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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. 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

  5. The distribution of ligand-binding pockets around protein-protein interfaces suggests a general mechanism for pocket formation

    OpenAIRE

    Gao, Mu; Skolnick, Jeffrey

    2012-01-01

    Protein-protein and protein-ligand interactions are ubiquitous in a biological cell. Here, we report a comprehensive study of the distribution of protein-ligand interaction sites, namely ligand-binding pockets, around protein-protein interfaces where protein-protein interactions occur. We inspected a representative set of 1,611 representative protein-protein complexes and identified pockets with a potential for binding small molecule ligands. The majority of these pockets are within a 6 Å dis...

  6. Protein-protein binding affinities calculated using the LIE method

    OpenAIRE

    Andberg, Tor Arne Heim

    2011-01-01

    Absolute binding free energies for the third domain of the turkey ovomucoid inhibitor in complex with Streptomyces griseus proteinase B and porcine pancreatic elastase has been calculated using the linear interaction energy method.

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

    OpenAIRE

    Selvaraj S; Jayaram B; Saranya N; Gromiha M; Fukui Kazuhiko

    2011-01-01

    Abstract Background Protein-protein interactions are important for several cellular processes. Understanding the mechanism of protein-protein recognition and predicting the binding sites in protein-protein complexes are long standing goals in molecular and computational biology. Methods We have developed an energy based approach for identifying the binding site residues in protein–protein complexes. The binding site residues have been analyzed with sequence and structure based parameters such...

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

    Directory of Open Access Journals (Sweden)

    Selvaraj S

    2011-10-01

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

  9. Predicting the Impact of Missense Mutations on Protein-Protein Binding Affinity.

    Science.gov (United States)

    Li, Minghui; Petukh, Marharyta; Alexov, Emil; Panchenko, Anna R

    2014-04-01

    The crucial prerequisite for proper biological function is the protein's ability to establish highly selective interactions with macromolecular partners. A missense mutation that alters the protein binding affinity may cause significant perturbations or complete abolishment of the function, potentially leading to diseases. The availability of computational methods to evaluate the impact of mutations on protein-protein binding is critical for a wide range of biomedical applications. Here, we report an efficient computational approach for predicting the effect of single and multiple missense mutations on protein-protein binding affinity. It is based on a well-tested simulation protocol for structure minimization, modified MM-PBSA and statistical scoring energy functions with parameters optimized on experimental sets of several thousands of mutations. Our simulation protocol yields very good agreement between predicted and experimental values with Pearson correlation coefficients of 0.69 and 0.63 and root-mean-square errors of 1.20 and 1.90 kcal mol(-1) for single and multiple mutations, respectively. Compared with other available methods, our approach achieves high speed and prediction accuracy and can be applied to large datasets generated by modern genomics initiatives. In addition, we report a crucial role of water model and the polar solvation energy in estimating the changes in binding affinity. Our analysis also reveals that prediction accuracy and effect of mutations on binding strongly depends on the type of mutation and its location in a protein complex. PMID:24803870

  10. Cell-Binding Assays for Determining the Affinity of Protein-Protein Interactions: Technologies and Considerations.

    Science.gov (United States)

    Hunter, S A; Cochran, J R

    2016-01-01

    Determining the equilibrium-binding affinity (Kd) of two interacting proteins is essential not only for the biochemical study of protein signaling and function but also for the engineering of improved protein and enzyme variants. One common technique for measuring protein-binding affinities uses flow cytometry to analyze ligand binding to proteins presented on the surface of a cell. However, cell-binding assays require specific considerations to accurately quantify the binding affinity of a protein-protein interaction. Here we will cover the basic assumptions in designing a cell-based binding assay, including the relevant equations and theory behind determining binding affinities. Further, two major considerations in measuring binding affinities-time to equilibrium and ligand depletion-will be discussed. As these conditions have the potential to greatly alter the Kd, methods through which to avoid or minimize them will be provided. We then outline detailed protocols for performing direct- and competitive-binding assays against proteins displayed on the surface of yeast or mammalian cells that can be used to derive accurate Kd values. Finally, a comparison of cell-based binding assays to other types of binding assays will be presented. PMID:27586327

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

    Science.gov (United States)

    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.

  12. Improved Computation of Protein-Protein Relative Binding Energies with the Nwat-MMGBSA Method.

    Science.gov (United States)

    Maffucci, Irene; Contini, Alessandro

    2016-09-26

    A MMGBSA variant (here referred to as Nwat-MMGBSA), based on the inclusion of a certain number of explicit water molecules (Nwat) during the calculations, has been tested on a set of 20 protein-protein complexes, using the correlation between predicted and experimental binding energy as the evaluation metric. Besides the Nwat parameter, the effect of the force field, the molecular dynamics simulation length, and the implicit solvent model used in the MMGBSA analysis have been also evaluated. We found that considering 30 interfacial water molecules improved the correlation between predicted and experimental binding energies by up to 30%, compared to the standard approach. Moreover, the correlation resulted in being rather sensitive to the force field and, to a minor extent, to the implicit solvent model and to the length of the MD simulation. PMID:27500550

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

    Science.gov (United States)

    Cao, Huaiqing; Huang, Yongqi; Liu, Zhirong

    2016-07-01

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

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

    Science.gov (United States)

    Cao, Huaiqing; Huang, Yongqi; Liu, Zhirong

    2016-07-01

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

  15. Bifunctional Ligands for Inhibition of Tight-Binding Protein-Protein Interactions.

    Science.gov (United States)

    Ivan, Taavi; Enkvist, Erki; Viira, Birgit; Manoharan, Ganesh Babu; Raidaru, Gerda; Pflug, Alexander; Alam, Kazi Asraful; Zaccolo, Manuela; Engh, Richard Alan; Uri, Asko

    2016-08-17

    The acknowledged potential of small-molecule therapeutics targeting disease-related protein-protein interactions (PPIs) has promoted active research in this field. The strategy of using small molecule inhibitors (SMIs) to fight strong (tight-binding) PPIs tends to fall short due to the flat and wide interfaces of PPIs. Here we propose a biligand approach for disruption of strong PPIs. The potential of this approach was realized for disruption of the tight-binding (KD = 100 pM) tetrameric holoenzyme of cAMP-dependent protein kinase (PKA). Supported by X-ray analysis of cocrystals, bifunctional inhibitors (ARC-inhibitors) were constructed that simultaneously associated with both the ATP-pocket and the PPI interface area of the catalytic subunit of PKA (PKAc). Bifunctional inhibitor ARC-1411, possessing a KD value of 3 pM toward PKAc, induced the dissociation of the PKA holoenzyme with a low-nanomolar IC50, whereas the ATP-competitive inhibitor H89 bound to the PKA holoenzyme without disruption of the protein tetramer. PMID:27389935

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

    Science.gov (United States)

    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.

  17. Hot spots and transient pockets: predicting the determinants of small-molecule binding to a protein-protein interface.

    Science.gov (United States)

    Metz, Alexander; Pfleger, Christopher; Kopitz, Hannes; Pfeiffer-Marek, Stefania; Baringhaus, Karl-Heinz; Gohlke, Holger

    2012-01-23

    Protein-protein interfaces are considered difficult targets for small-molecule protein-protein interaction modulators (PPIMs ). Here, we present for the first time a computational strategy that simultaneously considers aspects of energetics and plasticity in the context of PPIM binding to a protein interface. The strategy aims at identifying the determinants of small-molecule binding, hot spots, and transient pockets, in a protein-protein interface in order to make use of this knowledge for predicting binding modes of and ranking PPIMs with respect to their affinity. When applied to interleukin-2 (IL-2), the computationally inexpensive constrained geometric simulation method FRODA outperforms molecular dynamics simulations in sampling hydrophobic transient pockets. We introduce the PPIAnalyzer approach for identifying transient pockets on the basis of geometrical criteria only. A sequence of docking to identified transient pockets, starting structure selection based on hot spot information, RMSD clustering and intermolecular docking energies, and MM-PBSA calculations allows one to enrich IL-2 PPIMs from a set of decoys and to discriminate between subgroups of IL-2 PPIMs with low and high affinity. Our strategy will be applicable in a prospective manner where nothing else than a protein-protein complex structure is known; hence, it can well be the first step in a structure-based endeavor to identify PPIMs. PMID:22087639

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

    Science.gov (United States)

    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.

  19. 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.

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

    DEFF Research Database (Denmark)

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

    1997-01-01

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

  1. 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...

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Baskin Berivan

    2003-03-01

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

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

    Science.gov (United States)

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

    NARCIS (Netherlands)

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

    2014-01-01

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

  7. 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.

  8. 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.

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

    OpenAIRE

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

    2003-01-01

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

  10. Identification of protein-protein binding sites by incorporating the physicochemical properties and stationary wavelet transforms into pseudo amino acid composition.

    Science.gov (United States)

    Jia, Jianhua; Liu, Zi; Xiao, Xuan; Liu, Bingxiang; Chou, Kuo-Chen

    2016-09-01

    With the explosive growth of protein sequences entering into protein data banks in the post-genomic era, it is highly demanded to develop automated methods for rapidly and effectively identifying the protein-protein binding sites (PPBSs) based on the sequence information alone. To address this problem, we proposed a predictor called iPPBS-PseAAC, in which each amino acid residue site of the proteins concerned was treated as a 15-tuple peptide segment generated by sliding a window along the protein chains with its center aligned with the target residue. The working peptide segment is further formulated by a general form of pseudo amino acid composition via the following procedures: (1) it is converted into a numerical series via the physicochemical properties of amino acids; (2) the numerical series is subsequently converted into a 20-D feature vector by means of the stationary wavelet transform technique. Formed by many individual "Random Forest" classifiers, the operation engine to run prediction is a two-layer ensemble classifier, with the 1st-layer voting out the best training data-set from many bootstrap systems and the 2nd-layer voting out the most relevant one from seven physicochemical properties. Cross-validation tests indicate that the new predictor is very promising, meaning that many important key features, which are deeply hidden in complicated protein sequences, can be extracted via the wavelets transform approach, quite consistent with the facts that many important biological functions of proteins can be elucidated with their low-frequency internal motions. The web server of iPPBS-PseAAC is accessible at http://www.jci-bioinfo.cn/iPPBS-PseAAC , by which users can easily acquire their desired results without the need to follow the complicated mathematical equations involved. PMID:26375780

  11. PeptideMine - A webserver for the design of peptides for protein-peptide binding studies derived from protein-protein interactomes

    Directory of Open Access Journals (Sweden)

    Gopal Balasubramanian

    2010-09-01

    Full Text Available Abstract Background Signal transduction events often involve transient, yet specific, interactions between structurally conserved protein domains and polypeptide sequences in target proteins. The identification and validation of these associating domains is crucial to understand signal transduction pathways that modulate different cellular or developmental processes. Bioinformatics strategies to extract and integrate information from diverse sources have been shown to facilitate the experimental design to understand complex biological events. These methods, primarily based on information from high-throughput experiments, have also led to the identification of new connections thus providing hypothetical models for cellular events. Such models, in turn, provide a framework for directing experimental efforts for validating the predicted molecular rationale for complex cellular processes. In this context, it is envisaged that the rational design of peptides for protein-peptide binding studies could substantially facilitate the experimental strategies to evaluate a predicted interaction. This rational design procedure involves the integration of protein-protein interaction data, gene ontology, physico-chemical calculations, domain-domain interaction data and information on functional sites or critical residues. Results Here we describe an integrated approach called "PeptideMine" for the identification of peptides based on specific functional patterns present in the sequence of an interacting protein. This approach based on sequence searches in the interacting sequence space has been developed into a webserver, which can be used for the identification and analysis of peptides, peptide homologues or functional patterns from the interacting sequence space of a protein. To further facilitate experimental validation, the PeptideMine webserver also provides a list of physico-chemical parameters corresponding to the peptide to determine the feasibility of

  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. Protein-protein interactions

    DEFF Research Database (Denmark)

    Byron, Olwyn; Vestergaard, Bente

    2015-01-01

    . 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......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...

  14. Flavodoxin cofactor binding induces structural changes that are required for protein-protein interactions with NADP(+) oxidoreductase and pyruvate formate-lyase activating enzyme.

    Science.gov (United States)

    Crain, Adam V; Broderick, Joan B

    2013-12-01

    Flavodoxin (Fld) conformational changes, thermal stability, and cofactor binding were studied using circular dichroism (CD), isothermal titration calorimetry (ITC), and limited proteolysis. Thermodynamics of apo and holo-Fld folding were examined to discern the features of this important electron transfer protein and to provide data on apo-Fld. With the exception of fluorescence and UV-vis binding experiments with its cofactor flavin mononucleotide (FMN), apo-Fld is almost completely uncharacterized in Escherichia coli. Fld is more structured when the FMN cofactor is bound; the association is tight and driven by enthalpy of binding. Surface plasmon resonance binding experiments were carried out under anaerobic conditions for both apo- and holo-Fld and demonstrate the importance of structure and conformation for the interaction with binding partners. Holo-Fld is capable of associating with NADP(+)-dependent flavodoxin oxidoreductase (FNR) and pyruvate formate-lyase activating enzyme (PFL-AE) whereas there is no detectable interaction between apo-Fld and either protein. Limited proteolysis experiments were analyzed by LC-MS to identify the regions in Fld that are involved in conformation changes upon cofactor binding. Docking software was used to model the Fld/PFL-AE complex to understand the interactions between these two proteins and gain insight into electron transfer reactions from Fld to PFL-AE.

  15. Binding of the AVR4 elicitor of Cladosporium fulvum to chitotriose units is facilitated by positive allosteric protein-protein interactions

    NARCIS (Netherlands)

    Burg, van den H.A.; Spronk, C.A.E.M.; Boeren, S.; Kennedy, M.A.; Vissers, J.P.C.; Vuister, G.W.; Wit, de P.J.G.M.; Vervoort, J.J.M.

    2004-01-01

    The attack of fungal cell walls by plant chitinases is an important plant defense response to fungal infection. Anti-fungal activity of plant chitinases is largely restricted to chitinases that contain a noncatalytic, plant-specific chitin-binding domain (ChBD) ( also called Hevein domain). Current

  16. 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.

  17. Hydrophilicity matching - a potential prerequisite for the formation of protein-protein complexes in the cell.

    Directory of Open Access Journals (Sweden)

    Mario Hlevnjak

    Full Text Available A binding event between two proteins typically consists of a diffusional search of binding partners for one another, followed by a specific recognition of the compatible binding sites resulting in the formation of the complex. However, it is unclear how binding partners find each other in the context of the crowded, constantly fluctuating, and interaction-rich cellular environment. Here we examine the non-specific component of protein-protein interactions, which refers to those physicochemical properties of the binding partners that are independent of the exact details of their binding sites, but which can affect their localization or diffusional search for one another. We show that, for a large set of high-resolution experimental 3D structures of binary, transient protein complexes taken from the DOCKGROUND database, the binding partners display a surprising, statistically significant similarity in terms of their total hydration free energies normalized by a size-dependent variable. We hypothesize that colocalization of binding partners, even within individual cellular compartments such as the cytoplasm, may be influenced by their relative hydrophilicity, potentially in response to local hydrophilic gradients.

  18. 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...

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

    OpenAIRE

    La, David; Kihara, Daisuke

    2011-01-01

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

  20. The second extracellular loop of pore-forming subunits of ATP-binding cassette transporters for basic amino acids plays a crucial role in interaction with the cognate solute binding protein(s).

    Science.gov (United States)

    Eckey, Viola; Weidlich, Daniela; Landmesser, Heidi; Bergmann, Ulf; Schneider, Erwin

    2010-04-01

    In the thermophile Geobacillus stearothermophilus, the uptake of basic amino acids is mediated by an ABC transporter composed of the substrate binding protein (receptor) ArtJ and a homodimer each of the pore-forming subunit, ArtM, and the nucleotide-binding subunit, ArtP. We recently identified two putative binding sites in ArtJ that might interact with the Art(MP)(2) complex, thereby initiating the transport cycle (A. Vahedi-Faridi et al., J. Mol. Biol. 375:448-459, 2008). Here we investigated the contribution of charged amino acid residues in the second extracellular loop of ArtM to contact with ArtJ. Our results demonstrate a crucial role for residues K177, R185, and E188, since mutations to oppositely charged amino acids or glutamine led to a complete loss of ArtJ-stimulated ATPase activity of the complex variants in proteoliposomes. The defects could not be suppressed by ArtJ variants carrying mutations in site I (K39E and K152E) or II (E163K and D170K), suggesting a more complex interplay than that by a single salt bridge. These findings were supported by cross-linking assays demonstrating physical proximity between ArtJ(N166C) and ArtM(E182C). The importance of positively charged residues for receptor-transporter interaction was underscored by mutational analysis of the closely related transporter HisJ/LAO-HisQMP(2) of Salmonella enterica serovar Typhimurium. While transporter variants with mutated positively charged residues in HisQ displayed residual ATPase activities, corresponding mutants of HisM could no longer be stimulated by HisJ/LAO. Interestingly, the ATPase activity of the HisQM(K187E)P(2) variant was inhibited by l- and d-histidine in detergent, suggesting a role of the residue in preventing free histidine from gaining access to the substrate binding site within HisQM. PMID:20154136

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

    Directory of Open Access Journals (Sweden)

    Su-Fang Wang

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Lehne Benjamin

    2009-04-01

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

  3. 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.

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

    Science.gov (United States)

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

    2016-06-01

    Proteins may utilize complex networks of interactions to create/proceed signaling pathways of highly adaptive responses such as programmed cell death. Direct binary interactions study of proteins may help propose models for protein-protein interaction. Towards this goal we applied a combination of thermodynamic kinetics and crystal structure analyses to elucidate the complexity and diversity in such interactions. By determining the heat change on the association of two galactose-specific legume lectins from Butea monosperma (BML) and Spatholobus parviflorus (SPL) belonging to Fabaceae family helped to compute the binding equilibrium. It was extended further by X-ray structural analysis of BML-SPL binary complex. In order to chart the proteins interacting mainly through their interfaces, identification of the nature of forces which stabilized the association of the lectin-lectin complex was examined. Comprehensive analysis of the BMLSPL complex by isothermal titration calorimetry and X-ray crystal structure threw new light on the lectin-lectin interactions suggesting of their use in diverse areas of glycobiology. PMID:26945504

  5. Principles of protein-protein interactions.

    OpenAIRE

    Jones, S; Thornton, J. M.

    1996-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  7. Hub Promiscuity in Protein-Protein Interaction Networks

    OpenAIRE

    Haruki Nakamura; Kengo Kinoshita; Ashwini Patil

    2010-01-01

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

  8. 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.

  9. 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....

  10. Binding of the AVR4 elicitor of Cladosporium fulvum to chitotriose units is facilitated by positive allosteric protein-protein interactions - The chitin-binding site of AVR4 represents a novel binding site on the folding scaffold shared between the invertebrate and the plant chitin-binding domain

    NARCIS (Netherlands)

    Burg, H.A. van den; Spronk, C.A.E.M.; Boeren, S.; Kennedy, M.A.; Vissers, J.P.C.; Vuister, G.W.; Wit, P. de; Vervoort, J.

    2004-01-01

    The attack of fungal cell walls by plant chitinases is an important plant defense response to fungal infection. Anti-fungal activity of plant chitinases is largely restricted to chitinases that contain a noncatalytic, plant-specific chitin-binding domain (ChBD) ( also called Hevein domain). Current

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

    International Nuclear Information System (INIS)

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

  12. 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.

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

    OpenAIRE

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

    2008-01-01

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

  14. Protein-Protein Interaction Analysis by Docking

    OpenAIRE

    Stephan Ederer; Florian Fink; Wolfram Gronwald

    2009-01-01

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

  15. Protein-protein complexation in bioluminescence

    OpenAIRE

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

    2011-01-01

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

  16. Parallel force assay for protein-protein interactions.

    Directory of Open Access Journals (Sweden)

    Daniela Aschenbrenner

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

  17. 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.

  18. 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.

  19. Peptiderive server: derive peptide inhibitors from protein-protein interactions.

    Science.gov (United States)

    Sedan, Yuval; Marcu, Orly; Lyskov, Sergey; Schueler-Furman, Ora

    2016-07-01

    The Rosetta Peptiderive protocol identifies, in a given structure of a protein-protein interaction, the linear polypeptide segment suggested to contribute most to binding energy. Interactions that feature a 'hot segment', a linear peptide with significant binding energy compared to that of the complex, may be amenable for inhibition and the peptide sequence and structure derived from the interaction provide a starting point for rational drug design. Here we present a web server for Peptiderive, which is incorporated within the ROSIE web interface for Rosetta protocols. A new feature of the protocol also evaluates whether derived peptides are good candidates for cyclization. Fast computation times and clear visualization allow users to quickly assess the interaction of interest. The Peptiderive server is available for free use at http://rosie.rosettacommons.org/peptiderive. PMID:27141963

  20. Understanding Protein-Protein Interactions Using Local Structural Features

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  1. 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/.

  2. 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.

  3. 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. PMID:26496636

  4. 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.

  5. Mapping Protein-Protein Interactions by Quantitative Proteomics

    DEFF Research Database (Denmark)

    Dengjel, Joern; Kratchmarova, Irina; Blagoev, Blagoy

    2010-01-01

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

  6. 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

  7. 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.

  8. 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.

  9. Estimating effective higher order terms in the post-Newtonian binding energy and gravitational-wave flux: Non-spinning compact binary inspiral

    CERN Document Server

    Kapadia, Shasvath J; Ajith, Parameswaran

    2016-01-01

    In the adiabatic post-Newtonian (PN) approximation, the phase evolution of gravitational waves (GWs) from inspiralling compact binaries in quasicircular orbits is computed by equating the change in binding energy with the GW flux. This energy balance equation can be solved in different ways, which result in multiple approximants of the PN waveforms. Due to the poor convergence of the PN expansion, these approximants tend to differ from each other during the late inspiral. Which of these approximants should be chosen as templates for detection and parameter estimation of GWs from inspiraling compact binaries is not obvious. In this paper, we present estimates of the effective higher order (beyond the currently available 4PN and 3.5PN) non-spinning terms in the PN expansion of the binding energy and the GW flux that minimize the difference of multiple PN approximants (TaylorT1, TaylorT2, TaylorT4, TaylorF2) with effective one body waveforms calibrated to numerical relativity (EOBNR). We show that PN approximant...

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

    OpenAIRE

    Lehne Benjamin; Schlitt Thomas

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Kalyan S. Chakrabarti

    2016-01-01

    Full Text Available Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection or are caused in response to ligand binding (induced fit. Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here, we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsin kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using nuclear magnetic resonance (NMR spectroscopy, stopped-flow kinetics, and isothermal titration calorimetry, we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Protein dynamics in free recoverin limits the overall rate of binding.

  12. 3D-interologs: an evolution database of physical protein- protein interactions across multiple genomes

    OpenAIRE

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

    2010-01-01

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

  13. Restricted Mobility of Conserved Residues in Protein-Protein Interfaces in Molecular Simulations

    OpenAIRE

    Yogurtcu, Osman N.; Erdemli, S. Bora; Nussinov, Ruth; Turkay, Metin; Keskin, Ozlem

    2008-01-01

    Conserved residues in protein-protein interfaces correlate with residue hot-spots. To obtain insight into their roles, we have studied their mobility. We have performed 39 explicit solvent simulations of 15 complexes and their monomers, with the interfaces varying in size, shape, and function. The dynamic behavior of conserved residues in unbound monomers illustrates significantly lower flexibility as compared to their environment, suggesting that already before binding they are constrained i...

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    Jillian L Blatti

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

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

    Directory of Open Access Journals (Sweden)

    Hongbo Zhu

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

  19. 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

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

    Directory of Open Access Journals (Sweden)

    Haasl Ryan J

    2005-11-01

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

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

    Science.gov (United States)

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

    2016-08-15

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

  2. 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.

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

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  4. 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.

  5. 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.

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

    DEFF Research Database (Denmark)

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

    2003-01-01

    Mass spectrometry-based proteomics can reveal protein-protein interactions on a large scale, but it has been difficult to separate background binding from functionally important interactions and still preserve weak binders. To investigate the epidermal growth factor receptor (EGFR) pathway, we...... and Src homologous and collagen (Shc) protein. We identified 228 proteins, of which 28 were selectively enriched upon stimulation. EGFR and Shc, which interact directly with the bait, had large differential ratios. Many signaling molecules specifically formed complexes with the activated EGFR-Shc, as did...... plectin, epiplakin, cytokeratin networks, histone H3, the glycosylphosphatidylinositol (GPI)-anchored molecule CD59, and two novel proteins. SILAC combined with modification-based affinity purification is a useful approach to detect specific and functional protein-protein interactions....

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

    Directory of Open Access Journals (Sweden)

    Kaare eTeilum

    2015-07-01

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

  8. 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.

  9. 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.

  10. 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.

  11. 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. .

  12. Protein-Protein Interfaces Mimics and Inhibitors Design for Cancers Caused by the disruption of HDAC-3

    Directory of Open Access Journals (Sweden)

    K. Rajaganapathy

    2015-03-01

    Full Text Available Protein-Protein interactions are deregulated or disrupted; it’s a new target for an anti-cancer agent development. In this work, the protein-protein interfaces mimics on a small molecule inhibitors of a molecular combinatorial ligand library (as a similar structure of protein-protein interfaces was designed for disruption of NcoRSIN3- HDAC3 complexes. And molecular docking study was performed with Schrodinger-Maestro-9.3.5-Version, the designed five Ligands was shown good binding interactions and their docking score was around -11.9, As a result of five ligand of a novel analogue is showing superior anti- cancerous histone deacetylase inhibitor caused by the disruption of HDAC-3.

  13. 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.

  14. Identifying Protein-Protein Interaction Sites Using Covering Algorithm

    OpenAIRE

    Jie Song; Jiaxing Cheng; Xiuquan Du

    2009-01-01

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

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

    OpenAIRE

    Leonardo Garma; Srayanta Mukherjee; Pralay Mitra; Yang Zhang

    2012-01-01

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

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

    OpenAIRE

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

    2009-01-01

    Understanding complex networks of protein-protein interactions (PPIs) is one of the foremost challenges of the post-genomic era. Due to the recent advances in experimental bio-technology, including yeast-2-hybrid (Y2H), tandem affinity purification (TAP) and other high-throughput methods for protein-protein interaction (PPI) detection, huge amounts of PPI network data are becoming available. Of major concern, however, are the levels of noise and incompleteness. For example, for Y2H screens, i...

  17. Reverse MAPPIT: screening for protein-protein interaction modifiers in mammalian cells.

    Science.gov (United States)

    Eyckerman, Sven; Lemmens, Irma; Catteeuw, Dominiek; Verhee, Annick; Vandekerckhove, Joel; Lievens, Sam; Tavernier, Jan

    2005-06-01

    Interactions between proteins are at the heart of the cellular machinery. It is therefore not surprising that altered interaction profiles caused by aberrant protein expression patterns or by the presence of mutations can trigger cellular dysfunction, eventually leading to disease. Moreover, many viral and bacterial pathogens rely on protein-protein interactions to exert their damaging effects. Interfering with such interactions is an obvious pharmaceutical goal, but detailed insights into the protein binding properties as well as efficient screening platforms are needed. In this report, we describe a cytokine receptor-based assay with a positive readout to screen for disrupters of designated protein-protein interactions in intact mammalian cells and evaluate this concept using polypeptides as well as small organic molecules. These reverse mammalian protein-protein interaction trap (MAPPIT) screens were developed to monitor interactions between the erythropoietin receptor (EpoR) and suppressors of cytokine signaling (SOCS) proteins, between FKBP12 and ALK4, and between MDM2 and p53. PMID:15908921

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

    Science.gov (United States)

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

    2010-08-01

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

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

    Science.gov (United States)

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

    2010-03-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

    Dukare, Sandeep; Klempnauer, Karl-Heinz

    2016-07-01

    The transcription factor c-Myb plays a key role in the control of proliferation and differentiation in hematopoietic progenitor cells and has been implicated in the development of leukemia and certain non-hematopoietic tumors. c-Myb activity is highly dependent on the interaction with the coactivator p300 which is mediated by the transactivation domain of c-Myb and the KIX domain of p300. We have previously observed that conservative valine-to-isoleucine amino acid substitutions in a conserved stretch of hydrophobic amino acids have a profound effect on Myb activity. Here, we have explored the function of the hydrophobic region as a mediator of protein-protein interactions. We show that the hydrophobic region facilitates Myb self-interaction and binding of the histone acetyl transferase Tip60, a previously identified Myb interacting protein. We show that these interactions are affected by the valine-to-isoleucine amino acid substitutions and suppress Myb activity by interfering with the interaction of Myb and the KIX domain of p300. Taken together, our work identifies the hydrophobic region in the Myb transactivation domain as a binding site for homo- and heteromeric protein interactions and leads to a picture of the c-Myb transactivation domain as a composite protein binding region that facilitates interdependent protein-protein interactions of Myb with regulatory proteins. PMID:27080133

  2. 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.

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

    Science.gov (United States)

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

    2015-06-01

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

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

    Science.gov (United States)

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

    2015-01-01

    Accurate identification of protein-protein interactions (PPI) is the key step in understanding proteins' biological functions, which are typically context-dependent. Many existing PPI predictors rely on aggregated features from protein sequences, however only a few methods exploit local information about specific residue contacts. In this work we present a two-stage machine learning approach for prediction of protein-protein interactions. We start with the carefully filtered data on protein complexes available for Saccharomyces cerevisiae in the Protein Data Bank (PDB) database. First, we build linear descriptions of interacting and non-interacting sequence segment pairs based on their inter-residue distances. Secondly, we train machine learning classifiers to predict binary segment interactions for any two short sequence fragments. The final prediction of the protein-protein interaction is done using the 2D matrix representation of all-against-all possible interacting sequence segments of both analysed proteins. The level-I predictor achieves 0.88 AUC for micro-scale, i.e., residue-level prediction. The level-II predictor improves the results further by a more complex learning paradigm. We perform 30-fold macro-scale, i.e., protein-level cross-validation experiment. The level-II predictor using PSIPRED-predicted secondary structure reaches 0.70 precision, 0.68 recall, and 0.70 AUC, whereas other popular methods provide results below 0.6 threshold (recall, precision, AUC). Our results demonstrate that multi-scale sequence features aggregation procedure is able to improve the machine learning results by more than 10% as compared to other sequence representations. Prepared datasets and source code for our experimental pipeline are freely available for download from: http://zubekj.github.io/mlppi/ (open source Python implementation, OS independent). PMID:26157620

  5. Mapping the Protein-Protein Interactome Networks Using Yeast Two-Hybrid Screens.

    Science.gov (United States)

    Rajagopala, Seesandra Venkatappa

    2015-01-01

    The yeast two-hybrid system (Y2H) is a powerful method to identify binary protein-protein interactions in vivo. Here we describe Y2H screening strategies that use defined libraries of open reading frames (ORFs) and cDNA libraries. The array-based Y2H system is well suited for interactome studies of small genomes with an existing ORFeome clones preferentially in a recombination based cloning system. For large genomes, pooled library screening followed by Y2H pairwise retests may be more efficient in terms of time and resources, but multiple sampling is necessary to ensure comprehensive screening. While the Y2H false positives can be efficiently reduced by using built-in controls, retesting, and evaluation of background activation; implementing the multiple variants of the Y2H vector systems is essential to reduce the false negatives and ensure comprehensive coverage of an interactome. PMID:26621469

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Rational disruption of the oligomerization of the mini-ferritin E. coli DPS through protein-protein interface mutation

    OpenAIRE

    Zhang, Yu; Fu, Jing; Chee, Sze Y; Ang, Emmiline X W; Orner, Brendan P.

    2011-01-01

    DNA-binding protein from starved cells (DPS), a mini-ferritin capable of self-assembling into a 12-meric nano-cage, was chosen as the basis for an alanine-shaving mutagenesis study to investigate the importance of key amino acid residues, located at symmetry-related protein-protein interfaces, in controlling protein stability and self-assembly. Nine mutants were designed through simple inspection, synthesized, and subjected to transmission electron microscopy, circular dichroism, size exclusi...

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

    OpenAIRE

    Zhe Zhang; Schindler, Christina E. M.; Lange, Oliver F.; Martin Zacharias

    2015-01-01

    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 Hamilto...

  13. Clostridium difficile binary toxin CDT

    OpenAIRE

    Gerding, Dale N.; Johnson, Stuart; Rupnik, Maja; Aktories, Klaus

    2013-01-01

    Binary toxin (CDT) is frequently observed in Clostridium difficile strains associated with increased severity of C. difficile infection (CDI). CDT belongs to the family of binary ADP-ribosylating toxins consisting of two separate toxin components: CDTa, the enzymatic ADP-ribosyltransferase which modifies actin, and CDTb which binds to host cells and translocates CDTa into the cytosol. CDTb is activated by serine proteases and binds to lipolysis stimulated lipoprotein receptor. ADP-ribosylatio...

  14. 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...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-08-31

    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

  16. 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

  17. Motif-Driven Design of Protein-Protein Interfaces.

    Science.gov (United States)

    Silva, Daniel-Adriano; Correia, Bruno E; Procko, Erik

    2016-01-01

    Protein-protein interfaces regulate many critical processes for cellular function. The ability to accurately control and regulate these molecular interactions is of major interest for biomedical and synthetic biology applications, as well as to address fundamental biological questions. In recent years, computational protein design has emerged as a tool for designing novel protein-protein interactions with functional relevance. Although attractive, these computational tools carry a steep learning curve. In order to make some of these methods more accessible, we present detailed descriptions and examples of ROSETTA computational protocols for the design of functional protein binders using seeded protein interface design. In these protocols, a motif of known structure that interacts with the target site is grafted into a scaffold protein, followed by design of the surrounding interaction surface. PMID:27094298

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

    Science.gov (United States)

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

    2015-01-01

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

  19. Sentence Simplification Aids Protein-Protein Interaction Extraction

    OpenAIRE

    Jonnalagadda, Siddhartha; Gonzalez, Graciela

    2010-01-01

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

  20. Protein-Protein Interaction Detection: Methods and Analysis

    OpenAIRE

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

    2014-01-01

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

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

    OpenAIRE

    Nepusz, Tamás; Yu, Haiyuan; Paccanaro, Alberto

    2012-01-01

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

  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. 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.

  4. Report on the research conducted under the funding of the Sloan foundation postdoctoral fellowship in Computational Molecular Biology [Systematic study of protein-protein complexes] Final report

    Energy Technology Data Exchange (ETDEWEB)

    Sheinerman, Felix

    2001-06-01

    A central question in molecular biology is what structural features are common at protein-protein interfaces and what energetic factors define the affinity and specificity of protein-protein association. Analysis of structural and mutational data on protein-protein interfaces revealed that protein-protein interfaces of different functional classes contain many more energetically important charged and polar residues than was previously thought. Since, in the context of protein folding studies, polar interactions are believed to destabilize the folded proteins, this observation raised the question as to the forces that determine the stability of protein complexes. To investigate this issue in detail, the authors developed a number of partitioning schemes that allowed them to investigate the role of selected residues, ion pairs, and networks of polar interactions in protein-protein association. The methods developed were applied to the analysis of four different protein-protein interfaces: the ribonuclease barnase and its inhibitor barstar, the human growth hormone and its receptor, subtype N9 influenze virus neuraminidase and NC41 antibody, and the Ras Binding Domain of kinase cRaf and a Ras homologue Rap1A. The calculations revealed a surprising variability in how polar interactions affect the stability of different complexes. The finding that positions of charged and polar residues on protein-protein interfaces are optimized with respect to electrostatic interactions suggests that this property can be employed for the discrimination between native conformations and trial complexes generated by a docking algorithm. Analysis indicated the presence of SH2 domains in Janus family of non-receptor protein tyrosine kinases.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

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

    Science.gov (United States)

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

    2012-08-01

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

  12. 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.

  13. 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.

  14. 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.

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

    Science.gov (United States)

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

    2016-08-16

    Capillary electrophoresis (CE) has been identified as a useful platform for detecting, quantifying, and screening for modulators of protein-protein interactions (PPIs). In this method, one protein binding partner is labeled with a fluorophore, the protein binding partners are mixed, and then, the complex is separated from free protein to allow direct determination of bound to free ratios. Although it possesses many advantages for PPI studies, the method is limited by the need to have separation conditions that both prevent protein adsorption to capillary and maintain protein interactions during the separation. In this work, we use protein cross-linking capillary electrophoresis (PXCE) to overcome this limitation. In PXCE, the proteins are cross-linked under binding conditions and then separated. This approach eliminates the need to maintain noncovalent interactions during electrophoresis and facilitates method development. We report PXCE methods for an antibody-antigen interaction and heterodimer and homodimer heat shock protein complexes. Complexes are cross-linked by short treatments with formaldehyde after reaching binding equilibrium. Cross-linked complexes are separated by electrophoretic mobility using free solution CE or by size using sieving electrophoresis of SDS complexes. The method gives good quantitative results; e.g., a lysozyme-antibody interaction was found to have Kd = 24 ± 3 nM by PXCE and Kd = 17 ± 2 nM using isothermal calorimetry (ITC). Heat shock protein 70 (Hsp70) in complex with bcl2 associated athanogene 3 (Bag3) was found to have Kd = 25 ± 5 nM by PXCE which agrees with Kd values reported without cross-linking. Hsp70-Bag3 binding site mutants and small molecule inhibitors of Hsp70-Bag3 were characterized by PXCE with good agreement to inhibitory constants and IC50 values obtained by a bead-based flow cytometry protein interaction assay (FCPIA). PXCE allows rapid method development for quantitative analysis of PPIs. PMID:27434096

  16. 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.

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

    Science.gov (United States)

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

    2015-10-01

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

  18. In vivo Biotinylation Based Method for the Study of Protein-Protein Proximity in Eukaryotic Cells

    Directory of Open Access Journals (Sweden)

    Arman Kulyyassov

    2014-01-01

    Full Text Available Introduction: The spatiotemporal order plays an important role in cell functioning and is affected in many pathologies such as cancer and neurodegenerative diseases. One of the ultimate goals of molecular biology is reconstruction of the spatiotemporal structure of a living cell at the molecular level. This task includes determination of proximities between different molecular components in the cell and monitoring their time- and physiological state-dependent changes. In many cases, proximity between macromolecules arises due to their interactions; however, the contribution of dynamic self-organization in generation of spatiotemporal order is emerging as another viable possibility. Specifically, in proteomics, this implies that the detection of protein-protein proximity is a more general task than gaining information about physical interactions between proteins, as it could detail aspects of spatial order in vivo that are challenging to reconstitute in binding experiments in vitro. Methods: In this work, we have developed a method of monitoring protein-protein proximity in vivo. For this purpose, the BirA was fused to one of the interaction partners, whereas the BAP was modified to make the detection of its biotinylation possible by mass spectrometry. Results: Using several experimental systems, we showed that the biotinylation is interaction dependent. In addition, we demonstrated that BAP domains with different primary amino acid structures and thus with different molecular weights can be used in the same experiment, providing the possibility of multiplexing. Alternatively to the changes in primary amino acid structure, the stable isotope format can also be used, providing another way to perform multiplexing experiments. Finally, we also demonstrated that our system could help to overcome another limitation of current methodologies to detect protein-protein proximity. For example, one can follow the state of a protein of interest at a defined

  19. Identification of hot regions in protein-protein interactions by sequential pattern mining

    Directory of Open Access Journals (Sweden)

    Lin Chien-Chieh

    2007-05-01

    Full Text Available Abstract Background Identification of protein interacting sites is an important task in computational molecular biology. As more and more protein sequences are deposited without available structural information, it is strongly desirable to predict protein binding regions by their sequences alone. This paper presents a pattern mining approach to tackle this problem. It is observed that a functional region of protein structures usually consists of several peptide segments linked with large wildcard regions. Thus, the proposed mining technology considers large irregular gaps when growing patterns, in order to find the residues that are simultaneously conserved but largely separated on the sequences. A derived pattern is called a cluster-like pattern since the discovered conserved residues are always grouped into several blocks, which each corresponds to a local conserved region on the protein sequence. Results The experiments conducted in this work demonstrate that the derived long patterns automatically discover the important residues that form one or several hot regions of protein-protein interactions. The methodology is evaluated by conducting experiments on the web server MAGIIC-PRO based on a well known benchmark containing 220 protein chains from 72 distinct complexes. Among the tested 218 proteins, there are 900 sequential blocks discovered, 4.25 blocks per protein chain on average. About 92% of the derived blocks are observed to be clustered in space with at least one of the other blocks, and about 66% of the blocks are found to be near the interface of protein-protein interactions. It is summarized that for about 83% of the tested proteins, at least two interacting blocks can be discovered by this approach. Conclusion This work aims to demonstrate that the important residues associated with the interface of protein-protein interactions may be automatically discovered by sequential pattern mining. The detected regions possess high

  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. Protein-protein interactions in DNA mismatch repair.

    Science.gov (United States)

    Friedhoff, Peter; Li, Pingping; Gotthardt, Julia

    2016-02-01

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

  2. 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.

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

    Science.gov (United States)

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

    2016-04-01

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

  5. GalaxyRefineComplex: Refinement of protein-protein complex model structures driven by interface repacking.

    Science.gov (United States)

    Heo, Lim; Lee, Hasup; Seok, Chaok

    2016-01-01

    Protein-protein docking methods have been widely used to gain an atomic-level understanding of protein interactions. However, docking methods that employ low-resolution energy functions are popular because of computational efficiency. Low-resolution docking tends to generate protein complex structures that are not fully optimized. GalaxyRefineComplex takes such low-resolution docking structures and refines them to improve model accuracy in terms of both interface contact and inter-protein orientation. This refinement method allows flexibility at the protein interface and in the overall docking structure to capture conformational changes that occur upon binding. Symmetric refinement is also provided for symmetric homo-complexes. This method was validated by refining models produced by available docking programs, including ZDOCK and M-ZDOCK, and was successfully applied to CAPRI targets in a blind fashion. An example of using the refinement method with an existing docking method for ligand binding mode prediction of a drug target is also presented. A web server that implements the method is freely available at http://galaxy.seoklab.org/refinecomplex. PMID:27535582

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

    OpenAIRE

    Peng Liu; Lei Yang; Daming Shi; Xianglong Tang

    2015-01-01

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

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

    OpenAIRE

    Maroun, M; Aronheim, A

    1999-01-01

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

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

    Science.gov (United States)

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

    2015-10-01

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

  10. Modularity detection in protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Narayanan Tejaswini

    2011-12-01

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

  11. 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

  12. Evolution of binary stars in multiple-population globular clusters - II. Compact binaries

    Science.gov (United States)

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

    2016-04-01

    We present the results of a survey of N-body simulations aimed at exploring the evolution of compact binaries in multiple-population globular clusters. We show that as a consequence of the initial differences in the structural properties of the first-generation (FG) and the second-generation (SG) populations and the effects of dynamical processes on binary stars, the SG binary fraction decreases more rapidly than that of the FG population. The difference between the FG and SG binary fraction is qualitatively similar to but quantitatively smaller than that found for wider binaries in our previous investigations. The evolution of the radial variation of the binary fraction is driven by the interplay between binary segregation, ionization and ejection. Ionization and ejection counteract in part the effects of mass segregation but for compact binaries the effects of segregation dominate and the inner binary fraction increases during the cluster evolution. We explore the variation of the difference between the FG and the SG binary fraction with the distance from the cluster centre and its dependence on the binary binding energy and cluster structural parameters. The difference between the binary fraction in the FG and the SG populations found in our simulations is consistent with the results of observational studies finding a smaller binary fraction in the SG population.

  13. Binary Planets

    Science.gov (United States)

    Ryan, Keegan; Nakajima, Miki; Stevenson, David J.

    2014-11-01

    Can a bound pair of similar mass terrestrial planets exist? We are interested here in bodies with a mass ratio of ~ 3:1 or less (so Pluto/Charon or Earth/Moon do not qualify) and we do not regard the absence of any such discoveries in the Kepler data set to be significant since the tidal decay and merger of a close binary is prohibitively fast well inside of 1AU. SPH simulations of equal mass “Earths” were carried out to seek an answer to this question, assuming encounters that were only slightly more energetic than parabolic (zero energy). We were interested in whether the collision or near collision of two similar mass bodies would lead to a binary in which the two bodies remain largely intact, effectively a tidal capture hypothesis though with the tidal distortion being very large. Necessarily, the angular momentum of such an encounter will lead to bodies separated by only a few planetary radii if capture occurs. Consistent with previous work, mostly by Canup, we find that most impacts are disruptive, leading to a dominant mass body surrounded by a disk from which a secondary forms whose mass is small compared to the primary, hence not a binary planet by our adopted definition. However, larger impact parameter “kissing” collisions were found to produce binaries because the dissipation upon first encounter was sufficient to provide a bound orbit that was then rung down by tides to an end state where the planets are only a few planetary radii apart. The long computational times for these simulation make it difficult to fully map the phase space of encounters for which this outcome is likely but the indications are that the probability is not vanishingly small and since planetary encounters are a plausible part of planet formation, we expect binary planets to exist and be a non-negligible fraction of the larger orbital radius exoplanets awaiting discovery.

  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. 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...

  16. 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.

  17. 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.

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

    Science.gov (United States)

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

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Zheng Sun

    2014-01-01

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

  20. 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

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

    Science.gov (United States)

    Witherow, D. Scott; Carson, Sue

    2011-01-01

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

  2. 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. ...

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

    Directory of Open Access Journals (Sweden)

    Jian-Feng Li

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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  6. 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

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

    Directory of Open Access Journals (Sweden)

    Min He

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

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

    Science.gov (United States)

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

    2016-08-19

    The interaction between the cell-cell adhesion proteins CD2 and CD58 plays a crucial role in lymphocyte recruitment to inflammatory sites, and inhibitors of this interaction have potential as immunomodulatory drugs in autoimmune diseases. Peptides from the CD2 adhesion domain were designed to inhibit CD2:CD58 interactions. To improve the stability of the peptides, β-sheet epitopes from the CD2 region implicated in CD58 recognition were grafted into the cyclic peptide frameworks of sunflower trypsin inhibitor and rhesus theta defensin. The designed multicyclic peptides were evaluated for their ability to modulate cell-cell interactions in three different cell adhesion assays, with one candidate, SFTI-a, showing potent activity in the nanomolar range (IC50: 51 nM). This peptide also suppresses the immune responses in T cells obtained from mice that exhibit the autoimmune disease rheumatoid arthritis. SFTI-a was resistant to thermal denaturation, as judged by circular dichroism spectroscopy and mass spectrometry, and had a half-life of ∼24 h in human serum. Binding of this peptide to CD58 was predicted by molecular docking studies and experimentally confirmed by surface plasmon resonance experiments. Our results suggest that cyclic peptides from natural sources are promising scaffolds for modulating protein-protein interactions that are typically difficult to target with small-molecule compounds. PMID:27337048

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

    Directory of Open Access Journals (Sweden)

    Lee MG

    2001-07-01

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

  10. Targeting protein-protein interactions for parasite control.

    Directory of Open Access Journals (Sweden)

    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

  11. BISC: binary subcomplexes in proteins database.

    Science.gov (United States)

    Juettemann, Thomas; Gerloff, Dietlind L

    2011-01-01

    Binary subcomplexes in proteins database (BISC) is a new protein-protein interaction (PPI) database linking up the two communities most active in their characterization: structural biology and functional genomics researchers. The BISC resource offers users (i) a structural perspective and related information about binary subcomplexes (i.e. physical direct interactions between proteins) that are either structurally characterized or modellable entries in the main functional genomics PPI databases BioGRID, IntAct and HPRD; (ii) selected web services to further investigate the validity of postulated PPI by inspection of their hypothetical modelled interfaces. Among other uses we envision that this resource can help identify possible false positive PPI in current database records. BISC is freely available at http://bisc.cse.ucsc.edu. PMID:21081561

  12. SLIDER: Mining correlated motifs in protein-protein interaction networks

    NARCIS (Netherlands)

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

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Davis Melissa J

    2009-02-01

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

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

    Science.gov (United States)

    Bier, David; Bartel, Maria; Sies, Katharina; Halbach, Sebastian; Higuchi, Yusuke; Haranosono, Yu; Brummer, Tilman; Kato, Nobuo; Ottmann, Christian

    2016-04-19

    Small-molecule modulation of protein-protein interactions (PPIs) is one of the most promising new areas in drug discovery. In the vast majority of cases only inhibition or disruption of PPIs is realized, whereas the complementary strategy of targeted stabilization of PPIs is clearly under-represented. Here, we report the example of a semi-synthetic natural product derivative--ISIR-005--that stabilizes the cancer-relevant interaction of the adaptor protein 14-3-3 and Gab2. The crystal structure of ISIR-005 in complex with 14-3-3 and the binding motif of Gab2 comprising two phosphorylation sites (Gab2pS210pT391) showed how the stabilizing molecule binds to the rim-of-the-interface of the protein complex. Only in the direct vicinity of 14-3-3/Gab2pT391 site is a pre-formed pocket occupied by ISIR-005; binding of the Gab2pS210 motif to 14-3-3 does not create an interface pocket suitable for the molecule. Accordingly, ISIR-005 only stabilizes the binding of the Gab2pT391 but not the Gab2pS210 site. This study represents structural and biochemical proof of the druggability of the 14-3-3/Gab2 PPI interface with important implications for the development of PPI stabilizers. PMID:26644359

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-07-01

    Intercellular protein-protein interactions (PPIs) enable communication between cells in diverse biological processes, including cell proliferation, immune responses, infection, and synaptic transmission, but they are challenging to visualize because existing techniques have insufficient sensitivity and/or specificity. Here we report a split horseradish peroxidase (sHRP) as a sensitive and specific tool for the detection of intercellular PPIs. The two sHRP fragments, engineered through screening of 17 cut sites in HRP followed by directed evolution, reconstitute into an active form when driven together by an intercellular PPI, producing bright fluorescence or contrast for electron microscopy. Fusing the sHRP fragments to the proteins neurexin (NRX) and neuroligin (NLG), which bind each other across the synaptic cleft, enabled sensitive visualization of synapses between specific sets of neurons, including two classes of synapses in the mouse visual system. sHRP should be widely applicable to studying mechanisms of communication between a variety of cell types. PMID:27240195

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Zhang, Zhe; Schindler, Christina E M; Lange, Oliver F; Zacharias, Martin

    2015-01-01

    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. PMID:26053419

  20. 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.

    A new series of metal complexes of Cd(II), Cu(II), Ni(II) and Co(III) with Schiff base ligand, H2L, 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 1H 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.

  1. The Protein-Protein Interface Evolution Acts in a Similar Way to Antibody Affinity Maturation*

    OpenAIRE

    Li, Bohua; Zhao, Lei; Wang, Chong; Guo, Huaizu; Wu, Lan; Zhang, Xunming; Qian, Weizhu; Wang, Hao; Guo, Yajun

    2009-01-01

    Understanding the evolutionary mechanism that acts at the interfaces of protein-protein complexes is a fundamental issue with high interest for delineating the macromolecular complexes and networks responsible for regulation and complexity in biological systems. To investigate whether the evolution of protein-protein interface acts in a similar way as antibody affinity maturation, we incorporated evolutionary information derived from antibody affinity maturation with common simulation techniq...

  2. 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.

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

    OpenAIRE

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

    2013-01-01

    While protein-surface interactions have been widely studied, relatively little is understood at this time regarding how protein-surface interaction effects are influenced by protein-protein interactions and how these effects combine with the internal stability of a protein to influence its adsorbed-state structure and bioactivity. The objectives of this study were to develop a method to study these combined effects under widely varying protein-protein interaction conditions using hen egg-whit...

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

    OpenAIRE

    Sun Zhirong; Liu Ke; Chen Hu; Zhang Song

    2009-01-01

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

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

    OpenAIRE

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

    2014-01-01

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

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

    OpenAIRE

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

    2011-01-01

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

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

    OpenAIRE

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

    2013-01-01

    Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on th...

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. FUNCTIONAL INTERACTOMICS: DETERMINING THE ROLES PLAYED BY MEMBERS OF THE POPULAR BIOMASS PROTEIN-PROTEIN INTERACTOME

    Energy Technology Data Exchange (ETDEWEB)

    Beers, Eric; Brunner, Amy; Helm, Richard

    2015-07-31

    Proteins are molecular machines that are required for nearly all biological functions based on interactions with other molecules such as carbohydrates, lipids, other low molecular weight molecules, nucleic acids and other proteins. Here we map protein-protein interactions relevant to biomass production by focusing on proteins coexpressed in poplar xylem, the site of the majority of lignocellulose synthesis and hence biomass accumulation in poplar. Work proposed here will yield novel biological and bioinformatic resources that can benefit a variety of ongoing and future projects focusing on plant biomass/cell wall biology. The protein-protein interaction map that results from these studies will comprise an advanced view of protein-protein interactions in a model biomass tissue. Results will be made available to the biomass research community to serve as tools for developing new strategies for altering biomass quality and quantity.

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

    Science.gov (United States)

    Koshiba, Takumi

    2015-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

    Freire, Ernesto

    2010-03-01

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

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

    Science.gov (United States)

    Cau, Ylenia; Fiorillo, Annarita; Mori, Mattia; Ilari, Andrea; Botta, Maurizo; Lalle, Marco

    2015-12-28

    Giardiasis is a gastrointestinal diarrheal illness caused by the protozoan parasite Giardia duodenalis, which affects annually over 200 million people worldwide. The limited antigiardial drug arsenal and the emergence of clinical cases refractory to standard treatments dictate the need for new chemotherapeutics. The 14-3-3 family of regulatory proteins, extensively involved in protein-protein interactions (PPIs) with pSer/pThr clients, represents a highly promising target. Despite homology with human counterparts, the single 14-3-3 of G. duodenalis (g14-3-3) is characterized by a constitutive phosphorylation in a region critical for target binding, thus affecting the function and the conformation of g14-3-3/clients interaction. However, to approach the design of specific small molecule modulators of g14-3-3 PPIs, structural elucidations are required. Here, we present a detailed computational and crystallographic study exploring the implications of g14-3-3 phosphorylation on protein structure and target binding. Self-Guided Langevin Dynamics and classical molecular dynamics simulations show that phosphorylation affects locally and globally g14-3-3 conformation, inducing a structural rearrangement more suitable for target binding. Profitable features for g14-3-3/clients interaction were highlighted using a hydrophobicity-based descriptor to characterize g14-3-3 client peptides. Finally, the X-ray structure of g14-3-3 in complex with a mode-1 prototype phosphopeptide was solved and combined with structure-based simulations to identify molecular features relevant for clients binding to g14-3-3. The data presented herein provide a further and structural understanding of g14-3-3 features and set the basis for drug design studies. PMID:26551337

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

    Science.gov (United States)

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

    2014-03-20

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

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. Rational design of small-molecule inhibitors for β-catenin/T-cell factor protein-protein interactions by bioisostere replacement.

    Science.gov (United States)

    Yu, Binxun; Huang, Zheng; Zhang, Min; Dillard, Darren R; Ji, Haitao

    2013-03-15

    A new hot spot-based design strategy using bioisostere replacement is reported to rationally design nonpeptidic small-molecule inhibitors for protein-protein interactions. This method is applied to design new potent inhibitors for β-catenin/T-cell factor (Tcf) interactions. Three hot spot regions of Tcf for binding to β-catenin were quantitatively evaluated; the key binding elements around K435 and K508 of β-catenin were derived; a bioisostere library was used to generate new fragments that can match the proposed critical binding elements. The most potent inhibitor, with a molecular weight of 230, has a Kd of 0.531 μM for binding to β-catenin and a Ki of 3.14 μM to completely disrupt β-catenin/Tcf interactions. The binding mode of the designed inhibitors was validated by the site-directed mutagenesis and structure-activity relationship (SAR) studies. This study provides a new approach to design new small-molecule inhibitors that bind to β-catenin and effectively disrupt β-catenin/Tcf interactions specific for canonical Wnt signaling. PMID:23272635

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  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. 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

  13. 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

    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...

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

    OpenAIRE

    Nazar Zaki; Elfadil A. Mohamed; Antonio Mora

    2015-01-01

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

  15. 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

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

    Science.gov (United States)

    Zhang, Shu-Bo; Tang, Qiang-Rong

    2016-07-21

    Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction. PMID:27117309

  17. Computational Study for Protein-Protein Docking Using Global Optimization and Empirical Potentials

    Directory of Open Access Journals (Sweden)

    Kyoungrim Lee

    2008-01-01

    Full Text Available Protein-protein interactions are important for biochemical processes in biological systems. The 3D structure of the macromolecular complex resulting from the protein-protein association is a very useful source to understand its specific functions. This work focuses on computational study for protein-protein docking, where the individually crystallized structures of interacting proteins are treated as rigid, and the conformational space generated by the two interacting proteins is explored extensively. The energy function consists of intermolecular electrostatic potential, desolvation free energy represented by empirical contact potential, and simple repulsive energy terms. The conformational space is six dimensional, represented by translational vectors and rotational angles formed between two interacting proteins. The conformational sampling is carried out by the search algorithms such as simulated annealing (SA, conformational space annealing (CSA, and CSA combined with SA simulations (combined CSA/SA. Benchmark tests are performed on a set of 18 protein-protein complexes selected from various protein families to examine feasibility of these search methods coupled with the energy function above for protein docking study.

  18. 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

  19. 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.

  20. 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.

  1. Bound water at protein-protein interfaces: partners, roles and hydrophobic bubbles as a conserved motif.

    Directory of Open Access Journals (Sweden)

    Mostafa H Ahmed

    Full Text Available BACKGROUND: There is a great interest in understanding and exploiting protein-protein associations as new routes for treating human disease. However, these associations are difficult to structurally characterize or model although the number of X-ray structures for protein-protein complexes is expanding. One feature of these complexes that has received little attention is the role of water molecules in the interfacial region. METHODOLOGY: A data set of 4741 water molecules abstracted from 179 high-resolution (≤ 2.30 Å X-ray crystal structures of protein-protein complexes was analyzed with a suite of modeling tools based on the HINT forcefield and hydrogen-bonding geometry. A metric termed Relevance was used to classify the general roles of the water molecules. RESULTS: The water molecules were found to be involved in: a (bridging interactions with both proteins (21%, b favorable interactions with only one protein (53%, and c no interactions with either protein (26%. This trend is shown to be independent of the crystallographic resolution. Interactions with residue backbones are consistent for all classes and account for 21.5% of all interactions. Interactions with polar residues are significantly more common for the first group and interactions with non-polar residues dominate the last group. Waters interacting with both proteins stabilize on average the proteins' interaction (-0.46 kcal mol(-1, but the overall average contribution of a single water to the protein-protein interaction energy is unfavorable (+0.03 kcal mol(-1. Analysis of the waters without favorable interactions with either protein suggests that this is a conserved phenomenon: 42% of these waters have SASA ≤ 10 Å(2 and are thus largely buried, and 69% of these are within predominantly hydrophobic environments or "hydrophobic bubbles". Such water molecules may have an important biological purpose in mediating protein-protein interactions.

  2. 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.

  3. PHOEBE: PHysics Of Eclipsing BinariEs

    Science.gov (United States)

    Prsa, Andrej; Matijevic, Gal; Latkovic, Olivera; Vilardell, Francesc; Wils, Patrick

    2011-06-01

    PHOEBE (PHysics Of Eclipsing BinariEs) is a modeling package for eclipsing binary stars, built on top of the widely used WD program (Wilson & Devinney 1971). This introductory paper overviews most important scientific extensions (incorporating observational spectra of eclipsing binaries into the solution-seeking process, extracting individual temperatures from observed color indices, main-sequence constraining and proper treatment of the reddening), numerical innovations (suggested improvements to WD's Differential Corrections method, the new Nelder & Mead's downhill Simplex method) and technical aspects (back-end scripter structure, graphical user interface). While PHOEBE retains 100% WD compatibility, its add-ons are a powerful way to enhance WD by encompassing even more physics and solution reliability.

  4. 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.

  5. 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/.

  6. A computational system for modelling flexible protein-protein and protein-DNA docking.

    Science.gov (United States)

    Sternberg, M J; Aloy, P; Gabb, H A; Jackson, R M; Moont, G; Querol, E; Aviles, F X

    1998-01-01

    A computational system is described that predicts the structure of protein/protein and protein/DNA complexes starting from unbound coordinate sets. The approach is (i) a global search with rigid-body docking for complexes with shape complementarity and favourable electrostatics; (ii) use of distance constraints from experimental (or predicted) knowledge of critical residues; (iii) use of pair potential to screen docked complexes and (iv) refinement and further screening by protein-side chain optimisation and interfacial energy minimisation. The system has been applied to model ten protein/protein and eight protein-repressor/DNA (steps i to iii only) complexes. In general a few complexes, one of which is close to the true structure, can be generated. PMID:9783224

  7. Structural basis of a rationally rewired protein-protein interface critical to bacterial signaling.

    Science.gov (United States)

    Podgornaia, Anna I; Casino, Patricia; Marina, Alberto; Laub, Michael T

    2013-09-01

    Two-component signal transduction systems typically involve a sensor histidine kinase that specifically phosphorylates a single, cognate response regulator. This protein-protein interaction relies on molecular recognition via a small set of residues in each protein. To better understand how these residues determine the specificity of kinase-substrate interactions, we rationally rewired the interaction interface of a Thermotoga maritima two-component system, HK853-RR468, to match that found in a different two-component system, Escherichia coli PhoR-PhoB. The rewired proteins interacted robustly with each other, but no longer interacted with the parent proteins. Analysis of the crystal structures of the wild-type and mutant protein complexes and a systematic mutagenesis study reveal how individual mutations contribute to the rewiring of interaction specificity. Our approach and conclusions have implications for studies of other protein-protein interactions and protein evolution and for the design of novel protein interfaces. PMID:23954504

  8. 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.

  9. 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.

  10. 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.

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

    Science.gov (United States)

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

    1999-04-01

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

  12. 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

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

    OpenAIRE

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

    2011-01-01

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

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

    OpenAIRE

    Panstruga Ralph; Lahaye Thomas; Bhat Riyaz A

    2006-01-01

    Abstract Non-invasive fluorophore-based protein interaction assays like fluorescence resonance energy transfer (FRET) and bimolecular fluorescence complementation (BiFC, also referred to as "split YFP") have been proven invaluable tools to study protein-protein interactions in living cells. Both methods are now frequently used in the plant sciences and are likely to develop into standard techniques for the identification, verification and in-depth analysis of polypeptide interactions. In this...

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

    OpenAIRE

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

    2012-01-01

    We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the t...

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

    OpenAIRE

    Zhao Yiqiang; Mooney Sean D

    2012-01-01

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

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

    OpenAIRE

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

    2008-01-01

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

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

    OpenAIRE

    Tan Kai; Kim Jongkwang

    2010-01-01

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

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

    OpenAIRE

    Ru Shen; Xiaosheng Wang; Chittibabu Guda

    2015-01-01

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

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

    OpenAIRE

    Xiaomin Wang; Zhengzhi Wang; Jun Ye

    2011-01-01

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

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

    OpenAIRE

    Best, Christoph; Zimmer, Ralf; Apostolakis, Joannis

    2005-01-01

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

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

    OpenAIRE

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

    2011-01-01

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

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

    OpenAIRE

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

    2011-01-01

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

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

    OpenAIRE

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

    2013-01-01

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

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

    OpenAIRE

    Lei Yang; Xianglong Tang

    2014-01-01

    Cliques (maximal complete subnets) in protein-protein interaction (PPI) network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based m...

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

    OpenAIRE

    Gillis, Jesse; Ballouz, Sara; Pavlidis, Paul

    2014-01-01

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

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

    OpenAIRE

    Jiang Jonathan Q; Wu Maoying

    2012-01-01

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

  8. PPIRank - an advanced method for ranking protein-protein interations in TAP/MS data

    OpenAIRE

    Sun, Xiaoyun; Hong, Pengyu; Kulkarni, Meghana; Kwon, Young; Perrimon, Norbert

    2013-01-01

    Background: Tandem affinity purification coupled with mass-spectrometry (TAP/MS) analysis is a popular method for the identification of novel endogenous protein-protein interactions (PPIs) in large-scale. Computational analysis of TAP/MS data is a critical step, particularly for high-throughput datasets, yet it remains challenging due to the noisy nature of TAP/MS data. Results: We investigated several major TAP/MS data analysis methods for identifying PPIs, and developed an advanced method, ...

  9. 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.

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

    OpenAIRE

    Zohar Itzhaki

    2011-01-01

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

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

    OpenAIRE

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

    2012-01-01

    Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP) and thioesterase (TE) govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr) as a model, a structural simulation of docking...

  12. 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.

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

    Science.gov (United States)

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

    2004-04-01

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

  14. 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.

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

    Directory of Open Access Journals (Sweden)

    Jaume Torres

    2015-06-01

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

  16. 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.

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

    Science.gov (United States)

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

    2014-05-01

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

  19. 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

  20. 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.

  1. 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.

  2. Painting proteins blue: β-(1-azulenyl)-L-alanine as a probe for studying protein-protein interactions.

    Science.gov (United States)

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

    2013-01-18

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

  3. 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...

  4. 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.

  5. 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

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

    OpenAIRE

    Nielsen Jens; Jouhten Paula; Nandy Subir K

    2010-01-01

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

  7. 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

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

    Science.gov (United States)

    Cole, Daniel J; Rajendra, Eeson; Roberts-Thomson, Meredith; Hardwick, Bryn; McKenzie, Grahame J; Payne, Mike C; Venkitaraman, Ashok R; Skylaris, Chris-Kriton

    2011-07-01

    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 experimental tools for the

  9. 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

  10. 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

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

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    Sony Malhotra

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

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

    Science.gov (United States)

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

    2015-10-01

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

  13. 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.

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

    Directory of Open Access Journals (Sweden)

    Panstruga Ralph

    2006-06-01

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

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

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

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

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

    OpenAIRE

    Cuendet, Michel A.; Michielin, Olivier

    2008-01-01

    We present a novel steered molecular dynamics scheme to induce the dissociation of large protein-protein complexes. We apply this scheme to study the interaction of a T cell receptor (TCR) with a major histocompatibility complex (MHC) presenting a peptide (p). Two TCR-pMHC complexes are considered, which only differ by the mutation of a single amino acid on the peptide; one is a strong agonist that produces T cell activation in vivo, while the other is an antagonist. We investigate the intera...

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

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    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

  18. Binaries migrating in a gaseous disk: Where are the Galactic center binaries?

    CERN Document Server

    Baruteau, C; Lin, D N C

    2010-01-01

    The massive stars in the Galactic center inner arcsecond share analogous properties with the so-called Hot Jupiters. Most of these young stars have highly eccentric orbits, and were probably not formed in-situ. It has been proposed that these stars acquired their current orbits from the tidal disruption of compact massive binaries scattered toward the proximity of the central supermassive black hole. Assuming a binary star formed in a thin gaseous disk beyond 0.1 pc from the central object, we investigate the relevance of disk-satellite interactions to harden the binding energy of the binary, and to drive its inward migration. A massive, equal-mass binary star is found to become more tightly wound as it migrates inwards toward the central black hole. The migration timescale is very similar to that of a single-star satellite of the same mass. The binary's hardening is caused by the formation of spiral tails lagging the stars inside the binary's Hill radius. We show that the hardening timescale is mostly determ...

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

    Science.gov (United States)

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

    2006-04-01

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

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. Analysis of the interface variability in NMR structure ensembles of protein-protein complexes.

    Science.gov (United States)

    Calvanese, Luisa; D'Auria, Gabriella; Vangone, Anna; Falcigno, Lucia; Oliva, Romina

    2016-06-01

    NMR structures consist in ensembles of conformers, all satisfying the experimental restraints, which exhibit a certain degree of structural variability. We analyzed here the interface in NMR ensembles of protein-protein heterodimeric complexes and found it to span a wide range of different conservations. The different exhibited conservations do not simply correlate with the size of the systems/interfaces, and are most probably the result of an interplay between different factors, including the quality of experimental data and the intrinsic complex flexibility. In any case, this information is not to be missed when NMR structures of protein-protein complexes are analyzed; especially considering that, as we also show here, the first NMR conformer is usually not the one which best reflects the overall interface. To quantify the interface conservation and to analyze it, we used an approach originally conceived for the analysis and ranking of ensembles of docking models, which has now been extended to directly deal with NMR ensembles. We propose this approach, based on the conservation of the inter-residue contacts at the interface, both for the analysis of the interface in whole ensembles of NMR complexes and for the possible selection of a single conformer as the best representative of the overall interface. In order to make the analyses automatic and fast, we made the protocol available as a web tool at: https://www.molnac.unisa.it/BioTools/consrank/consrank-nmr.html. PMID:26968364

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

    Science.gov (United States)

    Klussmann, Enno

    2016-07-01

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

  6. 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.

  7. 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.

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    Johanna Scheper

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

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

    Science.gov (United States)

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

    2014-04-01

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

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Bickerton George R

    2011-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Sandip Chakraborty

    2016-01-01

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

  14. Empirically controlled mapping of the Caenorhabditis elegans protein-protein interactome network.

    Science.gov (United States)

    Simonis, Nicolas; Rual, Jean-François; Carvunis, Anne-Ruxandra; Tasan, Murat; Lemmens, Irma; Hirozane-Kishikawa, Tomoko; Hao, Tong; Sahalie, Julie M; Venkatesan, Kavitha; Gebreab, Fana; Cevik, Sebiha; Klitgord, Niels; Fan, Changyu; Braun, Pascal; Li, Ning; Ayivi-Guedehoussou, Nono; Dann, Elizabeth; Bertin, Nicolas; Szeto, David; Dricot, Amélie; Yildirim, Muhammed A; Lin, Chenwei; de Smet, Anne-Sophie; Kao, Huey-Ling; Simon, Christophe; Smolyar, Alex; Ahn, Jin Sook; Tewari, Muneesh; Boxem, Mike; Milstein, Stuart; Yu, Haiyuan; Dreze, Matija; Vandenhaute, Jean; Gunsalus, Kristin C; Cusick, Michael E; Hill, David E; Tavernier, Jan; Roth, Frederick P; Vidal, Marc

    2009-01-01

    To provide accurate biological hypotheses and elucidate global properties of cellular networks, systematic identification of protein-protein interactions must meet high quality standards.We present an expanded C. elegans protein-protein interaction network, or 'interactome' map, derived from testing a matrix of approximately 10,000 x approximately 10,000 proteins using a highly specific, high-throughput yeast two-hybrid system. Through a new empirical quality control framework, we show that the resulting data set (Worm Interactome 2007, or WI-2007) was similar in quality to low-throughput data curated from the literature. We filtered previous interaction data sets and integrated them with WI-2007 to generate a high-confidence consolidated map (Worm Interactome version 8, or WI8). This work allowed us to estimate the size of the worm interactome at approximately 116,000 interactions. Comparison with other types of functional genomic data shows the complementarity of distinct experimental approaches in predicting different functional relationships between genes or proteins PMID:19123269

  15. 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.

  16. 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.

  17. 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

  18. Binaries in globular clusters

    Science.gov (United States)

    Hut, Piet; Mcmillan, Steve; Goodman, Jeremy; Mateo, Mario; Phinney, E. S.; Pryor, Carlton; Richer, Harvey B.; Verbunt, Frank; Weinberg, Martin

    1992-01-01

    Recent observations have shown that globular clusters contain a substantial number of binaries most of which are believed to be primordial. We discuss different successful optical search techniques, based on radial-velocity variables, photometric variables, and the positions of stars in the color-magnitude diagram. In addition, we review searches in other wavelengths, which have turned up low-mass X-ray binaries and more recently a variety of radio pulsars. On the theoretical side, we give an overview of the different physical mechanisms through which individual binaries evolve. We discuss the various simulation techniques which recently have been employed to study the effects of a primordial binary population, and the fascinating interplay between stellar evolution and stellar dynamics which drives globular-cluster evolution.

  19. The binary proletariat

    OpenAIRE

    Bolt, Nate

    2000-01-01

    In the endless quest to transform itself, capitalism has spawned a new working class. The proletariat was an essential product of the industrial revolution, and the lighter, more efficient capitalism of the digital revolution has created the Binary Proletariat.

  20. 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.

  1. Stellar collisions during binary-binary and binary-single star interactions

    NARCIS (Netherlands)

    J.M. Fregeau; P. Cheung; S.F. Portegies Zwart; F.A. Rasio

    2004-01-01

    Physical collisions between stars occur frequently in dense star clusters, either via close encounters between two single stars, or during strong dynamical interactions involving binary stars. Here we study stellar collisions that occur during binary-single and binary-binary interactions, by perform

  2. Monte Carlo population synthesis of post-common-envelope white dwarf binaries and type Ia supernova rate

    CERN Document Server

    Ablimit, Iminhaji; Li, Xiang-Dong

    2016-01-01

    Binary population synthesis (BPS) study provides a comprehensive way to understand evolutions of binaries and their end products. Close white dwarf (WD) binaries have crucial characteristics in examining in uence of yetunresolved physical parameters on the binary evolution. In this paper, we perform Monte Carlo BPS simulations, investigating the population of WD/main sequence (WD/MS) binaries and double WD binaries, with a publicly available binary star evolution code under 37 different assumptions on key physical processes and binary initial conditions. We considered different combinations of the binding energy parameter (lambda_g:considering gravitational energy only, lambda_b: considering both gravitational energy and internal energy, and lambda_e:considering gravitational energy, internal energy, and entropy of the envelope, the values of them derived with the MESA code), CE effciency, critical mass ratio, initial primary mass function and metallicity. We find that a larger number of post-CE WD/MS binarie...

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    Romina Oliva

    2015-07-01

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

  5. 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

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

    Science.gov (United States)

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

    2014-04-01

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

  7. Atomic analysis of protein-protein interfaces with known inhibitors: the 2P2I database.

    Directory of Open Access Journals (Sweden)

    Raphaël Bourgeas

    Full Text Available BACKGROUND: In the last decade, the inhibition of protein-protein interactions (PPIs has emerged from both academic and private research as a new way to modulate the activity of proteins. Inhibitors of these original interactions are certainly the next generation of highly innovative drugs that will reach the market in the next decade. However, in silico design of such compounds still remains challenging. METHODOLOGY/PRINCIPAL FINDINGS: Here we describe this particular PPI chemical space through the presentation of 2P2I(DB, a hand-curated database dedicated to the structure of PPIs with known inhibitors. We have analyzed protein/protein and protein/inhibitor interfaces in terms of geometrical parameters, atom and residue properties, buried accessible surface area and other biophysical parameters. The interfaces found in 2P2I(DB were then compared to those of representative datasets of heterodimeric complexes. We propose a new classification of PPIs with known inhibitors into two classes depending on the number of segments present at the interface and corresponding to either a single secondary structure element or to a more globular interacting domain. 2P2I(DB complexes share global shape properties with standard transient heterodimer complexes, but their accessible surface areas are significantly smaller. No major conformational changes are seen between the different states of the proteins. The interfaces are more hydrophobic than general PPI's interfaces, with less charged residues and more non-polar atoms. Finally, fifty percent of the complexes in the 2P2I(DB dataset possess more hydrogen bonds than typical protein-protein complexes. Potential areas of study for the future are proposed, which include a new classification system consisting of specific families and the identification of PPI targets with high druggability potential based on key descriptors of the interaction. CONCLUSIONS: 2P2I database stores structural information about PPIs

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

    Science.gov (United States)

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

    2016-01-01

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

  9. 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.

  10. 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.

  11. 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.

  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. 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.

  14. 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.

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

    Science.gov (United States)

    Duncan, R R

    2006-11-01

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

  16. 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.

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  19. 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.

  20. 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 ...

  1. 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.

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

    Science.gov (United States)

    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. PMID:27493967

  3. 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.

  4. 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.

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

    Science.gov (United States)

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

    2016-06-01

    Using hearts from mice overexpressing integrin linked kinase (ILK) behind the cardiac specific promoter αMHC, we have performed immunoprecipitation and mass spectrometry to identify novel ILK protein:protein interactions that regulate cardiomyocyte activity and calcium flux. Integrin linked kinase complexes were captured from mouse heart lysates using a commercial antibody, with subsequent liquid chromatography tandem mass spectral analysis. Interacting partners were identified using the MASCOT server, and important interactions verified using reverse immunoprecipitation and mass spectrometry. All ILK interacting proteins were identified in a non-biased manner, and are stored in the ProteomeXchange Consortium via the PRIDE partner repository (reference ID PRIDE: PXD001053). The functional role of identified ILK interactions in cardiomyocyte function and arrhythmia were subsequently confirmed in human iPSC-cardiomyocytes. PMID:27408918

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

    Science.gov (United States)

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

    2016-02-17

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

  7. 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.

  8. 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.

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

    Science.gov (United States)

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

    2016-01-01

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

  10. 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.

  11. Identification of Protein-Protein Interactions by Detecting Correlated Mutation at the Interface.

    Science.gov (United States)

    Guo, Fei; Ding, Yijie; Li, Zhao; Tang, Jijun

    2015-09-28

    Protein-protein interactions play key roles in a multitude of biological processes, such as de novo drug design, immune response, and enzymatic activity. It is of great interest to understand how proteins in a complex interact with each other. Here, we present a novel method for identifying protein-protein interactions, based on typical co-evolutionary information. Correlated mutation analysis can be used to predict interface residues. In this paper, we propose a non-redundant database to detect correlated mutation at the interface. First, we construct structure alignments for one input protein, based on all aligned proteins in the database. Evolutionary distance matrices, one for each input protein, can be calculated through geometric similarity and evolutionary information. Then, we use evolutionary distance matrices to estimate correlation coefficient between each pair of fragments from two input proteins. Finally, we extract interacting residues with high values of correlation coefficient, which can be grouped as interacting patches. Experiments illustrate that our method achieves better results than some existing co-evolution-based methods. Applied to SK/RR interaction between sensor kinase and response regulator proteins, our method has accuracy and coverage values of 53% and 45%, which improves upon accuracy and coverage values of 50% and 30% for DCA method. We evaluate interface prediction on four protein families, and our method has overall accuracy and coverage values of 34% and 30%, which improves upon overall accuracy and coverage values of 27% and 21% for PIFPAM. Our method has overall accuracy and coverage values of 59% and 63% on Benchmark v4.0, and 50% and 49% on CAPRI targets. Comparing to existing methods, our method improves overall accuracy value by at least 2%. PMID:26284382

  12. 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...

  13. 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...

  14. 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.

  15. 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......) and 779 protein-protein interactions. A number of proteins were identified having interactions with more than one of the protein kinases. The fully reconstructed interaction network includes all the information available in separate databases for all the proteins included in the network (nodes......) and for all the interactions between them (edges). The annotated information is readily available utilizing the functionalities of network modelling tools such as Cytoscape and CellDesigner. CONCLUSIONS: The reported fully annotated interaction model serves as a platform for integrated systems biology studies...

  16. 3D model for Cancerous Inhibitor of Protein Phosphatase 2A armadillo domain unveils highly conserved protein-protein interaction characteristics.

    Science.gov (United States)

    Dahlström, Käthe M; Salminen, Tiina A

    2015-12-01

    Cancerous Inhibitor of Protein Phosphatase 2A (CIP2A) is a human oncoprotein, which exerts its cancer-promoting function through interaction with other proteins, for example Protein Phosphatase 2A (PP2A) and MYC. The lack of structural information for CIP2A significantly prevents the design of anti-cancer therapeutics targeting this protein. In an attempt to counteract this fact, we modeled the three-dimensional structure of the N-terminal domain (CIP2A-ArmRP), analyzed key areas and amino acids, and coupled the results to the existing literature. The model reliably shows a stable armadillo repeat fold with a positively charged groove. The fact that this conserved groove highly likely binds peptides is corroborated by the presence of a conserved polar ladder, which is essential for the proper peptide-binding mode of armadillo repeat proteins and, according to our results, several known CIP2A interaction partners appropriately possess an ArmRP-binding consensus motif. Moreover, we show that Arg229Gln, which has been linked to the development of cancer, causes a significant change in charge and surface properties of CIP2A-ArmRP. In conclusion, our results reveal that CIP2A-ArmRP shares the typical fold, protein-protein interaction site and interaction patterns with other natural armadillo proteins and that, presumably, several interaction partners bind into the central groove of the modeled CIP2A-ArmRP. By providing essential structural characteristics of CIP2A, the present study significantly increases our knowledge on how CIP2A interacts with other proteins in cancer progression and how to develop new therapeutics targeting CIP2A. PMID:26393783

  17. 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.

  18. One-Pot N2C/C2C/N2N Ligation To Trap Weak Protein-Protein Interactions.

    Science.gov (United States)

    Zhao, Lei; Ehrt, Christiane; Koch, Oliver; Wu, Yao-Wen

    2016-07-01

    Weak transient protein-protein interactions (PPIs) play an essential role in cellular dynamics. However, it is challenging to obtain weak protein complexes owing to their short lifetime. Herein we present a general and facile method for trapping weak PPIs in an unbiased manner using proximity-induced ligations. To expand the chemical ligation spectrum, we developed novel N2N (N-terminus to N-terminus) and C2C (C-terminus to C-terminus) ligation approaches. By using N2C (N-terminus to C-terminus), N2N, and C2C ligations in one pot, the interacting proteins were linked. The weak Ypt1:GDI interaction drove C2C ligation with t1/2 of 4.8 min and near quantitative conversion. The Ypt1-GDI conjugate revealed that binding of Ypt1 G-domain causes opening of the lipid-binding site of GDI, which can accommodate one prenyl group, giving insights into Rab membrane recycling. Moreover, we used this strategy to trap the KRas homodimer, which plays an important role in Ras signaling. PMID:27213482

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

    Directory of Open Access Journals (Sweden)

    Nielsen Jens

    2010-05-01

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

  20. 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.

  1. 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.

  2. Hypervelocity binary stars: smoking gun of massive binary black holes

    CERN Document Server

    Lu, Youjun; Lin, D N C

    2007-01-01

    The hypervelocity stars recently found in the Galactic halo are expelled from the Galactic center through interactions between binary stars and the central massive black hole or between single stars and a hypothetical massive binary black hole. In this paper, we demonstrate that binary stars can be ejected out of the Galactic center with velocities up to 10^3 km/s, while preserving their integrity, through interactions with a massive binary black hole. Binary stars are unlikely to attain such high velocities via scattering by a single massive black hole or through any other mechanisms. Based on the above theoretical prediction, we propose a search for binary systems among the hypervelocity stars. Discovery of hypervelocity binary stars, even one, is a definitive evidence of the existence of a massive binary black hole in the Galactic center.

  3. Milli-arcsecond Binaries

    CERN Document Server

    Torres, R M; Mioduszewki, A; Rodríguez, L F

    2008-01-01

    As part of an astrometric program, we have used the Very Long Baseline Array to measure the trigonometric parallax of several young stars in the Taurus and Ophiuchus star-forming regions with great accuracy. Additionally, we have obtained an unprecedented sample of high-resolution (~ 1 mas) images of several young stellar systems. These images revealed that about 70% of the stars in our sample are very tight binary stars (with separations of a few mas). Since it is highly unlikely that 70% of all stars are such tight binaries, we argue that selection effects are at work.

  4. Binary Cumulant Varieties

    CERN Document Server

    Sturmfels, Bernd

    2011-01-01

    Algebraic statistics for binary random variables is concerned with highly structured algebraic varieties in the space of 2x2x...x2-tensors. We demonstrate the advantages of representing such varieties in the coordinate system of binary cumulants. Our primary focus lies on hidden subset models. Parametrizations and implicit equations in cumulants are derived for hyperdeterminants, for secant and tangential varieties of Segre varieties, and for certain context-specific independence models. Extending work of Rota and collaborators, we explore the polynomial inequalities satisfied by cumulants.

  5. 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

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

    Science.gov (United States)

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

    2013-02-01

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

  7. Formation of binary radio pulsars

    International Nuclear Information System (INIS)

    In the framework of the standard scenario of the evolution of massive binary stars a study is made of the formation of final binary systems in which at least one of the components is a neutron star. It is found that about every fortieth radio pulsar must be a member of a close binary system. This is confirmed by observations. Radio pulsars are not formed in wide binary systems, possibly because of the very slow rotation of the presupernova stars

  8. Quantum Binary Symmetric Channels

    Institute of Scientific and Technical Information of China (English)

    陈小余; 仇佩亮

    2001-01-01

    Quantum binary symmetric channels are defined via the invariance of fidelity under unitary transformations ofthe input density operators. In this definition, they not only include the most studied case of the depolarizingchannel but also other channels. We investigate the character of the latter and find the maximum of the coherentinformation to estimate the capacities of the channels.

  9. 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

  10. 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

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

    OpenAIRE

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

    2012-01-01

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

  12. An effective system for detecting protein-protein interaction based on in vivo cleavage by PPV NIa protease.

    Science.gov (United States)

    Zheng, Nuoyan; Huang, Xiahe; Yin, Bojiao; Wang, Dan; Xie, Qi

    2012-12-01

    Detection of protein-protein interaction can provide valuable information for investigating the biological function of proteins. The current methods that applied in protein-protein interaction, such as co-immunoprecipitation and pull down etc., often cause plenty of working time due to the burdensome cloning and purification procedures. Here we established a system that characterization of protein-protein interaction was accomplished by co-expression and simply purification of target proteins from one expression cassette within E. coli system. We modified pET vector into co-expression vector pInvivo which encoded PPV NIa protease, two cleavage site F and two multiple cloning sites that flanking cleavage sites. The target proteins (for example: protein A and protein B) were inserted at multiple cloning sites and translated into polyprotein in the order of MBP tag-protein A-site F-PPV NIa protease-site F-protein B-His(6) tag. PPV NIa protease carried out intracellular cleavage along expression, then led to the separation of polyprotein components, therefore, the interaction between protein A-protein B can be detected through one-step purification and analysis. Negative control for protein B was brought into this system for monitoring interaction specificity. We successfully employed this system to prove two cases of reported protien-protein interaction: RHA2a/ANAC and FTA/FTB. In conclusion, a convenient and efficient system has been successfully developed for detecting protein-protein interaction.

  13. 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

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

    OpenAIRE

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

    2011-01-01

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

  15. A Domain-Based Approach to Predict Protein-Protein Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Singhal, Mudita; Resat, Haluk

    2007-06-13

    Background:Understanding of biological processes necessitates knowing not only which proteins exist in a certain organism or cell type but also how these proteins interact with each other. However, the determination of the protein-protein interaction (PPI) networks is a daunting task and it has been the subject of extensive research. Despite the development of reasonably successful methods, serious technical difficulties still exist as is evident from the small overlap between the high-throughput experimental approaches. Results:In this manuscript we present DomainGA which is a Genetic Algorithm based method that optimizes the domain-domain interactions scores which can be used to predict protein-protein interactions (PPI). We show the robustness and insensitivity of the DomainGA method to the selection of the parameter sets, score ranges, and detection rules using the Yeast PPI data. In a two-fold cross-validation study, the DomainGA optimization achieves an explanation ratio of 99% and the cross validation test results are 97% and 88% for the positive and negative PPIs, respectively. We discuss how the DomainGA method significantly improves on the random predictions, particularly for predicting the non-interacting protein pairs. Based on our cross-verification tests on Human PPI, comparison of the optimized scores with the structurally observed domain interactions obtained from the iPFAM database, and sensitivity & specificity analysis; we conclude that our DomainGA method shows great promise to be applicable across multiple organisms. Conclusions:We envision the DomainGA as a first step of a multiple tier approach to constructing PPIs. As it is based on the fundamental structural information, DomainGA approach can be used to create the potential PPIs and the accuracy of the constructed interaction template can be improved later using complementary methods such as literature search or other prediction methods. Obtained explanation ratios during the reported test

  16. Protein-protein structure prediction by scoring molecular dynamics trajectories of putative poses.

    Science.gov (United States)

    Sarti, Edoardo; Gladich, Ivan; Zamuner, Stefano; Correia, Bruno E; Laio, Alessandro

    2016-09-01

    The prediction of protein-protein interactions and their structural configuration remains a largely unsolved problem. Most of the algorithms aimed at finding the native conformation of a protein complex starting from the structure of its monomers are based on searching the structure corresponding to the global minimum of a suitable scoring function. However, protein complexes are often highly flexible, with mobile side chains and transient contacts due to thermal fluctuations. Flexibility can be neglected if one aims at finding quickly the approximate structure of the native complex, but may play a role in structure refinement, and in discriminating solutions characterized by similar scores. We here benchmark the capability of some state-of-the-art scoring functions (BACH-SixthSense, PIE/PISA and Rosetta) in discriminating finite-temperature ensembles of structures corresponding to the native state and to non-native configurations. We produce the ensembles by running thousands of molecular dynamics simulations in explicit solvent starting from poses generated by rigid docking and optimized in vacuum. We find that while Rosetta outperformed the other two scoring functions in scoring the structures in vacuum, BACH-SixthSense and PIE/PISA perform better in distinguishing near-native ensembles of structures generated by molecular dynamics in explicit solvent. Proteins 2016; 84:1312-1320. © 2016 Wiley Periodicals, Inc. PMID:27253756

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

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

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

    2016-01-01

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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

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

    Science.gov (United States)

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

    2015-01-01

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

  6. 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.

  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. 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.

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

    Institute of Scientific and Technical Information of China (English)

    Purnima Guda; Sridar V. Chittur; Chittibabu Guda

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Xiuquan Du

    2015-01-01

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

  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. Polar Recognition Group Study of Keap1-Nrf2 Protein-Protein Interaction Inhibitors.

    Science.gov (United States)

    Lu, Meng-Chen; Tan, Shi-Jie; Ji, Jian-Ai; Chen, Zhi-Yun; Yuan, Zhen-Wei; You, Qi-Dong; Jiang, Zheng-Yu

    2016-09-01

    Directly disrupting the Keap1-Nrf2 protein-protein interaction (PPI) has emerged as an attractive way to activate Nrf2, and Keap1-Nrf2 PPI inhibitors have been proposed as potential agents to relieve inflammatory and oxidative stress diseases. In this work, we investigated the diacetic moiety around the potent Keap1-Nrf2 PPI inhibitor DDO1018 (2), which was reported by our group previously. Exploration of bioisosteric replacements afforded the ditetrazole analog 7, which maintains the potent PPI inhibition activity (IC50 = 15.8 nM) in an in vitro fluorescence polarization assay. Physicochemical property determination demonstrated that ditetrazole replacement can improve the drug-like property, including elevation of pK a, log D, and transcellular permeability. Additionally, 7 is more efficacious than 2 on inducing the expression of Nrf2-dependent gene products in cells. This study provides an alternative way to replace the diacetic moiety and occupy the polar subpockets in Keap1, which can benefit the subsequent development of Keap1-Nrf2 PPI inhibitor. PMID:27660687

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

    Directory of Open Access Journals (Sweden)

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

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Lei Yang

    2014-01-01

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

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

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    He Wei

    2010-10-01

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

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

    Science.gov (United States)

    Yang, Lei; Tang, Xianglong

    2014-01-01

    Cliques (maximal complete subnets) in protein-protein interaction (PPI) network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO) annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP) and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning. PMID:24578640

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jianhua eYang

    2013-01-01

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

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

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    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.

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

    Science.gov (United States)

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

    2015-01-01

    Genome-wide network analysis is well implemented to study proteins of unknown function. Here, we effectively explored protein functions and the biological mechanism based on inferred high confident protein-protein interaction (PPI) network in cyanobacteria. We integrated data from seven different sources and predicted 1,997 PPIs, which were evaluated by experiments in molecular mechanism, text mining of literatures in proved direct/indirect evidences, and "interologs" in conservation. Combined the predicted PPIs with known PPIs, we obtained 4,715 no-redundant PPIs (involving 3,231 proteins covering over 90% of genome) to generate the PPI network. Based on the PPI network, terms in Gene ontology (GO) were assigned to function-unknown proteins. Functional modules were identified by dissecting the PPI network into sub-networks and analyzing pathway enrichment, with which we investigated novel function of underlying proteins in protein complexes and pathways. Examples of photosynthesis and DNA repair indicate that the network approach is a powerful tool in protein function analysis. Overall, this systems biology approach provides a new insight into posterior functional analysis of PPIs in cyanobacteria. PMID:26490033

  1. 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.

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

    Science.gov (United States)

    Wallach, Thomas; Schellenberg, Katja; Maier, Bert; Kalathur, Ravi Kiran Reddy; Porras, Pablo; Wanker, Erich E; Futschik, Matthias E; Kramer, Achim

    2013-03-01

    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. PMID:23555304

  3. 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.

  4. Template-based identification of protein-protein interfaces using eFindSitePPI.

    Science.gov (United States)

    Maheshwari, Surabhi; Brylinski, Michal

    2016-01-15

    Protein-protein interactions orchestrate virtually all cellular processes, therefore, their exhaustive exploration is essential for the comprehensive understanding of cellular networks. A reliable identification of interfacial residues is vital not only to infer the function of individual proteins and their assembly into biological complexes, but also to elucidate the molecular and physicochemical basis of interactions between proteins. With the exponential growth of protein sequence data, computational approaches for detecting protein interface sites have drawn an increased interest. In this communication, we discuss the major features of eFindSite(PPI), a recently developed template-based method for interface residue prediction available at http://brylinski.cct.lsu.edu/efindsiteppi. We describe the requirements and installation procedures for the stand-alone version, and explain the content and format of output data. Furthermore, the functionality of the eFindSite(PPI) web application that is designed to provide a simple and convenient access for the scientific community is presented with illustrative examples. Finally, we discuss common problems encountered in predicting protein interfaces and set forth directions for the future development of eFindSite(PPI). PMID:26235816

  5. P-Finder: Reconstruction of Signaling Networks from Protein-Protein Interactions and GO Annotations.

    Science.gov (United States)

    Young-Rae Cho; Yanan Xin; Speegle, Greg

    2015-01-01

    Because most complex genetic diseases are caused by defects of cell signaling, illuminating a signaling cascade is essential for understanding their mechanisms. We present three novel computational algorithms to reconstruct signaling networks between a starting protein and an ending protein using genome-wide protein-protein interaction (PPI) networks and gene ontology (GO) annotation data. A signaling network is represented as a directed acyclic graph in a merged form of multiple linear pathways. An advanced semantic similarity metric is applied for weighting PPIs as the preprocessing of all three methods. The first algorithm repeatedly extends the list of nodes based on path frequency towards an ending protein. The second algorithm repeatedly appends edges based on the occurrence of network motifs which indicate the link patterns more frequently appearing in a PPI network than in a random graph. The last algorithm uses the information propagation technique which iteratively updates edge orientations based on the path strength and merges the selected directed edges. Our experimental results demonstrate that the proposed algorithms achieve higher accuracy than previous methods when they are tested on well-studied pathways of S. cerevisiae. Furthermore, we introduce an interactive web application tool, called P-Finder, to visualize reconstructed signaling networks.

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

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    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.

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

    Science.gov (United States)

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

    2016-02-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

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    G Jack Peterson

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

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

    Science.gov (United States)

    Gruet, Antoine; Dosnon, Marion; Blocquel, David; Brunel, Joanna; Gerlier, Denis; Das, Rahul K; Bonetti, Daniela; Gianni, Stefano; Fuxreiter, Monika; Longhi, Sonia; Bignon, Christophe

    2016-02-01

    Despite the partial disorder-to-order transition that intrinsically disordered proteins often undergo upon binding to their partners, a considerable amount of residual disorder may be retained in the bound form, resulting in a fuzzy complex. Fuzzy regions flanking molecular recognition elements may enable partner fishing through non-specific, transient contacts, thereby facilitating binding, but may also disfavor binding through various mechanisms. So far, few computational or experimental studies have addressed the effect of fuzzy appendages on partner recognition by intrinsically disordered proteins. In order to shed light onto this issue, we used the interaction between the intrinsically disordered C-terminal domain of the measles virus (MeV) nucleoprotein (NTAIL ) and the X domain (XD) of the viral phosphoprotein as model system. After binding to XD, the N-terminal region of NTAIL remains conspicuously disordered, with α-helical folding taking place only within a short molecular recognition element. To study the effect of the N-terminal fuzzy region on NTAIL /XD binding, we generated N-terminal truncation variants of NTAIL , and assessed their binding abilities towards XD. The results revealed that binding increases with shortening of the N-terminal fuzzy region, with this also being observed with hsp70 (another MeV NTAIL binding partner), and for the homologous NTAIL /XD pairs from the Nipah and Hendra viruses. Finally, similar results were obtained when the MeV NTAIL fuzzy region was replaced with a highly dissimilar artificial disordered sequence, supporting a sequence-independent inhibitory effect of the fuzzy region. PMID:26684000

  11. Binary MEMS gas sensors

    International Nuclear Information System (INIS)

    A novel sensing mechanism for electrostatic MEMS that employs static bifurcation-based sensing and binary detection is demonstrated. It is implemented as an ethanol vapour sensor that exploits the static pull-in bifurcation. Sensor detection of 5 ppm of ethanol vapour in dry nitrogen, equivalent to a detectable mass of 165 pg, is experimentally demonstrated. Sensor robustness to external disturbances is also demonstrated. A closed-form expression for the sensitivity of statically detected electrostatic MEMS sensors is derived. It is shown that the sensitivity of static bifurcation-based binary electrostatic MEMS sensors represents an upper bound on the sensitivity of static detection for given sensor dimensions and material properties. (paper)

  12. FS CMa type binaries

    CERN Document Server

    Miroshnichenko, Anatoly

    2015-01-01

    FS CMa type stars is a group of ~70 objects formerly known as unclassified stars with the B[e] phenomenon. Their very strong emission-line spectra in combination with a nearly main-sequence luminosity suggest the binary nature for them. They possess strong IR excesses due to radiation of circumstellar dust that implies a compact distribution probably in a circumbinary disk. Our long-term spectroscopic monitoring revealed neutral metal lines, which always include that of Li I 6708 \\AA, in the spectra of some FS CMa objects indicating the presence of a cool star. We present a summary of our results with a first overview of FS CMa type binaries and review possible implications for the nature and evolutionary status of the entire group.

  13. 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

  14. Massive Black Hole Binary Evolution

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    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.

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

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    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

  16. 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

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

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    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

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

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    Cedano Juan

    2010-10-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  20. 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.

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

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    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.

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

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    Jain Shobhit

    2010-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Chou Lih-Ching

    2010-04-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Wako Hiroshi

    2010-07-01

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

  6. 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.

  7. 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.

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

    Science.gov (United States)

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

    2016-08-16

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

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    Hao Wu

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

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

    Science.gov (United States)

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

    2014-01-01

    In this paper, we present a novel rough-fuzzy clustering (RFC) method to detect overlapping protein complexes in protein-protein interaction (PPI) networks. RFC focuses on fuzzy relation model rather than graph model by integrating fuzzy sets and rough sets, employs the upper and lower approximations of rough sets to deal with overlapping complexes, and calculates the number of complexes automatically. Fuzzy relation between proteins is established and then transformed into fuzzy equivalence relation. Non-overlapping complexes correspond to equivalence classes satisfying certain equivalence relation. To obtain overlapping complexes, we calculate the similarity between one protein and each complex, and then determine whether the protein belongs to one or multiple complexes by computing the ratio of each similarity to maximum similarity. To validate RFC quantitatively, we test it in Gavin, Collins, Krogan and BioGRID datasets. Experiment results show that there is a good correspondence to reference complexes in MIPS and SGD databases. Then we compare RFC with several previous methods, including ClusterONE, CMC, MCL, GCE, OSLOM and CFinder. Results show the precision, sensitivity and separation are 32.4%, 42.9% and 81.9% higher than mean of the five methods in four weighted networks, and are 0.5%, 11.2% and 66.1% higher than mean of the six methods in five unweighted networks. Our method RFC works well for protein complexes detection and provides a new insight of network division, and it can also be applied to identify overlapping community structure in social networks and LFR benchmark networks. PMID:24642838

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

    Shashikanth, Nitesh; Kisting, Meridith A; Leckband, Deborah E

    2016-01-01

    The binding properties of adhesion proteins are typically quantified from measurements with soluble fragments, under conditions that differ radically from the confined microenvironment of membrane bound proteins in adhesion zones. Using classical cadherin as a model adhesion protein, we tested the postulate that confinement within quasi two-dimensional intercellular gaps exposes weak protein interactions that are not detected in solution binding assays. Micropipette-based measurements of cadherin-mediated, cell-cell binding kinetics identified a unique kinetic signature that reflects both adhesive (trans) bonds between cadherins on opposing cells and lateral (cis) interactions between cadherins on the same cell. In solution, proposed lateral interactions were not detected, even at high cadherin concentrations. Mutations postulated to disrupt lateral cadherin association altered the kinetic signatures, but did not affect the adhesive (trans) binding affinity. Perturbed kinetics further coincided with altered cadherin distributions at junctions, wound healing dynamics, and paracellular permeability. Intercellular binding kinetics thus revealed cadherin interactions that occur within confined, intermembrane gaps but not in solution. Findings further demonstrate the impact of these revealed interactions on the organization and function of intercellular junctions. PMID:27009566

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

    Science.gov (United States)

    He, Yi-Ming; Ma, Bin-Guang

    2016-05-01

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

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

    Science.gov (United States)

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

    2016-01-01

    Nanoparticle-mediated delivery of functional macromolecules is a promising method for treating a variety of human diseases. Among nanoparticles, cell-derived exosomes have recently been highlighted as a new therapeutic strategy for the in vivo delivery of nucleotides and chemical drugs. Here we describe a new tool for intracellular delivery of target proteins, named 'exosomes for protein loading via optically reversible protein-protein interactions' (EXPLORs). By integrating a reversible protein-protein interaction module controlled by blue light with the endogenous process of exosome biogenesis, we are able to successfully load cargo proteins into newly generated exosomes. Treatment with protein-loaded EXPLORs is shown to significantly increase intracellular levels of cargo proteins and their function in recipient cells in vitro and in vivo. These results clearly indicate the potential of EXPLORs as a mechanism for the efficient intracellular transfer of protein-based therapeutics into recipient cells and tissues. PMID:27447450

  16. Binary optics: Trends and limitations

    Science.gov (United States)

    Farn, Michael W.; Veldkamp, Wilfrid B.

    1993-08-01

    We describe the current state of binary optics, addressing both the technology and the industry (i.e., marketplace). With respect to the technology, the two dominant aspects are optical design methods and fabrication capabilities, with the optical design problem being limited by human innovation in the search for new applications and the fabrication issue being limited by the availability of resources required to improve fabrication capabilities. With respect to the industry, the current marketplace does not favor binary optics as a separate product line and so we expect that companies whose primary purpose is the production of binary optics will not represent the bulk of binary optics production. Rather, binary optics' more natural role is as an enabling technology - a technology which will directly result in a competitive advantage in a company's other business areas - and so we expect that the majority of binary optics will be produced for internal use.

  17. Binaries in the Kuiper Belt

    CERN Document Server

    Noll, K S; Chiang, E I; Margot, J L; Kern, S D; Noll, Keith S.; Grundy, William M.; Chiang, Eugene I.; Margot, Jean-Luc; Kern, Susan D.

    2007-01-01

    Binaries have played a crucial role many times in the history of modern astronomy and are doing so again in the rapidly evolving exploration of the Kuiper Belt. The large fraction of transneptunian objects that are binary or multiple, 48 such systems are now known, has been an unanticipated windfall. Separations and relative magnitudes measured in discovery images give important information on the statistical properties of the binary population that can be related to competing models of binary formation. Orbits, derived for 13 systems, provide a determination of the system mass. Masses can be used to derive densities and albedos when an independent size measurement is available. Angular momenta and relative sizes of the majority of binaries are consistent with formation by dynamical capture. The small satellites of the largest transneptunian objects, in contrast, are more likely formed from collisions. Correlations of the fraction of binaries with different dynamical populations or with other physical variabl...

  18. 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

  19. 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...

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

    OpenAIRE

    Yi-Ming He; Bin-Guang Ma

    2016-01-01

    Protein complexes are major forms of protein-protein interactions and implement essential biological functions. The subunit interface in a protein complex is related to its thermostability. Though the roles of interface properties in thermal adaptation have been investigated for protein complexes, the relationship between the interface size and the expression level of the subunits remains unknown. In the present work, we studied this relationship and found a positive correlation in thermophil...

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

    OpenAIRE

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

    2014-01-01

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

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

    OpenAIRE

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

    2013-01-01

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

  3. Biclustering Sparse Binary Genomic Data

    OpenAIRE

    Van Uitert, M.; Meuleman, W.; Wessels, L. F. A.

    2008-01-01

    Genomic datasets often consist of large, binary, sparse data matrices. In such a dataset, one is often interested in finding contiguous blocks that (mostly) contain ones. This is a biclustering problem, and while many algorithms have been proposed to deal with gene expression data, only two algorithms have been proposed that specifically deal with binary matrices. None of the gene expression biclustering algorithms can handle the large number of zeros in sparse binary matrices. The two propos...

  4. Development of computational methods for the prediction of protein structure, protein binding, and mutational effects using free energy calculations.

    OpenAIRE

    Becker, Caroline

    2014-01-01

    A molecular understanding of protein-protein or protein-ligand binding is of crucial importance for the design of proteins or ligands with defined binding characteristics. The comprehensive analysis of biomolecular binding and the coupled rational in silico design of protein-ligand interfaces requires both, accurate and computationally fast methods for the prediction of free energies. Accurate free energy methods usually involve atomistic molecular dynamics simulations that are computationall...

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

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

    NARCIS (Netherlands)

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

    2011-01-01

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

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

    Science.gov (United States)

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

    1987-06-01

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

  13. 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

  14. 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

  15. 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

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

    Directory of Open Access Journals (Sweden)

    Resat Haluk

    2007-06-01

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

  17. 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.

  18. Studies of protein-protein and protein-RNA complexes by mass spectrometry

    International Nuclear Information System (INIS)

    Electrospray ionization mass spectrometry (ESI-MS) enables the determination of not only the molecular sizes of non-covalent macromolecular complexes, but also the binding affinities. This paper shows the advantages of ESI-MS over other techniques in structural studies of biological macromolecular complexes, using as an example our recent analysis of TRAP, trp RNA-binding attenuation protein, and its complexes with RNA and protein ligands. TRAP and its regulator anti-TRAP protein (AT) play the principal roles in controlling tryptophan synthesis in Bacillus species. We have characterized both wild-type (wt) and mutant TRAP from B. stearothermophilus, and their complexes with RNA or AT by ESI-MS. Wild-type TRAP forms homo-11mer rings. The mutant used carries three copies of the TRAP monomer on a single polypeptide chain, so that it associates to form a 12mer ring with four polypeptides. Mass spectra showed that both the wt TRAP 11mer and the mutant TRAP 12mer can bind a cognate single-stranded RNA. The crystal structure of wt TRAP complexed with AT shows a TRAP 12mer ring surrounded by six AT trimers. However, ESI-MS of wild-type TRAP mixed with AT shows four species with different binding stoichiometries, and the complex observed by crystallography represents only a minor species in solution; most of the TRAP remains in an 11mer ring form. Mass spectra of mutant TRAP showed only a single species, TRAP 12mer + six copies of AT trimer, which is observed by crystallography. The crystal structure of the TRAP-AT complexes shows that only a 12mer TRAP ring can bind with six copies of AT trimer. These results suggest that crystallization selects only the most symmetrical TRAP-AT complex from the solution, while ESI-MS can take a 'snapshot' of all the species in solution. (author)

  19. 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.

  20. 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

  1. Multiple GTP-binding proteins participate in clathrin-coated vesicle- mediated endocytosis

    OpenAIRE

    1993-01-01

    We have examined the effects of various agonists and antagonists of GTP- binding proteins on receptor-mediated endocytosis in vitro. Stage- specific assays which distinguish coated pit assembly, invagination, and coat vesicle budding have been used to demonstrate requirements for GTP-binding protein(s) in each of these events. Coated pit invagination and coated vesicle budding are both stimulated by addition of GTP and inhibited by GDP beta S. Although coated pit invagination is resistant to ...

  2. Modeling Binary Neutron Stars

    Science.gov (United States)

    Park, Conner; Read, Jocelyn; Flynn, Eric; Lockett-Ruiz, Veronica

    2016-03-01

    Gravitational waves, predicted by Einstein's Theory of Relativity, are a new frontier in astronomical observation we can use to observe phenomena in the universe. Laser Interferometer Gravitational wave Observatory (LIGO) is currently searching for gravitational wave signals, and requires accurate predictions in order to best extract astronomical signals from all other sources of fluctuations. The focus of my research is in increasing the accuracy of Post-Newtonian models of binary neutron star coalescence to match the computationally expensive Numerical models. Numerical simulations can take months to compute a couple of milliseconds of signal whereas the Post-Newtonian can generate similar signals in seconds. However the Post-Newtonian model is an approximation, e.g. the Taylor T4 Post-Newtonian model assumes that the two bodies in the binary neutron star system are point charges. To increase the effectiveness of the approximation, I added in tidal effects, resonance frequencies, and a windowing function. Using these observed effects from simulations significantly increases the Post-Newtonian model's similarity to the Numerical signal.

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

    Science.gov (United States)

    Lai, Hsien-Tsung; Chiang, Cheng-Ming

    2016-01-01

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

  4. 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.

  5. 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.

  6. 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.

  7. Relativistic Binaries in Globular Clusters

    Directory of Open Access Journals (Sweden)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-04-29

    CDC25 phosphatases are key cell cycle regulators and represent very attractive but challenging targets for anticancer drug discovery. Here, we explored whether fragment-based screening represents a valid approach to identify inhibitors of CDC25B. This resulted in identification of 2-fluoro-4-hydroxybenzonitrile, which directly binds to the catalytic domain of CDC25B. Interestingly, NMR data and the crystal structure demonstrate that this compound binds to the pocket distant from the active site and adjacent to the protein–protein interaction interface with CDK2/Cyclin A substrate. Furthermore, we developed a more potent analogue that disrupts CDC25B interaction with CDK2/Cyclin A and inhibits dephosphorylation of CDK2. Based on these studies, we provide a proof of concept that targeting CDC25 phosphatases by inhibiting their protein–protein interactions with CDK2/Cyclin A substrate represents a novel, viable opportunity to target this important class of enzymes.

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    related MAGUK proteins contain three consecutive PDZ domains, hence we envisioned that targeting all three PDZ domains simultaneously would lead to more potent and potentially more specific interactions with the MAGUK proteins. Here we describe the design, synthesis and characterization of a series of...... trimeric ligands targeting all three PDZ domains of PSD-95 and the related MAGUK proteins, PSD-93, SAP-97 and SAP-102. Using our dimeric ligands targeting the PDZ1-2 tandem as starting point, we designed novel trimeric ligands by introducing a PDZ3-binding peptide moiety via a cysteine-derivatized NPEG...... linker. The trimeric ligands generally displayed increased affinities compared to the dimeric ligands in fluorescence polarization binding experiments and optimized trimeric ligands showed low nanomolar inhibition towards the four MAGUK proteins, thus being the most potent inhibitors described. Kinetic...

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

    OpenAIRE

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

    2015-01-01

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

  11. Identification of the lipid droplet targeting domain of the Cidea protein[S

    OpenAIRE

    Christianson, Jennifer L.; Boutet, Emilie; Puri, Vishwajeet; Chawla, Anil; Czech, Michael P.

    2010-01-01

    Cidea, the cell death-inducing DNA fragmentation factor-α-like effector (CIDE) domain-containing protein, is targeted to lipid droplets in mouse adipocytes, where it inhibits triglyceride hydrolysis and promotes lipid storage. In mice, Cidea may prevent lipolysis by binding and shielding lipid droplets from lipase association. Here we demonstrate that human Cidea localizes with lipid droplets in both adipocyte and nonadipocyte cell lines, and we ascribe specific functions to its protein domai...

  12. 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.

  13. Planets in evolved binary systems

    CERN Document Server

    Perets, Hagai B

    2010-01-01

    Exoplanets are typically thought to form in protoplanetary disks left over from protostellar disk of their newly formed host star. However, additional planetary formation and evolution routes may exist in old evolved binary systems. Here we discuss the implications of binary stellar evolution on planetary systems. In these binary systems stellar evolution could lead to the formation of symbiotic stars, where mass is lost from one star and could be transferred to its binary companion, and may form an accretion disk around it. This raises the possibility that such a disk could provide the necessary environment for the formation of a new, second generation of planets in both circumstellar or circumbinary configurations. Pre-existing first generation planets surviving the post-MS evolution of such systems would be dynamically effected by the mass loss in the systems and may also interact with the newly formed disk. Second generation planetary systems should be typically found in white dwarf binary systems, and ma...

  14. Pairing mechanisms for binary stars

    CERN Document Server

    Kouwenhoven, M B N; Goodwin, S P; Zwart, S F Portegies; Kaper, L; 10.1002/asna.200811061

    2008-01-01

    Knowledge of the binary population in stellar groupings provides important information about the outcome of the star forming process in different environments. Binarity is also a key ingredient in stellar population studies and is a prerequisite to calibrate the binary evolution channels. In these proceedings we present an overview of several commonly used methods to pair individual stars into binary systems, which we refer to as the pairing function. Many pairing functions are frequently used by observers and computational astronomers, either for the mathematical convenience, or because they roughly describe the expected outcome of the star forming process. We discuss the consequences of each pairing function for the interpretation of observations and numerical simulations. The binary fraction and mass ratio distribution generally depend strongly on the selection of the range in primary spectral type in a sample. These quantities, when derived from a binary survey with a mass-limited sample of target stars, ...

  15. Convergent evolution among immunoglobulin G-binding bacterial proteins.

    OpenAIRE

    Frick, I M; Wikström, M.; Forsén, S.; Drakenberg, T; Gomi, H.; Sjöbring, U; Björck, L

    1992-01-01

    Protein G, a bacterial cell-wall protein with high affinity for the constant region of IgG (IgGFc) antibodies, contains homologous repeats responsible for the interaction with IgGFc. A synthetic peptide corresponding to an 11-amino acid-long sequence in the COOH-terminal region of the repeats was found to bind to IgGFc and block the interaction with protein G. Moreover, two other IgGFc-binding bacterial proteins (proteins A and H), which do not contain any sequences homologous to the peptide,...

  16. 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.

  17. 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.

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

    OpenAIRE

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

    2009-01-01

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

  19. 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...

  20. 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.

  1. 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.

  2. XLPM: efficient algorithm for the analysis of protein-protein contacts using chemical cross-linking mass spectrometry

    OpenAIRE

    Jaiswal, Mihir; Crabtree, Nathaniel Mark; Bauer, Michael A; Hall, Roger; Raney, Kevin D.; Boris L Zybailov

    2014-01-01

    Background Chemical cross-linking is used for protein-protein contacts mapping and for structural analysis. One of the difficulties in cross-linking studies is the analysis of mass-spectrometry data and the assignment of the site of cross-link incorporation. The difficulties are due to higher charges of fragment ions, and to the overall low-abundance of cross-link species in the background of linear peptides. Cross-linkers non-specific at one end, such as photo-inducible diazirines, may compl...

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

    OpenAIRE

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

    2002-01-01

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

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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...

  9. 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-...

  10. 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'.

  11. 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.

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

    Science.gov (United States)

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

    2016-04-21

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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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...

  20. Binary nucleation beyond capillarity approximation

    OpenAIRE

    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 is taken into account within Gibbsian approximation. Binary clusters are treated by means of statistical-mechanical considerations: tracing out the molecular degrees of freedom of the more volatil...

  1. Coalescence of Binary Neutron Stars

    OpenAIRE

    Oohara, Ken-ichi; Namamura, Takashi

    1996-01-01

    The most important sources for laser-interferometric gravitational-wave detectors like LIGO or VIRGO are catastrophic events such as coalescence of a neutron-star binary. The final phase, or the last three milliseconds, of coalescence is considered. We describe results of numerical simulations of coalescing binary neutron stars using Newtonian and post-Newtonian hydrodynamics code and then discuss recent development of our 3D GR code.

  2. 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...

  3. 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

  4. 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.

  5. Binary Encodings of Non-binary Constraint Satisfaction Problems: Algorithms and Experimental Results

    CERN Document Server

    Samaras, N; 10.1613/jair.1776

    2011-01-01

    A non-binary Constraint Satisfaction Problem (CSP) can be solved directly using extended versions of binary techniques. Alternatively, the non-binary problem can be translated into an equivalent binary one. In this case, it is generally accepted that the translated problem can be solved by applying well-established techniques for binary CSPs. In this paper we evaluate the applicability of the latter approach. We demonstrate that the use of standard techniques for binary CSPs in the encodings of non-binary problems is problematic and results in models that are very rarely competitive with the non-binary representation. To overcome this, we propose specialized arc consistency and search algorithms for binary encodings, and we evaluate them theoretically and empirically. We consider three binary representations; the hidden variable encoding, the dual encoding, and the double encoding. Theoretical and empirical results show that, for certain classes of non-binary constraints, binary encodings are a competitive op...

  6. 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.

  7. Investigation of Protein - Protein Interactions by Surface Plasmon Resonance%表面等离子体共振技术在蛋白质-蛋白质相互作用研究中的应用

    Institute of Scientific and Technical Information of China (English)

    杨彦; 戴宗; 邹小勇

    2009-01-01

    The technique of surface plasmon resonance(SPR) has been rapidly developed to investigate the interactions of biomolecules in recent years due to its exceptional capabilities with respects to label-free, specificity, sensitivity, sample dosage, real-time and online detection. Recently, the applications of SPR have been extended to immunology, proteomic, drug screening, cellular signal transduction, ligand/receptor fishing and so on. In this paper, the principle and the experimental design of biosensor chip technology of SPR biosensors was firstly briefly described. Its application on protein - protein interaction, including dynamic study by measuring the equilibrium binding constants , the association - dissociation rates, structure - function study, mutation and fragment analysis, and signal transduction were reviewed. In addition, several key techniques of SPR technology used in protein - protein interaction study, including surface modification of the sensor chip, methods to resist non-specific adsorption and surface regeneration, were discussed. When coupled with other spectral, electrochemical techniques, SPR biosensors can extend the capability to obtain more specific interfacing properties during the protein - protein interaction process.%表面等离子共振(SPR)近年来迅速发展为用于分析生物分子相互作用的一项技术.该技术无需标记、特异性强、灵敏度高、样品用量小,可实现在线连续实时检测.目前SPR已被广泛应用于免疫学、蛋白质组学、药物筛选、细胞信号转导、受体/配体垂钓等领域.该文阐述了基于表面等离子体共振技术生物传感器的基本原理和技术流程,综述了SPR在蛋白质-蛋白质相互作用动力学研究、蛋白质结构及功能研究、蛋白质突变和碎片分析、信号转导中的应用以及SPR在蛋白质-蛋白质相互作用研究中的多项关键技术.指出SPR通过与光谱、电化学等多技术联用后,可以获得更加详实的信息.

  8. 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

  9. 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

  10. 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...

  11. 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). PMID:16661764

  12. Binaries and Globular Cluster Dynamics

    CERN Document Server

    Rasio, F A; Joshi, K J; Rasio, Frederic A.; Fregeau, John M.; Joshi, Kriten J.

    2001-01-01

    We summarize the results of recent theoretical work on the dynamical evolution of globular clusters containing primordial binaries. Even a very small initial binary fraction (e.g., 10%) can play a key role in supporting a cluster against gravothermal collapse for many relaxation times. Inelastic encounters between binaries and single stars or other binaries provide a very significant energy source for the cluster. These dynamical interactions also lead to the production of large numbers of exotic systems such as ultracompact X-ray binaries, recycled radio pulsars, double degenerate systems, and blue stragglers. Our work is based on a new parallel supercomputer code implementing Henon's Monte Carlo method for simulating the dynamical evolution of dense stellar systems in the Fokker-Planck approximation. This new code allows us to calculate very accurately the evolution of a cluster containing a realistic number of stars (N ~ 10^5 - 10^6) in typically a few hours to a few days of computing time. The discrete, s...

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2015-03-01

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

  15. 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.

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  18. 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

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

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    Brann Jessica H

    2010-05-01

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

  20. Characterizing changes in the rate of protein-protein dissociation upon interface mutation using hotspot energy and organization.

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    Rudi Agius

    Full Text Available Predicting the effects of mutations on the kinetic rate constants of protein-protein interactions is central to both the modeling of complex diseases and the design of effective peptide drug inhibitors. However, while most studies have concentrated on the determination of association rate constants, dissociation rates have received less attention. In this work we take a novel approach by relating the changes in dissociation rates upon mutation to the energetics and architecture of hotspots and hotregions, by performing alanine scans pre- and post-mutation. From these scans, we design a set of descriptors that capture the change in hotspot energy and distribution. The method is benchmarked on 713 kinetically characterized mutations from the SKEMPI database. Our investigations show that, with the use of hotspot descriptors, energies from single-point alanine mutations may be used for the estimation of off-rate mutations to any residue type and also multi-point mutations. A number of machine learning models are built from a combination of molecular and hotspot descriptors, with the best models achieving a Pearson's Correlation Coefficient of 0.79 with experimental off-rates and a Matthew's Correlation Coefficient of 0.6 in the detection of rare stabilizing mutations. Using specialized feature selection models we identify descriptors that are highly specific and, conversely, broadly important to predicting the effects of different classes of mutations, interface regions and complexes. Our results also indicate that the distribution of the critical stability regions across protein-protein interfaces is a function of complex size more strongly than interface area. In addition, mutations at the rim are critical for the stability of small complexes, but consistently harder to characterize. The relationship between hotregion size and the dissociation rate is also investigated and, using hotspot descriptors which model cooperative effects within