PPI extraction. In this paper, we propose a novel approach to tree kernel-based PPI extraction, where the tree representation generated from a constituent syntactic parser is further refined using the shortest dependency path between two proteins derived from a dependency parser. Specifically, all the constituent tree nodes associated with the nodes on the shortest dependency path are kept intact, while other nodes are removed safely to make the constituent tree concise and precise for PPI extraction. Compared with previously used constituent tree setups, our dependency-motivated constituent tree setup achieves the best results across five commonly used PPI corpora. Moreover, our tree kernel-based method outperforms other single kernel-based ones and performs comparably with some multiple kernel ones on the most commonly tested AIMed corpus.

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

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

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    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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-01-01

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

  16. Rotational mixing in close binaries

    CERN Document Server

    de Mink, S E; Langer, N; Yoon, S -Ch; Brott, I; Glebbeek, E; Verkoulen, M; Pols, O R

    2008-01-01

    Rotational mixing is a very important but uncertain process in the evolution of massive stars. We propose to use close binaries to test its efficiency. Based on rotating single stellar models we predict nitrogen surface enhancements for tidally locked binaries. Furthermore we demonstrate the possibility of a new evolutionary scenario for very massive (M > 40 solar mass) close (P < 3 days) binaries: Case M, in which mixing is so efficient that the stars evolve quasi-chemically homogeneously, stay compact and avoid any Roche-lobe overflow, leading to very close (double) WR binaries.

  17. Evolution of Close Binary Systems

    Energy Technology Data Exchange (ETDEWEB)

    Yakut, K; Eggleton, P

    2005-01-24

    We collected data on the masses, radii, etc. of three classes of close binary stars: low-temperature contact binaries (LTCBs), near-contact binaries (NCBs), and detached close binaries (DCBs). They restrict themselves to systems where (1) both components are, at least arguably, near the Main Sequence, (2) the periods are less than a day, and (3) there is both spectroscopic and photometric analysis leading to reasonably reliable data. They discuss the possible evolutionary connections between these three classes, emphasizing the roles played by mass loss and angular momentum loss in rapidly-rotating cool stars.

  18. Chaos in Binary Category Computation

    CERN Document Server

    Gonçalves, Carlos Pedro

    2010-01-01

    Category computation theory deals with a web-based systemic processing that underlies the morphic webs, which constitute the basis of categorial logical calculus. It is proven that, for these structures, algorithmically incompressible binary patterns can be morphically compressed, with respect to the local connectivities, in a binary morphic program. From the local connectivites, there emerges a global morphic connection that can be characterized by a low length binary string, leading to the identification of chaotic categorial dynamics, underlying the algorithmically random pattern. The work focuses on infinite binary chains of C2, which is a category that implements an X-OR-based categorial logical calculus.

  19. Low autocorrelation binary sequences

    Science.gov (United States)

    Packebusch, Tom; Mertens, Stephan

    2016-04-01

    Binary sequences with minimal autocorrelations have applications in communication engineering, mathematics and computer science. In statistical physics they appear as groundstates of the Bernasconi model. Finding these sequences is a notoriously hard problem, that so far can be solved only by exhaustive search. We review recent algorithms and present a new algorithm that finds optimal sequences of length N in time O(N {1.73}N). We computed all optimal sequences for N≤slant 66 and all optimal skewsymmetric sequences for N≤slant 119.

  20. Microlensing modulation by binaries

    CERN Document Server

    Dubath, F; Durrer, R; Dubath, Florian; Gasparini, Maria Alice; Durrer, Ruth

    2006-01-01

    We compute the effect of the lens quadrupole on microlensing. The time dependence of the quadrupole can lead to specific modulations of the amplification signal. We study especially binary system lenses in our galaxy. The modulation is observable if the rotation period of the system is smaller than the time over which the amplification is significant and if the impact parameter of the passing light ray is sufficiently close to the Einstein radius so that the amplification is very large. Observations of this modulation can reveal important information on the quadrupole and thus on the gravitational radiation emitted by the lens.

  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.

  2. Evolution of Binaries in Dense Stellar Systems

    CERN Document Server

    Ivanova, Natalia

    2011-01-01

    In contrast to the field, the binaries in dense stellar systems are frequently not primordial, and could be either dynamically formed or significantly altered from their primordial states. Destruction and formation of binaries occur in parallel all the time. The destruction, which constantly removes soft binaries from a binary pool, works as an energy sink and could be a reason for cluster entering the binary-burning phase. The true binary fraction is greater than observed, as a result, the observable binary fraction evolves differently from the predictions. Combined measurements of binary fractions in globular clusters suggest that most of the clusters are still core-contracting. The formation, on other hand, affects most the more evolutionary advanced stars, which significantly enhances the population of X-ray sources in globular clusters. The formation of binaries with a compact objects proceeds mainly through physical collisions, binary-binary and single-binary encounters; however, it is the dynamical for...

  3. Spin Correlation in Binary Systems

    CERN Document Server

    Farbiash, N; Farbiash, Netzach; Steinitz, Raphael

    2004-01-01

    We examine the correlation of projected rotational velocities in binary systems. It is an extension of previous work (Steinitz and Pyper, 1970; Levato, 1974). An enlarged data basis and new tests enable us to conclude that there is indeed correlation between the projected rotational velocities of components of binaries. In fact we suggest that spins are already correlated.

  4. Evolutionary Memory in Binary Systems?

    CERN Document Server

    Steinitz, N F R

    2004-01-01

    Correlation between the spins (rotational velocities) in binaries has previously been established. We now continue and show that the degree of spin correlation is independent of the components' separation. Such a result might be related for example to Zhang's non-linear model for the formation of binary stars from a nebula.

  5. Relativistic Binaries in Globular Clusters

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    Matthew J. Benacquista

    2013-03-01

    Full Text Available Galactic globular clusters are old, dense star systems typically containing 10^4 – 10^6 stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution that leads to relativistic binaries, and current and possible future observational evidence for this population. Our discussion of globular cluster evolution will focus on the processes that boost the production of tight binary systems and the subsequent interaction of these binaries that can alter the properties of both bodies and can lead to exotic objects. Direct N-body integrations and Fokker–Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.

  6. PERIODIC COMPLEMENTARY BINARY SEQUENCE PAIRS

    Institute of Scientific and Technical Information of China (English)

    XuChengqian; ZhaoXiaoqun

    2002-01-01

    A new set of binary sequences-Periodic Complementary Binary Sequence Pair (PCSP)is proposed .A new class of block design-Difference Family Pair (DFP)is also proposed .The relationship between PCSP and DFP,the properties and exising conditions of PCSP and the recursive constructions for PCSP are given.

  7. PERIODIC COMPLEMENTARY BINARY SEQUENCE PAIRS

    Institute of Scientific and Technical Information of China (English)

    Xu Chengqian; Zhao Xiaoqun

    2002-01-01

    A new set of binary sequences-Periodic Complementary Binary Sequence Pair (PCSP) is proposed. A new class of block design-Difference Family Pair (DFP) is also proposed.The relationship between PCSP and DFP, the properties and existing conditions of PCSP and the recursive constructions for PCSP are given.

  8. Relativistic Binaries in Globular Clusters

    Directory of Open Access Journals (Sweden)

    Benacquista Matthew J.

    2006-02-01

    Full Text Available The galactic population of globular clusters are old, dense star systems, with a typical cluster containing 10^4 - 10^7 stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss the theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution which lead to relativistic binaries, and current and possible future observational evidence for this population. Globular cluster evolution will focus on the properties that boost the production of hard binary systems and on the tidal interactions of the galaxy with the cluster, which tend to alter the structure of the globular cluster with time. The interaction of the components of hard binary systems alters the evolution of both bodies and can lead to exotic objects. Direct N-body integrations and Fokker-Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.

  9. Relativistic Binaries in Globular Clusters

    Directory of Open Access Journals (Sweden)

    Benacquista Matthew

    2002-01-01

    Full Text Available The galactic population of globular clusters are old, dense star systems, with a typical cluster containing $10^4 - 10^6$ stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss the theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution which lead to relativistic binaries, and current and possible future observational evidence for this population. Globular cluster evolution will focus on the properties that boost the production of hard binary systems and on the tidal interactions of the galaxy with the cluster, which tend to alter the structure of the globular cluster with time. The interaction of the components of hard binary systems alters the evolution of both bodies and can lead to exotic objects. Direct $N$-body integrations and Fokker--Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.

  10. A pipeline for determining protein-protein interactions and proximities in the cellular milieu.

    Science.gov (United States)

    Subbotin, Roman I; Chait, Brian T

    2014-11-01

    It remains extraordinarily challenging to elucidate endogenous protein-protein interactions and proximities within the cellular milieu. The dynamic nature and the large range of affinities of these interactions augment the difficulty of this undertaking. Among the most useful tools for extracting such information are those based on affinity capture of target bait proteins in combination with mass spectrometric readout of the co-isolated species. Although highly enabling, the utility of affinity-based methods is generally limited by difficulties in distinguishing specific from nonspecific interactors, preserving and isolating all unique interactions including those that are weak, transient, or rapidly exchanging, and differentiating proximal interactions from those that are more distal. Here, we have devised and optimized a set of methods to address these challenges. The resulting pipeline involves flash-freezing cells in liquid nitrogen to preserve the cellular environment at the moment of freezing; cryomilling to fracture the frozen cells into intact micron chunks to allow for rapid access of a chemical reagent and to stabilize the intact endogenous subcellular assemblies and interactors upon thawing; and utilizing the high reactivity of glutaraldehyde to achieve sufficiently rapid stabilization at low temperatures to preserve native cellular interactions. In the course of this work, we determined that relatively low molar ratios of glutaraldehyde to reactive amines within the cellular milieu were sufficient to preserve even labile and transient interactions. This mild treatment enables efficient and rapid affinity capture of the protein assemblies of interest under nondenaturing conditions, followed by bottom-up MS to identify and quantify the protein constituents. For convenience, we have termed this approach Stabilized Affinity Capture Mass Spectrometry. Here, we demonstrate that Stabilized Affinity Capture Mass Spectrometry allows us to stabilize and elucidate

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

    Directory of Open Access Journals (Sweden)

    Chen Bor-Sen

    2010-03-01

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

  12. 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.

  13. 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

  14. 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.

  15. New GATEWAY vectors for High Throughput Analyses of Protein-Protein Interactions by Bimolecular Fluorescence Complementation

    Institute of Scientific and Technical Information of China (English)

    Christian Gehl; Rainer Waadt; J(o)rg Kudla; Ralf-R. Mendel; Robert Hansch

    2009-01-01

    Complex protein interaction networks constitute plant metabolic and signaling systems. Bimolecular fluores-cence complementation (BiFC) is a suitable technique to investigate the formation of protein complexes and the locali-zation of protein-protein interactions in planta. However, the generation of large plasmid collections to facilitate the exploration of complex interaction networks is often limited by the need for conventional cloning techniques. Here, we report the implementation of a GATEWAY vector system enabling large-scale combination and investigation of can-didate proteins in BiFC studies. We describe a set of 12 GATEWAY-compatible BiFC vectors that efficiently permit the com-bination of candidate protein pairs with every possible N-or C-terminal sub-fragment of S(CFP)3A or Venus, respectively, and enable the performance of multicolor BiFC (mcBiFC). We used proteins of the plant molybdenum metabolism, in that more than 20 potentially interacting proteins are assumed to form the cellular molybdenum network, as a case study to establish the functionality of the new vectors. Using these vectors, we report the formation of the molybdopterin synthase complex by interaction of Arabidopsis proteins Cnx6 and Cnx7 detected by BiFC as well as the simultaneous formation of Cn×6/Cn×6 and Cn×6/Cn×7 complexes revealed by mcBiFC. Consequently, these GATEWAY-based BiFC vector systems should significantly facilitate the large-scale investigation of complex regulatory networks in plant cells.

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

    Directory of Open Access Journals (Sweden)

    Zheng-Wei Li

    2016-08-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  18. Adding protein context to the human protein-protein interaction network to reveal meaningful interactions.

    Directory of Open Access Journals (Sweden)

    Martin H Schaefer

    Full Text Available Interactions of proteins regulate signaling, catalysis, gene expression and many other cellular functions. Therefore, characterizing the entire human interactome is a key effort in current proteomics research. This challenge is complicated by the dynamic nature of protein-protein interactions (PPIs, which are conditional on the cellular context: both interacting proteins must be expressed in the same cell and localized in the same organelle to meet. Additionally, interactions underlie a delicate control of signaling pathways, e.g. by post-translational modifications of the protein partners - hence, many diseases are caused by the perturbation of these mechanisms. Despite the high degree of cell-state specificity of PPIs, many interactions are measured under artificial conditions (e.g. yeast cells are transfected with human genes in yeast two-hybrid assays or even if detected in a physiological context, this information is missing from the common PPI databases. To overcome these problems, we developed a method that assigns context information to PPIs inferred from various attributes of the interacting proteins: gene expression, functional and disease annotations, and inferred pathways. We demonstrate that context consistency correlates with the experimental reliability of PPIs, which allows us to generate high-confidence tissue- and function-specific subnetworks. We illustrate how these context-filtered networks are enriched in bona fide pathways and disease proteins to prove the ability of context-filters to highlight meaningful interactions with respect to various biological questions. We use this approach to study the lung-specific pathways used by the influenza virus, pointing to IRAK1, BHLHE40 and TOLLIP as potential regulators of influenza virus pathogenicity, and to study the signalling pathways that play a role in Alzheimer's disease, identifying a pathway involving the altered phosphorylation of the Tau protein. Finally, we provide the

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

    Science.gov (United States)

    Tikk, Domonkos; Thomas, Philippe; Palaga, Peter; Hakenberg, Jörg; Leser, Ulf

    2010-07-01

    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 shows that three

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

    Directory of Open Access Journals (Sweden)

    Chuanhua Xing

    2011-07-01

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

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

    Science.gov (United States)

    Xing, Chuanhua; Dunson, David B

    2011-07-01

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

  2. Computational prediction of protein-protein interactions in Leishmania predicted proteomes.

    Directory of Open Access Journals (Sweden)

    Antonio M Rezende

    Full Text Available The Trypanosomatids parasites Leishmania braziliensis, Leishmania major and Leishmania infantum are important human pathogens. Despite of years of study and genome availability, effective vaccine has not been developed yet, and the chemotherapy is highly toxic. Therefore, it is clear just interdisciplinary integrated studies will have success in trying to search new targets for developing of vaccines and drugs. An essential part of this rationale is related to protein-protein interaction network (PPI study which can provide a better understanding of complex protein interactions in biological system. Thus, we modeled PPIs for Trypanosomatids through computational methods using sequence comparison against public database of protein or domain interaction for interaction prediction (Interolog Mapping and developed a dedicated combined system score to address the predictions robustness. The confidence evaluation of network prediction approach was addressed using gold standard positive and negative datasets and the AUC value obtained was 0.94. As result, 39,420, 43,531 and 45,235 interactions were predicted for L. braziliensis, L. major and L. infantum respectively. For each predicted network the top 20 proteins were ranked by MCC topological index. In addition, information related with immunological potential, degree of protein sequence conservation among orthologs and degree of identity compared to proteins of potential parasite hosts was integrated. This information integration provides a better understanding and usefulness of the predicted networks that can be valuable to select new potential biological targets for drug and vaccine development. Network modularity which is a key when one is interested in destabilizing the PPIs for drug or vaccine purposes along with multiple alignments of the predicted PPIs were performed revealing patterns associated with protein turnover. In addition, around 50% of hypothetical protein present in the networks

  3. 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

  4. Protein-protein interface detection using the energy centrality relationship (ECR characteristic of proteins.

    Directory of Open Access Journals (Sweden)

    Sanjana Sudarshan

    Full Text Available Specific protein interactions are responsible for most biological functions. Distinguishing Functionally Linked Interfaces of Proteins (FLIPs, from Functionally uncorrelated Contacts (FunCs, is therefore important to characterizing these interactions. To achieve this goal, we have created a database of protein structures called FLIPdb, containing proteins belonging to various functional sub-categories. Here, we use geometric features coupled with Kortemme and Baker's computational alanine scanning method to calculate the energetic sensitivity of each amino acid at the interface to substitution, identify hotspots, and identify other factors that may contribute towards an interface being FLIP or FunC. Using Principal Component Analysis and K-means clustering on a training set of 160 interfaces, we could distinguish FLIPs from FunCs with an accuracy of 76%. When these methods were applied to two test sets of 18 and 170 interfaces, we achieved similar accuracies of 78% and 80%. We have identified that FLIP interfaces have a stronger central organizing tendency than FunCs, due, we suggest, to greater specificity. We also observe that certain functional sub-categories, such as enzymes, antibody-heavy-light, antibody-antigen, and enzyme-inhibitors form distinct sub-clusters. The antibody-antigen and enzyme-inhibitors interfaces have patterns of physical characteristics similar to those of FunCs, which is in agreement with the fact that the selection pressures of these interfaces is differently evolutionarily driven. As such, our ECR model also successfully describes the impact of evolution and natural selection on protein-protein interfaces. Finally, we indicate how our ECR method may be of use in reducing the false positive rate of docking calculations.

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

    Science.gov (United States)

    Durmuş, Saliha; Ülgen, Kutlu Ö

    2017-01-01

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

  6. Signature Visualization of Software Binaries

    Energy Technology Data Exchange (ETDEWEB)

    Panas, T

    2008-07-01

    In this paper we present work on the visualization of software binaries. In particular, we utilize ROSE, an open source compiler infrastructure, to pre-process software binaries, and we apply a landscape metaphor to visualize the signature of each binary (malware). We define the signature of a binary as a metric-based layout of the functions contained in the binary. In our initial experiment, we visualize the signatures of a series of computer worms that all originate from the same line. These visualizations are useful for a number of reasons. First, the images reveal how the archetype has evolved over a series of versions of one worm. Second, one can see the distinct changes between version. This allows the viewer to form conclusions about the development cycle of a particular worm.

  7. Observing binary inspiral with LIGO

    CERN Document Server

    Finn, L S

    1994-01-01

    Gravitational radiation from a binary neutron star or black hole system leads to orbital decay and the eventual coalescence of the binary's components. During the last several minutes before the binary components coalesce, the radiation will enter the bandwidth of the United States Laser Inteferometer Gravitational-wave Observatory (LIGO) and the French/Italian VIRGO gravitational radiation detector. The combination of detector sensitivity, signal strength, and source density and distribution all point to binary inspiral as the most likely candidate for observation among all the anticipated sources of gravitational radiation for LIGO/VIRGO. Here I review briefly some of the questions that are posed to theorists by the impending observation of binary inspiral.

  8. Towards Physarum Binary Adders

    CERN Document Server

    Jones, Jeff; 10.1016/j.biosystems.2010.04.005

    2010-01-01

    Plasmodium of \\emph{Physarum polycephalum} is a single cell visible by unaided eye. The plasmodium's foraging behaviour is interpreted in terms of computation. Input data is a configuration of nutrients, result of computation is a network of plasmodium's cytoplasmic tubes spanning sources of nutrients. Tsuda et al (2004) experimentally demonstrated that basic logical gates can be implemented in foraging behaviour of the plasmodium. We simplify the original designs of the gates and show --- in computer models --- that the plasmodium is capable for computation of two-input two-output gate $ \\to $ and three-input two-output $ \\to $. We assemble the gates in a binary one-bit adder and demonstrate validity of the design using computer simulation.

  9. Towards Physarum binary adders.

    Science.gov (United States)

    Jones, Jeff; Adamatzky, Andrew

    2010-07-01

    Plasmodium of Physarum polycephalum is a single cell visible by unaided eye. The plasmodium's foraging behaviour is interpreted in terms of computation. Input data is a configuration of nutrients, result of computation is a network of plasmodium's cytoplasmic tubes spanning sources of nutrients. Tsuda et al. (2004) experimentally demonstrated that basic logical gates can be implemented in foraging behaviour of the plasmodium. We simplify the original designs of the gates and show - in computer models - that the plasmodium is capable for computation of two-input two-output gate x, y-->xy, x+y and three-input two-output x,y,z-->x yz,x+y+z. We assemble the gates in a binary one-bit adder and demonstrate validity of the design using computer simulation.

  10. Eccentric Binary Millisecond Pulsars

    CERN Document Server

    Freire, Paulo C C

    2009-01-01

    In this paper we review the recent discovery of several millisecond pulsars (MSPs) in eccentric binary systems. Timing these MSPs we were able to estimate (and in one case precisely measure) their masses. These results suggest that, as a class, MSPs have a much wider range of masses (1.3 to > 2 solar masses) than the normal and mildly recycled pulsars found in double neutron star (DNS) systems (1.25 < Mp < 1.44 solar masses). This is very likely to be due to the prolonged accretion episode that is thought to be required to form a MSP. The likely existence of massive MSPs makes them a powerful probe for understanding the behavior of matter at densities larger than that of the atomic nucleus; in particular, the precise measurement of the mass of PSR J1903+0327 ($1.67 +/- 0.01 solar masses) excludes several "soft" equations of state for dense matter.

  11. High-throughput mammalian two-hybrid screening for protein-protein interactions using transfected cell arrays

    Directory of Open Access Journals (Sweden)

    Thamm Sabine

    2008-02-01

    Full Text Available Abstract Background Most of the biological processes rely on the formation of protein complexes. Investigation of protein-protein interactions (PPI is therefore essential for understanding of cellular functions. It is advantageous to perform mammalian PPI analysis in mammalian cells because the expressed proteins can then be subjected to essential post-translational modifications. Until now mammalian two-hybrid assays have been performed on individual gene scale. We here describe a new and cost-effective method for the high-throughput detection of protein-protein interactions in mammalian cells that combines the advantages of mammalian two-hybrid systems with those of DNA microarrays. Results In this cell array protein-protein interaction assay (CAPPIA, mixtures of bait and prey expression plasmids together with an auto-fluorescent reporter are immobilized on glass slides in defined array formats. Adherent cells that grow on top of the micro-array will become fluorescent only if the expressed proteins interact and subsequently trans-activate the reporter. Using known interaction partners and by screening 160 different combinations of prey and bait proteins associated with the human androgen receptor we demonstrate that this assay allows the quantitative detection of specific protein interactions in different types of mammalian cells and under the influence of different compounds. Moreover, different strategies in respect to bait-prey combinations are presented. Conclusion We demonstrate that the CAPPIA assay allows the quantitative detection of specific protein interactions in different types of mammalian cells and under the influence of different compounds. The high number of preys that can be tested per slide together with the flexibility to interrogate any bait of interest and the small amounts of reagents that are required makes this assay currently one of the most economical high-throughput detection assays for protein-protein interactions

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

    OpenAIRE

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

    2013-01-01

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

  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. 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. 

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

    Science.gov (United States)

    Hosur, Raghavendra; Peng, Jian; Vinayagam, Arunachalam; Stelzl, Ulrich; Xu, Jinbo; Perrimon, Norbert; Bienkowska, Jadwiga; Berger, Bonnie

    2012-08-31

    Improving the quality and coverage of the protein interactome is of tantamount importance for biomedical research, particularly given the various sources of uncertainty in high-throughput techniques. We introduce a structure-based framework, Coev2Net, for computing a single confidence score that addresses both false-positive and false-negative rates. Coev2Net is easily applied to thousands of binary protein interactions and has superior predictive performance over existing methods. We experimentally validate selected high-confidence predictions in the human MAPK network and show that predicted interfaces are enriched for cancer -related or damaging SNPs. Coev2Net can be downloaded at http://struct2net.csail.mit.edu.

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

    Science.gov (United States)

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

    2014-05-30

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

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

    Science.gov (United States)

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

    2015-11-01

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

  18. A Cautionary Note on the Use of Split-YFP/BiFC in Plant Protein-Protein Interaction Studies

    Directory of Open Access Journals (Sweden)

    Anneke Horstman

    2014-05-01

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

  19. An information-theoretic classification of amino acids for the assessment of interfaces in protein-protein docking.

    Science.gov (United States)

    Jardin, Christophe; Stefani, Arno G; Eberhardt, Martin; Huber, Johannes B; Sticht, Heinrich

    2013-09-01

    Docking represents a versatile and powerful method to predict the geometry of protein-protein complexes. However, despite significant methodical advances, the identification of good docking solutions among a large number of false solutions still remains a difficult task. We have previously demonstrated that the formalism of mutual information (MI) from information theory can be adapted to protein docking, and we have now extended this approach to enhance its robustness and applicability. A large dataset consisting of 22,934 docking decoys derived from 203 different protein-protein complexes was used for an MI-based optimization of reduced amino acid alphabets representing the protein-protein interfaces. This optimization relied on a clustering analysis that allows one to estimate the mutual information of whole amino acid alphabets by considering all structural features simultaneously, rather than by treating them individually. This clustering approach is fast and can be applied in a similar fashion to the generation of reduced alphabets for other biological problems like fold recognition, sequence data mining, or secondary structure prediction. The reduced alphabets derived from the present work were converted into a scoring function for the evaluation of docking solutions, which is available for public use via the web service score-MI: http://score-MI.biochem.uni-erlangen.de.

  20. Improving protein protein interaction prediction based on phylogenetic information using a least-squares support vector machine.

    Science.gov (United States)

    Craig, Roger A; Liao, Li

    2007-12-01

    Predicting protein-protein interactions has become a key step of reverse-engineering biological networks to better understand cellular functions. The experimental methods in determining protein-protein interactions are time-consuming and costly, which has motivated vigorous development of computational approaches for predicting protein-protein interactions. A set of recently developed bioinformatics methods utilizes coevolutionary information of the interacting partners (e.g., as exhibited in the form of correlations between distance matrices, where, for each protein, a matrix stores the pairwise distances between the protein and its orthologs in a group of reference genomes). We proposed a novel method to account for the intra-matrix correlations in improving predictive accuracy. The distance matrices for a pair of proteins are transformed and concatenated into a phylogenetic vector. A least-squares support vector machine is trained and tested on pairs of proteins, represented as phylogenetic vectors, whose interactions are known. The intra-matrix correlations are accounted for by introducing a weighted linear kernel, which determines the dot product of two phylogenetic vectors. The performance, measured as receiver operator characteristic (ROC) score in cross-validation experiments, shows significant improvement of our method (ROC score 0.928) over that obtained by Pearson correlations (0.659).

  1. Projected Constraints on Scalarization with Gravitational Waves from Neutron Star Binaries

    CERN Document Server

    Sampson, Laura; Cornish, Neil; Ponce, Marcelo; Barausse, Enrico; Klein, Antoine; Palenzuela, Carlos; Lehner, Luis

    2014-01-01

    Certain scalar-tensor theories have the property of endowing stars with scalar hair, sourced either by the star's own compactness (spontaneous scalarization) or, for binary systems, by the companion's scalar hair (induced scalarization) or by the orbital binding energy (dynamical scalarization). Scalarized stars in binaries present different conservative dynamics than in General Relativity, and can also excite a scalar mode in the metric perturbation that carries away dipolar radiation. As a result, the binary orbit shrinks faster than predicted in General Relativity, modifying the rate of decay of the orbital period. In spite of this, scalar-tensor theories can pass existing binary pulsar tests, because observed pulsars may not be compact enough or sufficiently orbitally bound to activate scalarization. Gravitational waves emitted during the last stages of compact binary inspirals are thus ideal probes of scalarization effects. For the standard projected sensitivity of advanced LIGO, we here show that, if ne...

  2. Identification of AOSC-binding proteins in neurons

    Institute of Scientific and Technical Information of China (English)

    LIU Ming; NIE Qin; XIN Xianliang; GENG Meiyu

    2008-01-01

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

  3. Dynamical Evolution of Wide Binaries

    Directory of Open Access Journals (Sweden)

    Esmeralda H. Mallada

    2001-01-01

    Full Text Available We simulate numerically encounters of wide binaries with field stars and Giant Molecular Clouds (GMCs by means of the impulse approximation. We analyze the time evolution of the distributions of eccentricities and semimajor axes of wide binaries with given initial conditions, at intervals of 109 yr, up to 1010 yr (assumed age of the Galaxy. We compute the fraction of surviving binaries for stellar encounters, for GMC encounters and for a combination of both, and hence, the dynamical lifetime for different semimajor axes and different masses of binaries (0.5, 1, 1.2, 1.5, 2.5, and 3 Msolar. We find that the dynamical lifetime of wide binaries considering only GMCs is half than that considering only stars. For encounters with GMCs we analyze the influence of the initial inclination of the orbital plane of the binary with respect to the plane perpendicular to the relative velocity vector of the binary and the GMC. We find that the perturbation is maximum when the angle is minimum.

  4. Protein-protein interaction domains of Bacillus subtilis DivIVA.

    Science.gov (United States)

    van Baarle, Suey; Celik, Ilkay Nazli; Kaval, Karan Gautam; Bramkamp, Marc; Hamoen, Leendert W; Halbedel, Sven

    2013-03-01

    DivIVA proteins are curvature-sensitive membrane binding proteins that recruit other proteins to the poles and the division septum. They consist of a conserved N-terminal lipid binding domain fused to a less conserved C-terminal domain. DivIVA homologues interact with different proteins involved in cell division, chromosome segregation, genetic competence, or cell wall synthesis. It is unknown how DivIVA interacts with these proteins, and we used the interaction of Bacillus subtilis DivIVA with MinJ and RacA to investigate this. MinJ is a transmembrane protein controlling division site selection, and the DNA-binding protein RacA is crucial for chromosome segregation during sporulation. Initial bacterial two-hybrid experiments revealed that the C terminus of DivIVA appears to be important for recruiting both proteins. However, the interpretation of these results is limited since it appeared that C-terminal truncations also interfere with DivIVA oligomerization. Therefore, a chimera approach was followed, making use of the fact that Listeria monocytogenes DivIVA shows normal polar localization but is not biologically active when expressed in B. subtilis. Complementation experiments with different chimeras of B. subtilis and L. monocytogenes DivIVA suggest that MinJ and RacA bind to separate DivIVA domains. Fluorescence microscopy of green fluorescent protein-tagged RacA and MinJ corroborated this conclusion and suggests that MinJ recruitment operates via the N-terminal lipid binding domain, whereas RacA interacts with the C-terminal domain. We speculate that this difference is related to the cellular compartments in which MinJ and RacA are active: the cell membrane and the cytoplasm, respectively.

  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. Protein-protein docking with F(2Dock 2.0 and GB-rerank.

    Directory of Open Access Journals (Sweden)

    Rezaul Chowdhury

    Full Text Available MOTIVATION: Computational simulation of protein-protein docking can expedite the process of molecular modeling and drug discovery. This paper reports on our new F(2 Dock protocol which improves the state of the art in initial stage rigid body exhaustive docking search, scoring and ranking by introducing improvements in the shape-complementarity and electrostatics affinity functions, a new knowledge-based interface propensity term with FFT formulation, a set of novel knowledge-based filters and finally a solvation energy (GBSA based reranking technique. Our algorithms are based on highly efficient data structures including the dynamic packing grids and octrees which significantly speed up the computations and also provide guaranteed bounds on approximation error. RESULTS: The improved affinity functions show superior performance compared to their traditional counterparts in finding correct docking poses at higher ranks. We found that the new filters and the GBSA based reranking individually and in combination significantly improve the accuracy of docking predictions with only minor increase in computation time. We compared F(2 Dock 2.0 with ZDock 3.0.2 and found improvements over it, specifically among 176 complexes in ZLab Benchmark 4.0, F(2 Dock 2.0 finds a near-native solution as the top prediction for 22 complexes; where ZDock 3.0.2 does so for 13 complexes. F(2 Dock 2.0 finds a near-native solution within the top 1000 predictions for 106 complexes as opposed to 104 complexes for ZDock 3.0.2. However, there are 17 and 15 complexes where F(2 Dock 2.0 finds a solution but ZDock 3.0.2 does not and vice versa; which indicates that the two docking protocols can also complement each other. AVAILABILITY: The docking protocol has been implemented as a server with a graphical client (TexMol which allows the user to manage multiple docking jobs, and visualize the docked poses and interfaces. Both the server and client are available for download. Server

  7. Improving protein-protein interactions prediction accuracy using protein evolutionary information and relevance vector machine model.

    Science.gov (United States)

    An, Ji-Yong; Meng, Fan-Rong; You, Zhu-Hong; Chen, Xing; Yan, Gui-Ying; Hu, Ji-Pu

    2016-10-01

    Predicting protein-protein interactions (PPIs) is a challenging task and essential to construct the protein interaction networks, which is important for facilitating our understanding of the mechanisms of biological systems. Although a number of high-throughput technologies have been proposed to predict PPIs, there are unavoidable shortcomings, including high cost, time intensity, and inherently high false positive rates. For these reasons, many computational methods have been proposed for predicting PPIs. However, the problem is still far from being solved. In this article, we propose a novel computational method called RVM-BiGP that combines the relevance vector machine (RVM) model and Bi-gram Probabilities (BiGP) for PPIs detection from protein sequences. The major improvement includes (1) Protein sequences are represented using the Bi-gram probabilities (BiGP) feature representation on a Position Specific Scoring Matrix (PSSM), in which the protein evolutionary information is contained; (2) For reducing the influence of noise, the Principal Component Analysis (PCA) method is used to reduce the dimension of BiGP vector; (3) The powerful and robust Relevance Vector Machine (RVM) algorithm is used for classification. Five-fold cross-validation experiments executed on yeast and Helicobacter pylori datasets, which achieved very high accuracies of 94.57 and 90.57%, respectively. Experimental results are significantly better than previous methods. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the yeast dataset. The experimental results demonstrate that our RVM-BiGP method is significantly better than the SVM-based method. In addition, we achieved 97.15% accuracy on imbalance yeast dataset, which is higher than that of balance yeast dataset. The promising experimental results show the efficiency and robust of the proposed method, which can be an automatic decision support tool for future

  8. Membrane Binding and Modulation of the PDZ Domain of PICK1

    DEFF Research Database (Denmark)

    Erlendsson, Simon; Madsen, Kenneth Lindegaard

    2015-01-01

    Scaffolding proteins serve to assemble protein complexes in dynamic processes by means of specific protein-protein and protein-lipid binding domains. Many of these domains bind either proteins or lipids exclusively; however, it has become increasingly evident that certain domains are capable of b...... lipids. Moreover, we review how these PDZ-membrane interactions are regulated in the case of the synaptic scaffolding protein PICK1 and how this might affect cellular localization and function....

  9. Binding Procurement

    Science.gov (United States)

    Rao, Gopalakrishna M.; Vaidyanathan, Hari

    2007-01-01

    This viewgraph presentation reviews the use of the binding procurement process in purchasing Aerospace Flight Battery Systems. NASA Engineering and Safety Center (NESC) requested NASA Aerospace Flight Battery Systems Working Group to develop a set of guideline requirements document for Binding Procurement Contracts.

  10. Chaotic zones around gravitating binaries

    CERN Document Server

    Shevchenko, Ivan I

    2014-01-01

    The extent of the continuous zone of chaotic orbits of a small-mass tertiary around a system of two gravitationally bound bodies (a double star, a double black hole, a binary asteroid, etc.) is estimated analytically, in function of the tertiary's orbital eccentricity. The separatrix map theory is used to demonstrate that the central continuous chaos zone emerges due to overlapping of the orbital resonances corresponding to the integer ratios p:1 between the tertiary and the binary periods. The binary's mass ratio, above which such a chaotic zone is universally present, is also estimated.

  11. Modified evolution of stellar binaries from supermassive black hole binaries

    Science.gov (United States)

    Liu, Bin; Wang, Yi-Han; Yuan, Ye-Fei

    2017-04-01

    The evolution of main-sequence binaries resided in the galactic centre is influenced a lot by the central supermassive black hole (SMBH). Due to this perturbation, the stars in a dense environment are likely to experience mergers or collisions through secular or non-secular interactions. In this work, we study the dynamics of the stellar binaries at galactic centre, perturbed by another distant SMBH. Geometrically, such a four-body system is supposed to be decomposed into the inner triple (SMBH-star-star) and the outer triple (SMBH-stellar binary-SMBH). We survey the parameter space and determine the criteria analytically for the stellar mergers and the tidal disruption events (TDEs). For a relative distant and equal masses SMBH binary, the stars have more opportunities to merge as a result from the Lidov-Kozai (LK) oscillations in the inner triple. With a sample of tight stellar binaries, our numerical experiments reveal that a significant fraction of the binaries, ∼70 per cent, experience merger eventually. Whereas the majority of the stellar TDEs are likely to occur at a close periapses to the SMBH, induced by the outer Kozai effect. The tidal disruptions are found numerically as many as ∼10 per cent for a close SMBH binary that is enhanced significantly than the one without the external SMBH. These effects require the outer perturber to have an inclined orbit (≥40°) relatively to the inner orbital plane and may lead to a burst of the extremely astronomical events associated with the detection of the SMBH binary.

  12. High-content positional biosensor screening assay for compounds to prevent or disrupt androgen receptor and transcriptional intermediary factor 2 protein-protein interactions.

    Science.gov (United States)

    Hua, Yun; Shun, Tong Ying; Strock, Christopher J; Johnston, Paul A

    2014-09-01

    The androgen receptor-transcriptional intermediary factor 2 (AR-TIF2) positional protein-protein interaction (PPI) biosensor assay described herein combines physiologically relevant cell-based assays with the specificity of binding assays by incorporating structural information of AR and TIF2 functional domains along with intracellular targeting sequences and fluorescent reporters. Expression of the AR-red fluorescent protein (RFP) "prey" and TIF2-green fluorescent protein (GFP) "bait" components of the biosensor was directed by recombinant adenovirus constructs that expressed the ligand binding and activation function 2 surface domains of AR fused to RFP with nuclear localization and nuclear export sequences, and three α-helical LXXLL motifs from TIF2 fused to GFP and an HIV Rev nucleolar targeting sequence. In unstimulated cells, AR-RFP was localized predominantly to the cytoplasm and TIF2-GFP was localized to nucleoli. Dihydrotestosterone (DHT) treatment induced AR-RFP translocation into the nucleus where the PPIs between AR and TIF2 resulted in the colocalization of both biosensors within the nucleolus. We adapted the translocation enhanced image analysis module to quantify the colocalization of the AR-RFP and TIF2-GFP biosensors in images acquired on the ImageXpress platform. DHT induced a concentration-dependent AR-TIF2 colocalization and produced a characteristic condensed punctate AR-RFP PPI nucleolar distribution pattern. The heat-shock protein 90 inhibitor 17-N-allylamino-17-demethoxygeldanamycin (17-AAG) and antiandrogens flutamide and bicalutamide inhibited DHT-induced AR-TIF2 PPI formation with 50% inhibition concentrations (IC50s) of 88.5±12.5 nM, 7.6±2.4 μM, and 1.6±0.4 μM, respectively. Images of the AR-RFP distribution phenotype allowed us to distinguish between 17-AAG and flutamide, which prevented AR translocation, and bicalutamide, which blocked AR-TIF2 PPIs. We screened the Library of Pharmacologically Active Compounds (LOPAC) set

  13. Binary Oscillatory Crossflow Electrophoresis

    Science.gov (United States)

    Molloy, Richard F.; Gallagher, Christopher T.; Leighton, David T., Jr.

    1997-01-01

    Electrophoresis has long been recognized as an effective analytic technique for the separation of proteins and other charged species, however attempts at scaling up to accommodate commercial volumes have met with limited success. In this report we describe a novel electrophoretic separation technique - Binary Oscillatory Crossflow Electrophoresis (BOCE). Numerical simulations indicate that the technique has the potential for preparative scale throughputs with high resolution, while simultaneously avoiding many problems common to conventional electrophoresis. The technique utilizes the interaction of an oscillatory electric field and a transverse oscillatory shear flow to create an active binary filter for the separation of charged protein species. An oscillatory electric field is applied across the narrow gap of a rectangular channel inducing a periodic motion of charged protein species. The amplitude of this motion depends on the dimensionless electrophoretic mobility, alpha = E(sub o)mu/(omega)d, where E(sub o) is the amplitude of the electric field oscillations, mu is the dimensional mobility, omega is the angular frequency of oscillation and d is the channel gap width. An oscillatory shear flow is induced along the length of the channel resulting in the separation of species with different mobilities. We present a model that predicts the oscillatory behavior of charged species and allows estimation of both the magnitude of the induced convective velocity and the effective diffusivity as a function of a in infinitely long channels. Numerical results indicate that in addition to the mobility dependence, the steady state behavior of solute species may be strongly affected by oscillating fluid into and out of the active electric field region at the ends of the cell. The effect is most pronounced using time dependent shear flows of the same frequency (cos((omega)t)) flow mode) as the electric field oscillations. Under such conditions, experiments indicate that

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

    Science.gov (United States)

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

    2013-11-01

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

  15. Stability of binaries. Part II: Rubble-pile binaries

    Science.gov (United States)

    Sharma, Ishan

    2016-10-01

    We consider the stability of the binary asteroids whose members are granular aggregates held together by self-gravity alone. A binary is said to be stable whenever both its members are orbitally and structurally stable to both orbital and structural perturbations. To this end, we extend the stability analysis of Sharma (Sharma [2015] Icarus, 258, 438-453), that is applicable to binaries with rigid members, to the case of binary systems with rubble members. We employ volume averaging (Sharma et al. [2009] Icarus, 200, 304-322), which was inspired by past work on elastic/fluid, rotating and gravitating ellipsoids. This technique has shown promise when applied to rubble-pile ellipsoids, but requires further work to settle some of its underlying assumptions. The stability test is finally applied to some suspected binary systems, viz., 216 Kleopatra, 624 Hektor and 90 Antiope. We also see that equilibrated binaries that are close to mobilizing their maximum friction can sustain only a narrow range of shapes and, generally, congruent shapes are preferred.

  16. Evaluation of the coarse-grained OPEP force field for protein-protein docking

    OpenAIRE

    Kynast, Philipp; Derreumaux, Philippe; Strodel, Birgit

    2016-01-01

    International audience; Background: Knowing the binding site of protein–protein complexes helps understand their function and shows possible regulation sites. The ultimate goal of protein–protein docking is the prediction of the three-dimensional structure of a protein–protein complex. Docking itself only produces plausible candidate structures, which must be ranked using scoring functions to identify the structures that are most likely to occur in nature. Methods: In this work, we rescore ri...

  17. Binary nucleation beyond capillarity approximation

    NARCIS (Netherlands)

    Kalikmanov, V.I.

    2010-01-01

    Large discrepancies between binary classical nucleation theory (BCNT) and experiments result from adsorption effects and inability of BCNT, based on the phenomenological capillarity approximation, to treat small clusters. We propose a model aimed at eliminating both of these deficiencies. Adsorption

  18. Discs in misaligned binary systems

    CERN Document Server

    Rawiraswattana, Krisada; Goodwin, Simon P

    2016-01-01

    We perform SPH simulations to study precession and changes in alignment between the circumprimary disc and the binary orbit in misaligned binary systems. We find that the precession process can be described by the rigid-disc approximation, where the disc is considered as a rigid body interacting with the binary companion only gravitationally. Precession also causes change in alignment between the rotational axis of the disc and the spin axis of the primary star. This type of alignment is of great important for explaining the origin of spin-orbit misaligned planetary systems. However, we find that the rigid-disc approximation fails to describe changes in alignment between the disc and the binary orbit. This is because the alignment process is a consequence of interactions that involve the fluidity of the disc, such as the tidal interaction and the encounter interaction. Furthermore, simulation results show that there are not only alignment processes, which bring the components towards alignment, but also anti-...

  19. Simulating relativistic binaries with Whisky

    Science.gov (United States)

    Baiotti, L.

    We report about our first tests and results in simulating the last phase of the coalescence and the merger of binary relativistic stars. The simulations were performed using our code Whisky and mesh refinement through the Carpet driver.

  20. An adaptable binary entropy coder

    Science.gov (United States)

    Kiely, A.; Klimesh, M.

    2001-01-01

    We present a novel entropy coding technique which is based on recursive interleaving of variable-to-variable length binary source codes. We discuss code design and performance estimation methods, as well as practical encoding and decoding algorithms.

  1. Magnetic braking in ultracompact binaries

    CERN Document Server

    Farmer, Alison

    2010-01-01

    Angular momentum loss in ultracompact binaries, such as the AM Canum Venaticorum stars, is usually assumed to be due entirely to gravitational radiation. Motivated by the outflows observed in ultracompact binaries, we investigate whether magnetically coupled winds could in fact lead to substantial additional angular momentum losses. We remark that the scaling relations often invoked for the relative importance of gravitational and magnetic braking do not apply, and instead use simple non-empirical expressions for the braking rates. In order to remove significant angular momentum, the wind must be tied to field lines anchored in one of the binary's component stars; uncertainties remain as to the driving mechanism for such a wind. In the case of white dwarf accretors, we find that magnetic braking can potentially remove angular momentum on comparable or even shorter timescales than gravitational waves over a large range in orbital period. We present such a solution for the 17-minute binary AM CVn itself which a...

  2. Cryptography with DNA binary strands.

    Science.gov (United States)

    Leier, A; Richter, C; Banzhaf, W; Rauhe, H

    2000-06-01

    Biotechnological methods can be used for cryptography. Here two different cryptographic approaches based on DNA binary strands are shown. The first approach shows how DNA binary strands can be used for steganography, a technique of encryption by information hiding, to provide rapid encryption and decryption. It is shown that DNA steganography based on DNA binary strands is secure under the assumption that an interceptor has the same technological capabilities as sender and receiver of encrypted messages. The second approach shown here is based on steganography and a method of graphical subtraction of binary gel-images. It can be used to constitute a molecular checksum and can be combined with the first approach to support encryption. DNA cryptography might become of practical relevance in the context of labelling organic and inorganic materials with DNA 'barcodes'.

  3. AN IMPROVED DESIGN OF REVERSIBLE BINARY TO BINARY CODED DECIMAL CONVERTER FOR BINARY CODED DECIMAL MULTIPLICATION

    Directory of Open Access Journals (Sweden)

    Praveena Murugesan

    2014-01-01

    Full Text Available Reversible logic gates under ideal conditions produce zero power dissipation. This factor highlights the usage of these gates in optical computing, low power CMOS design, quantum optics and quantum computing. The growth of decimal arithmetic in various applications as stressed the need to propose the study on reversible binary to BCD converter which plays a greater role in decimal multiplication for providing faster results. The different parameters such as gate count,garbage output and constant input are more optimized in the proposed fixed bit binary to binary coded decimal converter than the existing design.

  4. Transient Black Hole Binaries

    CERN Document Server

    Belloni, T M

    2016-01-01

    The last two decades have seen a great improvement in our understand- ing of the complex phenomenology observed in transient black-hole binary systems, especially thanks to the activity of the Rossi X-Ray Timing Explorer satellite, com- plemented by observations from many other X-ray observatories and ground-based radio, optical and infrared facilities. Accretion alone cannot describe accurately the intricate behavior associated with black-hole transients and it is now clear that the role played by different kinds of (often massive) outflows seen at different phases of the outburst evolution of these systems is as fundamental as the one played by the accretion process itself. The spectral-timing states originally identified in the X-rays and fundamentally based on the observed effect of accretion, have acquired new importance as they now allow to describe within a coherent picture the phenomenology observed at other wave- length, where the effects of ejection processes are most evident. With a particular focu...

  5. Residue arithmetic in binary systems

    OpenAIRE

    Barsi, Ferruccio

    1988-01-01

    A natural approach to the problem of performing mod m computations in a binary system is presented and a solution is suggested which is based upon a straightforward relation between the residues of a same integer X with respect to different moduli. The proposed solution proves fruitful in various applications, such as converting binary integers to residue notation and mod m addition or multiplication. Even if the most usual implementation approach for mod m processors is based on look-up tabl...

  6. Coevolution of Binaries and Gaseous Discs

    CERN Document Server

    Fleming, David P

    2016-01-01

    The recent discoveries of circumbinary planets by $\\it Kepler$ raise questions for contemporary planet formation models. Understanding how these planets form requires characterizing their formation environment, the circumbinary protoplanetary disc, and how the disc and binary interact and change as a result. The central binary excites resonances in the surrounding protoplanetary disc that drive evolution in both the binary orbital elements and in the disc. To probe how these interactions impact binary eccentricity and disc structure evolution, N-body smooth particle hydrodynamics (SPH) simulations of gaseous protoplanetary discs surrounding binaries based on Kepler 38 were run for $10^4$ binary periods for several initial binary eccentricities. We find that nearly circular binaries weakly couple to the disc via a parametric instability and excite disc eccentricity growth. Eccentric binaries strongly couple to the disc causing eccentricity growth for both the disc and binary. Discs around sufficiently eccentri...

  7. Unsupervised learning of binary vectors

    Science.gov (United States)

    Copelli Lopes da Silva, Mauro

    In this thesis, unsupervised learning of binary vectors from data is studied using methods from Statistical Mechanics of disordered systems. In the model, data vectors are distributed according to a single symmetry-breaking direction. The aim of unsupervised learning is to provide a good approximation to this direction. The difference with respect to previous studies is the knowledge that this preferential direction has binary components. It is shown that sampling from the posterior distribution (Gibbs learning) leads, for general smooth distributions, to an exponentially fast approach to perfect learning in the asymptotic limit of large number of examples. If the distribution is non-smooth, then first order phase transitions to perfect learning are expected. In the limit of poor performance, a second order phase transition ("retarded learning") is predicted to occur if the data distribution is not biased. Using concepts from Bayesian inference, the center of mass of the Gibbs ensemble is shown to have maximal average (Bayes-optimal) performance. This upper bound for continuous vectors is extended to a discrete space, resulting in the clipped center of mass of the Gibbs ensemble having maximal average performance among the binary vectors. To calculate the performance of this best binary vector, the geometric properties of the center of mass of binary vectors are studied. The surprising result is found that the center of mass of infinite binary vectors which obey some simple constraints, is again a binary vector. When disorder is taken into account in the calculation, however, a vector with continuous components is obtained. The performance of the best binary vector is calculated and shown to always lie above that of Gibbs learning and below the Bayes-optimal performance. Making use of a variational approach under the replica symmetric ansatz, an optimal potential is constructed in the limits of zero temperature and mutual overlap 1. Minimization of this potential

  8. Rational Design, Synthesis and Evaluation of Coumarin Derivatives as Protein-protein Interaction Inhibitors.

    Science.gov (United States)

    De Luca, Laura; Agharbaoui, Fatima E; Gitto, Rosaria; Buemi, Maria Rosa; Christ, Frauke; Debyser, Zeger; Ferro, Stefania

    2016-09-01

    Herein we describe the design and synthesis of a new series of coumarin derivatives searching for novel HIV-1 integrase (IN) allosteric inhibitors. All new obtained compounds were tested in order to evaluate their ability to inhibit the interaction between the HIV-1 IN enzyme and the nuclear protein lens epithelium growth factor LEDGF/p75. A combined approach of docking and molecular dynamic simulations has been applied to clarify the activity of the new compounds. Specifically, the binding free energies by using the method of molecular mechanics-generalized Born surface area (MM-GBSA) was calculated, whereas hydrogen bond occupancies were monitored throughout simulations methods.

  9. Novel Inhibitors of Protein-Protein Interaction for Prostate Cancer Therapy

    Science.gov (United States)

    2014-04-01

    which indicates their inability to compete with andro - gen for binding to AR-LBD, were considered for further studies. AR-JunDInhibitors Prevent Cell...induced AR-JunD interaction. Andro - gen-dependent LNCaP cells were treated for 72hr either with 2nmol/l androgen R1881, positive control (a) or with 2nmol...interaction in þR, 5mmol/L GWARJD10 was not significantly different from andro - gen-deprivedcontrolR,Veh.C.N¼12fieldscountedpercondition across

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

    Directory of Open Access Journals (Sweden)

    Srinivasan Narayanaswamy

    2010-06-01

    Full Text Available Abstract Background Dengue virus along with the other members of the flaviviridae family has reemerged as deadly human pathogens. Understanding the mechanistic details of these infections can be highly rewarding in developing effective antivirals. During maturation of the virus inside the host cell, the coat proteins E and M undergo conformational changes, altering the morphology of the viral coat. However, due to low resolution nature of the available 3-D structures of viral assemblies, the atomic details of these changes are still elusive. Results In the present analysis, starting from Cα positions of low resolution cryo electron microscopic structures the residue level details of protein-protein interaction interfaces of dengue virus coat proteins have been predicted. By comparing the preexisting structures of virus in different phases of life cycle, the changes taking place in these predicted protein-protein interaction interfaces were followed as a function of maturation process of the virus. Besides changing the current notion about the presence of only homodimers in the mature viral coat, the present analysis indicated presence of a proline-rich motif at the protein-protein interaction interface of the coat protein. Investigating the conservation status of these seemingly functionally crucial residues across other members of flaviviridae family enabled dissecting common mechanisms used for infections by these viruses. Conclusions Thus, using computational approach the present analysis has provided better insights into the preexisting low resolution structures of virus assemblies, the findings of which can be made use of in designing effective antivirals against these deadly human pathogens.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. The MLLE domain of the ubiquitin ligase UBR5 binds to its catalytic domain to regulate substrate binding.

    Science.gov (United States)

    Muñoz-Escobar, Juliana; Matta-Camacho, Edna; Kozlov, Guennadi; Gehring, Kalle

    2015-09-11

    E3 ubiquitin ligases catalyze the transfer of ubiquitin from an E2-conjugating enzyme to a substrate. UBR5, homologous to the E6AP C terminus (HECT)-type E3 ligase, mediates the ubiquitination of proteins involved in translation regulation, DNA damage response, and gluconeogenesis. In addition, UBR5 functions in a ligase-independent manner by prompting protein/protein interactions without ubiquitination of the binding partner. Despite recent functional studies, the mechanisms involved in substrate recognition and selective ubiquitination of its binding partners remain elusive. The C terminus of UBR5 harbors the HECT catalytic domain and an adjacent MLLE domain. MLLE domains mediate protein/protein interactions through the binding of a conserved peptide motif, termed PAM2. Here, we characterize the binding properties of the UBR5 MLLE domain to PAM2 peptides from Paip1 and GW182. The crystal structure with a Paip1 PAM2 peptide reveals the network of hydrophobic and ionic interactions that drive binding. In addition, we identify a novel interaction of the MLLE domain with the adjacent HECT domain mediated by a PAM2-like sequence. Our results confirm the role of the MLLE domain of UBR5 in substrate recruitment and suggest a potential role in regulating UBR5 ligase activity.

  13. A complete waveform model for compact binaries on eccentric orbits

    CERN Document Server

    Huerta, E A; Agarwal, Bhanu; George, Daniel; Schive, Hsi-Yu; Pfeiffer, Harald P; Chu, Tony; Boyle, Michael; Hemberger, Daniel A; Kidder, Lawrence E; Scheel, Mark A; Szilagyi, Bela

    2016-01-01

    We present a time domain waveform model that describes the inspiral, merger and ringdown of compact binary systems whose components are non-spinning, and which evolve on orbits with low to moderate eccentricity. The inspiral evolution is described using third order post-Newtonian equations both for the equations of motion of the binary, and its far-zone radiation field. This latter component also includes instantaneous, tails and tails-of-tails contributions, and a contribution due to non-linear memory. This framework reduces to the post-Newtonian approximant $\\texttt{TaylorT4}$ at third post-Newtonian order in the zero eccentricity limit. To improve phase accuracy, we also incorporate higher-order post-Newtonian corrections for the energy flux of quasi-circular binaries and gravitational self-force corrections to the binding energy of compact binaries. This enhanced prescription for the inspiral evolution is combined with a fully analytical prescription for the merger-ringdown evolution constructed using a c...

  14. Exoplanets Bouncing Between Binary Stars

    CERN Document Server

    Moeckel, Nickolas

    2012-01-01

    Exoplanetary systems are found not only among single stars, but also binaries of widely varying parameters. Binaries with separations of 100--1000 au are prevalent in the Solar neighborhood; at these separations planet formation around a binary member may largely proceed as if around a single star. During the early dynamical evolution of a planetary system, planet--planet scattering can eject planets from a star's grasp. In a binary, the motion of a planet ejected from one star has effectively entered a restricted three-body system consisting of itself and the two stars, and the equations of motion of the three body problem will apply as long as the ejected planet remains far from the remaining planets. Depending on its energy, escape from the binary as a whole may be impossible or delayed until the three-body approximation breaks down, and further close interactions with its planetary siblings boost its energy when it passes close to its parent star. Until then this planet may be able to transition from the ...

  15. Formation of Kuiper Belt Binaries

    CERN Document Server

    Goldreich, P; Sari, R; Goldreich, Peter; Lithwick, Yoram; Sari, Re'em

    2002-01-01

    It appears that at least several percent of large Kuiper belt objects are members of wide binaries. Physical collisions are too infrequent to account for their formation. Collisionless gravitational interactions are more promising. These provide two channels for binary formation. In each, the initial step is the formation of a transient binary when two large bodies penetrate each other's Hill spheres. Stabilization of a transient binary requires that it lose energy. Either dynamical friction due to small bodies or the scattering of a third large body can be responsible. Our estimates favor the former, albeit by a small margin. We predict that most objects of size comparable to those currently observed in the Kuiper belt are members of multiple systems. More specifically, we derive the probability that a large body is a member of a binary with semi-major axis of order a. The probability depends upon sigma, the total surface density, Sigma, the surface density of large bodies having radius R, and theta=10^-4, t...

  16. Kinetics of protein-protein complex coacervation and biphasic release of salbutamol sulfate from coacervate matrix.

    Science.gov (United States)

    Tiwari, Ananya; Bindal, Sonal; Bohidar, H B

    2009-01-12

    Turbidimetric titration was used to initiate associative intermolecular interactions between a pair of protein molecules, gelatin-A and gelatin-B, having complementary charges that led to pH-induced liquid-liquid phase separation and the formation of complex coacervate. The stoichiometric binding ratio was found to be [gelatin-A]/[gelatin-B]=3:2. The size of soluble intermolecular aggregates present in the supernatant exhibited interesting time-dependent coacervation because of residual electrostatic interactions. Dynamic light scattering and turbidity studies provided a systematic account of coacervation behavior. Rheology studies attributed the softening of the coacervate matrix to the presence of encapsulated salbutamol sulfate. The in vitro drug release kinetics was probed in simulated gastric fluid medium at physiological temperature (37 degrees C), which showed biphasic behavior. The initial release kinetics exhibited an exponential growth to saturation behavior, followed by a slower logarithmic release process.

  17. 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.

  18. Enhancements to the Rosetta Energy Function Enable Improved Identification of Small Molecules that Inhibit Protein-Protein Interactions.

    Directory of Open Access Journals (Sweden)

    Andrea Bazzoli

    Full Text Available Protein-protein interactions are among today's most exciting and promising targets for therapeutic intervention. To date, identifying small-molecules that selectively disrupt these interactions has proven particularly challenging for virtual screening tools, since these have typically been optimized to perform well on more "traditional" drug discovery targets. Here, we test the performance of the Rosetta energy function for identifying compounds that inhibit protein interactions, when these active compounds have been hidden amongst pools of "decoys." Through this virtual screening benchmark, we gauge the effect of two recent enhancements to the functional form of the Rosetta energy function: the new "Talaris" update and the "pwSHO" solvation model. Finally, we conclude by developing and validating a new weight set that maximizes Rosetta's ability to pick out the active compounds in this test set. Looking collectively over the course of these enhancements, we find a marked improvement in Rosetta's ability to identify small-molecule inhibitors of protein-protein interactions.

  19. A review on protein-protein interaction network of APE1/Ref-1 and its associated biological functions.

    Science.gov (United States)

    Thakur, S; Dhiman, M; Tell, G; Mantha, A K

    2015-04-01

    Apurinic/apyrimidinic endonuclease 1 (APE1) is a classic example of functionally variable protein. Besides its well-known role in (i) DNA repair of oxidative base damage, APE1 also plays a critical role in (ii) redox regulation of transcription factors controlling gene expression for cell survival pathways, for which it is also known as redox effector factor 1 (Ref-1), and recent evidences advocates for (iii) coordinated control of other non-canonical protein-protein interaction(s) responsible for significant biological functions in mammalian cells. The diverse functions of APE1 can be ascribed to its ability to interact with different protein partners, owing to the attainment of unfolded domains during evolution. Association of dysregulation of APE1 with various human pathologies, such as cancer, cardiovascular diseases and neurodegeneration, is attributable to its multifunctional nature, and this makes APE1 a potential therapeutic target. This review covers the important aspects of APE1 in terms of its significant protein-protein interaction(s), and this knowledge is required to understand the onset and development of human pathologies and to design or improve the strategies to target such interactions for treatment and management of various human diseases.

  20. Expression of mRNA and protein-protein interaction of the antiviral endoribonuclease RNase L in mouse spleen.

    Science.gov (United States)

    Gupta, Ankush; Rath, Pramod C

    2014-08-01

    The interferon-inducible, 2',5'-oligoadenylate (2-5A)-dependent endoribonuclease, RNase L is a unique antiviral RNA-degrading enzyme involved in RNA-metabolism, translational regulation, stress-response besides its anticancer/tumor-suppressor and antibacterial functions. RNase L represents complex cellular RNA-regulations in mammalian cells but diverse functions of RNase L are not completely explained by its 2-5A-regulated endoribonuclease activity. We hypothesized that RNase L has housekeeping function(s) through interaction with cellular proteins. We investigated RNase L mRNA expression in mouse tissues by RT-PCR and its protein-protein interaction in spleen by GST-pulldown and immunoprecipitation assays followed by proteomic analysis. RNase L mRNA is constitutively and differentially expressed in nine different mouse tissues, its level is maximum in immunological tissues (spleen, thymus and lungs), moderate in reproductive tissues (testis and prostate) and low in metabolic tissues (kidney, brain, liver and heart). Cellular proteins from mouse spleen [fibronectin precursor, β-actin, troponin I, myosin heavy chain 9 (non-muscle), growth-arrest specific protein 11, clathrin light chain B, a putative uncharacterized protein (Ricken cDNA 8030451F13) isoform (CRA_d) and alanyl tRNA synthetase] were identified as cellular RNase L-interacting proteins. Thus our results suggest for more general cellular functions of RNase L through protein-protein interactions in the spleen for immune response in mammals.

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

    Science.gov (United States)

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

    2017-02-01

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

  2. PETs: A Stable and Accurate Predictor of Protein-Protein Interacting Sites Based on Extremely-Randomized Trees.

    Science.gov (United States)

    Xia, Bin; Zhang, Hong; Li, Qianmu; Li, Tao

    2015-12-01

    Protein-protein interaction (PPI) plays crucial roles in the performance of various biological processes. A variety of methods are dedicated to identify whether proteins have interaction residues, but it is often more crucial to recognize each amino acid. In practical applications, the stability of a prediction model is as important as its accuracy. However, random sampling, which is widely used in previous prediction models, often brings large difference between each training model. In this paper, a Predictor of protein-protein interaction sites based on Extremely-randomized Trees (PETs) is proposed to improve the prediction accuracy while maintaining the prediction stability. In PETs, a cluster-based sampling strategy is proposed to ensure the model stability: first, the training dataset is divided into subsets using specific features; second, the subsets are clustered using K-means; and finally the samples are selected from each cluster. Using the proposed sampling strategy, samples which have different types of significant features could be selected independently from different clusters. The evaluation shows that PETs is able to achieve better accuracy while maintaining a good stability. The source code and toolkit are available at https://github.com/BinXia/PETs.

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. Dissecting the specificity of protein-protein interaction in bacterial two-component signaling: orphans and crosstalks.

    Directory of Open Access Journals (Sweden)

    Andrea Procaccini

    Full Text Available Predictive understanding of the myriads of signal transduction pathways in a cell is an outstanding challenge of systems biology. Such pathways are primarily mediated by specific but transient protein-protein interactions, which are difficult to study experimentally. In this study, we dissect the specificity of protein-protein interactions governing two-component signaling (TCS systems ubiquitously used in bacteria. Exploiting the large number of sequenced bacterial genomes and an operon structure which packages many pairs of interacting TCS proteins together, we developed a computational approach to extract a molecular interaction code capturing the preferences of a small but critical number of directly interacting residue pairs. This code is found to reflect physical interaction mechanisms, with the strongest signal coming from charged amino acids. It is used to predict the specificity of TCS interaction: Our results compare favorably to most available experimental results, including the prediction of 7 (out of 8 known interaction partners of orphan signaling proteins in Caulobacter crescentus. Surveying among the available bacterial genomes, our results suggest 15∼25% of the TCS proteins could participate in out-of-operon "crosstalks". Additionally, we predict clusters of crosstalking candidates, expanding from the anecdotally known examples in model organisms. The tools and results presented here can be used to guide experimental studies towards a system-level understanding of two-component signaling.

  6. Detecting reliable non interacting proteins (NIPs) significantly enhancing the computational prediction of protein-protein interactions using machine learning methods.

    Science.gov (United States)

    Srivastava, A; Mazzocco, G; Kel, A; Wyrwicz, L S; Plewczynski, D

    2016-03-01

    Protein-protein interactions (PPIs) play a vital role in most biological processes. Hence their comprehension can promote a better understanding of the mechanisms underlying living systems. However, besides the cost and the time limitation involved in the detection of experimentally validated PPIs, the noise in the data is still an important issue to overcome. In the last decade several in silico PPI prediction methods using both structural and genomic information were developed for this purpose. Here we introduce a unique validation approach aimed to collect reliable non interacting proteins (NIPs). Thereafter the most relevant protein/protein-pair related features were selected. Finally, the prepared dataset was used for PPI classification, leveraging the prediction capabilities of well-established machine learning methods. Our best classification procedure displayed specificity and sensitivity values of 96.33% and 98.02%, respectively, surpassing the prediction capabilities of other methods, including those trained on gold standard datasets. We showed that the PPI/NIP predictive performances can be considerably improved by focusing on data preparation.

  7. Prediction of protein-protein interactions using chaos game representation and wavelet transform via the random forest algorithm.

    Science.gov (United States)

    Jia, J H; Liu, Z; Chen, X; Xiao, X; Liu, B X

    2015-10-02

    Studying the network of protein-protein interactions (PPIs) will provide valuable insights into the inner workings of cells. It is vitally important to develop an automated, high-throughput tool that efficiently predicts protein-protein interactions. This study proposes a new model for PPI prediction based on the concept of chaos game representation and the wavelet transform, which means that a considerable amount of sequence-order effects can be incorporated into a set of discrete numbers. The advantage of using chaos game representation and the wavelet transform to formulate the protein sequence is that it can more effectively reflect its overall sequence-order characteristics than the conventional correlation factors. Using such a formulation frame to represent the protein sequences means that the random forest algorithm can be used to conduct the prediction. The results for a large-scale independent test dataset show that the proposed model can achieve an excellent performance with an accuracy value of about 0.86 and a geometry mean value of about 0.85. The model is therefore a useful supplementary tool for PPI predictions. The predictor used in this article is freely available at http://www.jci-bioinfo.cn/PPI.

  8. Evaporative Instability in Binary Mixtures

    Science.gov (United States)

    Narayanan, Ranga; Uguz, Erdem

    2012-11-01

    In this talk we depict the physics of evaporative convection for binary systems in the presence of surface tension gradient effects. Two results are of importance. The first is that a binary system, in the absence of gravity, can generate an instability only when heated from the vapor side. This is to be contrasted with the case of a single component where instability can occur only when heated from the liquid side. The second result is that a binary system, in the presence of gravity, will generate an instability when heated from either the vapor or the liquid side provided the heating is strong enough. In addition to these results we show the conditions at which interfacial patterns can occur. Support from NSF OISE 0968313, Partner Univ. Fund and a Chateaubriand Fellowship is acknowledged.

  9. Marangoni Convection in Binary Mixtures

    CERN Document Server

    Zhang, J; Oron, A; Behringer, Robert P.; Oron, Alexander; Zhang, Jie

    2006-01-01

    Marangoni instabilities in binary mixtures are different from those in pure liquids. In contrast to a large amount of experimental work on Marangoni convection in pure liquids, such experiments in binary mixtures are not available in the literature, to our knowledge. Using binary mixtures of sodium chloride/water, we have systematically investigated the pattern formation for a set of substrate temperatures and solute concentrations in an open system. The flow patterns evolve with time, driven by surface-tension fluctuations due to evaporation and the Soret effect, while the air-liquid interface does not deform. A shadowgraph method is used to follow the pattern formation in time. The patterns are mainly composed of polygons and rolls. The mean pattern size first decreases slightly, and then gradually increases during the evolution. Evaporation affects the pattern formation mainly at the early stage and the local evaporation rate tends to become spatially uniform at the film surface. The Soret effect becomes i...

  10. Asymmetric distances for binary embeddings.

    Science.gov (United States)

    Gordo, Albert; Perronnin, Florent; Gong, Yunchao; Lazebnik, Svetlana

    2014-01-01

    In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes that binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances that are applicable to a wide variety of embedding techniques including locality sensitive hashing (LSH), locality sensitive binary codes (LSBC), spectral hashing (SH), PCA embedding (PCAE), PCAE with random rotations (PCAE-RR), and PCAE with iterative quantization (PCAE-ITQ). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques.

  11. Black Hole Binaries in Quiescence

    CERN Document Server

    Bailyn, Charles D

    2016-01-01

    I discuss some of what is known and unknown about the behavior of black hole binary systems in the quiescent accretion state. Quiescence is important for several reasons: 1) the dominance of the companion star in the optical and IR wavelengths allows the binary parameters to be robustly determined - as an example, we argue that the longer proposed distance to the X-ray source GRO J1655-40 is correct; 2) quiescence represents the limiting case of an extremely low accretion rate, in which both accretion and jets can be observed; 3) understanding the evolution and duration of the quiescent state is a key factor in determining the overall demographics of X-rary binaries, which has taken on a new importance in the era of gravitational wave astronomy.

  12. Practical Binary Adaptive Block Coder

    CERN Document Server

    Reznik, Yuriy A

    2007-01-01

    This paper describes design of a low-complexity algorithm for adaptive encoding/ decoding of binary sequences produced by memoryless sources. The algorithm implements universal block codes constructed for a set of contexts identified by the numbers of non-zero bits in previous bits in a sequence. We derive a precise formula for asymptotic redundancy of such codes, which refines previous well-known estimate by Krichevsky and Trofimov, and provide experimental verification of this result. In our experimental study we also compare our implementation with existing binary adaptive encoders, such as JBIG's Q-coder, and MPEG AVC (ITU-T H.264)'s CABAC algorithms.

  13. Statistical Study of Visual Binaries

    CERN Document Server

    Abdel-Rahman, H I; Elsanhoury, W H

    2016-01-01

    In this paper, some statistical distributions of wide pairs included in Double Star Catalogue are investigated. Frequency distributions and testing hypothesis are derived for some basic parameters of visual binaries. The results reached indicate that, it was found that the magnitude difference is distributed exponentially, which means that the majority of the component of the selected systems is of the same spectral type. The distribution of the mass ratios is concentrated about 0.7 which agree with Salpeter mass function. The distribution of the linear separation appears to be exponentially, which contradict with previous studies for close binaries.

  14. Binding-site assessment by virtual fragment screening.

    Directory of Open Access Journals (Sweden)

    Niu Huang

    Full Text Available The accurate prediction of protein druggability (propensity to bind high-affinity drug-like small molecules would greatly benefit the fields of chemical genomics and drug discovery. We have developed a novel approach to quantitatively assess protein druggability by computationally screening a fragment-like compound library. In analogy to NMR-based fragment screening, we dock approximately 11,000 fragments against a given binding site and compute a computational hit rate based on the fraction of molecules that exceed an empirically chosen score cutoff. We perform a large-scale evaluation of the approach on four datasets, totaling 152 binding sites. We demonstrate that computed hit rates correlate with hit rates measured experimentally in a previously published NMR-based screening method. Secondly, we show that the in silico fragment screening method can be used to distinguish known druggable and non-druggable targets, including both enzymes and protein-protein interaction sites. Finally, we explore the sensitivity of the results to different receptor conformations, including flexible protein-protein interaction sites. Besides its original aim to assess druggability of different protein targets, this method could be used to identifying druggable conformations of flexible binding site for lead discovery, and suggesting strategies for growing or joining initial fragment hits to obtain more potent inhibitors.

  15. The biotin repressor: thermodynamic coupling of corepressor binding, protein assembly, and sequence-specific DNA binding.

    Science.gov (United States)

    Streaker, Emily D; Gupta, Aditi; Beckett, Dorothy

    2002-12-03

    The Escherichia coli biotin repressor, an allosteric transcriptional regulator, is activated for binding to the biotin operator by the small molecule biotinyl-5'-AMP. Results of combined thermodynamic, kinetic, and structural studies of the protein have revealed that corepressor binding results in disorder to order transitions in the protein monomer that facilitate tighter dimerization. The enhanced stability of the dimer leads to stabilization of the resulting biotin repressor-biotin operator complex. It is not clear, however, that the allosteric response in the system is transmitted solely through the protein-protein interface. In this work, the allosteric mechanism has been quantitatively probed by measuring the biotin operator binding and dimerization properties of three biotin repressor species: the apo or unliganded form, the biotin-bound form, and the holo or bio-5'-AMP-bound form. Comparisons of the pairwise differences in the bioO binding and dimerization energetics for the apo and holo species reveal that the enhanced DNA binding energetics resulting from adenylate binding track closely with the enhanced assembly energetics. However, when the results for repressor pairs that include the biotin-bound species are compared, no such equivalence is observed.

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

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

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

  17. KEPLER ECLIPSING BINARIES WITH STELLAR COMPANIONS

    Energy Technology Data Exchange (ETDEWEB)

    Gies, D. R.; Matson, R. A.; Guo, Z.; Lester, K. V. [Center for High Angular Resolution Astronomy and Department of Physics and Astronomy, Georgia State University, P.O. Box 5060, Atlanta, GA 30302-5060 (United States); Orosz, J. A. [Department of Astronomy, San Diego State University, San Diego, CA 92182-1221 (United States); Peters, G. J., E-mail: gies@chara.gsu.edu, E-mail: rmatson@chara.gsu.edu, E-mail: guo@chara.gsu.edu, E-mail: lester@chara.gsu.edu, E-mail: jorosz@mail.sdsu.edu, E-mail: gjpeters@mucen.usc.edu [Space Sciences Center and Department of Physics and Astronomy, University of Southern California, Los Angeles, CA 90089-1341 (United States)

    2015-12-15

    Many short-period binary stars have distant orbiting companions that have played a role in driving the binary components into close separation. Indirect detection of a tertiary star is possible by measuring apparent changes in eclipse times of eclipsing binaries as the binary orbits the common center of mass. Here we present an analysis of the eclipse timings of 41 eclipsing binaries observed throughout the NASA Kepler mission of long duration and precise photometry. This subset of binaries is characterized by relatively deep and frequent eclipses of both stellar components. We present preliminary orbital elements for seven probable triple stars among this sample, and we discuss apparent period changes in seven additional eclipsing binaries that may be related to motion about a tertiary in a long period orbit. The results will be used in ongoing investigations of the spectra and light curves of these binaries for further evidence of the presence of third stars.

  18. Binary/BCD-to-ASCII data converter

    Science.gov (United States)

    Miller, A. J.

    1977-01-01

    Converter inputs multiple precision binary words, converts data to multiple precision binary-coded decimal, and routes data back to computer. Converter base can be readily changed without need for new gate structure for each base changeover.

  19. Binary stars in the RAVE survey

    Directory of Open Access Journals (Sweden)

    Zwitter T.

    2012-02-01

    Full Text Available We searched the sample of RAVE survey spectra for both types of spectroscopic binary stars in order to estimate their number in the sample and perform a study on newly discovered binaries.

  20. In vitro auxin binding to cellular membranes of cucumber fruits.

    Science.gov (United States)

    Narayanan, K R; Mudge, K W; Poovaiah, B W

    1981-04-01

    Specific binding of 1-naphthaleneacetic acid (NAA) to crude membrane preparations from cucumber (Cucumis sativus L.) was demonstrated. This in vitro binding had a pH optimum of 3.75 and an equilibrium dissociation constant of 10 to 20 micromolar with 1250 picomoles binding sites per gram fresh weight. The NAA-binding sites were pronase sensitive. The supernatant from the fruit partially inhibited the in vitro NAA binding to fruit membranes. NAA, 2-naphthoxyacetic acid, 3-indoleacetic acid, 2-4-dichlorophenoxyacetic acid, and 2,3,5-triiodobenzoic acid, which are reported to be very good inducers of parthenocarpy in cucumber, showed a high degree of specific binding to cucumber fruit membranes. In comparison, 2-naphthaleneacetic acid and indolepropionic acid, which are reported to be very weak auxins in corn coleoptile, pea stem, and strawberry fruit growth bioassays, did not bind efficiently to cucumber fruit membranes. In vitro binding studies with fruit membranes suggest that auxin stimulated fruit growth may be mediated by membrane-associated, auxin-binding protein(s).

  1. 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

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

    Directory of Open Access Journals (Sweden)

    Kuang Lin-Yun

    2008-10-01

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

  3. Bayesian analysis of binary sequences

    Science.gov (United States)

    Torney, David C.

    2005-03-01

    This manuscript details Bayesian methodology for "learning by example", with binary n-sequences encoding the objects under consideration. Priors prove influential; conformable priors are described. Laplace approximation of Bayes integrals yields posterior likelihoods for all n-sequences. This involves the optimization of a definite function over a convex domain--efficiently effectuated by the sequential application of the quadratic program.

  4. CHAOTIC ZONES AROUND GRAVITATING BINARIES

    Energy Technology Data Exchange (ETDEWEB)

    Shevchenko, Ivan I., E-mail: iis@gao.spb.ru [Pulkovo Observatory of the Russian Academy of Sciences, Pulkovskoje ave. 65, St. Petersburg 196140 (Russian Federation)

    2015-01-20

    The extent of the continuous zone of chaotic orbits of a small-mass tertiary around a system of two gravitationally bound primaries of comparable masses (a binary star, a binary black hole, a binary asteroid, etc.) is estimated analytically, as a function of the tertiary's orbital eccentricity. The separatrix map theory is used to demonstrate that the central continuous chaos zone emerges (above a threshold in the primaries' mass ratio) due to overlapping of the orbital resonances corresponding to the integer ratios p:1 between the tertiary and the central binary periods. In this zone, the unlimited chaotic orbital diffusion of the tertiary takes place, up to its ejection from the system. The primaries' mass ratio, above which such a chaotic zone is universally present at all initial eccentricities of the tertiary, is estimated. The diversity of the observed orbital configurations of biplanetary and circumbinary exosystems is shown to be in accord with the existence of the primaries' mass parameter threshold.

  5. A Galactic Binary Detection Pipeline

    Science.gov (United States)

    Littenberg, Tyson B.

    2011-01-01

    The Galaxy is suspected to contain hundreds of millions of binary white dwarf systems, a large fraction of which will have sufficiently small orbital period to emit gravitational radiation in band for space-based gravitational wave detectors such as the Laser Interferometer Space Antenna (LISA). LISA's main science goal is the detection of cosmological events (supermassive black hole mergers, etc.) however the gravitational signal from the galaxy will be the dominant contribution to the data - including instrumental noise over approximately two decades in frequency. The catalogue of detectable binary systems will serve as an unparalleled means of studying the Galaxy. Furthermore, to maximize the scientific return from the mission, the data must be "cleansed" of the galactic foreground. We will present an algorithm that can accurately resolve and subtract 2:: 10000 of these sources from simulated data supplied by the Mock LISA Data Challenge Task Force. Using the time evolution of the gravitational wave frequency, we will reconstruct the position of the recovered binaries and show how LISA will sample the entire compact binary population in the Galaxy.

  6. The Meritfactor of Binary Seqences

    DEFF Research Database (Denmark)

    Høholdt, Tom

    1999-01-01

    Binary sequences with small aperiodic correlations play an important role in many applications ranging from radar to modulation and testing of systems. Golay(1977) introduced the merit factor as a measure of the goodness of the sequence and conjectured an upper bound for this. His conjecture is s...

  7. Eccentricity distribution of wide binaries

    CERN Document Server

    Tokovinin, Andrei

    2015-01-01

    A sample of 477 solar-type binaries within 67pc with projected separations larger than 50AU is studied by a new statistical method. Speed and direction of the relative motion are determined from the short observed arcs or known orbits, and their joint distribution is compared to the numerical simulations. By inverting the observed distribution with the help of simulations, we find that average eccentricity of wide binaries is 0.59+-0.02 and the eccentricity distribution can be modeled as f(e) ~= 1.2 e + 0.4. However, wide binaries containing inner subsystems, i.e. triple or higher-order multiples, have significantly smaller eccentricities with the average e = 0.52+-0.05 and the peak at e ~ 0.5. We find that the catalog of visual orbits is strongly biased against large eccentricities. A marginal evidence of eccentricity increasing with separation (or period) is found for this sample. Comparison with spectroscopic binaries proves the reality of the controversial period-eccentricity relation. The average eccentr...

  8. Coevolution of binaries and circumbinary gaseous discs

    Science.gov (United States)

    Fleming, David P.; Quinn, Thomas R.

    2017-01-01

    The recent discoveries of circumbinary planets by Kepler raise questions for contemporary planet formation models. Understanding how these planets form requires characterizing their formation environment, the circumbinary protoplanetary disc and how the disc and binary interact and change as a result. The central binary excites resonances in the surrounding protoplanetary disc which drive evolution in both the binary orbital elements and in the disc. To probe how these interactions impact binary eccentricity and disc structure evolution, N-body smooth particle hydrodynamics simulations of gaseous protoplanetary discs surrounding binaries based on Kepler 38 were run for 104 binary periods for several initial binary eccentricities. We find that nearly circular binaries weakly couple to the disc via a parametric instability and excite disc eccentricity growth. Eccentric binaries strongly couple to the disc causing eccentricity growth for both the disc and binary. Discs around sufficiently eccentric binaries which strongly couple to the disc develop an m = 1 spiral wave launched from the 1:3 eccentric outer Lindblad resonance which corresponds to an alignment of gas particle longitude of periastrons. All systems display binary semimajor axis decay due to dissipation from the viscous disc.

  9. Formation and evolution of compact binaries

    NARCIS (Netherlands)

    Sluijs, Marcel Vincent van der

    2006-01-01

    In this thesis we investigate the formation and evolution of compact binaries. Chapters 2 through 4 deal with the formation of luminous, ultra-compact X-ray binaries in globular clusters. We show that the proposed scenario of magnetic capture produces too few ultra-compact X-ray binaries to explain

  10. Statistical analysis on protein-protein interface in crystals:Specific and non-specific interfaces are differentially distributed

    Institute of Scientific and Technical Information of China (English)

    FENG Dan; ZENG Zonghao

    2004-01-01

    The distribution of contact areas, or fractions of contacting, of protein-protein interfaces in crystals of pure polypeptides contains two components: a major exponential distribution and a minor flatter distribution. Suppose the two components belong to specific and non-specific contacts, respectively, then the probability of a contact with a given area, or fraction of contacting, can be estimated. By dividing the whole database into two sub-databases, one of them is known to contain more specific contacts than the other, this hypothesis is confirmed and it is also proved that the fraction of contacting is more effective than the contact area on discriminating specific and non-specific contacts in protein crystals.

  11. 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.

  12. 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.

  13. Dictionary and Gene Ontology Based Similarity for Named Entity Relationship Protein-protein Interaction Prediction from Biotext Corpus

    Directory of Open Access Journals (Sweden)

    Smt K. Prabavathy

    2014-12-01

    Full Text Available Protein-protein interactions functions as a significant key role in several biological systems. These involves in complex formation and many pathways which are used to perform biological processes. By accurate identification of the set of interacting proteins can get rid of new light on the functional role of various proteins in the complex surroundings of the cell. The ability to construct biologically consequential gene networks and identification of the exact relationship in the gene network is critical for present-day systems biology. In earlier research, the power of presented gene modules to shed light on the functioning of complex biological systems is studied. Most of modules in these networks have shown small link with meaningful biological function, because these methods doesn’t exactly calculate the semantic relationship between the entities. In order to overcome these problems and improve the PPI results in the biotext corpus a new method is proposed in this research. The proposed method which directly incorporates Gene Ontology (GO annotation in construction of gene modules and Dictionary-based text is proposed to extract biotext information. Dictionary-Based Text and Gene Ontology (DBTGO approach that integrates with various gene-gene pairwise similarity values, protein-protein interaction relationship obtained from gene expression, in order to gain better biotext information retrieval result. A result analysis has been carried out on Biotext Project at UC Berkley. Testing the DBTGO algorithm indicates that it is able to improve PPI relationship identification result with all previously suggested methods in terms of the precision, recall, F measure and Normalized Discounted Cumulative Gain (NDCG. The proposed DBTGO algorithm can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level.

  14. Effect of reference genome selection on the performance of computational methods for genome-wide protein-protein interaction prediction.

    Directory of Open Access Journals (Sweden)

    Vijaykumar Yogesh Muley

    Full Text Available BACKGROUND: Recent progress in computational methods for predicting physical and functional protein-protein interactions has provided new insights into the complexity of biological processes. Most of these methods assume that functionally interacting proteins are likely to have a shared evolutionary history. This history can be traced out for the protein pairs of a query genome by correlating different evolutionary aspects of their homologs in multiple genomes known as the reference genomes. These methods include phylogenetic profiling, gene neighborhood and co-occurrence of the orthologous protein coding genes in the same cluster or operon. These are collectively known as genomic context methods. On the other hand a method called mirrortree is based on the similarity of phylogenetic trees between two interacting proteins. Comprehensive performance analyses of these methods have been frequently reported in literature. However, very few studies provide insight into the effect of reference genome selection on detection of meaningful protein interactions. METHODS: We analyzed the performance of four methods and their variants to understand the effect of reference genome selection on prediction efficacy. We used six sets of reference genomes, sampled in accordance with phylogenetic diversity and relationship between organisms from 565 bacteria. We used Escherichia coli as a model organism and the gold standard datasets of interacting proteins reported in DIP, EcoCyc and KEGG databases to compare the performance of the prediction methods. CONCLUSIONS: Higher performance for predicting protein-protein interactions was achievable even with 100-150 bacterial genomes out of 565 genomes. Inclusion of archaeal genomes in the reference genome set improves performance. We find that in order to obtain a good performance, it is better to sample few genomes of related genera of prokaryotes from the large number of available genomes. Moreover, such a sampling

  15. Construction and analysis of the protein-protein interaction networks based on gene expression profiles of Parkinson's disease.

    Directory of Open Access Journals (Sweden)

    Hindol Rakshit

    Full Text Available BACKGROUND: Parkinson's Disease (PD is one of the most prevailing neurodegenerative diseases. Improving diagnoses and treatments of this disease is essential, as currently there exists no cure for this disease. Microarray and proteomics data have revealed abnormal expression of several genes and proteins responsible for PD. Nevertheless, few studies have been reported involving PD-specific protein-protein interactions. RESULTS: Microarray based gene expression data and protein-protein interaction (PPI databases were combined to construct the PPI networks of differentially expressed (DE genes in post mortem brain tissue samples of patients with Parkinson's disease. Samples were collected from the substantia nigra and the frontal cerebral cortex. From the microarray data, two sets of DE genes were selected by 2-tailed t-tests and Significance Analysis of Microarrays (SAM, run separately to construct two Query-Query PPI (QQPPI networks. Several topological properties of these networks were studied. Nodes with High Connectivity (hubs and High Betweenness Low Connectivity (bottlenecks were identified to be the most significant nodes of the networks. Three and four-cliques were identified in the QQPPI networks. These cliques contain most of the topologically significant nodes of the networks which form core functional modules consisting of tightly knitted sub-networks. Hitherto unreported 37 PD disease markers were identified based on their topological significance in the networks. Of these 37 markers, eight were significantly involved in the core functional modules and showed significant change in co-expression levels. Four (ARRB2, STX1A, TFRC and MARCKS out of the 37 markers were found to be associated with several neurotransmitters including dopamine. CONCLUSION: This study represents a novel investigation of the PPI networks for PD, a complex disease. 37 proteins identified in our study can be considered as PD network biomarkers. These network

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

    Science.gov (United States)

    Klein, Hélène; Abu-Arish, Asmahan; Trinh, Nguyen Thu Ngan; Luo, Yishan; Wiseman, Paul W; Hanrahan, John W; Brochiero, Emmanuelle; Sauvé, Rémy

    2016-01-01

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

  17. Gravitational Microlensing of Binary and Binary and Multiple Stars

    Science.gov (United States)

    Cherepashchuk, A. M.

    1995-08-01

    Recent observations of the effect of microlensing of stars of large Magellanic Clouds by dark bodies of Galactic Halo have led to the discovery of new population in our galaxy - dark bodies with amsses ~ 0.1 M(sun). As a consequence, astronomers have gained a unique possibility of using gravitational microlensing as an effective extraterestrial telescope with extremely high angular resolution. Application of this to binary stars is discussed. of particular interest is to apply microlensing to search for planetary stars . Planets and stars move about the center of gravity of the system , so the appaarent motion of a star in nonuniform and the light curve is asymetrical and colour dependent. This allows to determin basic parameters of binary system

  18. Permutation Entropy for Random Binary Sequences

    Directory of Open Access Journals (Sweden)

    Lingfeng Liu

    2015-12-01

    Full Text Available In this paper, we generalize the permutation entropy (PE measure to binary sequences, which is based on Shannon’s entropy, and theoretically analyze this measure for random binary sequences. We deduce the theoretical value of PE for random binary sequences, which can be used to measure the randomness of binary sequences. We also reveal the relationship between this PE measure with other randomness measures, such as Shannon’s entropy and Lempel–Ziv complexity. The results show that PE is consistent with these two measures. Furthermore, we use PE as one of the randomness measures to evaluate the randomness of chaotic binary sequences.

  19. Solid-phase synthesis and screening of N-acylated polyamine (NAPA) combinatorial libraries for protein binding.

    Science.gov (United States)

    Iera, Jaclyn A; Jenkins, Lisa M Miller; Kajiyama, Hiroshi; Kopp, Jeffrey B; Appella, Daniel H

    2010-11-15

    Inhibitors for protein-protein interactions are challenging to design, in part due to the unique and complex architectures of each protein's interaction domain. Most approaches to develop inhibitors for these interactions rely on rational design, which requires prior structural knowledge of the target and its ligands. In the absence of structural information, a combinatorial approach may be the best alternative to finding inhibitors of a protein-protein interaction. Current chemical libraries, however, consist mostly of molecules designed to inhibit enzymes. In this manuscript, we report the synthesis and screening of a library based on an N-acylated polyamine (NAPA) scaffold that we designed to have specific molecular features necessary to inhibit protein-protein interactions. Screens of the library identified a member with favorable binding properties to the HIV viral protein R (Vpr), a regulatory protein from HIV, that is involved in numerous interactions with other proteins critical for viral replication.

  20. Populating the Galaxy with close Be binaries

    CERN Document Server

    Kiel, P D; Murray, J R; Hayasaki, K

    2007-01-01

    Be/X-ray binaries comprise roughly two-thirds of the high-mass X-ray binaries (HMXBs), which is a class of X-ray binaries that results from the high mass of the companion or donor star (> 10 solar masses). Currently the formation and evolution of X-ray producing Be binaries is a matter of great debate. Modelling of these systems requires knowledge of Be star evolution and also consideration of how the evolution changes when the star is in close proximity to a companion. Within this work we complete a full population synthesis study of Be binaries for the Galaxy. The results for the first time match aspects of the observational data, most notably the observed upper limit to the period distribution. We conclude that greater detailed studies on the evolution of Be stars within X-ray binaries needs to be completed, so that rapid binary evolution population synthesis packages may best evolve these systems.

  1. Purification of proteins specifically binding human endogenous retrovirus K long terminal repeat by affinity elution chromatography.

    Science.gov (United States)

    Trubetskoy, D O; Zavalova, L L; Akopov, S B; Nikolaev, L G

    2002-11-01

    A novel affinity elution procedure for purification of DNA-binding proteins was developed and employed to purify to near homogeneity the proteins recognizing a 21 base pair sequence within the long terminal repeat of human endogenous retroviruses K. The approach involves loading the initial protein mixture on a heparin-agarose column and elution of protein(s) of interest with a solution of double-stranded oligonucleotide containing binding sites of the protein(s). The affinity elution has several advantages over conventional DNA-affinity chromatography: (i) it is easier and faster, permitting to isolate proteins in a 1 day-one stage procedure; (ii) yield of a target protein is severalfold higher than that in DNA-affinity chromatography; (iii) it is not necessary to prepare a special affinity support for each factor to be isolated. Theaffinity elution could be a useful alternative to conventional DNA-affinity chromatography.

  2. Close supermassive binary black holes

    Science.gov (United States)

    Gaskell, C. Martin

    2010-01-01

    It has been proposed that when the peaks of the broad emission lines in active galactic nuclei (AGNs) are significantly blueshifted or redshifted from the systemic velocity of the host galaxy, this could be a consequence of orbital motion of a supermassive blackhole binary (SMB). The AGN J1536+0441 (=SDSS J153636.22+044127.0) has recently been proposed as an example of this phenomenon. It is proposed here instead that 1536+044 is an example of line emission from a disc. If this is correct, the lack of clear optical spectral evidence for close SMBs is significant and argues either that the merging of close SMBs is much faster than has generally been hitherto thought, or if the approach is slow, that when the separation of the binary is comparable to the size of the torus and broad-line region, the feeding of the black holes is disrupted.

  3. Desktop setup for binary holograms

    Science.gov (United States)

    Ginter, Olaf; Rothe, Hendrik

    1996-08-01

    Binary gratings as holograms itself or as photographic masking tools for further fabrication steps can fulfill a lot of applications. The commonly used semiconductor technologies for direct writing of high resolution structures are often too expensive. On the other hand computer plots at a reasonable price with photographic reduction do not meet the needs of precision e.g. for interferometric inspection. The lack of cheap and reliable instruments for direct writing in an appropriate resolution is still a problem in fabricating synthetic holograms. Using off-the-shelf components a direct writing plotter for binary patterns can be built at moderate costs. Typical design rules as well as experimental results are given and the final setup is introduced.

  4. Slim Sets of Binary Trees

    CERN Document Server

    Grünewald, Stefan

    2010-01-01

    A classical problem in phylogenetic tree analysis is to decide whether there is a phylogenetic tree $T$ that contains all information of a given collection $\\cP$ of phylogenetic trees. If the answer is "yes" we say that $\\cP$ is compatible and $T$ displays $\\cP$. This decision problem is NP-complete even if all input trees are quartets, that is binary trees with exactly four leaves. In this paper, we prove a sufficient condition for a set of binary phylogenetic trees to be compatible. That result is used to give a short and self-contained proof of the known characterization of quartet sets of minimal cardinality which are displayed by a unique phylogenetic tree.

  5. Mass transfer between binary stars

    Science.gov (United States)

    Modisette, J. L.; Kondo, Y.

    1980-01-01

    The transfer of mass from one component of a binary system to another by mass ejection is analyzed through a stellar wind mechanism, using a model which integrates the equations of motion, including the energy equation, with an initial static atmosphere and various temperature fluctuations imposed at the base of the star's corona. The model is applied to several situations and the energy flow is calculated along the line of centers between the two binary components, in the rotating frame of the system, thereby incorporating the centrifugal force. It is shown that relatively small disturbances in the lower chromosphere or photosphere can produce mass loss through a stellar wind mechanism, due to the amplification of the disturbance propagating into the thinner atmosphere. Since there are many possible sources of the disturbance, the model can be used to explain many mass ejection phenomena.

  6. Classification with binary gene expressions

    OpenAIRE

    Tuna, Salih; Niranjan, Mahesan

    2009-01-01

    Microarray gene expression measurements are reported, used and archived usually to high numerical precision. However, properties of mRNA molecules, such as their low stability and availability in small copy numbers, and the fact that measurements correspond to a population of cells, rather than a single cell, makes high precision meaningless. Recent work shows that reducing measurement precision leads to very little loss of information, right down to binary levels. In this paper we show how p...

  7. Binary neuron with optical devices

    Science.gov (United States)

    Degeratu, Vasile; Degeratu, Ştefania; Şchiopu, Paul; Şchiopu, Carmen

    2009-01-01

    In this paper the authors present a model of binary neuron, a model of McCulloch-Pitts neuron with optical devices. This model of neuron can be implemented not only in the optic integrated circuits but also in the classic optical circuits it being cheap and immune not only into electromagnetic fields but also into any kind of radiation. The transfer speed of information through the neuron is very higher, it being limited only by the light speed from the received medium.

  8. Anisotropic mass ejection in binary mergers

    CERN Document Server

    Morris, T; Podsiadlowski, Ph.

    2006-01-01

    We investigate the mass loss from a rotationally distorted envelope following the early, rapid in-spiral of a companion star inside a common envelope. For initially wide, massive binaries (M_1+M_2=20M_{\\odot}, P\\sim 10 yr), the primary has a convective envelope at the onset of mass transfer and is able to store much of the available orbital angular momentum in its expanded envelope. Three-dimensional SPH calculations show that mass loss is enhanced at mid-latitudes due to shock reflection from a torus-shaped outer envelope. Mass ejection in the equatorial plane is completely suppressed if the shock wave is too weak to penetrate the outer envelope in the equatorial direction (typically when the energy deposited in the star is less than about 1/3 of the binding energy of the envelope). We present a parameter study to show how the geometry of the ejecta depends on the angular momentum and the energy deposited in the envelope during a merging event. Applications to the nearly axisymmetric, but very non-spherical ...

  9. Be/X-ray binaries

    CERN Document Server

    Reig, Pablo

    2011-01-01

    The purpose of this work is to review the observational properties of Be/X-ray binaries. The open questions in Be/X-ray binaries include those related to the Be star companion, that is, the so-called "Be phenomenon", such as, timescales associated to the formation and dissipation of the equatorial disc, mass-ejection mechanisms, V/R variability, and rotation rates; those related to the neutron star, such as, mass determination, accretion physics, and spin period evolution; but also, those that result from the interaction of the two constituents, such as, disc truncation and mass transfer. Until recently, it was thought that the Be stars' disc was not significantly affected by the neutron star. In this review, I present the observational evidence accumulated in recent years on the interaction between the circumstellar disc and the compact companion. The most obvious effect is the tidal truncation of the disc. As a result, the equatorial discs in Be/X-ray binaries are smaller and denser than those around isolat...

  10. Detecting gravitational waves from highly eccentric compact binaries

    CERN Document Server

    Tai, Kai Sheng; Pretorius, Frans

    2014-01-01

    In dense stellar regions, highly eccentric binaries of black holes and neutron stars can form through various n-body interactions. Such a binary could emit a significant fraction of its binding energy in a sequence of largely isolated gravitational wave bursts prior to merger. Given expected black hole and neutron star masses, many such systems will emit these repeated bursts at frequencies within the sensitive band of contemporary ground-based gravitational wave detectors. Unfortunately, existing gravitational wave searches are ill-suited to detect these signals. In this work, we adapt a "power stacking" method to the detection of gravitational wave signals from highly eccentric binaries. We implement this method as an extension of the Q-transform, a projection onto a multiresolution basis of windowed complex exponentials that has previously been used to analyze data from the network of LIGO/Virgo detectors. Our method searches for excess power over an ensemble of time-frequency tiles. We characterize the pe...

  11. Massive black hole binaries in gaseous nuclear discs

    CERN Document Server

    Dotti, M; Haardt, F; Mayer, L

    2008-01-01

    We study the evolution of a massive black hole pair in a rotationally supported nuclear disc. The distributions of stars and gas mimic the nuclear region of a gas-rich galaxy merger remnant. Using high-resolution SPH simulations, we follow the black hole dynamics and trace the evolution of the underlying background, until the black holes form a binary. We find that the gravitational perturbation of the pair creates a core in the disc density profile, hence decreasing the gas-dynamical drag. This leads the newly formed binary to stall at a separation of ~5 pc. In the early phases of the sinking, black holes lose memory of their initial orbital eccentricity if they co-rotate with the disc, as rotation of the gaseous background promotes circularization of the black hole orbits. Circularization is efficient until the black holes bind in a binary, though in the latest stages of the simulations a residual eccentricity > 0.1 is still present. Black holes are treated as sink particles, allowing for gas accretion. We ...

  12. Massive black hole binary evolution in gas-rich mergers

    CERN Document Server

    Colpi, M; Dotti, M; Mayer, L

    2009-01-01

    We report on key studies on the dynamics of black holes (BHs) in gas-rich galaxy mergers that underscore the vital role played by gas dissipation in promoting BH inspiral down to the smallest scales ever probed with use of high-resolution numerical simulations. In major mergers, the BHs sink rapidly under the action of gas-dynamical friction while orbiting inside the massive nuclear disc resulting from the merger. The BHs then bind and form a Keplerian binary on a scale of 5 pc. In minor mergers, BH pairing proceeds down to the minimum scale explored of 10-100 pc only when the gas fraction in the less massive galaxy is comparatively large to avoid its tidal and/or ram pressure disruption and the wandering of the light BH in the periphery of the main halo. Binary BHs enter the gravitational wave dominated inspiral only when their relative distance is typically of 0.001 pc. If the gas preserves the degree of dissipation expected in a star-burst environment, binary decay continues down to 0.1 pc, the smallest le...

  13. SEARCHING FOR BINARY Y DWARFS WITH THE GEMINI MULTI-CONJUGATE ADAPTIVE OPTICS SYSTEM (GeMS)

    Energy Technology Data Exchange (ETDEWEB)

    Opitz, Daniela; Tinney, C. G. [School of Physics, University of New South Wales, NSW 2052 (Australia); Faherty, Jacqueline K. [Department of Terrestrial Magnetism, Carnegie Institution of Washington, Washington, DC 20015 (United States); Sweet, Sarah [Research School of Astronomy and Astrophysics, Australian National University, Canberra, ACT 2611 (Australia); Gelino, Christopher R.; Kirkpatrick, J. Davy, E-mail: daniela.opitz@student.unsw.edu.au [Infrared Processing and Analysis Center, MS 100-22, California Institute of Technology, Pasadena, CA 91125 (United States)

    2016-03-01

    The NASA Wide-field Infrared Survey Explorer (WISE) has discovered almost all the known members of the new class of Y-type brown dwarfs. Most of these Y dwarfs have been identified as isolated objects in the field. It is known that binaries with L- and T-type brown dwarf primaries are less prevalent than either M-dwarf or solar-type primaries, they tend to have smaller separations and are more frequently detected in near-equal mass configurations. The binary statistics for Y-type brown dwarfs, however, are sparse, and so it is unclear if the same trends that hold for L- and T-type brown dwarfs also hold for Y-type ones. In addition, the detection of binary companions to very cool Y dwarfs may well be the best means available for discovering even colder objects. We present results for binary properties of a sample of five WISE Y dwarfs with the Gemini Multi-Conjugate Adaptive Optics System. We find no evidence for binary companions in these data, which suggests these systems are not equal-luminosity (or equal-mass) binaries with separations larger than ∼0.5–1.9 AU. For equal-mass binaries at an age of 5 Gyr, we find that the binary binding energies ruled out by our observations (i.e., 10{sup 42} erg) are consistent with those observed in previous studies of hotter ultra-cool dwarfs.

  14. Visual Binaries in the Orion Nebula Cluster

    CERN Document Server

    Reipurth, Bo; Connelley, Michael S; Bally, John

    2007-01-01

    We have carried out a major survey for visual binaries towards the Orion Nebula Cluster using HST images obtained with an H-alpha filter. Among 781 likely ONC members more than 60" from theta-1 Ori C, we find 78 multiple systems (75 binaries and 3 triples), of which 55 are new discoveries, in the range from 0.1" to 1.5". About 9 binaries are likely line-of-sight associations. We find a binary fraction of 8.8%+-1.1% within the limited separation range from 67.5 to 675 AU. The field binary fraction in the same range is a factor 1.5 higher. Within the range 150 AU to 675 AU we find that T Tauri associations have a factor 2.2 more binaries than the ONC. The binary separation distribution function of the ONC shows unusual structure, with a sudden steep decrease in the number of binaries as the separation increases beyond 0.5", corresponding to 225 AU. We have measured the ratio of binaries wider than 0.5" to binaries closer than 0.5" as a function of distance from the Trapezium, and find that this ratio is signifi...

  15. Theory on the mechanisms of combinatorial binding of transcription factors with DNA

    CERN Document Server

    Murugan, R

    2016-01-01

    We develop a theoretical framework on the mechanism of combinatorial binding of transcription factors (TFs) with their specific binding sites on DNA. We consider three possible mechanisms viz. monomer, hetero-oligomer and coordinated recruitment pathways. In the monomer pathway, combinatorial TFs search for their targets in an independent manner and the protein-protein interactions among them will be insignificant. The protein-protein interactions are very strong so that the hetero-oligomer complex of TFs as a whole searches for the cognate sites in case of hetero-oligomer pathway. The TF which arrived first will recruit the adjacent TFs in a sequential manner in the recruitment pathway. The free energy released from the protein-protein interactions among TFs will be in turn utilized to stabilize the TFs-DNA complex. Such coordinated binding of TFs in fact emerges as the cooperative effect. Monomer and hetero-oligomer pathways are efficient only when few TFs are involved in the combinatorial regulation. Detai...

  16. The use of Gene Ontology terms for predicting highly-connected 'hub' nodes in protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Cherkasov Artem

    2008-09-01

    Full Text Available Abstract Background Protein-protein interactions mediate a wide range of cellular functions and responses and have been studied rigorously through recent large-scale proteomics experiments and bioinformatics analyses. One of the most important findings of those endeavours was the observation that 'hub' proteins participate in significant numbers of protein interactions and play critical roles in the organization and function of cellular protein interaction networks (PINs 12. It has also been demonstrated that such hub proteins may constitute an important pool of attractive drug targets. Thus, it is crucial to be able to identify hub proteins based not only on experimental data but also by means of bioinformatics predictions. Results A hub protein classifier has been developed based on the available interaction data and Gene Ontology (GO annotations for proteins in the Escherichia coli, Saccharomyces cerevisiae, Drosophila melanogaster and Homo sapiens genomes. In particular, by utilizing the machine learning method of boosting trees we were able to create a predictive bioinformatics tool for the identification of proteins that are likely to play the role of a hub in protein interaction networks. Testing the developed hub classifier on external sets of experimental protein interaction data in Methicillin-resistant Staphylococcus aureus (MRSA 252 and Caenorhabditis elegans demonstrated that our approach can predict hub proteins with a high degree of accuracy. A practical application of the developed bioinformatics method has been illustrated by the effective protein bait selection for large-scale pull-down experiments that aim to map complete protein-protein interaction networks for several species. Conclusion The successful development of an accurate hub classifier demonstrated that highly-connected proteins tend to share certain relevant functional properties reflected in their Gene Ontology annotations. It is anticipated that the developed

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

    Directory of Open Access Journals (Sweden)

    Lv Jie

    2011-10-01

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

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

    Science.gov (United States)

    Du, Pufeng; Wang, Lusheng

    2014-01-01

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

  19. The PPI3D web server for searching, analyzing and modeling protein-protein interactions in the context of 3D structures.

    Science.gov (United States)

    Dapkūnas, Justas; Timinskas, Albertas; Olechnovič, Kliment; Margelevičius, Mindaugas; Dičiūnas, Rytis; Venclovas, Česlovas

    2016-12-22

    The PPI3D web server is focused on searching and analyzing the structural data on protein-protein interactions. Reducing the data redundancy by clustering and analyzing the properties of interaction interfaces using Voronoi tessellation makes this software a highly effective tool for addressing different questions related to protein interactions.

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

    Directory of Open Access Journals (Sweden)

    Koonin Eugene V

    2003-01-01

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