WorldWideScience

Sample records for underlying protein interactions

  1. Concentration Dependent Ion-Protein Interaction Patterns Underlying Protein Oligomerization Behaviours

    Science.gov (United States)

    Batoulis, Helena; Schmidt, Thomas H.; Weber, Pascal; Schloetel, Jan-Gero; Kandt, Christian; Lang, Thorsten

    2016-04-01

    Salts and proteins comprise two of the basic molecular components of biological materials. Kosmotropic/chaotropic co-solvation and matching ion water affinities explain basic ionic effects on protein aggregation observed in simple solutions. However, it is unclear how these theories apply to proteins in complex biological environments and what the underlying ionic binding patterns are. Using the positive ion Ca2+ and the negatively charged membrane protein SNAP25, we studied ion effects on protein oligomerization in solution, in native membranes and in molecular dynamics (MD) simulations. We find that concentration-dependent ion-induced protein oligomerization is a fundamental chemico-physical principle applying not only to soluble but also to membrane-anchored proteins in their native environment. Oligomerization is driven by the interaction of Ca2+ ions with the carboxylate groups of aspartate and glutamate. From low up to middle concentrations, salt bridges between Ca2+ ions and two or more protein residues lead to increasingly larger oligomers, while at high concentrations oligomers disperse due to overcharging effects. The insights provide a conceptual framework at the interface of physics, chemistry and biology to explain binding of ions to charged protein surfaces on an atomistic scale, as occurring during protein solubilisation, aggregation and oligomerization both in simple solutions and membrane systems.

  2. Molecular mechanisms underlying the interaction of protein phosphatase-1c with ASPP proteins.

    Science.gov (United States)

    Skene-Arnold, Tamara D; Luu, Hue Anh; Uhrig, R Glen; De Wever, Veerle; Nimick, Mhairi; Maynes, Jason; Fong, Andrea; James, Michael N G; Trinkle-Mulcahy, Laura; Moorhead, Greg B; Holmes, Charles F B

    2013-02-01

    The serine/threonine PP-1c (protein phosphatase-1 catalytic subunit) is regulated by association with multiple regulatory subunits. Human ASPPs (apoptosis-stimulating proteins of p53) comprise three family members: ASPP1, ASPP2 and iASPP (inhibitory ASPP), which is uniquely overexpressed in many cancers. While ASPP2 and iASPP are known to bind PP-1c, we now identify novel and distinct molecular interactions that allow all three ASPPs to bind differentially to PP-1c isoforms and p53. iASPP lacks a PP-1c-binding RVXF motif; however, we show it interacts with PP-1c via a RARL sequence with a Kd value of 26 nM. Molecular modelling and mutagenesis of PP-1c-ASPP protein complexes identified two additional modes of interaction. First, two positively charged residues, Lys260 and Arg261 on PP-1c, interact with all ASPP family members. Secondly, the C-terminus of the PP-1c α, β and γ isoforms contain a type-2 SH3 (Src homology 3) poly-proline motif (PxxPxR), which binds directly to the SH3 domains of ASPP1, ASPP2 and iASPP. In PP-1cγ this comprises residues 309-314 (PVTPPR). When the Px(T)PxR motif is deleted or mutated via insertion of a phosphorylation site mimic (T311D), PP-1c fails to bind to all three ASPP proteins. Overall, we provide the first direct evidence for PP-1c binding via its C-terminus to an SH3 protein domain.

  3. Conformational transitions and interactions underlying the function of membrane embedded receptor protein kinases.

    Science.gov (United States)

    Bocharov, Eduard V; Sharonov, Georgy V; Bocharova, Olga V; Pavlov, Konstantin V

    2017-09-01

    Among membrane receptors, the single-span receptor protein kinases occupy a broad but specific functional niche determined by distinctive features of the underlying transmembrane signaling mechanisms that are briefly overviewed on the basis of some of the most representative examples, followed by a more detailed discussion of several hierarchical levels of organization and interactions involved. All these levels, including single-molecule interactions (e.g., dimerization, liganding, chemical modifications), local processes (e.g. lipid membrane perturbations, cytoskeletal interactions), and larger scale phenomena (e.g., effects of membrane surface shape or electrochemical potential gradients) appear to be closely integrated to achieve the observed diversity of the receptor functioning. Different species of receptor protein kinases meet their specific functional demands through different structural features defining their responses to stimulation, but certain common patterns exist. Signaling by receptor protein kinases is typically associated with the receptor dimerization and clustering, ligand-induced rearrangements of receptor domains through allosteric conformational transitions with involvement of lipids, release of the sequestered lipids, restriction of receptor diffusion, cytoskeleton and membrane shape remodeling. Understanding of complexity and continuity of the signaling processes can help identifying currently neglected opportunities for influencing the receptor signaling with potential therapeutic implications. This article is part of a Special Issue entitled: Interactions between membrane receptors in cellular membranes edited by Kalina Hristova. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Protein-protein interactions

    DEFF Research Database (Denmark)

    Byron, Olwyn; Vestergaard, Bente

    2015-01-01

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

  5. Cytoplasmic FMR1-Interacting Protein 2 Is a Major Genetic Factor Underlying Binge Eating.

    Science.gov (United States)

    Kirkpatrick, Stacey L; Goldberg, Lisa R; Yazdani, Neema; Babbs, R Keith; Wu, Jiayi; Reed, Eric R; Jenkins, David F; Bolgioni, Amanda F; Landaverde, Kelsey I; Luttik, Kimberly P; Mitchell, Karen S; Kumar, Vivek; Johnson, W Evan; Mulligan, Megan K; Cottone, Pietro; Bryant, Camron D

    2017-05-01

    Eating disorders are lethal and heritable; however, the underlying genetic factors are unknown. Binge eating is a highly heritable trait associated with eating disorders that is comorbid with mood and substance use disorders. Therefore, understanding its genetic basis will inform therapeutic development that could improve several comorbid neuropsychiatric conditions. We assessed binge eating in closely related C57BL/6 mouse substrains and in an F 2 cross to identify quantitative trait loci associated with binge eating. We used gene targeting to validate candidate genetic factors. Finally, we used transcriptome analysis of the striatum via messenger RNA sequencing to identify the premorbid transcriptome and the binge-induced transcriptome to inform molecular mechanisms mediating binge eating susceptibility and establishment. C57BL/6NJ but not C57BL/6J mice showed rapid and robust escalation in palatable food consumption. We mapped a single genome-wide significant quantitative trait locus on chromosome 11 (logarithm of the odds = 7.4) to a missense mutation in cytoplasmic FMR1-interacting protein 2 (Cyfip2). We validated Cyfip2 as a major genetic factor underlying binge eating in heterozygous knockout mice on a C57BL/6N background that showed reduced binge eating toward a wild-type C57BL/6J-like level. Transcriptome analysis of premorbid genetic risk identified the enrichment terms morphine addiction and retrograde endocannabinoid signaling, whereas binge eating resulted in the downregulation of a gene set enriched for decreased myelination, oligodendrocyte differentiation, and expression. We identified Cyfip2 as a major significant genetic factor underlying binge eating and provide a behavioral paradigm for future genome-wide association studies in populations with increased genetic complexity. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  6. 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...

  7. Study of protein-protein interactions in under saturated and supersaturated lysozyme solutions in heavy water as a function of temperature

    International Nuclear Information System (INIS)

    Gripon, C.; Legrand, L.; Rosenman, I.; Vidal, O.; Robert, M.C.; Boue, F.

    1996-01-01

    We have studied freshly prepared lysozyme solutions in heavy water for two NaCl concentrations as a function of temperature. Lysozyme solubilities in this solvent are determined by static light scattering. By small angle neutron scattering, we evidence that interactions between lysozyme molecules are characterized by a second virial coefficient A 2 whether the solution is under-saturated or supersaturated. From the variation of A 2 as a function of temperature we have evaluated the enthalpy corresponding to the interaction between lysozyme molecules. We show that the interactions between protein molecules are higher in heavy water than in light water. (authors). 13 refs., 3 figs

  8. Lipid interaction converts prion protein to a PrPSc-like proteinase K-resistant conformation under physiological conditions.

    Science.gov (United States)

    Wang, Fei; Yang, Fan; Hu, Yunfei; Wang, Xu; Wang, Xinhe; Jin, Changwen; Ma, Jiyan

    2007-06-12

    The conversion of prion protein (PrP) to the pathogenic PrPSc conformation is central to prion disease. Previous studies revealed that PrP interacts with lipids and the interaction induces PrP conformational changes, yet it remains unclear whether in the absence of any denaturing treatment, PrP-lipid interaction is sufficient to convert PrP to the classic proteinase K-resistant conformation. Using recombinant mouse PrP, we analyzed PrP-lipid interaction under physiological conditions and followed lipid-induced PrP conformational change with proteinase K (PK) digestion. We found that the PrP-lipid interaction was initiated by electrostatic contact and followed by hydrophobic interaction. The PrP-lipid interaction converted full-length alpha-helix-rich recombinant PrP to different forms. A significant portion of PrP gained a conformation reminiscent of PrPSc, with a PrPSc-like PK-resistant core and increased beta-sheet content. The efficiency for lipid-induced PrP conversion depended on lipid headgroup structure and/or the arrangement of lipids on the surface of vesicles. When lipid vesicles were disrupted by Triton X-100, PrP aggregation was necessary to maintain the lipid-induced PrPSc-like conformation. However, the PK resistance of lipid-induced PrPSc-like conformation does not depend on amyloid fiber formation. Our results clearly revealed that the lipid interaction can overcome the energy barrier and convert full-length alpha-helix-rich PrP to a PrPSc-like conformation under physiological conditions, supporting the relevance of lipid-induced PrP conformational change to in vivo PrP conversion.

  9. Aquaporin Protein-Protein Interactions

    Directory of Open Access Journals (Sweden)

    Jennifer Virginia Roche

    2017-10-01

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

  10. Our interests in protein-protein interactions

    Indian Academy of Sciences (India)

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

  11. Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology

    DEFF Research Database (Denmark)

    Rossin, Elizabeth J.; Hansen, Kasper Lage; Raychaudhuri, Soumya

    2011-01-01

    in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein-protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more...... that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non...... evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease....

  12. Protein–protein interactions

    OpenAIRE

    Janin, J.; Bonvin, A.M.J.J.

    2013-01-01

    We are proud to present the first edition of the Protein–protein interactions Section of Current Opinion in Structural Biology. The Section is new, but the topic has been present in the journal from the very start. Volume 1, Issue 1, dated February 1991, had a review by Janin entitled Protein–protein interactions and assembly, and others by Bode and Huber on Proteinase–inhibitor interaction, and by Chothia on Antigen recognition. The Editorial Overview, signed by TE Creighton and PS Kim, note...

  13. Interactive protein manipulation

    Energy Technology Data Exchange (ETDEWEB)

    SNCrivelli@lbl.gov

    2003-07-01

    We describe an interactive visualization and modeling program for the creation of protein structures ''from scratch''. The input to our program is an amino acid sequence -decoded from a gene- and a sequence of predicted secondary structure types for each amino acid-provided by external structure prediction programs. Our program can be used in the set-up phase of a protein structure prediction process; the structures created with it serve as input for a subsequent global internal energy minimization, or another method of protein structure prediction. Our program supports basic visualization methods for protein structures, interactive manipulation based on inverse kinematics, and visualization guides to aid a user in creating ''good'' initial structures.

  14. Interactive protein manipulation

    International Nuclear Information System (INIS)

    2003-01-01

    We describe an interactive visualization and modeling program for the creation of protein structures ''from scratch''. The input to our program is an amino acid sequence -decoded from a gene- and a sequence of predicted secondary structure types for each amino acid-provided by external structure prediction programs. Our program can be used in the set-up phase of a protein structure prediction process; the structures created with it serve as input for a subsequent global internal energy minimization, or another method of protein structure prediction. Our program supports basic visualization methods for protein structures, interactive manipulation based on inverse kinematics, and visualization guides to aid a user in creating ''good'' initial structures

  15. Ontological visualization of protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Hill David P

    2005-02-01

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

  16. Interaction proteins of invertase and invertase inhibitor in cold-stored potato tubers suggested a protein complex underlying post-translational regulation of invertase.

    Science.gov (United States)

    Lin, Yuan; Liu, Jun; Liu, Xun; Ou, Yongbin; Li, Meng; Zhang, Huiling; Song, Botao; Xie, Conghua

    2013-12-01

    The activity of vacuolar invertase (VI) is vital to potato cold-induced sweetening (CIS). A post-translational regulation of VI activity has been proposed which involves invertase inhibitor (VIH), but the mechanism for the interaction between VI and VIH has not been fully understood. To identify the potential partners of VI and VIH, two cDNA libraries were respectively constructed from CIS-resistant wild potato species Solanum berthaultii and CIS-sensitive potato cultivar AC035-01 for the yeast two-hybrid analysis. The StvacINV1 (one of the potato VIs) and StInvInh2B (one of the potato VIHs), previously identified to be associated with potato CIS, were used as baits to screen the two libraries. Through positive selection and sequencing, 27 potential target proteins of StvacINV1 and eight of StInvInh2B were clarified. The Kunitz-type protein inhibitors were captured by StvacINV1 in both libraries and the interaction between them was confirmed by bimolecular fluorescence complementation assay in tobacco cells, reinforcing a fundamental interaction between VI and VIH. Notably, a sucrose non-fermenting-1-related protein kinase 1 was captured by both the baits, suggesting that a protein complex could be necessary for fine turning of the invertase activity. The target proteins clarified in present research provide a route to elucidate the mechanism by which the VI activity can be subtly modulated. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  17. Evolution of protein-protein interactions

    Indian Academy of Sciences (India)

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

  18. Multimodal Interaction with BCL-2 Family Proteins Underlies the Pro-Apoptotic Activity of PUMA BH3

    Science.gov (United States)

    Edwards, Amanda L.; Gavathiotis, Evripidis; LaBelle, James L.; Braun, Craig R.; Opoku-Nsiah, Kwadwo A.; Bird, Gregory H.; Walensky, Loren D.

    2013-01-01

    SUMMARY PUMA is a pro-apoptotic BCL-2 family member that drives the apoptotic response to a diversity of p53-dependent and independent cellular insults. Deciphering the spectrum of PUMA interactions that confer its context-dependent pro-apoptotic properties remains a high priority goal. Here, we report the synthesis of PUMA SAHBs, structurally-stabilized PUMA BH3 helices that, in addition to broadly targeting anti-apoptotic proteins, directly bind to BAX. NMR, photocrosslinking, and biochemical analyses revealed that PUMA SAHBs engage an α1/α6 trigger site on BAX to initiate its functional activation. We further demonstrated that a cell-permeable PUMA SAHB analog induces apoptosis in neuroblastoma cells and, like expressed PUMA protein, engages BCL-2, MCL-1 and BAX. Thus, we find that PUMA BH3 is a dual anti-apoptotic inhibitor and pro-apoptotic direct activator, and its mimetics may serve as effective pharmacologic triggers of apoptosis in resistant human cancers. PMID:23890007

  19. Novel near-infrared BiFC systems from a bacterial phytochrome for imaging protein interactions and drug evaluation under physiological conditions.

    Science.gov (United States)

    Chen, Minghai; Li, Wei; Zhang, Zhiping; Liu, Sanying; Zhang, Xiaowei; Zhang, Xian-En; Cui, Zongqiang

    2015-04-01

    Monitoring protein-protein interactions (PPIs) in live subjects is critical for understanding these fundamental biological processes. Bimolecular fluorescence complementation (BiFC) provides a good technique for imaging PPIs; however, a BiFC system with a long wavelength remains to be pursued for in vivo imaging. Here, we conducted systematic screening of split reporters from a bacterial phytochrome-based, near-infrared fluorescent protein (iRFP). Several new near-infrared phytochrome BiFC systems were built based on selected split sites including the amino acids residues 97/98, 99/100, 122/123, and 123/124. These new near-infrared BiFC systems from a bacterial phytochrome were verified as powerful tools for imaging PPIs under physiological conditions in live cells and in live mice. The interaction between HIV-1 integrase (IN) and cellular cofactor protein Lens epithelium-derived growth factor (LEDGF/p75) was visualized in live cells using the newly constructed iRFP BiFC system because of its important roles in HIV-1 integration and replication. Because the HIV IN-LEDGF/p75 interaction is an attractive anti-HIV target, drug evaluation assays to inhibit the HIV IN-LEDGF/p75 interaction were also performed using the newly constructed BiFC system. The results showed that compound 6 and carbidopa inhibit the HIV IN-LEDGF/p75 interaction in a dose-dependent manner under physiological conditions in the BiFC assays. This study provides novel near-infrared BiFC systems for imaging protein interactions under physiological conditions and provides guidance for splitting other bacterial phytochrome-like proteins to construct BiFC systems. The study also provides a new method for drug evaluation in live cells based on iRFP BiFC systems and supplies some new information regarding candidate drugs for anti-HIV therapies. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Transient interactions between photosynthetic proteins

    NARCIS (Netherlands)

    Hulsker, Rinske

    2008-01-01

    The biological processes that are the basis of all life forms are mediated largely by protein-protein interactions. The protein complexes involved in these interactions can be categorised by their affinity, which results in a range from static to transient complexes. Electron transfer complexes,

  1. The interactive effect of dietary protein and vitamin levels on the depression of gonadal development in growing male rats kept under disturbed daily rhythm.

    Science.gov (United States)

    Hanai, Miho; Esashi, Takatoshi

    2007-04-01

    The purpose of this study was to clarify the effects of nutrients on the gonadal development of male rats kept under constant darkness as a model of disturbed daily rhythm. The present study examined protein and vitamins, and their interactions. This study was based on three-way ANOVA; the three factors were lighting conditions, dietary protein and dietary vitamins, respectively. The levels of dietary protein were low or normal: 9% casein or 20% casein. The levels of dietary vitamins were low, normal or high: 1/3.3 of normal (AIN-93G diet) content, normal content, or three times the normal content, respectively. Other compositions were the same as those of the AIN-93G diet, and six kinds of experimental diet were prepared. Four-week-old rats (Fischer 344 strain) were kept under constant darkness or normal lighting (12-h light/dark cycle) for 4 wk. After 4 wk, the gonadal weights and serum testosterone content were evaluated. In the constant darkness groups (D-groups), the low-protein diet induced reduction of gonadal organ weights and serum testosterone concentrations. This reduction of gonadal organ weights was exacerbated by progressively higher levels of dietary vitamins. In the case of a normal-protein diet, the depression of gonadal development was not accelerated by high-vitamin intake. In the normal lighting groups (N-groups), the low-protein and high-vitamin diet slightly depressed gonadal development. These results suggest that the metabolism of protein and vitamins is different in rats being kept under constant darkness, and that excess dietary vitamins have an adverse effect on gonadal development in rats fed a low-protein diet.

  2. A conserved mammalian protein interaction network.

    Directory of Open Access Journals (Sweden)

    Åsa Pérez-Bercoff

    Full Text Available Physical interactions between proteins mediate a variety of biological functions, including signal transduction, physical structuring of the cell and regulation. While extensive catalogs of such interactions are known from model organisms, their evolutionary histories are difficult to study given the lack of interaction data from phylogenetic outgroups. Using phylogenomic approaches, we infer a upper bound on the time of origin for a large set of human protein-protein interactions, showing that most such interactions appear relatively ancient, dating no later than the radiation of placental mammals. By analyzing paired alignments of orthologous and putatively interacting protein-coding genes from eight mammals, we find evidence for weak but significant co-evolution, as measured by relative selective constraint, between pairs of genes with interacting proteins. However, we find no strong evidence for shared instances of directional selection within an interacting pair. Finally, we use a network approach to show that the distribution of selective constraint across the protein interaction network is non-random, with a clear tendency for interacting proteins to share similar selective constraints. Collectively, the results suggest that, on the whole, protein interactions in mammals are under selective constraint, presumably due to their functional roles.

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

    Directory of Open Access Journals (Sweden)

    Peng Liu

    2015-01-01

    Full Text Available A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

  4. 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.

  5. Information assessment on predicting protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Gerstein Mark

    2004-10-01

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

  6. Interaction between plate make and protein in protein crystallisation screening.

    Directory of Open Access Journals (Sweden)

    Gordon J King

    Full Text Available BACKGROUND: Protein crystallisation screening involves the parallel testing of large numbers of candidate conditions with the aim of identifying conditions suitable as a starting point for the production of diffraction quality crystals. Generally, condition screening is performed in 96-well plates. While previous studies have examined the effects of protein construct, protein purity, or crystallisation condition ingredients on protein crystallisation, few have examined the effect of the crystallisation plate. METHODOLOGY/PRINCIPAL FINDINGS: We performed a statistically rigorous examination of protein crystallisation, and evaluated interactions between crystallisation success and plate row/column, different plates of same make, different plate makes and different proteins. From our analysis of protein crystallisation, we found a significant interaction between plate make and the specific protein being crystallised. CONCLUSIONS/SIGNIFICANCE: Protein crystal structure determination is the principal method for determining protein structure but is limited by the need to produce crystals of the protein under study. Many important proteins are difficult to crystallize, so that identification of factors that assist crystallisation could open up the structure determination of these more challenging targets. Our findings suggest that protein crystallisation success may be improved by matching a protein with its optimal plate make.

  7. Database of Interacting Proteins (DIP)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The DIP database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent...

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

    Directory of Open Access Journals (Sweden)

    Barkallah Insaf

    2009-04-01

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

  9. Carbohydrate-Aromatic Interactions in Proteins.

    Science.gov (United States)

    Hudson, Kieran L; Bartlett, Gail J; Diehl, Roger C; Agirre, Jon; Gallagher, Timothy; Kiessling, Laura L; Woolfson, Derek N

    2015-12-09

    Protein-carbohydrate interactions play pivotal roles in health and disease. However, defining and manipulating these interactions has been hindered by an incomplete understanding of the underlying fundamental forces. To elucidate common and discriminating features in carbohydrate recognition, we have analyzed quantitatively X-ray crystal structures of proteins with noncovalently bound carbohydrates. Within the carbohydrate-binding pockets, aliphatic hydrophobic residues are disfavored, whereas aromatic side chains are enriched. The greatest preference is for tryptophan with an increased prevalence of 9-fold. Variations in the spatial orientation of amino acids around different monosaccharides indicate specific carbohydrate C-H bonds interact preferentially with aromatic residues. These preferences are consistent with the electronic properties of both the carbohydrate C-H bonds and the aromatic residues. Those carbohydrates that present patches of electropositive saccharide C-H bonds engage more often in CH-π interactions involving electron-rich aromatic partners. These electronic effects are also manifested when carbohydrate-aromatic interactions are monitored in solution: NMR analysis indicates that indole favorably binds to electron-poor C-H bonds of model carbohydrates, and a clear linear free energy relationships with substituted indoles supports the importance of complementary electronic effects in driving protein-carbohydrate interactions. Together, our data indicate that electrostatic and electronic complementarity between carbohydrates and aromatic residues play key roles in driving protein-carbohydrate complexation. Moreover, these weak noncovalent interactions influence which saccharide residues bind to proteins, and how they are positioned within carbohydrate-binding sites.

  10. 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

  11. Intercellular protein-protein interactions at synapses.

    Science.gov (United States)

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

    2014-06-01

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

  12. Analysis of Protein-Membrane Interactions

    DEFF Research Database (Denmark)

    Kemmer, Gerdi Christine

    interactions between proteins and lipids. First, interactions of soluble proteins with membranes and specific lipids were studied, using two proteins: Annexin V and Tma1. The protein was first subjected to a lipid/protein overlay assay to identify candidate interaction partners in a fast and efficient way...

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

    Science.gov (United States)

    Waldo, Geoffrey S.; Cabantous, Stephanie

    2010-02-23

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

  14. NMR Studies of Protein Hydration and Protein-Ligand Interactions

    Science.gov (United States)

    Chong, Yuan

    Water on the surface of a protein is called hydration water. Hydration water is known to play a crucial role in a variety of biological processes including protein folding, enzymatic activation, and drug binding. Although the significance of hydration water has been recognized, the underlying mechanism remains far from being understood. This dissertation employs a unique in-situ nuclear magnetic resonance (NMR) technique to study the mechanism of protein hydration and the role of hydration in alcohol-protein interactions. Water isotherms in proteins are measured at different temperatures via the in-situ NMR technique. Water is found to interact differently with hydrophilic and hydrophobic groups on the protein. Water adsorption on hydrophilic groups is hardly affected by the temperature, while water adsorption on hydrophobic groups strongly depends on the temperature around 10 C, below which the adsorption is substantially reduced. This effect is induced by the dramatic decrease in the protein flexibility below 10 C. Furthermore, nanosecond to microsecond protein dynamics and the free energy, enthalpy, and entropy of protein hydration are studied as a function of hydration level and temperature. A crossover at 10 C in protein dynamics and thermodynamics is revealed. The effect of water at hydrophilic groups on protein dynamics and thermodynamics shows little temperature dependence, whereas water at hydrophobic groups has stronger effect above 10 C. In addition, I investigate the role of water in alcohol binding to the protein using the in-situ NMR detection. The isotherms of alcohols are first measured on dry proteins, then on proteins with a series of controlled hydration levels. The free energy, enthalpy, and entropy of alcohol binding are also determined. Two distinct types of alcohol binding are identified. On the one hand, alcohols can directly bind to a few specific sites on the protein. This type of binding is independent of temperature and can be

  15. Topology and weights in a protein domain interaction network – a novel way to predict protein interactions

    Directory of Open Access Journals (Sweden)

    Wuchty Stefan

    2006-05-01

    Full Text Available Abstract Background While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. Results We consider a web of interactions between protein domains of the Protein Family database (PFAM, which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Conclusion Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we

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

    Science.gov (United States)

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

    2013-05-01

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

  17. Carbohydrate–Aromatic Interactions in Proteins

    Science.gov (United States)

    2015-01-01

    Protein–carbohydrate interactions play pivotal roles in health and disease. However, defining and manipulating these interactions has been hindered by an incomplete understanding of the underlying fundamental forces. To elucidate common and discriminating features in carbohydrate recognition, we have analyzed quantitatively X-ray crystal structures of proteins with noncovalently bound carbohydrates. Within the carbohydrate-binding pockets, aliphatic hydrophobic residues are disfavored, whereas aromatic side chains are enriched. The greatest preference is for tryptophan with an increased prevalence of 9-fold. Variations in the spatial orientation of amino acids around different monosaccharides indicate specific carbohydrate C–H bonds interact preferentially with aromatic residues. These preferences are consistent with the electronic properties of both the carbohydrate C–H bonds and the aromatic residues. Those carbohydrates that present patches of electropositive saccharide C–H bonds engage more often in CH−π interactions involving electron-rich aromatic partners. These electronic effects are also manifested when carbohydrate–aromatic interactions are monitored in solution: NMR analysis indicates that indole favorably binds to electron-poor C–H bonds of model carbohydrates, and a clear linear free energy relationships with substituted indoles supports the importance of complementary electronic effects in driving protein–carbohydrate interactions. Together, our data indicate that electrostatic and electronic complementarity between carbohydrates and aromatic residues play key roles in driving protein–carbohydrate complexation. Moreover, these weak noncovalent interactions influence which saccharide residues bind to proteins, and how they are positioned within carbohydrate-binding sites. PMID:26561965

  18. Mass spectrometric analysis of protein interactions

    DEFF Research Database (Denmark)

    Borch, Jonas; Jørgensen, Thomas J. D.; Roepstorff, Peter

    2005-01-01

    Mass spectrometry is a powerful tool for identification of interaction partners and structural characterization of protein interactions because of its high sensitivity, mass accuracy and tolerance towards sample heterogeneity. Several tools that allow studies of protein interaction are now availa...... labels, cleavable cross-linkers or fragment ions. The use of mass spectrometers to study protein interactions using deuterium exchange and for analysis of intact protein complexes recently has progressed considerably....

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

    Science.gov (United States)

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

    2011-12-01

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

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

    Science.gov (United States)

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

    2011-01-01

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

  1. PCorral--interactive mining of protein interactions from MEDLINE.

    Science.gov (United States)

    Li, Chen; Jimeno-Yepes, Antonio; Arregui, Miguel; Kirsch, Harald; Rebholz-Schuhmann, Dietrich

    2013-01-01

    The extraction of information from the scientific literature is a complex task-for researchers doing manual curation and for automatic text processing solutions. The identification of protein-protein interactions (PPIs) requires the extraction of protein named entities and their relations. Semi-automatic interactive support is one approach to combine both solutions for efficient working processes to generate reliable database content. In principle, the extraction of PPIs can be achieved with different methods that can be combined to deliver high precision and/or high recall results in different combinations at the same time. Interactive use can be achieved, if the analytical methods are fast enough to process the retrieved documents. PCorral provides interactive mining of PPIs from the scientific literature allowing curators to skim MEDLINE for PPIs at low overheads. The keyword query to PCorral steers the selection of documents, and the subsequent text analysis generates high recall and high precision results for the curator. The underlying components of PCorral process the documents on-the-fly and are available, as well, as web service from the Whatizit infrastructure. The human interface summarizes the identified PPI results, and the involved entities are linked to relevant resources and databases. Altogether, PCorral serves curator at both the beginning and the end of the curation workflow for information retrieval and information extraction. Database URL: http://www.ebi.ac.uk/Rebholz-srv/pcorral.

  2. Drosophila Protein interaction Map (DPiM)

    OpenAIRE

    Guruharsha, K.G.; Obar, Robert A.; Mintseris, Julian; Aishwarya, K.; Krishnan, R.T.; VijayRaghavan, K.; Artavanis-Tsakonas, Spyros

    2012-01-01

    Proteins perform essential cellular functions as part of protein complexes, often in conjunction with RNA, DNA, metabolites and other small molecules. The genome encodes thousands of proteins but not all of them are expressed in every cell type; and expressed proteins are not active at all times. Such diversity of protein expression and function accounts for the level of biological intricacy seen in nature. Defining protein-protein interactions in protein complexes, and establishing the when,...

  3. Functional module identification in protein interaction networks by interaction patterns

    Science.gov (United States)

    Wang, Yijie; Qian, Xiaoning

    2014-01-01

    Motivation: Identifying functional modules in protein–protein interaction (PPI) networks may shed light on cellular functional organization and thereafter underlying cellular mechanisms. Many existing module identification algorithms aim to detect densely connected groups of proteins as potential modules. However, based on this simple topological criterion of ‘higher than expected connectivity’, those algorithms may miss biologically meaningful modules of functional significance, in which proteins have similar interaction patterns to other proteins in networks but may not be densely connected to each other. A few blockmodel module identification algorithms have been proposed to address the problem but the lack of global optimum guarantee and the prohibitive computational complexity have been the bottleneck of their applications in real-world large-scale PPI networks. Results: In this article, we propose a novel optimization formulation LCP2 (low two-hop conductance sets) using the concept of Markov random walk on graphs, which enables simultaneous identification of both dense and sparse modules based on protein interaction patterns in given networks through searching for LCP2 by random walk. A spectral approximate algorithm SLCP2 is derived to identify non-overlapping functional modules. Based on a bottom-up greedy strategy, we further extend LCP2 to a new algorithm (greedy algorithm for LCP2) GLCP2 to identify overlapping functional modules. We compare SLCP2 and GLCP2 with a range of state-of-the-art algorithms on synthetic networks and real-world PPI networks. The performance evaluation based on several criteria with respect to protein complex prediction, high level Gene Ontology term prediction and especially sparse module detection, has demonstrated that our algorithms based on searching for LCP2 outperform all other compared algorithms. Availability and implementation: All data and code are available at http://www.cse.usf.edu/∼xqian/fmi/slcp2hop

  4. Towards Inferring Protein Interactions: Challenges and Solutions

    Directory of Open Access Journals (Sweden)

    Ji Xiang

    2006-01-01

    Full Text Available Discovering interacting proteins has been an essential part of functional genomics. However, existing experimental techniques only uncover a small portion of any interactome. Furthermore, these data often have a very high false rate. By conceptualizing the interactions at domain level, we provide a more abstract representation of interactome, which also facilitates the discovery of unobserved protein-protein interactions. Although several domain-based approaches have been proposed to predict protein-protein interactions, they usually assume that domain interactions are independent on each other for the convenience of computational modeling. A new framework to predict protein interactions is proposed in this paper, where no assumption is made about domain interactions. Protein interactions may be the result of multiple domain interactions which are dependent on each other. A conjunctive norm form representation is used to capture the relationships between protein interactions and domain interactions. The problem of interaction inference is then modeled as a constraint satisfiability problem and solved via linear programing. Experimental results on a combined yeast data set have demonstrated the robustness and the accuracy of the proposed algorithm. Moreover, we also map some predicted interacting domains to three-dimensional structures of protein complexes to show the validity of our predictions.

  5. Evidence of probabilistic behaviour in protein interaction networks.

    Science.gov (United States)

    Ivanic, Joseph; Wallqvist, Anders; Reifman, Jaques

    2008-01-31

    Data from high-throughput experiments of protein-protein interactions are commonly used to probe the nature of biological organization and extract functional relationships between sets of proteins. What has not been appreciated is that the underlying mechanisms involved in assembling these networks may exhibit considerable probabilistic behaviour. We find that the probability of an interaction between two proteins is generally proportional to the numerical product of their individual interacting partners, or degrees. The degree-weighted behaviour is manifested throughout the protein-protein interaction networks studied here, except for the high-degree, or hub, interaction areas. However, we find that the probabilities of interaction between the hubs are still high. Further evidence is provided by path length analyses, which show that these hubs are separated by very few links. The results suggest that protein-protein interaction networks incorporate probabilistic elements that lead to scale-rich hierarchical architectures. These observations seem to be at odds with a biologically-guided organization. One interpretation of the findings is that we are witnessing the ability of proteins to indiscriminately bind rather than the protein-protein interactions that are actually utilized by the cell in biological processes. Therefore, the topological study of a degree-weighted network requires a more refined methodology to extract biological information about pathways, modules, or other inferred relationships among proteins.

  6. Evidence of probabilistic behaviour in protein interaction networks

    Directory of Open Access Journals (Sweden)

    Reifman Jaques

    2008-01-01

    Full Text Available Abstract Background Data from high-throughput experiments of protein-protein interactions are commonly used to probe the nature of biological organization and extract functional relationships between sets of proteins. What has not been appreciated is that the underlying mechanisms involved in assembling these networks may exhibit considerable probabilistic behaviour. Results We find that the probability of an interaction between two proteins is generally proportional to the numerical product of their individual interacting partners, or degrees. The degree-weighted behaviour is manifested throughout the protein-protein interaction networks studied here, except for the high-degree, or hub, interaction areas. However, we find that the probabilities of interaction between the hubs are still high. Further evidence is provided by path length analyses, which show that these hubs are separated by very few links. Conclusion The results suggest that protein-protein interaction networks incorporate probabilistic elements that lead to scale-rich hierarchical architectures. These observations seem to be at odds with a biologically-guided organization. One interpretation of the findings is that we are witnessing the ability of proteins to indiscriminately bind rather than the protein-protein interactions that are actually utilized by the cell in biological processes. Therefore, the topological study of a degree-weighted network requires a more refined methodology to extract biological information about pathways, modules, or other inferred relationships among proteins.

  7. Yeast Interacting Proteins Database: YPL095C, YGL198W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available d to late Golgi vesicles; computational analysis of large-scale protein-protein interaction data suggests a ...gene name YIP4 Prey description Protein that interacts with Rab GTPases, localized to late Golgi vesicles; computation

  8. Yeast Interacting Proteins Database: YGL161C, YDR084C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YGL161C YIP5 Protein that interacts with Rab GTPases, localized to late Golgi vesicles; computation...GTPases, localized to late Golgi vesicles; computational analysis of large-scale protein-protein interaction

  9. 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.

  10. Building blocks for protein interaction devices

    OpenAIRE

    Gr?nberg, Raik; Ferrar, Tony S.; van der Sloot, Almer M.; Constante, Marco; Serrano, Luis

    2010-01-01

    Here, we propose a framework for the design of synthetic protein networks from modular protein?protein or protein?peptide interactions and provide a starter toolkit of protein building blocks. Our proof of concept experiments outline a general work flow for part?based protein systems engineering. We streamlined the iterative BioBrick cloning protocol and assembled 25 synthetic multidomain proteins each from seven standardized DNA fragments. A systematic screen revealed two main factors contro...

  11. Integral UBL domain proteins: a family of proteasome interacting proteins

    DEFF Research Database (Denmark)

    Hartmann-Petersen, Rasmus; Gordon, Colin

    2004-01-01

    The family of ubiquitin-like (UBL) domain proteins (UDPs) comprises a conserved group of proteins involved in a multitude of different cellular activities. However, recent studies on UBL-domain proteins indicate that these proteins appear to share a common property in their ability to interact......-domain proteins catalyse the formation of ubiquitin-protein conjugates, whereas others appear to target ubiquitinated proteins for degradation and interact with chaperones. Hence, by binding to the 26S proteasome the UBL-domain proteins seem to tailor and direct the basic proteolytic functions of the particle...

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

    Science.gov (United States)

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

    2015-02-23

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

  13. Coevolution of gene expression among interacting proteins

    Energy Technology Data Exchange (ETDEWEB)

    Fraser, Hunter B.; Hirsh, Aaron E.; Wall, Dennis P.; Eisen,Michael B.

    2004-03-01

    Physically interacting proteins or parts of proteins are expected to evolve in a coordinated manner that preserves proper interactions. Such coevolution at the amino acid-sequence level is well documented and has been used to predict interacting proteins, domains, and amino acids. Interacting proteins are also often precisely coexpressed with one another, presumably to maintain proper stoichiometry among interacting components. Here, we show that the expression levels of physically interacting proteins coevolve. We estimate average expression levels of genes from four closely related fungi of the genus Saccharomyces using the codon adaptation index and show that expression levels of interacting proteins exhibit coordinated changes in these different species. We find that this coevolution of expression is a more powerful predictor of physical interaction than is coevolution of amino acid sequence. These results demonstrate previously uncharacterized coevolution of gene expression, adding a different dimension to the study of the coevolution of interacting proteins and underscoring the importance of maintaining coexpression of interacting proteins over evolutionary time. Our results also suggest that expression coevolution can be used for computational prediction of protein protein interactions.

  14. PSAIA – Protein Structure and Interaction Analyzer

    Directory of Open Access Journals (Sweden)

    Vlahoviček Kristian

    2008-04-01

    Full Text Available Abstract Background PSAIA (Protein Structure and Interaction Analyzer was developed to compute geometric parameters for large sets of protein structures in order to predict and investigate protein-protein interaction sites. Results In addition to most relevant established algorithms, PSAIA offers a new method PIADA (Protein Interaction Atom Distance Algorithm for the determination of residue interaction pairs. We found that PIADA produced more satisfactory results than comparable algorithms implemented in PSAIA. Particular advantages of PSAIA include its capacity to combine different methods to detect the locations and types of interactions between residues and its ability, without any further automation steps, to handle large numbers of protein structures and complexes. Generally, the integration of a variety of methods enables PSAIA to offer easier automation of analysis and greater reliability of results. PSAIA can be used either via a graphical user interface or from the command-line. Results are generated in either tabular or XML format. Conclusion In a straightforward fashion and for large sets of protein structures, PSAIA enables the calculation of protein geometric parameters and the determination of location and type for protein-protein interaction sites. XML formatted output enables easy conversion of results to various formats suitable for statistic analysis. Results from smaller data sets demonstrated the influence of geometry on protein interaction sites. Comprehensive analysis of properties of large data sets lead to new information useful in the prediction of protein-protein interaction sites.

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

    Science.gov (United States)

    Haris, Parvez I

    2010-08-01

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

  16. Evolutionary dynamics under interactive diversity

    Science.gov (United States)

    Su, Qi; Li, Aming; Wang, Long

    2017-10-01

    As evidenced by many cases in human societies, individuals often make different behavior decisions in different interactions, and adaptively adjust their behavior in changeable interactive scenarios. However, up to now, how such diverse interactive behavior affects cooperation dynamics has still remained unknown. Here we develop a general framework of interactive diversity, which models individuals’ separated behavior against distinct opponents and their adaptive adjustment in response to opponents’ strategies, to explore the evolution of cooperation. We find that interactive diversity enables individuals to reciprocate every single opponent, and thus sustains large-scale reciprocal interactions. Our work witnesses an impressive boost of cooperation for a notably extensive range of parameters and for all pairwise games. These results are robust against well-mixed and various networked populations, and against degree-normalized and cumulative payoff patterns. From the perspective of network dynamics, distinguished from individuals competing for nodes in most previous work, in this paper, the system evolves in the form of behavior disseminating along edges. We propose a theoretical method based on evolution of edges, which predicts well both the frequency of cooperation and the compact cooperation clusters. Our thorough investigation clarifies the positive role of interactive diversity in resolving social dilemmas and highlights the significance of understanding evolutionary dynamics from the viewpoint of edge dynamics.

  17. Ontology integration to identify protein complex in protein interaction networks

    Directory of Open Access Journals (Sweden)

    Yang Zhihao

    2011-10-01

    Full Text Available Abstract Background Protein complexes can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of protein complexes detection algorithms. Methods We have developed novel semantic similarity method, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. Following the approach of that of the previously proposed clustering algorithm IPCA which expands clusters starting from seeded vertices, we present a clustering algorithm OIIP based on the new weighted Protein-Protein interaction networks for identifying protein complexes. Results The algorithm OIIP is applied to the protein interaction network of Sacchromyces cerevisiae and identifies many well known complexes. Experimental results show that the algorithm OIIP has higher F-measure and accuracy compared to other competing approaches.

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

    Directory of Open Access Journals (Sweden)

    Sushmita Roy

    2009-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Joseph Ivanic

    2009-06-01

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

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

    Science.gov (United States)

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

    2009-06-05

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

  1. Yeast Interacting Proteins Database: YNL189W, YOR284W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ait as prey (0) YOR284W HUA2 Cytoplasmic protein of unknown function; computation...protein of unknown function; computational analysis of large-scale protein-protein interaction data suggests

  2. Integral UBL domain proteins: a family of proteasome interacting proteins

    DEFF Research Database (Denmark)

    Hartmann-Petersen, Rasmus; Gordon, Colin

    2004-01-01

    The family of ubiquitin-like (UBL) domain proteins (UDPs) comprises a conserved group of proteins involved in a multitude of different cellular activities. However, recent studies on UBL-domain proteins indicate that these proteins appear to share a common property in their ability to interact wi...

  3. Mapping Protein-Protein Interactions by Quantitative Proteomics

    DEFF Research Database (Denmark)

    Dengjel, Joern; Kratchmarova, Irina; Blagoev, Blagoy

    2010-01-01

    Proteins exert their function inside a cell generally in multiprotein complexes. These complexes are highly dynamic structures changing their composition over time and cell state. The same protein may thereby fulfill different functions depending on its binding partners. Quantitative mass...... to characterize protein interaction networks. In this chapter we describe in detail the use of stable isotope labeling by amino acids in cell culture (SILAC) for the quantitative analysis of stimulus-dependent dynamic protein interactions....

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

    Science.gov (United States)

    Pattin, Kristine A; Moore, Jason H

    2009-12-01

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

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

    Science.gov (United States)

    Garner, Amanda L; Janda, Kim D

    2011-01-01

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

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

    OpenAIRE

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

    2006-01-01

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

  7. 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

  8. Yeast Interacting Proteins Database: YDL226C, YGL198W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available s bait as prey (0) YGL198W YIP4 Protein that interacts with Rab GTPases, localized to late Golgi vesicles; computation...iption Protein that interacts with Rab GTPases, localized to late Golgi vesicles; computation

  9. Yeast Interacting Proteins Database: YPR103W, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available tein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors...gulated gene expression; interacts with protein kinase Snf1p, glucose sensors Snf

  10. Yeast Interacting Proteins Database: YGR268C, YER125W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available larity to that of Type I J-proteins; computational analysis of large-scale protein-protein interaction data ...equence similarity to that of Type I J-proteins; computational analysis of large-scale protein-protein inter

  11. Building blocks for protein interaction devices.

    Science.gov (United States)

    Grünberg, Raik; Ferrar, Tony S; van der Sloot, Almer M; Constante, Marco; Serrano, Luis

    2010-05-01

    Here, we propose a framework for the design of synthetic protein networks from modular protein-protein or protein-peptide interactions and provide a starter toolkit of protein building blocks. Our proof of concept experiments outline a general work flow for part-based protein systems engineering. We streamlined the iterative BioBrick cloning protocol and assembled 25 synthetic multidomain proteins each from seven standardized DNA fragments. A systematic screen revealed two main factors controlling protein expression in Escherichia coli: obstruction of translation initiation by mRNA secondary structure or toxicity of individual domains. Eventually, 13 proteins were purified for further characterization. Starting from well-established biotechnological tools, two general-purpose interaction input and two readout devices were built and characterized in vitro. Constitutive interaction input was achieved with a pair of synthetic leucine zippers. The second interaction was drug-controlled utilizing the rapamycin-induced binding of FRB(T2098L) to FKBP12. The interaction kinetics of both devices were analyzed by surface plasmon resonance. Readout was based on Förster resonance energy transfer between fluorescent proteins and was quantified for various combinations of input and output devices. Our results demonstrate the feasibility of parts-based protein synthetic biology. Additionally, we identify future challenges and limitations of modular design along with approaches to address them.

  12. Yeast Interacting Proteins Database: YGL198W, YDR084C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YGL198W YIP4 Protein that interacts with Rab GTPases, localized to late Golgi vesicles; computation... GTPases, localized to late Golgi vesicles; computational analysis of large-scale protein-protein interactio

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

    Science.gov (United States)

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

    2002-05-01

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

  14. Yeast Interacting Proteins Database: YLR447C, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available xpression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Sp...; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; act

  15. 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. .

  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. Interaction between -Synuclein and Other Proteins in Neurodegenerative Disorders

    Directory of Open Access Journals (Sweden)

    Kurt A. Jellinger

    2011-01-01

    Full Text Available Protein aggregation is a common characteristic of many neurodegenerative disorders, and the interaction between pathological/toxic proteins to cause neurodegeneration is a hot topic of current neuroscience research. Despite clinical, genetic, and experimental differences, evidence increasingly indicates considerable overlap between synucleinopathies and tauopathies or other protein-misfolding diseases. Inclusions, characteristics of these disorders, also occurring in other neurodegenerative diseases, suggest interactions of pathological proteins engaging common downstream pathways. Novel findings that have shifted our understanding in the role of pathologic proteins in the pathogenesis of Parkinson and Alzheimer diseases have confirmed correlations/overlaps between these and other neurodegenerative disorders. The synergistic effects of α-synuclein, hyperphosphorylated tau, amyloid-β, and other pathologic proteins, and the underlying molecular pathogenic mechanisms, including induction and spread of protein aggregates, are critically reviewed, suggesting a dualism or triad of neurodegeneration in protein-misfolding disorders, although the etiology of most of these processes is still mysterious.

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

    OpenAIRE

    Lund, Mikael; Jönsson, Bo

    2003-01-01

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

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

    Science.gov (United States)

    Kiran, M; Nagarajaram, H A

    2016-08-16

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

  20. Fluorescence Studies of Protein Crystallization Interactions

    Science.gov (United States)

    Pusey, Marc L.; Smith, Lori; Forsythe, Elizabeth

    1999-01-01

    We are investigating protein-protein interactions in under- and over-saturated crystallization solution conditions using fluorescence methods. The use of fluorescence requires fluorescent derivatives where the probe does not markedly affect the crystal packing. A number of chicken egg white lysozyme (CEWL) derivatives have been prepared, with the probes covalently attached to one of two different sites on the protein molecule; the side chain carboxyl of ASP 101, within the active site cleft, and the N-terminal amine. The ASP 101 derivatives crystallize while the N-terminal amine derivatives do not. However, the N-terminal amine is part of the contact region between adjacent 43 helix chains, and blocking this site does would not interfere with formation of these structures in solution. Preliminary FRET data have been obtained at pH 4.6, 0.1M NaAc buffer, at 5 and 7% NaCl, 4 C, using the N-terminal bound pyrene acetic acid (PAA, Ex 340 nm, Em 376 nm) and ASP 101 bound Lucifer Yellow (LY, Ex 425 nm, Em 525 nm) probe combination. The corresponding Csat values are 0.471 and 0.362 mg/ml (approximately 3.3 and approximately 2.5 x 10 (exp 5) M respectively), and all experiments were carried out at approximately Csat or lower total protein concentration. The data at both salt concentrations show a consistent trend of decreasing fluorescence yield of the donor species (PAA) with increasing total protein concentration. This decrease is apparently more pronounced at 7% NaCl, consistent with the expected increased intermolecular interactions at higher salt concentrations (reflected in the lower solubility). The estimated average distance between protein molecules at 5 x 10 (exp 6) M is approximately 70 nm, well beyond the range where any FRET can be expected. The calculated RO, where 50% of the donor energy is transferred to the acceptor, for the PAA-CEWL * LY-CEWL system is 3.28 nm, based upon a PAA-CEWL quantum efficiency of 0.41.

  1. Yeast Interacting Proteins Database: YOR124C, YGR268C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available that of Type I J-proteins; computational analysis of large-scale protein-protein interaction data suggests a...plasmic protein containing a zinc finger domain with sequence similarity to that of Type I J-proteins; computation

  2. Modeling protein network evolution under genome duplication and domain shuffling

    Directory of Open Access Journals (Sweden)

    Isambert Hervé

    2007-11-01

    Full Text Available Abstract Background Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. Such exponential evolutionary processes must have largely contributed to shape the topology of protein-protein interaction (PPI networks by outweighing, in particular, all time-linear network growths modeled so far. Results We propose and solve a mathematical model of PPI network evolution under successive genome duplications. This demonstrates, from first principles, that evolutionary conservation and scale-free topology are intrinsically linked properties of PPI networks and emerge from i prevailing exponential network dynamics under duplication and ii asymmetric divergence of gene duplicates. While required, we argue that this asymmetric divergence arises, in fact, spontaneously at the level of protein-binding sites. This supports a refined model of PPI network evolution in terms of protein domains under exponential and asymmetric duplication/divergence dynamics, with multidomain proteins underlying the combinatorial formation of protein complexes. Genome duplication then provides a powerful source of PPI network innovation by promoting local rearrangements of multidomain proteins on a genome wide scale. Yet, we show that the overall conservation and topology of PPI networks are robust to extensive domain shuffling of multidomain proteins as well as to finer details of protein interaction and evolution. Finally, large scale features of direct and indirect PPI networks of S. cerevisiae are well reproduced numerically with only two adjusted parameters of clear biological significance (i.e. network effective growth rate and average number of protein-binding domains per protein. Conclusion This study demonstrates the statistical consequences of genome duplication and domain shuffling on the conservation and topology of PPI networks over a broad evolutionary scale across eukaryote kingdoms. In particular, scale

  3. Yeast Interacting Proteins Database: YGL161C, YGL198W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YGL161C YIP5 Protein that interacts with Rab GTPases, localized to late Golgi vesicles; computation...that interacts with Rab GTPases, localized to late Golgi vesicles; computational ...eracts with Rab GTPases, localized to late Golgi vesicles; computational analysis of large-scale protein-pro...ized to late Golgi vesicles; computational analysis of large-scale protein-protein interaction data suggests

  4. Yeast Interacting Proteins Database: YGL198W, YGL161C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YGL198W YIP4 Protein that interacts with Rab GTPases, localized to late Golgi vesicles; computation...that interacts with Rab GTPases, localized to late Golgi vesicles; computational ...eracts with Rab GTPases, localized to late Golgi vesicles; computational analysis of large-scale protein-pro...ized to late Golgi vesicles; computational analysis of large-scale protein-protein interaction data suggests

  5. Data management of protein interaction networks

    CERN Document Server

    Cannataro, Mario

    2012-01-01

    Interactomics: a complete survey from data generation to knowledge extraction With the increasing use of high-throughput experimental assays, more and more protein interaction databases are becoming available. As a result, computational analysis of protein-to-protein interaction (PPI) data and networks, now known as interactomics, has become an essential tool to determine functionally associated proteins. From wet lab technologies to data management to knowledge extraction, this timely book guides readers through the new science of interactomics, giving them the tools needed to: Generate

  6. Characterizing carbohydrate-protein interactions by NMR

    Science.gov (United States)

    Bewley, Carole A.; Shahzad-ul-Hussan, Syed

    2013-01-01

    Interactions between proteins and soluble carbohydrates and/or surface displayed glycans are central to countless recognition, attachment and signaling events in biology. The physical chemical features associated with these binding events vary considerably, depending on the biological system of interest. For example, carbohydrate-protein interactions can be stoichiometric or multivalent, the protein receptors can be monomeric or oligomeric, and the specificity of recognition can be highly stringent or rather promiscuous. Equilibrium dissociation constants for carbohydrate binding are known to vary from micromolar to millimolar, with weak interactions being far more prevalent; and individual carbohydrate binding sites can be truly symmetrical or merely homologous, and hence, the affinities of individual sites within a single protein can vary, as can the order of binding. Several factors, including the weak affinities with which glycans bind their protein receptors, the dynamic nature of the glycans themselves, and the non-equivalent interactions among oligomeric carbohydrate receptors, have made NMR an especially powerful tool for studying and defining carbohydrate-protein interactions. Here we describe those NMR approaches that have proven to be the most robust in characterizing these systems, and explain what type of information can (or cannot) be obtained from each. Our goal is to provide to the reader the information necessary for selecting the correct experiment or sets of experiments to characterize their carbohydrate-protein interaction of interest. PMID:23784792

  7. Prion protein self-peptides modulate prion interactions and conversion

    NARCIS (Netherlands)

    Rigter, A.; Priem, J.; Timmers-Parohi, D.; Langeveld, J.P.M.; Zijderveld, van F.G.; Bossers, A.

    2009-01-01

    Background: Molecular mechanisms underlying prion agent replication, converting host-encoded cellular prion protein (PrPC) into the scrapie associated isoform (PrPSc), are poorly understood. Selective self-interaction between PrP molecules forms a basis underlying the observed differences of the

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

    Directory of Open Access Journals (Sweden)

    Hirsh Aaron E

    2003-05-01

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

  9. Treponema denticola interactions with host proteins

    Directory of Open Access Journals (Sweden)

    J. Christopher Fenno

    2012-02-01

    Full Text Available Oral Treponema species, most notably T. denticola, are implicated in the destructive effects of human periodontal disease. Progress in the molecular analysis of interactions between T. denticola and host proteins is reviewed here, with particular emphasis on the characterization of surface-expressed and secreted proteins of T. denticola involved in interactions with host cells, extracellular matrix components, and components of the innate immune system.

  10. Yeast Interacting Proteins Database: YGL237C, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding prote... expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein

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

    Science.gov (United States)

    Zhang, Zhe; Witham, Shawn; Alexov, Emil

    2011-01-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

    Zhang, Zhe; Witham, Shawn; Alexov, Emil

    2011-06-01

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

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

    Science.gov (United States)

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

  15. Eukaryotic LYR Proteins Interact with Mitochondrial Protein Complexes

    Directory of Open Access Journals (Sweden)

    Heike Angerer

    2015-02-01

    Full Text Available In eukaryotic cells, mitochondria host ancient essential bioenergetic and biosynthetic pathways. LYR (leucine/tyrosine/arginine motif proteins (LYRMs of the Complex1_LYR-like superfamily interact with protein complexes of bacterial origin. Many LYR proteins function as extra subunits (LYRM3 and LYRM6 or novel assembly factors (LYRM7, LYRM8, ACN9 and FMC1 of the oxidative phosphorylation (OXPHOS core complexes. Structural insights into complex I accessory subunits LYRM6 and LYRM3 have been provided by analyses of EM and X-ray structures of complex I from bovine and the yeast Yarrowia lipolytica, respectively. Combined structural and biochemical studies revealed that LYRM6 resides at the matrix arm close to the ubiquinone reduction site. For LYRM3, a position at the distal proton-pumping membrane arm facing the matrix space is suggested. Both LYRMs are supposed to anchor an acyl-carrier protein (ACPM independently to complex I. The function of this duplicated protein interaction of ACPM with respiratory complex I is still unknown. Analysis of protein-protein interaction screens, genetic analyses and predicted multi-domain LYRMs offer further clues on an interaction network and adaptor-like function of LYR proteins in mitochondria.

  16. Website on Protein Interaction and Protein Structure Related Work

    Science.gov (United States)

    Samanta, Manoj; Liang, Shoudan; Biegel, Bryan (Technical Monitor)

    2003-01-01

    In today's world, three seemingly diverse fields - computer information technology, nanotechnology and biotechnology are joining forces to enlarge our scientific knowledge and solve complex technological problems. Our group is dedicated to conduct theoretical research exploring the challenges in this area. The major areas of research include: 1) Yeast Protein Interactions; 2) Protein Structures; and 3) Current Transport through Small Molecules.

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

    Science.gov (United States)

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

  18. Interactions between whey proteins and kaolinite surfaces

    International Nuclear Information System (INIS)

    Barral, S.; Villa-Garcia, M.A.; Rendueles, M.; Diaz, M.

    2008-01-01

    The nature of the interactions between whey proteins and kaolinite surfaces was investigated by adsorption-desorption experiments at room temperature, performed at the isoelectric point (IEP) of the proteins and at pH 7. It was found that kaolinite is a strong adsorbent for proteins, reaching the maximum adsorption capacity at the IEP of each protein. At pH 7.0, the retention capacity decreased considerably. The adsorption isotherms showed typical Langmuir characteristics. X-ray diffraction data for the protein-kaolinite complexes showed that protein molecules were not intercalated in the mineral structure, but immobilized at the external surfaces and the edges of the kaolinite. Fourier transform IR results indicate the absence of hydrogen bonding between kaolinite surfaces and the polypeptide chain. The adsorption patterns appear to be related to electrostatic interactions, although steric effects should be also considered

  19. HCVpro: Hepatitis C virus protein interaction database

    KAUST Repository

    Kwofie, Samuel K.

    2011-12-01

    It is essential to catalog characterized hepatitis C virus (HCV) protein-protein interaction (PPI) data and the associated plethora of vital functional information to augment the search for therapies, vaccines and diagnostic biomarkers. In furtherance of these goals, we have developed the hepatitis C virus protein interaction database (HCVpro) by integrating manually verified hepatitis C virus-virus and virus-human protein interactions curated from literature and databases. HCVpro is a comprehensive and integrated HCV-specific knowledgebase housing consolidated information on PPIs, functional genomics and molecular data obtained from a variety of virus databases (VirHostNet, VirusMint, HCVdb and euHCVdb), and from BIND and other relevant biology repositories. HCVpro is further populated with information on hepatocellular carcinoma (HCC) related genes that are mapped onto their encoded cellular proteins. Incorporated proteins have been mapped onto Gene Ontologies, canonical pathways, Online Mendelian Inheritance in Man (OMIM) and extensively cross-referenced to other essential annotations. The database is enriched with exhaustive reviews on structure and functions of HCV proteins, current state of drug and vaccine development and links to recommended journal articles. Users can query the database using specific protein identifiers (IDs), chromosomal locations of a gene, interaction detection methods, indexed PubMed sources as well as HCVpro, BIND and VirusMint IDs. The use of HCVpro is free and the resource can be accessed via http://apps.sanbi.ac.za/hcvpro/ or http://cbrc.kaust.edu.sa/hcvpro/. © 2011 Elsevier B.V.

  20. Protein complexes predictions within protein interaction networks using genetic algorithms.

    Science.gov (United States)

    Ramadan, Emad; Naef, Ahmed; Ahmed, Moataz

    2016-07-25

    Protein-protein interaction networks are receiving increased attention due to their importance in understanding life at the cellular level. A major challenge in systems biology is to understand the modular structure of such biological networks. Although clustering techniques have been proposed for clustering protein-protein interaction networks, those techniques suffer from some drawbacks. The application of earlier clustering techniques to protein-protein interaction networks in order to predict protein complexes within the networks does not yield good results due to the small-world and power-law properties of these networks. In this paper, we construct a new clustering algorithm for predicting protein complexes through the use of genetic algorithms. We design an objective function for exclusive clustering and overlapping clustering. We assess the quality of our proposed clustering algorithm using two gold-standard data sets. Our algorithm can identify protein complexes that are significantly enriched in the gold-standard data sets. Furthermore, our method surpasses three competing methods: MCL, ClusterOne, and MCODE in terms of the quality of the predicted complexes. The source code and accompanying examples are freely available at http://faculty.kfupm.edu.sa/ics/eramadan/GACluster.zip .

  1. Yeast Interacting Proteins Database: YEL017W, YEL017W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available Bait description Protein of unknown function with a possible role in glutathione metabolism, as suggested by computation...ion Protein of unknown function with a possible role in glutathione metabolism, as suggested by computationa...putational analysis of large-scale protein-protein interaction data; GFP-fusion pro...17W GTT3 Protein of unknown function with a possible role in glutathione metabolism, as suggested by compu...tational analysis of large-scale protein-protein interaction data; GFP-fusion prote

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

    Directory of Open Access Journals (Sweden)

    Susan Khor

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

  3. PIWI Proteins and PIWI-Interacting RNA

    DEFF Research Database (Denmark)

    Han, Yi Neng; Li, Yuan; Xia, Sheng Qiang

    2017-01-01

    P-Element induced wimpy testis (PIWI)-interacting RNAs (piRNAs) are a type of noncoding RNAs (ncRNAs) and interact with PIWI proteins. piRNAs were primarily described in the germline, but emerging evidence revealed that piRNAs are expressed in a tissue-specific manner among multiple human somatic...... diagnosis and clinical treatment....

  4. Yeast Interacting Proteins Database: YDL226C, YJL151C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available s bait as prey (0) YJL151C SNA3 Integral membrane protein localized to vacuolar intralumenal vesicles, computation...intralumenal vesicles, computational analysis of large-scale protein-protein interaction data suggests a pos... gene name SNA3 Prey description Integral membrane protein localized to vacuolar

  5. Yeast Interacting Proteins Database: YML064C, YOR284W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available th this bait as prey (0) YOR284W HUA2 Cytoplasmic protein of unknown function; computational analysis of lar...Rows with this bait as prey (0) Prey ORF YOR284W Prey gene name HUA2 Prey description Cytoplasmic protein of unknown function; comput...ational analysis of large-scale protein-protein interact

  6. Yeast Interacting Proteins Database: YGL145W, YNL258C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ripheral membrane protein required for Golgi-to-ER retrograde traffic; component ... membrane protein required for Golgi-to-ER retrograde traffic; component of the ER target site that interact

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

    Directory of Open Access Journals (Sweden)

    Ji'an Pan

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

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

    Directory of Open Access Journals (Sweden)

    Oleksii Kuchaiev

    2009-08-01

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

  9. Detecting protein-protein interactions in living cells

    DEFF Research Database (Denmark)

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

    2009-01-01

    -terminal of the NMDA receptor and PDZ2 of PSD-95 were fused to green fluorescent protein (GFP) and Renilla luciferase (Rluc) and expressed in COS7 cells. A robust and specific BRET signal was obtained by expression of the appropriate partner proteins and subsequently, the assay was used to evaluate a Tat......The PDZ domain mediated interaction between the NMDA receptor and its intracellular scaffolding protein, PSD-95, is a potential target for treatment of ischemic brain diseases. We have recently developed a number of peptide analogues with improved affinity for the PDZ domains of PSD-95 compared...... to the endogenous C-terminal peptide of the NMDA receptor, as evaluated by a cell-free protein-protein interaction assay. However, it is important to address both membrane permeability and effect in living cells. Therefore a bioluminescence resonance energy transfer (BRET) assay was established, where the C...

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

    Directory of Open Access Journals (Sweden)

    Andrew Schoenrock

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

  11. Modeling disordered protein interactions from biophysical principles.

    Directory of Open Access Journals (Sweden)

    Lenna X Peterson

    2017-04-01

    Full Text Available Disordered protein-protein interactions (PPIs, those involving a folded protein and an intrinsically disordered protein (IDP, are prevalent in the cell, including important signaling and regulatory pathways. IDPs do not adopt a single dominant structure in isolation but often become ordered upon binding. To aid understanding of the molecular mechanisms of disordered PPIs, it is crucial to obtain the tertiary structure of the PPIs. However, experimental methods have difficulty in solving disordered PPIs and existing protein-protein and protein-peptide docking methods are not able to model them. Here we present a novel computational method, IDP-LZerD, which models the conformation of a disordered PPI by considering the biophysical binding mechanism of an IDP to a structured protein, whereby a local segment of the IDP initiates the interaction and subsequently the remaining IDP regions explore and coalesce around the initial binding site. On a dataset of 22 disordered PPIs with IDPs up to 69 amino acids, successful predictions were made for 21 bound and 18 unbound receptors. The successful modeling provides additional support for biophysical principles. Moreover, the new technique significantly expands the capability of protein structure modeling and provides crucial insights into the molecular mechanisms of disordered PPIs.

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

    Science.gov (United States)

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

    2010-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Melody G Campbell

    2011-01-01

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

  14. Yeast Interacting Proteins Database: YOR047C, YKL038W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available racts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a...Bait description Protein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose senso...rs Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regulator of the tra

  15. Annotation and retrieval in protein interaction databases

    Science.gov (United States)

    Cannataro, Mario; Hiram Guzzi, Pietro; Veltri, Pierangelo

    2014-06-01

    Biological databases have been developed with a special focus on the efficient retrieval of single records or the efficient computation of specialized bioinformatics algorithms against the overall database, such as in sequence alignment. The continuos production of biological knowledge spread on several biological databases and ontologies, such as Gene Ontology, and the availability of efficient techniques to handle such knowledge, such as annotation and semantic similarity measures, enable the development on novel bioinformatics applications that explicitly use and integrate such knowledge. After introducing the annotation process and the main semantic similarity measures, this paper shows how annotations and semantic similarity can be exploited to improve the extraction and analysis of biologically relevant data from protein interaction databases. As case studies, the paper presents two novel software tools, OntoPIN and CytoSeVis, both based on the use of Gene Ontology annotations, for the advanced querying of protein interaction databases and for the enhanced visualization of protein interaction networks.

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

    NARCIS (Netherlands)

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

    2000-01-01

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

  17. Identifying hubs in protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Ravishankar R Vallabhajosyula

    Full Text Available In spite of the scale-free degree distribution that characterizes most protein interaction networks (PINs, it is common to define an ad hoc degree scale that defines "hub" proteins having special topological and functional significance. This raises the concern that some conclusions on the functional significance of proteins based on network properties may not be robust.In this paper we present three objective methods to define hub proteins in PINs: one is a purely topological method and two others are based on gene expression and function. By applying these methods to four distinct PINs, we examine the extent of agreement among these methods and implications of these results on network construction.We find that the methods agree well for networks that contain a balance between error-free and unbiased interactions, indicating that the hub concept is meaningful for such networks.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-06-14

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

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

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

    Science.gov (United States)

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

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

  1. Yeast Interacting Proteins Database: YDR425W, YGL198W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available with this bait as prey (0) YGL198W YIP4 Protein that interacts with Rab GTPases, localized to late Golgi vesicles; computation...IP4 Prey description Protein that interacts with Rab GTPases, localized to late Golgi vesicles; computatio

  2. Yeast Interacting Proteins Database: YDR425W, YGL161C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available with this bait as prey (0) YGL161C YIP5 Protein that interacts with Rab GTPases, localized to late Golgi vesicles; computation...IP5 Prey description Protein that interacts with Rab GTPases, localized to late Golgi vesicles; computatio

  3. Yeast Interacting Proteins Database: YMR280C, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available olved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensor... glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, an

  4. Toxicological Significance of Silicon-protein Interaction

    OpenAIRE

    Farhat N. Jaffery; P. N. Viswanathan

    1987-01-01

    In order to understand the molecular mechanism of the toxicity of Si containing particulate air pollutants, the interaction between silicate anion and proteins was studied. On the basis of molecular sieving profile, the presence of a protein fraction capable of binding silicic acid was detected in rat lung and serum. The binding is firm being able to withstand dialysis, Si-binding by Bovine Serum Albumin (BSA) follows stoichiometric principles indicating true chemical reaction in terms of eff...

  5. Quantitative Interaction Proteomics of Neurodegenerative Disease Proteins

    Directory of Open Access Journals (Sweden)

    Fabian Hosp

    2015-05-01

    Full Text Available Several proteins have been linked to neurodegenerative disorders (NDDs, but their molecular function is not completely understood. Here, we used quantitative interaction proteomics to identify binding partners of Amyloid beta precursor protein (APP and Presenilin-1 (PSEN1 for Alzheimer’s disease (AD, Huntingtin (HTT for Huntington’s disease, Parkin (PARK2 for Parkinson’s disease, and Ataxin-1 (ATXN1 for spinocerebellar ataxia type 1. Our network reveals common signatures of protein degradation and misfolding and recapitulates known biology. Toxicity modifier screens and comparison to genome-wide association studies show that interaction partners are significantly linked to disease phenotypes in vivo. Direct comparison of wild-type proteins and disease-associated variants identified binders involved in pathogenesis, highlighting the value of differential interactome mapping. Finally, we show that the mitochondrial protein LRPPRC interacts preferentially with an early-onset AD variant of APP. This interaction appears to induce mitochondrial dysfunction, which is an early phenotype of AD.

  6. Targeting protein-protein interactions for parasite control.

    Directory of Open Access Journals (Sweden)

    Christina M Taylor

    2011-04-01

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

  7. Yeast Interacting Proteins Database: YOR358W, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; act...rotein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regulator o

  8. Influenza A Virus-Host Protein Interactions Control Viral Pathogenesis.

    Science.gov (United States)

    Zhao, Mengmeng; Wang, Lingyan; Li, Shitao

    2017-08-01

    The influenza A virus (IAV), a member of the Orthomyxoviridae family, is a highly transmissible respiratory pathogen and represents a continued threat to global health with considerable economic and social impact. IAV is a zoonotic virus that comprises a plethora of strains with different pathogenic profiles. The different outcomes of viral pathogenesis are dependent on the engagement between the virus and the host cellular protein interaction network. The interactions may facilitate virus hijacking of host molecular machinery to fulfill the viral life cycle or trigger host immune defense to eliminate the virus. In recent years, much effort has been made to discover the virus-host protein interactions and understand the underlying mechanisms. In this paper, we review the recent advances in our understanding of IAV-host interactions and how these interactions contribute to host defense and viral pathogenesis.

  9. Understanding Protein-Protein Interactions Using Local Structural Features

    DEFF Research Database (Denmark)

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

    2013-01-01

    of this classification suggests that the balance between favoring and disfavoring structural features determines if a pair of proteins interacts or not. Our results are in agreement with previous works and support the funnel-like intermolecular energy landscape theory that explains PPIs. We have used these features...

  10. Studying protein-protein interactions using peptide arrays

    NARCIS (Netherlands)

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

    2010-01-01

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

  11. PCNA Structure and Interactions with Partner Proteins

    KAUST Repository

    Oke, Muse

    2018-01-29

    Proliferating cell nuclear antigen (PCNA) consists of three identical monomers that topologically encircle double-stranded DNA. PCNA stimulates the processivity of DNA polymerase δ and, to a less extent, the intrinsically highly processive DNA polymerase ε. It also functions as a platform that recruits and coordinates the activities of a large number of DNA processing proteins. Emerging structural and biochemical studies suggest that the nature of PCNA-partner proteins interactions is complex. A hydrophobic groove at the front side of PCNA serves as a primary docking site for the consensus PIP box motifs present in many PCNA-binding partners. Sequences that immediately flank the PIP box motif or regions that are distant from it could also interact with the hydrophobic groove and other regions of PCNA. Posttranslational modifications on the backside of PCNA could add another dimension to its interaction with partner proteins. An encounter of PCNA with different DNA structures might also be involved in coordinating its interactions. Finally, the ability of PCNA to bind up to three proteins while topologically linked to DNA suggests that it would be a versatile toolbox in many different DNA processing reactions.

  12. A framework for protein and membrane interactions

    Directory of Open Access Journals (Sweden)

    Giorgio Bacci

    2009-11-01

    Full Text Available We introduce the BioBeta Framework, a meta-model for both protein-level and membrane-level interactions of living cells. This formalism aims to provide a formal setting where to encode, compare and merge models at different abstraction levels; in particular, higher-level (e.g. membrane activities can be given a formal biological justification in terms of low-level (i.e., protein interactions. A BioBeta specification provides a protein signature together a set of protein reactions, in the spirit of the kappa-calculus. Moreover, the specification describes when a protein configuration triggers one of the only two membrane interaction allowed, that is "pinch" and "fuse". In this paper we define the syntax and semantics of BioBeta, analyse its properties, give it an interpretation as biobigraphical reactive systems, and discuss its expressivity by comparing with kappa-calculus and modelling significant examples. Notably, BioBeta has been designed after a bigraphical metamodel for the same purposes. Hence, each instance of the calculus corresponds to a bigraphical reactive system, and vice versa (almost. Therefore, we can inherith the rich theory of bigraphs, such as the automatic construction of labelled transition systems and behavioural congruences.

  13. 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.

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

    Science.gov (United States)

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

    2015-01-01

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

  15. Spin-label EPR approaches to protein interactions

    NARCIS (Netherlands)

    Son, Martin van

    2014-01-01

    Protein-protein interactions are essential for various biological processes including cell metabolism, muscle contraction, and signal transduction. The dissertation describes a study of the interaction between the proteins cytochrome c and cytochrome c peroxidase by electron paramagnetic resonance

  16. Drosophila protein interaction map (DPiM): a paradigm for metazoan protein complex interactions.

    Science.gov (United States)

    Guruharsha, K G; Obar, Robert A; Mintseris, Julian; Aishwarya, K; Krishnan, R T; Vijayraghavan, K; Artavanis-Tsakonas, Spyros

    2012-01-01

    Proteins perform essential cellular functions as part of protein complexes, often in conjunction with RNA, DNA, metabolites and other small molecules. The genome encodes thousands of proteins but not all of them are expressed in every cell type; and expressed proteins are not active at all times. Such diversity of protein expression and function accounts for the level of biological intricacy seen in nature. Defining protein-protein interactions in protein complexes, and establishing the when, what and where of potential interactions, is therefore crucial to understanding the cellular function of any protein-especially those that have not been well studied by traditional molecular genetic approaches. We generated a large-scale resource of affinity-tagged expression-ready clones and used co-affinity purification combined with tandem mass-spectrometry to identify protein partners of nearly 5,000 Drosophila melanogaster proteins. The resulting protein complex "map" provided a blueprint of metazoan protein complex organization. Here we describe how the map has provided valuable insights into protein function in addition to generating hundreds of testable hypotheses. We also discuss recent technological advancements that will be critical in addressing the next generation of questions arising from the map.

  17. 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.

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

    Science.gov (United States)

    Chakraborty, Sandip; Alvarez-Ponce, David

    2016-01-01

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

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jain Shobhit

    2010-11-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2017-05-12

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

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

    Science.gov (United States)

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

    2018-03-06

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

  4. Yeast Interacting Proteins Database: YDR084C, YGL198W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available with Rab GTPases, localized to late Golgi vesicles; computational analysis of lar...gene name YIP4 Prey description Protein that interacts with Rab GTPases, localized to late Golgi vesicles; computation

  5. Screening for protein-DNA interactions by automatable DNA-protein interaction ELISA.

    Directory of Open Access Journals (Sweden)

    Luise H Brand

    Full Text Available DNA-binding proteins (DBPs, such as transcription factors, constitute about 10% of the protein-coding genes in eukaryotic genomes and play pivotal roles in the regulation of chromatin structure and gene expression by binding to short stretches of DNA. Despite their number and importance, only for a minor portion of DBPs the binding sequence had been disclosed. Methods that allow the de novo identification of DNA-binding motifs of known DBPs, such as protein binding microarray technology or SELEX, are not yet suited for high-throughput and automation. To close this gap, we report an automatable DNA-protein-interaction (DPI-ELISA screen of an optimized double-stranded DNA (dsDNA probe library that allows the high-throughput identification of hexanucleotide DNA-binding motifs. In contrast to other methods, this DPI-ELISA screen can be performed manually or with standard laboratory automation. Furthermore, output evaluation does not require extensive computational analysis to derive a binding consensus. We could show that the DPI-ELISA screen disclosed the full spectrum of binding preferences for a given DBP. As an example, AtWRKY11 was used to demonstrate that the automated DPI-ELISA screen revealed the entire range of in vitro binding preferences. In addition, protein extracts of AtbZIP63 and the DNA-binding domain of AtWRKY33 were analyzed, which led to a refinement of their known DNA-binding consensi. Finally, we performed a DPI-ELISA screen to disclose the DNA-binding consensus of a yet uncharacterized putative DBP, AtTIFY1. A palindromic TGATCA-consensus was uncovered and we could show that the GATC-core is compulsory for AtTIFY1 binding. This specific interaction between AtTIFY1 and its DNA-binding motif was confirmed by in vivo plant one-hybrid assays in protoplasts. Thus, the value and applicability of the DPI-ELISA screen for de novo binding site identification of DBPs, also under automatized conditions, is a promising approach for a

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

    Directory of Open Access Journals (Sweden)

    Sun Zhirong

    2009-12-01

    Full Text Available Abstract Background Genome sequencing projects generate massive amounts of sequence data but there are still many proteins whose functions remain unknown. The availability of large scale protein-protein interaction data sets makes it possible to develop new function prediction methods based on protein-protein interaction (PPI networks. Although several existing methods combine multiple information resources, there is no study that integrates protein domain information and PPI networks to predict protein functions. Results The domain context similarity can be a useful index to predict protein function similarity. The prediction accuracy of our method in yeast is between 63%-67%, which outperforms the other methods in terms of ROC curves. Conclusion This paper presents a novel protein function prediction method that combines protein domain composition information and PPI networks. Performance evaluations show that this method outperforms existing methods.

  7. Structures of multidomain proteins adsorbed on hydrophobic interaction chromatography surfaces.

    Science.gov (United States)

    Gospodarek, Adrian M; Sun, Weitong; O'Connell, John P; Fernandez, Erik J

    2014-12-05

    In hydrophobic interaction chromatography (HIC), interactions between buried hydrophobic residues and HIC surfaces can cause conformational changes that interfere with separations and cause yield losses. This paper extends our previous investigations of protein unfolding in HIC chromatography by identifying protein structures on HIC surfaces under denaturing conditions and relating them to solution behavior. The thermal unfolding of three model multidomain proteins on three HIC surfaces of differing hydrophobicities was investigated with hydrogen exchange mass spectrometry (HXMS). The data were analyzed to obtain unfolding rates and Gibbs free energies for unfolding of adsorbed proteins. The melting temperatures of the proteins were lowered, but by different amounts, on the different surfaces. In addition, the structures of the proteins on the chromatographic surfaces were similar to the partially unfolded structures produced in the absence of a surface by temperature as well as by chemical denaturants. Finally, it was found that patterns of residue exposure to solvent on different surfaces at different temperatures can be largely superimposed. These findings suggest that protein unfolding on various HIC surfaces might be quantitatively related to protein unfolding in solution and that details of surface unfolding behavior might be generalized. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Poly(ethylene glycol) interactions with proteins

    Czech Academy of Sciences Publication Activity Database

    Hašek, Jindřich

    2006-01-01

    Roč. 2, č. 23 (2006), s. 613-618 ISSN 0044-2968. [European Powder Diffraction Conference /9./. Prague, 02.09.2004-05.09.2004] R&D Projects: GA ČR(CZ) GA204/02/0843 Institutional research plan: CEZ:AV0Z40500505 Keywords : poly(ethylene glycol) * PEO * protein-polymer interaction Subject RIV: CD - Macromolecular Chemistry Impact factor: 1.897, year: 2006

  9. HMGB proteins: Interactions with DNA and chromatin

    Czech Academy of Sciences Publication Activity Database

    Štros, Michal

    2010-01-01

    Roč. 1799, 1-2 (2010), s. 101-113 ISSN 1874-9399 R&D Projects: GA ČR(CZ) GA204/08/1530; GA AV ČR(CZ) IAA400040702 Institutional research plan: CEZ:AV0Z50040507; CEZ:AV0Z50040702 Keywords : HMG-box * DNA-protein interaction * chromatin Subject RIV: BO - Biophysics Impact factor: 4.000, year: 2010

  10. Yeast Interacting Proteins Database: YNL258C, YKR022C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YNL258C DSL1 Peripheral membrane protein required for Golgi-to-ER retrograde traffi...equired for Golgi-to-ER retrograde traffic; component of the ER target site that interacts with coatomer, th...it ORF YNL258C Bait gene name DSL1 Bait description Peripheral membrane protein r

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2015-05-15

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

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

    Science.gov (United States)

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

    2016-11-01

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

  14. The Entamoeba histolytica TBP and TRF1 transcription factors are GAAC-box binding proteins, which display differential gene expression under different stress stimuli and during the interaction with mammalian cells.

    Science.gov (United States)

    Narayanasamy, Ravi Kumar; Castañón-Sanchez, Carlos Alberto; Luna-Arias, Juan Pedro; García-Rivera, Guillermina; Avendaño-Borromeo, Bartolo; Labra-Barrios, María Luisa; Valdés, Jesús; Herrera-Aguirre, María Esther; Orozco, Esther

    2018-03-07

    Entamoeba histolytica is the protozoan parasite responsible for human amebiasis. It causes up to 100,000 deaths worldwide each year. This parasite has two closely related basal transcription factors, the TATA-box binding protein (EhTBP) and the TBP-related factor 1 (EhTRF1). TBP binds to the canonical TATTTAAA-box, as well as to different TATA variants. TRF1 also binds to the TATTTAAA-box. However, their binding capacity to diverse core promoter elements, including the GAAC-element, and their role in gene regulation in this parasite remains unknown. EMSA experiments were performed to determine the binding capacity of recombinant TBP and TRF1 to TATA variants, GAAC and GAAC-like boxes. For the functional analysis under different stress stimuli (e.g. growth curve, serum depletion, heat-shock, and UV-irradiation) and during the interaction with mammalian cells (erythrocytes, MDCK cell monolayers, and hepatocytes of hamsters), RT-qPCR, and gene knockdown were performed. Both transcription factors bound to the different TATA variants tested, as well as to the GAAC-boxes, suggesting that they are GAAC-box-binding proteins. The K D values determined for TBP and TRF1 for the different TATA variants and GAAC-box were in the range of 10 -12  M to 10 -11  M. During the death phase of growth or in serum depletion, Ehtbp mRNA levels significantly increased, whereas the mRNA level of Ehtrf1 did not change under these conditions. Ehtrf1 gene expression was negatively regulated by UV-irradiation and heat-shock stress, with no changes in Ehtbp gene expression. Moreover, Ehtrf1 gene also showed a negative regulation during erythrophagocytosis, liver abscess formation, and a transient expression level increase at the initial phase of MDCK cell destruction. Finally, the Ehtbp gene knockdown displayed a drastic decrease in the efficiency of erythrophagocytosis in G3 trophozoites. To our knowledge, this study reveals that these basal transcription factors are able to bind multiple

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

    Directory of Open Access Journals (Sweden)

    Vincent Vagenende

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

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  17. PREFACE: Physics approaches to protein interactions and gene regulation Physics approaches to protein interactions and gene regulation

    Science.gov (United States)

    Nussinov, Ruth; Panchenko, Anna R.; Przytycka, Teresa

    2011-06-01

    Physics approaches focus on uncovering, modeling and quantitating the general principles governing the micro and macro universe. This has always been an important component of biological research, however recent advances in experimental techniques and the accumulation of unprecedented genome-scale experimental data produced by these novel technologies now allow for addressing fundamental questions on a large scale. These relate to molecular interactions, principles of bimolecular recognition, and mechanisms of signal propagation. The functioning of a cell requires a variety of intermolecular interactions including protein-protein, protein-DNA, protein-RNA, hormones, peptides, small molecules, lipids and more. Biomolecules work together to provide specific functions and perturbations in intermolecular communication channels often lead to cellular malfunction and disease. A full understanding of the interactome requires an in-depth grasp of the biophysical principles underlying individual interactions as well as their organization in cellular networks. Phenomena can be described at different levels of abstraction. Computational and systems biology strive to model cellular processes by integrating and analyzing complex data from multiple experimental sources using interdisciplinary tools. As a result, both the causal relationships between the variables and the general features of the system can be discovered, which even without knowing the details of the underlying mechanisms allow for putting forth hypotheses and predicting the behavior of the systems in response to perturbation. And here lies the strength of in silico models which provide control and predictive power. At the same time, the complexity of individual elements and molecules can be addressed by the fields of molecular biophysics, physical biology and structural biology, which focus on the underlying physico-chemical principles and may explain the molecular mechanisms of cellular function. In this issue

  18. 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.

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

    Science.gov (United States)

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

    2016-01-15

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

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

    OpenAIRE

    Samsonov, Sergey

    2009-01-01

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

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

    Science.gov (United States)

    Hubner, Nina C; Mann, Matthias

    2011-04-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-01-01

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

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

    Science.gov (United States)

    Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

    2013-04-01

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

  4. Fragment molecular orbital method for studying lanthanide interactions with proteins

    Energy Technology Data Exchange (ETDEWEB)

    Tsushima, Satoru [Helmholtz-Zentrum Dresden-Rossendorf e.V., Dresden (Germany). Biophysics; Komeiji, Y. [National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba (Japan); Mochizuki, Y. [Rikkyo Univ., Tokyo (Japan)

    2017-06-01

    The binding affinity of the calcium-binding protein calmodulin towards Eu{sup 3+} was studied as a model for lanthanide protein interactions in the large family of ''EF-hand'' calcium-binding proteins.

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

    Directory of Open Access Journals (Sweden)

    Meijing Li

    2015-01-01

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

  6. Glycosphingolipid–Protein Interaction in Signal Transduction

    Directory of Open Access Journals (Sweden)

    Domenico Russo

    2016-10-01

    Full Text Available Glycosphingolipids (GSLs are a class of ceramide-based glycolipids essential for embryo development in mammals. The synthesis of specific GSLs depends on the expression of distinctive sets of GSL synthesizing enzymes that is tightly regulated during development. Several reports have described how cell surface receptors can be kept in a resting state or activate alternative signalling events as a consequence of their interaction with GSLs. Specific GSLs, indeed, interface with specific protein domains that are found in signalling molecules and which act as GSL sensors to modify signalling responses. The regulation exerted by GSLs on signal transduction is orthogonal to the ligand–receptor axis, as it usually does not directly interfere with the ligand binding to receptors. Due to their properties of adjustable production and orthogonal action on receptors, GSLs add a new dimension to the control of the signalling in development. GSLs can, indeed, dynamically influence progenitor cell response to morphogenetic stimuli, resulting in alternative differentiation fates. Here, we review the available literature on GSL–protein interactions and their effects on cell signalling and development.

  7. The Foundations of Protein-Ligand Interaction

    Science.gov (United States)

    Klebe, Gerhard

    For the specific design of a drug we must first answer the question: How does a drug achieve its activity? An active ingredient must, in order to develop its action, bind to a particular target molecule in the body. Usually this is a protein, but also nucleic acids in the form of RNA and DNA can be target structures for active agents. The most important condition for binding is at first that the active agent exhibits the correct size and shape in order to optimally fit into a cavity exposed to the surface of the protein, the "bindingpocket". It is further necessary for the surface properties of the ligand and protein to be mutually compatible to form specific interactions. In 1894 Emil Fischer compared the exact fit of a substrate for the catalytic centre of an enzyme with the picture of a "lock-and-key". Paul Ehrlich coined in 1913 "Corpora non agunt nisi fixata", literally "bodies do not work when they are not bound". He wanted to imply that active agents that are meant to kill bacteria or parasites must be "fixed" by them, i.e. linked to their structures. Both concepts form the starting point for any rational concept in the development of active pharmaceutical ingredients. In many respects they still apply today. A drug must, after being administered, reach its target and interact with a biological macromolecule. Specific agents have a large affinity and sufficient selectivity to bind to the macromolecule's active site. This is the only way they can develop the desired biological activity without side-effects.

  8. A receptor-interacting protein 1 (RIP1)-independent necrotic death under the control of protein phosphatase PP2A that involves the reorganization of actin cytoskeleton and the action of cofilin-1.

    Science.gov (United States)

    Tomasella, Andrea; Blangy, Anne; Brancolini, Claudio

    2014-09-12

    Cell death by necrosis is emerging not merely as a passive phenomenon but as a cell-regulated process. Here, by using different necrotic triggers, we prove the existence of two distinct necrotic pathways. The mitochondrial reactive oxygen species generator 2,3-dimethoxy-1,4-naphthoquinone elicits necrosis characterized by the involvement of RIP1 and Drp1. However, G5, a non-selective isopeptidase inhibitor, triggers a distinct necrotic pathway that depends on the protein phosphatase PP2A and the actin cytoskeleton. PP2A catalytic subunit is stabilized by G5 treatment, and its activity is increased. Furthermore, PP2Ac accumulates into the cytoplasm during necrosis similarly to HMGB1. We have also defined in the actin-binding protein cofilin-1 a link between PP2A, actin cytoskeleton, and necrotic death. Cofilin-1-severing/depolymerization activity is negatively regulated by phosphorylation of serine 3. PP2A contributes to the dephosphorylation of serine 3 elicited by G5. Finally, a cofilin mutant that mimics phosphorylated Ser-3 can partially rescue necrosis in response to G5. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

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

    Science.gov (United States)

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

    2012-07-01

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

  10. Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.

    Science.gov (United States)

    Fu, Changhe; Deng, Su; Jin, Guangxu; Wang, Xinxin; Yu, Zu-Guo

    2017-09-21

    Molecular interaction data at proteomic and genetic levels provide physical and functional insights into a molecular biosystem and are helpful for the construction of pathway structures complementarily. Despite advances in inferring biological pathways using genetic interaction data, there still exists weakness in developed models, such as, activity pathway networks (APN), when integrating the data from proteomic and genetic levels. It is necessary to develop new methods to infer pathway structure by both of interaction data. We utilized probabilistic graphical model to develop a new method that integrates genetic interaction and protein interaction data and infers exquisitely detailed pathway structure. We modeled the pathway network as Bayesian network and applied this model to infer pathways for the coherent subsets of the global genetic interaction profiles, and the available data set of endoplasmic reticulum genes. The protein interaction data were derived from the BioGRID database. Our method can accurately reconstruct known cellular pathway structures, including SWR complex, ER-Associated Degradation (ERAD) pathway, N-Glycan biosynthesis pathway, Elongator complex, Retromer complex, and Urmylation pathway. By comparing N-Glycan biosynthesis pathway and Urmylation pathway identified from our approach with that from APN, we found that our method is able to overcome its weakness (certain edges are inexplicable). According to underlying protein interaction network, we defined a simple scoring function that only adopts genetic interaction information to avoid the balance difficulty in the APN. Using the effective stochastic simulation algorithm, the performance of our proposed method is significantly high. We developed a new method based on Bayesian network to infer detailed pathway structures from interaction data at proteomic and genetic levels. The results indicate that the developed method performs better in predicting signaling pathways than previously

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

    National Research Council Canada - National Science Library

    Somerville, Ronald

    1998-01-01

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

  12. 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.

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

    Science.gov (United States)

    Hall, Randy A

    2004-01-01

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

  14. Elucidating the Interacting Domains of Chandipura Virus Nucleocapsid Protein

    Directory of Open Access Journals (Sweden)

    Kapila Kumar

    2013-01-01

    Full Text Available The nucleocapsid (N protein of Chandipura virus (CHPV plays a crucial role in viral life cycle, besides being an important structural component of the virion through proper organization of its interactions with other viral proteins. In a recent study, the authors had mapped the associations among CHPV proteins and shown that N protein interacts with four of the viral proteins: N, phosphoprotein (P, matrix protein (M, and glycoprotein (G. The present study aimed to distinguish the regions of CHPV N protein responsible for its interactions with other viral proteins. In this direction, we have generated the structure of CHPV N protein by homology modeling using SWISS-MODEL workspace and Accelrys Discovery Studio client 2.55 and mapped the domains of N protein using PiSQRD. The interactions of N protein fragments with other proteins were determined by ZDOCK rigid-body docking method and validated by yeast two-hybrid and ELISA. The study revealed a unique binding site, comprising of amino acids 1–30 at the N terminus of the nucleocapsid protein (N1 that is instrumental in its interactions with N, P, M, and G proteins. It was also observed that N2 associates with N and G proteins while N3 interacts with N, P, and M proteins.

  15. Probing the extent of randomness in protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Joseph Ivanic

    Full Text Available Protein-protein interaction (PPI networks are commonly explored for the identification of distinctive biological traits, such as pathways, modules, and functional motifs. In this respect, understanding the underlying network structure is vital to assess the significance of any discovered features. We recently demonstrated that PPI networks show degree-weighted behavior, whereby the probability of interaction between two proteins is generally proportional to the product of their numbers of interacting partners or degrees. It was surmised that degree-weighted behavior is a characteristic of randomness. We expand upon these findings by developing a random, degree-weighted, network model and show that eight PPI networks determined from single high-throughput (HT experiments have global and local properties that are consistent with this model. The apparent random connectivity in HT PPI networks is counter-intuitive with respect to their observed degree distributions; however, we resolve this discrepancy by introducing a non-network-based model for the evolution of protein degrees or "binding affinities." This mechanism is based on duplication and random mutation, for which the degree distribution converges to a steady state that is identical to one obtained by averaging over the eight HT PPI networks. The results imply that the degrees and connectivities incorporated in HT PPI networks are characteristic of unbiased interactions between proteins that have varying individual binding affinities. These findings corroborate the observation that curated and high-confidence PPI networks are distinct from HT PPI networks and not consistent with a random connectivity. These results provide an avenue to discern indiscriminate organizations in biological networks and suggest caution in the analysis of curated and high-confidence networks.

  16. Probing the extent of randomness in protein interaction networks.

    Science.gov (United States)

    Ivanic, Joseph; Wallqvist, Anders; Reifman, Jaques

    2008-07-11

    Protein-protein interaction (PPI) networks are commonly explored for the identification of distinctive biological traits, such as pathways, modules, and functional motifs. In this respect, understanding the underlying network structure is vital to assess the significance of any discovered features. We recently demonstrated that PPI networks show degree-weighted behavior, whereby the probability of interaction between two proteins is generally proportional to the product of their numbers of interacting partners or degrees. It was surmised that degree-weighted behavior is a characteristic of randomness. We expand upon these findings by developing a random, degree-weighted, network model and show that eight PPI networks determined from single high-throughput (HT) experiments have global and local properties that are consistent with this model. The apparent random connectivity in HT PPI networks is counter-intuitive with respect to their observed degree distributions; however, we resolve this discrepancy by introducing a non-network-based model for the evolution of protein degrees or "binding affinities." This mechanism is based on duplication and random mutation, for which the degree distribution converges to a steady state that is identical to one obtained by averaging over the eight HT PPI networks. The results imply that the degrees and connectivities incorporated in HT PPI networks are characteristic of unbiased interactions between proteins that have varying individual binding affinities. These findings corroborate the observation that curated and high-confidence PPI networks are distinct from HT PPI networks and not consistent with a random connectivity. These results provide an avenue to discern indiscriminate organizations in biological networks and suggest caution in the analysis of curated and high-confidence networks.

  17. Interaction of Proteins Identified in Human Thyroid Cells

    Science.gov (United States)

    Pietsch, Jessica; Riwaldt, Stefan; Bauer, Johann; Sickmann, Albert; Weber, Gerhard; Grosse, Jirka; Infanger, Manfred; Eilles, Christoph; Grimm, Daniela

    2013-01-01

    Influence of gravity forces on the regulation of protein expression by healthy and malignant thyroid cells was studied with the aim to identify protein interactions. Western blot analyses of a limited number of proteins suggested a time-dependent regulation of protein expression by simulated microgravity. After applying free flow isoelectric focusing and mass spectrometry to search for differently expressed proteins by thyroid cells exposed to simulated microgravity for three days, a considerable number of candidates for gravi-sensitive proteins were detected. In order to show how proteins sensitive to microgravity could directly influence other proteins, we investigated all polypeptide chains identified with Mascot scores above 100, looking for groups of interacting proteins. Hence, UniProtKB entry numbers of all detected proteins were entered into the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and processed. The program indicated that we had detected various groups of interacting proteins in each of the three cell lines studied. The major groups of interacting proteins play a role in pathways of carbohydrate and protein metabolism, regulation of cell growth and cell membrane structuring. Analyzing these groups, networks of interaction could be established which show how a punctual influence of simulated microgravity may propagate via various members of interaction chains. PMID:23303277

  18. Evolution of a protein domain interaction network

    International Nuclear Information System (INIS)

    Li-Feng, Gao; Jian-Jun, Shi; Shan, Guan

    2010-01-01

    In this paper, we attempt to understand complex network evolution from the underlying evolutionary relationship between biological organisms. Firstly, we construct a Pfam domain interaction network for each of the 470 completely sequenced organisms, and therefore each organism is correlated with a specific Pfam domain interaction network; secondly, we infer the evolutionary relationship of these organisms with the nearest neighbour joining method; thirdly, we use the evolutionary relationship between organisms constructed in the second step as the evolutionary course of the Pfam domain interaction network constructed in the first step. This analysis of the evolutionary course shows: (i) there is a conserved sub-network structure in network evolution; in this sub-network, nodes with lower degree prefer to maintain their connectivity invariant, and hubs tend to maintain their role as a hub is attached preferentially to new added nodes; (ii) few nodes are conserved as hubs; most of the other nodes are conserved as one with very low degree; (iii) in the course of network evolution, new nodes are added to the network either individually in most cases or as clusters with relative high clustering coefficients in a very few cases. (general)

  19. Mechanistic understanding of protein-silicone oil interactions.

    Science.gov (United States)

    Li, Jinjiang; Pinnamaneni, Swathi; Quan, Yong; Jaiswal, Archana; Andersson, Fredrik I; Zhang, Xiaochun

    2012-06-01

    To investigate interactions between protein and silicone oil so that we can provide some mechanistic understanding of protein aggregation in silicone oil lubricated syringes and its prevention by formulation additives such as Polysorbate 80 and Poloxamer 188. Interfacial tension values of silicone oil/water interface of abatacept solutions with and without formulation additives were obtained under equilibrium conditions using Attension Theta optical tensiometer. Their adsorption and desorption profiles were measured using Quartz Crystal Microbalancing with Dissipation monitoring (QCM-D). The degree of aggregation of abatacept was assessed based on size exclusion measurement. Adsorption of abatacept at the oil/water interface was shown. Polysorbat 80 was more effective than Poloxamer 188 in preventing abatacept adsorption. Moreover, it was noted that some of the adsorbed abatacept molecules were not desorbed readily upon buffer rinse. Finally, no homogeneous aggregation was observed at room temperature and a slight increase of aggregation was only observed for samples measured at 40°C which can be prevented using Polysorbate 80. Interfacial adsorption of proteins is the key step and maybe responsible for the phenomenon of soluble-protein loss when contacting silicone oil and the irreversible adsorption of protein may be associated with protein denaturation/aggregation.

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

    Science.gov (United States)

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

    2010-01-01

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

  1. Predicting and validating protein interactions using network structure.

    Directory of Open Access Journals (Sweden)

    Pao-Yang Chen

    2008-07-01

    Full Text Available Protein interactions play a vital part in the function of a cell. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Protein interactions appear to form a network with a relatively high degree of local clustering. In this paper we exploit this clustering by suggesting a score based on triplets of observed protein interactions. The score utilises both protein characteristics and network properties. Our score based on triplets is shown to complement existing techniques for predicting protein interactions, outperforming them on data sets which display a high degree of clustering. The predicted interactions score highly against test measures for accuracy. Compared to a similar score derived from pairwise interactions only, the triplet score displays higher sensitivity and specificity. By looking at specific examples, we show how an experimental set of interactions can be enriched and validated. As part of this work we also examine the effect of different prior databases upon the accuracy of prediction and find that the interactions from the same kingdom give better results than from across kingdoms, suggesting that there may be fundamental differences between the networks. These results all emphasize that network structure is important and helps in the accurate prediction of protein interactions. The protein interaction data set and the program used in our analysis, and a list of predictions and validations, are available at http://www.stats.ox.ac.uk/bioinfo/resources/PredictingInteractions.

  2. Bactericidal Permeability-Increasing Proteins Shape Host-Microbe Interactions

    Directory of Open Access Journals (Sweden)

    Fangmin Chen

    2017-04-01

    Full Text Available We characterized bactericidal permeability-increasing proteins (BPIs of the squid Euprymna scolopes, EsBPI2 and EsBPI4. They have molecular characteristics typical of other animal BPIs, are closely related to one another, and nest phylogenetically among invertebrate BPIs. Purified EsBPIs had antimicrobial activity against the squid’s symbiont, Vibrio fischeri, which colonizes light organ crypt epithelia. Activity of both proteins was abrogated by heat treatment and coincubation with specific antibodies. Pretreatment under acidic conditions similar to those during symbiosis initiation rendered V. fischeri more resistant to the antimicrobial activity of the proteins. Immunocytochemistry localized EsBPIs to the symbiotic organ and other epithelial surfaces interacting with ambient seawater. The proteins differed in intracellular distribution. Further, whereas EsBPI4 was restricted to epithelia, EsBPI2 also occurred in blood and in a transient juvenile organ that mediates hatching. The data provide evidence that these BPIs play different defensive roles early in the life of E. scolopes, modulating interactions with the symbiont.

  3. Annotating the protein-RNA interaction sites in proteins using evolutionary information and protein backbone structure.

    Science.gov (United States)

    Li, Tao; Li, Qian-Zhong

    2012-11-07

    RNA-protein interactions play important roles in various biological processes. The precise detection of RNA-protein interaction sites is very important for understanding essential biological processes and annotating the function of the proteins. In this study, based on various features from amino acid sequence and structure, including evolutionary information, solvent accessible surface area and torsion angles (φ, ψ) in the backbone structure of the polypeptide chain, a computational method for predicting RNA-binding sites in proteins is proposed. When the method is applied to predict RNA-binding sites in three datasets: RBP86 containing 86 protein chains, RBP107 containing 107 proteins chains and RBP109 containing 109 proteins chains, better sensitivities and specificities are obtained compared to previously published methods in five-fold cross-validation tests. In order to make further examination for the efficiency of our method, the RBP107 dataset is used as training set, RBP86 and RBP109 datasets are used as the independent test sets. In addition, as examples of our prediction, RNA-binding sites in a few proteins are presented. The annotated results are consistent with the PDB annotation. These results show that our method is useful for annotating RNA binding sites of novel proteins.

  4. Unraveling interlimb interactions underlying bimanual coordination

    NARCIS (Netherlands)

    Ridderikhoff, A.; Daffertshofer, A.; Peper, C.E.; Beek, P.J.

    2005-01-01

    Three sources of interlimb interactions have been postulated to underlie the stability characteristics of bimanual coordination but have never been evaluated in conjunction: integrated timing of feedforward control signals, phase entrainment by contralateral afference, and timing corrections based

  5. Luminescent and paramagnetic properties of nanoparticles shed light on their interactions with proteins

    OpenAIRE

    Dal Cortivo, Giuditta; Wagner, Gabriel E.; Cortelletti, Paolo; Padmanabha Das, Krishna Mohan; Zangger, Klaus; Speghini, Adolfo; Dell’Orco, Daniele; Meyer, N. Helge

    2018-01-01

    Nanoparticles have been recognized as promising tools for targeted drug-delivery and protein therapeutics. However, the mechanisms of protein-nanoparticle interaction and the dynamics underlying the binding process are poorly understood. Here, we present a general methodology for the characterization of protein-nanoparticle interaction on a molecular level. To this end we combined biophysical techniques including nuclear magnetic resonance (NMR), circular dichroism (CD), resonance energy tran...

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

    NARCIS (Netherlands)

    Rahmani, Hossein

    2012-01-01

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

  7. Gap junctions and connexin-interacting proteins

    NARCIS (Netherlands)

    Giepmans, Ben N G

    2004-01-01

    Gap junctions form channels between adjacent cells. The core proteins of these channels are the connexins. Regulation of gap junction communication (GJC) can be modulated by connexin-associating proteins, such as regulatory protein phosphatases and protein kinases, of which c-Src is the

  8. Regulation of PCNA-protein interactions for genome stability

    DEFF Research Database (Denmark)

    Mailand, Niels; Gibbs-Seymour, Ian; Bekker-Jensen, Simon

    2013-01-01

    Proliferating cell nuclear antigen (PCNA) has a central role in promoting faithful DNA replication, providing a molecular platform that facilitates the myriad protein-protein and protein-DNA interactions that occur at the replication fork. Numerous PCNA-associated proteins compete for binding...

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

    OpenAIRE

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

    2008-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Arnout Voet

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

  11. AtPIN: Arabidopsis thaliana Protein Interaction Network

    Directory of Open Access Journals (Sweden)

    Silva-Filho Marcio C

    2009-12-01

    Full Text Available Abstract Background Protein-protein interactions (PPIs constitute one of the most crucial conditions to sustain life in living organisms. To study PPI in Arabidopsis thaliana we have developed AtPIN, a database and web interface for searching and building interaction networks based on publicly available protein-protein interaction datasets. Description All interactions were divided into experimentally demonstrated or predicted. The PPIs in the AtPIN database present a cellular compartment classification (C3 which divides the PPI into 4 classes according to its interaction evidence and subcellular localization. It has been shown in the literature that a pair of genuine interacting proteins are generally expected to have a common cellular role and proteins that have common interaction partners have a high chance of sharing a common function. In AtPIN, due to its integrative profile, the reliability index for a reported PPI can be postulated in terms of the proportion of interaction partners that two proteins have in common. For this, we implement the Functional Similarity Weight (FSW calculation for all first level interactions present in AtPIN database. In order to identify target proteins of cytosolic glutamyl-tRNA synthetase (Cyt-gluRS (AT5G26710 we combined two approaches, AtPIN search and yeast two-hybrid screening. Interestingly, the proteins glutamine synthetase (AT5G35630, a disease resistance protein (AT3G50950 and a zinc finger protein (AT5G24930, which has been predicted as target proteins for Cyt-gluRS by AtPIN, were also detected in the experimental screening. Conclusions AtPIN is a friendly and easy-to-use tool that aggregates information on Arabidopsis thaliana PPIs, ontology, and sub-cellular localization, and might be a useful and reliable strategy to map protein-protein interactions in Arabidopsis. AtPIN can be accessed at http://bioinfo.esalq.usp.br/atpin.

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

    Science.gov (United States)

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

    2016-11-01

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

  13. Protein-lipid interactions: paparazzi hunting for snap-shots

    NARCIS (Netherlands)

    Haberkant, P.|info:eu-repo/dai/nl/311488749; van Meer, G.|info:eu-repo/dai/nl/068570368

    2009-01-01

    Photoactivatable groups meeting the criterion of minimal perturbance allow the investigation of interactions in biological samples. Here, we review the application of photoactivatable groups in lipids enabling the study of protein-lipid interactions in (biological) membranes. The chemistry of

  14. Interactions between globular proteins and procyanidins of different degrees of polymerization

    NARCIS (Netherlands)

    Prigent, S.V.E.; Voragen, A.G.J.; Koningsveld, van G.A.; Baron, A.; Renard, C.M.; Gruppen, H.

    2009-01-01

    Interactions of proteins with phenolic compounds occur in food products containing vegetable sources, such as cocoa, cereals, or yogurts containing fruit. Such interactions can modify protein digestion and protein industrial properties. Noncovalent interactions between globular proteins (proteins

  15. Visualization of protein interaction networks: problems and solutions

    Science.gov (United States)

    2013-01-01

    Background Visualization concerns the representation of data visually and is an important task in scientific research. Protein-protein interactions (PPI) are discovered using either wet lab techniques, such mass spectrometry, or in silico predictions tools, resulting in large collections of interactions stored in specialized databases. The set of all interactions of an organism forms a protein-protein interaction network (PIN) and is an important tool for studying the behaviour of the cell machinery. Since graphic representation of PINs may highlight important substructures, e.g. protein complexes, visualization is more and more used to study the underlying graph structure of PINs. Although graphs are well known data structures, there are different open problems regarding PINs visualization: the high number of nodes and connections, the heterogeneity of nodes (proteins) and edges (interactions), the possibility to annotate proteins and interactions with biological information extracted by ontologies (e.g. Gene Ontology) that enriches the PINs with semantic information, but complicates their visualization. Methods In these last years many software tools for the visualization of PINs have been developed. Initially thought for visualization only, some of them have been successively enriched with new functions for PPI data management and PIN analysis. The paper analyzes the main software tools for PINs visualization considering four main criteria: (i) technology, i.e. availability/license of the software and supported OS (Operating System) platforms; (ii) interoperability, i.e. ability to import/export networks in various formats, ability to export data in a graphic format, extensibility of the system, e.g. through plug-ins; (iii) visualization, i.e. supported layout and rendering algorithms and availability of parallel implementation; (iv) analysis, i.e. availability of network analysis functions, such as clustering or mining of the graph, and the possibility to

  16. The dynamic multisite interactions between two intrinsically disordered proteins

    KAUST Repository

    Wu, Shaowen

    2017-05-11

    Protein interactions involving intrinsically disordered proteins (IDPs) comprise a variety of binding modes, from the well characterized folding upon binding to dynamic fuzzy complex. To date, most studies concern the binding of an IDP to a structured protein, while the Interaction between two IDPs is poorly understood. In this study, we combined NMR, smFRET, and molecular dynamics (MD) simulation to characterize the interaction between two IDPs, the C-terminal domain (CTD) of protein 4.1G and the nuclear mitotic apparatus (NuMA) protein. It is revealed that CTD and NuMA form a fuzzy complex with remaining structural disorder. Multiple binding sites on both proteins were identified by MD and mutagenesis studies. Our study provides an atomic scenario in which two IDPs bearing multiple binding sites interact with each other in dynamic equilibrium. The combined approach employed here could be widely applicable for investigating IDPs and their dynamic interactions.

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

    DEFF Research Database (Denmark)

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

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Xiaomin Wang

    2011-01-01

    Full Text Available With the availability of more and more genome-scale protein-protein interaction (PPI networks, research interests gradually shift to Systematic Analysis on these large data sets. A key topic is to predict protein complexes in PPI networks by identifying clusters that are densely connected within themselves but sparsely connected with the rest of the network. In this paper, we present a new topology-based algorithm, HKC, to detect protein complexes in genome-scale PPI networks. HKC mainly uses the concepts of highest k-core and cohesion to predict protein complexes by identifying overlapping clusters. The experiments on two data sets and two benchmarks show that our algorithm has relatively high F-measure and exhibits better performance compared with some other methods.

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

    Science.gov (United States)

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

    2018-01-15

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

  20. Reconstituting Protein Interaction Networks Using Parameter-Dependent Domain-Domain Interactions

    Science.gov (United States)

    2013-05-07

    that approximately 80% of eukaryotic proteins and 67% of prokaryotic proteins have multiple domains [13,14]. Most annotation databases characterize...domain annotations, Domain-domain interactions, Protein-protein interaction networks Background The living cell is a dynamic, interconnected system...detailed in Methods. Here, we illustrate its application on a well- annotated single- cell organism. We created a merged set of protein-domain annotations

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

    Science.gov (United States)

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

    2017-09-25

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

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

    Directory of Open Access Journals (Sweden)

    Yonatan Schweitzer

    2015-02-01

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

  3. Receptors, G proteins, and their interactions

    NARCIS (Netherlands)

    Hollmann, Markus W.; Strumper, Danja; Herroeder, Susanne; Durieux, Marcel E.

    2005-01-01

    Membrane receptors coupling to intracellular G proteins (G protein-coupled receptors) form one of the major classes of membrane signaling proteins. They are of great importance to the practice of anesthesiology because they are involved in many systems of relevance to the specialty (cardiovascular

  4. 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.

  5. A two-hybrid assay to study protein interactions within the secretory pathway.

    Directory of Open Access Journals (Sweden)

    Danielle H Dube

    Full Text Available Interactions of transcriptional activators are difficult to study using transcription-based two-hybrid assays due to potent activation resulting in false positives. Here we report the development of the Golgi two-hybrid (G2H, a method that interrogates protein interactions within the Golgi, where transcriptional activators can be assayed with negligible background. The G2H relies on cell surface glycosylation to report extracellularly on protein-protein interactions occurring within the secretory pathway. In the G2H, protein pairs are fused to modular domains of the reporter glycosyltransferase, Och1p, and proper cell wall formation due to Och1p activity is observed only when a pair of proteins interacts. Cells containing interacting protein pairs are identified by selectable phenotypes associated with Och1p activity and proper cell wall formation: cells that have interacting proteins grow under selective conditions and display weak wheat germ agglutinin (WGA binding by flow cytometry, whereas cells that lack interacting proteins display stunted growth and strong WGA binding. Using this assay, we detected the interaction between transcription factor MyoD and its binding partner Id2. Interfering mutations along the MyoD:Id2 interaction interface ablated signal in the G2H assay. Furthermore, we used the G2H to detect interactions of the activation domain of Gal4p with a variety of binding partners. Finally, selective conditions were used to enrich for cells encoding interacting partners. The G2H detects protein-protein interactions that cannot be identified via traditional two-hybrid methods and should be broadly useful for probing previously inaccessible subsets of the interactome, including transcriptional activators and proteins that traffic through the secretory pathway.

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

    Science.gov (United States)

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

    2013-03-08

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

  7. FACETS: multi-faceted functional decomposition of protein interaction networks

    Science.gov (United States)

    Seah, Boon-Siew; Bhowmick, Sourav S.; Forbes Dewey, C.

    2012-01-01

    Motivation: The availability of large-scale curated protein interaction datasets has given rise to the opportunity to investigate higher level organization and modularity within the protein–protein interaction (PPI) network using graph theoretic analysis. Despite the recent progress, systems level analysis of high-throughput PPIs remains a daunting task because of the amount of data they present. In this article, we propose a novel PPI network decomposition algorithm called FACETS in order to make sense of the deluge of interaction data using Gene Ontology (GO) annotations. FACETS finds not just a single functional decomposition of the PPI network, but a multi-faceted atlas of functional decompositions that portray alternative perspectives of the functional landscape of the underlying PPI network. Each facet in the atlas represents a distinct interpretation of how the network can be functionally decomposed and organized. Our algorithm maximizes interpretative value of the atlas by optimizing inter-facet orthogonality and intra-facet cluster modularity. Results: We tested our algorithm on the global networks from IntAct, and compared it with gold standard datasets from MIPS and KEGG. We demonstrated the performance of FACETS. We also performed a case study that illustrates the utility of our approach. Contact: seah0097@ntu.edu.sg or assourav@ntu.edu.sg Supplementary information: Supplementary data are available at the Bioinformatics online. Availability: Our software is available freely for non-commercial purposes from: http://www.cais.ntu.edu.sg/∼assourav/Facets/ PMID:22908217

  8. Prediction of protein–protein interactions: unifying evolution and structure at protein interfaces

    International Nuclear Information System (INIS)

    Tuncbag, Nurcan; Gursoy, Attila; Keskin, Ozlem

    2011-01-01

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

  9. Mitochondrial nucleoid interacting proteins support mitochondrial protein synthesis.

    Science.gov (United States)

    He, J; Cooper, H M; Reyes, A; Di Re, M; Sembongi, H; Litwin, T R; Gao, J; Neuman, K C; Fearnley, I M; Spinazzola, A; Walker, J E; Holt, I J

    2012-07-01

    Mitochondrial ribosomes and translation factors co-purify with mitochondrial nucleoids of human cells, based on affinity protein purification of tagged mitochondrial DNA binding proteins. Among the most frequently identified proteins were ATAD3 and prohibitin, which have been identified previously as nucleoid components, using a variety of methods. Both proteins are demonstrated to be required for mitochondrial protein synthesis in human cultured cells, and the major binding partner of ATAD3 is the mitochondrial ribosome. Altered ATAD3 expression also perturbs mtDNA maintenance and replication. These findings suggest an intimate association between nucleoids and the machinery of protein synthesis in mitochondria. ATAD3 and prohibitin are tightly associated with the mitochondrial membranes and so we propose that they support nucleic acid complexes at the inner membrane of the mitochondrion.

  10. A Physical Interaction Network of Dengue Virus and Human Proteins*

    Science.gov (United States)

    Khadka, Sudip; Vangeloff, Abbey D.; Zhang, Chaoying; Siddavatam, Prasad; Heaton, Nicholas S.; Wang, Ling; Sengupta, Ranjan; Sahasrabudhe, Sudhir; Randall, Glenn; Gribskov, Michael; Kuhn, Richard J.; Perera, Rushika; LaCount, Douglas J.

    2011-01-01

    Dengue virus (DENV), an emerging mosquito-transmitted pathogen capable of causing severe disease in humans, interacts with host cell factors to create a more favorable environment for replication. However, few interactions between DENV and human proteins have been reported to date. To identify DENV-human protein interactions, we used high-throughput yeast two-hybrid assays to screen the 10 DENV proteins against a human liver activation domain library. From 45 DNA-binding domain clones containing either full-length viral genes or partially overlapping gene fragments, we identified 139 interactions between DENV and human proteins, the vast majority of which are novel. These interactions involved 105 human proteins, including six previously implicated in DENV infection and 45 linked to the replication of other viruses. Human proteins with functions related to the complement and coagulation cascade, the centrosome, and the cytoskeleton were enriched among the DENV interaction partners. To determine if the cellular proteins were required for DENV infection, we used small interfering RNAs to inhibit their expression. Six of 12 proteins targeted (CALR, DDX3X, ERC1, GOLGA2, TRIP11, and UBE2I) caused a significant decrease in the replication of a DENV replicon. We further showed that calreticulin colocalized with viral dsRNA and with the viral NS3 and NS5 proteins in DENV-infected cells, consistent with a direct role for calreticulin in DENV replication. Human proteins that interacted with DENV had significantly higher average degree and betweenness than expected by chance, which provides additional support for the hypothesis that viruses preferentially target cellular proteins that occupy central position in the human protein interaction network. This study provides a valuable starting point for additional investigations into the roles of human proteins in DENV infection. PMID:21911577

  11. A physical interaction network of dengue virus and human proteins.

    Science.gov (United States)

    Khadka, Sudip; Vangeloff, Abbey D; Zhang, Chaoying; Siddavatam, Prasad; Heaton, Nicholas S; Wang, Ling; Sengupta, Ranjan; Sahasrabudhe, Sudhir; Randall, Glenn; Gribskov, Michael; Kuhn, Richard J; Perera, Rushika; LaCount, Douglas J

    2011-12-01

    Dengue virus (DENV), an emerging mosquito-transmitted pathogen capable of causing severe disease in humans, interacts with host cell factors to create a more favorable environment for replication. However, few interactions between DENV and human proteins have been reported to date. To identify DENV-human protein interactions, we used high-throughput yeast two-hybrid assays to screen the 10 DENV proteins against a human liver activation domain library. From 45 DNA-binding domain clones containing either full-length viral genes or partially overlapping gene fragments, we identified 139 interactions between DENV and human proteins, the vast majority of which are novel. These interactions involved 105 human proteins, including six previously implicated in DENV infection and 45 linked to the replication of other viruses. Human proteins with functions related to the complement and coagulation cascade, the centrosome, and the cytoskeleton were enriched among the DENV interaction partners. To determine if the cellular proteins were required for DENV infection, we used small interfering RNAs to inhibit their expression. Six of 12 proteins targeted (CALR, DDX3X, ERC1, GOLGA2, TRIP11, and UBE2I) caused a significant decrease in the replication of a DENV replicon. We further showed that calreticulin colocalized with viral dsRNA and with the viral NS3 and NS5 proteins in DENV-infected cells, consistent with a direct role for calreticulin in DENV replication. Human proteins that interacted with DENV had significantly higher average degree and betweenness than expected by chance, which provides additional support for the hypothesis that viruses preferentially target cellular proteins that occupy central position in the human protein interaction network. This study provides a valuable starting point for additional investigations into the roles of human proteins in DENV infection.

  12. Interactions of carbohydrates and proteins by fluorophore-assisted ...

    Indian Academy of Sciences (India)

    A sensitive, specific, and rapid method for the detection of carbohydrate-protein interactions is demonstrated by fluorophore-assisted carbohydrate electrophoresis (FACE). The procedure is simple and the cost is low. The advantage of this method is that carbohydrate-protein interactions can be easily displayed by FACE, ...

  13. Small sets of interacting proteins suggest functional linkage mechanisms via Bayesian analogical reasoning.

    Science.gov (United States)

    Airoldi, Edoardo M; Heller, Katherine A; Silva, Ricardo

    2011-07-01

    Proteins and protein complexes coordinate their activity to execute cellular functions. In a number of experimental settings, including synthetic genetic arrays, genetic perturbations and RNAi screens, scientists identify a small set of protein interactions of interest. A working hypothesis is often that these interactions are the observable phenotypes of some functional process, which is not directly observable. Confirmatory analysis requires finding other pairs of proteins whose interaction may be additional phenotypical evidence about the same functional process. Extant methods for finding additional protein interactions rely heavily on the information in the newly identified set of interactions. For instance, these methods leverage the attributes of the individual proteins directly, in a supervised setting, in order to find relevant protein pairs. A small set of protein interactions provides a small sample to train parameters of prediction methods, thus leading to low confidence. We develop RBSets, a computational approach to ranking protein interactions rooted in analogical reasoning; that is, the ability to learn and generalize relations between objects. Our approach is tailored to situations where the training set of protein interactions is small, and leverages the attributes of the individual proteins indirectly, in a Bayesian ranking setting that is perhaps closest to propensity scoring in mathematical psychology. We find that RBSets leads to good performance in identifying additional interactions starting from a small evidence set of interacting proteins, for which an underlying biological logic in terms of functional processes and signaling pathways can be established with some confidence. Our approach is scalable and can be applied to large databases with minimal computational overhead. Our results suggest that analogical reasoning within a Bayesian ranking problem is a promising new approach for real-time biological discovery. Java code is available at

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

    Rosell, Mireia; Fernández-Recio, Juan

    2018-04-01

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

  16. Interactions among tobacco sieve element occlusion (SEO) proteins.

    Science.gov (United States)

    Jekat, Stephan B; Ernst, Antonia M; Zielonka, Sascia; Noll, Gundula A; Prüfer, Dirk

    2012-12-01

    Angiosperms transport their photoassimilates through sieve tubes, which comprise longitudinally-connected sieve elements. In dicots and also some monocots, the sieve elements contain parietal structural proteins known as phloem proteins or P-proteins. Following injury, P proteins disperse and accumulate as viscous plugs at the sieve plates to prevent the loss of valuable transport sugars. Tobacco (Nicotiana tabacum) P-proteins are multimeric complexes comprising subunits encoded by members of the SEO (sieve element occlusion) gene family. The existence of multiple subunits suggests that P-protein assembly involves interactions between SEO proteins, but this process is largely uncharacterized and it is unclear whether the different subunits perform unique roles or are redundant. We therefore extended our analysis of the tobacco P-proteins NtSEO1 and NtSEO2 to investigate potential interactions between them, and found that both proteins can form homomeric and heteromeric complexes in planta.

  17. Structural study of surfactant-dependent interaction with protein

    Energy Technology Data Exchange (ETDEWEB)

    Mehan, Sumit; Aswal, Vinod K., E-mail: vkaswal@barc.gov.in [Solid State Physics Division, Bhabha Atomic Research Centre, Mumbai 400 085 (India); Kohlbrecher, Joachim [Laboratory for Neutron Scattering, Paul Scherrer Institut, CH-5232 PSI Villigen (Switzerland)

    2015-06-24

    Small-angle neutron scattering (SANS) has been used to study the complex structure of anionic BSA protein with three different (cationic DTAB, anionic SDS and non-ionic C12E10) surfactants. These systems form very different surfactant-dependent complexes. We show that the structure of protein-surfactant complex is initiated by the site-specific electrostatic interaction between the components, followed by the hydrophobic interaction at high surfactant concentrations. It is also found that hydrophobic interaction is preferred over the electrostatic interaction in deciding the resultant structure of protein-surfactant complexes.

  18. Identification of Brain-Specific Angiogenesis Inhibitor 2 as an Interaction Partner of Glutaminase Interacting Protein

    Science.gov (United States)

    Zencir, Sevil; Ovee, Mohiuddin; Dobson, Melanie J.; Banerjee, Monimoy; Topcu, Zeki; Mohanty, Smita

    2011-01-01

    The vast majority of physiological processes in living cells are mediated by protein-protein interactions often specified by particular protein sequence motifs. PDZ domains, composed of 80–100 amino acid residues, are an important class of interaction motif. Among the PDZ-containing proteins, Glutaminase Interacting Protein (GIP), also known as Tax Interacting Protein TIP-1, is unique in being composed almost exclusively of a single PDZ domain. GIP has important roles in cellular signalling, protein scaffolding and modulation of tumor growth and interact with a number of physiological partner proteins, including Glutaminase L, β-Catenin, FAS, HTLV Tax, HPV E6, Rhotekin and Kir 2.3. To identify the network of proteins that interact with GIP, a human fetal brain cDNA library was screened using a yeast two-hybrid assay with GIP as bait. We identified Brain-specific Angiogenesis Inhibitor 2 (BAI2), a member of the adhesion-G protein-coupled receptors (GPCRs), as a new partner of GIP. BAI2 is expressed primarily in neurons, further expanding GIP cellular functions. The interaction between GIP and the carboxy-terminus of BAI2 was characterized using fluorescence, Circular Dichroism (CD) and Nuclear Magnetic Resonance (NMR) spectroscopy assays. These biophysical analyses support the interaction identified in the yeast two-hybrid assay. This is the first study reporting BAI2 as an interaction partner of GIP. PMID:21787750

  19. Imaging protein-protein interactions in living cells

    NARCIS (Netherlands)

    Hink, M.A.; Bisseling, T.; Visser, A.J.W.G.

    2002-01-01

    The complex organization of plant cells makes it likely that the molecular behaviour of proteins in the test tube and the cell is different. For this reason, it is essential though a challenge to study proteins in their natural environment. Several innovative microspectroscopic approaches provide

  20. Understanding protein–protein interactions by genetic suppression

    Indian Academy of Sciences (India)

    Unknown

    Protein–protein interactions influence many cellular processes and it is increasingly being felt that even a weak and remote interplay between two subunits of a protein or between two proteins in a complex may govern the fate of a par- ticular biochemical pathway. In a bacterial system where the complete genome ...

  1. Understanding protein–protein interactions by genetic suppression

    Indian Academy of Sciences (India)

    Protein–protein interactions influence many cellular processes and it is increasingly being felt that even a weak and remote interplay between two subunits of a protein or between two proteins in a complex may govern the fate of a particular biochemical pathway. In a bacterial system where the complete genome sequence ...

  2. Interaction between Protein, Phytate, and Microbial Phytase. In Vitro Studies

    NARCIS (Netherlands)

    Kies, A.K.; Jonge, de L.H.; Kemme, P.A.; Jongbloed, A.W.

    2006-01-01

    The interaction between protein and phytate was investigated in vitro using proteins extracted from five common feedstuffs and from casein. The appearance of naturally present soluble protein-phytate complexes in the feedstuffs, the formation of complexes at different pHs, and the degradation of

  3. Interaction between Vaccinium bracteatum Thunb. leaf pigment and rice proteins.

    Science.gov (United States)

    Wang, Li; Xu, Yuan; Zhou, Sumei; Qian, Haifeng; Zhang, Hui; Qi, Xiguang; Fan, Meihua

    2016-03-01

    In this study, we investigated the interaction of Vaccinium bracteatum Thunb. leaf (VBTL) pigment and rice proteins. In the presence of rice protein, VBTL pigment antioxidant activity and free polyphenol content decreased by 67.19% and 68.11%, respectively, and L(∗) of the protein-pigment complex decreased significantly over time. L(∗) values of albumin, globulin and glutelin during 60-min pigment exposure decreased by 55.00, 57.14, and 54.30%, respectively, indicating that these proteins had bound to the pigment. A significant difference in protein surface hydrophobicity was observed between rice proteins and pigment-protein complexes, indicating that hydrophobic interaction is a major binding mechanism between VBTL pigment and rice proteins. A significant difference in secondary structures between proteins and protein-pigment complexes was also uncovered, indicating that hydrogen bonding may be another mode of interaction between VBTL pigment and rice proteins. Our results indicate that VBTL pigment can stain rice proteins with hydrophobic and hydrogen interactions. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Protein-lipid interactions: from membrane domains to cellular networks

    National Research Council Canada - National Science Library

    Tamm, Lukas K

    2005-01-01

    ... membranes is the lipid bilayer. Embedded in the fluid lipid bilayer are proteins of various shapes and traits. This volume illuminates from physical, chemical and biological angles the numerous - mostly quite weak - interactions between lipids, proteins, and proteins and lipids that define the delicate, highly dynamic and yet so stable fabri...

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

    Science.gov (United States)

    Park, Byungkyu; Han, Kyungsook

    2010-01-18

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

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

    NARCIS (Netherlands)

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

    2014-01-01

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

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

    NARCIS (Netherlands)

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

    2014-01-01

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

  8. Casein - whey protein interactions in heated milk

    NARCIS (Netherlands)

    Vasbinder, Astrid Jolanda

    2002-01-01

    Heating of milk is an essential step in the processing of various dairy products, like for example yoghurt. A major consequence of the heat treatment is the denaturation of whey proteins, which either associate with the casein micelle or form soluble whey protein aggregates. By combination of

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

    Science.gov (United States)

    Matos, Sérgio; Antunes, Rui

    2017-12-13

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

  10. Molecular interactions of graphene oxide with human blood plasma proteins

    Science.gov (United States)

    Kenry, Affa Affb Affc; Loh, Kian Ping; Lim, Chwee Teck

    2016-04-01

    We investigate the molecular interactions between graphene oxide (GO) and human blood plasma proteins. To gain an insight into the bio-physico-chemical activity of GO in biological and biomedical applications, we performed a series of biophysical assays to quantify the molecular interactions between GO with different lateral size distributions and the three essential human blood plasma proteins. We elucidate the various aspects of the GO-protein interactions, particularly, the adsorption, binding kinetics and equilibrium, and conformational stability, through determination of quantitative parameters, such as GO-protein association constants, binding cooperativity, and the binding-driven protein structural changes. We demonstrate that the molecular interactions between GO and plasma proteins are significantly dependent on the lateral size distribution and mean lateral sizes of the GO nanosheets and their subtle variations may markedly influence the GO-protein interactions. Consequently, we propose the existence of size-dependent molecular interactions between GO nanosheets and plasma proteins, and importantly, the presence of specific critical mean lateral sizes of GO nanosheets in achieving very high association and fluorescence quenching efficiency of the plasma proteins. We anticipate that this work will provide a basis for the design of graphene-based and other related nanomaterials for a plethora of biological and biomedical applications.

  11. Dendrimer-protein interactions versus dendrimer-based nanomedicine.

    Science.gov (United States)

    Shcharbin, Dzmitry; Shcharbina, Natallia; Dzmitruk, Volha; Pedziwiatr-Werbicka, Elzbieta; Ionov, Maksim; Mignani, Serge; de la Mata, F Javier; Gómez, Rafael; Muñoz-Fernández, Maria Angeles; Majoral, Jean-Pierre; Bryszewska, Maria

    2017-04-01

    Dendrimers are hyperbranched polymers belonging to the huge class of nanomedical devices. Their wide application in biology and medicine requires understanding of the fundamental mechanisms of their interactions with biological systems. Summarizing, electrostatic force plays the predominant role in dendrimer-protein interactions, especially with charged dendrimers. Other kinds of interactions have been proven, such as H-bonding, van der Waals forces, and even hydrophobic interactions. These interactions depend on the characteristics of both participants: flexibility and surface charge of a dendrimer, rigidity of protein structure and the localization of charged amino acids at its surface. pH and ionic strength of solutions can significantly modulate interactions. Ligands and cofactors attached to a protein can also change dendrimer-protein interactions. Binding of dendrimers to a protein can change its secondary structure, conformation, intramolecular mobility and functional activity. However, this strongly depends on rigidity versus flexibility of a protein's structure. In addition, the potential applications of dendrimers to nanomedicine are reviwed related to dendrimer-protein interactions. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Interactions between soy protein hydrolyzates and wheat proteins in noodle making dough.

    Science.gov (United States)

    Guo, Xingfeng; Sun, Xiaohong; Zhang, Yingying; Wang, Ruihong; Yan, Xin

    2018-04-15

    Soy protein hydrolyzate has been used as supplements in wheat flour to enhance the nutritional value of its products, but it may negatively affect the gluten properties simultaneously. In order to explore the mechanism of this effect, protein characteristics including disulfide bond, protein composition, intermolecular force of dough proteins, and atomic force microscope images of gluten were obtained. Results showed that disulfide bonds in dough increased when soy protein hydrolyzate was added, but glutenin macropolymer decreased. Atomic force microscope images showed that gluten were weakened by soy protein hydrolyzate. Based on these results, a model was developed to describe the interaction between soy protein hydrolyzates and wheat proteins: soy protein hydrolyzates linked with wheat proteins through disulfide bond, disrupted the glutenins polymerization, thus hindered gluten networks formation. The interaction between wheat proteins and soy protein hydrolyzates in noodle making dough could be described with this model reasonably. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Decoding the intrinsic mechanism that prohibits ALIX interaction with ESCRT and viral proteins.

    Science.gov (United States)

    Zhou, Xi; Si, Jiali; Corvera, Joe; Gallick, Gary E; Kuang, Jian

    2010-12-15

    The adaptor protein ALIX [ALG-2 (apoptosis-linked-gene-2 product)-interacting protein X] links retroviruses to ESCRT (endosomal sorting complex required for transport) machinery during retroviral budding. This function of ALIX requires its interaction with the ESCRT-III component CHMP4 (charged multivesicular body protein 4) at the N-terminal Bro1 domain and retroviral Gag proteins at the middle V domain. Since cytoplasmic or recombinant ALIX is unable to interact with CHMP4 or retroviral Gag proteins under non-denaturing conditions, we constructed ALIX truncations and mutations to define the intrinsic mechanism through which ALIX interactions with these partner proteins are prohibited. Our results demonstrate that an intramolecular interaction between Patch 2 in the Bro1 domain and the TSG101 (tumour susceptibility gene 101 protein)-docking site in the proline-rich domain locks ALIX into a closed conformation that renders ALIX unable to interact with CHMP4 and retroviral Gag proteins. Relieving the intramolecular interaction of ALIX, by ectopically expressing a binding partner for one of the intramolecular interaction sites or by deleting one of these sites, promotes ALIX interaction with these partner proteins and facilitates ALIX association with the membrane. Ectopic expression of a GFP (green fluorescent protein)-ALIX mutant with a constitutively open conformation, but not the wild-type protein, increases EIAV (equine infectious anaemia virus) budding from HEK (human embryonic kidney)-293 cells. These findings predict that relieving the autoinhibitory intramolecular interaction of ALIX is a critical step for ALIX to participate in retroviral budding.

  14. Differential occurrence of interactions and interaction domains in proteins containing homopolymeric amino acid repeats

    Directory of Open Access Journals (Sweden)

    Ilaria ePelassa

    2015-12-01

    Full Text Available Homopolymeric amino acids repeats (AARs, which are widespread in proteomes, have often been viewed simply as spacers between protein domains, or even as ‘junk’ sequences with no obvious function but with a potential to cause harm upon expansion as in genetic diseases associated with polyglutamine or polyalanine expansions, including Huntington disease and cleidocranial dysplasia. A growing body of evidence indicates however that at least some AARs can form organized, functional protein structures and can regulate protein function. In particular, certain AARs can mediate protein-protein interactions, either through homotypic AAR-AAR contacts or through heterotypic contacts with other protein domains. It is still unclear however, whether AARs may have a generalized, proteome-wide role in shaping protein-protein interaction networks. Therefore, we have undertaken here a bioinformatics screening of the human proteome and interactome in search of quantitative evidence of such a role. We first identified the sets of proteins that contain repeats of any one of the 20 amino acids, as well as control sets of proteins chosen at random in the proteome. We then analyzed the connectivity between the proteins of the AAR-containing protein sets and we compared it with that observed in the corresponding control networks. We find evidence for different degrees of connectivity in the different AAR-containing protein networks. Indeed, networks of proteins containing polyglutamine, polyglutamate, polyproline and other AARs show significantly increased levels of connectivity, whereas networks containing polyleucine and other hydrophobic repeats show lower degrees of connectivity. Furthermore, we observed that numerous protein-protein, -nucleic acid and -lipid interaction domains are significantly enriched in specific AAR protein groups. These findings support the notion of a generalized, combinatorial role of AARs, together with conventional protein interaction

  15. The role of electrostatics in protein-protein interactions of a monoclonal antibody.

    Science.gov (United States)

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

    2014-07-07

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

  16. In silico study of interaction between rice proteins enhanced disease ...

    Indian Academy of Sciences (India)

    EDS1 interacts with its positive co-regulator phytoalexin deficient 4 (PAD4), resulting in mobilization of the salicylic acid defence pathway. Limited information regarding this interaction in rice is available. To study this interaction, a model of EDS1 and PAD4 proteins from rice was generated and validated with Accelrys DS ...

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

    Science.gov (United States)

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

    2017-11-14

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

  18. Ion-solid interactions under channeling conditions

    International Nuclear Information System (INIS)

    Kurup, M.B.

    1992-01-01

    When an energetic beam of ions enters a single crystal target along one of its major crystallographic directions, channeling of these ions takes place. For the well channeled ions, low impact parameter collisions are strongly suppressed and it was shown that for such ions moving with velocities v i >> v f , where v f is the Fermi velocity of the target electrons, the projectiles can be treated as being bombarded by a weakly bound target electron gas. Even though this was established several years ago, the utility of this effect to study electron capture and loss processes in highly charges ions has become evident only recently. Radiative electron capture (REC) and dielectronic capture into inner shells of few electron ions under channeling conditions have shown very interesting features in recent experiments. It has also been seen that the K-shell REC cross-sections follow a universal scaling behaviour with the adiabaticity parameter η (the ratio of kinetic energy of the electron in the projectile frame to the K-shell binding energy of the projectile). There are also indication that electron capture and loss processes in highly stripped ions are not symmetric. In the present talk, we will review the current status of these areas in the light of recent experimental and theoretical results, particularly using fully stripped, hydrogen like and helium like heavy ions. (author). 17 refs., 15 figs

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

    Science.gov (United States)

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

    2013-01-01

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

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

    DEFF Research Database (Denmark)

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

    2013-01-01

    the degradation pathway. This protein belongs to the recently identified GPCR-associated sorting proteins (GASPs) family that comprises ten members for which structural and functional details are poorly documented. We present here a detailed structure-function relationship analysis of the molecular interaction...

  1. A protein domain interaction interface database: InterPare

    Directory of Open Access Journals (Sweden)

    Lee Jungsul

    2005-08-01

    Full Text Available Abstract Background Most proteins function by interacting with other molecules. Their interaction interfaces are highly conserved throughout evolution to avoid undesirable interactions that lead to fatal disorders in cells. Rational drug discovery includes computational methods to identify the interaction sites of lead compounds to the target molecules. Identifying and classifying protein interaction interfaces on a large scale can help researchers discover drug targets more efficiently. Description We introduce a large-scale protein domain interaction interface database called InterPare http://interpare.net. It contains both inter-chain (between chains interfaces and intra-chain (within chain interfaces. InterPare uses three methods to detect interfaces: 1 the geometric distance method for checking the distance between atoms that belong to different domains, 2 Accessible Surface Area (ASA, a method for detecting the buried region of a protein that is detached from a solvent when forming multimers or complexes, and 3 the Voronoi diagram, a computational geometry method that uses a mathematical definition of interface regions. InterPare includes visualization tools to display protein interior, surface, and interaction interfaces. It also provides statistics such as the amino acid propensities of queried protein according to its interior, surface, and interface region. The atom coordinates that belong to interface, surface, and interior regions can be downloaded from the website. Conclusion InterPare is an open and public database server for protein interaction interface information. It contains the large-scale interface data for proteins whose 3D-structures are known. As of November 2004, there were 10,583 (Geometric distance, 10,431 (ASA, and 11,010 (Voronoi diagram entries in the Protein Data Bank (PDB containing interfaces, according to the above three methods. In the case of the geometric distance method, there are 31,620 inter-chain domain

  2. Computational studies on the interactions of nanomaterials with proteins and their impacts

    Science.gov (United States)

    An, De-Yi; Su, Ji-Guo; Li, Chun-Hua; Li, Jing-Yuan

    2015-12-01

    The intensive concern over the biosafety of nanomaterials demands the systematic study of the mechanisms underlying their biological effects. Many of the effects of nanomaterials can be attributed to their interactions with proteins and their impacts on protein function. On the other hand, nanomaterials show potential for a variety of biomedical applications, many of which also involve direct interactions with proteins. In this paper, we review some recent computational studies on this subject, especially those investigating the interactions of carbon and gold nanomaterials. Beside hydrophobic and π-stacking interactions, the mode of interaction of carbon nanomaterials can also be regulated by their functional groups. The coatings of gold nanomaterials similarly adjust their mode of interaction, in addition to coordination interactions with the sulfur groups of cysteine residues and the imidazole groups of histidine residues. Nanomaterials can interact with multiple proteins and their impacts on protein activity are attributed to a wide spectrum of mechanisms. These findings on the mechanisms of nanomaterial-protein interactions can further guide the design and development of nanomaterials to realize their application in disease diagnosis and treatment. Project supported by the National Natural Science Foundation of China (Grant Nos. 21273240, 11204267, and 11474013).

  3. Yeast Interacting Proteins Database: YDL239C, YGR268C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ith sequence similarity to that of Type I J-proteins; computational analysis of large-scale protein-protein ...equence similarity to that of Type I J-proteins; computational analysis of large-scale protein-protein inter

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

    Science.gov (United States)

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

    2018-01-01

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

  5. A protein interaction map of the kalimantacin biosynthesis assembly line

    Directory of Open Access Journals (Sweden)

    Birgit Uytterhoeven

    2016-11-01

    Full Text Available The antimicrobial secondary metabolite kalimantacin is produced by a hybrid polyketide/ non-ribosomal peptide system in Pseudomonas fluorescens BCCM_ID9359. In this study, the kalimantacin biosynthesis gene cluster is analyzed by yeast two-hybrid analysis, creating a protein-protein interaction map of the entire assembly line. In total, 28 potential interactions were identified, of which 13 could be confirmed further. These interactions include the dimerization of ketosynthase domains, a link between assembly line modules 9 and 10, and a specific interaction between the trans-acting enoyl reductase BatK and the carrier proteins of modules 8 and 10. These interactions reveal fundamental insight into the biosynthesis of secondary metabolites.This study is the first to reveal interactions in a complete biosynthetic pathway. Similar future studies could build a strong basis for engineering strategies in such clusters.

  6. 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.

  7. Trypanosoma cruzi tryparedoxin II interacts with different peroxiredoxins under physiological and oxidative stress conditions.

    Science.gov (United States)

    Dias, L; Peloso, E F; Leme, A F P; Carnielli, C M; Pereira, C N; Werneck, C C; Guerrero, S; Gadelha, F R

    2018-01-01

    Trypanosoma cruzi, the etiologic agent of Chagas disease, has to cope with reactive oxygen and nitrogen species during its life cycle in order to ensure its survival and infection. The parasite detoxifies these species through a series of pathways centered on trypanothione that depend on glutathione or low molecular mass dithiol proteins such as tryparedoxins. These proteins transfer reducing equivalents to peroxidases, including mitochondrial and cytosolic peroxiredoxins, TcMPx and TcCPx, respectively. In T. cruzi two tryparedoxins have been identified, TXNI and TXNII with different intracellular locations. TXNI is a cytosolic protein while TXNII due to a C-terminal hydrophobic tail is anchored in the outer membrane of the mitochondrion, endoplasmic reticulum and glycosomes. TXNs have been suggested to be involved in a majority of biological processes ranging from redox mechanisms to protein translation. Herein, a comparison of the TXNII interactomes under physiological and oxidative stress conditions was examined. Under physiological conditions, apart from the proteins with unknown biological process annotation, the majority of the identified proteins are related to cell redox homeostasis and biosynthetic processes, while under oxidative stress conditions, are involved in stress response, cell redox homeostasis, arginine biosynthesis and microtubule based process. Interestingly, although TXNII interacts with both peroxiredoxins under physiological conditions, upon oxidative stress, TcMPx interaction prevails. The relevance of the interactions is discussed opening a new perspective of TXNII functions. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Bilayer-thickness-mediated interactions between integral membrane proteins.

    Science.gov (United States)

    Kahraman, Osman; Koch, Peter D; Klug, William S; Haselwandter, Christoph A

    2016-04-01

    Hydrophobic thickness mismatch between integral membrane proteins and the surrounding lipid bilayer can produce lipid bilayer thickness deformations. Experiment and theory have shown that protein-induced lipid bilayer thickness deformations can yield energetically favorable bilayer-mediated interactions between integral membrane proteins, and large-scale organization of integral membrane proteins into protein clusters in cell membranes. Within the continuum elasticity theory of membranes, the energy cost of protein-induced bilayer thickness deformations can be captured by considering compression and expansion of the bilayer hydrophobic core, membrane tension, and bilayer bending, resulting in biharmonic equilibrium equations describing the shape of lipid bilayers for a given set of bilayer-protein boundary conditions. Here we develop a combined analytic and numerical methodology for the solution of the equilibrium elastic equations associated with protein-induced lipid bilayer deformations. Our methodology allows accurate prediction of thickness-mediated protein interactions for arbitrary protein symmetries at arbitrary protein separations and relative orientations. We provide exact analytic solutions for cylindrical integral membrane proteins with constant and varying hydrophobic thickness, and develop perturbative analytic solutions for noncylindrical protein shapes. We complement these analytic solutions, and assess their accuracy, by developing both finite element and finite difference numerical solution schemes. We provide error estimates of our numerical solution schemes and systematically assess their convergence properties. Taken together, the work presented here puts into place an analytic and numerical framework which allows calculation of bilayer-mediated elastic interactions between integral membrane proteins for the complicated protein shapes suggested by structural biology and at the small protein separations most relevant for the crowded membrane

  9. Anomalous Protein-Protein Interactions in Multivalent Salt Solution

    Czech Academy of Sciences Publication Activity Database

    Pasquier, C.; Vazdar, M.; Forsman, J.; Jungwirth, Pavel; Lund, M.

    2017-01-01

    Roč. 121, č. 14 (2017), s. 3000-3006 ISSN 1520-6106 R&D Projects: GA ČR(CZ) GA16-01074S Institutional support: RVO:61388963 Keywords : Monte Carlo * molecular dynamics * membranes * proteins * multivalent salts Subject RIV: CF - Physical ; Theoretical Chemistry OBOR OECD: Physical chemistry Impact factor: 3.177, year: 2016

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

    Science.gov (United States)

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

    2014-12-01

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

  11. 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.

  12. Hydrophobic Interaction Chromatography for Bottom-Up Proteomics Analysis of Single Proteins and Protein Complexes.

    Science.gov (United States)

    Rackiewicz, Michal; Große-Hovest, Ludger; Alpert, Andrew J; Zarei, Mostafa; Dengjel, Jörn

    2017-06-02

    Hydrophobic interaction chromatography (HIC) is a robust standard analytical method to purify proteins while preserving their biological activity. It is widely used to study post-translational modifications of proteins and drug-protein interactions. In the current manuscript we employed HIC to separate proteins, followed by bottom-up LC-MS/MS experiments. We used this approach to fractionate antibody species followed by comprehensive peptide mapping as well as to study protein complexes in human cells. HIC-reversed-phase chromatography (RPC)-mass spectrometry (MS) is a powerful alternative to fractionate proteins for bottom-up proteomics experiments making use of their distinct hydrophobic properties.

  13. Reciprocal carbonyl-carbonyl interactions in small molecules and proteins.

    Science.gov (United States)

    Rahim, Abdur; Saha, Pinaki; Jha, Kunal Kumar; Sukumar, Nagamani; Sarma, Bani Kanta

    2017-07-19

    Carbonyl-carbonyl n→π* interactions where a lone pair (n) of the oxygen atom of a carbonyl group is delocalized over the π* orbital of a nearby carbonyl group have attracted a lot of attention in recent years due to their ability to affect the 3D structure of small molecules, polyesters, peptides, and proteins. In this paper, we report the discovery of a "reciprocal" carbonyl-carbonyl interaction with substantial back and forth n→π* and π→π* electron delocalization between neighboring carbonyl groups. We have carried out experimental studies, analyses of crystallographic databases and theoretical calculations to show the presence of this interaction in both small molecules and proteins. In proteins, these interactions are primarily found in polyproline II (PPII) helices. As PPII are the most abundant secondary structures in unfolded proteins, we propose that these local interactions may have implications in protein folding.Carbonyl-carbonyl π* non covalent interactions affect the structure and stability of small molecules and proteins. Here, the authors carry out experimental studies, analyses of crystallographic databases and theoretical calculations to describe an additional type of carbonyl-carbonyl interaction.

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

    Directory of Open Access Journals (Sweden)

    Yuichiro Shimizu

    2010-01-01

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

  15. Effect of Astringent Stimuli on Salivary Protein Interactions Elucidated by Complementary Proteomics Approaches.

    Science.gov (United States)

    Delius, Judith; Médard, Guillaume; Kuster, Bernhard; Hofmann, Thomas

    2017-03-15

    The interaction of astringent substances with salivary proteins, which results in protein precipitation, is considered a key event in the molecular mechanism underlying the oral sensation of puckering astringency. As the chemical nature of orally active astringents is diverse and the knowledge of their interactions with salivary proteins rather fragmentary, human whole saliva samples were incubated with suprathreshold and isointensity solutions of the astringent polyphenol (-)-epigallocatechin gallate, the multivalent metal salt iron(III) sulfate, the amino-functionalized polysaccharide chitosan, and the basic protein lysozyme. After separation of the precipitated proteins, the proteins affected by the astringents were identified and relatively quantified for the first time by complementary bottom-up and top-down mass spectrometry-based proteomics approaches. Major salivary target proteins, which may be involved in astringency perception, are reported here for each astringent stimulus.

  16. Interaction of puroindolines with gluten proteins

    Science.gov (United States)

    The effect of puroindolines (PINs) on structural characteristics of gluten proteins was investigated in Triticum turgidum ssp. durum (cv. Svevo) and Triticum aestivum (cv. Alpowa) and from their respective derivatives in which PIN genes were expressed (Soft Svevo) or the distal end of the short arm ...

  17. Membrane interaction of retroviral Gag proteins

    Directory of Open Access Journals (Sweden)

    Robert Alfred Dick

    2014-04-01

    Full Text Available Assembly of an infectious retroviral particle relies on multimerization of the Gag polyprotein at the inner leaflet of the plasma membrane. The three domains of Gag common to all retroviruses-- MA, CA, and NC-- provide the signals for membrane binding, assembly, and viral RNA packaging, respectively. These signals do not function independently of one another. For example, Gag multimerization enhances membrane binding and is more efficient when NC is interacting with RNA. MA binding to the plasma membrane is governed by several principles, including electrostatics, recognition of specific lipid head groups, hydrophobic interactions, and membrane order. HIV-1 uses many of these principles while Rous sarcoma virus (RSV appears to use fewer. This review describes the principles that govern Gag interactions with membranes, focusing on RSV and HIV-1 Gag. The review also defines lipid and membrane behavior, and discusses the complexities in determining how lipid and membrane behavior impact Gag membrane binding.

  18. Dynamic protein interaction modules in human hepatocellular carcinoma progression.

    Science.gov (United States)

    Yu, Hui; Lin, Chen-Ching; Li, Yuan-Yuan; Zhao, Zhongming

    2013-01-01

    Gene expression profiles have been frequently integrated with the human protein interactome to uncover functional modules under specific conditions like disease state. Beyond traditional differential expression analysis, differential co-expression analysis has emerged as a robust approach to reveal condition-specific network modules, with successful applications in a few human disease studies. Hepatocellular carcinoma (HCC), which is often interrelated with the Hepatitis C virus, typically develops through multiple stages. A comprehensive investigation of HCC progression-specific differential co-expression modules may advance our understanding of HCC's pathophysiological mechanisms. Compared with differentially expressed genes, differentially co-expressed genes were found more likely enriched with Hepatitis C virus binding proteins and cancer-mutated genes, and they were clustered more densely in the human reference protein interaction network. These observations indicated that a differential co-expression approach could outperform the standard differential expression network analysis in searching for disease-related modules. We then proposed a differential co-expression network approach to uncover network modules involved in HCC development. Specifically, we discovered subnetworks that enriched differentially co-expressed gene pairs in each HCC transition stage, and further resolved modules with coherent co-expression change patterns over all HCC developmental stages. Our identified network modules were enriched with HCC-related genes and implicated in cancer-related biological functions. In particular, APC and YWHAZ were highlighted as two most remarkable genes in the network modules, and their dynamic interaction partnership was resolved in HCC development. We demonstrated that integration of differential co-expression with the protein interactome could outperform the traditional differential expression approach in discovering network modules of human diseases

  19. Modifications in nanoparticle-protein interactions by varying the protein conformation

    Science.gov (United States)

    Kumar, Sugam; Yadav, I.; Aswal, V. K.; Kohlbrecher, J.

    2017-05-01

    Small-angle neutron scattering has been used to study the interaction of silica nanoparticle with Bovine Serum Albumin (BSA) protein without and with a protein denaturing agent urea. The measurements have been carried out at pH 7 where both the components (nanoparticle and protein) are similarly charged. We show that the interactions in nanoparticle-protein system can be modified by changing the conformation of protein through the presence of urea. In the absence of urea, the strong electrostatic repulsion between the nanoparticle and protein prevents protein adsorption on nanoparticle surface. This non-adsorption, in turn gives rise to depletion attraction between nanoparticles. However, with addition of urea the depletion attraction is completely suppressed. Urea driven denaturation of protein is utilized to expose the positively charged patched of the BSA molecules which eventually leads to adsorption of BSA on nanoparticles eliminating the depletion interaction.

  20. 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.

  1. Measurements of Protein-Protein Interactions by Size Exclusion Chromatography

    OpenAIRE

    Bloustine, J.; Berejnov, V.; Fraden, S.

    2003-01-01

    A method is presented for determining second virial coefficients (B2) of protein solutions from retention time measurements in size exclusion chromatography. We determine B2 by analyzing the concentration dependence of the chromatographic partition coefficient. We show the ability of this method to track the evolution of B2 from positive to negative values in lysozyme and bovine serum albumin solutions. Our size exclusion chromatography results agree quantitatively with data obtained by light...

  2. Weighted Protein Interaction Network Analysis of Frontotemporal Dementia.

    Science.gov (United States)

    Ferrari, Raffaele; Lovering, Ruth C; Hardy, John; Lewis, Patrick A; Manzoni, Claudia

    2017-02-03

    The genetic analysis of complex disorders has undoubtedly led to the identification of a wealth of associations between genes and specific traits. However, moving from genetics to biochemistry one gene at a time has, to date, rather proved inefficient and under-powered to comprehensively explain the molecular basis of phenotypes. Here we present a novel approach, weighted protein-protein interaction network analysis (W-PPI-NA), to highlight key functional players within relevant biological processes associated with a given trait. This is exemplified in the current study by applying W-PPI-NA to frontotemporal dementia (FTD): We first built the state of the art FTD protein network (FTD-PN) and then analyzed both its topological and functional features. The FTD-PN resulted from the sum of the individual interactomes built around FTD-spectrum genes, leading to a total of 4198 nodes. Twenty nine of 4198 nodes, called inter-interactome hubs (IIHs), represented those interactors able to bridge over 60% of the individual interactomes. Functional annotation analysis not only reiterated and reinforced previous findings from single genes and gene-coexpression analyses but also indicated a number of novel potential disease related mechanisms, including DNA damage response, gene expression regulation, and cell waste disposal and potential biomarkers or therapeutic targets including EP300. These processes and targets likely represent the functional core impacted in FTD, reflecting the underlying genetic architecture contributing to disease. The approach presented in this study can be applied to other complex traits for which risk-causative genes are known as it provides a promising tool for setting the foundations for collating genomics and wet laboratory data in a bidirectional manner. This is and will be critical to accelerate molecular target prioritization and drug discovery.

  3. Small-angle neutron scattering study of structure and interaction of nanoparticle, protein, and surfactant complexes.

    Science.gov (United States)

    Mehan, Sumit; Chinchalikar, Akshay J; Kumar, Sugam; Aswal, Vinod K; Schweins, Ralf

    2013-09-10

    Small-angle neutron scattering (SANS) measurements have been carried out from the multicomponent system composed of Ludox HS40 silica nanoparticle, bovine serum albumin (BSA) protein, and sodium dodecyl sulfate (SDS) surfactant in an aqueous system under the solution condition that all the components are negatively charged. Although the components are similarly charged, strong structural evolutions among them have been observed. The complexes of different components in pairs (nanoparticle-protein, nanoparticle-surfactant, and protein-surfactant) have been examined to correlate the role of each component in the three-component nanoparticle-protein-surfactant system. The nanoparticle-protein system shows depletion interaction induced aggregation of nanoparticles in the presence of protein. Both nanoparticle and surfactant coexist individually in a nanoparticle-surfactant system. In the case of a protein-surfactant system, the cooperative binding of surfactant with protein leads to micelle-like clusters of surfactant formed along the unfolded protein chain. The structure of the three-component (nanoparticle-protein-surfactant) system is found to be governed by the synergetic effect of nanoparticle-protein and protein-surfactant interactions. The nanoparticle aggregates coexist with the structures of protein-surfactant complex in the three-component system. The nanoparticle aggregation as well as unfolding of protein is enhanced in this system as compared to the corresponding two-component systems.

  4. Designing specificity of protein-substrate interactions

    NARCIS (Netherlands)

    Coluzza, I.; Frenkel, D.

    2004-01-01

    One of the key properties of biological molecules is that they can bind strongly to certain substrates yet interact only weakly with the very large number of other molecules that they encounter. Using a simple lattice model, we test several methods to design molecule-substrate binding specificity.

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

    Science.gov (United States)

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

    2014-12-01

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

  6. Transient interactions studied by NMR : iron sulfur proteins and their interaction partners

    NARCIS (Netherlands)

    Xu, Xingfu

    2009-01-01

    The interactions between proteins are of central importance for virtually every process in a living cell. It has long been a mystery how two proteins associate to form a complex in a complicated cellular context. Recently, it was found that an intermediate state called encounter state, of a protein

  7. Identification of Essential Proteins Based on a New Combination of Local Interaction Density and Protein Complexes.

    Directory of Open Access Journals (Sweden)

    Jiawei Luo

    Full Text Available Computational approaches aided by computer science have been used to predict essential proteins and are faster than expensive, time-consuming, laborious experimental approaches. However, the performance of such approaches is still poor, making practical applications of computational approaches difficult in some fields. Hence, the development of more suitable and efficient computing methods is necessary for identification of essential proteins.In this paper, we propose a new method for predicting essential proteins in a protein interaction network, local interaction density combined with protein complexes (LIDC, based on statistical analyses of essential proteins and protein complexes. First, we introduce a new local topological centrality, local interaction density (LID, of the yeast PPI network; second, we discuss a new integration strategy for multiple bioinformatics. The LIDC method was then developed through a combination of LID and protein complex information based on our new integration strategy. The purpose of LIDC is discovery of important features of essential proteins with their neighbors in real protein complexes, thereby improving the efficiency of identification.Experimental results based on three different PPI(protein-protein interaction networks of Saccharomyces cerevisiae and Escherichia coli showed that LIDC outperformed classical topological centrality measures and some recent combinational methods. Moreover, when predicting MIPS datasets, the better improvement of performance obtained by LIDC is over all nine reference methods (i.e., DC, BC, NC, LID, PeC, CoEWC, WDC, ION, and UC.LIDC is more effective for the prediction of essential proteins than other recently developed methods.

  8. Identification of interacting proteins of the TaFVE protein involved in spike development in bread wheat.

    Science.gov (United States)

    Zheng, Yong-Sheng; Lu, Yu-Qing; Meng, Ying-Ying; Zhang, Rong-Zhi; Zhang, Han; Sun, Jia-Mei; Wang, Mu-Mu; Li, Li-Hui; Li, Ru-Yu

    2017-05-01

    WD-40 repeat-containing protein MSI4 (FVE)/MSI4 plays important roles in determining flowering time in Arabidopsis. However, its function is unexplored in wheat. In the present study, coimmunoprecipitation and nanoscale liquid chromatography coupled to MS/MS were used to identify FVE in wheat (TaFVE)-interacting or associated proteins. Altogether 89 differentially expressed proteins showed the same downregulated expression trends as TaFVE in wheat line 5660M. Among them, 62 proteins were further predicted to be involved in the interaction network of TaFVE and 11 proteins have been shown to be potential TaFVE interactors based on curated databases and experimentally determined in other species by the STRING. Both yeast two-hybrid assay and bimolecular fluorescence complementation assay showed that histone deacetylase 6 and histone deacetylase 15 directly interacted with TaFVE. Multiple chromatin-remodelling proteins and polycomb group proteins were also identified and predicted to interact with TaFVE. These results showed that TaFVE directly interacted with multiple proteins to form multiple complexes to regulate spike developmental process, e.g. histone deacetylate, chromatin-remodelling and polycomb repressive complex 2 complexes. In addition, multiple flower development regulation factors (e.g. flowering locus K homology domain, flowering time control protein FPA, FY, flowering time control protein FCA, APETALA 1) involved in floral transition were also identified in the present study. Taken together, these results further elucidate the regulatory functions of TaFVE and help reveal the genetic mechanisms underlying wheat spike differentiation. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    Directory of Open Access Journals (Sweden)

    Aalt D J van Dijk

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

  10. Yeast Interacting Proteins Database: YLR291C, YPL070W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YPL070W MUK1 Cytoplasmic protein of unknown function containing a Vps9 domain; computation...rotein of unknown function containing a Vps9 domain; computational analysis of large-scale protein-protein i

  11. Yeast Interacting Proteins Database: YML109W, YGL190C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available sential regulatory subunit B of protein phosphatase 2A, which has multiple roles ...-essential regulatory subunit B of protein phosphatase 2A, which has multiple roles in mitosis and protein b

  12. Quantification of protein interaction kinetics in a micro droplet

    International Nuclear Information System (INIS)

    Yin, L. L.; Wang, S. P.; Shan, X. N.; Tao, N. J.; Zhang, S. T.

    2015-01-01

    Characterization of protein interactions is essential to the discovery of disease biomarkers, the development of diagnostic assays, and the screening for therapeutic drugs. Conventional flow-through kinetic measurements need relative large amount of sample that is not feasible for precious protein samples. We report a novel method to measure protein interaction kinetics in a single droplet with sub microliter or less volume. A droplet in a humidity-controlled environmental chamber is replacing the microfluidic channels as the reactor for the protein interaction. The binding process is monitored by a surface plasmon resonance imaging (SPRi) system. Association curves are obtained from the average SPR image intensity in the center area of the droplet. The washing step required by conventional flow-through SPR method is eliminated in the droplet method. The association and dissociation rate constants and binding affinity of an antigen-antibody interaction are obtained by global fitting of association curves at different concentrations. The result obtained by this method is accurate as validated by conventional flow-through SPR system. This droplet-based method not only allows kinetic studies for proteins with limited supply but also opens the door for high-throughput protein interaction study in a droplet-based microarray format that enables measurement of many to many interactions on a single chip

  13. Quantification of protein interaction kinetics in a micro droplet

    Energy Technology Data Exchange (ETDEWEB)

    Yin, L. L. [Center for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, Tempe, Arizona 85287 (United States); College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044 (China); Wang, S. P., E-mail: shaopeng.wang@asu.edu, E-mail: njtao@asu.edu; Shan, X. N.; Tao, N. J., E-mail: shaopeng.wang@asu.edu, E-mail: njtao@asu.edu [Center for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, Tempe, Arizona 85287 (United States); Zhang, S. T. [College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044 (China)

    2015-11-15

    Characterization of protein interactions is essential to the discovery of disease biomarkers, the development of diagnostic assays, and the screening for therapeutic drugs. Conventional flow-through kinetic measurements need relative large amount of sample that is not feasible for precious protein samples. We report a novel method to measure protein interaction kinetics in a single droplet with sub microliter or less volume. A droplet in a humidity-controlled environmental chamber is replacing the microfluidic channels as the reactor for the protein interaction. The binding process is monitored by a surface plasmon resonance imaging (SPRi) system. Association curves are obtained from the average SPR image intensity in the center area of the droplet. The washing step required by conventional flow-through SPR method is eliminated in the droplet method. The association and dissociation rate constants and binding affinity of an antigen-antibody interaction are obtained by global fitting of association curves at different concentrations. The result obtained by this method is accurate as validated by conventional flow-through SPR system. This droplet-based method not only allows kinetic studies for proteins with limited supply but also opens the door for high-throughput protein interaction study in a droplet-based microarray format that enables measurement of many to many interactions on a single chip.

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

    Science.gov (United States)

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

    2013-04-01

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

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

    DEFF Research Database (Denmark)

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

    2003-01-01

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

  16. 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

  17. GPCR-interacting proteins (GIPs): nature and functions.

    Science.gov (United States)

    Bockaert, J; Roussignol, G; Bécamel, C; Gavarini, S; Joubert, L; Dumuis, A; Fagni, L; Marin, P

    2004-11-01

    The simplistic idea that seven transmembrane receptors are single monomeric proteins that interact with heterotrimeric G-proteins after agonist binding is definitively out of date. Indeed, GPCRs (G-protein-coupled receptors) are part of multiprotein networks organized around scaffolding proteins. These GIPs (GPCR-interacting proteins) are either transmembrane or cytosolic proteins. Proteomic approaches can be used to get global pictures of these 'receptosomes'. This approach allowed us to identify direct but also indirect binding partners of serotonin receptors. GIPs are involved in a wide range of functions including control of the targeting, trafficking and signalling of GPCRs. One of them, Shank, which is a secondary and tertiary partner of metabotropic and ionotropic glutamate receptors, respectively, can induce the formation of a whole functional glutamate 'receptosome' and the structure to which it is associated, the dendritic spine.

  18. Yeast Interacting Proteins Database: YNR006W, YHL002W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ling Golgi proteins, forming lumenal membranes and sorting ubiquitinated proteins destined for degradation; ..., as well as for recycling of Golgi proteins and formation of lumenal membranes Rows with this prey as prey ...1p; required for recycling Golgi proteins, forming lumenal membranes and sorting ubiquitinated proteins dest...degradation, as well as for recycling of Golgi proteins and formation of lumenal membranes

  19. 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.

  20. In silico study of interaction between rice proteins enhanced disease ...

    Indian Academy of Sciences (India)

    2012-06-25

    Jun 25, 2012 ... a dimeric protein complex, which, similar to that in Arabidopsis, is perhaps also important for triggering the salicylic acid signalling pathway in plants. [Singh I and Shah K 2012 In silico study of interaction between rice proteins enhanced disease susceptibility 1 and phytoalexin deficient 4, the regulators of ...

  1. Prediction of localization and interactions of apoptotic proteins

    Directory of Open Access Journals (Sweden)

    Matula Pavel

    2009-07-01

    Full Text Available Abstract During apoptosis several mitochondrial proteins are released. Some of them participate in caspase-independent nuclear DNA degradation, especially apoptosis-inducing factor (AIF and endonuclease G (endoG. Another interesting protein, which was expected to act similarly as AIF due to the high sequence homology with AIF is AIF-homologous mitochondrion-associated inducer of death (AMID. We studied the structure, cellular localization, and interactions of several proteins in silico and also in cells using fluorescent microscopy. We found the AMID protein to be cytoplasmic, most probably incorporated into the cytoplasmic side of the lipid membranes. Bioinformatic predictions were conducted to analyze the interactions of the studied proteins with each other and with other possible partners. We conducted molecular modeling of proteins with unknown 3D structures. These models were then refined by MolProbity server and employed in molecular docking simulations of interactions. Our results show data acquired using a combination of modern in silico methods and image analysis to understand the localization, interactions and functions of proteins AMID, AIF, endonuclease G, and other apoptosis-related proteins.

  2. Rare disease relations through common genes and protein interactions.

    Science.gov (United States)

    Fernandez-Novo, Sara; Pazos, Florencio; Chagoyen, Monica

    2016-06-01

    ODCs (Orphan Disease Connections), available at http://csbg.cnb.csic.es/odcs, is a novel resource to explore potential molecular relations between rare diseases. These molecular relations have been established through the integration of disease susceptibility genes and human protein-protein interactions. The database currently contains 54,941 relations between 3032 diseases. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

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

    Science.gov (United States)

    Raut, Ashlesha S; Kalonia, Devendra S

    2015-09-08

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

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

    Directory of Open Access Journals (Sweden)

    Greenblatt Jack

    2006-07-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  8. 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.

  9. Mechanisms of Peroxynitrite Interactions with Heme Proteins

    Science.gov (United States)

    Su, Jia; Groves, John T.

    2010-01-01

    Oxygenated hemoproteins are known to react rapidly with nitric oxide (NO) to produce peroxynitrite (PN) at the heme site. This process could lead either to attenuation of the effects of NO or to nitrosative protein damage. Peroxynitrite is a powerful nitrating and oxidizing agent that has been implicated in a variety of cell injuries. Accordingly, it is important to delineate the nature and variety of reaction mechanisms of PN reactions with heme proteins. In this Forum we survey the range of reactions of PN with heme proteins, with particular attention to myoglobin and cytochrome c. While these two proteins are textbook paradigms for oxygen binding and electron transfer, respectively, both have recently been shown to have other important functions that involve nitric oxide and peroxynitrite. We have recently described direct evidence that ferrylMb and NO2 are both produced during the reaction of PN and metmyolgobin (metMb). Kinetic evidence indicates that these products evolve from initial formation of a caged radical intermediate [FeIV=O .NO2]. This caged pair reacts mainly via internal return with a rate constant kr to form metMb and nitrate in an oxygen rebound scenario. Detectable amounts of ferrylMb are observed by stopped-flow spectrophotometry, appearing at a rate consistent with the rate, kobs of heme-mediated PN decomposition. Freely-diffusing NO2, which is liberated concomitantly from the radical pair (ke), preferentially nitrates myoglobin Tyr103 and added fluorescein. For cytochrome c, Raman spectroscopy has revealed that a substantial fraction of cytochrome c converts to a β-sheet structure, at the expense of turns and helices at low pH. It is proposed that a short β-sheet segment, comprising residues 37-39 and 58-61, extends itself into the large 37-61 loop when the latter is destabilized by protonation of H26, which forms an anchoring H-bond to loop residue P44. This conformation change ruptures the Met80-Fe bond, as revealed by changes in

  10. Water-mediated ionic interactions in protein structures

    Indian Academy of Sciences (India)

    is defined as when one or more water molecules mediate an interaction between a pair of charged residues. For example, disruption of surface salt bridges (a class of ionic interactions) by water molecules in proteins permits protein–DNA inter- actions (Grove 2003) because it creates the cationic surface complementary to ...

  11. Screening of cellular proteins that interact with the classical swine ...

    Indian Academy of Sciences (India)

    The interactions detected by the Y2H system should be considered as preliminary results. Since identifying novel pathways and host targets, which play essential roles during infection, may provide potential targets for therapeutic development. The finding of proteins obtained from the SUVEC cDNA library that interact with ...

  12. PDZ domain-mediated interactions of G protein-coupled receptors with postsynaptic density protein 95

    DEFF Research Database (Denmark)

    Møller, Thor C; Wirth, Volker F; Roberts, Nina Ingerslev

    2013-01-01

    G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome. Their signaling is regulated by scaffold proteins containing PDZ domains, but although these interactions are important for GPCR function, they are still poorly understood. We here present ...

  13. The BAR domain protein PICK1 regulates cell recognition and morphogenesis by interacting with Neph proteins.

    Science.gov (United States)

    Höhne, Martin; Lorscheider, Johannes; von Bardeleben, Anna; Dufner, Matthias; Scharf, M Antonia; Gödel, Markus; Helmstädter, Martin; Schurek, Eva-Maria; Zank, Sibylle; Gerke, Peter; Kurschat, Christine; Sivritas, Sema Hayriye; Neumann-Haefelin, Elke; Huber, Tobias B; Reinhardt, H Christian; Schauss, Astrid C; Schermer, Bernhard; Fischbach, Karl-Friedrich; Benzing, Thomas

    2011-08-01

    Neph proteins are evolutionarily conserved membrane proteins of the immunoglobulin superfamily that control the formation of specific intercellular contacts. Cell recognition through these proteins is essential in diverse cellular contexts such as patterning of the compound eye in Drosophila melanogaster, neuronal connectivity in Caenorhabditis elegans, and the formation of the kidney filtration barrier in mammals. Here we identify the PDZ and BAR domain protein PICK1 (protein interacting with C-kinase 1) as a Neph-interacting protein. Binding required dimerization of PICK1, was dependent on PDZ domain protein interactions, and mediated stabilization of Neph1 at the plasma membrane. Moreover, protein kinase C (PKCα) activity facilitated the interaction through releasing Neph proteins from their binding to the multidomain scaffolding protein zonula occludens 1 (ZO-1), another PDZ domain protein. In Drosophila, the Neph homologue Roughest is essential for sorting of interommatidial precursor cells and patterning of the compound eye. RNA interference-mediated knockdown of PICK1 in the Drosophila eye imaginal disc caused a Roughest destabilization at the plasma membrane and a phenotype that resembled rst mutation. These data indicate that Neph proteins and PICK1 synergistically regulate cell recognition and contact formation.

  14. ProteinShop: A tool for interactive protein manipulation and steering

    Energy Technology Data Exchange (ETDEWEB)

    Crivelli, Silvia; Kreylos, Oliver; Max, Nelson; Hamann, Bernd; Bethel, Wes

    2004-05-25

    We describe ProteinShop, a new visualization tool that streamlines and simplifies the process of determining optimal protein folds. ProteinShop may be used at different stages of a protein structure prediction process. First, it can create protein configurations containing secondary structures specified by the user. Second, it can interactively manipulate protein fragments to achieve desired folds by adjusting the dihedral angles of selected coil regions using an Inverse Kinematics method. Last, it serves as a visual framework to monitor and steer a protein structure prediction process that may be running on a remote machine. ProteinShop was used to create initial configurations for a protein structure prediction method developed by a team that competed in CASP5. ProteinShop's use accelerated the process of generating initial configurations, reducing the time required from days to hours. This paper describes the structure of ProteinShop and discusses its main features.

  15. Behavior of whey protein concentrates under extreme storage conditions

    Science.gov (United States)

    The overseas demand for whey protein concentrates (WPC) has increased steadily in recent years. Emergency aid foods often include WPC, but shelf-life studies of whey proteins under different shipment and storage conditions have not been conducted in the last 50 yr. Microbial quality, compound form...

  16. A cell-based method for screening RNA-protein interactions: identification of constitutive transport element-interacting proteins.

    Directory of Open Access Journals (Sweden)

    Robert L Nakamura

    Full Text Available We have developed a mammalian cell-based screening platform to identify proteins that assemble into RNA-protein complexes. Based on Tat-mediated activation of the HIV LTR, proteins that interact with an RNA target elicit expression of a GFP reporter and are captured by fluorescence activated cell sorting. This "Tat-hybrid" screening platform was used to identify proteins that interact with the Mason Pfizer monkey virus (MPMV constitutive transport element (CTE, a structured RNA hairpin that mediates the transport of unspliced viral mRNAs from the nucleus to the cytoplasm. Several hnRNP-like proteins, including hnRNP A1, were identified and shown to interact with the CTE with selectivity in the reporter system comparable to Tap, a known CTE-binding protein. In vitro gel shift and pull-down assays showed that hnRNP A1 is able to form a complex with the CTE and Tap and that the RGG domain of hnRNP A1 mediates binding to Tap. These results suggest that hnRNP-like proteins may be part of larger export-competent RNA-protein complexes and that the RGG domains of these proteins play an important role in directing these binding events. The results also demonstrate the utility of the screening platform for identifying and characterizing new components of RNA-protein complexes.

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

    Directory of Open Access Journals (Sweden)

    Sony Malhotra

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

  18. Foot-printing of Protein Interactions by Tritium Labeling

    Energy Technology Data Exchange (ETDEWEB)

    Mousseau, Guillaume; Thomas, Olivier P.; Agez, Morgane; Thai, Robert; Cintrat, Jean-Christophe; Rousseau, Bernard [IBITECS, CNRS CEA, F-91191 Gif-sur-Yvette (France); Raffy, Quentin; Renault, Jean Philippe [IRAMIS, CNRS CEA, F-91191 Gif-sur-Yvette (France); Pin, Serge [IBITECS, CNRS CEA, F-91191 Gif-sur-Yvette (France); IRAMIS, CNRS CEA, F-91191 Gif-sur-Yvette (France); Ochsenbein, Francoise [IBITECS, CNRS CEA, F-91191 Gif-sur-Yvette (France); URA 2096, Systemes membranaires, photobiologie, stress et detoxication, CNRS CEA, F-91191 Gif-sur-Yvette (France)

    2010-07-01

    A new foot-printing method for mapping protein interactions has been developed, using tritium as a radioactive label. As residues involved in an interaction are less labeled when the complex is formed, they can be identified via comparison of the tritium incorporation of each residue of the bound protein with that of the unbound one. Application of this foot-printing method to the complex formed by the histone H3 fragment H3{sub 122-135} and the protein hAsflA{sub 1-156} afforded data in good agreement with NMR results. (authors)

  19. INTERACTION OF ALDEHYDES DERIVED FROM LIPID PEROXIDATION AND MEMBRANE PROTEINS.

    Directory of Open Access Journals (Sweden)

    Stefania ePizzimenti

    2013-09-01

    Full Text Available A great variety of compounds are formed during lipid peroxidation of polyunsaturated fatty acids of membrane phospholipids. Among them, bioactive aldehydes, such as 4-hydroxyalkenals, malondialdehyde (MDA and acrolein, have received particular attention since they have been considered as toxic messengers that can propagate and amplify oxidative injury. In the 4-hydroxyalkenal class, 4-hydroxy-2-nonenal (HNE is the most intensively studied aldehyde, in relation not only to its toxic function, but also to its physiological role. Indeed, HNE can be found at low concentrations in human tissues and plasma and participates in the control of biological processes, such as signal transduction, cell proliferation and differentiation. Moreover, at low doses, HNE exerts an anti-cancer effect, by inhibiting cell proliferation, angiogenesis, cell adhesion and by inducing differentiation and/or apoptosis in various tumor cell lines. It is very likely that a substantial fraction of the effects observed in cellular responses, induced by HNE and related aldehydes, be mediated by their interaction with proteins, resulting in the formation of covalent adducts or in the modulation of their expression and/or activity. In this review we focus on membrane proteins affected by lipid peroxidation-derived aldehydes, under physiological and pathological conditions.

  20. Disease candidate gene identification and prioritization using protein interaction networks

    Directory of Open Access Journals (Sweden)

    Aronow Bruce J

    2009-02-01

    Full Text Available Abstract Background Although most of the current disease candidate gene identification and prioritization methods depend on functional annotations, the coverage of the gene functional annotations is a limiting factor. In the current study, we describe a candidate gene prioritization method that is entirely based on protein-protein interaction network (PPIN analyses. Results For the first time, extended versions of the PageRank and HITS algorithms, and the K-Step Markov method are applied to prioritize disease candidate genes in a training-test schema. Using a list of known disease-related genes from our earlier study as a training set ("seeds", and the rest of the known genes as a test list, we perform large-scale cross validation to rank the candidate genes and also evaluate and compare the performance of our approach. Under appropriate settings – for example, a back probability of 0.3 for PageRank with Priors and HITS with Priors, and step size 6 for K-Step Markov method – the three methods achieved a comparable AUC value, suggesting a similar performance. Conclusion Even though network-based methods are generally not as effective as integrated functional annotation-based methods for disease candidate gene prioritization, in a one-to-one comparison, PPIN-based candidate gene prioritization performs better than all other gene features or annotations. Additionally, we demonstrate that methods used for studying both social and Web networks can be successfully used for disease candidate gene prioritization.

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

    Science.gov (United States)

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

    2011-07-18

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

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

    Directory of Open Access Journals (Sweden)

    Armstrong J Douglas

    2011-07-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2011-09-01

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

  5. Yeast Interacting Proteins Database: YOR284W, YOR284W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YOR284W HUA2 Cytoplasmic protein of unknown function; computational analysis of lar...it as bait (1) Rows with this bait as prey (4) YOR284W HUA2 Cytoplasmic protein of unknown function; computation...tein of unknown function; computational analysis of large-scale protein-protein i... HUA2 Prey description Cytoplasmic protein of unknown function; computational ana

  6. Yeast Interacting Proteins Database: YHL002W, YNR006W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ycling of Golgi proteins and formation of lumenal membranes Rows with this bait as bait (1) Rows with this b...required for recycling Golgi proteins, forming lumenal membranes and sorting ubiquitinated proteins destined...on, as well as for recycling of Golgi proteins and formation of lumenal membranes...ith Hse1p; required for recycling Golgi proteins, forming lumenal membranes and sorting ubiquitinated protei

  7. Interaction of influenza virus proteins with nucleosomes

    International Nuclear Information System (INIS)

    Garcia-Robles, Inmaculada; Akarsu, Hatice; Mueller, Christoph W.; Ruigrok, Rob W.H.; Baudin, Florence

    2005-01-01

    During influenza virus infection, transcription and replication of the viral RNA take place in the cell nucleus. Directly after entry in the nucleus the viral ribonucleoproteins (RNPs, the viral subunits containing vRNA, nucleoprotein and the viral polymerase) are tightly associated with the nuclear matrix. Here, we have analysed the binding of RNPs, M1 and NS2/NEP proteins to purified nucleosomes, reconstituted histone octamers and purified single histones. RNPs and M1 both bind to the chromatin components but at two different sites, RNP to the histone tails and M1 to the globular domain of the histone octamer. NS2/NEP did not bind to nucleosomes at all. The possible consequences of these findings for nuclear release of newly made RNPs and for other processes during the infection cycle are discussed

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

    OpenAIRE

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

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jun Pan

    2014-01-01

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

  10. 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).

  11. Studying host cell protein interactions with monoclonal antibodies using high throughput protein A chromatography.

    Science.gov (United States)

    Sisodiya, Vikram N; Lequieu, Joshua; Rodriguez, Maricel; McDonald, Paul; Lazzareschi, Kathlyn P

    2012-10-01

    Protein A chromatography is typically used as the initial capture step in the purification of monoclonal antibodies produced in Chinese hamster ovary (CHO) cells. Although exploiting an affinity interaction for purification, the level of host cell proteins in the protein A eluent varies significantly with different feedstocks. Using a batch binding chromatography method, we performed a controlled study to assess host cell protein clearance across both MabSelect Sure and Prosep vA resins. We individually spiked 21 purified antibodies into null cell culture fluid generated with a non-producing cell line, creating mock cell culture fluids for each antibody with an identical composition of host cell proteins and antibody concentration. We demonstrated that antibody-host cell protein interactions are primarily responsible for the variable levels of host cell proteins in the protein A eluent for both resins when antibody is present. Using the additives guanidine HCl and sodium chloride, we demonstrated that antibody-host cell protein interactions may be disrupted, reducing the level of host cell proteins present after purification on both resins. The reduction in the level of host cell proteins differed between antibodies suggesting that the interaction likely varies between individual antibodies but encompasses both an electrostatic and hydrophobic component. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    Science.gov (United States)

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

    2013-03-01

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

  13. Intracellular Localization, Interactions and Functions of Capsicum Chlorosis Virus Proteins.

    Science.gov (United States)

    Widana Gamage, Shirani M K; Dietzgen, Ralf G

    2017-01-01

    Tospoviruses are among the most devastating viruses of horticultural and field crops. Capsicum chlorosis virus (CaCV) has emerged as an important pathogen of capsicum and tomato in Australia and South-east Asia. Present knowledge about CaCV protein functions in host cells is lacking. We determined intracellular localization and interactions of CaCV proteins by live plant cell imaging to gain insight into the associations of viral proteins during infection. Proteins were transiently expressed as fusions to autofluorescent proteins in leaf epidermal cells of Nicotiana benthamiana and capsicum. All viral proteins localized at least partially in the cell periphery suggestive of cytoplasmic replication and assembly of CaCV. Nucleocapsid (N) and non-structural movement (NSm) proteins localized exclusively in the cell periphery, while non-structural suppressor of silencing (NSs) protein and Gc and Gn glycoproteins accumulated in both the cell periphery and the nucleus. Nuclear localization of CaCV Gn and NSs is unique among tospoviruses. We validated nuclear localization of NSs by immunofluorescence in protoplasts. Bimolecular fluorescence complementation showed self-interactions of CaCV N, NSs and NSm, and heterotypic interactions of N with NSs and Gn. All interactions occurred in the cytoplasm, except NSs self-interaction was exclusively nuclear. Interactions of a tospoviral NSs protein with itself and with N had not been reported previously. Functionally, CaCV NSs showed strong local and systemic RNA silencing suppressor activity and appears to delay short-distance spread of silencing signal. Cell-to-cell movement activity of NSm was demonstrated by trans -complementation of a movement-defective tobamovirus replicon. CaCV NSm localized at plasmodesmata and its transient expression led to the formation of tubular structures that protruded from protoplasts. The D 155 residue in the 30K-like movement protein-specific LxD/N 50-70 G motif of NSm was critical for

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

    Directory of Open Access Journals (Sweden)

    Albrecht von Brunn

    2007-05-01

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

  15. Protein-lipid interactions of bacteriophage M13 major coat protein

    OpenAIRE

    Stopar, D.; Spruijt, R.B.; Wolfs, C.J.A.M.; Hemminga, M.A.

    2003-01-01

    During the past years, remarkable progress has been made in our understanding of the replication cycle of bacteriophage M13 and the molecular details that enable phage proteins to navigate in the complex environment of the host cell. With new developments in molecular membrane biology in combination with spectroscopic techniques, we are now in a position to ask how phages carry out this delicate process on a molecular level, and what sort of protein-lipid and protein-protein interactions are ...

  16. Plant neighbour identity matters to belowground interactions under controlled conditions.

    Science.gov (United States)

    Armas, Cristina; Pugnaire, Francisco Ignacio

    2011-01-01

    Root competition is an almost ubiquitous feature of plant communities with profound effects on their structure and composition. Far beyond the traditional view that plants interact mainly through resource depletion (exploitation competition), roots are known to be able to interact with their environment using a large variety of mechanisms that may inhibit or enhance access of other roots to the resource or affect plant growth (contest interactions). However, an extensive analysis on how these contest root interactions may affect species interaction abilities is almost lacking. In a common garden experiment with ten perennial plant species we forced pairs of plants of the same or different species to overlap their roots and analyzed how belowground contest interactions affected plant performance, biomass allocation patterns, and competitive abilities under abundant resource supply. Our results showed that net interaction outcome ranged from negative to positive, affecting total plant mass and allocation patterns. A species could be a strong competitor against one species, weaker against another one, and even facilitator to a third species. This leads to sets of species where competitive hierarchies may be clear but also to groups where such rankings are not, suggesting that intransitive root interactions may be crucial for species coexistence. The outcome of belowground contest interactions is strongly dependent on neighbours' identity. In natural plant communities this conditional outcome may hypothetically help species to interact in non-hierarchical and intransitive networks, which in turn might promote coexistence.

  17. Plant neighbour identity matters to belowground interactions under controlled conditions.

    Directory of Open Access Journals (Sweden)

    Cristina Armas

    Full Text Available BACKGROUND: Root competition is an almost ubiquitous feature of plant communities with profound effects on their structure and composition. Far beyond the traditional view that plants interact mainly through resource depletion (exploitation competition, roots are known to be able to interact with their environment using a large variety of mechanisms that may inhibit or enhance access of other roots to the resource or affect plant growth (contest interactions. However, an extensive analysis on how these contest root interactions may affect species interaction abilities is almost lacking. METHODOLOGY/PRINCIPAL FINDINGS: In a common garden experiment with ten perennial plant species we forced pairs of plants of the same or different species to overlap their roots and analyzed how belowground contest interactions affected plant performance, biomass allocation patterns, and competitive abilities under abundant resource supply. Our results showed that net interaction outcome ranged from negative to positive, affecting total plant mass and allocation patterns. A species could be a strong competitor against one species, weaker against another one, and even facilitator to a third species. This leads to sets of species where competitive hierarchies may be clear but also to groups where such rankings are not, suggesting that intransitive root interactions may be crucial for species coexistence. CONCLUSIONS/SIGNIFICANCE: The outcome of belowground contest interactions is strongly dependent on neighbours' identity. In natural plant communities this conditional outcome may hypothetically help species to interact in non-hierarchical and intransitive networks, which in turn might promote coexistence.

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

    Science.gov (United States)

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

  19. Amyloid precursor protein interaction network in human testis: sentinel proteins for male reproduction.

    Science.gov (United States)

    Silva, Joana Vieira; Yoon, Sooyeon; Domingues, Sara; Guimarães, Sofia; Goltsev, Alexander V; da Cruz E Silva, Edgar Figueiredo; Mendes, José Fernando F; da Cruz E Silva, Odete Abreu Beirão; Fardilha, Margarida

    2015-01-16

    Amyloid precursor protein (APP) is widely recognized for playing a central role in Alzheimer's disease pathogenesis. Although APP is expressed in several tissues outside the human central nervous system, the functions of APP and its family members in other tissues are still poorly understood. APP is involved in several biological functions which might be potentially important for male fertility, such as cell adhesion, cell motility, signaling, and apoptosis. Furthermore, APP superfamily members are known to be associated with fertility. Knowledge on the protein networks of APP in human testis and spermatozoa will shed light on the function of APP in the male reproductive system. We performed a Yeast Two-Hybrid screen and a database search to study the interaction network of APP in human testis and sperm. To gain insights into the role of APP superfamily members in fertility, the study was extended to APP-like protein 2 (APLP2). We analyzed several topological properties of the APP interaction network and the biological and physiological properties of the proteins in the APP interaction network were also specified by gene ontologyand pathways analyses. We classified significant features related to the human male reproduction for the APP interacting proteins and identified modules of proteins with similar functional roles which may show cooperative behavior for male fertility. The present work provides the first report on the APP interactome in human testis. Our approach allowed the identification of novel interactions and recognition of key APP interacting proteins for male reproduction, particularly in sperm-oocyte interaction.

  20. 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.

  1. 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

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

    Science.gov (United States)

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

    2010-07-01

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

  3. Yeast Interacting Proteins Database: YLR295C, YJR083C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available 7) Rows with this bait as prey (0) YJR083C ACF4 Protein of unknown function, computational analysis of large...me ACF4 Prey description Protein of unknown function, computational analysis of l

  4. Yeast Interacting Proteins Database: YDL239C, YPL070W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available it as prey (1) YPL070W MUK1 Cytoplasmic protein of unknown function containing a Vps9 domain; computation...ey description Cytoplasmic protein of unknown function containing a Vps9 domain; computational analysis of l

  5. Yeast Interacting Proteins Database: YPL070W, YLR245C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YPL070W MUK1 Cytoplasmic protein of unknown function containing a Vps9 domain; computation... name MUK1 Bait description Cytoplasmic protein of unknown function containing a Vps9 domain; computation

  6. Yeast Interacting Proteins Database: YPL070W, YOR155C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YPL070W MUK1 Cytoplasmic protein of unknown function containing a Vps9 domain; computation...me MUK1 Bait description Cytoplasmic protein of unknown function containing a Vps9 domain; computation

  7. Yeast Interacting Proteins Database: YPL070W, YPR193C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YPL070W MUK1 Cytoplasmic protein of unknown function containing a Vps9 domain; computation...1 Bait description Cytoplasmic protein of unknown function containing a Vps9 domain; computation

  8. Yeast Interacting Proteins Database: YLR291C, YOR284W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YOR284W HUA2 Cytoplasmic protein of unknown function; computational analysis of l...prey (0) Prey ORF YOR284W Prey gene name HUA2 Prey description Cytoplasmic protein of unknown function; computation

  9. Yeast Interacting Proteins Database: YNL152W, YMR032W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YNL152W INN1 Essential protein that associates with the contractile actomyosin ring... Bait description Essential protein that associates with the contractile actomyosin ring, required for ingre

  10. Yeast Interacting Proteins Database: YLR373C, YGL190C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ase 2A, which has multiple roles in mitosis and protein biosynthesis; involved in regulation of mitotic exit...phosphatase 2A, which has multiple roles in mitosis and protein biosynthesis; involved in regulation of mito

  11. Yeast Interacting Proteins Database: YNL258C, YGL145W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YNL258C DSL1 Peripheral membrane protein required for Golgi-to-ER retrograde traffi...t description Peripheral membrane protein required for Golgi-to-ER retrograde traffic; component of the ER t

  12. Yeast Interacting Proteins Database: YKL002W, YFL034C-B [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthes...ntegral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthesi

  13. Yeast Interacting Proteins Database: YKL002W, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthes...ng of integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly s

  14. Yeast Interacting Proteins Database: YJR091C, YKL002W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available g of integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly sy... integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthe

  15. Yeast Interacting Proteins Database: YCL046W, YGL115W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YCL046W - Dubious open reading frame unlikely to encode a protein, based on availab...ading frame unlikely to encode a protein, based on available experimental and comparative sequence data; par

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

    Directory of Open Access Journals (Sweden)

    Andrew Kaplan

    2017-01-01

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

  17. Energetics of the protein-DNA-water interaction

    Directory of Open Access Journals (Sweden)

    Marabotti Anna

    2007-01-01

    Full Text Available Abstract Background To understand the energetics of the interaction between protein and DNA we analyzed 39 crystallographically characterized complexes with the HINT (Hydropathic INTeractions computational model. HINT is an empirical free energy force field based on solvent partitioning of small molecules between water and 1-octanol. Our previous studies on protein-ligand complexes demonstrated that free energy predictions were significantly improved by taking into account the energetic contribution of water molecules that form at least one hydrogen bond with each interacting species. Results An initial correlation between the calculated HINT scores and the experimentally determined binding free energies in the protein-DNA system exhibited a relatively poor r2 of 0.21 and standard error of ± 1.71 kcal mol-1. However, the inclusion of 261 waters that bridge protein and DNA improved the HINT score-free energy correlation to an r2 of 0.56 and standard error of ± 1.28 kcal mol-1. Analysis of the water role and energy contributions indicate that 46% of the bridging waters act as linkers between amino acids and nucleotide bases at the protein-DNA interface, while the remaining 54% are largely involved in screening unfavorable electrostatic contacts. Conclusion This study quantifies the key energetic role of bridging waters in protein-DNA associations. In addition, the relevant role of hydrophobic interactions and entropy in driving protein-DNA association is indicated by analyses of interaction character showing that, together, the favorable polar and unfavorable polar/hydrophobic-polar interactions (i.e., desolvation mostly cancel.

  18. Response of the mosquito protein interaction network to dengue infection

    Directory of Open Access Journals (Sweden)

    Pike Andrew D

    2010-06-01

    Full Text Available Abstract Background Two fifths of the world's population is at risk from dengue. The absence of effective drugs and vaccines leaves vector control as the primary intervention tool. Understanding dengue virus (DENV host interactions is essential for the development of novel control strategies. The availability of genome sequences for both human and mosquito host greatly facilitates genome-wide studies of DENV-host interactions. Results We developed the first draft of the mosquito protein interaction network using a computational approach. The weighted network includes 4,214 Aedes aegypti proteins with 10,209 interactions, among which 3,500 proteins are connected into an interconnected scale-free network. We demonstrated the application of this network for the further annotation of mosquito proteins and dissection of pathway crosstalk. Using three datasets based on physical interaction assays, genome-wide RNA interference (RNAi screens and microarray assays, we identified 714 putative DENV-associated mosquito proteins. An integrated analysis of these proteins in the network highlighted four regions consisting of highly interconnected proteins with closely related functions in each of replication/transcription/translation (RTT, immunity, transport and metabolism. Putative DENV-associated proteins were further selected for validation by RNAi-mediated gene silencing, and dengue viral titer in mosquito midguts was significantly reduced for five out of ten (50.0% randomly selected genes. Conclusions Our results indicate the presence of common host requirements for DENV in mosquitoes and humans. We discuss the significance of our findings for pharmacological intervention and genetic modification of mosquitoes for blocking dengue transmission.

  19. Huntingtin-associated protein-1 (HAP1) regulates endocytosis and interacts with multiple trafficking-related proteins.

    Science.gov (United States)

    Mackenzie, Kimberly D; Lim, Yoon; Duffield, Michael D; Chataway, Timothy; Zhou, Xin-Fu; Keating, Damien J

    2017-07-01

    Huntingtin-associated protein 1 (HAP1) was initially identified as a binding partner of huntingtin, mutations in which underlie Huntington's disease. Subcellular localization and protein interaction data indicate that HAP1 may be important in vesicle trafficking, cell signalling and receptor internalization. In this study, a proteomics approach was used for the identification of novel HAP1-interacting partners to attempt to shed light on the physiological function of HAP1. Using affinity chromatography with HAP1-GST protein fragments bound to Sepharose columns, this study identified a number of trafficking-related proteins that bind to HAP1. Interestingly, many of the proteins that were identified by mass spectrometry have trafficking-related functions and include the clathrin light chain B and Sec23A, an ER to Golgi trafficking vesicle coat component. Using co-immunoprecipitation and GST-binding assays the association between HAP1 and clathrin light chain B has been validated in vitro. This study also finds that HAP1 co-localizes with clathrin light chain B. In line with a physiological function of the HAP1-clathrin interaction this study detected a dramatic reduction in vesicle retrieval and endocytosis in adrenal chromaffin cells. Furthermore, through examination of transferrin endocytosis in HAP1 -/- cortical neurons, this study has determined that HAP1 regulates neuronal endocytosis. In this study, the interaction between HAP1 and Sec23A was also validated through endogenous co-immunoprecipitation in rat brain homogenate. Through the identification of novel HAP1 binding partners, many of which have putative trafficking roles, this study provides us with new insights into the mechanisms underlying the important physiological function of HAP1 as an intracellular trafficking protein through its protein-protein interactions. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Arc Interacts with the Integral Endoplasmic Reticulum Protein, Calnexin

    Directory of Open Access Journals (Sweden)

    Craig Myrum

    2017-09-01

    Full Text Available Activity-regulated cytoskeleton-associated protein, Arc, is a major regulator of long-term synaptic plasticity and memory formation. Here we reveal a novel interaction partner of Arc, a resident endoplasmic reticulum transmembrane protein, calnexin. We show an interaction between recombinantly-expressed GST-tagged Arc and endogenous calnexin in HEK293, SH-SY5Y neuroblastoma and PC12 cells. The interaction was dependent on the central linker region of the Arc protein that is also required for endocytosis of AMPA-type glutamate receptors. High-resolution proximity-ligation assays (PLAs demonstrate molecular proximity of endogenous Arc with the cytosolic C-terminus, but not the lumenal N-terminus of calnexin. In hippocampal neuronal cultures treated with brain-derived neurotrophic factor (BDNF, Arc interacted with calnexin in the perinuclear cytoplasm and dendritic shaft. Arc also interacted with C-terminal calnexin in the adult rat dentate gyrus (DG. After induction of long-term potentiation (LTP in the perforant path projection to the DG of adult anesthetized rats, enhanced interaction between Arc and calnexin was obtained in the dentate granule cell layer (GCL. Although Arc and calnexin are both implicated in the regulation of receptor endocytosis, no modulation of endocytosis was detected in transferrin uptake assays. Previous work showed that Arc interacts with multiple protein partners to regulate synaptic transmission and nuclear signaling. The identification of calnexin as a binding partner further supports the role of Arc as a hub protein and extends the range of Arc function to the endoplasmic reticulum, though the function of the Arc/calnexin interaction remains to be defined.

  1. Preferential interactions and the effect of protein PEGylation

    DEFF Research Database (Denmark)

    Holm, Louise Stenstrup; Thulstrup, Peter Waaben; Kasimova, Marina Robertovna

    2015-01-01

    excipients that preferentially interact with the protein. METHODOLOGY/PRINCIPAL FINDINGS: The model protein hen egg white lysozyme was doubly PEGylated on two lysines with 5 kDa linear PEGs (mPEG-succinimidyl valerate, MW 5000) and studied in the absence and presence of preferentially excluded sucrose...... enthalpy was decreased to half the value for PEGylated lysozyme. The ratio between calorimetric and van't Hoff enthalpy suggests that our PEGylated lysozyme is a dimer. CONCLUSION/SIGNIFICANCE: The PEGylated model protein displayed similar stability responses to the addition of preferentially active......BACKGROUND: PEGylation is a strategy used by the pharmaceutical industry to prolong systemic circulation of protein drugs, whereas formulation excipients are used for stabilization of proteins during storage. Here we investigate the role of PEGylation in protein stabilization by formulation...

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

    Science.gov (United States)

    Song, Xueyu

    2014-03-01

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

  3. Impact of surface coating and food-mimicking media on nanosilver-protein interaction

    Energy Technology Data Exchange (ETDEWEB)

    Burcza, Anna, E-mail: anna.burcza@mri.bund.de; Gräf, Volker; Walz, Elke; Greiner, Ralf [Max Rubner-Institute, Department of Food Technology and Bioprocess Engineering (Germany)

    2015-11-15

    The application of silver nanoparticles (AgNPs) in food contact materials has recently become a subject of dispute due to the possible migration of silver in nanoform into foods and beverages. Therefore, the analysis of the interaction of AgNPs with food components, especially proteins, is of high importance in order to increase our knowledge of the behavior of nanoparticles in food matrices. AgPURE™ W10 (20 nm), an industrially applied nanomaterial, was compared with AgNPs of similar size frequently investigated for scientific purposes differing in the surface capping agent (spherical AgNP coated with either PVP or citrate). The interactions of the AgNPs with whey proteins (BSA, α-lactalbumin and β-lactoglobulin) at different pH values (4.2, 7 or 7.4) were investigated using surface plasmon resonance, SDS-PAGE, and asymmetric flow field-flow fractionation. The data obtained by the three different methods correlated well. Besides the nature of the protein and the nanoparticle coating, the environment was shown to affect the interaction significantly. The strongest interaction was obtained with BSA and AgNPs in an acidic environment. Neutral and slightly alkaline conditions however, seemed to prevent the AgNP-protein interaction almost completely. Furthermore, the interaction of whey proteins with AgPURE™ W10 was found to be weaker compared to the interaction with the other two AgNPs under all conditions investigated.

  4. Impact of surface coating and food-mimicking media on nanosilver-protein interaction

    International Nuclear Information System (INIS)

    Burcza, Anna; Gräf, Volker; Walz, Elke; Greiner, Ralf

    2015-01-01

    The application of silver nanoparticles (AgNPs) in food contact materials has recently become a subject of dispute due to the possible migration of silver in nanoform into foods and beverages. Therefore, the analysis of the interaction of AgNPs with food components, especially proteins, is of high importance in order to increase our knowledge of the behavior of nanoparticles in food matrices. AgPURE™ W10 (20 nm), an industrially applied nanomaterial, was compared with AgNPs of similar size frequently investigated for scientific purposes differing in the surface capping agent (spherical AgNP coated with either PVP or citrate). The interactions of the AgNPs with whey proteins (BSA, α-lactalbumin and β-lactoglobulin) at different pH values (4.2, 7 or 7.4) were investigated using surface plasmon resonance, SDS-PAGE, and asymmetric flow field-flow fractionation. The data obtained by the three different methods correlated well. Besides the nature of the protein and the nanoparticle coating, the environment was shown to affect the interaction significantly. The strongest interaction was obtained with BSA and AgNPs in an acidic environment. Neutral and slightly alkaline conditions however, seemed to prevent the AgNP-protein interaction almost completely. Furthermore, the interaction of whey proteins with AgPURE™ W10 was found to be weaker compared to the interaction with the other two AgNPs under all conditions investigated

  5. CAG trinucleotide RNA repeats interact with RNA-binding proteins

    Energy Technology Data Exchange (ETDEWEB)

    McLaughlin, B.A.; Eberwine, J.; Spencer, C. [Univ. of Pennsylvania, Philadelphia, PA (United States)

    1996-09-01

    Genes associated with several neurological diseases are characterized by the presence of an abnormally long trinucleotide repeat sequence. By way of example, Huntington`s disease (HD), is characterized by selective neuronal degeneration associated with the expansion of a polyglutamine-encoding CAG tract. Normally, this CAG tract is comprised of 11-34 repeats, but in HD it is expanded to >37 repeats in affected individuals. The mechanism by which CAG repeats cause neuronal degeneration is unknown, but it has been speculated that the expansion primarily causes abnormal protein functioning, which in turn causes HD pathology. Other mechanisms, however, have not been ruled out. Interactions between RNA and RNA-binding proteins have previously been shown to play a role in the expression of several eukaryotic genes. Herein, we report the association of cytoplasmic proteins with normal length and extended CAG repeats, using gel shift and LJV crosslinking assays. Cytoplasmic protein extracts from several rat brain regions, including the striatum and cortex, sites of neuronal degeneration in HD, contain a 63-kD RNA-binding protein that specifically interacts with these CAG-repeat sequences. These protein-RNA interactions are dependent on the length of the CAG repeat, with longer repeats binding substantially more protein. Two CAG repeat-binding proteins are present in human cortex and striatum; one comigrates with the rat protein at 63 kD, while the other migrates at 49 kD. These data suggest mechanisms by which RNA-binding proteins may be involved in the pathological course of trinucleotide repeat-associated neurological diseases. 47 refs., 5 figs.

  6. Membrane protein simulations with a united-atom lipid and all-atom protein model: lipid-protein interactions, side chain transfer free energies and model proteins

    International Nuclear Information System (INIS)

    Tieleman, D Peter; MacCallum, Justin L; Ash, Walter L; Kandt, Christian; Xu Zhitao; Monticelli, Luca

    2006-01-01

    We have reparameterized the dihedral parameters in a commonly used united-atom lipid force field so that they can be used with the all-atom OPLS force field for proteins implemented in the molecular dynamics simulation software GROMACS. Simulations with this new combination give stable trajectories and sensible behaviour of both lipids and protein. We have calculated the free energy of transfer of amino acid side chains between water and 'lipid-cyclohexane', made of lipid force field methylene groups, as a hydrophobic mimic of the membrane interior, for both the OPLS-AA and a modified OPLS-AA force field which gives better hydration free energies under simulation conditions close to those preferred for the lipid force field. The average error is 4.3 kJ mol -1 for water-'lipid-cyclohexane' compared to 3.2 kJ mol -1 for OPLS-AA cyclohexane and 2.4 kJ mol -1 for the modified OPLS-AA water-'lipid-cyclohexane'. We have also investigated the effect of different methods to combine parameters between the united-atom lipid force field and the united-atom protein force field ffgmx. In a widely used combination, the strength of interactions between hydrocarbon lipid tails and proteins is significantly overestimated, causing a decrease in the area per lipid and an increase in lipid ordering. Using straight combination rules improves the results. Combined, we suggest that using OPLS-AA together with the united-atom lipid force field implemented in GROMACS is a reasonable approach to membrane protein simulations. We also suggest that using partial volume information and free energies of transfer may help to improve the parameterization of lipid-protein interactions and point out the need for accurate experimental data to validate and improve force field descriptions of such interactions

  7. Interaction of milk whey protein with common phenolic acids

    Science.gov (United States)

    Zhang, Hao; Yu, Dandan; Sun, Jing; Guo, Huiyuan; Ding, Qingbo; Liu, Ruihai; Ren, Fazheng

    2014-01-01

    Phenolics-rich foods such as fruit juices and coffee are often consumed with milk. In this study, the interactions of α-lactalbumin and β-lactoglobulin with the phenolic acids (chlorogenic acid, caffeic acid, ferulic acid, and coumalic acid) were examined. Fluorescence, CD, and FTIR spectroscopies were used to analyze the binding modes, binding constants, and the effects of complexation on the conformation of whey protein. The results showed that binding constants of each whey protein-phenolic acid interaction ranged from 4 × 105 to 7 × 106 M-n and the number of binding sites n ranged from 1.28 ± 0.13 to 1.54 ± 0.34. Because of these interactions, the conformation of whey protein was altered, with a significant reduction in the amount of α-helix and an increase in the amounts of β-sheet and turn structures.

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

    Directory of Open Access Journals (Sweden)

    Chen Xue-Wen

    2006-01-01

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

  9. Preferential Interactions and the Effect of Protein PEGylation.

    Directory of Open Access Journals (Sweden)

    Louise Stenstrup Holm

    Full Text Available PEGylation is a strategy used by the pharmaceutical industry to prolong systemic circulation of protein drugs, whereas formulation excipients are used for stabilization of proteins during storage. Here we investigate the role of PEGylation in protein stabilization by formulation excipients that preferentially interact with the protein.The model protein hen egg white lysozyme was doubly PEGylated on two lysines with 5 kDa linear PEGs (mPEG-succinimidyl valerate, MW 5000 and studied in the absence and presence of preferentially excluded sucrose and preferentially bound guanine hydrochloride. Structural characterization by far- and near-UV circular dichroism spectroscopy was supplemented by investigation of protein thermal stability with the use of differential scanning calorimetry, far and near-UV circular dichroism and fluorescence spectroscopy. It was found that PEGylated lysozyme was stabilized by the preferentially excluded excipient and destabilized by the preferentially bound excipient in a similar manner as lysozyme. However, compared to lysozyme in all cases the melting transition was lower by up to a few degrees and the calorimetric melting enthalpy was decreased to half the value for PEGylated lysozyme. The ratio between calorimetric and van't Hoff enthalpy suggests that our PEGylated lysozyme is a dimer.The PEGylated model protein displayed similar stability responses to the addition of preferentially active excipients. This suggests that formulation principles using preferentially interacting excipients are similar for PEGylated and non-PEGylated proteins.

  10. Dynamics of DNA conformations and DNA-protein interaction

    DEFF Research Database (Denmark)

    Metzler, R.; Ambjörnsson, T.; Lomholt, Michael Andersen

    2005-01-01

    denaturation (bubble breathing), deriving its dynamic response to external physical parameters and the DNA sequence in terms of the bubble relaxation time spectrum and the autocorrelation function of bubble breathing. The interaction with binding proteins that selectively bind to the DNA single strand exposed......Optical tweezers, atomic force microscopes, patch clamping, or fluorescence techniques make it possible to study both the equilibrium conformations and dynamics of single DNA molecules as well as their interaction with binding proteins. In this paper we address the dynamics of local DNA...... in a denaturation bubble are shown to involve an interesting competition of time scales, varying between kinetic blocking of protein binding up to full binding protein-induced denaturation of the DNA. We will also address the potential to use DNA physics for the design of nanosensors. Finally, we report recent...

  11. Analytical techniques for the study of polyphenol-protein interactions.

    Science.gov (United States)

    Poklar Ulrih, Nataša

    2017-07-03

    This mini review focuses on advances in biophysical techniques to study polyphenol interactions with proteins. Polyphenols have many beneficial pharmacological properties, as a result of which they have been the subject of intensive studies. The most conventional techniques described here can be divided into three groups: (i) methods used for screening (in-situ methods); (ii) methods used to gain insight into the mechanisms of polyphenol-protein interactions; and (iii) methods used to study protein aggregation and precipitation. All of these methods used to study polyphenol-protein interactions are based on modifications to the physicochemical properties of the polyphenols or proteins after binding/complex formation in solution. To date, numerous review articles have been published in the field of polyphenols. This review will give a brief insight in computational methods and biosensors and cell-based methods, spectroscopic methods including fluorescence emission, UV-vis adsorption, circular dichroism, Fourier transform infrared and mass spectrometry, nuclear magnetic resonance, X-ray diffraction, and light scattering techniques including small-angle X-ray scattering and small-angle neutron scattering, and calorimetric techniques (isothermal titration calorimetry and differential scanning calorimetry), microscopy, the techniques which have been successfully used for polyphenol-protein interactions. At the end the new methods based on single molecule detection with high potential to study polyphenol-protein interactions will be presented. The advantages and disadvantages of each technique will be discussed as well as the thermodynamic, kinetic or structural parameters, which can be obtained. The other relevant biophysical experimental techniques that have proven to be valuable, such electrochemical methods, hydrodynamic techniques and chromatographic techniques will not be described here.

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

    Directory of Open Access Journals (Sweden)

    Chin-Jen Wu

    2013-06-01

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

  13. Investigation of the pH‐dependence of dye‐doped protein–protein interactions

    OpenAIRE

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

    2016-01-01

    Proteins can dramatically change their conformation under environmental conditions such as temperature and pH. In this context, Glycoprotein's conformational determination is challenging. This is due to the variety of domains which contain rich chemical characters existing within this complex. Here we demonstrate a new, straightforward and efficient technique that uses the pH‐dependent properties of dyes‐doped Pig Gastric Mucin (PGM) for predicting and controlling protein–protein interaction ...

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

    Science.gov (United States)

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

    2018-01-05

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

  15. Protein-lipid interactions in bilayer membranes: A lattice model

    Science.gov (United States)

    Pink, David A.; Chapman, Dennis

    1979-01-01

    A lattice model has been developed to study the effects of intrinsic membrane proteins upon the thermodynamic properties of a lipid bilayer membrane. We assume that only nearest-neighbor van der Waals and steric interactions are important and that the polar group interactions can be represented by effective pressure—area terms. Phase diagrams, the temperature T0, which locates the gel—fluid melting, the transition enthalpy, and correlations were calculated by mean field and cluster approximations. Average lipid chain areas and chain areas when the lipid is in a given protein environment were obtained. Proteins that have a “smooth” homogeneous surface (“cholesterol-like”) and those that have inhomogeneous surfaces or that bind lipids specifically were considered. We find that T0 can vary depending upon the interactions and that another peak can appear upon the shoulder of the main peak which reflects the melting of a eutectic mixture. The transition enthalpy decreases generally, as was found before, but when a second peak appears departures from this behavior reflect aspects of the eutectic mixture. We find that proteins have significant nonzero probabilities for being adjacent to one another so that no unbroken “annulus” of lipid necessarily exists around a protein. If T0 does not increase much, or decreases, with increasing c, then lipids adjacent to a protein cannot all be all-trans on the time scale (10-7 sec) of our system. Around a protein the lipid correlation depth is about one lipid layer, and this increases with c. Possible consequences of ignoring changes in polar group interactions due to clustering of proteins are discussed. PMID:286996

  16. Topological and functional analysis of nonalcoholic steatohepatitis through protein interaction mapping

    Science.gov (United States)

    Asadzadeh-Aghdaee, Hamid; Mansouri, Vahid; Peyvandi, Ali Asghar; Moztarzadeh, Fathollah; Okhovatian, Farshad; Lahmi, Farhad; Vafaee, Reza; Zali, Mohammad Reza

    2016-01-01

    Aim: The corresponding proteins are important for network mapping since the interaction analysis can provide a new interpretation about disease underlying mechanisms as the aim of this study. Backgroud: Nonalcoholic steatohepatitis (NASH) is one of the main causes of liver disease in the world. It has been known with many susceptible proteins that play essential role in its pathogenesis. Methods: In this paper, protein-protein interaction (PPI) network analysis of fatty liver disease retrieved from STRING db by the application of Cytoscape Software. ClueGO analyzed the associated pathways for the selected top proteins. Results: INS, PPARA, LEP, SREBF1, and ALB are the introduced biomarker panel for fatty liver disease. Conclusion: It seems that pathways related to insulin have a prominent role in fatty liver disease. Therefore, investigation in this case is required to confirm the possible linkage of introduced panel and involvement of insulin pathway in the disease. PMID:28224024

  17. Hydrophobic interaction adsorption of hen egg white proteins albumin, conalbumin, and lysozyme.

    Science.gov (United States)

    Rojas, Edwin E Garcia; dos Reis Coimbra, Jane S; Minim, Luis A; Saraiva, Sérgio H; da Silva, César A Sodré

    2006-08-18

    Hydrophobic adsorption equilibrium data of the hen egg white proteins albumin, conalbumin, and lysozyme were obtained in batch systems, at 25 degrees C, using the Streamline Phenyl resin as adsorbent. The influence of three types of salt, NaCl, Na(2)SO(4), or (NH(4))(2)SO(4), and their concentration on the equilibrium data were evaluated. The salt Na(2)SO(4) showed the higher interaction with the studied proteins, thus favoring the adsorption of proteins by the adsorbent, even though each type of salt interacted in a distinct manner with each protein. The isotherm models of Langmuir, Langmuir exponential, and Chen and Sun were well fitted to the equilibrium data, with no significant difference being observed at the 5% level of significance. The mass transfer model applied simulated correctly adsorption kinetics of the proteins under the studied conditions.

  18. Effect of mass overloading on binding and elution of unstable proteins in hydrophobic interaction chromatography.

    Science.gov (United States)

    Muca, Renata; Marek, Wojciech; Żurawski, Marek; Piątkowski, Wojciech; Antos, Dorota

    2017-04-07

    Adsorption behavior of unstable proteins, i.e., bovine serum albumin and α-lactalbumin, has been studied on a hydrophobic interaction chromatography medium under mass overloading conditions at different kosmotropic salt concentrations in the mobile phase. A mechanistic model has been formulated and used to describe kinetics and thermodynamics of protein interactions with the adsorbent surface. The model assumed two-site binding adsorption and reversible protein unfolding, which allowed predicting the inhibition of protein unfolding at high column loadings. A simplified procedure for the determination of model parameters has been developed, which was based on the inverse method. The model was successfully used to reproduce the pattern of chromatographic elution as well as the course of breakthrough curves. The model formulation was supported by Nano Differential Scanning Fluorimetry measurements, which were exploited to determine the protein stability in the liquid and adsorbed phases at different column loadings and salt concentrations. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Dynamics of DNA conformations and DNA-protein interaction

    DEFF Research Database (Denmark)

    Metzler, R.; Ambjörnsson, T.; Lomholt, Michael Andersen

    2005-01-01

    Optical tweezers, atomic force microscopes, patch clamping, or fluorescence techniques make it possible to study both the equilibrium conformations and dynamics of single DNA molecules as well as their interaction with binding proteins. In this paper we address the dynamics of local DNA...... denaturation (bubble breathing), deriving its dynamic response to external physical parameters and the DNA sequence in terms of the bubble relaxation time spectrum and the autocorrelation function of bubble breathing. The interaction with binding proteins that selectively bind to the DNA single strand exposed...

  20. Interactions of polyphenols with carbohydrates, lipids and proteins.

    Science.gov (United States)

    Jakobek, Lidija

    2015-05-15

    Polyphenols are secondary metabolites in plants, investigated intensively because of their potential positive effects on human health. Their bioavailability and mechanism of positive effects have been studied, in vitro and in vivo. Lately, a high number of studies takes into account the interactions of polyphenols with compounds present in foods, like carbohydrates, proteins or lipids, because these food constituents can have significant effects on the activity of phenolic compounds. This paper reviews the interactions between phenolic compounds and lipids, carbohydrates and proteins and their impact on polyphenol activity. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Studying RNA-protein interactions in vivo by RNA immunoprecipitation

    DEFF Research Database (Denmark)

    Selth, Luke A; Close, Pierre; Svejstrup, Jesper Q

    2011-01-01

    The crucial roles played by RNA-binding proteins in all aspects of RNA metabolism, particularly in the regulation of transcription, have become increasingly evident. Moreover, other factors that do not directly interact with RNA molecules can nevertheless function proximally to RNA polymerases an...... and have significant effects on gene expression. RNA immunoprecipitation (RIP) is a powerful technique used to detect direct and indirect interactions between individual proteins and specific RNA molecules in vivo. Here, we describe RIP methods for both yeast and mammalian cells....

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

    Science.gov (United States)

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

    2006-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Jessica B Hostetler

    2015-12-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

  5. Yeast Interacting Proteins Database: YNL201C, YBL046W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YNL201C PSY2 Putative subunit of an evolutionarily conserved protein phosphatase co...s prey (0) YBL046W PSY4 Putative regulatory subunit of an evolutionarily conserve...ne name PSY2 Bait description Putative subunit of an evolutionarily conserved protein phosphatase complex co...gene name PSY4 Prey description Putative regulatory subunit of an evolutionarily conserved protein phosphata

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

    Directory of Open Access Journals (Sweden)

    Li Min

    2012-03-01

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

  7. Atom depth analysis delineates mechanisms of protein intermolecular interactions

    International Nuclear Information System (INIS)

    Alocci, Davide; Bernini, Andrea; Niccolai, Neri

    2013-01-01

    Highlights: •3D atom depth analysis is proposed to identify different layers in protein structures. •Amino acid contents for each layers have been analyzed for a large protein dataset. •Charged amino acids in the most external layer are present at very different extents. •Atom depth indexes of K residues reflect their side chains flexibility. •Mobile surface charges can be responsible for long range protein–protein recognition. -- Abstract: The systematic analysis of amino acid distribution, performed inside a large set of resolved protein structures, sheds light on possible mechanisms driving non random protein–protein approaches. Protein Data Bank entries have been selected using as filters a series of restrictions ensuring that the shape of protein surface is not modified by interactions with large or small ligands. 3D atom depth has been evaluated for all the atoms of the 2,410 selected structures. The amino acid relative population in each of the structural layers formed by grouping atoms on the basis of their calculated depths, has been evaluated. We have identified seven structural layers, the inner ones reproducing the core of proteins and the outer one incorporating their most protruding moieties. Quantitative analysis of amino acid contents of structural layers identified, as expected, different behaviors. Atoms of Q, R, K, N, D residues are increasingly more abundant in going from core to surfaces. An opposite trend is observed for V, I, L, A, C, and G. An intermediate behavior is exhibited by P, S, T, M, W, H, F and Y. The outer structural layer hosts predominantly E and K residues whose charged moieties, protruding from outer regions of the protein surface, reorient free from steric hindrances, determining specific electrodynamics maps. This feature may represent a protein signature for long distance effects, driving the formation of encounter complexes and the eventual short distance approaches that are required for protein–protein

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

    DEFF Research Database (Denmark)

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

    2003-01-01

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

  9. Investigating the Nature of GxE Interaction under Different ...

    African Journals Online (AJOL)

    for this study were from Intermediate to Late Hybrid Trials (ILHT) conducted in ... This phenomenon, referred to as COI, introduces a degree of uncertainty into the ... Investigating the Nature of GxE Interaction under Different Management Systems [3]. Materials and Methods. Setup of the trial. The number of trial sites used for ...

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

    Directory of Open Access Journals (Sweden)

    Alexandra Traister

    2016-06-01

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

  11. 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.

  12. Plasma–Surface Interactions Under High Heat and Particle Fluxes

    Directory of Open Access Journals (Sweden)

    Gregory De Temmerman

    2013-01-01

    Full Text Available The plasma-surface interactions expected in the divertor of a future fusion reactor are characterized by extreme heat and particle fluxes interacting with the plasma-facing surfaces. Powerful linear plasma generators are used to reproduce the expected plasma conditions and allow plasma-surface interactions studies under those very harsh conditions. While the ion energies on the divertor surfaces of a fusion device are comparable to those used in various plasma-assited deposition and etching techniques, the ion (and energy fluxes are up to four orders of magnitude higher. This large upscale in particle flux maintains the surface under highly non-equilibrium conditions and bring new effects to light, some of which will be described in this paper.

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

    Science.gov (United States)

    Holland, David O; Johnson, Margaret E

    2018-03-01

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

  14. Identification of proteins interacting with Arabidopsis ACD11

    DEFF Research Database (Denmark)

    Petersen, Nikolaj H T; Joensen, Jan; McKinney, Lea V

    2009-01-01

    The Arabidopsis ACD11 gene encodes a sphingosine transfer protein and was identified by the accelerated cell death phenotype of the loss of function acd11 mutant, which exhibits heightened expression of genes involved in the disease resistance hypersensitive response (HR). We used ACD11 as bait...... in a yeast two-hybrid screen of an Arabidopsis cDNA library to identify ACD11 interacting proteins. One interactor identified is a protein of unknown function with an RNA recognition motif (RRM) designated BPA1 (binding partner of ACD11). Co-immunoprecipitation experiments confirmed the ACD11-BPA1...

  15. Molecular enzymology underlying regulation of protein phosphatase-1 by natural toxins.

    Science.gov (United States)

    Holmes, C F B; Maynes, J T; Perreault, K R; Dawson, J F; James, M N G

    2002-11-01

    The protein serine/threonine phosphatases constitute a unique class of enzymes that are critical for cell regulation, as they must counteract the activities of thousands of protein kinases in human cells. Uncontrolled inhibition of phosphatase activity by toxic inhibitors can lead to widespread catastrophic effects. Over the past decade, a number of natural product toxins have been identified that specifically and potently inhibit protein phosphatase-1 and 2A. Amongst these are the cyanobacteria-derived cyclic heptapeptide microcystin-LR and the polyether fatty acid okadaic acid from dinoflagellate sources. The molecular mechanism underlying potent inhibition of protein phosphatase-1 by these toxins is becoming clear through insights gathered from diverse sources. These include: 1. Comparison of structure-activity relationships amongst the different classes of toxins. 2. Delineation of the structural differences between protein phosphatase-1 and 2A that account for their differing sensitivity to toxins, particularly okadaic acid and microcystin-LR. 3. Determination of the crystal structure of protein phosphatase-1 with microcystin-LR, okadaic acid and calyculin bound. 4. Site-specific mutagenesis and biochemical analysis of protein phosphatase-1 mutants. Taken together, these data point to a common binding site on protein phosphatase-1 for okadaic acid, microcystin-LR and the calyculins. However, careful analysis of these data suggest that each toxin binds to the common binding site in a subtly different way, relying on distinct structural interactions such as hydrophobic binding, hydrogen bonding and electrostatic interactions to different degrees. The insights derived from studying the molecular enzymology of protein phosphatase-1 may help explain the different sensitivities of other structurally conserved protein serine/theonine phosphatases to toxin inhibition. Furthermore, studies on the binding of structurally diverse toxins at the active site of protein

  16. Trimeric transmembrane domain interactions in paramyxovirus fusion proteins: roles in protein folding, stability, and function.

    Science.gov (United States)

    Smith, Everett Clinton; Smith, Stacy E; Carter, James R; Webb, Stacy R; Gibson, Kathleen M; Hellman, Lance M; Fried, Michael G; Dutch, Rebecca Ellis

    2013-12-13

    Paramyxovirus fusion (F) proteins promote membrane fusion between the viral envelope and host cell membranes, a critical early step in viral infection. Although mutational analyses have indicated that transmembrane (TM) domain residues can affect folding or function of viral fusion proteins, direct analysis of TM-TM interactions has proved challenging. To directly assess TM interactions, the oligomeric state of purified chimeric proteins containing the Staphylococcal nuclease (SN) protein linked to the TM segments from three paramyxovirus F proteins was analyzed by sedimentation equilibrium analysis in detergent and buffer conditions that allowed density matching. A monomer-trimer equilibrium best fit was found for all three SN-TM constructs tested, and similar fits were obtained with peptides corresponding to just the TM region of two different paramyxovirus F proteins. These findings demonstrate for the first time that class I viral fusion protein TM domains can self-associate as trimeric complexes in the absence of the rest of the protein. Glycine residues have been implicated in TM helix interactions, so the effect of mutations at Hendra F Gly-508 was assessed in the context of the whole F protein. Mutations G508I or G508L resulted in decreased cell surface expression of the fusogenic form, consistent with decreased stability of the prefusion form of the protein. Sedimentation equilibrium analysis of TM domains containing these mutations gave higher relative association constants, suggesting altered TM-TM interactions. Overall, these results suggest that trimeric TM interactions are important driving forces for protein folding, stability and membrane fusion promotion.

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

    Directory of Open Access Journals (Sweden)

    Liao Li

    2007-01-01

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

  18. 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.

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

    Science.gov (United States)

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

    2015-01-01

    Protein-protein interactions are important layers of regulation in all kingdoms of life. Identification and characterization of these interactions is one challenging task of the post-genomic era and crucial for understanding of molecular processes within a cell. Several methods have been successfully employed during the past decades to identify protein-protein interactions in bacteria, but most of them include tedious and time-consuming manipulations of DNA. In contrast, the MultiSite Gateway system is a fast tool for transfer of multiple DNA fragments between plasmids enabling simultaneous and site directed cloning of up to four fragments into one construct. Here we developed a new set of Gateway vectors including custom made entry vectors and modular Destination vectors for studying protein-protein interactions via Fluorescence Resonance Energy Transfer (FRET), Bacterial two Hybrid (B2H) and split Gaussia luciferase (Gluc), as well as for fusions with SNAP-tag and HaloTag for dual-color super-resolution microscopy. As proof of principle, we characterized the interaction between the Salmonella effector SipA and its chaperone InvB via split Gluc and B2H approach. The suitability for FRET analysis as well as functionality of fusions with SNAP- and HaloTag could be demonstrated by studying the transient interaction between chemotaxis response regulator CheY and its phosphatase CheZ. PMID:25856398

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

    Science.gov (United States)

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

    2017-06-01

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

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

    Science.gov (United States)

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

    2017-03-24

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

  2. Topological and functional properties of the small GTPases protein interaction network.

    Directory of Open Access Journals (Sweden)

    Anna Delprato

    Full Text Available Small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran regulate key cellular processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. A great deal of experimental evidence supports the existence of signaling cascades and feedback loops within and among the small GTPase subfamilies suggesting that these proteins function in a coordinated and cooperative manner. The interplay occurs largely through association with bi-partite regulatory and effector proteins but can also occur through the active form of the small GTPases themselves. In order to understand the connectivity of the small GTPases signaling routes, a systems-level approach that analyzes data describing direct and indirect interactions was used to construct the small GTPases protein interaction network. The data were curated from the Search Tool for the Retrieval of Interacting Genes (STRING database and include only experimentally validated interactions. The network method enables the conceptualization of the overall structure as well as the underlying organization of the protein-protein interactions. The interaction network described here is comprised of 778 nodes and 1943 edges and has a scale-free topology. Rac1, Cdc42, RhoA, and HRas are identified as the hubs. Ten sub-network motifs are also identified in this study with themes in apoptosis, cell growth/proliferation, vesicle traffic, cell adhesion/junction dynamics, the nicotinamide adenine dinucleotide phosphate (NADPH oxidase response, transcription regulation, receptor-mediated endocytosis, gene silencing, and growth factor signaling. Bottleneck proteins that bridge signaling paths and proteins that overlap in multiple small GTPase networks are described along with the functional annotation of all proteins in the network.

  3. Study of the interactions between riboflavin and protein

    International Nuclear Information System (INIS)

    Zhao Hongwei; Zhang Zhaoxia; Zhu Hongping; Ge Min; Miao Jinling; Wang Wenfeng; Yao Side

    2006-01-01

    Riboflavin (VB 2 ), a vitamin that is a natural constituent of living organisms, plays an important role in the process of metabolism and it is essential for normal cellular functions and growth. As an endogenous photosensitizer, riboflavin induces photooxidation damages to cells of skin and eye, causing inflammation, accelerated aging and mutation. The photodynamic actions of riboflavin on DNA have been studied extensively, however, its photodynamic actions on protein and enzyme are less studied due to the complex types and structures of proteins, and less attentions have been paid to photosensitive protein damages than DNA. In our lab, the interactions between riboflavin and serum albumin and lysozyme have been carried out by using transient absorption spectrometry, emission spectrometer analysis and electrophoresis techniques. It was found that stable state products and transient process of photosensitive damage to proteins were closely relative to concentration of riboflavin, time of irradiation and the atmosphere of the solutions. The results indicates that proteins can be photosensitive damaged by riboflavin irradiated by UV lights. Riboflavin can quench the intrinsic fluorescence of protein. Both dynamic and static quenching are simultaneous involved. The binding constants, the kinetics and spectroscopic properties of riboflavin interaction with albumin and lysozyme have also been investigated. Mechanisms of the photosensitive damages to proteins were discussed. The experiments also indicated that antioxidants such as melatonin and chlorogenic acid can reduce the damage of lysozyme effectively. (authors)

  4. Research advances in interactions related to Toxoplasma gondii microneme proteins.

    Science.gov (United States)

    Liu, Qing; Li, Fa-Cai; Zhou, Chun-Xue; Zhu, Xing-Quan

    2017-05-01

    Toxoplasma gondii microneme proteins (TgMICs), secreted by micronemes upon contact with host cells, are reported to play important roles in multiple stages of the T. gondii life cycle, including parasite motility, invasion, intracellular survival, and egress from host cells. Meanwhile, during these processes, TgMICs participate in many protein-protein and protein-carbohydrate interactions, such as undergoing proteolytic maturation, binding to aldolase, engaging the host cell receptors and forming the moving junction (MJ), relying on different types of ectodomains, transmembrane (TM) domains and cytoplasmic domains (CDs). In this review, we summarize the research advances in protein-protein and protein-carbohydrate interactions related to TgMICs, and their intimate associations with corresponding biological processes during T. gondii infection, which will contribute to an improved understanding of the molecular pathogenesis of T. gondii infection, and provide a basis for developing effective control strategies against T. gondii. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Yuval Gilad

    2014-08-01

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

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

    NARCIS (Netherlands)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-12-01

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

  8. A systematic evaluation of protein kinase a-a-kinase anchoring protein interaction motifs

    NARCIS (Netherlands)

    Burgers, Pepijn P|info:eu-repo/dai/nl/341566551; van der Heyden, Marcel A G; Kok, Bart; Heck, Albert J R|info:eu-repo/dai/nl/105189332; Scholten, Arjen|info:eu-repo/dai/nl/313939780

    2015-01-01

    Protein kinase A (PKA) in vertebrates is localized to specific locations in the cell via A-kinase anchoring proteins (AKAPs). The regulatory subunits of the four PKA isoforms (RIα, RIβ, RIIα, and RIIβ) each form a homodimer, and their dimerization domain interacts with a small helical region present

  9. A systematic evaluation of protein kinase A-A-kinase anchoring protein interaction motifs

    NARCIS (Netherlands)

    Burgers, Pepijn P; van der Heyden, MAG; Kok, Bart; Heck, Albert J R; Scholten, Arjen

    2015-01-01

    Protein kinase A (PKA) in vertebrates is localized to specific locations in the cell via A-kinase anchoring proteins (AKAPs). The regulatory subunits of the four PKA isoforms (RIα, RIβ, RIIα, and RIIβ) each form a homodimer, and their dimerization domain interacts with a small helical region present

  10. Dough and hearth bread characteristics influenced by protein composition, protein content, DATEM, and their interactions

    NARCIS (Netherlands)

    Aamodt, A.; Magnus, E.M.; Hollung, K.; Uhlen, A.K.; Færgestad, E.M.

    2005-01-01

    The effects of protein composition, protein content, diacetyl tartaric acid ester of monoglycerides (DATEM), and their interaction on dough and bread characteristics were studied by small- and pilot-scale hearth bread baking, dough rheological testing using the Kieffer extensibility rig, and size

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

    Directory of Open Access Journals (Sweden)

    Nora López

    2012-09-01

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

  12. 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.

  13. Characterization of host proteins interacting with the lymphocytic choriomeningitis virus L protein.

    Science.gov (United States)

    Khamina, Kseniya; Lercher, Alexander; Caldera, Michael; Schliehe, Christopher; Vilagos, Bojan; Sahin, Mehmet; Kosack, Lindsay; Bhattacharya, Anannya; Májek, Peter; Stukalov, Alexey; Sacco, Roberto; James, Leo C; Pinschewer, Daniel D; Bennett, Keiryn L; Menche, Jörg; Bergthaler, Andreas

    2017-12-01

    RNA-dependent RNA polymerases (RdRps) play a key role in the life cycle of RNA viruses and impact their immunobiology. The arenavirus lymphocytic choriomeningitis virus (LCMV) strain Clone 13 provides a benchmark model for studying chronic infection. A major genetic determinant for its ability to persist maps to a single amino acid exchange in the viral L protein, which exhibits RdRp activity, yet its functional consequences remain elusive. To unravel the L protein interactions with the host proteome, we engineered infectious L protein-tagged LCMV virions by reverse genetics. A subsequent mass-spectrometric analysis of L protein pulldowns from infected human cells revealed a comprehensive network of interacting host proteins. The obtained LCMV L protein interactome was bioinformatically integrated with known host protein interactors of RdRps from other RNA viruses, emphasizing interconnected modules of human proteins. Functional characterization of selected interactors highlighted proviral (DDX3X) as well as antiviral (NKRF, TRIM21) host factors. To corroborate these findings, we infected Trim21-/- mice with LCMV and found impaired virus control in chronic infection. These results provide insights into the complex interactions of the arenavirus LCMV and other viral RdRps with the host proteome and contribute to a better molecular understanding of how chronic viruses interact with their host.

  14. 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.

  15. Transcriptional robustness and protein interactions are associated in yeast

    Directory of Open Access Journals (Sweden)

    Conant Gavin C

    2011-05-01

    Full Text Available Abstract Background Robustness to insults, both external and internal, is a characteristic feature of life. One level of biological organization for which noise and robustness have been extensively studied is gene expression. Cells have a variety of mechanisms for buffering noise in gene expression, but it is not completely clear what rules govern whether or not a given gene uses such tools to maintain appropriate expression. Results Here, we show a general association between the degree to which yeast cells have evolved mechanisms to buffer changes in gene expression and whether they possess protein-protein interactions. We argue that this effect bears an affinity to epistasis, because yeast appears to have evolved regulatory mechanisms such that distant changes in gene copy number for a protein-protein interaction partner gene can alter a gene's expression. This association is not unexpected given recent work linking epistasis and the deleterious effects of changes in gene dosage (i.e., the dosage balance hypothesis. Using gene expression data from artificial aneuploid strains of bakers' yeast, we found that genes coding for proteins that physically interact with other proteins show less expression variation in response to aneuploidy than do other genes. This effect is even more pronounced for genes whose products interact with proteins encoded on aneuploid chromosomes. We further found that genes targeted by transcription factors encoded on aneuploid chromosomes were more likely to change in expression after aneuploidy. Conclusions We suggest that these observations can be best understood as resulting from the higher fitness cost of misexpression in epistatic genes and a commensurate greater regulatory control of them.

  16. Huntingtin interacting proteins are genetic modifiers of neurodegeneration.

    Directory of Open Access Journals (Sweden)

    Linda S Kaltenbach

    2007-05-01

    Full Text Available Huntington's disease (HD is a fatal neurodegenerative condition caused by expansion of the polyglutamine tract in the huntingtin (Htt protein. Neuronal toxicity in HD is thought to be, at least in part, a consequence of protein interactions involving mutant Htt. We therefore hypothesized that genetic modifiers of HD neurodegeneration should be enriched among Htt protein interactors. To test this idea, we identified a comprehensive set of Htt interactors using two complementary approaches: high-throughput yeast two-hybrid screening and affinity pull down followed by mass spectrometry. This effort led to the identification of 234 high-confidence Htt-associated proteins, 104 of which were found with the yeast method and 130 with the pull downs. We then tested an arbitrary set of 60 genes encoding interacting proteins for their ability to behave as genetic modifiers of neurodegeneration in a Drosophila model of HD. This high-content validation assay showed that 27 of 60 orthologs tested were high-confidence genetic modifiers, as modification was observed with more than one allele. The 45% hit rate for genetic modifiers seen among the interactors is an order of magnitude higher than the 1%-4% typically observed in unbiased genetic screens. Genetic modifiers were similarly represented among proteins discovered using yeast two-hybrid and pull-down/mass spectrometry methods, supporting the notion that these complementary technologies are equally useful in identifying biologically relevant proteins. Interacting proteins confirmed as modifiers of the neurodegeneration phenotype represent a diverse array of biological functions, including synaptic transmission, cytoskeletal organization, signal transduction, and transcription. Among the modifiers were 17 loss-of-function suppressors of neurodegeneration, which can be considered potential targets for therapeutic intervention. Finally, we show that seven interacting proteins from among 11 tested were able to

  17. Prediction of Effective Drug Combinations by Chemical Interaction, Protein Interaction and Target Enrichment of KEGG Pathways

    Directory of Open Access Journals (Sweden)

    Lei Chen

    2013-01-01

    Full Text Available Drug combinatorial therapy could be more effective in treating some complex diseases than single agents due to better efficacy and reduced side effects. Although some drug combinations are being used, their underlying molecular mechanisms are still poorly understood. Therefore, it is of great interest to deduce a novel drug combination by their molecular mechanisms in a robust and rigorous way. This paper attempts to predict effective drug combinations by a combined consideration of: (1 chemical interaction between drugs, (2 protein interactions between drugs’ targets, and (3 target enrichment of KEGG pathways. A benchmark dataset was constructed, consisting of 121 confirmed effective combinations and 605 random combinations. Each drug combination was represented by 465 features derived from the aforementioned three properties. Some feature selection techniques, including Minimum Redundancy Maximum Relevance and Incremental Feature Selection, were adopted to extract the key features. Random forest model was built with its performance evaluated by 5-fold cross-validation. As a result, 55 key features providing the best prediction result were selected. These important features may help to gain insights into the mechanisms of drug combinations, and the proposed prediction model could become a useful tool for screening possible drug combinations.

  18. Prediction of Effective Drug Combinations by Chemical Interaction, Protein Interaction and Target Enrichment of KEGG Pathways

    Science.gov (United States)

    Chen, Lei; Zheng, Ming-Yue; Zhang, Jian; Feng, Kai-Yan; Cai, Yu-Dong

    2013-01-01

    Drug combinatorial therapy could be more effective in treating some complex diseases than single agents due to better efficacy and reduced side effects. Although some drug combinations are being used, their underlying molecular mechanisms are still poorly understood. Therefore, it is of great interest to deduce a novel drug combination by their molecular mechanisms in a robust and rigorous way. This paper attempts to predict effective drug combinations by a combined consideration of: (1) chemical interaction between drugs, (2) protein interactions between drugs' targets, and (3) target enrichment of KEGG pathways. A benchmark dataset was constructed, consisting of 121 confirmed effective combinations and 605 random combinations. Each drug combination was represented by 465 features derived from the aforementioned three properties. Some feature selection techniques, including Minimum Redundancy Maximum Relevance and Incremental Feature Selection, were adopted to extract the key features. Random forest model was built with its performance evaluated by 5-fold cross-validation. As a result, 55 key features providing the best prediction result were selected. These important features may help to gain insights into the mechanisms of drug combinations, and the proposed prediction model could become a useful tool for screening possible drug combinations. PMID:24083237

  19. Strong Selection Significantly Increases Epistatic Interactions in the Long-Term Evolution of a Protein.

    Directory of Open Access Journals (Sweden)

    Aditi Gupta

    2016-03-01

    Full Text Available Epistatic interactions between residues determine a protein's adaptability and shape its evolutionary trajectory. When a protein experiences a changed environment, it is under strong selection to find a peak in the new fitness landscape. It has been shown that strong selection increases epistatic interactions as well as the ruggedness of the fitness landscape, but little is known about how the epistatic interactions change under selection in the long-term evolution of a protein. Here we analyze the evolution of epistasis in the protease of the human immunodeficiency virus type 1 (HIV-1 using protease sequences collected for almost a decade from both treated and untreated patients, to understand how epistasis changes and how those changes impact the long-term evolvability of a protein. We use an information-theoretic proxy for epistasis that quantifies the co-variation between sites, and show that positive information is a necessary (but not sufficient condition that detects epistasis in most cases. We analyze the "fossils" of the evolutionary trajectories of the protein contained in the sequence data, and show that epistasis continues to enrich under strong selection, but not for proteins whose environment is unchanged. The increase in epistasis compensates for the information loss due to sequence variability brought about by treatment, and facilitates adaptation in the increasingly rugged fitness landscape of treatment. While epistasis is thought to enhance evolvability via valley-crossing early-on in adaptation, it can hinder adaptation later when the landscape has turned rugged. However, we find no evidence that the HIV-1 protease has reached its potential for evolution after 9 years of adapting to a drug environment that itself is constantly changing. We suggest that the mechanism of encoding new information into pairwise interactions is central to protein evolution not just in HIV-1 protease, but for any protein adapting to a changing

  20. Systematic discovery of new recognition peptides mediating protein interaction networks

    DEFF Research Database (Denmark)

    Neduva, Victor; Linding, Rune; Su-Angrand, Isabelle

    2005-01-01

    Many aspects of cell signalling, trafficking, and targeting are governed by interactions between globular protein domains and short peptide segments. These domains often bind multiple peptides that share a common sequence pattern, or "linear motif" (e.g., SH3 binding to PxxP). Many domains are kn...

  1. Interaction of cholesterol-crystallization-promoting proteins with vesicles

    NARCIS (Netherlands)

    de Bruijn, M. A.; Goldhoorn, B. G.; Zijlstra, A. I.; Tytgat, G. N.; Groen, A. K.

    1995-01-01

    In this study, the interaction of mucin and concanavalin A-binding proteins isolated from human bile with cholesterol/phospholipid vesicles was investigated. Using resonance energy transfer assays originally developed by Struck, Hoekstra and Pagano [(1981) Biochemistry 20, 4093-4099], no significant

  2. Interaction of maize chromatin-associated HMG proteins with mononucleosomes

    DEFF Research Database (Denmark)

    Lichota, J.; Grasser, Klaus D.

    2003-01-01

    Two groups of plant chromatin-associated high mobility group (HMG) proteins, namely the HMGA family, typically containing four A/T-hook DNA-binding motifs, and the HMGB family, containing a single HMG-box DNA-binding domain, have been identified. We have examined the interaction of recombinant...

  3. Water-mediated ionic interactions in protein structures

    Indian Academy of Sciences (India)

    It is well known that water molecules play an indispensable role in the structure and function of biological macromolecules. The water-mediated ionic interactions between the charged residues provide stability and plasticity and in turn address the function of the protein structures. Thus, this study specifically addresses the ...

  4. Connecting Protein Structure to Intermolecular Interactions: A Computer Modeling Laboratory

    Science.gov (United States)

    Abualia, Mohammed; Schroeder, Lianne; Garcia, Megan; Daubenmire, Patrick L.; Wink, Donald J.; Clark, Ginevra A.

    2016-01-01

    An understanding of protein folding relies on a solid foundation of a number of critical chemical concepts, such as molecular structure, intra-/intermolecular interactions, and relating structure to function. Recent reports show that students struggle on all levels to achieve these understandings and use them in meaningful ways. Further, several…

  5. Screening of cellular proteins that interact with the classical swine ...

    Indian Academy of Sciences (India)

    In the current study, aiming to find more clues in understanding the molecular mechanisms of CSFV NS5A's function, the yeast two-hybrid (Y2H) system was adopted to screen for CSFV NS5A interactive proteins in the cDNA library of the swine umbilical vein endothelial cell (SUVEC). Alignment with the NCBI database ...

  6. Protein and Drug Interactions in the Minor Groove of DNA

    Czech Academy of Sciences Publication Activity Database

    Morávek, Z.; Neidle, S.; Schneider, Bohdan

    2002-01-01

    Roč. 30, č. 5 (2002), s. 1182-1191 ISSN 0305-1048 R&D Projects: GA MŠk LN00A032 Institutional research plan: CEZ:AV0Z4040901 Keywords : protein * DNA * interactions Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 7.051, year: 2002

  7. Boosting compound-protein interaction prediction by deep learning.

    Science.gov (United States)

    Tian, Kai; Shao, Mingyu; Wang, Yang; Guan, Jihong; Zhou, Shuigeng

    2016-11-01

    The identification of interactions between compounds and proteins plays an important role in network pharmacology and drug discovery. However, experimentally identifying compound-protein interactions (CPIs) is generally expensive and time-consuming, computational approaches are thus introduced. Among these, machine-learning based methods have achieved a considerable success. However, due to the nonlinear and imbalanced nature of biological data, many machine learning approaches have their own limitations. Recently, deep learning techniques show advantages over many state-of-the-art machine learning methods in some applications. In this study, we aim at improving the performance of CPI prediction based on deep learning, and propose a method called DL-CPI (the abbreviation of Deep Learning for Compound-Protein Interactions prediction), which employs deep neural network (DNN) to effectively learn the representations of compound-protein pairs. Extensive experiments show that DL-CPI can learn useful features of compound-protein pairs by a layerwise abstraction, and thus achieves better prediction performance than existing methods on both balanced and imbalanced datasets. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. The specificity of interactions between proteins and sulfated polysaccharides

    Directory of Open Access Journals (Sweden)

    Mulloy Barbara

    2005-01-01

    Full Text Available Sulfated polysaccharides are capable of binding with proteins at several levels of specificity. As highly acidic macromolecules, they can bind non-specifically to any basic patch on a protein surface at low ionic strength, and such interactions are not likely to be physiologically significant. On the other hand, several systems have been identified in which very specific substructures of sulfated polysaccharides confer high affinity for particular proteins; the best-known example of this is the pentasaccharide in heparin with high affinity for antithrombin, but other examples may be taken from the study of marine invertebrates: the importance of the fine structure of dermatan sulfate (DS to its interaction with heparin cofactor II (HCII, and the involvement of sea urchin egg-jelly fucans in species specific fertilization. A third, intermediate, kind of specific interaction is described for the cell-surface glycosaminoglycan heparan sulfate (HS, in which patterns of sulfate substitution can show differential affinities for cytokines, growth factors, and morphogens at cell surfaces and in the intracellular matrix. This complex interplay of proteins and glycans is capable of influencing the diffusion of such proteins through tissue, as well as modulating cellular responses to them.

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

    Science.gov (United States)

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

    2017-09-15

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

  10. Synergistic effect of temperature, protein and salt concentration on structures and interactions among lysozyme proteins

    Science.gov (United States)

    Kundu, Sarathi; Aswal, V. K.; Kohlbrecher, Joachim

    2016-07-01

    Synergistic effect of temperature, protein and salt concentration on structures and interactions among lysozyme proteins in solution has been studied using small angle neutron scattering technique. Scattering study shows that for a particular protein concentration, with increasing temperature, short-range attraction decreases but long-range repulsion becomes system specific. In absence of salt, lower value of attractive interaction is obtained, however, in presence of salt it becomes higher and decreases with increasing temperature. For specific condition, weak long range attraction and intermediate range repulsion exists. At higher temperature (90 °C), fractal structure develops and the corresponding fractal dimension depends upon the experimental conditions.

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

    Directory of Open Access Journals (Sweden)

    Panwen Wang

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

  12. Probing hydrogen bonding interactions and proton transfer in proteins

    Science.gov (United States)

    Nie, Beining

    Scope and method of study. Hydrogen bonding is a fundamental element in protein structure and function. Breaking a single hydrogen bond may impair the stability of a protein. It is therefore important to probe dynamic changes in hydrogen bonding interactions during protein folding and function. Time-resolved Fourier transform infrared spectroscopy is highly sensitive to hydrogen bonding interactions. However, it lacks quantitative correlation between the vibrational frequencies and the number, type, and strength of hydrogen bonding interactions of ionizable and polar residues. We employ quantum physics theory based ab initio calculations to study the effects of hydrogen bonding interactions on vibrational frequencies of Asp, Glu, and Tyr residues and to develop vibrational spectral markers for probing hydrogen bonding interactions using infrared spectroscopy. In addition, proton transfer process plays a crucial role in a wide range of energy transduction, signal transduction, and enzymatic reactions. We study the structural basis for proton transfer using photoactive yellow protein as an excellent model system. Molecular dynamics simulation is employed to investigate the structures of early intermediate states. Quantum theory based ab initio calculations are used to study the impact of hydrogen bond interactions on proton affinity and proton transfer. Findings and conclusions. Our extensive density function theory based calculations provide rich structural, spectral, and energetic information on hydrogen bonding properties of protonated side chain groups of Asp/Glu and Tyr. We developed vibrational spectral markers and 2D FTIR spectroscopy for structural characterization on the number and the type of hydrogen bonding interactions of the COOH group of Asp/Glu and neutral phenolic group of Tyr. These developments greatly enhance the power of time-resolved FTIR spectroscopy as a major experimental tool for structural characterization of functionally important

  13. Yeast Interacting Proteins Database: YKL002W, YLR423C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthes... into lumenal vesicles of multivesicular bodies, and for delivery of newly synthesized vacuolar enzymes to t

  14. Yeast Interacting Proteins Database: YKL002W, YDL165W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthes...ins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthesized vacuolar enzymes t

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

    Science.gov (United States)

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

    2018-03-01

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

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

    Czech Academy of Sciences Publication Activity Database

    Kysilka, Jiří; Vondrášek, Jiří

    2012-01-01

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

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

    KAUST Repository

    Haidar, Malak

    2017-09-08

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

  18. THERMODYNAMICS OF PROTEIN-LIGAND INTERACTIONS AND THEIR ANALYSIS

    Directory of Open Access Journals (Sweden)

    Rummi Devi Saini

    2017-11-01

    Full Text Available Physiological processes are controlled mainly by intermolecular recognition mechanisms which involve protein–protein and protein–ligand interactions with a high specificity and affinity to form a specific complex. Proteins being an important class of macromolecules in biological systems, it is important to understand their actions through binding to other molecules of proteins or ligands. In fact, the binding of low molecular weight ligands to proteins plays a significant role in regulating biological processes such as cellular metabolism and signal transmission. Therefore knowledge of the protein–ligand interactions and the knowledge of the mechanisms involved in the protein-ligand recognition and binding are key in understanding biology at molecular level which will facilitate the discovery, design, and development of drugs. In this review, the mechanisms involved in protein–ligand binding, the binding kinetics, thermodynamic concepts and binding driving forces are discussed. Thermodynamic mechanisms involved in a few important protein-ligand binding are described. Various spectroscopic, non-spectroscopic and computational method for analysis of protein–ligand binding are also discussed.

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

    Science.gov (United States)

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

    2013-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Mile Sikić

    2009-01-01

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

  1. 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.

  2. Structure and evolution of protein interaction networks: a statistical model for link dynamics and gene duplications

    Directory of Open Access Journals (Sweden)

    Wagner Andreas

    2004-11-01

    Full Text Available Abstract Background The structure of molecular networks derives from dynamical processes on evolutionary time scales. For protein interaction networks, global statistical features of their structure can now be inferred consistently from several large-throughput datasets. Understanding the underlying evolutionary dynamics is crucial for discerning random parts of the network from biologically important properties shaped by natural selection. Results We present a detailed statistical analysis of the protein interactions in Saccharomyces cerevisiae based on several large-throughput datasets. Protein pairs resulting from gene duplications are used as tracers into the evolutionary past of the network. From this analysis, we infer rate estimates for two key evolutionary processes shaping the network: (i gene duplications and (ii gain and loss of interactions through mutations in existing proteins, which are referred to as link dynamics. Importantly, the link dynamics is asymmetric, i.e., the evolutionary steps are mutations in just one of the binding parters. The link turnover is shown to be much faster than gene duplications. Both processes are assembled into an empirically grounded, quantitative model for the evolution of protein interaction networks. Conclusions According to this model, the link dynamics is the dominant evolutionary force shaping the statistical structure of the network, while the slower gene duplication dynamics mainly affects its size. Specifically, the model predicts (i a broad distribution of the connectivities (i.e., the number of binding partners of a protein and (ii correlations between the connectivities of interacting proteins, a specific consequence of the asymmetry of the link dynamics. Both features have been observed in the protein interaction network of S. cerevisiae.

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

    Science.gov (United States)

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

    2016-02-01

    Despite the partial disorder-to-order transition that intrinsically disordered proteins often undergo upon binding to their partners, a considerable amount of residual disorder may be retained in the bound form, resulting in a fuzzy complex. Fuzzy regions flanking molecular recognition elements may enable partner fishing through non-specific, transient contacts, thereby facilitating binding, but may also disfavor binding through various mechanisms. So far, few computational or experimental studies have addressed the effect of fuzzy appendages on partner recognition by intrinsically disordered proteins. In order to shed light onto this issue, we used the interaction between the intrinsically disordered C-terminal domain of the measles virus (MeV) nucleoprotein (NTAIL ) and the X domain (XD) of the viral phosphoprotein as model system. After binding to XD, the N-terminal region of NTAIL remains conspicuously disordered, with α-helical folding taking place only within a short molecular recognition element. To study the effect of the N-terminal fuzzy region on NTAIL /XD binding, we generated N-terminal truncation variants of NTAIL , and assessed their binding abilities towards XD. The results revealed that binding increases with shortening of the N-terminal fuzzy region, with this also being observed with hsp70 (another MeV NTAIL binding partner), and for the homologous NTAIL /XD pairs from the Nipah and Hendra viruses. Finally, similar results were obtained when the MeV NTAIL fuzzy region was replaced with a highly dissimilar artificial disordered sequence, supporting a sequence-independent inhibitory effect of the fuzzy region. © 2015 Federation of European Biochemical Societies.

  4. Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs

    LENUS (Irish Health Repository)

    Casey, Fergal

    2011-08-22

    Abstract Background Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks. Results We examined triplet motifs in a network of quantitative epistatic genetic relationships, and found a non-random distribution of particular motif classes. Individual motif classes were found to be associated with different functional properties, suggestive of an underlying biological significance. These associations were apparent not only for motif classes, but for individual positions within the motifs. As expected, NNN (all negative) motifs were strongly associated with previously reported genetic (i.e. synthetic lethal) interactions, while PPP (all positive) motifs were associated with protein complexes. The two other motif classes (NNP: a positive interaction spanned by two negative interactions, and NPP: a negative spanned by two positives) showed very distinct functional associations, with physical interactions dominating for the former but alternative enrichments, typical of biochemical pathways, dominating for the latter. Conclusion We present a model showing how NNP motifs can be used to recognize supportive relationships between protein complexes, while NPP motifs often identify opposing or regulatory behaviour between a gene and an associated pathway. The ability to use motifs to point toward underlying biological organizational themes is likely to be increasingly important as more extensive epistasis mapping projects in higher organisms begin.

  5. Yeast Interacting Proteins Database: YDR252W, YGR134W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available plex which binds ribosomes via its beta-subunits in close proximity to nascent polypeptides; interacts with ... nascent polypeptide-associated complex which binds ribosomes via its beta-subunits in close proximity to na

  6. Yeast Interacting Proteins Database: YNR051C, YER151C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available that coregulates anterograde and retrograde transport between the endoplasmic reticulum and Golgi compartme...C UBP3 Ubiquitin-specific protease that interacts with Bre5p to co-regulate anterograde and retrograde...t coregulates anterograde and retrograde transport between the endoplasmic reticulum and Golgi compartments;...3 Prey description Ubiquitin-specific protease that interacts with Bre5p to co-regulate anterograde and retrograde

  7. Small angle X-ray studies of protein-polymer interactions

    International Nuclear Information System (INIS)

    Torriani, Iris; Oliveira, Cristiano L.P. de; Almeida, Nara L.; Loh, Watson

    2003-01-01

    Full text: The interaction between biological macromolecules and non-adsorbing polymers is considered of utmost importance in the study of protein crystallization processes and in the study of a large number of protein-polymer systems or artificial surfaces used in medical procedures, in which polymeric materials are in contact with blood proteins. The structural information furnished by small angle X-ray scattering (SAXS) experiments can be used to describe protein-polymer interaction in solution mixtures considering the dispersion as a two-component system. In this work, two proteins, lysozyme and bovine serum albumin (BSA), were studied in the presence of Poly(ethylene oxide) (PEO), various EO/PO copolymers of varied composition and Poly(ethylene glycol) (PEG). Thermal stability of both lysozyme and BSA was studied in the presence of these polymers. X-ray scattering experiments were performed at the SAXS beamline of the Laboratorio Nacional de Luz Sincrotron, Campinas, SP, using the facility available for liquid dispersions under controlled temperature. Room temperature measurements were aimed at detecting possible polymer-protein interactions. Thermal denaturation processes were studied in some of these systems in order to check the stabilizing effect of some of the polymers used, at fixed temperatures of 25, 50, 60 and 70 deg C. At 80 deg C, using a real time data acquisition system, structural changes could be followed as a function of time in a sequence of frames that show denaturation and aggregation of the proteins. Real space analysis of the intensity functions was performed using a mathematical expression derived for the form factor of a system of particles of different shapes. The pair distance distribution functions of each component of the system could be calculated separately. The possibility of complex formation in the case of the proteins studied is not supported by our results. The presence of polymers may affect the protein-protein interaction

  8. Fast and accurate multivariate Gaussian modeling of protein families: predicting residue contacts and protein-interaction partners.

    Directory of Open Access Journals (Sweden)

    Carlo Baldassi

    Full Text Available In the course of evolution, proteins show a remarkable conservation of their three-dimensional structure and their biological function, leading to strong evolutionary constraints on the sequence variability between homologous proteins. Our method aims at extracting such constraints from rapidly accumulating sequence data, and thereby at inferring protein structure and function from sequence information alone. Recently, global statistical inference methods (e.g. direct-coupling analysis, sparse inverse covariance estimation have achieved a breakthrough towards this aim, and their predictions have been successfully implemented into tertiary and quaternary protein structure prediction methods. However, due to the discrete nature of the underlying variable (amino-acids, exact inference requires exponential time in the protein length, and efficient approximations are needed for practical applicability. Here we propose a very efficient multivariate Gaussian modeling approach as a variant of direct-coupling analysis: the discrete amino-acid variables are replaced by continuous Gaussian random variables. The resulting statistical inference problem is efficiently and exactly solvable. We show that the quality of inference is comparable or superior to the one achieved by mean-field approximations to inference with discrete variables, as done by direct-coupling analysis. This is true for (i the prediction of residue-residue contacts in proteins, and (ii the identification of protein-protein interaction partner in bacterial signal transduction. An implementation of our multivariate Gaussian approach is available at the website http://areeweb.polito.it/ricerca/cmp/code.

  9. Fast and accurate multivariate Gaussian modeling of protein families: predicting residue contacts and protein-interaction partners.

    Science.gov (United States)

    Baldassi, Carlo; Zamparo, Marco; Feinauer, Christoph; Procaccini, Andrea; Zecchina, Riccardo; Weigt, Martin; Pagnani, Andrea

    2014-01-01

    In the course of evolution, proteins show a remarkable conservation of their three-dimensional structure and their biological function, leading to strong evolutionary constraints on the sequence variability between homologous proteins. Our method aims at extracting such constraints from rapidly accumulating sequence data, and thereby at inferring protein structure and function from sequence information alone. Recently, global statistical inference methods (e.g. direct-coupling analysis, sparse inverse covariance estimation) have achieved a breakthrough towards this aim, and their predictions have been successfully implemented into tertiary and quaternary protein structure prediction methods. However, due to the discrete nature of the underlying variable (amino-acids), exact inference requires exponential time in the protein length, and efficient approximations are needed for practical applicability. Here we propose a very efficient multivariate Gaussian modeling approach as a variant of direct-coupling analysis: the discrete amino-acid variables are replaced by continuous Gaussian random variables. The resulting statistical inference problem is efficiently and exactly solvable. We show that the quality of inference is comparable or superior to the one achieved by mean-field approximations to inference with discrete variables, as done by direct-coupling analysis. This is true for (i) the prediction of residue-residue contacts in proteins, and (ii) the identification of protein-protein interaction partner in bacterial signal transduction. An implementation of our multivariate Gaussian approach is available at the website http://areeweb.polito.it/ricerca/cmp/code.

  10. A method for computing association rate constants of atomistically represented proteins under macromolecular crowding

    Science.gov (United States)

    Qin, Sanbo; Cai, Lu; Zhou, Huan-Xiang

    2012-12-01

    In cellular environments, two protein molecules on their way to form a specific complex encounter many bystander macromolecules. The latter molecules, or crowders, affect both the energetics of the interaction between the test molecules and the dynamics of their relative motion. In earlier work (Zhou and Szabo 1991 J. Chem. Phys. 95 5948-52), it has been shown that, in modeling the association kinetics of the test molecules, the presence of crowders can be accounted for by their energetic and dynamic effects. The recent development of the transient-complex theory for protein association in dilute solutions makes it possible to easily incorporate the energetic and dynamic effects of crowders. The transient complex refers to a late on-pathway intermediate, in which the two protein molecules have near-native relative separation and orientation, but have yet to form the many short-range specific interactions of the native complex. The transient-complex theory predicts the association rate constant as ka = ka0exp( - ΔG*el/kBT), where ka0 is the ‘basal’ rate constant for reaching the transient complex by unbiased diffusion, and the Boltzmann factors captures the influence of long-range electrostatic interactions between the protein molecules. Crowders slow down the diffusion, therefore reducing the basal rate constant (to kac0), and induce an effective interaction energy ΔGc. We show that the latter interaction energy for atomistic proteins in the presence of spherical crowders is ‘long’-ranged, allowing the association rate constant under crowding to be computed as kac = kac0exp[ - (ΔG*el + ΔG*c)/kBT]. Applications demonstrate that this computational method allows for realistic modeling of protein association kinetics under crowding.

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

    Science.gov (United States)

    Raut, Ashlesha S; Kalonia, Devendra S

    2016-01-01

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

  12. Versatile Tool for the Analysis of Metal-Protein Interactions Reveals the Promiscuity of Metallodrug-Protein Interactions.

    Science.gov (United States)

    Lee, Ronald F S; Menin, Laure; Patiny, Luc; Ortiz, Daniel; Dyson, Paul J

    2017-11-21

    Metallodrug-protein interactions contribute to their therapeutic effect (even when DNA is the dominant target), side-effects and are implicit in drug resistance. Here, we provide mass spectrometric-based evidence to show that metallodrug interactions with proteins are considerably more complex than current literature would suggest. Using native-like incubation and electrospray conditions together with an automated tool we designed for exhaustive mass spectra matching, the promiscuity of binding of cisplatin to ubiquitin is revealed, with 14 different binding sites observed. There is a binding preference to negatively charged sites on the protein, consistent with the cationic nature of the cisplatin adduct following aquation. These results have implications in metallodrug development and beyond to the toxicological effects of metal ions more generally.

  13. Investigation of the Interaction between Mucins and β-Lactoglobulin under Tribological Stress

    DEFF Research Database (Denmark)

    Celebioglu, Hilal Yilmaz; Guðjónsdóttir, María; Chronakis, Ioannis S.

    2016-01-01

    The interaction characteristics between mucins and beta-lactoglobulin (BLG) under tribological stress were investigated by comparing the lubricity of mixed solutions of mucineBLG with that of neat protein solutions at compliant hydrophobic interfaces. Surface adsorption properties of the proteins......BSM and BLGePGM, reduced significantly, and BLG appeared to dominate the surface adsorption event, presumably due to the reduced concentration of mucins and the Vroman effect. While pin-on-disk tribometry and mini-traction machine (MTM) were employed to provide the tribological contacts with varying contact...... acidic pH, such as at pH 3.5. More importantly, pH dependent lubricating properties of BLGeBSM mixed solutions appeared to be determined by competitive adsorption of the two proteins onto the substrates, which suggests that they do not form as strong aggregates as BLGesaliva, especially under...

  14. AESOP: A Python Library for Investigating Electrostatics in Protein Interactions.

    Science.gov (United States)

    Harrison, Reed E S; Mohan, Rohith R; Gorham, Ronald D; Kieslich, Chris A; Morikis, Dimitrios

    2017-05-09

    Electric fields often play a role in guiding the association of protein complexes. Such interactions can be further engineered to accelerate complex association, resulting in protein systems with increased productivity. This is especially true for enzymes where reaction rates are typically diffusion limited. To facilitate quantitative comparisons of electrostatics in protein families and to describe electrostatic contributions of individual amino acids, we previously developed a computational framework called AESOP. We now implement this computational tool in Python with increased usability and the capability of performing calculations in parallel. AESOP utilizes PDB2PQR and Adaptive Poisson-Boltzmann Solver to generate grid-based electrostatic potential files for protein structures provided by the end user. There are methods within AESOP for quantitatively comparing sets of grid-based electrostatic potentials in terms of similarity or generating ensembles of electrostatic potential files for a library of mutants to quantify the effects of perturbations in protein structure and protein-protein association. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  15. Interaction between the enamel matrix proteins amelogenin and ameloblastin

    International Nuclear Information System (INIS)

    Ravindranath, Hanumanth H.; Chen, Li-Sha; Zeichner-David, Margaret; Ishima, Rieko; Ravindranath, Rajeswari M.H.

    2004-01-01

    Enamel matrix consists of amelogenin and non-amelogenins. Though amelogenin is not involved in nucleation of minerals, the enamel mineralization is impaired when amelogenin or other matrix protein (ameloblastin/enamelin) genes are mutated. We hypothesize that amelogenin may promote enamel mineralization by interacting with the calcium-binding matrix proteins. Specific binding of amelogenin to N-acetylglucosamine (GlcNAc), GlcNAc-mimicking peptides (GMps), and their carrier proteins and the identification of amelogenin-trityrosyl-motif-peptide (ATMP) as a GlcNAc/GMp-binding domain in amelogenin favor the hypothesis. This study tested the interaction of amelogenin with ameloblastin, a carrier of GMp sequence at intermittent sites. Neither GlcNAc nor sialic acids were identified in the recombinant-ameloblastin. Amelogenin bound to recombinant-ameloblastin in both Western blots and in ELISA. More specifically, [ 3 H]ATMP bound to both recombinant and native ameloblastins. Dosimetry and Scatchard analyses showed the specific interaction between ATMP and ameloblastin, suggesting that amelogenin may interact with ameloblastin to form a heteromolecular assembly

  16. Interaction between the enamel matrix proteins amelogenin and ameloblastin.

    Science.gov (United States)

    Ravindranath, Hanumanth H; Chen, Li-Sha; Zeichner-David, Margaret; Ishima, Rieko; Ravindranath, Rajeswari M H

    2004-10-22

    Enamel matrix consists of amelogenin and non-amelogenins. Though amelogenin is not involved in nucleation of minerals, the enamel mineralization is impaired when amelogenin or other matrix protein (ameloblastin/enamelin) genes are mutated. We hypothesize that amelogenin may promote enamel mineralization by interacting with the calcium-binding matrix proteins. Specific binding of amelogenin to N-acetylglucosamine (GlcNAc), GlcNAc-mimicking peptides (GMps), and their carrier proteins and the identification of amelogenin-trityrosyl-motif-peptide (ATMP) as a GlcNAc/GMp-binding domain in amelogenin favor the hypothesis. This study tested the interaction of amelogenin with ameloblastin, a carrier of GMp sequence at intermittent sites. Neither GlcNAc nor sialic acids were identified in the recombinant-ameloblastin. Amelogenin bound to recombinant-ameloblastin in both Western blots and in ELISA. More specifically, [(3)H]ATMP bound to both recombinant and native ameloblastins. Dosimetry and Scatchard analyses showed the specific interaction between ATMP and ameloblastin, suggesting that amelogenin may interact with ameloblastin to form a heteromolecular assembly.

  17. A membrane protein / signaling protein interaction network for Arabidopsis version AMPv2

    Directory of Open Access Journals (Sweden)

    Sylvie Lalonde

    2010-09-01

    Full Text Available Interactions between membrane proteins and the soluble fraction are essential for signal transduction and for regulating nutrient transport. To gain insights into the membrane-based interactome, 3,852 open reading frames (ORFs out of a target list of 8,383 representing membrane and signaling proteins from Arabidopsis thaliana were cloned into a Gateway compatible vector. The mating-based split-ubiquitin system was used to screen for potential protein-protein interactions (pPPIs among 490 Arabidopsis ORFs. A binary robotic screen between 142 receptor-like kinases, 72 transporters, 57 soluble protein kinases and phosphatases, 40 glycosyltransferases, 95 proteins of various functions and 89 proteins with unknown function detected 387 out of 90,370 possible PPIs. A secondary screen confirmed 343 (of 387 pPPIs between 179 proteins, yielding a scale-free network (r2=0.863. Eighty of 142 transmembrane receptor-like kinases (RLK tested positive, identifying three homomers, 63 heteromers and 80 pPPIs with other proteins. Thirty-one out of 142 RLK interactors (including RLKs had previously been found to be phosphorylated; thus interactors may be substrates for respective RLKs. None of the pPPIs described here had been reported in the major interactome databases, including potential interactors of G protein-coupled receptors, phospholipase C, and AMT ammonium transporters. Two RLKs found as putative interactors of AMT1;1 were independently confirmed using a split luciferase assay in Arabidopsis protoplasts. These RLKs may be involved in ammonium-dependent phosphorylation of the C-terminus and regulation of ammonium uptake activity. The robotic screening method established here will enable a systematic analysis of membrane protein interactions in fungi, plants and metazoa.

  18. Exploration of the pathways and interaction network involved in bladder cancer cell line with knockdown of Opa interacting protein 5.

    Science.gov (United States)

    He, Xuefeng; Ding, Xiang; Wen, Duangai; Hou, Jianquan; Ping, Jigen; He, Jun

    2017-09-01

    In our previous study, we displayed that knockdown of Opa interacting protein 5 (OIP5) inhibited cell growth, disturbed cell cycle and increased cell apoptosis in bladder cancer (BC) cell line. Our present study aimed to explore the underlying pathways and interaction network involved in the roles of OIP5 in BC. Microarray analysis was conducted to obtain mRNA expression profiling of OIP5 knockdown (shOIP5) and control (shCtrl) BC cell lines. Bioinformatics analyses were performed including differentially expressed mRNAs (DEGs) identification, protein-protein interaction network construction, biological functions of prediction and ingenuity pathways analysis (IPA). Western Blotting (WB) was subjected to validate the protein expression levels of candidate DEGs in shOIP5 BC cell line. Respective 255 up- and 184 down-regulated DEGs were identified in shOIP5 group compared with shCtrl group. In the PPI network, CAND1 and MYC had the highest connectivity with DEGs. 439 DEGs were significantly enriched in inflammatory response, regulation of cell proliferation, Toll-like receptor signaling pathway, cytokine-cytokine receptor interaction and bladder cancer. In the disease and function enrichment, DEGs were obviously involved in cellular movement, cellular growth and proliferation, cancer, inflammatory response, cell death and survival. In the OIP5 regulatory network, CDH2, IRS1, IRAK3, ID1, TNF, IL6, ITGA6, MYC and SOD2 interacted with OIP5. The WB validation results were compatible with our bioinformatics analyses. OIP5 interaction network might function as an oncogene in BC progression based on aberrant inflammatory responses. Our study might provide valuable information for investigation of tumorigenesis mechanism in BC. Copyright © 2017 Elsevier GmbH. All rights reserved.

  19. Bioinformatic prediction and in vivo validation of residue-residue interactions in human proteins

    Science.gov (United States)

    Jordan, Daniel; Davis, Erica; Katsanis, Nicholas; Sunyaev, Shamil

    2014-03-01

    Identifying residue-residue interactions in protein molecules is important for understanding both protein structure and function in the context of evolutionary dynamics and medical genetics. Such interactions can be difficult to predict using existing empirical or physical potentials, especially when residues are far from each other in sequence space. Using a multiple sequence alignment of 46 diverse vertebrate species we explore the space of allowed sequences for orthologous protein families. Amino acid changes that are known to damage protein function allow us to identify specific changes that are likely to have interacting partners. We fit the parameters of the continuous-time Markov process used in the alignment to conclude that these interactions are primarily pairwise, rather than higher order. Candidates for sites under pairwise epistasis are predicted, which can then be tested by experiment. We report the results of an initial round of in vivo experiments in a zebrafish model that verify the presence of multiple pairwise interactions predicted by our model. These experimentally validated interactions are novel, distant in sequence, and are not readily explained by known biochemical or biophysical features.

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

    Directory of Open Access Journals (Sweden)

    Moschopoulos Charalampos

    2011-06-01

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

  1. Human cytomegalovirus RL13 protein interacts with host NUDT14 protein affecting viral DNA replication.

    Science.gov (United States)

    Wang, Guili; Ren, Gaowei; Cui, Xin; Lu, Zhitao; Ma, Yanping; Qi, Ying; Huang, Yujing; Liu, Zhongyang; Sun, Zhengrong; Ruan, Qiang

    2016-03-01

    The interaction between the host and human cytomegalovirus (HCMV) is important in determining the outcome of a viral infection. The HCMV RL13 gene product exerts independent, inhibitory effects on viral growth in fibroblasts and epithelial cells. At present, there are few reports on the interactions between the HCMV RL13 protein and human host proteins. The present study provided direct evidence for the specific interaction between HCMV RL13 and host nucleoside diphosphate linked moiety X (nudix)‑type motif 14 (NUDT14), a UDP‑glucose pyrophosphatase, using two‑hybrid screening, an in vitro glutathione S‑transferase pull‑down assay, and co‑immunoprecipitation in human embryonic kidney HEK293 cells. Additionally, the RL13 protein was shown to co‑localize with the NUDT14 protein in the HEK293 cell membrane and cytoplasm, demonstrated using fluorescence confocal microscopy. Decreasing the expression level of NUDT14 via NUDT14‑specific small interfering RNAs increased the number of viral DNA copies in the HCMV‑infected cells. However, the overexpression of NUDT14 in a stably expressing cell line did not affect viral DNA levels significantly in the HCMV infected cells. Based on the known functions of NUDT14, the results of the present study suggested that the interaction between the RL13 protein and NUDT14 protein may be involved in HCMV DNA replication, and that NUDT14 may offer potential in the modulation of viral infection.

  2. Protein disulfide-isomerase interacts with a substrate protein at all stages along its folding pathway.

    Directory of Open Access Journals (Sweden)

    Alistair G Irvine

    Full Text Available In contrast to molecular chaperones that couple protein folding to ATP hydrolysis, protein disulfide-isomerase (PDI catalyzes protein folding coupled to formation of disulfide bonds (oxidative folding. However, we do not know how PDI distinguishes folded, partly-folded and unfolded protein substrates. As a model intermediate in an oxidative folding pathway, we prepared a two-disulfide mutant of basic pancreatic trypsin inhibitor (BPTI and showed by NMR that it is partly-folded and highly dynamic. NMR studies show that it binds to PDI at the same site that binds peptide ligands, with rapid binding and dissociation kinetics; surface plasmon resonance shows its interaction with PDI has a Kd of ca. 10(-5 M. For comparison, we characterized the interactions of PDI with native BPTI and fully-unfolded BPTI. Interestingly, PDI does bind native BPTI, but binding is quantitatively weaker than with partly-folded and unfolded BPTI. Hence PDI recognizes and binds substrates via permanently or transiently unfolded regions. This is the first study of PDI's interaction with a partly-folded protein, and the first to analyze this folding catalyst's changing interactions with substrates along an oxidative folding pathway. We have identified key features that make PDI an effective catalyst of oxidative protein folding - differential affinity, rapid ligand exchange and conformational flexibility.

  3. The coat protein complex II, COPII, protein Sec13 directly interacts with presenilin-1

    International Nuclear Information System (INIS)

    Nielsen, Anders Lade

    2009-01-01

    Mutations in the human gene encoding presenilin-1, PS1, account for most cases of early-onset familial Alzheimer's disease. PS1 has nine transmembrane domains and a large loop orientated towards the cytoplasm. PS1 locates to cellular compartments as endoplasmic reticulum (ER), Golgi apparatus, vesicular structures, and plasma membrane, and is an integral member of γ-secretase, a protein protease complex with specificity for intra-membranous cleavage of substrates such as β-amyloid precursor protein. Here, an interaction between PS1 and the Sec13 protein is described. Sec13 takes part in coat protein complex II, COPII, vesicular trafficking, nuclear pore function, and ER directed protein sequestering and degradation control. The interaction maps to the N-terminal part of the large hydrophilic PS1 loop and the first of the six WD40-repeats present in Sec13. The identified Sec13 interaction to PS1 is a new candidate interaction for linking PS1 to secretory and protein degrading vesicular circuits.

  4. Fanconi Anemia Proteins and Their Interacting Partners: A Molecular Puzzle

    Science.gov (United States)

    Kaddar, Tagrid; Carreau, Madeleine

    2012-01-01

    In recent years, Fanconi anemia (FA) has been the subject of intense investigations, primarily in the DNA repair research field. Many discoveries have led to the notion of a canonical pathway, termed the FA pathway, where all FA proteins function sequentially in different protein complexes to repair DNA cross-link damages. Although a detailed architecture of this DNA cross-link repair pathway is emerging, the question of how a defective DNA cross-link repair process translates into the disease phenotype is unresolved. Other areas of research including oxidative metabolism, cell cycle progression, apoptosis, and transcriptional regulation have been studied in the context of FA, and some of these areas were investigated before the fervent enthusiasm in the DNA repair field. These other molecular mechanisms may also play an important role in the pathogenesis of this disease. In addition, several FA-interacting proteins have been identified with roles in these “other” nonrepair molecular functions. Thus, the goal of this paper is to revisit old ideas and to discuss protein-protein interactions related to other FA-related molecular functions to try to give the reader a wider perspective of the FA molecular puzzle. PMID:22737580

  5. Treponema pallidum receptor binding proteins interact with fibronectin

    Energy Technology Data Exchange (ETDEWEB)

    Peterson, K.M.; Baseman, J.B.; Alderete, J.F.

    1983-06-01

    Analysis of plasma proteins avidly bound to T. pallidum surfaces revealed the ability of T. pallidum to acquire numerous host macromolecules. No acquisition was evident by the avirulent spirochete, T. phagedenis biotype Reiter. Western blotting technology using hyperimmune antifibronectin serum as a probe revealed the ability of virulent treponemes to avidly bind fibronectin from a complex medium such as plasma. The specificity of the tiplike adherence of motile T. pallidum to fibronectin-coated glass surfaces and to fibronectin on HEp-2 cells was reinforced by the observation that pretreatment of coverslips or cell monolayers with monospecific antiserum against fibronectin substantially reduced T. pallidum attachment. The stoichiometric binding of T. pallidum to fibronectin-coated coverslips and the inability of unlabeled or /sup 35/S-radiolabeled treponemes to interact with glass surfaces treated with other plasma proteins further established the specific nature of the interaction between virulent T. pallidum and fibronectin. The avid association between three outer envelope proteins of T. pallidum and fibronectin was also demonstrated. These treponemal surface proteins have been previously identified as putative receptor-binding proteins responsible for T. pallidum parasitism of host cells. The data suggest that surface fibronectin mediates tip-oriented attachment of T. pallidum to host cells via a receptor-ligand mechanism of recognition.

  6. Identification of Inhibitors of Biological Interactions Involving Intrinsically Disordered Proteins

    Directory of Open Access Journals (Sweden)

    Daniela Marasco

    2015-04-01

    Full Text Available Protein–protein interactions involving disordered partners have unique features and represent prominent targets in drug discovery processes. Intrinsically Disordered Proteins (IDPs are involved in cellular regulation, signaling and control: they bind to multiple partners and these high-specificity/low-affinity interactions play crucial roles in many human diseases. Disordered regions, terminal tails and flexible linkers are particularly abundant in DNA-binding proteins and play crucial roles in the affinity and specificity of DNA recognizing processes. Protein complexes involving IDPs are short-lived and typically involve short amino acid stretches bearing few “hot spots”, thus the identification of molecules able to modulate them can produce important lead compounds: in this scenario peptides and/or peptidomimetics, deriving from structure-based, combinatorial or protein dissection approaches, can play a key role as hit compounds. Here, we propose a panoramic review of the structural features of IDPs and how they regulate molecular recognition mechanisms focusing attention on recently reported drug-design strategies in the field of IDPs.

  7. Chaperoning Roles of Macromolecules Interacting with Proteins in Vivo

    Directory of Open Access Journals (Sweden)

    Baik L. Seong

    2011-03-01

    Full Text Available The principles obtained from studies on molecular chaperones have provided explanations for the assisted protein folding in vivo. However, the majority of proteins can fold without the assistance of the known molecular chaperones, and little attention has been paid to the potential chaperoning roles of other macromolecules. During protein biogenesis and folding, newly synthesized polypeptide chains interact with a variety of macromolecules, including ribosomes, RNAs, cytoskeleton, lipid bilayer, proteolytic system, etc. In general, the hydrophobic interactions between molecular chaperones and their substrates have been widely believed to be mainly responsible for the substrate stabilization against aggregation. Emerging evidence now indicates that other features of macromolecules such as their surface charges, probably resulting in electrostatic repulsions, and steric hindrance, could play a key role in the stabilization of their linked proteins against aggregation. Such stabilizing mechanisms are expected to give new insights into our understanding of the chaperoning functions for de novo protein folding. In this review, we will discuss the possible chaperoning roles of these macromolecules in de novo folding, based on their charge and steric features.

  8. Yeast Interacting Proteins Database: YHL004W, YDL100C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available it as bait (3) Rows with this bait as prey (0) YDL100C GET3 Guanine nucleotide exchange factor for Gpa1p; amplifies...exchange factor for Gpa1p; amplifies G protein signaling; subunit of the GET complex, which is involved in G

  9. Yeast Interacting Proteins Database: YDL121C, YDL100C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available as bait (1) Rows with this bait as prey (0) YDL100C GET3 Guanine nucleotide exchange factor for Gpa1p; amplifies...ion Guanine nucleotide exchange factor for Gpa1p; amplifies G protein signaling; subunit of the GET complex,

  10. Yeast Interacting Proteins Database: YJR091C, YDR389W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available to the actin cytoskeleton, null mutations suppress tor2 mutations and temperature sensitive mutations in act...ion GTPase activating protein (GAP) for Rho1p, involved in signaling to the actin cytoskeleton, null mutations suppress tor2 mutation...s and temperature sensitive mutations in actin; potential Cdc28p substrate Rows wit

  11. Surface (glyco-)proteins: primary structure and crystallization under microgravity conditions

    Science.gov (United States)

    Claus, H.; Akca, E.; Schultz, N.; Karbach, G.; Schlott, B.; Debaerdemaeker, T.; De Clercq, J.-P.; König, H.

    2001-08-01

    The Archaea comprise microorganisms that live under environmental extremes, like high temperature, low pH value or high salt concentration. Their cells are often covered by a single layer of (glyco)protein subunits (S-layer) in hexagonal arrangement. In order to get further hints about the molecular mechanisms of protein stabilization we compared the primary and secondary structures of archaeal S-layer (glyco)proteins. We found an increase of charged amino acids in the S-layer proteins of the extreme thermophilic species compared to their mesophilic counterparts. Our data and those of other authors suggest that ionic interactions, e.g., salt bridges seem to be played a major role in protein stabilization at high temperatures. Despite the differences in the growth optima and the predominance of some amino acids the primary structures of S-layers revealed also a significant degree of identity between phylogenetically related archaea. These obervations indicate that protein sequences of S-layers have been conserved during the evolution from extremely thermophilic to mesophilic life. To support these findings the three-dimensional structure of the S-layer proteins has to be elucidated. Recently, we described the first successful crystallization of an extreme thermophilic surface(glyco)protein under microgravity conditions.

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

    Science.gov (United States)

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

    2014-04-01

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

  13. Growing functional modules from a seed protein via integration of protein interaction and gene expression data

    Directory of Open Access Journals (Sweden)

    Dimitrakopoulou Konstantina

    2007-10-01

    Full Text Available Abstract Background Nowadays modern biology aims at unravelling the strands of complex biological structures such as the protein-protein interaction (PPI networks. A key concept in the organization of PPI networks is the existence of dense subnetworks (functional modules in them. In recent approaches clustering algorithms were applied at these networks and the resulting subnetworks were evaluated by estimating the coverage of well-established protein complexes they contained. However, most of these algorithms elaborate on an unweighted graph structure which in turn fails to elevate those interactions that would contribute to the construction of biologically more valid and coherent functional modules. Results In the current study, we present a method that corroborates the integration of protein interaction and microarray data via the discovery of biologically valid functional modules. Initially the gene expression information is overlaid as weights onto the PPI network and the enriched PPI graph allows us to exploit its topological aspects, while simultaneously highlights enhanced functional association in specific pairs of proteins. Then we present an algorithm that unveils the functional modules of the weighted graph by expanding a kernel protein set, which originates from a given 'seed' protein used as starting-point. Conclusion The integrated data and the concept of our approach provide reliable functional modules. We give proofs based on yeast data that our method manages to give accurate results in terms both of structural coherency, as well as functional consistency.

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

    Science.gov (United States)

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

    2011-03-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-07-28

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

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

    Science.gov (United States)

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

    2015-12-01

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

  17. NOX Activation by Subunit Interaction and Underlying Mechanisms in Disease.

    Science.gov (United States)

    Rastogi, Radhika; Geng, Xiaokun; Li, Fengwu; Ding, Yuchuan

    2016-01-01

    Nicotinamide adenine dinucleotide phosphate (NAPDH) oxidase (NOX) is an enzyme complex with the sole function of producing superoxide anion and reactive oxygen species (ROS) at the expense of NADPH. Vital to the immune system as well as cellular signaling, NOX is also involved in the pathologies of a wide variety of disease states. Particularly, it is an integral player in many neurological diseases, including stroke, TBI, and neurodegenerative diseases. Pathologically, NOX produces an excessive amount of ROS that exceed the body's antioxidant ability to neutralize them, leading to oxidative stress and aberrant signaling. This prevalence makes it an attractive therapeutic target and as such, NOX inhibitors have been studied and developed to counter NOX's deleterious effects. However, recent studies of NOX have created a better understanding of the NOX complex. Comprised of independent cytosolic subunits, p47- phox , p67- phox , p40- phox and Rac , and membrane subunits, gp91- phox and p22- phox , the NOX complex requires a unique activation process through subunit interaction. Of these subunits, p47- phox plays the most important role in activation, binding and translocating the cytosolic subunits to the membrane and anchoring to p22- phox to organize the complex for NOX activation and function. Moreover, these interactions, particularly that between p47- phox and p22- phox , are dependent on phosphorylation initiated by upstream processes involving protein kinase C (PKC). This review will look at these interactions between subunits and with PKC. It will focus on the interaction involving p47- phox with p22- phox , key in bringing the cytosolic subunits to the membrane. Furthermore, the implication of these interactions as a target for NOX inhibitors such as apocynin will be discussed as a potential avenue for further investigation, in order to develop more specific NOX inhibitors based on the inhibition of NOX assembly and activation.

  18. Mapping side chain interactions at protein helix termini.

    Science.gov (United States)

    Newell, Nicholas E

    2015-07-25

    Interactions that involve one or more amino acid side chains near the ends of protein helices stabilize helix termini and shape the geometry of the adjacent loops, making a substantial contribution to overall protein structure. Previous work has identified key helix-terminal motifs, such as Asx/ST N-caps, the capping box, and hydrophobic and electrostatic interactions, but important questions remain, including: 1) What loop backbone geometries are favoured by each motif? 2) To what extent are multi-amino acid motifs likely to represent genuine cooperative interactions? 3) Can new motifs be identified in a large, recent dataset using the latest bioinformatics tools? Three analytical tools are applied here to answer these questions. First, helix-terminal structures are partitioned by loop backbone geometry using a new 3D clustering algorithm. Next, Cascade Detection, a motif detection algorithm recently published by the author, is applied to each cluster to determine which sequence motifs are overrepresented in each geometry. Finally, the results for each motif are presented in a CapMap, a 3D conformational heatmap that displays the distribution of the motif's overrepresentation across loop geometries, enabling the rapid isolation and characterization of the associated side chain interaction. This work identifies a library of geometry-specific side chain interactions that provides a new, detailed picture of loop structure near the helix terminus. Highlights include determinations of the favoured loop geometries for the Asx/ST N-cap motifs, capping boxes, "big" boxes, and other hydrophobic, electrostatic, H-bond, and pi stacking interactions, many of which have not been described before. This work demonstrates that the combination of structural clustering and motif detection in the sequence space can efficiently identify side chain motifs and map them to the loop geometries which they support. Protein designers should find this study useful, because it identifies side

  19. Dataset concerning GroEL chaperonin interaction with proteins

    Directory of Open Access Journals (Sweden)

    V.V. Marchenkov

    2016-03-01

    Full Text Available GroEL chaperonin is well-known to interact with a wide variety of polypeptide chains. Here we show the data related to our previous work (http://dx.doi.org/10.1016/j.pep.2015.11.020 [1], and concerning the interaction of GroEL with native (lysozyme, α-lactalbumin and denatured (lysozyme, α-lactalbumin and pepsin proteins in solution. The use of affinity chromatography on the base of denatured pepsin for GroEL purification from fluorescent impurities is represented as well.

  20. Protein Interaction Data Curation - The International Molecular Exchange Consortium (IMEx)

    Science.gov (United States)

    Orchard, Sandra; Kerrien, Samuel; Abbani, Sara; Aranda, Bruno; Bhate, Jignesh; Bidwell, Shelby; Bridge, Alan; Briganti, Leonardo; Brinkman, Fiona S. L.; Cesareni, Gianni; Chatr-aryamontri, Andrew; Chautard, Emilie; Chen, Carol; Dumousseau, Marine; Goll, Johannes; Hancock, Robert E. W.; Hannick, Linda I.; Jurisica, Igor; Khadake, Jyoti; Lynn, David J.; Mahadevan, Usha; Perfetto, Livia; Raghunath, Arathi; Ricard-Blum, Sylvie; Roechert, Bernd; Salwinski, Lukasz; Stümpflen, Volker; Tyers, Mike; Uetz, Peter; Xenarios, Ioannis; Hermjakob, Henning

    2013-01-01

    The IMEx consortium is an international collaboration between major public interaction data providers to share curation effort and make a non-redundant set of protein interactions available in a single search interface on a common website (www.imexconsortium.org). Common curation rules have been developed and a central registry is used to manage the selection of articles to enter into the dataset. The advantages of such a service to the user, quality control measures adopted and data distribution practices are discussed. PMID:22453911

  1. Yeast Interacting Proteins Database: YMR047C, YOR112W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ort pathway; interacts with nuclear pore component Nup116p; copurifies with tRNA export receptors Los1p and ...ts with nuclear pore component Nup116p; copurifies with tRNA export receptors Los1p and Msn5p, as well as eI

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

    Directory of Open Access Journals (Sweden)

    Wan Li

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

  3. PRDM14 directly interacts with heat shock proteins HSP90α and glucose-regulated protein 78.

    Science.gov (United States)

    Moriya, Chiharu; Taniguchi, Hiroaki; Nagatoishi, Satoru; Igarashi, Hisayoshi; Tsumoto, Kouhei; Imai, Kohzoh

    2018-02-01

    PRDM14 is overexpressed in various cancers and can regulate cancer phenotype under certain conditions. Inhibiting PRDM14 expression in breast and pancreatic cancers has been reported to reduce cancer stem-like phenotypes, which are associated with aggressive tumor properties. Therefore, PRDM14 is considered a promising target for cancer therapy. To develop a pharmaceutical treatment, the mechanism and interacting partners of PRDM14 need to be clarified. Here, we identified the proteins interacting with PRDM14 in triple-negative breast cancer (TNBC) cells, which do not express the three most common types of receptor (estrogen receptors, progesterone receptors, and HER2). We obtained 13 candidates that were pulled down with PRDM14 in TNBC HCC1937 cells and identified them by mass spectrometry. Two candidates-glucose-regulated protein 78 (GRP78) and heat shock protein 90-α (HSP90α)-were confirmed in immunoprecipitation assay in two TNBC cell lines (HCC1937 and MDA-MB231). Surface plasmon resonance analysis using GST-PRDM14 showed that these two proteins directly interacted with PRDM14 and that the interactions required the C-terminal region of PRDM14, which includes zinc finger motifs. We also confirmed the interactions in living cells by NanoLuc luciferase-based bioluminescence resonance energy transfer (NanoBRET) assay. Moreover, HSP90 inhibitors (17DMAG and HSP990) significantly decreased breast cancer stem-like CD24 -  CD44 + and side population (SP) cells in HCC1937 cells, but not in PRDM14 knockdown HCC1937 cells. The combination of the GRP78 inhibitor HA15 and PRDM14 knockdown significantly decreased cell proliferation and SP cell number in HCC1937 cells. These results suggest that HSP90α and GRP78 interact with PRDM14 and participate in cancer regulation. © 2017 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

  4. Predicting protein complex in protein interaction network - a supervised learning based method.

    Science.gov (United States)

    Yu, Feng; Yang, Zhi; Tang, Nan; Lin, Hong; Wang, Jian; Yang, Zhi

    2014-01-01

    Protein complexes are important for understanding principles of cellular organization and function. High-throughput experimental techniques have produced a large amount of protein interactions, making it possible to predict protein complexes from protein -protein interaction networks. However, most of current methods are unsupervised learning based methods which can't utilize the information of the large amount of available known complexes. We present a supervised learning-based method for predicting protein complexes in protein - protein interaction networks. The method extracts rich features from both the unweighted and weighted networks to train a Regression model, which is then used for the cliques filtering, growth, and candidate complex filtering. The model utilizes additional "uncertainty" samples and, therefore, is more discriminative when used in the complex detection algorithm. In addition, our method uses the maximal cliques found by the Cliques algorithm as the initial cliques, which has been proven to be more effective than the method of expanding from the seeding proteins used in other methods. The experimental results on several PIN datasets show that in most cases the performance of our method are superior to comparable state-of-the-art protein complex detection techniques. The results demonstrate the several advantages of our method over other state-of-the-art techniques. Firstly, our method is a supervised learning-based method that can make full use of the information of the available known complexes instead of being only based on the topological structure of the PIN. That also means, if more training samples are provided, our method can achieve better performance than those unsupervised methods. Secondly, we design the rich feature set to describe the properties of the known complexes, which includes not only the features from the unweighted network, but also those from the weighted network built based on the Gene Ontology information. Thirdly

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

    Science.gov (United States)

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

    2017-08-01

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

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

    DEFF Research Database (Denmark)

    He, Li; Steinocher, Helena; Shelar, Ashish

    2017-01-01

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

  7. Opa-interacting protein 5 modulates docetaxel-induced cell death via regulation of mitophagy in gastric cancer.

    Science.gov (United States)

    Kim, Tae Woo; Lee, Seon-Jin; Park, Young-Jun; Park, Sang Yoon; Oh, Byung Moo; Park, Yun Sun; Kim, Bo-Yeon; Lee, Young-Ha; Cho, Hee Jun; Yoon, Suk Ran; Choe, Yong-Kyung; Lee, Hee Gu

    2017-10-01

    Damage to mitochondria induces mitophagy, a cellular process that is gaining interest for its therapeutic relevance to a variety of human diseases. However, the mechanism underlying mitochondrial depolarization and clearance in mitophagy remains poorly understood. We previously reported that mitochondria-induced cell death was caused by knockdown of Neisseria gonorrhoeae opacity-associated-interacting protein 5 in gastric cancer. In this study, we show that Neisseria gonorrhoeae opacity-associated-interacting protein 5 loss and gain of function modulates mitophagy induced by treatment with docetaxel, a chemotherapy drug for gastric cancer. The activation of mitophagy by Neisseria gonorrhoeae opacity-associated-interacting protein 5 overexpression promoted cell survival, preventing docetaxel-induced mitochondrial clearance. Conversely, short interfering RNA-mediated knockdown of Neisseria gonorrhoeae opacity-associated-interacting protein 5 accelerated docetaxel-induced apoptosis while increasing mitochondrial depolarization, reactive oxygen species, and endoplasmic reticulum stress and decreasing adenosine triphosphate production. We also found that the mitochondrial outer membrane proteins mitofusin 2 and phosphatase and tensin homolog-induced putative kinase 1 colocalized with Neisseria gonorrhoeae opacity-associated-interacting protein 5 in mitochondria and that mitofusin 2 knockdown altered Neisseria gonorrhoeae opacity-associated-interacting protein 5 expression. These findings indicate that Neisseria gonorrhoeae opacity-associated-interacting protein 5 modulates docetaxel-induced mitophagic cell death and therefore suggest that this protein comprises a potential therapeutic target for gastric cancer treatment.

  8. Interaction of Colloidal Gold Nanoparticles with Model Serum Proteins: The Nanoparticle-Protein 'Corona' from a PhysicoChemical Viewpoint

    Science.gov (United States)

    Dominguez Medina, Sergio

    microscopy revealed that under low protein-to-nanoparticle binding ratios, serum albumin irreversibly unfolds upon adsorption and spreads across the available nanoparticle surface area. Unfolded proteins then interact with one another, triggering nanoparticle aggregation. Fibrinogen and globulin also triggered aggregation when exposed to cationic nanoparticles. In an effort to relate these physico-chemical observations to relevant biological parameters, the uptake of protein coated gold nanoparticles by a model cancer cell line was investigated under different incubation conditions. Those nanoparticles pre-incubated with bovine serum albumin before fetal bovine serum were found to be uptaken three times more than those only incubated in serum.

  9. Screening of cellular proteins that interact with the classical swine ...

    Indian Academy of Sciences (India)

    2014-01-27

    Jan 27, 2014 ... tein can induce oxidative stress in the host endothelial cells. (He et al. 2012); however, the exact ..... migration route, and hence they could be influenced by the same growth signal (Chang et al. 2002; Chi .... protein 70 and its relationship to intestine under acute heat stress in broilers: 2. Intestinal oxidative ...

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

    Science.gov (United States)

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

    2017-01-01

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

  11. (S)Pinning down protein interactions by NMR

    DEFF Research Database (Denmark)

    Teilum, Kaare; Kunze, Micha Ben Achim; Erlendsson, Simon

    2017-01-01

    Protein molecules are highly diverse communication platforms and their interaction repertoire stretches from atoms over small molecules such as sugars and lipids to macromolecules. An important route to understanding molecular communication is to quantitatively describe their interactions....... These types of analyses determine the amounts and proportions of individual constituents that participate in a reaction as well as their rates of reactions and their thermodynamics. Although many different methods are available, there is currently no single method able to quantitatively capture and describe...... all types of protein reactions, which can span orders of magnitudes in affinities, reaction rates and lifetimes of states. As the more versatile technique, solution NMR spectroscopy offers a remarkable catalogue of methods that can be successfully applied to the quantitative as well as qualitative...

  12. Protein-Lipid Interactions New Approaches and Emerging Concepts

    CERN Document Server

    Mateo, C. Reyes; Villalaín, José; González-Ros, José M

    2006-01-01

    Biological membranes have long been identified as key elements in a wide variety of cellular processes including cell defense communication, photosynthesis, signal transduction, and motility; thus they emerge as primary targets in both basic and applied research. This book brings together in a single volume the most recent views of experts in the area of protein–lipid interactions, providing an overview of the advances that have been achieved in the field in recent years, from very basic aspects to specialized technological applications. Topics include the application of X-ray and neutron diffraction, infrared and fluorescence spectroscopy, and high-resolution NMR to the understanding of the specific interactions between lipids and proteins within biological membranes, their structural relationships, and the implications for the biological functions that they mediate. Also covered in this volume are the insertion of proteins and peptides into the membrane and the concomitant formation of definite lipid doma...

  13. Controlled Immobilization Strategies to Probe Short Hyaluronan-Protein Interactions

    Science.gov (United States)

    Minsky, Burcu Baykal; Antoni, Christiane H.; Boehm, Heike

    2016-01-01

    Well-controlled grafting of small hyaluronan oligosaccharides (sHA) enables novel approaches to investigate biological processes such as angiogenesis, immune reactions and cancer metastasis. We develop two strategies for covalent attachment of sHA, a fast high-density adsorption and a two-layer system that allows tuning the density and mode of immobilization. We monitored the sHA adlayer formation and subsequent macromolecular interactions by label-free quartz crystal microbalance with dissipation (QCM-D). The modified surfaces are inert to unspecific protein adsorption, and yet retain the specific binding capacity of sHA. Thus they are an ideal tool to study the interactions of hyaluronan-binding proteins and short hyaluronan molecules as demonstrated by the specific recognition of LYVE-1 and aggrecan. Both hyaladherins recognize sHA and the binding is independent to the presence of the reducing end. PMID:26883791

  14. 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

  15. Interaction of Hepatitis C virus proteins with pattern recognition receptors

    Directory of Open Access Journals (Sweden)

    Imran Muhammad

    2012-06-01

    Full Text Available Abstract Hepatitis C virus (HCV is an important human pathogen that causes acute and chronic hepatitis, cirrhosis and hepatocellular carcinoma worldwide. This positive stranded RNA virus is extremely efficient in establishing persistent infection by escaping immune detection or hindering the host immune responses. Recent studies have discovered two important signaling pathways that activate the host innate immunity against viral infection. One of these pathways utilizes members of Toll-like receptor (TLR family and the other uses the RNA helicase retinoic acid inducible gene I (RIG-I as the receptors for intracellular viral double stranded RNA (dsRNA, and activation of transcription factors. In this review article, we summarize the interaction of HCV proteins with various host receptors/sensors through one of these two pathways or both, and how they exploit these interactions to escape from host defense mechanisms. For this purpose, we searched data from Pubmed and Google Scholar. We found that three HCV proteins; Core (C, non structural 3/4 A (NS3/4A and non structural 5A (NS5A have direct interactions with these two pathways. Core protein only in the monomeric form stimulates TLR2 pathway assisting the virus to evade from the innate immune system. NS3/4A disrupts TLR3 and RIG-1 signaling pathways by cleaving Toll/IL-1 receptor domain-containing adapter inducing IFN-beta (TRIF and Cardif, the two important adapter proteins of these signaling cascades respectively, thus halting the defense against HCV. NS5A downmodulates the expressions of NKG2D on natural killer cells (NK cells via TLR4 pathway and impairs the functional ability of these cells. TLRs and RIG-1 pathways have a central role in innate immunity and despite their opposing natures to HCV proteins, when exploited together, HCV as an ever developing virus against host immunity is able to accumulate these mechanisms for near unbeatable survival.

  16. Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Chien-Hung Huang

    2015-01-01

    Full Text Available Many proteins are known to be associated with cancer diseases. It is quite often that their precise functional role in disease pathogenesis remains unclear. A strategy to gain a better understanding of the function of these proteins is to make use of a combination of different aspects of proteomics data types. In this study, we extended Aragues’s method by employing the protein-protein interaction (PPI data, domain-domain interaction (DDI data, weighted domain frequency score (DFS, and cancer linker degree (CLD data to predict cancer proteins. Performances were benchmarked based on three kinds of experiments as follows: (I using individual algorithm, (II combining algorithms, and (III combining the same classification types of algorithms. When compared with Aragues’s method, our proposed methods, that is, machine learning algorithm and voting with the majority, are significantly superior in all seven performance measures. We demonstrated the accuracy of the proposed method on two independent datasets. The best algorithm can achieve a hit ratio of 89.4% and 72.8% for lung cancer dataset and lung cancer microarray study, respectively. It is anticipated that the current research could help understand disease mechanisms and diagnosis.

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

    Science.gov (United States)

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

    2014-01-01

    We present two web-based components for the display of Protein-Protein Interaction networks using different self-organizing layout methods: force-directed and circular. These components conform to the BioJS standard and can be rendered in an HTML5-compliant browser without the need for third-party plugins. We provide examples of interaction networks and how the components can be used to visualize them, and refer to a more complex tool that uses these components. http://github.com/biojs/biojs; http://dx.doi.org/10.5281/zenodo.7753.

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    The dopamine transporter (DAT) plays a key role in regulating dopaminergic signalling in the brain by mediating rapid clearance of dopamine from the synaptic clefts. The psychostimulatory actions of cocaine and amphetamine are primarily the result of a direct interaction of these compounds with DAT...... cells have also recently become available such as fluorescently tagged cocaine analogues and fluorescent substrates. Here we review the current knowledge about the role of protein-protein interactions in DAT regulation as well as we describe the most recent methodological developments that have been...

  19. Protein-Ligand Empirical Interaction Components for Virtual Screening.

    Science.gov (United States)

    Yan, Yuna; Wang, Weijun; Sun, Zhaoxi; Zhang, John Z H; Ji, Changge

    2017-08-28

    A major shortcoming of empirical scoring functions is that they often fail to predict binding affinity properly. Removing false positives of docking results is one of the most challenging works in structure-based virtual screening. Postdocking filters, making use of all kinds of experimental structure and activity information, may help in solving the issue. We describe a new method based on detailed protein-ligand interaction decomposition and machine learning. Protein-ligand empirical interaction components (PLEIC) are used as descriptors for support vector machine learning to develop a classification model (PLEIC-SVM) to discriminate false positives from true positives. Experimentally derived activity information is used for model training. An extensive benchmark study on 36 diverse data sets from the DUD-E database has been performed to evaluate the performance of the new method. The results show that the new method performs much better than standard empirical scoring functions in structure-based virtual screening. The trained PLEIC-SVM model is able to capture important interaction patterns between ligand and protein residues for one specific target, which is helpful in discarding false positives in postdocking filtering.

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

    Science.gov (United States)

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

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

  1. Probing protein-lipid interactions by FRET between membrane fluorophores

    Science.gov (United States)

    Trusova, Valeriya M.; Gorbenko, Galyna P.; Deligeorgiev, Todor; Gadjev, Nikolai

    2016-09-01

    Förster resonance energy transfer (FRET) is a powerful fluorescence technique that has found numerous applications in medicine and biology. One area where FRET proved to be especially informative involves the intermolecular interactions in biological membranes. The present study was focused on developing and verifying a Monte-Carlo approach to analyzing the results of FRET between the membrane-bound fluorophores. This approach was employed to quantify FRET from benzanthrone dye ABM to squaraine dye SQ-1 in the model protein-lipid system containing a polycationic globular protein lysozyme and negatively charged lipid vesicles composed of phosphatidylcholine and phosphatidylglycerol. It was found that acceptor redistribution between the lipid bilayer and protein binding sites resulted in the decrease of FRET efficiency. Quantification of this effect in terms of the proposed methodology yielded both structural and binding parameters of lysozyme-lipid complexes.

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

    Directory of Open Access Journals (Sweden)

    Lynn eRichardson

    2011-06-01

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

  3. Organo-mineral interactions in contrasting soils under natural vegetation

    Directory of Open Access Journals (Sweden)

    Edward eJones

    2014-02-01

    Full Text Available Organo-mineral interactions are important for the cycling and preservation of organic carbon (OC in soils. To understand the role of soil mineral surfaces in organo-mineral interactions, we used a sequential density fractionation procedure to isolate 2.6 g cm-3 density fractions from topsoils (0-10 cm of contrasting mineralogies. These soils were under natural vegetation of four major Australian soil types - Chromosol, Ferrosol, Sodosol and Vertosol. The soils and their organic matter (OM contents were found to be partitioned in four distinct pools: i particulate organic matter 2.6 g cm-3; and iv Fe oxides dominant >2.0 g cm-3 (in the Ferrosol. X-ray photoelectron spectroscopy was used to investigate organic C and N bonding environments associated within each density fraction. Mineral pools were shown to be enriched in distinct organic functional groups: phyllosilicate dominant fractions were enriched with oxidized OC species (C-O, C=O, O-C=O and protonated amide forms; quartz and feldspar dominated fractions were enriched in aliphatic C and protonated amide forms; Fe oxides dominant fractions had the greatest proportions of oxidized OC species and were low in protonated amide forms. The enrichment of different C species was related to the interaction of functional groups with the mineral surfaces. These results demonstrate the potential of mineral surfaces in influencing the chemical composition of OM bound in surfaces reactions and subsequently the stability of OM in organo-mineral interactions.

  4. Network compression as a quality measure for protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Loic Royer

    Full Text Available With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients.

  5. Probability weighted ensemble transfer learning for predicting interactions between HIV-1 and human proteins.

    Directory of Open Access Journals (Sweden)

    Suyu Mei

    Full Text Available Reconstruction of host-pathogen protein interaction networks is of great significance to reveal the underlying microbic pathogenesis. However, the current experimentally-derived networks are generally small and should be augmented by computational methods for less-biased biological inference. From the point of view of computational modelling, data scarcity, data unavailability and negative data sampling are the three major problems for host-pathogen protein interaction networks reconstruction. In this work, we are motivated to address the three concerns and propose a probability weighted ensemble transfer learning model for HIV-human protein interaction prediction (PWEN-TLM, where support vector machine (SVM is adopted as the individual classifier of the ensemble model. In the model, data scarcity and data unavailability are tackled by homolog knowledge transfer. The importance of homolog knowledge is measured by the ROC-AUC metric of the individual classifiers, whose outputs are probability weighted to yield the final decision. In addition, we further validate the assumption that only the homolog knowledge is sufficient to train a satisfactory model for host-pathogen protein interaction prediction. Thus the model is more robust against data unavailability with less demanding data constraint. As regards with negative data construction, experiments show that exclusiveness of subcellular co-localized proteins is unbiased and more reliable than random sampling. Last, we conduct analysis of overlapped predictions between our model and the existing models, and apply the model to novel host-pathogen PPIs recognition for further biological research.

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Changchuan Yin

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

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

    Directory of Open Access Journals (Sweden)

    Straßer Wolfgang

    2006-12-01

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

  9. The thermodynamics of protein interactions with essential first row transition metals.

    Science.gov (United States)

    Bou-Abdallah, Fadi; Giffune, Thomas R

    2016-05-01

    The binding of metal ions to proteins is a crucial process required for their catalytic activity, structural stability and/or functional regulation. Isothermal titration calorimetry provides a wealth of fundamental information which when combined with structural data allow for a much deeper understanding of the underlying molecular mechanism. A rigorous understanding of any molecular interaction requires in part an in-depth quantification of its thermodynamic properties. Here, we provide an overview of recent studies that have used ITC to quantify the interaction of essential first row transition metals with relevant proteins and highlight major findings from these thermodynamic studies. The thermodynamic characterization of metal ion-protein interactions is one important step to understanding the role that metal ions play in living systems. Such characterization has important implications not only to elucidating proteins' structure-function relationships and biological properties but also in the biotechnology sector, medicine and drug design particularly since a number of metal ions are involved in several neurodegenerative diseases. Isothermal titration calorimetry measurements can provide complete thermodynamic profiles of any molecular interaction through the simultaneous determination of the reaction binding stoichiometry, binding affinity as well as the enthalpic and entropic contributions to the free energy change thus enabling a more in-depth understanding of the nature of these interactions. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Applications of hydrophilic interaction chromatography to amino acids, peptides, and proteins.

    Science.gov (United States)

    Periat, Aurélie; Krull, Ira S; Guillarme, Davy

    2015-02-01

    This review summarizes the recent advances in the analysis of amino acids, peptides, and proteins using hydrophilic interaction chromatography. Various reports demonstrate the successful analysis of amino acids under such conditions. However, a baseline resolution of the 20 natural amino acids has not yet been published and for this reason, there is often a need to use mass spectrometry for detection to further improve selectivity. Hydrophilic interaction