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Sample records for protein 7a interacts

  1. ATF-7, a novel bZIP protein, interacts with the PRL-1 protein-tyrosine phosphatase.

    PubMed

    Peters, C S; Liang, X; Li, S; Kannan, S; Peng, Y; Taub, R; Diamond, R H

    2001-04-27

    We have identified a novel basic leucine zipper (bZIP) protein, designated ATF-7, that physically interacts with the PRL-1 protein-tyrosine phosphatase (PTPase). PRL-1 is a predominantly nuclear, farnesylated PTPase that has been linked to the control of cellular growth and differentiation. This interaction was initially found using the yeast two-hybrid system. ATF-7 is most closely related to members of the ATF/CREB family of bZIP proteins, with highest homology to ATF-4. ATF-7 homodimers can bind specifically to CRE elements. ATF-7 is expressed in a number of different tissues and is expressed in association with differentiation in the Caco-2 cell model of intestinal differentiation. We have confirmed the PRL-1.ATF-7 interaction and mapped the regions of ATF-7 and PRL-1 important for interaction to ATF-7's bZIP region and PRL-1's phosphatase domain. Finally, we have determined that PRL-1 is able to dephosphorylate ATF-7 in vitro. Further insight into ATF-7's precise cellular roles, transcriptional function, and downstream targets are likely be of importance in understanding the mechanisms underlying the complex processes of maintenance, differentiation, and turnover of epithelial tissues.

  2. Solution structure and intermolecular interactions of the third metal-binding domain of ATP7A, the Menkes disease protein.

    PubMed

    Banci, Lucia; Bertini, Ivano; Cantini, Francesca; DellaMalva, Nunzia; Herrmann, Torsten; Rosato, Antonio; Wüthrich, Kurt

    2006-09-29

    The third metal-binding domain of the human Menkes protein (MNK3), a copper(I)-transporting ATPase, has been expressed in Escherichia coli and characterized in solution. The solution structure of MNK3, its copper(I)-binding properties, and its interaction with the physiological partner, HAH1, have been studied. MNK3 is the domain most dissimilar in structure from the other domains of the Menkes protein. This is reflected in a significant rearrangement of the last strand of the four-stranded beta-sheet when compared with the other known homologous proteins or protein domains. MNK3 is also peculiar with respect to its interaction with the copper(I) ion, as it was found to be a comparatively weak binder. Copper(I) transfer from metal-loaded HAH1 was observed experimentally, but the metal distribution was shifted toward binding by HAH1. This is at variance with what is observed for the other Menkes domains.

  3. Direct interactions of adaptor protein complexes 1 and 2 with the copper transporter ATP7A mediate its anterograde and retrograde trafficking

    PubMed Central

    Yi, Ling; Kaler, Stephen G.

    2015-01-01

    ATP7A is a P-type ATPase in which diverse mutations lead to X-linked recessive Menkes disease or occipital horn syndrome. Recently, two previously unknown ATP7A missense mutations, T994I and P1386S, were shown to cause an isolated distal motor neuropathy without clinical or biochemical features of other ATP7A disorders. These mutant alleles cause subtle defects in ATP7A intracellular trafficking, resulting in preferential plasma membrane localization compared with wild-type ATP7A. We reported previously that ATP7AP1386S causes unstable insertion of the eighth and final transmembrane segment, preventing proper position of the carboxyl-terminal tail in a proportion of mutant molecules. Here, we utilize this and other naturally occurring and engineered mutant ATP7A alleles to identify mechanisms of normal ATP7A trafficking. We show that adaptor protein (AP) complexes 1 and 2 physically interact with ATP7A and that binding is mediated in part by a carboxyl-terminal di-leucine motif. In contrast to other ATP7A missense mutations, ATP7AP1386S partially disturbs interactions with both APs, leading to abnormal axonal localization in transfected NSC-34 motor neurons and altered calcium-signaling following glutamate stimulation. Our results imply that AP-1 normally tethers ATP7A at the trans-Golgi network in the somatodendritic segments of motor neurons and that alterations affecting the ATP7A carboxyl-terminal tail induce release of the copper transporter to the axons or axonal membranes. The latter effects are intensified by diminished interaction with AP-2, impeding ATP7A retrograde trafficking. Taken together, these findings further illuminate the normal molecular mechanisms of ATP7A trafficking and suggest a pathophysiological basis for ATP7A-related distal motor neuropathy. PMID:25574028

  4. Functional interaction of hepatic nuclear factor-4 and peroxisome proliferator-activated receptor-gamma coactivator 1alpha in CYP7A1 regulation is inhibited by a key lipogenic activator, sterol regulatory element-binding protein-1c.

    PubMed

    Ponugoti, Bhaskar; Fang, Sungsoon; Kemper, Jongsook Kim

    2007-11-01

    Insulin inhibits transcription of cholesterol 7alpha-hydroxylase (Cyp7a1), a key gene in bile acid synthesis, and the hepatic nuclear factor-4 (HNF-4) site in the promoter was identified as a negative insulin response sequence. Using a fasting/feeding protocol in mice and insulin treatment in HepG2 cells, we explored the inhibition mechanisms. Expression of sterol regulatory element-binding protein-1c (SREBP-1c), an insulin-induced lipogenic factor, inversely correlated with Cyp7a1 expression in mouse liver. Interaction of HNF-4 with its coactivator, peroxisome proliferator-activated receptor-gamma coactivator 1alpha (PGC-1alpha), was observed in livers of fasted mice and was reduced after feeding. Conversely, HNF-4 interaction with SREBP-1c was increased after feeding. In vitro studies suggested that SREBP-1c competed with PGC-1alpha for direct interaction with the AF2 domain of HNF-4. Reporter assays showed that SREBP-1c, but not of a SREBP-1c mutant lacking the HNF-4 interacting domain, inhibited HNF-4/PGC-1alpha transactivation of Cyp7a1. SREBP-1c also inhibited PGC-1alpha-coactivation of estrogen receptor, constitutive androstane receptor, pregnane X receptor, and farnesoid X receptor, implying inhibition of HNF-4 by SREBP-1c could extend to other nuclear receptors. In chromatin immunoprecipitation studies, HNF-4 binding to the promoter was not altered, but PGC-1alpha was dissociated, SREBP-1c and histone deacetylase-2 (HDAC2) were recruited, and acetylation of histone H3 was decreased upon feeding. Adenovirus-mediated expression of a SREBP-1c dominant-negative mutant, which blocks the interaction of SREBP-1c and HNF-4, partially but significantly reversed the inhibition of Cyp7a1 after feeding. Our data show that SREBP-1c functions as a non-DNA-binding inhibitor and mediates, in part, suppression of Cyp7a1 by blocking functional interaction of HNF-4 and PGC-1alpha. This mechanism may be relevant to known repression of many other HNF-4 target genes upon

  5. PIC: Protein Interactions Calculator

    PubMed Central

    Tina, K. G.; Bhadra, R.; Srinivasan, N.

    2007-01-01

    Interactions within a protein structure and interactions between proteins in an assembly are essential considerations in understanding molecular basis of stability and functions of proteins and their complexes. There are several weak and strong interactions that render stability to a protein structure or an assembly. Protein Interactions Calculator (PIC) is a server which, given the coordinate set of 3D structure of a protein or an assembly, computes various interactions such as disulphide bonds, interactions between hydrophobic residues, ionic interactions, hydrogen bonds, aromatic–aromatic interactions, aromatic–sulphur interactions and cation–π interactions within a protein or between proteins in a complex. Interactions are calculated on the basis of standard, published criteria. The identified interactions between residues can be visualized using a RasMol and Jmol interface. The advantage with PIC server is the easy availability of inter-residue interaction calculations in a single site. It also determines the accessible surface area and residue-depth, which is the distance of a residue from the surface of the protein. User can also recognize specific kind of interactions, such as apolar–apolar residue interactions or ionic interactions, that are formed between buried or exposed residues or near the surface or deep inside. PMID:17584791

  6. PIC: Protein Interactions Calculator.

    PubMed

    Tina, K G; Bhadra, R; Srinivasan, N

    2007-07-01

    Interactions within a protein structure and interactions between proteins in an assembly are essential considerations in understanding molecular basis of stability and functions of proteins and their complexes. There are several weak and strong interactions that render stability to a protein structure or an assembly. Protein Interactions Calculator (PIC) is a server which, given the coordinate set of 3D structure of a protein or an assembly, computes various interactions such as disulphide bonds, interactions between hydrophobic residues, ionic interactions, hydrogen bonds, aromatic-aromatic interactions, aromatic-sulphur interactions and cation-pi interactions within a protein or between proteins in a complex. Interactions are calculated on the basis of standard, published criteria. The identified interactions between residues can be visualized using a RasMol and Jmol interface. The advantage with PIC server is the easy availability of inter-residue interaction calculations in a single site. It also determines the accessible surface area and residue-depth, which is the distance of a residue from the surface of the protein. User can also recognize specific kind of interactions, such as apolar-apolar residue interactions or ionic interactions, that are formed between buried or exposed residues or near the surface or deep inside.

  7. Interactive protein manipulation

    SciTech Connect

    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.

  8. Drugging Membrane Protein Interactions

    PubMed Central

    Yin, Hang; Flynn, Aaron D.

    2016-01-01

    The majority of therapeutics target membrane proteins, accessible on the surface of cells, to alter cellular signaling. Cells use membrane proteins to transduce signals into cells, transport ions and molecules, bind the cell to a surface or substrate, and catalyze reactions. Newly devised technologies allow us to drug conventionally “undruggable” regions of membrane proteins, enabling modulation of protein–protein, protein–lipid, and protein–nucleic acid interactions. In this review, we survey the state of the art in high-throughput screening and rational design in drug discovery, and we evaluate the advances in biological understanding and technological capacity that will drive pharmacotherapy forward against unorthodox membrane protein targets. PMID:26863923

  9. INTERACT: an object oriented protein-protein interaction database.

    PubMed

    Eilbeck, K; Brass, A; Paton, N; Hodgman, C

    1999-01-01

    Protein-protein interactions provide vital information concerning the function of proteins, complexes and networks. Currently there is no widely accepted repository of this interaction information. Our aim is to provide a single database with the necessary architecture to fully store, query and analyse interaction data. An object oriented database has been created which provides scientists with a resource for examining existing protein-protein interactions and inferring possible interactions from the data stored. It also provides a basis for examining networks of interacting proteins, via analysis of the data stored. The database contains over a thousand interactions. k.eilbeck@stud.man.ac.uk

  10. Cotton and Protein Interactions

    SciTech Connect

    Goheen, Steven C.; Edwards, J. V.; Rayburn, Alfred R.; Gaither, Kari A.; Castro, Nathan J.

    2006-06-30

    The adsorbent properties of important wound fluid proteins and cotton cellulose are reviewed. This review focuses on the adsorption of albumin to cotton-based wound dressings and some chemically modified derivatives targeted for chronic wounds. Adsorption of elastase in the presence of albumin was examined as a model to understand the interactive properties of these wound fluid components with cotton fibers. In the chronic non-healing wound, elastase appears to be over-expressed, and it digests tissue and growth factors, interfering with the normal healing process. Albumin is the most prevalent protein in wound fluid, and in highly to moderately exudative wounds, it may bind significantly to the fibers of wound dressings. Thus, the relative binding properties of both elastase and albumin to wound dressing fibers are of interest in the design of more effective wound dressings. The present work examines the binding of albumin to two different derivatives of cotton, and quantifies the elastase binding to the same derivatives following exposure of albumin to the fiber surface. An HPLC adsorption technique was employed coupled with a colorimetric enzyme assay to quantify the relative binding properties of albumin and elastase to cotton. The results of wound protein binding are discussed in relation to the porosity and surface chemistry interactions of cotton and wound proteins. Studies are directed to understanding the implications of protein adsorption phenomena in terms of fiber-protein models that have implications for rationally designing dressings for chronic wounds.

  11. Tracking protein aggregate interactions

    PubMed Central

    Bartz, Jason C; Nilsson, K Peter R

    2011-01-01

    Amyloid fibrils share a structural motif consisting of highly ordered β-sheets aligned perpendicular to the fibril axis.1, 2 At each fibril end, β-sheets provide a template for recruiting and converting monomers.3 Different amyloid fibrils often co-occur in the same individual, yet whether a protein aggregate aids or inhibits the assembly of a heterologous protein is unclear. In prion disease, diverse prion aggregate structures, known as strains, are thought to be the basis of disparate disease phenotypes in the same species expressing identical prion protein sequences.4–7 Here we explore the interactions reported to occur when two distinct prion strains occur together in the central nervous system. PMID:21597336

  12. Carotenoid-Protein Interactions

    NASA Astrophysics Data System (ADS)

    Britton, George; Helliwell, John R.

    Chapter 5 shows that the aggregation of carotenoid molecules can have a profound effect on their properties and hence their functioning in biological systems. Another important influence is the interaction between carotenoids and other molecules. The way that interactions of carotenoids with lipid bilayers influence the structure and properties of membranes and membrane-asociated processes is discussed in Chapter 10, and the aggregation of carotenoid molecules within the bilayers in Chapter 5. Of particular importance, though, are interactions between carotenoids and proteins. These allow the hydrophobic carotenoids to be transported, to exist, and to function in an aqueous environment. In some cases they may modify strongly the light-absorption properties and hence the colour and photochemistry of the carotenoids.

  13. Interaction entropy for protein-protein binding

    NASA Astrophysics Data System (ADS)

    Sun, Zhaoxi; Yan, Yu N.; Yang, Maoyou; Zhang, John Z. H.

    2017-03-01

    Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interaction entropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interaction entropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.

  14. Length, protein protein interactions, and complexity

    NASA Astrophysics Data System (ADS)

    Tan, Taison; Frenkel, Daan; Gupta, Vishal; Deem, Michael W.

    2005-05-01

    The evolutionary reason for the increase in gene length from archaea to prokaryotes to eukaryotes observed in large-scale genome sequencing efforts has been unclear. We propose here that the increasing complexity of protein-protein interactions has driven the selection of longer proteins, as they are more able to distinguish among a larger number of distinct interactions due to their greater average surface area. Annotated protein sequences available from the SWISS-PROT database were analyzed for 13 eukaryotes, eight bacteria, and two archaea species. The number of subcellular locations to which each protein is associated is used as a measure of the number of interactions to which a protein participates. Two databases of yeast protein-protein interactions were used as another measure of the number of interactions to which each S. cerevisiae protein participates. Protein length is shown to correlate with both number of subcellular locations to which a protein is associated and number of interactions as measured by yeast two-hybrid experiments. Protein length is also shown to correlate with the probability that the protein is encoded by an essential gene. Interestingly, average protein length and number of subcellular locations are not significantly different between all human proteins and protein targets of known, marketed drugs. Increased protein length appears to be a significant mechanism by which the increasing complexity of protein-protein interaction networks is accommodated within the natural evolution of species. Consideration of protein length may be a valuable tool in drug design, one that predicts different strategies for inhibiting interactions in aberrant and normal pathways.

  15. PREFACE: Protein protein interactions: principles and predictions

    NASA Astrophysics Data System (ADS)

    Nussinov, Ruth; Tsai, Chung-Jung

    2005-06-01

    Proteins are the `workhorses' of the cell. Their roles span functions as diverse as being molecular machines and signalling. They carry out catalytic reactions, transport, form viral capsids, traverse membranes and form regulated channels, transmit information from DNA to RNA, making possible the synthesis of new proteins, and they are responsible for the degradation of unnecessary proteins and nucleic acids. They are the vehicles of the immune response and are responsible for viral entry into the cell. Given their importance, considerable effort has been centered on the prediction of protein function. A prime way to do this is through identification of binding partners. If the function of at least one of the components with which the protein interacts is known, that should let us assign its function(s) and the pathway(s) in which it plays a role. This holds since the vast majority of their chores in the living cell involve protein-protein interactions. Hence, through the intricate network of these interactions we can map cellular pathways, their interconnectivities and their dynamic regulation. Their identification is at the heart of functional genomics; their prediction is crucial for drug discovery. Knowledge of the pathway, its topology, length, and dynamics may provide useful information for forecasting side effects. The goal of predicting protein-protein interactions is daunting. Some associations are obligatory, others are continuously forming and dissociating. In principle, from the physical standpoint, any two proteins can interact, but under what conditions and at which strength? The principles of protein-protein interactions are general: the non-covalent interactions of two proteins are largely the outcome of the hydrophobic effect, which drives the interactions. In addition, hydrogen bonds and electrostatic interactions play important roles. Thus, many of the interactions observed in vitro are the outcome of experimental overexpression. Protein disorder

  16. Discovering interacting domains and motifs in protein-protein interactions.

    PubMed

    Hugo, Willy; Sung, Wing-Kin; Ng, See-Kiong

    2013-01-01

    Many important biological processes, such as the signaling pathways, require protein-protein interactions (PPIs) that are designed for fast response to stimuli. These interactions are usually transient, easily formed, and disrupted, yet specific. Many of these transient interactions involve the binding of a protein domain to a short stretch (3-10) of amino acid residues, which can be characterized by a sequence pattern, i.e., a short linear motif (SLiM). We call these interacting domains and motifs domain-SLiM interactions. Existing methods have focused on discovering SLiMs in the interacting proteins' sequence data. With the recent increase in protein structures, we have a new opportunity to detect SLiMs directly from the proteins' 3D structures instead of their linear sequences. In this chapter, we describe a computational method called SLiMDIet to directly detect SLiMs on domain interfaces extracted from 3D structures of PPIs. SLiMDIet comprises two steps: (1) interaction interfaces belonging to the same domain are extracted and grouped together using structural clustering and (2) the extracted interaction interfaces in each cluster are structurally aligned to extract the corresponding SLiM. Using SLiMDIet, de novo SLiMs interacting with protein domains can be computationally detected from structurally clustered domain-SLiM interactions for PFAM domains which have available 3D structures in the PDB database.

  17. Detecting protein-protein interactions using Renilla luciferase fusion proteins.

    PubMed

    Burbelo, Peter D; Kisailus, Adam E; Peck, Jeremy W

    2002-11-01

    We have developed a novel system designated the luciferase assay for protein detection (LAPD) to study protein-protein interactions. This method involves two protein fusions, a soluble reporter fusion and a fusion for immobilizing the target protein. The soluble reporter is an N-terminal Renilla luciferase fusion protein that exhibits high Renilla luciferase activity. Crude cleared lysates from transfected Cos1 cells that express the Renilla luciferase fusion protein can be used in binding assays with immobilized target proteins. Following incubation and washing, target-bound Renilla luciferase fusion proteins produce light from the coelenterazine substrate, indicating an interaction between the two proteins of interest. As proof of the principle, we reproduced known, transient protein-protein interactions between the Cdc42 GTPase and its effector proteins. GTPase Renilla fusion proteins produced in Cos1 cells were tested with immobilized recombinant GST-N-WASP and CEP5 effector proteins. Using this assay, we could detect specific interactions of Cdc42 with these effector proteins in approximately 50 min. The specificity of these interactions was demonstrated by showing that they were GTPase-specific and GTP-dependent and not seen with other unrelated target proteins. These results suggest that the LAPD method, which is both rapid and sensitive, may have research and practical applications.

  18. Protein ligand interaction database (PLID).

    PubMed

    Reddy, A Srinivas; Amarnath, H S Durga; Bapi, Raju S; Sastry, G Madhavi; Sastry, G Narahari

    2008-10-01

    A comprehensive database named, protein ligand interaction database (PLID), is created with 6295 ligands bound to proteins extracted from the protein data bank (PDB). This is by far the most comprehensive database of physico-chemical properties, quantum mechanical descriptors and the residues present in the active site of proteins. It is a publicly available web-based database (via the Internet) at http://203.199.182.73/gnsmmg/databases/plid/.

  19. Protopia: a protein-protein interaction tool

    PubMed Central

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

    2009-01-01

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

  20. Aeolotopic interactions of globular proteins

    PubMed Central

    Lomakin, Aleksey; Asherie, Neer; Benedek, George B.

    1999-01-01

    Protein crystallization, aggregation, liquid–liquid phase separation, and self-assembly are important in protein structure determination in the industrial processing of proteins and in the inhibition of protein condensation diseases. To fully describe such phase transformations in globular protein solutions, it is necessary to account for the strong spatial variation of the interactions on the protein surface. One difficulty is that each globular protein has its own unique surface, which is crucial for its biological function. However, the similarities amongst the macroscopic properties of different protein solutions suggest that there may exist a generic model that is capable of describing the nonuniform interactions between globular proteins. In this paper we present such a model, which includes the short-range interactions that vary from place to place on the surface of the protein. We show that this aeolotopic model [from the Greek aiolos (“variable”) and topos (“place”)] describes the phase diagram of globular proteins and provides insight into protein aggregation and crystallization. PMID:10449715

  1. Protein-protein interactions in multienzyme megasynthetases.

    PubMed

    Weissman, Kira J; Müller, Rolf

    2008-04-14

    The multienzyme polyketide synthases (PKSs), nonribosomal polypeptide synthetases (NRPSs), and their hybrids are responsible for the construction in bacteria of numerous natural products of clinical value. These systems generate high structural complexity by using a simple biosynthetic logic--that of the assembly line. Each of the individual steps in building the metabolites is designated to an independently folded domain within gigantic polypeptides. The domains are clustered into functional modules, and the modules are strung out along the proteins in the order in which they act. Every metabolite results, therefore, from the successive action of up to 100 individual catalysts. Despite the conceptual simplicity of this division-of-labor organization, we are only beginning to decipher the molecular details of the numerous protein-protein interactions that support assembly-line biosynthesis, and which are critical to attempts to re-engineer these systems as a tool in drug discovery. This review aims to summarize the state of knowledge about several aspects of protein-protein interactions, including current architectural models for PKS and NRPS systems, the central role of carrier proteins, and the structural basis for intersubunit recognition.

  2. Protein-protein interactions as drug targets.

    PubMed

    Skwarczynska, Malgorzata; Ottmann, Christian

    2015-01-01

    Modulation of protein-protein interactions (PPIs) is becoming increasingly important in drug discovery and chemical biology. While a few years ago this 'target class' was deemed to be largely undruggable an impressing number of publications and success stories now show that targeting PPIs with small, drug-like molecules indeed is a feasible approach. Here, we summarize the current state of small-molecule inhibition and stabilization of PPIs and review the active molecules from a structural and medicinal chemistry angle, especially focusing on the key examples of iNOS, LFA-1 and 14-3-3.

  3. Structure and intracellular targeting of the SARS-coronavirus Orf7a accessory protein.

    PubMed

    Nelson, Christopher A; Pekosz, Andrew; Lee, Chung A; Diamond, Michael S; Fremont, Daved H

    2005-01-01

    The open reading frame (ORF) 7a of the SARS-associated coronavirus (SARS-CoV) encodes a unique type I transmembrane protein of unknown function. We have determined the 1.8 A resolution crystal structure of the N-terminal ectodomain of orf7a, revealing a compact seven-stranded beta sandwich unexpectedly similar in fold and topology to members of the Ig superfamily. We also demonstrate that, in SARS-CoV- infected cells, the orf7a protein is expressed and retained intracellularly. Confocal microscopy studies using orf7a and orf7a/CD4 chimeras implicate the short cytoplasmic tail and transmembrane domain in trafficking of the protein within the endoplasmic reticulum and Golgi network. Taken together, our findings provide a structural and cellular framework in which to explore the role of orf7a in SARS-CoV pathogenesis.

  4. New Compound Classes: Protein-Protein Interactions.

    PubMed

    Ottmann, C

    2016-01-01

    "Protein-protein interactions (PPIs) are one of the most promising new targets in drug discovery. With estimates between 300,000 and 650,000 in human physiology, targeted modulation of PPIs would tremendously extend the "druggable" genome. In fact, in every disease a wealth of potentially addressable PPIs can be found making pharmacological intervention based on PPI modulators in principle a generally applicable technology. An impressing number of success stories in small-molecule PPI inhibition and natural-product PPI stabilization increasingly encourage academia and industry to invest in PPI modulation. In this chapter examples of both inhibition as well as stabilization of PPIs are reviewed including some of the technologies which has been used for their identification."

  5. Direct Probing of Protein-Protein Interactions

    SciTech Connect

    Noy, A; Sulchek, T A; Friddle, R W

    2005-03-10

    This project aimed to establish feasibility of using experimental techniques based on direct measurements of interaction forces on the single molecule scale to characterize equilibrium interaction potentials between individual biological molecules. Such capability will impact several research areas, ranging from rapid interaction screening capabilities to providing verifiable inputs for computational models. It should be one of the enabling technologies for modern proteomics research. This study used a combination of Monte-Carlo simulations, theoretical considerations, and direct experimental measurements to investigate two model systems that represented typical experimental situations: force-induced melting of DNA rigidly attached to the tip, and force-induced unbinding of a protein-antibody pair connected to flexible tethers. Our results establish that for both systems researchers can use force spectroscopy measurements to extract reliable information about equilibrium interaction potentials. However, the approaches necessary to extract these potentials in each case--Jarzynski reconstruction and Dynamic Force Spectroscopy--are very different. We also show how the thermodynamics and kinetics of unbinding process dictates the choice between in each case.

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

    DOEpatents

    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.

  7. Hydrodynamic interactions in protein folding

    NASA Astrophysics Data System (ADS)

    Cieplak, Marek; Niewieczerzał, Szymon

    2009-03-01

    We incorporate hydrodynamic interactions (HIs) in a coarse-grained and structure-based model of proteins by employing the Rotne-Prager hydrodynamic tensor. We study several small proteins and demonstrate that HIs facilitate folding. We also study HIV-1 protease and show that HIs make the flap closing dynamics faster. The HIs are found to affect time correlation functions in the vicinity of the native state even though they have no impact on same time characteristics of the structure fluctuations around the native state.

  8. Molecular modelling of protein-protein/protein-solvent interactions

    NASA Astrophysics Data System (ADS)

    Luchko, Tyler

    The inner workings of individual cells are based on intricate networks of protein-protein interactions. However, each of these individual protein interactions requires a complex physical interaction between proteins and their aqueous environment at the atomic scale. In this thesis, molecular dynamics simulations are used in three theoretical studies to gain insight at the atomic scale about protein hydration, protein structure and tubulin-tubulin (protein-protein) interactions, as found in microtubules. Also presented, in a fourth project, is a molecular model of solvation coupled with the Amber molecular modelling package, to facilitate further studies without the need of explicitly modelled water. Basic properties of a minimally solvated protein were calculated through an extended study of myoglobin hydration with explicit solvent, directly investigating water and protein polarization. Results indicate a close correlation between polarization of both water and protein and the onset of protein function. The methodology of explicit solvent molecular dynamics was further used to study tubulin and microtubules. Extensive conformational sampling of the carboxy-terminal tails of 8-tubulin was performed via replica exchange molecular dynamics, allowing the characterisation of the flexibility, secondary structure and binding domains of the C-terminal tails through statistical analysis methods. Mechanical properties of tubulin and microtubules were calculated with adaptive biasing force molecular dynamics. The function of the M-loop in microtubule stability was demonstrated in these simulations. The flexibility of this loop allowed constant contacts between the protofilaments to be maintained during simulations while the smooth deformation provided a spring-like restoring force. Additionally, calculating the free energy profile between the straight and bent tubulin configurations was used to test the proposed conformational change in tubulin, thought to cause microtubule

  9. Probing protein-sugar interactions.

    PubMed

    Ebel, C; Eisenberg, H; Ghirlando, R

    2000-01-01

    We have investigated the partial specific volumes (2) (ml/g), hydration, and cosolvent interactions of rabbit muscle aldolase by equilibrium sedimentation in the analytical ultracentrifuge and by direct density increment (partial differential/partial differentialc(2))(mu) measurements over a range of sugar concentrations and temperature. In a series of sugars increasing in size, glucose, sucrose, raffinose, and alpha-cyclodextrin, (partial differential/ partial differentialc(2))(mu) decreases linearly with the solvent density rho(0). These sugar cosolvents do not interact with the protein; however, the interaction parameter B(1) (g water/g protein) mildly increases with increasing sugar size. The experimental B(1) values are smaller than values calculated by excluded volume (rolling ball) considerations. B(1) relates to hydration in this and in other instances studied. It decreases with increasing temperature, leading to an increase in (2) due to reduced water of hydration electrostriction. The density increments (partial differential/ partial differentialc(2))(mu), however, decrease in concave up form in the case of glycerol and in concave down form for trehalose, leading to more complex behavior in the case of carbohydrates playing a biological role as osmolytes and antifreeze agents. A critical discussion, based on the thermodynamics of multicomponent solutions, is presented.

  10. Probing protein-sugar interactions.

    PubMed Central

    Ebel, C; Eisenberg, H; Ghirlando, R

    2000-01-01

    We have investigated the partial specific volumes (2) (ml/g), hydration, and cosolvent interactions of rabbit muscle aldolase by equilibrium sedimentation in the analytical ultracentrifuge and by direct density increment (partial differential/partial differentialc(2))(mu) measurements over a range of sugar concentrations and temperature. In a series of sugars increasing in size, glucose, sucrose, raffinose, and alpha-cyclodextrin, (partial differential/ partial differentialc(2))(mu) decreases linearly with the solvent density rho(0). These sugar cosolvents do not interact with the protein; however, the interaction parameter B(1) (g water/g protein) mildly increases with increasing sugar size. The experimental B(1) values are smaller than values calculated by excluded volume (rolling ball) considerations. B(1) relates to hydration in this and in other instances studied. It decreases with increasing temperature, leading to an increase in (2) due to reduced water of hydration electrostriction. The density increments (partial differential/ partial differentialc(2))(mu), however, decrease in concave up form in the case of glycerol and in concave down form for trehalose, leading to more complex behavior in the case of carbohydrates playing a biological role as osmolytes and antifreeze agents. A critical discussion, based on the thermodynamics of multicomponent solutions, is presented. PMID:10620302

  11. PRISM: protein interactions by structural matching.

    PubMed

    Ogmen, Utkan; Keskin, Ozlem; Aytuna, A Selim; Nussinov, Ruth; Gursoy, Attila

    2005-07-01

    Prism (http://gordion.hpc.eng.ku.edu.tr/prism) is a website for protein interface analysis and prediction of putative protein-protein interactions. It is composed of a database holding protein interface structures derived from the Protein Data Bank (PDB). The server also includes summary information about related proteins and an interactive protein interface viewer. A list of putative protein-protein interactions obtained by running our prediction algorithm can also be accessed. These results are applied to a set of protein structures obtained from the PDB at the time of algorithm execution (January 2004). Users can browse through the non-redundant dataset of representative interfaces on which the prediction algorithm depends, retrieve the list of similar structures to these interfaces or see the results of interaction predictions for a particular protein. Another service provided is interactive prediction. This is done by running the algorithm for user input structures.

  12. Evolutionary reprograming of protein-protein interaction specificity.

    PubMed

    Akiva, Eyal; Babbitt, Patricia C

    2015-10-22

    Using mutation libraries and deep sequencing, Aakre et al. study the evolution of protein-protein interactions using a toxin-antitoxin model. The results indicate probable trajectories via "intermediate" proteins that are promiscuous, thus avoiding transitions via non-interactions. These results extend observations about other biological interactions and enzyme evolution, suggesting broadly general principles.

  13. Copper transport during lactation in transgenic mice expressing the human ATP7A protein

    PubMed Central

    Llanos, Roxana M.; Michalczyk, Agnes A.; Freestone, David J.; Currie, Scott; Linder, Maria C.; Ackland, M. Leigh; Mercer, Julian F.B.

    2008-01-01

    Both copper transporting ATPases, ATP7A and ATP7B, are expressed in mammary epithelial cells but their role in copper delivery to milk has not been clarified. We investigated the role of ATP7A in delivery of copper to milk using transgenic mice that over-express human ATP7A. In mammary gland of transgenic mice, human ATP7A protein was 10- to 20-fold higher than in control mice, and was localized to the basolateral membrane of mammary epithelial cells in lactating mice. The copper concentration in the mammary gland of transgenic dams and stomach contents of transgenic pups was significantly reduced compared to non-transgenic mice. The mRNA levels of endogenous Atp7a, Atp7b, and Ctr1 copper transporters in the mammary gland were not altered by the expression of the ATP7A transgene, and the protein levels of Atp7b and ceruloplasmin were similar in transgenic and non-transgenic mice. These data suggest that ATP7A plays a role in removing excess copper from the mammary epithelial cells rather than supplying copper to milk. PMID:18515074

  14. Protein-Inhibitor Interaction Studies Using NMR

    PubMed Central

    Ishima, Rieko

    2015-01-01

    Solution-state NMR has been widely applied to determine the three-dimensional structure, dynamics, and molecular interactions of proteins. The designs of experiments used in protein NMR differ from those used for small-molecule NMR, primarily because the information available prior to an experiment, such as molecular mass and knowledge of the primary structure, is unique for proteins compared to small molecules. In this review article, protein NMR for structural biology is introduced with comparisons to small-molecule NMR, such as descriptions of labeling strategies and the effects of molecular dynamics on relaxation. Next, applications for protein NMR are reviewed, especially practical aspects for protein-observed ligand-protein interaction studies. Overall, the following topics are described: (1) characteristics of protein NMR, (2) methods to detect protein-ligand interactions by NMR, and (3) practical aspects of carrying out protein-observed inhibitor-protein interaction studies. PMID:26361636

  15. Hox protein interactions: screening and network building.

    PubMed

    Bergiers, Isabelle; Lambert, Barbara; Daakour, Sarah; Twizere, Jean-Claude; Rezsohazy, René

    2014-01-01

    Understanding the mode of action of Hox proteins requires the identification of molecular and cellular pathways they take part in. This includes to characterize the networks of protein-protein interactions involving Hox proteins. In this chapter we propose a strategy and methods to map Hox interaction networks, from yeast two-hybrid and high-throughput yeast two-hybrid interaction screening to bioinformatic analyses based on the software platform Cytoscape.

  16. Coevolution of gene expression among interacting proteins

    SciTech Connect

    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.

  17. Small molecules that target phosphorylation dependent protein-protein interaction.

    PubMed

    Watanabe, Nobumoto; Osada, Hiroyuki

    2016-08-01

    Protein-protein interaction is one of the key events in the signal transduction pathway. The interaction changes the conformations, activities, localization and stabilities of the proteins, and transduces the signal to the next step. Frequently, this interaction occurs upon the protein phosphorylation. When upstream signals are stimulated, protein kinase(s) is/are activated and phosphorylate(s) their substrates, and induce the phosphorylation dependent protein-protein interaction. For this interaction, several domains in proteins are known to specifically recognize the phosphorylated residues of target proteins. These specific domains for interaction are important in the progression of the diseases caused by disordered signal transduction such as cancer. Thus small molecules that modulate this interaction are attractive lead compounds for the treatment of such diseases. In this review, we focused on three examples of phosphorylation dependent protein-protein interaction modules (14-3-3, polo box domain of Plk1 and F-box proteins in SCF ubiquitin ligases) and summarize small molecules that modulate their interaction. We also introduce our original screening system to identify such small molecules. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Do cancer proteins really interact strongly in the human protein-protein interaction network?

    PubMed

    Xia, Junfeng; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

    2011-06-01

    Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. © 2011 Elsevier Ltd. All rights reserved.

  19. PSAIA – Protein Structure and Interaction Analyzer

    PubMed Central

    Mihel, Josip; Šikić, Mile; Tomić, Sanja; Jeren, Branko; Vlahoviček, Kristian

    2008-01-01

    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. PMID:18400099

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

    PubMed

    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.

  1. Protein-protein interactions in the synaptonemal complex.

    PubMed Central

    Tarsounas, M; Pearlman, R E; Gasser, P J; Park, M S; Moens, P B

    1997-01-01

    In mammalian systems, an approximately M(r) 30,000 Cor1 protein has been identified as a major component of the meiotic prophase chromosome cores, and a M(r) 125,000 Syn1 protein is present between homologue cores where they are synapsed and form the synaptonemal complex (SC). Immunolocalization of these proteins during meiosis suggests possible homo- and heterotypic interactions between the two as well as possible interactions with yet unrecognized proteins. We used the two-hybrid system in the yeast Saccharomyces cerevisiae to detect possible protein-protein associations. Segments of hamsters Cor1 and Syn1 proteins were tested in various combinations for homo- and heterotypic interactions. In the cause of Cor1, homotypic interactions involve regions capable of coiled-coil formation, observation confirmed by in vitro affinity coprecipitation experiments. The two-hybrid assay detects no interaction of Cor1 protein with central and C-terminal fragments of Syn1 protein and no homotypic interactions involving these fragments of Syn1. Hamster Cor1 and Syn1 proteins both associate with the human ubiquitin-conjugation enzyme Hsubc9 as well as with the hamster Ubc9 homologue. The interactions between SC proteins and the Ubc9 protein may be significant for SC disassembly, which coincides with the repulsion of homologs by late prophase I, and also for the termination of sister centromere cohesiveness at anaphase II. Images PMID:9285814

  2. A chimera carrying the functional domain of the orphan protein SLC7A14 in the backbone of SLC7A2 mediates trans-stimulated arginine transport.

    PubMed

    Jaenecke, Isabel; Boissel, Jean-Paul; Lemke, Matthias; Rupp, Johanna; Gasnier, Bruno; Closs, Ellen I

    2012-08-31

    In human skin fibroblasts, a lysosomal transport system specific for cationic amino acids has been described and named system c. We asked if SLC7A14 (solute carrier family 7 member A14), an orphan protein assigned to the SLC7 subfamily of cationic amino acid transporters (CATs) due to sequence homology, may represent system c. Fusion proteins between SLC7A14 and enhanced GFP localized to intracellular vesicles, co-staining with the lysosomal marker LysoTracker(®). To perform transport studies, we first tried to redirect SLC7A14 to the plasma membrane (by mutating putative lysosomal targeting motifs) but without success. We then created a chimera carrying the backbone of human (h) CAT-2 and the protein domain of SLC7A14 corresponding to the so-called "functional domain" of the hCAT proteins, a protein stretch of 81 amino acids that determines the apparent substrate affinity, sensitivity to trans-stimulation, and (as revealed in this study) pH dependence. The chimera mediated arginine transport and exhibited characteristics similar but not identical to hCAT-2A (the low affinity hCAT-2 isoform). Western blot and microscopic analyses confirmed localization of the chimera in the plasma membrane of Xenopus laevis oocytes. Noticeably, arginine transport by the hCAT-2/SLC7A14 chimera was pH-dependent, trans-stimulated, and inhibited by α-trimethyl-L-lysine, properties assigned to lysosomal transport system c in human skin fibroblasts. Expression analysis showed strong expression of SLC7A14 mRNA in these cells. Taken together, these data strongly suggest that SLC7A14 is a lysosomal transporter for cationic amino acids.

  3. Protein Synthesis--An Interactive Game.

    ERIC Educational Resources Information Center

    Clements, Lee Ann J.; Jackson, Karen E.

    1998-01-01

    Describes an interactive game designed to help students see and understand the dynamic relationship between DNA, RNA, and proteins. Appropriate for either a class or laboratory setting, following a lecture session about protein synthesis. (DDR)

  4. Protein Synthesis--An Interactive Game.

    ERIC Educational Resources Information Center

    Clements, Lee Ann J.; Jackson, Karen E.

    1998-01-01

    Describes an interactive game designed to help students see and understand the dynamic relationship between DNA, RNA, and proteins. Appropriate for either a class or laboratory setting, following a lecture session about protein synthesis. (DDR)

  5. Prediction of protein-protein interactions: unifying evolution and structure at protein interfaces.

    PubMed

    Tuncbag, Nurcan; Gursoy, Attila; Keskin, Ozlem

    2011-06-01

    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.

  6. Prediction of protein-protein interactions: unifying evolution and structure at protein interfaces

    NASA Astrophysics Data System (ADS)

    Tuncbag, Nurcan; Gursoy, Attila; Keskin, Ozlem

    2011-06-01

    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.

  7. Protein-Protein Interactions in Virus-Host Systems.

    PubMed

    Brito, Anderson F; Pinney, John W

    2017-01-01

    To study virus-host protein interactions, knowledge about viral and host protein architectures and repertoires, their particular evolutionary mechanisms, and information on relevant sources of biological data is essential. The purpose of this review article is to provide a thorough overview about these aspects. Protein domains are basic units defining protein interactions, and the uniqueness of viral domain repertoires, their mode of evolution, and their roles during viral infection make viruses interesting models of study. Mutations at protein interfaces can reduce or increase their binding affinities by changing protein electrostatics and structural properties. During the course of a viral infection, both pathogen and cellular proteins are constantly competing for binding partners. Endogenous interfaces mediating intraspecific interactions-viral-viral or host-host interactions-are constantly targeted and inhibited by exogenous interfaces mediating viral-host interactions. From a biomedical perspective, blocking such interactions is the main mechanism underlying antiviral therapies. Some proteins are able to bind multiple partners, and their modes of interaction define how fast these "hub proteins" evolve. "Party hubs" have multiple interfaces; they establish simultaneous/stable (domain-domain) interactions, and tend to evolve slowly. On the other hand, "date hubs" have few interfaces; they establish transient/weak (domain-motif) interactions by means of short linear peptides (15 or fewer residues), and can evolve faster. Viral infections are mediated by several protein-protein interactions (PPIs), which can be represented as networks (protein interaction networks, PINs), with proteins being depicted as nodes, and their interactions as edges. It has been suggested that viral proteins tend to establish interactions with more central and highly connected host proteins. In an evolutionary arms race, viral and host proteins are constantly changing their interface

  8. Protein interactions in human genetic diseases

    PubMed Central

    Schuster-Böckler, Benjamin; Bateman, Alex

    2008-01-01

    We present a novel method that combines protein structure information with protein interaction data to identify residues that form part of an interaction interface. Our prediction method can retrieve interaction hotspots with an accuracy of 60% (at a 20% false positive rate). The method was applied to all mutations in the Online Mendelian Inheritance in Man (OMIM) database, predicting 1,428 mutations to be related to an interaction defect. Combining predicted and hand-curated sets, we discuss how mutations affect protein interactions in general. PMID:18199329

  9. Dissecting protein-protein interactions using directed evolution.

    PubMed

    Bonsor, Daniel A; Sundberg, Eric J

    2011-04-05

    Protein-protein interactions are essential for life. They are responsible for most cellular functions and when they go awry often lead to disease. Proteins are inherently complex. They are flexible macromolecules whose constituent amino acid components act in combinatorial and networked ways when they engage one another in binding interactions. It is just this complexity that allows them to conduct such a broad array of biological functions. Despite decades of intense study of the molecular basis of protein-protein interactions, key gaps in our understanding remain, hindering our ability to accurately predict the specificities and affinities of their interactions. Until recently, most protein-protein investigations have been probed experimentally at the single-amino acid level, making them, by definition, incapable of capturing the combinatorial nature of, and networked communications between, the numerous residues within and outside of the protein-protein interface. This aspect of protein-protein interactions, however, is emerging as a major driving force for protein affinity and specificity. Understanding a combinatorial process necessarily requires a combinatorial experimental tool. Much like the organisms in which they reside, proteins naturally evolve over time, through a combinatorial process of mutagenesis and selection, to functionally associate. Elucidating the process by which proteins have evolved may be one of the keys to deciphering the molecular rules that govern their interactions with one another. Directed evolution is a technique performed in the laboratory that mimics natural evolution on a tractable time scale that has been utilized widely to engineer proteins with novel capabilities, including altered binding properties. In this review, we discuss directed evolution as an emerging tool for dissecting protein-protein interactions.

  10. Protein-protein interactions: methods for detection and analysis.

    PubMed Central

    Phizicky, E M; Fields, S

    1995-01-01

    The function and activity of a protein are often modulated by other proteins with which it interacts. This review is intended as a practical guide to the analysis of such protein-protein interactions. We discuss biochemical methods such as protein affinity chromatography, affinity blotting, coimmunoprecipitation, and cross-linking; molecular biological methods such as protein probing, the two-hybrid system, and phage display: and genetic methods such as the isolation of extragenic suppressors, synthetic mutants, and unlinked noncomplementing mutants. We next describe how binding affinities can be evaluated by techniques including protein affinity chromatography, sedimentation, gel filtration, fluorescence methods, solid-phase sampling of equilibrium solutions, and surface plasmon resonance. Finally, three examples of well-characterized domains involved in multiple protein-protein interactions are examined. The emphasis of the discussion is on variations in the approaches, concerns in evaluating the results, and advantages and disadvantages of the techniques. PMID:7708014

  11. Protein-protein Interactions using Radiolytic Footprinting

    SciTech Connect

    Takamoto,K.; Chance, M.

    2006-01-01

    Structural proteomics approaches using mass spectrometry are increasingly used in biology to examine the composition and structure of macromolecules. Hydroxyl radical-mediated protein footprinting using mass spectrometry has recently been developed to define structure, assembly, and conformational changes of macromolecules in solution based on measurements of reactivity of amino acid side chain groups with covalent modification reagents. Accurate measurements of side chain reactivity are achieved using quantitative liquid-chromatography-coupled mass spectrometry, whereas the side chain modification sites are identified using tandem mass spectrometry. In addition, the use of footprinting data in conjunction with computational modeling approaches is a powerful new method for testing and refining structural models of macromolecules and their complexes. In this review, we discuss the basic chemistry of hydroxyl radical reactions with peptides and proteins, highlight various approaches to map protein structure using radical oxidation methods, and describe state-of-the-art approaches to combine computational and footprinting data.

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

    PubMed Central

    Mitra, Pralay; Zhang, Yang

    2012-01-01

    Protein quaternary structure universe” refers to the ensemble of all protein-protein complexes across all organisms in nature. The number of quaternary folds thus corresponds to the number of ways proteins physically interact with other proteins. This study focuses on answering two basic questions: Whether the number of protein-protein interactions is limited and, if yes, how many different quaternary folds exist in nature. By all-to-all sequence and structure comparisons, we grouped the protein complexes in the protein data bank (PDB) into 3,629 families and 1,761 folds. A statistical model was introduced to obtain the quantitative relation between the numbers of quaternary families and quaternary folds in nature. The total number of possible protein-protein interactions was estimated around 4,000, which indicates that the current protein repository contains only 42% of quaternary folds in nature and a full coverage needs approximately a quarter century of experimental effort. The results have important implications to the protein complex structural modeling and the structure genomics of protein-protein interactions. PMID:22719985

  13. Protein interaction networks from literature mining

    NASA Astrophysics Data System (ADS)

    Ihara, Sigeo

    2005-03-01

    The ability to accurately predict and understand physiological changes in the biological network system in response to disease or drug therapeutics is of crucial importance in life science. The extensive amount of gene expression data generated from even a single microarray experiment often proves difficult to fully interpret and comprehend the biological significance. An increasing knowledge of protein interactions stored in the PubMed database, as well as the advancement of natural language processing, however, makes it possible to construct protein interaction networks from the gene expression information that are essential for understanding the biological meaning. From the in house literature mining system we have developed, the protein interaction network for humans was constructed. By analysis based on the graph-theoretical characterization of the total interaction network in literature, we found that the network is scale-free and semantic long-ranged interactions (i.e. inhibit, induce) between proteins dominate in the total interaction network, reducing the degree exponent. Interaction networks generated based on scientific text in which the interaction event is ambiguously described result in disconnected networks. In contrast interaction networks based on text in which the interaction events are clearly stated result in strongly connected networks. The results of protein-protein interaction networks obtained in real applications from microarray experiments are discussed: For example, comparisons of the gene expression data indicative of either a good or a poor prognosis for acute lymphoblastic leukemia with MLL rearrangements, using our system, showed newly discovered signaling cross-talk.

  14. Solid State NMR and Protein-Protein Interactions in Membranes

    PubMed Central

    Miao, Yimin; Cross, Timothy A.

    2013-01-01

    Solid state NMR spectroscopy has evolved rapidly in recent years into an excellent tool for the characterization of membrane proteins and their complexes. In the past few years it has also become clear that the structure of membrane proteins, especially helical membrane proteins is determined, in part, by the membrane environment. Therefore, the modeling of this environment by a liquid crystalline lipid bilayer for solid state NMR has generated a unique tool for the characterization of native conformational states, local and global dynamics, and high resolution structure for these proteins. Protein-protein interactions can also benefit from this solid state NMR capability to characterize membrane proteins in a native-like environment. These complexes take the form of oligomeric structures and hetero-protein interactions both with water soluble proteins and other membrane proteins. PMID:24034903

  15. Geminivirus C3 Protein: Replication Enhancement and Protein Interactions

    PubMed Central

    Settlage, Sharon B.; See, Renee G.; Hanley-Bowdoin, Linda

    2005-01-01

    Most dicot-infecting geminiviruses encode a replication enhancer protein (C3, AL3, or REn) that is required for optimal replication of their small, single-stranded DNA genomes. C3 interacts with C1, the essential viral replication protein that initiates rolling circle replication. C3 also homo-oligomerizes and interacts with at least two host-encoded proteins, proliferating cell nuclear antigen (PCNA) and the retinoblastoma-related protein (pRBR). It has been proposed that protein interactions contribute to C3 function. Using the C3 protein of Tomato yellow leaf curl virus, we examined the impact of mutations to amino acids that are conserved across the C3 protein family on replication enhancement and protein interactions. Surprisingly, many of the mutations did not affect replication enhancement activity of C3 in tobacco protoplasts. Other mutations either enhanced or were detrimental to C3 replication activity. Analysis of mutated proteins in yeast two-hybrid assays indicated that mutations that inactivate C3 replication enhancement activity also reduce or inactivate C3 oligomerization and interaction with C1 and PCNA. In contrast, mutated C3 proteins impaired for pRBR binding are fully functional in replication assays. Hydrophobic residues in the middle of the C3 protein were implicated in C3 interaction with itself, C1, and PCNA, while polar resides at both the N and C termini of the protein are important for C3-pRBR interaction. These experiments established the importance of C3-C3, C3-C1, and C3-PCNA interactions in geminivirus replication. While C3-pRBR interaction is not required for viral replication in cycling cells, it may play a role during infection of differentiated cells in intact plants. PMID:16014949

  16. APID: Agile Protein Interaction DataAnalyzer.

    PubMed

    Prieto, Carlos; De Las Rivas, Javier

    2006-07-01

    Agile Protein Interaction DataAnalyzer (APID) is an interactive bioinformatics web tool developed to integrate and analyze in a unified and comparative platform main currently known information about protein-protein interactions demonstrated by specific small-scale or large-scale experimental methods. At present, the application includes information coming from five main source databases enclosing an unified sever to explore >35 000 different proteins and 111 000 different proven interactions. The web includes search tools to query and browse upon the data, allowing selection of the interaction pairs based in calculated parameters that weight and qualify the reliability of each given protein interaction. Such parameters are for the 'proteins': connectivity, cluster coefficient, Gene Ontology (GO) functional environment, GO environment enrichment; and for the 'interactions': number of methods, GO overlapping, iPfam domain-domain interaction. APID also includes a graphic interactive tool to visualize selected sub-networks and to navigate on them or along the whole interaction network. The application is available open access at http://bioinfow.dep.usal.es/apid/.

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

    PubMed Central

    Wang, Su-Fang; Oh, Sangho; Si, Yue-Xiu; Wang, Zhi-Jiang; Han, Hong-Yan; Lee, Jinhyuk; Qian, Guo-Ying

    2012-01-01

    The various studies on tyrosinase have recently gained the attention of researchers due to their potential application values and the biological functions. In this study, we predicted the 3D structure of human tyrosinase and simulated the protein-protein interactions between tyrosinase and three binding partners, four and half LIM domains 2 (FHL2), cytochrome b-245 alpha polypeptide (CYBA), and RNA-binding motif protein 9 (RBM9). Our interaction simulations showed significant binding energy scores of −595.3 kcal/mol for FHL2, −859.1 kcal/mol for CYBA, and −821.3 kcal/mol for RBM9. We also investigated the residues of each protein facing toward the predicted site of interaction with tyrosinase. Our computational predictions will be useful for elucidating the protein-protein interactions of tyrosinase and studying its binding mechanisms. PMID:22577521

  18. Mapping interactions of Chikungunya virus nonstructural proteins.

    PubMed

    Sreejith, R; Rana, Jyoti; Dudha, Namrata; Kumar, Kapila; Gabrani, Reema; Sharma, Sanjeev K; Gupta, Amita; Vrati, Sudhanshu; Chaudhary, Vijay K; Gupta, Sanjay

    2012-10-01

    The four nonstructural proteins (nsPs1-4) of Chikungunya virus (CHIKV) play important roles involving enzymatic activities and specific interactions with both viral and host components, during different stages of viral pathogenesis. Elucidation of the presence and/or absence of interactions among nsPs in a systematic manner is thus of scientific interest. In the current study, each pair-wise combination among the four nonstructural proteins of CHIKV was systematically analyzed for possible interactions. Six novel protein interactions were identified for CHIKV, using systems such as yeast two-hybrid, GST pull down and ELISA, three of which have not been previously reported for the genus Alphavirus. These interactions form a network of organized associations that suggest the spatial arrangement of nonstructural proteins in the late replicase complex. The study identified novel interactions as well as concurred with previously described associations in related alphaviruses.

  19. MKP-7, a novel mitogen-activated protein kinase phosphatase, functions as a shuttle protein.

    PubMed

    Masuda, K; Shima, H; Watanabe, M; Kikuchi, K

    2001-10-19

    Mitogen-activated protein kinase (MAPK) phosphatases (MKPs) negatively regulate MAPK activity. In the present study, we have identified a novel MKP, designated MKP-7, and mapped it to human chromosome 12p12. MKP-7 possesses a long C-terminal stretch containing both a nuclear export signal and a nuclear localization signal, in addition to the rhodanese-like domain and the dual specificity phosphatase catalytic domain, both of which are conserved among MKP family members. When expressed in mammalian cells MKP-7 protein was localized exclusively in the cytoplasm, but this localization became exclusively nuclear following leptomycin B treatment or introduction of a mutation in the nuclear export signal. These findings indicate that MKP-7 is the first identified leptomycin B-sensitive shuttle MKP. Forced expression of MKP-7 suppressed activation of MAPKs in COS-7 cells in the order of selectivity, JNK p38 > ERK. Furthermore, a mutant form MKP-7 functioned as a dominant negative particularly against the dephosphorylation of JNK, suggesting that MKP-7 works as a JNK-specific phosphatase in vivo. Co-immunoprecipitation experiments and histological analysis suggested that MKP-7 determines the localization of MAPKs in the cytoplasm.

  20. Curvature-mediated interactions between membrane proteins.

    PubMed Central

    Kim, K S; Neu, J; Oster, G

    1998-01-01

    Membrane proteins can deform the lipid bilayer in which they are embedded. If the bilayer is treated as an elastic medium, then these deformations will generate elastic interactions between the proteins. The interaction between a single pair is repulsive. However, for three or more proteins, we show that there are nonpairwise forces whose magnitude is similar to the pairwise forces. When there are five or more proteins, we show that the nonpairwise forces permit the existence of stable protein aggregates, despite their pairwise repulsions. PMID:9788923

  1. Protein-protein interactions in complex cosolvent solutions.

    PubMed

    Javid, Nadeem; Vogtt, Karsten; Krywka, Chris; Tolan, Metin; Winter, Roland

    2007-04-02

    The effects of various kosmotropic and chaotropic cosolvents and salts on the intermolecular interaction potential of positively charged lysozyme is evaluated at varying protein concentrations by using synchrotron small-angle X-ray scattering in combination with liquid-state theoretical approaches. The experimentally derived static structure factors S(Q) obtained without and with added cosolvents and salts are analysed with a statistical mechanical model based on the Derjaguin-Landau-Verwey-Overbeek (DLVO) potential, which accounts for repulsive and attractive interactions between the protein molecules. Different cosolvents and salts influence the interactions between protein molecules differently as a result of changes in the hydration level or solvation, in charge screening, specific adsorption of the additives at the protein surface, or increased hydrophobic interactions. Intermolecular interaction effects are significant above protein concentrations of 1 wt %, and with increasing protein concentration, the repulsive nature of the intermolecular pair potential V(r) increases markedly. Kosmotropic cosolvents like glycerol and sucrose exhibit strong concentration-dependent effects on the interaction potential, leading to an increase of repulsive forces between the protein molecules at low to medium high osmolyte concentrations. Addition of trifluoroethanol exhibits a multiphasic effect on V(r) when changing its concentration. Salts like sodium chloride and potassium sulfate exhibit strong concentration-dependent changes of the interaction potential due to charge screening of the positively charged protein molecules. Guanidinium chloride (GdmCl) at low concentrations exhibits a similar charge-screening effect, resulting in increased attractive interactions between the protein molecules. At higher GdmCl concentrations, V(r) becomes more repulsive in nature due to the presence of high concentrations of Gdm(+) ions binding to the protein molecules. Our findings also

  2. An Interactive Introduction to Protein Structure

    ERIC Educational Resources Information Center

    Lee, W. Theodore

    2004-01-01

    To improve student understanding of protein structure and the significance of noncovalent interactions in protein structure and function, students are assigned a project to write a paper complemented with computer-generated images. The assignment provides an opportunity for students to select a protein structure that is of interest and detail…

  3. An Interactive Introduction to Protein Structure

    ERIC Educational Resources Information Center

    Lee, W. Theodore

    2004-01-01

    To improve student understanding of protein structure and the significance of noncovalent interactions in protein structure and function, students are assigned a project to write a paper complemented with computer-generated images. The assignment provides an opportunity for students to select a protein structure that is of interest and detail…

  4. Protein-protein interactions: scoring schemes and binding affinity.

    PubMed

    Gromiha, M Michael; Yugandhar, K; Jemimah, Sherlyn

    2017-06-01

    Protein-protein interactions mediate several cellular functions, which can be understood from the information obtained using the three-dimensional structures of protein-protein complexes and binding affinity data. This review focuses on computational aspects of predicting the best native-like complex structure and binding affinities. The first part covers the prediction of protein-protein complex structures and the advantages of conformational searching and scoring functions in protein-protein docking. The second part is devoted to various aspects of protein-protein interaction thermodynamics, such as databases for binding affinities and other thermodynamic parameters, computational methods to predict the binding affinity using either the three-dimensional structures of complexes or amino acid sequences, and change in binding affinities of the complexes upon mutations. We provide the latest developments on protein-protein docking and binding affinity studies along with a list of available computational resources for understanding protein-protein interactions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Inferring interaction partners from protein sequences

    PubMed Central

    Bitbol, Anne-Florence; Dwyer, Robert S.; Colwell, Lucy J.; Wingreen, Ned S.

    2016-01-01

    Specific protein−protein interactions are crucial in the cell, both to ensure the formation and stability of multiprotein complexes and to enable signal transduction in various pathways. Functional interactions between proteins result in coevolution between the interaction partners, causing their sequences to be correlated. Here we exploit these correlations to accurately identify, from sequence data alone, which proteins are specific interaction partners. Our general approach, which employs a pairwise maximum entropy model to infer couplings between residues, has been successfully used to predict the 3D structures of proteins from sequences. Thus inspired, we introduce an iterative algorithm to predict specific interaction partners from two protein families whose members are known to interact. We first assess the algorithm’s performance on histidine kinases and response regulators from bacterial two-component signaling systems. We obtain a striking 0.93 true positive fraction on our complete dataset without any a priori knowledge of interaction partners, and we uncover the origin of this success. We then apply the algorithm to proteins from ATP-binding cassette (ABC) transporter complexes, and obtain accurate predictions in these systems as well. Finally, we present two metrics that accurately distinguish interacting protein families from noninteracting ones, using only sequence data. PMID:27663738

  6. DIP: The Database of Interacting Proteins

    DOE Data Explorer

    The DIP Database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent set of protein-protein interactions. By interaction, the DIP Database creators mean that two amino acid chains were experimentally identified to bind to each other. The database lists such pairs to aid those studying a particular protein-protein interaction but also those investigating entire regulatory and signaling pathways as well as those studying the organisation and complexity of the protein interaction network at the cellular level. The data stored within the DIP database were curated, both, manually by expert curators and also automatically using computational approaches that utilize the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. It is a relational database that can be searched by protein, sequence, motif, article information, and pathBLAST. The website also serves as an access point to a number of projects related to DIP, such as LiveDIP, The Database of Ligand-Receptor Partners (DLRP) and JDIP. Users have free and open access to DIP after login. [Taken from the DIP Guide and the DIP website] (Specialized Interface) (Registration Required)

  7. Cation-pi interactions in protein-protein interfaces.

    PubMed

    Crowley, Peter B; Golovin, Adel

    2005-05-01

    Arginine is an abundant residue in protein-protein interfaces. The importance of this residue relates to the versatility of its side chain in intermolecular interactions. Different classes of protein-protein interfaces were surveyed for cation-pi interactions. Approximately half of the protein complexes and one-third of the homodimers analyzed were found to contain at least one intermolecular cation-pi pair. Interactions between arginine and tyrosine were found to be the most abundant. The electrostatic interaction energy was calculated to be approximately 3 kcal/mol, on average. A distance-based search of guanidinium:aromatic interactions was also performed using the Macromolecular Structure Database (MSD). This search revealed that half of the guanidinium:aromatic pairs pack in a coplanar manner. Furthermore, it was found that the cationic group of the cation-pi pair is frequently involved in intermolecular hydrogen bonds. In this manner the arginine side chain can participate in multiple interactions, providing a mechanism for inter-protein specificity. Thus, the cation-pi interaction is established as an important contributor to protein-protein interfaces.

  8. Predicting protein interactions by Brownian dynamics simulations.

    PubMed

    Meng, Xuan-Yu; Xu, Yu; Zhang, Hong-Xing; Mezei, Mihaly; Cui, Meng

    2012-01-01

    We present a newly adapted Brownian-Dynamics (BD)-based protein docking method for predicting native protein complexes. The approach includes global BD conformational sampling, compact complex selection, and local energy minimization. In order to reduce the computational costs for energy evaluations, a shell-based grid force field was developed to represent the receptor protein and solvation effects. The performance of this BD protein docking approach has been evaluated on a test set of 24 crystal protein complexes. Reproduction of experimental structures in the test set indicates the adequate conformational sampling and accurate scoring of this BD protein docking approach. Furthermore, we have developed an approach to account for the flexibility of proteins, which has been successfully applied to reproduce the experimental complex structure from the structure of two unbounded proteins. These results indicate that this adapted BD protein docking approach can be useful for the prediction of protein-protein interactions.

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

    NASA Astrophysics Data System (ADS)

    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.

  10. Capturing the Interaction Potential of Amyloidogenic Proteins

    SciTech Connect

    Javid, Nadeem; Vogtt, Karsten; Winter, Roland; Krywka, Christina; Tolan, Metin

    2007-07-13

    Experimentally derived static structure factors obtained for the aggregation-prone protein insulin were analyzed with a statistical mechanical model based on the Derjaguin-Landau-Verwey-Overbeek potential. The data reveal that the protein self-assembles into equilibrium clusters already at low concentrations. Furthermore, striking differences regarding interaction forces between aggregation-prone proteins such as insulin in the preaggregated regime and natively stable globular proteins are found.

  11. PPIM: A Protein-Protein Interaction Database for Maize1

    PubMed Central

    Wu, Aibo; Xu, Xin-Jian; Lu, Le; Liu, Jingdong; Cao, Yongwei; Chen, Luonan; Wu, Jun; Zhao, Xing-Ming

    2016-01-01

    Maize (Zea mays) is one of the most important crops worldwide. To understand the biological processes underlying various traits of the crop (e.g. yield and response to stress), a detailed protein-protein interaction (PPI) network is highly demanded. Unfortunately, there are very few such PPIs available in the literature. Therefore, in this work, we present the Protein-Protein Interaction Database for Maize (PPIM), which covers 2,762,560 interactions among 14,000 proteins. The PPIM contains not only accurately predicted PPIs but also those molecular interactions collected from the literature. The database is freely available at http://comp-sysbio.org/ppim with a user-friendly powerful interface. We believe that the PPIM resource can help biologists better understand the maize crop. PMID:26620522

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

    PubMed

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

    2015-03-01

    It is beyond any doubt that proteins and their interactions play an essential role in most complex biological processes. The understanding of their function individually, but also in the form of protein complexes is of a great importance. Nowadays, despite the plethora of various high-throughput experimental approaches for detecting protein-protein interactions, many computational methods aiming to predict new interactions have appeared and gained interest. In this review, we focus on text-mining based computational methodologies, aiming to extract information for proteins and their interactions from public repositories such as literature and various biological databases. We discuss their strengths, their weaknesses and how they complement existing experimental techniques by simultaneously commenting on the biological databases which hold such information and the benchmark datasets that can be used for evaluating new tools. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. Structural similarity enhances interaction propensity of proteins.

    PubMed

    Lukatsky, D B; Shakhnovich, B E; Mintseris, J; Shakhnovich, E I

    2007-02-02

    We study statistical properties of interacting protein-like surfaces and predict two strong, related effects: (i) statistically enhanced self-attraction of proteins; (ii) statistically enhanced attraction of proteins with similar structures. The effects originate in the fact that the probability to find a pattern self-match between two identical, even randomly organized interacting protein surfaces is always higher compared with the probability for a pattern match between two different, promiscuous protein surfaces. This theoretical finding explains statistical prevalence of homodimers in protein-protein interaction networks reported earlier. Further, our findings are confirmed by the analysis of curated database of protein complexes that showed highly statistically significant overrepresentation of dimers formed by structurally similar proteins with highly divergent sequences ("superfamily heterodimers"). We suggest that promiscuous homodimeric interactions pose strong competitive interactions for heterodimers evolved from homodimers. Such evolutionary bottleneck is overcome using the negative design evolutionary pressure applied against promiscuous homodimer formation. This is achieved through the formation of highly specific contacts formed by charged residues as demonstrated both in model and real superfamily heterodimers.

  14. Linkers in the structural biology of protein-protein interactions.

    PubMed

    Reddy Chichili, Vishnu Priyanka; Kumar, Veerendra; Sivaraman, J

    2013-02-01

    Linkers or spacers are short amino acid sequences created in nature to separate multiple domains in a single protein. Most of them are rigid and function to prohibit unwanted interactions between the discrete domains. However, Gly-rich linkers are flexible, connecting various domains in a single protein without interfering with the function of each domain. The advent of recombinant DNA technology made it possible to fuse two interacting partners with the introduction of artificial linkers. Often, independent proteins may not exist as stable or structured proteins until they interact with their binding partner, following which they gain stability and the essential structural elements. Gly-rich linkers have been proven useful for these types of unstable interactions, particularly where the interaction is weak and transient, by creating a covalent link between the proteins to form a stable protein-protein complex. Gly-rich linkers are also employed to form stable covalently linked dimers, and to connect two independent domains that create a ligand-binding site or recognition sequence. The lengths of linkers vary from 2 to 31 amino acids, optimized for each condition so that the linker does not impose any constraints on the conformation or interactions of the linked partners. Various structures of covalently linked protein complexes have been described using X-ray crystallography, nuclear magnetic resonance and cryo-electron microscopy techniques. In this review, we evaluate several structural studies where linkers have been used to improve protein quality, to produce stable protein-protein complexes, and to obtain protein dimers.

  15. Protein-phospholipid interactions in blood clotting.

    PubMed

    Morrissey, James H; Davis-Harrison, Rebecca L; Tavoosi, Narjes; Ke, Ke; Pureza, Vincent; Boettcher, John M; Clay, Mary C; Rienstra, Chad M; Ohkubo, Y Zenmei; Pogorelov, Taras V; Tajkhorshid, Emad

    2010-04-01

    Most steps of the blood clotting cascade require the assembly of a serine protease with its specific regulatory protein on a suitable phospholipid bilayer. Unfortunately, the molecular details of how blood clotting proteins bind to membrane surfaces remain poorly understood, owing to a dearth of techniques for studying protein-membrane interactions at high resolution. Our laboratories are tackling this question using a combination of approaches, including nanoscale membrane bilayers, solid-state NMR, and large-scale molecular dynamics simulations. These studies are now providing structural insights at atomic resolution into clotting protein-membrane interactions. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  16. Protein-Phospholipid Interactions in Blood Clotting

    PubMed Central

    Morrissey, James H.; Davis-Harrison, Rebecca L.; Tavoosi, Narjes; Ke, Ke; Pureza, Vincent; Boettcher, John M.; Clay, Mary C.; Rienstra, Chad M.; Ohkubo, Y. Zenmei; Pogorelov, Taras V.; Tajkhorshid, Emad

    2010-01-01

    Most steps of the blood clotting cascade require the assembly of a serine protease with its specific regulatory protein on a suitable phospholipid bilayer. Unfortunately, the molecular details of how blood clotting proteins bind to membrane surfaces remain poorly understood, owing to a dearth of techniques for studying protein-membrane interactions at high resolution. Our laboratories are tackling this question using a combination of approaches, including nanoscale membrane bilayers, solid-state NMR, and large-scale molecular dynamics simulations. These studies are now providing structural insights at atomic resolution into clotting protein-membrane interactions. PMID:20129649

  17. Single-Molecule Study of Protein-Protein and Protein-DNA Interaction Dynamics

    SciTech Connect

    Lu, H. PETER

    2005-03-01

    Protein-protein and protein-DNA interactions play critical roles in biological functions of living cells, such as cell signaling, receptor-ligand activation, cellular metabolism, DNA damage recognition and repair, gene expression, replication, etc. These protein interactions often involve complex mechanisms and inhomogeneous dynamics with significant conformational changes. Protein-protein, protein-ligand, and protein-DNA interactions are often intrinsically single-molecule processes at an induction stage associated with the initiation of crucial early eents in living cells. For example, cell-signaling processes are often initiated through a few copies of protein-interaction complexes, being amplified along the signaling pathway.

  18. Predicting the fission yeast protein interaction network.

    PubMed

    Pancaldi, Vera; Saraç, Omer S; Rallis, Charalampos; McLean, Janel R; Převorovský, Martin; Gould, Kathleen; Beyer, Andreas; Bähler, Jürg

    2012-04-01

    A systems-level understanding of biological processes and information flow requires the mapping of cellular component interactions, among which protein-protein interactions are particularly important. Fission yeast (Schizosaccharomyces pombe) is a valuable model organism for which no systematic protein-interaction data are available. We exploited gene and protein properties, global genome regulation datasets, and conservation of interactions between budding and fission yeast to predict fission yeast protein interactions in silico. We have extensively tested our method in three ways: first, by predicting with 70-80% accuracy a selected high-confidence test set; second, by recapitulating interactions between members of the well-characterized SAGA co-activator complex; and third, by verifying predicted interactions of the Cbf11 transcription factor using mass spectrometry of TAP-purified protein complexes. Given the importance of the pathway in cell physiology and human disease, we explore the predicted sub-networks centered on the Tor1/2 kinases. Moreover, we predict the histidine kinases Mak1/2/3 to be vital hubs in the fission yeast stress response network, and we suggest interactors of argonaute 1, the principal component of the siRNA-mediated gene silencing pathway, lost in budding yeast but preserved in S. pombe. Of the new high-quality interactions that were discovered after we started this work, 73% were found in our predictions. Even though any predicted interactome is imperfect, the protein network presented here can provide a valuable basis to explore biological processes and to guide wet-lab experiments in fission yeast and beyond. Our predicted protein interactions are freely available through PInt, an online resource on our website (www.bahlerlab.info/PInt).

  19. Intraviral protein interactions of Chandipura virus.

    PubMed

    Kumar, Kapila; Rana, Jyoti; Sreejith, R; Gabrani, Reema; Sharma, Sanjeev K; Gupta, Amita; Chaudhary, Vijay K; Gupta, Sanjay

    2012-10-01

    Chandipura virus (CHPV) is an emerging rhabdovirus responsible for several outbreaks of fatal encephalitis among children in India. The characteristic structure of the virus is a result of extensive and specific interplay among its five encoded proteins. The revelation of interactions among CHPV proteins can help in gaining insight into viral architecture and pathogenesis. In the current study, we carried out comprehensive yeast two-hybrid (Y2H) analysis to elucidate intraviral protein-protein interactions. All of the interactions identified by Y2H were assessed for reliability by GST pull-down and ELISA. A total of eight interactions were identified among four viral proteins. Five of these interactions are being reported for the first time for CHPV. Among these, the glycoprotein (G)-nucleocapsid (N) interaction could be considered novel, as this has not been reported for any members of the family Rhabdoviridae. This study provides a framework within which the roles of the identified protein interactions can be explored further for understanding the biology of this virus at the molecular level.

  20. Van der Waals Interactions Involving Proteins

    NASA Technical Reports Server (NTRS)

    Roth, Charles M.; Neal, Brian L.; Lenhoff, Abraham M.

    1996-01-01

    Van der Waals (dispersion) forces contribute to interactions of proteins with other molecules or with surfaces, but because of the structural complexity of protein molecules, the magnitude of these effects is usually estimated based on idealized models of the molecular geometry, e.g., spheres or spheroids. The calculations reported here seek to account for both the geometric irregularity of protein molecules and the material properties of the interacting media. Whereas the latter are found to fall in the generally accepted range, the molecular shape is shown to cause the magnitudes of the interactions to differ significantly from those calculated using idealized models. with important consequences. First, the roughness of the molecular surface leads to much lower average interaction energies for both protein-protein and protein-surface cases relative to calculations in which the protein molecule is approximated as a sphere. These results indicate that a form of steric stabilization may be an important effect in protein solutions. Underlying this behavior is appreciable orientational dependence, one reflection of which is that molecules of complementary shape are found to exhibit very strong attractive dispersion interactions. Although this has been widely discussed previously in the context of molecular recognition processes, the broader implications of these phenomena may also be important at larger molecular separations, e.g., in the dynamics of aggregation, precipitation, and crystal growth.

  1. Van der Waals interactions involving proteins.

    PubMed Central

    Roth, C M; Neal, B L; Lenhoff, A M

    1996-01-01

    Van der Waals (dispersion) forces contribute to interactions of proteins with other molecules or with surfaces, but because of the structural complexity of protein molecules, the magnitude of these effects is usually estimated based on idealized models of the molecular geometry, e.g., spheres or spheroids. The calculations reported here seek to account for both the geometric irregularity of protein molecules and the material properties of the interacting media. Whereas the latter are found to fall in the generally accepted range, the molecular shape is shown to cause the magnitudes of the interactions to differ significantly from those calculated using idealized models, with important consequences. First, the roughness of the molecular surface leads to much lower average interaction energies for both protein-protein and protein-surface cases relative to calculations in which the protein molecule is approximated as a sphere. These results indicate that a form of steric stabilization may be an important effect in protein solutions. Underlying this behavior is appreciable orientational dependence, one reflection of which is that molecules of complementary shape are found to exhibit very strong attractive dispersion interactions. Although this has been widely discussed previously in the context of molecular recognition processes, the broader implications of these phenomena may also be important at larger molecular separations, e.g., in the dynamics of aggregation, precipitation, and crystal growth. Images FIGURE 3 PMID:8789115

  2. Highly specific protein-protein interactions, evolution and negative design.

    PubMed

    Sear, Richard P

    2004-12-01

    We consider highly specific protein-protein interactions in proteomes of simple model proteins. We are inspired by the work of Zarrinpar et al (2003 Nature 426 676). They took a binding domain in a signalling pathway in yeast and replaced it with domains of the same class but from different organisms. They found that the probability of a protein binding to a protein from the proteome of a different organism is rather high, around one half. We calculate the probability of a model protein from one proteome binding to the protein of a different proteome. These proteomes are obtained by sampling the space of functional proteomes uniformly. In agreement with Zarrinpar et al we find that the probability of a protein binding a protein from another proteome is rather high, of order one tenth. Our results, together with those of Zarrinpar et al, suggest that designing, say, a peptide to block or reconstitute a single signalling pathway, without affecting any other pathways, requires knowledge of all the partners of the class of binding domains the peptide is designed to mimic. This knowledge is required to use negative design to explicitly design out interactions of the peptide with proteins other than its target. We also found that patches that are required to bind with high specificity evolve more slowly than those that are required only to not bind to any other patch. This is consistent with some analysis of sequence data for proteins engaged in highly specific interactions.

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

    PubMed

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

    2015-01-01

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

  4. STITCH: interaction networks of chemicals and proteins

    PubMed Central

    Kuhn, Michael; von Mering, Christian; Campillos, Monica; Jensen, Lars Juhl; Bork, Peer

    2008-01-01

    The knowledge about interactions between proteins and small molecules is essential for the understanding of molecular and cellular functions. However, information on such interactions is widely dispersed across numerous databases and the literature. To facilitate access to this data, STITCH (‘search tool for interactions of chemicals’) integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug–target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins. Each proposed interaction can be traced back to the original data sources. Our database contains interaction information for over 68 000 different chemicals, including 2200 drugs, and connects them to 1.5 million genes across 373 genomes and their interactions contained in the STRING database. STITCH is available at http://stitch.embl.de/ PMID:18084021

  5. Protein-protein interaction network of celiac disease.

    PubMed

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

    2016-01-01

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

  6. Contribution of Hydrophobic Interactions to Protein Stability

    PubMed Central

    Pace, C. Nick; Fu, Hailong; Fryar, Katrina Lee; Landua, John; Trevino, Saul R.; Shirley, Bret A.; Hendricks, Marsha McNutt; Iimura, Satoshi; Gajiwala, Ketan; Scholtz, J. Martin; Grimsley, Gerald R.

    2011-01-01

    Our goal was to gain a better understanding of the contribution of hydrophobic interactions to protein stability. We measured the change in conformational stability, Δ(ΔG), for hydrophobic mutants of four proteins: villin head piece subdomain (VHP) with 36 residues, a surface protein from Borrelia burgdorferi (VlsE) with 341 residues, and two proteins previously studied in our laboratory, ribonucleases Sa and T1. We compare our results with previous studies and reach the following conclusions. 1. Hydrophobic interactions contribute less to the stability of a small protein, VHP (0.6 ± 0.3 kcal/mole per –CH2– group), than to the stability of a large protein, VlsE (1.6 ± 0.3 kcal/mol per –CH2– group). 2. Hydrophobic interactions make the major contribution to the stability of VHP (40 kcal/mol) and the major contributors are (in kcal/mol): Phe 18 (3.9), Met 13 (3.1), Phe 7 (2.9), Phe 11 (2.7), and Leu 21 (2.7). 3. Based on Δ(ΔG) values for 148 hydrophobic mutants in 13 proteins, burying a –CH2– group on folding contributes, on average, 1.1 ± 0.5 kcal/mol to protein stability. 4. The experimental Δ(ΔG) values for aliphatic side chains (Ala, Val, Ile, and Leu) are in good agreement with their ΔGtr values from water to cyclohexane. 5. For 22 proteins with 36 to 534 residues, hydrophobic interactions contribute 60 ± 4% and hydrogen bonds 40 ± 4% to protein stability. 6. Conformational entropy contributes about 2.4 kcal/mol per residue to protein instability. The globular conformation of proteins is stabilized predominately by hydrophobic interactions. PMID:21377472

  7. Contribution of hydrophobic interactions to protein stability.

    PubMed

    Pace, C Nick; Fu, Hailong; Fryar, Katrina Lee; Landua, John; Trevino, Saul R; Shirley, Bret A; Hendricks, Marsha McNutt; Iimura, Satoshi; Gajiwala, Ketan; Scholtz, J Martin; Grimsley, Gerald R

    2011-05-06

    Our goal was to gain a better understanding of the contribution of hydrophobic interactions to protein stability. We measured the change in conformational stability, Δ(ΔG), for hydrophobic mutants of four proteins: villin headpiece subdomain (VHP) with 36 residues, a surface protein from Borrelia burgdorferi (VlsE) with 341 residues, and two proteins previously studied in our laboratory, ribonucleases Sa and T1. We compared our results with those of previous studies and reached the following conclusions: (1) Hydrophobic interactions contribute less to the stability of a small protein, VHP (0.6±0.3 kcal/mol per -CH(2)- group), than to the stability of a large protein, VlsE (1.6±0.3 kcal/mol per -CH(2)- group). (2) Hydrophobic interactions make the major contribution to the stability of VHP (40 kcal/mol) and the major contributors are (in kilocalories per mole) Phe18 (3.9), Met13 (3.1), Phe7 (2.9), Phe11 (2.7), and Leu21 (2.7). (3) Based on the Δ(ΔG) values for 148 hydrophobic mutants in 13 proteins, burying a -CH(2)- group on folding contributes, on average, 1.1±0.5 kcal/mol to protein stability. (4) The experimental Δ(ΔG) values for aliphatic side chains (Ala, Val, Ile, and Leu) are in good agreement with their ΔG(tr) values from water to cyclohexane. (5) For 22 proteins with 36 to 534 residues, hydrophobic interactions contribute 60±4% and hydrogen bonds contribute 40±4% to protein stability. (6) Conformational entropy contributes about 2.4 kcal/mol per residue to protein instability. The globular conformation of proteins is stabilized predominantly by hydrophobic interactions. Copyright © 2011 Elsevier Ltd. All rights reserved.

  8. APID: Agile Protein Interaction DataAnalyzer

    PubMed Central

    Prieto, Carlos; De Las Rivas, Javier

    2006-01-01

    Agile Protein Interaction DataAnalyzer (APID) is an interactive bioinformatics web tool developed to integrate and analyze in a unified and comparative platform main currently known information about protein–protein interactions demonstrated by specific small-scale or large-scale experimental methods. At present, the application includes information coming from five main source databases enclosing an unified sever to explore >35 000 different proteins and 111 000 different proven interactions. The web includes search tools to query and browse upon the data, allowing selection of the interaction pairs based in calculated parameters that weight and qualify the reliability of each given protein interaction. Such parameters are for the ‘proteins’: connectivity, cluster coefficient, Gene Ontology (GO) functional environment, GO environment enrichment; and for the ‘interactions’: number of methods, GO overlapping, iPfam domain–domain interaction. APID also includes a graphic interactive tool to visualize selected sub-networks and to navigate on them or along the whole interaction network. The application is available open access at . PMID:16845013

  9. Evolvability of yeast protein-protein interaction interfaces.

    PubMed

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

    2012-06-22

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

  10. Predicting the Fission Yeast Protein Interaction Network

    PubMed Central

    Pancaldi, Vera; Saraç, Ömer S.; Rallis, Charalampos; McLean, Janel R.; Převorovský, Martin; Gould, Kathleen; Beyer, Andreas; Bähler, Jürg

    2012-01-01

    A systems-level understanding of biological processes and information flow requires the mapping of cellular component interactions, among which protein–protein interactions are particularly important. Fission yeast (Schizosaccharomyces pombe) is a valuable model organism for which no systematic protein-interaction data are available. We exploited gene and protein properties, global genome regulation datasets, and conservation of interactions between budding and fission yeast to predict fission yeast protein interactions in silico. We have extensively tested our method in three ways: first, by predicting with 70–80% accuracy a selected high-confidence test set; second, by recapitulating interactions between members of the well-characterized SAGA co-activator complex; and third, by verifying predicted interactions of the Cbf11 transcription factor using mass spectrometry of TAP-purified protein complexes. Given the importance of the pathway in cell physiology and human disease, we explore the predicted sub-networks centered on the Tor1/2 kinases. Moreover, we predict the histidine kinases Mak1/2/3 to be vital hubs in the fission yeast stress response network, and we suggest interactors of argonaute 1, the principal component of the siRNA-mediated gene silencing pathway, lost in budding yeast but preserved in S. pombe. Of the new high-quality interactions that were discovered after we started this work, 73% were found in our predictions. Even though any predicted interactome is imperfect, the protein network presented here can provide a valuable basis to explore biological processes and to guide wet-lab experiments in fission yeast and beyond. Our predicted protein interactions are freely available through PInt, an online resource on our website (www.bahlerlab.info/PInt). PMID:22540037

  11. Moonlighting proteins in sperm-egg interactions.

    PubMed

    Petit, François M; Serres, Catherine; Auer, Jana

    2014-12-01

    Sperm-egg interaction is a highly species-specific step during the fertilization process. The first steps consist of recognition between proteins on the sperm head and zona pellucida (ZP) glycoproteins, the acellular coat that protects the oocyte. We aimed to determine which sperm head proteins interact with ZP2, ZP3 and ZP4 in humans. Two approaches were combined to identify these proteins: immunoblotting human spermatozoa targeted by antisperm antibodies (ASAs) from infertile men and far-Western blotting of human sperm proteins overlaid by each of the human recombinant ZP (hrZP) proteins. We used a proteomic approach with 2D electrophoretic separation of sperm protein revealed using either ASAs eluted from infertile patients or recombinant human ZP glycoproteins expressed in Chinese-hamster ovary (CHO) cells. Only spots highlighted by both methods were analysed by MALDI-MS/MS for identification. We identified proteins already described in human spermatozoa, but implicated in different metabolic pathways such as glycolytic enzymes [phosphokinase type 3 (PK3), enolase 1 (ENO1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), aldolase A (ALDOA) and triose phosphate isomerase (TPI)], detoxification enzymes [GST Mu (GSTM) and phospholipid hydroperoxide glutathione peroxidase (PHGPx) 4], ion channels [voltage-dependent anion channel 2 (VDAC2)] or structural proteins (outer dense fibre 2). Several proteins were localized on the sperm head by indirect immunofluorescence, and their interaction with ZP proteins was confirmed by co-precipitation experiments. These results confirm the complexity of the sperm-ZP recognition process in humans with the implication of different proteins interacting with the main three ZP glycoproteins. The multiple roles of these proteins suggest that they are multifaceted or moonlighting proteins.

  12. Interface-Resolved Network of Protein-Protein Interactions

    PubMed Central

    Johnson, Margaret E.; Hummer, Gerhard

    2013-01-01

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

  13. Carbohydrate-Aromatic Interactions in Proteins.

    PubMed

    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.

  14. A Tool for Interactive Protein Manipulation

    SciTech Connect

    Kreylos, Oliver; Max, Nelson; Bethel, Wes; Crivelli, Silvia; Lu, James; Crawford, Clark

    2005-03-28

    ProteinShop is a graphical environment that facilitates a solution to the protein prediction problem through a combination of unique features and capabilities. These include: 1. Helping researchers automatically generate 3D protein structures from scratcW by using the sequence of amino acids and secondary structure specifications as input. 2. Enabling users to apply their accumulated biochemical knowledge and intuition during the interactive manipulation of structures. 3. FacIlitating interactive comparison and analysis of alternative structures through visualization of free energy computed during modeling. 4. Accelerating discovery of low-energy configurations by applying local optimizations plug-in to user-selected protein structures. ProteinShop v.2.0 includes the following new features: - Visualizes multiple-domain structures - Automatically creates a user-specified number of beta-sheet configurations - Provides the interface and the libraries for energy visualization and local minimization of protein structures - Reads standard POB files without previous editing

  15. Brownian dynamics simulation of electrostatically interacting proteins

    NASA Astrophysics Data System (ADS)

    Ermakova, E.; Krushelnitsky, A. G.; Fedotov, V. D.

    Brownian dynamics simulation software has been developed to study the dynamics of proteins as a whole in solution. The proteins were modelled as spheres with point dipoles embedded in the centre of sphere. A set of Brownian dynamics simulations at different values of the dipole moments, protein concentration and translational diffusion coefficient was performed to investigate the influence of interprotein electrostatic interactions on dynamic protein behaviour in solution. It was shown that these interactions led to the slowing down of protein rotation and a complex non-exponential shape of the rotational correlation function. Analysis of the correlation functions was performed within the frame of the model of electrostatic interprotein interactions advanced earlier on the basis of NMR and dielectric spectroscopy data. This model assumes that, due to electrostatic interactions, protein Brownian rotation becomes anisotropic. The lifetime of this anisotropy is controlled mainly by translational diffusion of proteins. Thus, the correlation function can be decomposed into two components corresponding to anisotropic Brownian rotation and an isotropic motion of an external electric field vector produced by the surrounding proteins.

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

    PubMed Central

    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

  17. Eukaryotic LYR Proteins Interact with Mitochondrial Protein Complexes

    PubMed Central

    Angerer, Heike

    2015-01-01

    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. PMID:25686363

  18. Website on Protein Interaction and Protein Structure Related Work

    NASA Technical Reports Server (NTRS)

    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.

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

    Cancer.gov

    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 Emory_CTD^2_PPI_Reagents.xlsx Contact: Haian Fu

  20. Protein-protein interaction networks in the spinocerebellar ataxias

    PubMed Central

    Rubinsztein, David C

    2006-01-01

    A large yeast two-hybrid study investigating whether the proteins mutated in different forms of spinocerebellar ataxia have interacting protein partners in common suggests that some forms do share common pathways, and will provide a valuable resource for future work on these diseases. PMID:16904001

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

    Cancer.gov

    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

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

    Cancer.gov

    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.

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

    Cancer.gov

    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.

  4. Teaching Noncovalent Interactions Using Protein Molecular Evolution

    ERIC Educational Resources Information Center

    Fornasari, Maria Silvina; Parisi, Gustavo; Echave, Julian

    2008-01-01

    Noncovalent interactions and physicochemical properties of amino acids are important topics in biochemistry courses. Here, we present a computational laboratory where the capacity of each of the 20 amino acids to maintain different noncovalent interactions are used to investigate the stabilizing forces in a set of proteins coming from organisms…

  5. Teaching Noncovalent Interactions Using Protein Molecular Evolution

    ERIC Educational Resources Information Center

    Fornasari, Maria Silvina; Parisi, Gustavo; Echave, Julian

    2008-01-01

    Noncovalent interactions and physicochemical properties of amino acids are important topics in biochemistry courses. Here, we present a computational laboratory where the capacity of each of the 20 amino acids to maintain different noncovalent interactions are used to investigate the stabilizing forces in a set of proteins coming from organisms…

  6. Inferring Domain-Domain Interactions from Protein-Protein Interactions with Formal Concept Analysis

    PubMed Central

    Khor, Susan

    2014-01-01

    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. PMID:24586450

  7. Genetic variation in SLC7A2 interacts with calcium and magnesium intakes in modulating the risk of colorectal polyps.

    PubMed

    Sun, Pin; Zhu, Xiangzhu; Shrubsole, Martha J; Ness, Reid M; Hibler, Elizabeth A; Cai, Qiuyin; Long, Jirong; Chen, Zhi; Li, Guoliang; Hou, Lifang; Smalley, Walter E; Edwards, Todd L; Giovannucci, Edward; Zheng, Wei; Dai, Qi

    2017-09-01

    Solute carrier family 7, member 2 (SLC7A2) gene encodes a protein called cationic amino acid transporter 2, which mediates the transport of arginine, lysine and ornithine. l-Arginine is necessary for cancer development and progression, including an important role in colorectal cancer pathogenesis. Furthermore, previous studies found that both calcium and magnesium inhibit the transport of arginine. Thus, calcium, magnesium or calcium:magnesium intake ratio may interact with polymorphisms in the SLC7A2 gene in association with colorectal cancer. We conducted a two-phase case-control study within the Tennessee Colorectal Polyps Study. In the first phase, 23 tagging single-nucleotide polymorphisms in the SLC7A2 gene were included for 725 colorectal adenoma cases and 755 controls. In the second phase conducted in an independent set of 607 cases and 2113 controls, we replicated the significant findings in the first phase. We observed that rs2720574 significantly interacted with calcium:magnesium intake ratio in association with odds of adenoma, particularly multiple/advanced adenoma. In the combined analysis, among those with a calcium:magnesium intake ratio below 2.78, individuals who carried GC/CC genotypes demonstrated higher odds of adenoma [OR (95% CI):1.36 (1.11-1.68)] and multiple/advanced adenoma [OR (95% CI): 1.68 (1.28, 2.20)] than those who carried the GG genotype. The P values for interactions between calcium:magnesium intake ratio and rs2720574 were .002 for all adenomas and <.001 for multiple/advanced adenoma. Among those with the GG genotype, a high calcium:magnesium ratio was associated with increased odds of colorectal adenoma [OR (95% CI): 1.73 (1.27-2.36)] and advanced/multiple adenomas [1.62 (1.05-2.50)], whereas among those with the GC/CC genotypes, high calcium:magnesium ratio was related to reduced odds of colorectal adenoma [0.64 (0.42-0.99)] and advanced/multiple adenomas [0.55 (0.31-1.00)]. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Novel computational methods to design protein-protein interactions

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

    Despite the abundance of structural data, we still cannot accurately predict the structural and energetic changes resulting from mutations at protein interfaces. The inadequacy of current computational approaches to the analysis and design of protein-protein interactions has hampered the development of novel therapeutic and diagnostic agents. In this work, we apply a simple physical model that includes only a minimal set of geometrical constraints, excluded volume, and attractive van der Waals interactions to 1) rank the binding affinity of mutants of tetratricopeptide repeat proteins with their cognate peptides, 2) rank the energetics of binding of small designed proteins to the hydrophobic stem region of the influenza hemagglutinin protein, and 3) predict the stability of T4 lysozyme and staphylococcal nuclease mutants. This work will not only lead to a fundamental understanding of protein-protein interactions, but also to the development of efficient computational methods to rationally design protein interfaces with tunable specificity and affinity, and numerous applications in biomedicine. NSF DMR-1006537, PHY-1019147, Raymond and Beverly Sackler Institute for Biological, Physical and Engineering Sciences, and Howard Hughes Medical Institute.

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

    PubMed

    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 .

  10. The developmentally regulated expression of Menkes protein ATP7A suggests a role in axon extension and synaptogenesis.

    PubMed

    El Meskini, Rajaâ; Cline, Laura B; Eipper, Betty A; Ronnett, Gabriele V

    2005-01-01

    Menkes disease (MD) is a neurodegenerative disorder caused by mutation of the copper transporter ATP7A. While several enzymes expressed in mature neurons require copper, MD neurodegenerative changes cannot be explained by known requirements for ATP7A in neuronal development. To investigate additional roles for ATP7A during development, we characterized its pattern of expression using the olfactory system as a neurodevelopmental model. ATP7A expression in neurons was developmentally regulated rather than constitutively. Initially expressed in the cell bodies of developing neurons, ATP7A protein later shifted to extending axons, peaking prior to synaptogenesis. Similarly, after injury-stimulated neurogenesis, ATP7A expression increased in neurons and axons preceding synaptogenesis. Interestingly, copper-transport-deficient ATP7A still exhibits axonal localization. These results support a role for ATP7A in axon extension, which may contribute to the severe neurodegeneration characteristic of MD.

  11. A protein-protein interaction dictates Borrelial infectivity.

    PubMed

    Thakur, Meghna; Sharma, Kavita; Chao, Kinlin; Smith, Alexis A; Herzberg, Osnat; Pal, Utpal

    2017-06-07

    Two Borrelia burgdorferi interacting proteins, BB0238 and BB0323, play distinct roles in pathogen biology and infectivity although a significance of their interaction remained enigmatic. Here we identified the polypeptide segment essential for BB0238-BB0323 interaction and examined how it supports spirochete infectivity. We show that the interaction region in BB0323 requires amino acid residues 22-200, suggesting that the binding encompasses discontinuous protein segments. In contrast, the interaction region in BB0238 spans only 11 amino acids, residues 120-130. A deletion of these 11 amino acids neither alters the overall secondary structure of the protein, nor affects its stability or oligomerization property, however, it reduces the post-translational stability of the binding partner, BB0323. Mutant B. burgdorferi isolates producing BB0238 lacking the 11-amino acid interaction region were able to persist in ticks but failed to transmit to mice or to establish infection. These results suggest that BB0238-BB0323 interaction is critical for post-translational stability of BB0323, and that this interaction is important for mammalian infectivity and transmission of B. burgdorferi. We show that saturation or inhibition of BB0238-BB0323 interaction could be studied in a luciferase assay, which could be amenable for future identification of small molecule inhibitors to combat B. burgdorferi infection.

  12. Revealing protein-lncRNA interaction.

    PubMed

    Ferrè, Fabrizio; Colantoni, Alessio; Helmer-Citterich, Manuela

    2016-01-01

    Long non-coding RNAs (lncRNAs) are associated to a plethora of cellular functions, most of which require the interaction with one or more RNA-binding proteins (RBPs); similarly, RBPs are often able to bind a large number of different RNAs. The currently available knowledge is already drawing an intricate network of interactions, whose deregulation is frequently associated to pathological states. Several different techniques were developed in the past years to obtain protein-RNA binding data in a high-throughput fashion. In parallel, in silico inference methods were developed for the accurate computational prediction of the interaction of RBP-lncRNA pairs. The field is growing rapidly, and it is foreseeable that in the near future, the protein-lncRNA interaction network will rise, offering essential clues for a better understanding of lncRNA cellular mechanisms and their disease-associated perturbations. © The Author 2015. Published by Oxford University Press.

  13. A 1.7A structure of Fve, a member of the new fungal immunomodulatory protein family.

    PubMed

    Paaventhan, Palasingam; Joseph, Jeremiah S; Seow, See Voon; Vaday, Shai; Robinson, Howard; Chua, Kaw Yan; Kolatkar, Prasanna R

    2003-09-12

    Fve, a major fruiting body protein from Flammulina velutipes, a mushroom possessing immunomodulatory activity, stimulates lymphocyte mitogenesis, suppresses systemic anaphylaxis reactions and edema, enhances transcription of IL-2, IFN-gamma and TNF-alpha, and hemagglutinates red blood cells. It appears to be a lectin with specificity for complex cell-surface carbohydrates. Fve is a non-covalently linked homodimer containing no Cys, His or Met residues. It shares sequence similarity only to the other fungal immunomodulatory proteins (FIPs) LZ-8, Gts, Vvo and Vvl, all of unknown structure. The 1.7A structure of Fve solved by single anomalous diffraction of NaBr-soaked crystals is novel: each monomer consists of an N-terminal alpha-helix followed by a fibronectin III (FNIII) fold. The FNIII fold is the first instance of "pseudo-h-type" topology, a transition between the seven beta-stranded s-type and the eight beta-stranded h-type topologies. The structure suggests that dimerization, critical for the activity of FIPs, occurs by 3-D domain swapping of the N-terminal helices and is stabilized predominantly by hydrophobic interactions. The structure of Fve is the first in this lectin family to be reported, and the first of an FNIII domain-containing protein of fungal origin.

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

    PubMed

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

    2006-04-01

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

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

    PubMed

    Kuchaiev, Oleksii; Rasajski, Marija; Higham, Desmond J; Przulj, Natasa

    2009-08-01

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

  16. Interaction of melanosomal proteins with melanin.

    PubMed

    Donatien, P D; Orlow, S J

    1995-08-15

    Melanin is deposited in melanosomes upon a proteinaceous matrix enveloped by a melanosomal membrane. Since melanin is highly detergent insoluble, we hypothesized that the detergent solubility of proteins of the melanosomal matrix might be inversely related to the state of melanosomal melanization. Immunoblotting analyses were performed on extracts of albino and black melanocytes to test this hypothesis. The protein products of the silver (si) and the pink-eyed-dilution (p) loci as well as other matrix constituents were present at twofold higher levels in extracts of albino cells. When black cells were rendered amelanotic by growing cultures in the presence of the tyrosinase inhibitor phenylthiourea, the apparent levels of these proteins were also increased. To obviate the potential role of different levels of synthesis in contributing to these differences, we developed a cell-free melanosomal melanization assay. Upon incubation of a melanosome-rich fraction with the melanin precursor L-3,4-dihydroxyphenylalanine (Dopa) followed by immunoblot analysis, the si locus protein, the p locus protein, and other putative matrix constituents became rapidly insoluble in SDS when compared with the members of the tyrosinase-related family of melanosomal membrane proteins. Our results suggest that melanosomal proteins that interact with melanin may be identified by their relative insolubility in SDS under conditions of increasing melanization. In addition to the si locus protein and other putative melanosomal matrix proteins, the membrane-bound p locus protein may also interact closely with melanin.

  17. Protein-protein interaction network analysis of cirrhosis liver disease.

    PubMed

    Safaei, Akram; Rezaei Tavirani, Mostafa; Arefi Oskouei, Afsaneh; Zamanian Azodi, Mona; Mohebbi, Seyed Reza; Nikzamir, Abdol Rahim

    2016-01-01

    Evaluation of biological characteristics of 13 identified proteins of patients with cirrhotic liver disease is the main aim of this research. In clinical usage, liver biopsy remains the gold standard for diagnosis of hepatic fibrosis. Evaluation and confirmation of liver fibrosis stages and severity of chronic diseases require a precise and noninvasive biomarkers. Since the early detection of cirrhosis is a clinical problem, achieving a sensitive, specific and predictive novel method based on biomarkers is an important task. Essential analysis, such as gene ontology (GO) enrichment and protein-protein interactions (PPI) was undergone EXPASy, STRING Database and DAVID Bioinformatics Resources query. Based on GO analysis, most of proteins are located in the endoplasmic reticulum lumen, intracellular organelle lumen, membrane-enclosed lumen, and extracellular region. The relevant molecular functions are actin binding, metal ion binding, cation binding and ion binding. Cell adhesion, biological adhesion, cellular amino acid derivative, metabolic process and homeostatic process are the related processes. Protein-protein interaction network analysis introduced five proteins (fibroblast growth factor receptor 4, tropomyosin 4, tropomyosin 2 (beta), lectin, Lectin galactoside-binding soluble 3 binding protein and apolipoprotein A-I) as hub and bottleneck proteins. Our result indicates that regulation of lipid metabolism and cell survival are important biological processes involved in cirrhosis disease. More investigation of above mentioned proteins will provide a better understanding of cirrhosis disease.

  18. Protein-protein interaction network analysis of cirrhosis liver disease

    PubMed Central

    Safaei, Akram; Rezaei Tavirani, Mostafa; Arefi Oskouei, Afsaneh; Zamanian Azodi, Mona; Mohebbi, Seyed Reza; Nikzamir, Abdol Rahim

    2016-01-01

    Aim: Evaluation of biological characteristics of 13 identified proteins of patients with cirrhotic liver disease is the main aim of this research. Background: In clinical usage, liver biopsy remains the gold standard for diagnosis of hepatic fibrosis. Evaluation and confirmation of liver fibrosis stages and severity of chronic diseases require a precise and noninvasive biomarkers. Since the early detection of cirrhosis is a clinical problem, achieving a sensitive, specific and predictive novel method based on biomarkers is an important task. Methods: Essential analysis, such as gene ontology (GO) enrichment and protein-protein interactions (PPI) was undergone EXPASy, STRING Database and DAVID Bioinformatics Resources query. Results: Based on GO analysis, most of proteins are located in the endoplasmic reticulum lumen, intracellular organelle lumen, membrane-enclosed lumen, and extracellular region. The relevant molecular functions are actin binding, metal ion binding, cation binding and ion binding. Cell adhesion, biological adhesion, cellular amino acid derivative, metabolic process and homeostatic process are the related processes. Protein-protein interaction network analysis introduced five proteins (fibroblast growth factor receptor 4, tropomyosin 4, tropomyosin 2 (beta), lectin, Lectin galactoside-binding soluble 3 binding protein and apolipoprotein A-I) as hub and bottleneck proteins. Conclusion: Our result indicates that regulation of lipid metabolism and cell survival are important biological processes involved in cirrhosis disease. More investigation of above mentioned proteins will provide a better understanding of cirrhosis disease. PMID:27099671

  19. Enhancing interacting residue prediction with integrated contact matrix prediction in protein-protein interaction.

    PubMed

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

    2016-12-01

    Identifying the residues in a protein that are involved in protein-protein interaction and identifying the contact matrix for a pair of interacting proteins are two computational tasks at different levels of an in-depth analysis of protein-protein interaction. Various methods for solving these two problems have been reported in the literature. However, the interacting residue prediction and contact matrix prediction were handled by and large independently in those existing methods, though intuitively good prediction of interacting residues will help with predicting the contact matrix. In this work, we developed a novel protein interacting residue prediction system, contact matrix-interaction profile hidden Markov model (CM-ipHMM), with the integration of contact matrix prediction and the ipHMM interaction residue prediction. We propose to leverage what is learned from the contact matrix prediction and utilize the predicted contact matrix as "feedback" to enhance the interaction residue prediction. The CM-ipHMM model showed significant improvement over the previous method that uses the ipHMM for predicting interaction residues only. It indicates that the downstream contact matrix prediction could help the interaction site prediction.

  20. Biospecific protein immobilization for rapid analysis of weak protein interactions using self-interaction nanoparticle spectroscopy.

    PubMed

    Bengali, Aditya N; Tessier, Peter M

    2009-10-01

    "Reversible" protein interactions govern diverse biological behavior ranging from intracellular transport and toxic protein aggregation to protein crystallization and inactivation of protein therapeutics. Much less is known about weak protein interactions than their stronger counterparts since they are difficult to characterize, especially in a parallel format (in contrast to a sequential format) necessary for high-throughput screening. We have recently introduced a highly efficient approach of characterizing protein self-association, namely self-interaction nanoparticle spectroscopy (SINS; Tessier et al., 2008; J Am Chem Soc 130:3106-3112). This approach exploits the separation-dependent optical properties of gold nanoparticles to detect weak self-interactions between proteins immobilized on nanoparticles. A limitation of our previous work is that differences in the sequence and structure of proteins can lead to significant differences in their affinity to adsorb to nanoparticle surfaces, which complicates analysis of the corresponding protein self-association behavior. In this work we demonstrate a highly specific approach for coating nanoparticles with proteins using biotin-avidin interactions to generate protein-nanoparticle conjugates that report protein self-interactions through changes in their optical properties. Using lysozyme as a model protein that is refractory to characterization by conventional SINS, we demonstrate that surface Plasmon wavelengths for gold-avidin-lysozyme conjugates over a range of solution conditions (i.e., pH and ionic strength) are well correlated with lysozyme osmotic second virial coefficient measurements. Since SINS requires orders of magnitude less protein and time than conventional methods (e.g., static light scattering), we envision this approach will find application in large screens of protein self-association aimed at either preventing (e.g., protein aggregation) or promoting (e.g., protein crystallization) these

  1. The lumenal loop M672-P707 of the Menkes protein (ATP7A) transfers copper to peptidylglycine monooxygenase

    SciTech Connect

    Otoikhian, Adenike; Barry, Amanda N.; Mayfield, Mary; Nilges, Mark; Huang, Yiping; Lutsenko, Svetlana; Blackburn, Ninian

    2012-05-14

    Copper transfer to cuproproteins located in vesicular compartments of the secretory pathway depends on activity of the copper translocating ATPase (ATP7A or ATP7B) but the mechanism of transfer is largely unexplored. Copper-ATPase ATP7A is unique in having a sequence rich in histidine and methionine residues located on the lumenal side of the membrane. The corresponding fragment binds Cu(I) when expressed as a chimera with a scaffold protein, and mutations or deletions of His and/or Met residues in its sequence inhibit dephosphorylation of the ATPase, a catalytic step associated with copper release. Here we present evidence for a potential role of this lumenal region of ATP7A in copper transfer to cuproenzymes. Both Cu(II) and Cu(I) forms were investigated since the form in which copper is transferred to acceptor proteins is currently unknown. Analysis of Cu(II) using EPR demonstrated that at Cu:P ratios below 1:1, 15N-substituted protein had Cu(II) bound by 4 His residues, but this coordination changed as the Cu(II) to protein ratio increased towards 2:1. XAS confirmed this coordination via analysis of the intensity of outer-shell scattering from imidazole residues. The Cu(II) complexes could be reduced to their Cu(I) counterparts by ascorbate, but here again, as shown by EXAFS and XANES spectroscopy, the coordination was dependent on copper loading. At low copper Cu(I) was bound by a mixed ligand set of His + Met while at higher ratios His coordination predominated. The copper-loaded loop was able to transfer either Cu(II) or Cu(I) to peptidylglycine monooxygenase in the presence of chelating resin, generating catalytically active enzyme in a process that appeared to involve direct interaction between the two partners. The variation of coordination with copper loading suggests copper-dependent conformational change which in turn could act as a signal for regulating copper release by the ATPase pump.

  2. Effect of the quality of the interaction data on predicting protein function from protein-protein interactions.

    PubMed

    Ni, Qing-Shan; Wang, Zheng-Zhi; Li, Gang-Guo; Wang, Guang-Yun; Zhao, Ying-Jie

    2009-03-01

    Protein function prediction is an important issue in the post-genomic era. When protein function is deduced from protein interaction data, the traditional methods treat each interaction sample equally, where the qualities of the interaction samples are seldom taken into account. In this paper, we investigate the effect of the quality of protein-protein interaction data on predicting protein function. Moreover, two improved methods, weight neighbour counting method (WNC) and weight chi-square method (WCHI), are proposed by considering the quality of interaction samples with the neighbour counting method (NC) and chi-square method (CHI). Experimental results have shown that the qualities of interaction samples affect the performances of protein function prediction methods seriously. It is also demonstrated that WNC and WCHI methods outperform NC and CHI methods in protein function prediction when example weights are chosen properly.

  3. Inferring High-Confidence Human Protein-Protein Interactions

    DTIC Science & Technology

    2012-01-01

    iPfam: visualization of protein-protein interactions in PDB at domain and amino acid resolutions. Bioinformatics 2005, 21(3):410–412. 43. Kanehisa M, Goto...comprised proteins that had the same specific func- tion or were subunits of the same protein complex, such as branched chain keto acid E1 alpha (BCKDHA...and branched chain keto acid E1 beta (BCKDHB) [3,29], and dynein cytoplasmic 2 intermediate chain 1 (D2LIC) and dynein cytoplasmic 2 heavy chain 1

  4. Building protein interaction maps for Down's syndrome.

    PubMed

    Gardiner, Katheleen; Davisson, Muriel T; Crnic, Linda S

    2004-08-01

    Now that the complete sequences for human chromosome 21 and the orthologous mouse genomic regions are known, reasonably complete, conserved, protein-coding gene catalogues are also available. The central issue now facing Down's syndrome researchers is the correlation of increased expression of specific, normal, chromosome 21 genes with the development of specific deficits in learning and memory. Because of the number of candidate genes involved, the number of alternative splice variants of individual genes and the number of pathways in which these genes function, a pathway analysis approach will be critical to success. Here, three examples, both gene specific and pathway related, that would benefit from pathway analysis are discussed: (1) the potential roles of eight chromosome 21 proteins in RNA processing pathways; (2) the chromosome 21 protein intersectin 1 and its domain composition, alternative splicing, protein interactions and functions; and (3) the interactions of ten chromosome 21 proteins with components of the mitogen-activated protein kinase and the calcineurin signalling pathways. A productive approach to developing gene-phenotype correlations in Down's syndrome will make use of known and predicted functions and interactions of chromosome 21 genes to predict pathways that may be perturbed by their increased levels of expression. Investigations may then be targeted in animal models to specific interactions, intermediate steps or end-points of such pathways and the downstream - perhaps amplified - consequences of gene dosage directly assessed. Once pathway perturbations have been identified, the potential for rational design of therapeutics becomes practical.

  5. Predicting protein-peptide interactions from scratch

    NASA Astrophysics Data System (ADS)

    Yan, Chengfei; Xu, Xianjin; Zou, Xiaoqin; Zou lab Team

    Protein-peptide interactions play an important role in many cellular processes. The ability to predict protein-peptide complex structures is valuable for mechanistic investigation and therapeutic development. Due to the high flexibility of peptides and lack of templates for homologous modeling, predicting protein-peptide complex structures is extremely challenging. Recently, we have developed a novel docking framework for protein-peptide structure prediction. Specifically, given the sequence of a peptide and a 3D structure of the protein, initial conformations of the peptide are built through protein threading. Then, the peptide is globally and flexibly docked onto the protein using a novel iterative approach. Finally, the sampled modes are scored and ranked by a statistical potential-based energy scoring function that was derived for protein-peptide interactions from statistical mechanics principles. Our docking methodology has been tested on the Peptidb database and compared with other protein-peptide docking methods. Systematic analysis shows significantly improved results compared to the performances of the existing methods. Our method is computationally efficient and suitable for large-scale applications. Nsf CAREER Award 0953839 (XZ) NIH R01GM109980 (XZ).

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

    PubMed

    Schoenrock, Andrew; Burnside, Daniel; Moteshareie, Houman; Pitre, Sylvain; Hooshyar, Mohsen; Green, James R; Golshani, Ashkan; Dehne, Frank; Wong, Alex

    2017-01-01

    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.

  7. Evolution of protein-protein interaction networks in yeast

    PubMed Central

    Schoenrock, Andrew; Burnside, Daniel; Moteshareie, Houman; Pitre, Sylvain; Hooshyar, Mohsen; Green, James R.; Golshani, Ashkan; Dehne, Frank; Wong, Alex

    2017-01-01

    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. PMID:28248977

  8. Topology of Protein Interaction Network Shapes Protein Abundances and Strengths of Their Functional and Nonspecific Interactions

    SciTech Connect

    Maslov, S.; Heo, M.; Shakhnovich, E.

    2011-03-08

    How do living cells achieve sufficient abundances of functional protein complexes while minimizing promiscuous nonfunctional interactions? Here we study this problem using a first-principle model of the cell whose phenotypic traits are directly determined from its genome through biophysical properties of protein structures and binding interactions in a crowded cellular environment. The model cell includes three independent prototypical pathways, whose topologies of protein-protein interaction (PPI) subnetworks are different, but whose contributions to the cell fitness are equal. Model cells evolve through genotypic mutations and phenotypic protein copy number variations. We found a strong relationship between evolved physical-chemical properties of protein interactions and their abundances due to a 'frustration' effect: Strengthening of functional interactions brings about hydrophobic interfaces, which make proteins prone to promiscuous binding. The balancing act is achieved by lowering concentrations of hub proteins while raising solubilities and abundances of functional monomers. On the basis of these principles we generated and analyzed a possible realization of the proteome-wide PPI network in yeast. In this simulation we found that high-throughput affinity capture-mass spectroscopy experiments can detect functional interactions with high fidelity only for high-abundance proteins while missing most interactions for low-abundance proteins.

  9. Non-interacting proteins may resemble interacting proteins: prevalence and implications

    PubMed Central

    Launay, Guillaume; Ceres, Nicoletta; Martin, Juliette

    2017-01-01

    The vast majority of proteins do not form functional interactions in physiological conditions. We have considered several sets of protein pairs from S. cerevisiae with no functional interaction reported, denoted as non-interacting pairs, and compared their 3D structures to available experimental complexes. We identified some non-interacting pairs with significant structural similarity with experimental complexes, indicating that, even though they do not form functional interactions, they have compatible structures. We estimate that up to 8.7% of non-interacting protein pairs could have compatible structures. This number of interactions exceeds the number of functional interactions (around 0.2% of the total interactions) by a factor 40. Network analysis suggests that the interactions formed by non-interacting pairs with compatible structures could be particularly hazardous to the protein-protein interaction network. From a structural point of view, these interactions display no aberrant structural characteristics, and are even predicted as relatively stable and enriched in potential physical interactors, suggesting a major role of regulation to prevent them. PMID:28084410

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

    PubMed

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

    2015-01-01

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

  11. The binary protein-protein interaction landscape of Escherichia coli

    PubMed Central

    Rajagopala, Seesandra V.; Vlasblom, James; Arnold, Roland; Franca-Koh, Jonathan; Pakala, Suman B.; Phanse, Sadhna; Ceol, Arnaud; Häuser, Roman; Siszler, Gabriella; Wuchty, Stefan; Emili, Andrew; Babu, Mohan; Aloy, Patrick; Pieper, Rembert; Uetz, Peter

    2014-01-01

    Efforts to map the Escherichia coli interactome have identified several hundred macromolecular complexes, but direct binary protein-protein interactions (PPIs) have not been surveyed on a large scale. Here we performed yeast two-hybrid screens of 3,305 baits against 3,606 preys (~70% of the E. coli proteome) in duplicate to generate a map of 2,234 interactions, approximately doubling the number of known binary PPIs in E. coli. Integration of binary PPIs and genetic interactions revealed functional dependencies among components involved in cellular processes, including envelope integrity, flagellum assembly and protein quality control. Many of the binary interactions that could be mapped within multi-protein complexes were informative regarding internal topology and indicated that interactions within complexes are significantly more conserved than those interactions connecting different complexes. This resource will be useful for inferring bacterial gene function and provides a draft reference of the basic physical wiring network of this evolutionarily significant model microbe. PMID:24561554

  12. Protein-protein interaction network of celiac disease

    PubMed Central

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

    2016-01-01

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

  13. KFC Server: interactive forecasting of protein interaction hot spots.

    PubMed

    Darnell, Steven J; LeGault, Laura; Mitchell, Julie C

    2008-07-01

    The KFC Server is a web-based implementation of the KFC (Knowledge-based FADE and Contacts) model-a machine learning approach for the prediction of binding hot spots, or the subset of residues that account for most of a protein interface's; binding free energy. The server facilitates the automated analysis of a user submitted protein-protein or protein-DNA interface and the visualization of its hot spot predictions. For each residue in the interface, the KFC Server characterizes its local structural environment, compares that environment to the environments of experimentally determined hot spots and predicts if the interface residue is a hot spot. After the computational analysis, the user can visualize the results using an interactive job viewer able to quickly highlight predicted hot spots and surrounding structural features within the protein structure. The KFC Server is accessible at http://kfc.mitchell-lab.org.

  14. [Methods for analysis of protein-protein and protein-ligand interactions].

    PubMed

    Durech, M; Trčka, F; Vojtěšek, B; Müller, P

    2014-01-01

    In order to maintain cellular homeostasis, cellular proteins coexist in complex and variable molecular assemblies. Therefore, understanding of major physiological processes at molecular level is based on analysis of protein-protein interaction networks. Firstly, composition of the molecular assembly has to be qualitatively analyzed. In the next step, quantitative bio-chemical properties of the identified protein-protein interactions are determined. Detailed information about the protein-protein interaction interface can be obtained by crystallographic methods. Accordingly, the insight into the molecular architecture of these protein-protein complexes allows us to rationally design new synthetic compounds that specifically influence various physiological or pathological processes by targeted modulation of protein interactions. This review is focused on description of the most used methods applied in both qualitative and quantitative analysis of protein-protein interactions. Co- immunoprecipitation and affinity co- precipitation are basic methods designed for qualitative analysis of protein binding partners. Further bio-chemical analysis of the interaction requires definition of kinetic and thermodynamic parameters. Surface plasmon resonance (SPR) is used for description of affinity and kinetic profile of the interaction, fluorescence polarization (FP) method for fast determination of inhibition potential of inhibitors and isothermal titration calorimetry (ITC) for definition of thermodynamic parameters of the interaction (G, H and S). Besides the importance of uncovering the molecular basis of protein interactions for basic research, the same methodological approaches open new possibilities in rational design of novel therapeutic agents.

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

    NASA Astrophysics Data System (ADS)

    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

  16. Annotation and retrieval in protein interaction databases

    NASA Astrophysics Data System (ADS)

    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.

  17. Thermosensing via transmembrane protein-lipid interactions.

    PubMed

    Saita, Emilio A; de Mendoza, Diego

    2015-09-01

    Cell membranes are composed of a lipid bilayer containing proteins that cross and/or interact with lipids on either side of the two leaflets. The basic structure of cell membranes is this bilayer, composed of two opposing lipid monolayers with fascinating properties designed to perform all the functions the cell requires. To coordinate these functions, lipid composition of cellular membranes is tailored to suit their specialized tasks. In this review, we describe the general mechanisms of membrane-protein interactions and relate them to some of the molecular strategies organisms use to adjust the membrane lipid composition in response to a decrease in environmental temperature. While the activities of all biomolecules are altered as a function of temperature, the thermosensors we focus on here are molecules whose temperature sensitivity appears to be linked to changes in the biophysical properties of membrane lipids. This article is part of a Special Issue entitled: Lipid-protein interactions.

  18. The Usher 1B protein, MYO7A, is required for normal localization and function of the visual retinoid cycle enzyme, RPE65

    PubMed Central

    Lopes, Vanda S.; Gibbs, Daniel; Libby, Richard T.; Aleman, Tomas S.; Welch, Darcy L.; Lillo, Concepción; Jacobson, Samuel G.; Radu, Roxana A.; Steel, Karen P.; Williams, David S.

    2011-01-01

    Mutations in the MYO7A gene cause a deaf-blindness disorder, known as Usher syndrome 1B.  In the retina, the majority of MYO7A is in the retinal pigmented epithelium (RPE), where many of the reactions of the visual retinoid cycle take place.  We have observed that the retinas of Myo7a-mutant mice are resistant to acute light damage. In exploring the basis of this resistance, we found that Myo7a-mutant mice have lower levels of RPE65, the RPE isomerase that has a key role in the retinoid cycle.  We show for the first time that RPE65 normally undergoes a light-dependent translocation to become more concentrated in the central region of the RPE cells.  This translocation requires MYO7A, so that, in Myo7a-mutant mice, RPE65 is partly mislocalized in the light.  RPE65 is degraded more quickly in Myo7a-mutant mice, perhaps due to its mislocalization, providing a plausible explanation for its lower levels.  Following a 50–60% photobleach, Myo7a-mutant retinas exhibited increased all-trans-retinyl ester levels during the initial stages of dark recovery, consistent with a deficiency in RPE65 activity.  Lastly, MYO7A and RPE65 were co-immunoprecipitated from RPE cell lysate by antibodies against either of the proteins, and the two proteins were partly colocalized, suggesting a direct or indirect interaction.  Together, the results support a role for MYO7A in the translocation of RPE65, illustrating the involvement of a molecular motor in the spatiotemporal organization of the retinoid cycle in vision. PMID:21493626

  19. Lethality and entropy of protein interaction networks.

    PubMed

    Manke, Thomas; Demetrius, Lloyd; Vingron, Martin

    2005-01-01

    We characterize protein interaction networks in terms of network entropy. This approach suggests a ranking principle, which strongly correlates with elements of functional importance, such as lethal proteins. Our combined analysis of protein interaction networks and functional profiles in single cellular yeast and multi-cellular worm shows that proteins with large contribution to network entropy are preferentially lethal. While entropy is inherently a dynamical concept, the present analysis incorporates only structural information. Our result therefore highlights the importance of topological features, which appear as correlates of an underlying dynamical property, and which in turn determine functional traits. We argue that network entropy is a natural extension of previously studied observables, such as pathway multiplicity and centrality. It is also applicable to networks in which the processes can be quantified and therefore serves as a link to study questions of structural and dynamical robustness in a unified way.

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

    PubMed Central

    Mezhoud, Karim; Sghaier, Haïtham; Barkallah, Insaf

    2009-01-01

    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. PMID:19356244

  1. Hash subgraph pairwise kernel for protein-protein interaction extraction.

    PubMed

    Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng

    2012-01-01

    Extracting protein-protein interaction (PPI) from biomedical literature is an important task in biomedical text mining (BioTM). In this paper, we propose a hash subgraph pairwise (HSP) kernel-based approach for this task. The key to the novel kernel is to use the hierarchical hash labels to express the structural information of subgraphs in a linear time. We apply the graph kernel to compute dependency graphs representing the sentence structure for protein-protein interaction extraction task, which can efficiently make use of full graph structural information, and particularly capture the contiguous topological and label information ignored before. We evaluate the proposed approach on five publicly available PPI corpora. The experimental results show that our approach significantly outperforms all-path kernel approach on all five corpora and achieves state-of-the-art performance.

  2. [Chemical libraries dedicated to protein-protein interactions].

    PubMed

    Sperandio, Olivier; Villoutreix, Bruno O; Morelli, Xavier; Roche, Philippe

    2015-03-01

    The identification of complete networks of protein-protein interactions (PPI) within a cell has contributed to major breakthroughs in understanding biological pathways, host-pathogen interactions and cancer development. As a consequence, PPI have emerged as a new class of promising therapeutic targets. However, they are still considered as a challenging class of targets for drug discovery programs. Recent successes have allowed the characterization of structural and physicochemical properties of protein-protein interfaces leading to a better understanding of how they can be disrupted with small molecule compounds. In addition, characterization of the profiles of PPI inhibitors has allowed the development of PPI-focused libraries. In this review, we present the current efforts at developing chemical libraries dedicated to these innovative targets. © 2015 médecine/sciences – Inserm.

  3. A method for predicting protein-protein interaction types.

    PubMed

    Silberberg, Yael; Kupiec, Martin; Sharan, Roded

    2014-01-01

    Protein-protein interactions (PPIs) govern basic cellular processes through signal transduction and complex formation. The diversity of those processes gives rise to a remarkable diversity of interactions types, ranging from transient phosphorylation interactions to stable covalent bonding. Despite our increasing knowledge on PPIs in humans and other species, their types remain relatively unexplored and few annotations of types exist in public databases. Here, we propose the first method for systematic prediction of PPI type based solely on the techniques by which the interaction was detected. We show that different detection methods are better suited for detecting specific types. We apply our method to ten interaction types on a large scale human PPI dataset. We evaluate the performance of the method using both internal cross validation and external data sources. In cross validation, we obtain an area under receiver operating characteristic (ROC) curve ranging from 0.65 to 0.97 with an average of 0.84 across the predicted types. Comparing the predicted interaction types to external data sources, we obtained significant agreements for phosphorylation and ubiquitination interactions, with hypergeometric p-value = 2.3e(-54) and 5.6e(-28) respectively. We examine the biological relevance of our predictions using known signaling pathways and chart the abundance of interaction types in cell processes. Finally, we investigate the cross-relations between different interaction types within the network and characterize the discovered patterns, or motifs. We expect the resulting annotated network to facilitate the reconstruction of process-specific subnetworks and assist in predicting protein function or interaction.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    PubMed

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

    2010-01-01

    Förster (or Fluorescence) resonance energy transfer (FRET) is a physical process in which energy is transferred nonradiatively from an excited fluorophore, serving as a donor, to another chromophore (acceptor). Among the techniques related to fluorescence microscopy, FRET is unique in providing signals sensitive to intra- and intermolecular distances in the 1-10 nm range. Because of its potency, FRET is increasingly used to visualize and quantify the dynamics of protein-protein interaction in living cells, with high spatio-temporal resolution. Here we describe the physical bases of FRET, detailing the principal methods applied: (1) measurement of signal intensity and (2) analysis of fluorescence lifetime (FLIM). Although several technical complications must be carefully considered, both methods can be applied fruitfully to specific fields. For example, FRET based on intensity detection is more suitable to follow biological phenomena at a finely tuned spatial and temporal scale. Furthermore, a specific fluorescence signal occurring close to the plasma membrane (< or = 100 nm) can be obtained using a total internal reflection fluorescence (TIRF) microscopy system. When performing FRET experiments, care must be also taken to the method chosen for labeling interacting proteins. Two principal tools can be applied: (1) fluorophore tagged antibodies; (2) recombinant fluorescent fusion proteins. The latter method essentially takes advantage of the discovery and use of spontaneously fluorescent proteins, like the green fluorescent protein (GFP). Until now, FRET has been widely used to analyze the structural characteristics of several proteins, including integrins and ion channels. More recently, this method has been applied to clarify the interaction dynamics of these classes of membrane proteins with cytosolic signaling proteins. We report two examples in which the interaction dynamics between integrins and ion channels have been studied with FRET methods. Using

  6. Interaction site prediction by structural similarity to neighboring clusters in protein-protein interaction networks.

    PubMed

    Monji, Hiroyuki; Koizumi, Satoshi; Ozaki, Tomonobu; Ohkawa, Takenao

    2011-02-15

    Recently, revealing the function of proteins with protein-protein interaction (PPI) networks is regarded as one of important issues in bioinformatics. With the development of experimental methods such as the yeast two-hybrid method, the data of protein interaction have been increasing extremely. Many databases dealing with these data comprehensively have been constructed and applied to analyzing PPI networks. However, few research on prediction interaction sites using both PPI networks and the 3D protein structures complementarily has explored. We propose a method of predicting interaction sites in proteins with unknown function by using both of PPI networks and protein structures. For a protein with unknown function as a target, several clusters are extracted from the neighboring proteins based on their structural similarity. Then, interaction sites are predicted by extracting similar sites from the group of a protein cluster and the target protein. Moreover, the proposed method can improve the prediction accuracy by introducing repetitive prediction process. The proposed method has been applied to small scale dataset, then the effectiveness of the method has been confirmed. The challenge will now be to apply the method to large-scale datasets.

  7. Modulators of 14-3-3 Protein-Protein Interactions.

    PubMed

    Stevers, Loes M; Sijbesma, Eline; Botta, Maurizio; MacKintosh, Carol; Obsil, Tomas; Landrieu, Isabelle; Cau, Ylenia; Wilson, Andrew J; Karawajczyk, Anna; Eickhoff, Jan; Davis, Jeremy; Hann, Michael M; O'Mahony, Gavin; Doveston, Richard G; Brunsveld, Luc; Ottmann, Christian

    2017-10-02

    Direct interactions between proteins are essential for the regulation of their functions in biological pathways. Targeting the complex network of protein-protein interactions (PPIs) has now been widely recognized as an attractive means to therapeutically intervene in disease states. Even though this is a challenging endeavor and PPIs have long been regarded as 'undruggable' targets, the last two decades have seen an increasing number of successful examples of PPI modulators resulting in a growing interest in this field. PPI modulation requires novel approaches and the integrated efforts of multiple disciplines to be a fruitful strategy. This Perspective focuses on the hub protein 14-3-3, which has several hundred identified protein interaction partners and is therefore involved in a wide range of cellular processes and diseases. Here, we aim to provide an integrated overview of the approaches explored for the modulation of 14-3-3 PPIs and review the examples resulting from these efforts in both inhibiting and stabilizing specific 14-3-3 protein complexes by small molecules, peptide-mimetics and natural products.

  8. Structural biology and drug discovery for protein-protein interactions.

    PubMed

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

    2012-05-01

    Although targeting protein-protein interfaces of regulatory multiprotein complexes has become a significant focus in drug discovery, it continues to pose major challenges. Most interfaces would be classed as 'undruggable' by conventional analyses, as they tend to be large, flat and featureless. Over the past decade, encouragement has come from the discovery of hotspots that contribute much of the free energy of interaction, and this has led to the development of tethering methods that target small molecules to these sites, often inducing adaptive changes. Equally important has been the recognition that many protein-protein interactions involve a continuous epitope of one partner and a well-defined groove or series of specific small pockets. These observations have stimulated the development of stapled α-helical peptides and other proteomimetic approaches. They have also led to the realisation that fragments might gain low-affinity 'footholds' on some protein-protein interfaces, and that these fragments might be elaborated to useful modulators of the interactions.

  9. Targeting Protein-Protein Interactions for Parasite Control

    PubMed Central

    Taylor, Christina M.; Fischer, Kerstin; Abubucker, Sahar; Wang, Zhengyuan; Martin, John; Jiang, Daojun; Magliano, Marc; Rosso, Marie-Noëlle; Li, Ben-Wen; Fischer, Peter U.; Mitreva, Makedonka

    2011-01-01

    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 ortholgous 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 applicable. PMID

  10. The fragility of protein-protein interaction networks

    NASA Astrophysics Data System (ADS)

    Schneider, C. M.; Andrade, R. F. S.; Shinbrot, T.; Herrmann, H. J.

    2011-07-01

    The capacity to resist perturbations from the environment is crucial to the survival of all organisms. We quantitatively analyze the susceptibility of protein interaction networks of numerous organisms to random and targeted failures. We find for all organisms studied that random rewiring improves protein network robustness, so that actual networks are more fragile than rewired surrogates. This unexpected fragility contrasts with the behavior of networks such as the Internet, whose robustness decreases with random rewiring. We trace this surprising effect to the modular structure of protein networks.

  11. Quantitative study of protein-protein interactions by quartz nanopipettes

    NASA Astrophysics Data System (ADS)

    Tiwari, Purushottam Babu; Astudillo, Luisana; Miksovska, Jaroslava; Wang, Xuewen; Li, Wenzhi; Darici, Yesim; He, Jin

    2014-08-01

    In this report, protein-modified quartz nanopipettes were used to quantitatively study protein-protein interactions in attoliter sensing volumes. As shown by numerical simulations, the ionic current through the conical-shaped nanopipette is very sensitive to the surface charge variation near the pore mouth. With the appropriate modification of negatively charged human neuroglobin (hNgb) onto the inner surface of a nanopipette, we were able to detect concentration-dependent current change when the hNgb-modified nanopipette tip was exposed to positively charged cytochrome c (Cyt c) with a series of concentrations in the bath solution. Such current change is due to the adsorption of Cyt c to the inner surface of the nanopipette through specific interactions with hNgb. In contrast, a smaller current change with weak concentration dependence was observed when Cyt c was replaced with lysozyme, which does not specifically bind to hNgb. The equilibrium dissociation constant (KD) for the Cyt c-hNgb complex formation was derived and the value matched very well with the result from surface plasmon resonance measurement. This is the first quantitative study of protein-protein interactions by a conical-shaped nanopore based on charge sensing. Our results demonstrate that nanopipettes can potentially be used as a label-free analytical tool to quantitatively characterize protein-protein interactions.In this report, protein-modified quartz nanopipettes were used to quantitatively study protein-protein interactions in attoliter sensing volumes. As shown by numerical simulations, the ionic current through the conical-shaped nanopipette is very sensitive to the surface charge variation near the pore mouth. With the appropriate modification of negatively charged human neuroglobin (hNgb) onto the inner surface of a nanopipette, we were able to detect concentration-dependent current change when the hNgb-modified nanopipette tip was exposed to positively charged cytochrome c (Cyt c) with

  12. Self diffusion of interacting membrane proteins.

    PubMed Central

    Abney, J R; Scalettar, B A; Owicki, J C

    1989-01-01

    A two-dimensional version of the generalized Smoluchowski equation is used to analyze the time (or distance) dependent self diffusion of interacting membrane proteins in concentrated membrane systems. This equation provides a well established starting point for descriptions of the diffusion of particles that interact through both direct and hydrodynamic forces; in this initial work only the effects of direct interactions are explicitly considered. Data describing diffusion in the presence of hard-core repulsions, soft repulsions, and soft repulsions with weak attractions are presented. The effect that interactions have on the self-diffusion coefficient of a real protein molecule from mouse liver gap junctions is also calculated. The results indicate that self diffusion is always inhibited by direct interactions; this observation is interpreted in terms of the caging that will exist at finite protein concentration. It is also noted that, over small distance scales, the diffusion coefficient is determined entirely by the very strong Brownian forces; therefore, as a function of displacement the self-diffusion coefficient decays (rapidly) from its value at infinite dilution to its steady-state interaction-averaged value. The steady-state self-diffusion coefficient describes motion over distance scales that range from approximately 10 nm to cellular dimensions and is the quantity measured in fluorescence recovery after photobleaching experiments. The short-ranged behavior of the diffusion coefficient is important on the interparticle-distance scale and may therefore influence the rate at which nearest-neighbor collisional processes take place. The hard-disk theoretical results presented here are in excellent agreement with lattice Monte-Carlo results obtained by other workers. The concentration dependence of experimentally measured diffusion coefficients of antibody-hapten complexes bound to the membrane surface is consistent with that predicted by the theory. The

  13. Host interactions of Chandipura virus matrix protein.

    PubMed

    Rajasekharan, Sreejith; Kumar, Kapila; Rana, Jyoti; Gupta, Amita; Chaudhary, Vijay K; Gupta, Sanjay

    2015-09-01

    The rhabdovirus matrix (M) protein is a multifunctional virion protein that plays major role in virus assembly and budding, virus-induced inhibition of host gene expression and cytopathic effects observed in infected cells. The myriad roles played by this protein in the virus biology make it a critical player in viral pathogenesis. Therefore, discerning the interactions of this protein with host can greatly facilitate our understanding of virus infections, ultimately leading to both improved therapeutics and insight into cellular processes. Chandipura virus (CHPV; Family Rhabdoviridae, Genus Vesiculovirus) is an emerging rhabdovirus responsible for several outbreaks of fatal encephalitis among children in India. The present study aims to screen the human fetal brain cDNA library for interactors of CHPV M protein using yeast two-hybrid system. Ten host protein interactors were identified, three of which were further validated by affinity pull down and protein interaction ELISA. The study identified novel human host interactors for CHPV which concurred with previously described associations in other human viruses.

  14. Carbohydrate–Aromatic Interactions in Proteins

    PubMed Central

    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

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

    PubMed

    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.

  16. Measuring Protein Interactions by Optical Biosensors.

    PubMed

    Zhao, Huaying; Boyd, Lisa F; Schuck, Peter

    2017-04-03

    This unit gives an introduction to the basic techniques of optical biosensing for measuring equilibrium and kinetics of reversible protein interactions. Emphasis is placed on description of robust approaches that will provide reliable results with few assumptions. How to avoid the most commonly encountered problems and artifacts is also discussed. © 2017 by John Wiley & Sons, Inc.

  17. Finding protein-protein interaction patterns by contact map matching.

    PubMed

    Melo, R C; Ribeiro, C; Murray, C S; Veloso, C J M; da Silveira, C H; Neshich, G; Meira, W; Carceroni, R L; Santoro, M M

    2007-10-05

    We propose a novel method for defining patterns of contacts present in protein-protein complexes. A new use of the traditional contact maps (more frequently used for representation of the intra-chain contacts) is presented for analysis of inter-chain contacts. Using an algorithm based on image processing techniques, we can compare protein-protein interaction maps and also obtain a dissimilarity score between them. The same algorithm used to compare the maps can align the contacts of all the complexes and be helpful in the determination of a pattern of conserved interactions at the interfaces. We present an example for the application of this method by analyzing the pattern of interaction of bovine pancreatic trypsin inhibitors and trypsins, chymotrypsins, a thrombin, a matriptase, and a kallikrein - all classified as serine proteases. We found 20 contacts conserved in trypsins and chymotrypsins and 3 specific ones are present in all the serine protease complexes studied. The method was able to identify important contacts for the protein family studied and the results are in agreement with the literature.

  18. Experimental and bioinformatic approaches for interrogating protein-protein interactions to determine protein function.

    PubMed

    Droit, Arnaud; Poirier, Guy G; Hunter, Joanna M

    2005-04-01

    An ambitious goal of proteomics is to elucidate the structure, interactions and functions of all proteins within cells and organisms. One strategy to determine protein function is to identify the protein-protein interactions. The increasing use of high-throughput and large-scale bioinformatics-based studies has generated a massive amount of data stored in a number of different databases. A challenge for bioinformatics is to explore this disparate data and to uncover biologically relevant interactions and pathways. In parallel, there is clearly a need for the development of approaches that can predict novel protein-protein interaction networks in silico. Here, we present an overview of different experimental and bioinformatic methods to elucidate protein-protein interactions.

  19. Dynamic network analysis of protein interactions

    NASA Astrophysics Data System (ADS)

    Almaas, Eivind; Deri, Joya

    2007-03-01

    Network approaches have recently become a popular tool to study complex systems such as cellular metabolism and protein interactions. A substantial number of analyses of the protein interaction network (PIN) of the yeast Saccharomyces cerevisiae have considered this network as a static entity, not taking the network's dynamic nature into account. Here, we examine the time-variation of gene regulation superimposed on the PIN by defining mRNA expression profiles throughout the cell cycle as node weights. To characterize these network dynamics, we have both developed a set of novel network measures as well as studied previously published measures for weighted networks. We expect that our approach will provide a deeper understanding of protein regulation during the cell cycle.

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

    PubMed

    Goodfellow, Ian; Bailey, Dalan

    2014-01-01

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

  1. Integrating protein-protein interaction networks with phenotypes reveals signs of interactions

    PubMed Central

    Vinayagam, Arunachalam; Zirin, Jonathan; Roesel, Charles; Hu, Yanhui; Yilmazel, Bahar; Samsonova, Anastasia A.; Neumüller, Ralph A.; Mohr, Stephanie E.; Perrimon, Norbert

    2013-01-01

    A major objective of systems biology is to organize molecular interactions as networks and to characterize information-flow within networks. We describe a computational framework to integrate protein-protein interaction (PPI) networks and genetic screens to predict the “signs” of interactions (i.e. activation/inhibition relationships). We constructed a Drosophila melanogaster signed PPI network, consisting of 6,125 signed PPIs connecting 3,352 proteins that can be used to identify positive and negative regulators of signaling pathways and protein complexes. We identified an unexpected role for the metabolic enzymes Enolase and Aldo-keto reductase as positive and negative regulators of proteolysis, respectively. Characterization of the activation/inhibition relationships between physically interacting proteins within signaling pathways will impact our understanding of many biological functions, including signal transduction and mechanisms of disease. PMID:24240319

  2. Prediction of protein-protein interactions by combining structure and sequence conservation in protein interfaces.

    PubMed

    Aytuna, A Selim; Gursoy, Attila; Keskin, Ozlem

    2005-06-15

    Elucidation of the full network of protein-protein interactions is crucial for understanding of the principles of biological systems and processes. Thus, there is a need for in silico methods for predicting interactions. We present a novel algorithm for automated prediction of protein-protein interactions that employs a unique bottom-up approach combining structure and sequence conservation in protein interfaces. Running the algorithm on a template dataset of 67 interfaces and a sequentially non-redundant dataset of 6170 protein structures, 62 616 potential interactions are predicted. These interactions are compared with the ones in two publicly available interaction databases (Database of Interacting Proteins and Biomolecular Interaction Network Database) and also the Protein Data Bank. A significant number of predictions are verified in these databases. The unverified ones may correspond to (1) interactions that are not covered in these databases but known in literature, (2) unknown interactions that actually occur in nature and (3) interactions that do not occur naturally but may possibly be realized synthetically in laboratory conditions. Some unverified interactions, supported significantly with studies found in the literature, are discussed. http://gordion.hpc.eng.ku.edu.tr/prism agursoy@ku.edu.tr; okeskin@ku.edu.tr.

  3. Evolutionary Capacitance and Control of Protein Stability in Protein-Protein Interaction Networks

    PubMed Central

    Dixit, Purushottam D.; Maslov, Sergei

    2013-01-01

    In addition to their biological function, protein complexes reduce the exposure of the constituent proteins to the risk of undesired oligomerization by reducing the concentration of the free monomeric state. We interpret this reduced risk as a stabilization of the functional state of the protein. We estimate that protein-protein interactions can account for of additional stabilization; a substantial contribution to intrinsic stability. We hypothesize that proteins in the interaction network act as evolutionary capacitors which allows their binding partners to explore regions of the sequence space which correspond to less stable proteins. In the interaction network of baker's yeast, we find that statistically proteins that receive higher energetic benefits from the interaction network are more likely to misfold. A simplified fitness landscape wherein the fitness of an organism is inversely proportional to the total concentration of unfolded proteins provides an evolutionary justification for the proposed trends. We conclude by outlining clear biophysical experiments to test our predictions. PMID:23592969

  4. Semaphorin 7A protein variants differentially regulate T-cell activity.

    PubMed

    Gras, Christiane; Eiz-Vesper, Britta; Seltsam, Axel; Immenschuh, Stephan; Blasczyk, Rainer; Figueiredo, Constança

    2013-02-01

    Semaphorin 7A (Sema7A) carries the John-Milton-Hagen human blood group antigen on red blood cells and shows molecular diversity. It is known that Sema7A has immunomodulatory functions, but its regulatory effects on T-cell activation are not completely understood. In this study, the functional role of the R461C Sema7A polymorphism on T-cell responses was investigated. Soluble recombinant wild-type Sema7A (Sema7A_wt) and its R461C variant (Sema7A_R461C) were produced in human embryonic kidney cells. Specific assays were performed to determine the effects of Sema7A_wt and Sema7A_R461C on T-cell activation in terms of proliferation, phenotypic alterations, granzyme B transcript levels, and secretion of proinflammatory cytokines. Sema7A_wt did not affect T-cell activity, but Sema7A_R461C led to marked antigen-independent activation of T cells. In the presence of antigen stimulation, Sema7A_R461C had a major costimulatory effect on T-cell response. Upon Sema7A_R461C stimulation, CD4+ T cells strongly proliferated and exhibited a cytotoxic phenotype with significant up regulation of granzyme B transcripts (up to 220-fold), even in the absence of antigen stimulation. Antibody blocking studies indicated that Sema7A_R461C-mediated T-cell activation is largely β1 integrin dependent. These data demonstrate that Sema7A_R461C, unlike wild-type Sema7A, causes differential regulation of T-cell responses. Since Sema7A has important immunomodulatory functions in inflammatory responses, it might play a key role in autoimmune diseases and other major disorders. Further studies are needed to elucidate the regulatory role of Sema7A and its variants. © 2012 American Association of Blood Banks.

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

    PubMed Central

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

    2013-01-01

    While protein-surface interactions have been widely studied, relatively little is understood at this time regarding how protein-surface interaction effects are influenced by protein-protein interactions and how these effects combine with the internal stability of a protein to influence its adsorbed-state structure and bioactivity. The objectives of this study were to develop a method to study these combined effects under widely varying protein-protein interaction conditions using hen egg-white lysozyme (HEWL) adsorbed on silica glass, poly(methyl methacrylate), and polyethylene as our model systems. In order to vary protein-protein interaction effects over a wide range, HEWL was first adsorbed to each surface type under widely varying protein solution concentrations for 2 h to saturate the surface, followed by immersion in pure buffer solution for 15 h to equilibrate the adsorbed protein layers in the absence of additionally adsorbing protein. Periodic measurements were made at selected time points of the areal density of the adsorbed protein layer as an indicator of the level of protein-protein interaction effects within the layer, and these values were then correlated with measurements of the adsorbed protein’s secondary structure and bioactivity. The results from these studies indicate that protein-protein interaction effects help stabilize the structure of HEWL adsorbed on silica glass, have little influence on the structural behavior of HEWL on HDPE, and actually serve to destabilize HEWL’s structure on PMMA. The bioactivity of HEWL on silica glass and HDPE was found to decrease in direct proportion to the degree of adsorption-induce protein unfolding. A direct correlation between bioactivity and the conformational state of adsorbed HEWL was less apparent on PMMA, thus suggesting that other factors influenced HEWL’s bioactivity on this surface, such as the accessibility of HEWL’s bioactive site being blocked by neighboring proteins or the surface

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

    PubMed Central

    Ekman, Diana; Light, Sara; Björklund, Åsa 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 interaction network of Saccharomyces cerevisiae. Results The many interactions of hub proteins can only partly be explained by bindings to similar proteins or domains. It is evident that domain repeats, which are associated with binding, are enriched in hubs. Moreover, there is an over representation of multi-domain proteins and long proteins among the hubs. In addition, there are clear differences between party hubs and date hubs. Fewer of the party hubs contain long disordered regions compared to date hubs, indicating that these regions are important for flexible binding but less so for static interactions. Furthermore, party hubs interact to a large extent with each other, supporting the idea of party hubs as the cores of highly clustered functional modules. In addition, hub proteins, and in particular party hubs, are more often ancient. Finally, the more recent paralogs of party hubs are underrepresented. Conclusion Our results indicate that multiple and repeated domains are enriched in hub proteins and, further, that long disordered regions, which are common in date hubs, are particularly important for flexible binding. PMID:16780599

  7. Tools for controlling protein interactions using light.

    PubMed

    Tucker, Chandra L; Vrana, Justin D; Kennedy, Matthew J

    2014-09-02

    Genetically encoded actuators that allow control of protein-protein interactions using light, termed 'optical dimerizers', are emerging as new tools for experimental biology. In recent years, numerous new and versatile dimerizer systems have been developed. Here we discuss the design of optical dimerizer experiments, including choice of a dimerizer system, photoexcitation sources, and the coordinate use of imaging reporters. We provide detailed protocols for experiments using two dimerization systems we previously developed, CRY2/CIB and UVR8/UVR8, for use in controlling transcription, protein localization, and protein secretion using light. Additionally, we provide instructions and software for constructing a pulse-controlled LED device for use in experiments requiring extended light treatments.

  8. Tools for controlling protein interactions with light

    PubMed Central

    Tucker, Chandra L.; Vrana, Justin D.; Kennedy, Matthew J.

    2014-01-01

    Genetically-encoded actuators that allow control of protein-protein interactions with light, termed ‘optical dimerizers’, are emerging as new tools for experimental biology. In recent years, numerous new and versatile dimerizer systems have been developed. Here we discuss the design of optical dimerizer experiments, including choice of a dimerizer system, photoexcitation sources, and coordinate use of imaging reporters. We provide detailed protocols for experiments using two dimerization systems we previously developed, CRY2/CIB and UVR8/UVR8, for use controlling transcription, protein localization, and protein secretion with light. Additionally, we provide instructions and software for constructing a pulse-controlled LED light device for use in experiments requiring extended light treatments. PMID:25181301

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

    PubMed Central

    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

  10. KFC Server: interactive forecasting of protein interaction hot spots

    PubMed Central

    Darnell, Steven J.; LeGault, Laura; Mitchell, Julie C.

    2008-01-01

    The KFC Server is a web-based implementation of the KFC (Knowledge-based FADE and Contacts) model—a machine learning approach for the prediction of binding hot spots, or the subset of residues that account for most of a protein interface's; binding free energy. The server facilitates the automated analysis of a user submitted protein–protein or protein–DNA interface and the visualization of its hot spot predictions. For each residue in the interface, the KFC Server characterizes its local structural environment, compares that environment to the environments of experimentally determined hot spots and predicts if the interface residue is a hot spot. After the computational analysis, the user can visualize the results using an interactive job viewer able to quickly highlight predicted hot spots and surrounding structural features within the protein structure. The KFC Server is accessible at http://kfc.mitchell-lab.org. PMID:18539611

  11. Alignment-free protein interaction network comparison

    PubMed Central

    Ali, Waqar; Rito, Tiago; Reinert, Gesine; Sun, Fengzhu; Deane, Charlotte M.

    2014-01-01

    Motivation: Biological network comparison software largely relies on the concept of alignment where close matches between the nodes of two or more networks are sought. These node matches are based on sequence similarity and/or interaction patterns. However, because of the incomplete and error-prone datasets currently available, such methods have had limited success. Moreover, the results of network alignment are in general not amenable for distance-based evolutionary analysis of sets of networks. In this article, we describe Netdis, a topology-based distance measure between networks, which offers the possibility of network phylogeny reconstruction. Results: We first demonstrate that Netdis is able to correctly separate different random graph model types independent of network size and density. The biological applicability of the method is then shown by its ability to build the correct phylogenetic tree of species based solely on the topology of current protein interaction networks. Our results provide new evidence that the topology of protein interaction networks contains information about evolutionary processes, despite the lack of conservation of individual interactions. As Netdis is applicable to all networks because of its speed and simplicity, we apply it to a large collection of biological and non-biological networks where it clusters diverse networks by type. Availability and implementation: The source code of the program is freely available at http://www.stats.ox.ac.uk/research/proteins/resources. Contact: w.ali@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25161230

  12. Protein Phosphatase 1α Interacting Proteins in the Human Brain

    PubMed Central

    Esteves, Sara L.C.; Domingues, Sara C.; da Cruz e Silva, Odete A.B.; da Cruz e Silva, Edgar F.

    2012-01-01

    Abstract Protein Phosphatase 1 (PP1) is a major serine/threonine-phosphatase whose activity is dependent on its binding to regulatory subunits known as PP1 interacting proteins (PIPs), responsible for targeting PP1 to a specific cellular location, specifying its substrate or regulating its action. Today, more than 200 PIPs have been described involving PP1 in panoply of cellular mechanisms. Moreover, several PIPs have been identified that are tissue and event specific. In addition, the diversity of PP1/PIP complexes can further be achieved by the existence of several PP1 isoforms that can bind preferentially to a certain PIP. Thus, PP1/PIP complexes are highly specific for a particular function in the cell, and as such, they are excellent pharmacological targets. Hence, an in-depth survey was taken to identify specific PP1α PIPs in human brain by a high-throughput Yeast Two-Hybrid approach. Sixty-six proteins were recognized to bind PP1α, 39 being novel PIPs. A large protein interaction databases search was also performed to integrate with the results of the PP1α Human Brain Yeast Two-Hybrid and a total of 246 interactions were retrieved. PMID:22321011

  13. Characterization and modeling of protein protein interaction networks

    NASA Astrophysics Data System (ADS)

    Colizza, Vittoria; Flammini, Alessandro; Maritan, Amos; Vespignani, Alessandro

    2005-07-01

    The recent availability of high-throughput gene expression and proteomics techniques has created an unprecedented opportunity for a comprehensive study of the structure and dynamics of many biological networks. Global proteomic interaction data, in particular, are synthetically represented as undirected networks exhibiting features far from the random paradigm which has dominated past effort in network theory. This evidence, along with the advances in the theory of complex networks, has triggered an intense research activity aimed at exploiting the evolutionary and biological significance of the resulting network's topology. Here we present a review of the results obtained in the characterization and modeling of the yeast Saccharomyces Cerevisiae protein interaction networks obtained with different experimental techniques. We provide a comparative assessment of the topological properties and discuss possible biases in interaction networks obtained with different techniques. We report on dynamical models based on duplication mechanisms that cast the protein interaction networks in the family of dynamically growing complex networks. Finally, we discuss various results and analysis correlating the networks’ topology with the biological function of proteins.

  14. Using support vector machine for improving protein-protein interaction prediction utilizing domain interactions

    SciTech Connect

    Singhal, Mudita; Shah, Anuj R.; Brown, Roslyn N.; Adkins, Joshua N.

    2010-10-02

    Understanding protein interactions is essential to gain insights into the biological processes at the whole cell level. The high-throughput experimental techniques for determining protein-protein interactions (PPI) are error prone and expensive with low overlap amongst them. Although several computational methods have been proposed for predicting protein interactions there is definite room for improvement. Here we present DomainSVM, a predictive method for PPI that uses computationally inferred domain-domain interaction values in a Support Vector Machine framework to predict protein interactions. DomainSVM method utilizes evidence of multiple interacting domains to predict a protein interaction. It outperforms existing methods of PPI prediction by achieving very high explanation ratios, precision, specificity, sensitivity and F-measure values in a 10 fold cross-validation study conducted on the positive and negative PPIs in yeast. A Functional comparison study using GO annotations on the positive and the negative test sets is presented in addition to discussing novel PPI predictions in Salmonella Typhimurium.

  15. Protease-inhibitor interaction predictions: Lessons on the complexity of protein-protein interactions.

    PubMed

    Fortelny, Nikolaus; Butler, Georgina S; Overall, Christopher Mark; Pavlidis, Paul

    2017-04-06

    Protein interactions shape proteome function and thus biology. Identification of protein interactions is a major goal in molecular biology, but biochemical methods, although improving, remain limited in coverage and accuracy. Whereas computational predictions can guide biochemical experiments, low validation rates of predictions remain a major limitation. Here, we investigated computational methods in the prediction of a specific type of interaction, the inhibitory interactions between proteases and their inhibitors. Proteases generate thousands of proteoforms that dynamically shape the functional state of proteomes. Despite the important regulatory role of proteases, knowledge of their inhibitors remains largely incomplete with the vast majority of proteases lacking an annotated inhibitor. To link inhibitors to their target proteases on a large scale, we applied computational methods to predict inhibitory interactions between proteases and their inhibitors based on complementary data including coexpression, phylogenetic similarity, structural information, co-annotation, and colocalization, and also surveyed general protein interaction networks for potential inhibitory interactions. In testing nine predicted interactions biochemically, we validated the inhibition of kallikrein 5 by serpin B12. Despite the use of a wide array of complementary data, we found a high false positive rate of computational predictions in biochemical follow-up. Based on a protease-specific definition of true negatives derived from the biochemical classification of proteases and inhibitors, we analyzed prediction accuracy of individual features. Thereby we identified feature-specific limitations, which also affected general protein interaction prediction methods. Interestingly, proteases were often not coexpressed with most of their functional inhibitors, contrary to what is commonly assumed and extrapolated predominantly from cell culture experiments. Predictions of inhibitory interactions

  16. The interactions of peripheral membrane proteins with biological membranes

    SciTech Connect

    Johs, Alexander; Whited, A. M.

    2015-01-01

    The interactions of peripheral proteins with membrane surfaces are critical to many biological processes, including signaling, recognition, membrane trafficking, cell division and cell structure. On a molecular level, peripheral membrane proteins can modulate lipid composition, membrane dynamics and protein-protein interactions. Biochemical and biophysical studies have shown that these interactions are in fact highly complex, dominated by several different types of interactions, and have an interdependent effect on both the protein and membrane. Here we examine three major mechanisms underlying the interactions between peripheral membrane proteins and membranes: electrostatic interactions, hydrophobic interactions, and fatty acid modification of proteins. While experimental approaches continue to provide critical insights into specific interaction mechanisms, emerging bioinformatics resources and tools contribute to a systems-level picture of protein-lipid interactions. Through these recent advances, we begin to understand the pivotal role of protein-lipid interactions underlying complex biological functions at membrane interfaces.

  17. The interactions of peripheral membrane proteins with biological membranes

    DOE PAGES

    Johs, Alexander; Whited, A. M.

    2015-01-01

    The interactions of peripheral proteins with membrane surfaces are critical to many biological processes, including signaling, recognition, membrane trafficking, cell division and cell structure. On a molecular level, peripheral membrane proteins can modulate lipid composition, membrane dynamics and protein-protein interactions. Biochemical and biophysical studies have shown that these interactions are in fact highly complex, dominated by several different types of interactions, and have an interdependent effect on both the protein and membrane. Here we examine three major mechanisms underlying the interactions between peripheral membrane proteins and membranes: electrostatic interactions, hydrophobic interactions, and fatty acid modification of proteins. While experimental approachesmore » continue to provide critical insights into specific interaction mechanisms, emerging bioinformatics resources and tools contribute to a systems-level picture of protein-lipid interactions. Through these recent advances, we begin to understand the pivotal role of protein-lipid interactions underlying complex biological functions at membrane interfaces.« less

  18. Diversity in protein-protein interactions of connexins: emerging roles.

    PubMed

    Hervé, Jean-Claude; Bourmeyster, Nicolas; Sarrouilhe, Denis

    2004-03-23

    Gap junctions, specialised membrane structures that mediate cell-to-cell communication in almost all tissues, are composed of channel-forming integral membrane proteins termed connexins. The activity of these intercellular channels is closely regulated, particularly by intramolecular modifications as phosphorylations of proteins by protein kinases, which appear to regulate the gap junction at several levels, including assembly of channels in the plasma membrane, connexin turnover as well as directly affecting the opening and closure ("gating") of channels. The regulation of membrane channels by protein phosphorylation/dephosphorylation processes commonly requires the formation of a multiprotein complex, where pore-forming subunits bind to auxiliary proteins (e.g. scaffolding proteins, catalytic and regulatory subunits), that play essential roles in channel localisation and activity, linking signalling enzymes, substrates and effectors into a structure frequently anchored to the cytoskeleton. The present review summarises the up-to-date progress regarding the proteins capable of interacting or at least of co-localising with connexins and their functional importance.

  19. Drug Target Protein-Protein Interaction Networks: A Systematic Perspective.

    PubMed

    Feng, Yanghe; Wang, Qi; Wang, Tengjiao

    2017-01-01

    The identification and validation of drug targets are crucial in biomedical research and many studies have been conducted on analyzing drug target features for getting a better understanding on principles of their mechanisms. But most of them are based on either strong biological hypotheses or the chemical and physical properties of those targets separately. In this paper, we investigated three main ways to understand the functional biomolecules based on the topological features of drug targets. There are no significant differences between targets and common proteins in the protein-protein interactions network, indicating the drug targets are neither hub proteins which are dominant nor the bridge proteins. According to some special topological structures of the drug targets, there are significant differences between known targets and other proteins. Furthermore, the drug targets mainly belong to three typical communities based on their modularity. These topological features are helpful to understand how the drug targets work in the PPI network. Particularly, it is an alternative way to predict potential targets or extract nontargets to test a new drug target efficiently and economically. By this way, a drug target's homologue set containing 102 potential target proteins is predicted in the paper.

  20. Prediction and integration of regulatory and protein-protein interactions

    SciTech Connect

    Wichadakul, Duangdao; McDermott, Jason E.; Samudrala, Ram

    2009-04-20

    Knowledge of transcriptional regulatory interactions (TRIs) is essential for exploring functional genomics and systems biology in any organism. While several results from genome-wide analysis of transcriptional regulatory networks are available, they are limited to model organisms such as yeast [1] and worm [2]. Beyond these networks, experiments on TRIs study only individual genes and proteins of specific interest. In this chapter, we present a method for the integration of various data sets to predict TRIs for 54 organisms in the Bioverse [3]. We describe how to compile and handle various formats and identifiers of data sets from different sources, and how to predict the TRIs using a homology-based approach, utilizing the compiled data sets. Integrated data sets include experimentally verified TRIs, binding sites of transcription factors, promoter sequences, protein sub-cellular localization, and protein families. Predicted TRIs expand the networks of gene regulation for a large number of organisms. The integration of experimentally verified and predicted TRIs with other known protein-protein interactions (PPIs) gives insight into specific pathways, network motifs, and the topological dynamics of an integrated network with gene expression under different conditions, essential for exploring functional genomics and systems biology.

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

    PubMed Central

    2011-01-01

    Background Disrupting protein-protein interactions by small organic molecules is nowadays a promising strategy employed to block protein targets involved in different pathologies. However, structural changes occurring at the binding interfaces make difficult drug discovery processes using structure-based drug design/virtual screening approaches. Here we focused on two homologous calcium binding proteins, calmodulin and human centrin 2, involved in different cellular functions via protein-protein interactions, and known to undergo important conformational changes upon ligand binding. Results In order to find suitable protein conformations of calmodulin and centrin for further structure-based drug design/virtual screening, we performed in silico structural/energetic analysis and molecular docking of terphenyl (a mimicking alpha-helical molecule known to inhibit protein-protein interactions of calmodulin) into X-ray and NMR ensembles of calmodulin and centrin. We employed several scoring methods in order to find the best protein conformations. Our results show that docking on NMR structures of calmodulin and centrin can be very helpful to take into account conformational changes occurring at protein-protein interfaces. Conclusions NMR structures of protein-protein complexes nowadays available could efficiently be exploited for further structure-based drug design/virtual screening processes employed to design small molecule inhibitors of protein-protein interactions. PMID:21569443

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

    PubMed

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

    2013-10-01

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

  3. Small Molecule Inhibitors to Disrupt Protein-protein Interactions of Heat Shock Protein 90 Chaperone Machinery.

    PubMed

    Seo, Young Ho

    2015-03-01

    Heat shock protein 90 (Hsp90) is an adenosine triphosphate dependent molecular chaperone in eukaryotic cells that regulates the activation and maintenance of numerous regulatory and signaling proteins including epidermal growth factor receptor, human epidermal growth factor receptor 2, mesenchymal-epithelial transition factor, cyclin-dependent kinase-4, protein kinase B, hypoxia-inducible factor 1α, and matrix metalloproteinase-2. Since many of Hsp90 clients are oncogenic proteins, Hsp90 has become an attractive therapeutic target for treatment of cancer. To discover small molecule inhibitors targeting Hsp90 chaperone machinery, several strategies have been employed, which results in three classes of inhibitors such as N-terminal inhibitors, C-terminal inhibitors, and inhibitors disrupting protein-protein interactions of Hsp90 chaperone machinery. Developing small molecule inhibitors that modulate protein-protein interactions of Hsp90 is a challenging task, although it offers many alternative opportunities for therapeutic intervention. The lack of well-defined binding pocket and starting points for drug design challenges medicinal chemists to discover small molecule inhibitors disrupting protein-protein interactions of Hsp90. The present review will focus on the current studies on small molecule inhibitors disrupting protein-protein interactions of Hsp90 chaperone machinery, provide biological background on the structure, function and mechanism of Hsp90's protein-protein interactions, and discuss the challenges and promise of its small molecule modulations.

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

    PubMed

    Park, Byungkyu; Han, Kyungsook

    2010-02-01

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

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

    PubMed

    Yang, Lei; Zhao, Xudong; Tang, Xianglong

    2014-01-01

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

  6. Prox1 directly interacts with LSD1 and recruits the LSD1/NuRD complex to epigenetically co-repress CYP7A1 transcription.

    PubMed

    Ouyang, Huafang; Qin, Yi; Liu, Yanfeng; Xie, Youhua; Liu, Jing

    2013-01-01

    Cholesterol 7α-hydroxylase (CYP7A1) catalyzes the first and rate-limiting step in the classical pathway of bile acids synthesis in liver and is crucial for maintaining lipid homeostasis. Hepatocyte nuclear factor 4α (HNF4α) and α1-fetoprotein transcription factor (FTF) are two major transcription factors driving CYP7A1 promoter activity in hepatocytes. Previous researches have shown that Prospero-related homeobox (Prox1) directly interacts with both HNF4α and FTF and potently co-represses CYP7A1 transcription and bile acid synthesis through unidentified mechanisms. In this work, mechanisms involved in Prox1-mediated co-repression were explored by identifying Prox1-associated proteins using immunoprecipitation followed by mass spectrometry (IP-MS) methodology. Multiple components of the epigenetically repressive lysine-specific demethylase 1 (LSD1)/nucleosome remodeling and histone deacetylase (NuRD) complex, most notably LSD1 and histone deacetylase 2 (HDAC2), were found to be associated with Prox1 and GST pulldown assay demonstrated that Prox1 directly interacts with LSD1. Sequential chromatin immunoprecipitation (ChIP) assays showed that Prox1 co-localizes with HNF4α, LSD1 and HDAC2 on CYP7A1 promoter in HepG2 cells. Furthermore, by using ChIP assay on HepG2 cells with endogenous Prox1 knocked down by RNA interference, Prox1 was shown to recruit LSD1 and HDAC2 onto CYP7A1 promoter and cause increased H3K4 demethylation. Finally, bile acids treatment of HepG2 cells, which significantly repressed CYP7A1 transcription, resulted in increased Prox1 and LSD1/NuRD complex occupancy on CYP7A1 promoter with a concurrent increase in H3K4 demethylation and H3/H4 deacetylation. These results showed that Prox1 interacts with LSD1 to recruit the repressive LSD1/NuRD complex to CYP7A1 promoter and co-represses transcription through epigenetic mechanisms. In addition, such Prox1-mediated epigenetic repression is involved in the physiologically essential negative feedback

  7. Protein self-interaction chromatography on a microchip.

    PubMed

    Deshpande, Kedar; Ahamed, Tangir; van der Wielen, Luuk A M; Horst, Joop H Ter; Jansens, Peter J; Ottens, Marcel

    2009-02-21

    This paper presents the development of a novel miniaturized experimental procedure for the measurement of protein-protein interactions through Self-Interaction Chromatography (SIC) on a microchip, without the use of chromatographic resins. SIC was recently demonstrated to be a relatively easy method to obtain quantitative thermodynamic information about protein-protein interactions, like the osmotic second virial coefficient B(22), which relates to protein phase behavior including protein crystallization. This successful miniaturization to microchip level of a measurement device for protein self-interaction data is a first key step to a complete microfluidic screening platform for the rational design of protein crystallizations, using substantially less expensive protein and experimentation time.

  8. The Activity of Menkes Disease Protein ATP7A Is Essential for Redox Balance in Mitochondria*

    PubMed Central

    Bhattacharjee, Ashima; Yang, Haojun; Duffy, Megan; Robinson, Emily; Conrad-Antoville, Arianrhod; Lu, Ya-Wen; Capps, Tony; Braiterman, Lelita; Wolfgang, Michael; Murphy, Michael P.; Yi, Ling; Kaler, Stephen G.; Lutsenko, Svetlana; Ralle, Martina

    2016-01-01

    Copper-transporting ATPase ATP7A is essential for mammalian copper homeostasis. Loss of ATP7A activity is associated with fatal Menkes disease and various other pathologies. In cells, ATP7A inactivation disrupts copper transport from the cytosol into the secretory pathway. Using fibroblasts from Menkes disease patients and mouse 3T3-L1 cells with a CRISPR/Cas9-inactivated ATP7A, we demonstrate that ATP7A dysfunction is also damaging to mitochondrial redox balance. In these cells, copper accumulates in nuclei, cytosol, and mitochondria, causing distinct changes in their redox environment. Quantitative imaging of live cells using GRX1-roGFP2 and HyPer sensors reveals highest glutathione oxidation and elevation of H2O2 in mitochondria, whereas the redox environment of nuclei and the cytosol is much less affected. Decreasing the H2O2 levels in mitochondria with MitoQ does not prevent glutathione oxidation; i.e. elevated copper and not H2O2 is a primary cause of glutathione oxidation. Redox misbalance does not significantly affect mitochondrion morphology or the activity of respiratory complex IV but markedly increases cell sensitivity to even mild glutathione depletion, resulting in loss of cell viability. Thus, ATP7A activity protects mitochondria from excessive copper entry, which is deleterious to redox buffers. Mitochondrial redox misbalance could significantly contribute to pathologies associated with ATP7A inactivation in tissues with paradoxical accumulation of copper (i.e. renal epithelia). PMID:27226607

  9. The Activity of Menkes Disease Protein ATP7A Is Essential for Redox Balance in Mitochondria

    SciTech Connect

    Bhattacharjee, Ashima; Yang, Haojun; Duffy, Megan; Robinson, Emily; Conrad-Antoville, Arianrhod; Lu, Ya-Wen; Capps, Tony; Braiterman, Lelita; Wolfgang, Michael; Murphy, Michael P.; Yi, Ling; Kaler, Stephen G.; Lutsenko, Svetlana; Ralle, Martina

    2016-05-16

    Copper-transporting ATPase ATP7A is essential for mammalian copper homeostasis. Loss of ATP7A activity is associated with fatal Menkes disease and various other pathologies. In cells, ATP7A inactivation disrupts copper transport from the cytosol into the secretory pathway. Using fibroblasts from Menkes disease patients and mouse 3T3-L1 cells with a CRISPR/Cas9-inactivated ATP7A, we demonstrate that ATP7A dysfunction is also damaging to mitochondrial redox balance. In these cells, copper accumulates in nuclei, cytosol, and mitochondria, causing distinct changes in their redox environment. Quantitative imaging of live cells using GRX1-roGFP2 and HyPer sensors reveals highest glutathione oxidation and elevation of H2O2 in mitochondria, whereas the redox environment of nuclei and the cytosol is much less affected. Decreasing the H2O2 levels in mitochondria with MitoQ does not prevent glutathione oxidation; i.e. elevated copper and not H2O2 is a primary cause of glutathione oxidation. Redox misbalance does not significantly affect mitochondrion morphology or the activity of respiratory complex IV but markedly increases cell sensitivity to even mild glutathione depletion, resulting in loss of cell viability. Thus, ATP7A activity protects mitochondria from excessive copper entry, which is deleterious to redox buffers. Mitochondrial redox misbalance could significantly contribute to pathologies associated with ATP7A inactivation in tissues with paradoxical accumulation of copper (i.e. renal epithelia).

  10. ATP7A (Menkes Protein) functions in Axonal Targeting and Synaptogenesis

    PubMed Central

    Meskini, Rajaâ El; Crabtree, Kelli L.; Cline, Laura B.; Mains, Richard E.; Eipper, Betty A.; Ronnett, Gabriele V.

    2007-01-01

    Menkes Disease (MD) is a neurodegenerative disorder caused by mutations in the copper transporter, ATP7A, a P-type ATPase. We previously used the olfactory system to demonstrate that ATP7A expression is developmentally, not constitutive, regulated, peaking during synaptogenesis when it is highly expressed in extending axons in a copper-independent manner. Although not known to be associated with axonal functions, we explored the possibility that the inability of mutant ATP7A to support axon outgrowth contributes to the neurodegeneration seen in MD. In vivo analysis of the olfactory system in mottled brindled (Atp7aMobr) mice, a rodent model for MD, demonstrates that ATP7A deficiency affects olfactory sensory neuron (OSN) maturation. Disrupted OSN axonal projections and mitral/tufted cell dendritic growth lead to altered synapse integrity and glomerular disorganization in the olfactory bulbs of Atp7aMobr mice. Our data indicate that the neuronal abnormalities observed in MD are a result of specific age-dependent developmental defects. This study demonstrates a role for ATP7A and/or copper in axon outgrowth and synaptogenesis, and will further help identify the cause of the neuropathology that characterizes MD. PMID:17215139

  11. ATP7A (Menkes protein) functions in axonal targeting and synaptogenesis.

    PubMed

    El Meskini, Rajaâ; Crabtree, Kelli L; Cline, Laura B; Mains, Richard E; Eipper, Betty A; Ronnett, Gabriele V

    2007-03-01

    Menkes disease (MD) is a neurodegenerative disorder caused by mutations in the copper transporter, ATP7A, a P-type ATPase. We previously used the olfactory system to demonstrate that ATP7A expression is developmentally, not constitutive, regulated, peaking during synaptogenesis when it is highly expressed in extending axons in a copper-independent manner. Although not known to be associated with axonal functions, we explored the possibility that the inability of mutant ATP7A to support axon outgrowth contributes to the neurodegeneration seen in MD. In vivo analysis of the olfactory system in mottled brindled (Atp7aMobr) mice, a rodent model for MD, demonstrates that ATP7A deficiency affects olfactory sensory neuron (OSN) maturation. Disrupted OSN axonal projections and mitral/tufted cell dendritic growth lead to altered synapse integrity and glomerular disorganization in the olfactory bulbs of Atp7aMobr mice. Our data indicate that the neuronal abnormalities observed in MD are a result of specific age-dependent developmental defects. This study demonstrates a role for ATP7A and/or copper in axon outgrowth and synaptogenesis, and will further help identify the cause of the neuropathology that characterizes MD.

  12. Notable Aspects of Glycan-Protein Interactions

    PubMed Central

    Cohen, Miriam

    2015-01-01

    This mini review highlights several interesting aspects of glycan-mediated interactions that are common between cells, bacteria, and viruses. Glycans are ubiquitously found on all living cells, and in the extracellular milieu of multicellular organisms. They are known to mediate initial binding and recognition events of both immune cells and pathogens with their target cells or tissues. The host target tissues are hidden under a layer of secreted glycosylated decoy targets. In addition, pathogens can utilize and display host glycans to prevent identification as foreign by the host’s immune system (molecular mimicry). Both the host and pathogens continually evolve. The host evolves to prevent infection and the pathogens evolve to evade host defenses. Many pathogens express both glycan-binding proteins and glycosidases. Interestingly, these proteins are often located at the tip of elongated protrusions in bacteria, or in the leading edge of the cell. Glycan-protein interactions have low affinity and, as a result, multivalent interactions are often required to achieve biologically relevant binding. These enable dynamic forms of adhesion mechanisms, reviewed here, and include rolling (cells), stick and roll (bacteria) or surfacing (viruses). PMID:26340640

  13. Stabilizer-Guided Inhibition of Protein-Protein Interactions.

    PubMed

    Milroy, Lech-Gustav; Bartel, Maria; Henen, Morkos A; Leysen, Seppe; Adriaans, Joris M C; Brunsveld, Luc; Landrieu, Isabelle; Ottmann, Christian

    2015-12-21

    The discovery of novel protein-protein interaction (PPI) modulators represents one of the great molecular challenges of the modern era. PPIs can be modulated by either inhibitor or stabilizer compounds, which target different though proximal regions of the protein interface. In principle, protein-stabilizer complexes can guide the design of PPI inhibitors (and vice versa). In the present work, we combine X-ray crystallographic data from both stabilizer and inhibitor co-crystal complexes of the adapter protein 14-3-3 to characterize, down to the atomic scale, inhibitors of the 14-3-3/Tau PPI, a potential drug target to treat Alzheimer's disease. The most potent compound notably inhibited the binding of phosphorylated full-length Tau to 14-3-3 according to NMR spectroscopy studies. Our work sets a precedent for the rational design of PPI inhibitors guided by PPI stabilizer-protein complexes while potentially enabling access to new synthetically tractable stabilizers of 14-3-3 and other PPIs. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Heparan sulfate and heparin interactions with proteins

    PubMed Central

    Meneghetti, Maria C. Z.; Hughes, Ashley J.; Rudd, Timothy R.; Nader, Helena B.; Powell, Andrew K.; Yates, Edwin A.; Lima, Marcelo A.

    2015-01-01

    Heparan sulfate (HS) polysaccharides are ubiquitous components of the cell surface and extracellular matrix of all multicellular animals, whereas heparin is present within mast cells and can be viewed as a more sulfated, tissue-specific, HS variant. HS and heparin regulate biological processes through interactions with a large repertoire of proteins. Owing to these interactions and diverse effects observed during in vitro, ex vivo and in vivo experiments, manifold biological/pharmacological activities have been attributed to them. The properties that have been thought to bestow protein binding and biological activity upon HS and heparin vary from high levels of sequence specificity to a dependence on charge. In contrast to these opposing opinions, we will argue that the evidence supports both a level of redundancy and a degree of selectivity in the structure–activity relationship. The relationship between this apparent redundancy, the multi-dentate nature of heparin and HS polysaccharide chains, their involvement in protein networks and the multiple binding sites on proteins, each possessing different properties, will also be considered. Finally, the role of cations in modulating HS/heparin activity will be reviewed and some of the implications for structure–activity relationships and regulation will be discussed. PMID:26289657

  15. Factors affecting alum-protein interactions.

    PubMed

    Huang, Min; Wang, Wei

    2014-05-15

    Alum (or aluminum-containing) adjuvants are key components of many vaccines currently on the market. The immuno-potentiation effect of alum adjuvants is presumably due to their interaction with antigens, leading to adsorption on the alum particle surface. Understanding the mechanism of antigen adsorption/desorption and its influencing factors could provide guidance on formulation design and ensure proper in-vivo immuno-potentiation effect. In this paper, surface adsorption of several model proteins on two types of aluminum adjuvants (Alhydrogel(®) and Adjuphos(®)) are investigated to understand the underlying adsorption mechanisms, capacities, and potential influencing factors. It was found that electrostatic interactions are the major driving force for surface adsorption of all the model proteins except ovalbumin. Alhydrogel has a significantly higher adsorption capacity than Adjuphos. Several factors significantly change the adsorption capacity of both Alhydrogel and Adjuphos, including molecular weight of protein antigens, sodium chloride, phosphate buffer, denaturing agents, and size of aluminum particles. These important factors need to be carefully considered in the design of an effective protein antigen-based vaccine. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Heparan sulfate and heparin interactions with proteins.

    PubMed

    Meneghetti, Maria C Z; Hughes, Ashley J; Rudd, Timothy R; Nader, Helena B; Powell, Andrew K; Yates, Edwin A; Lima, Marcelo A

    2015-09-06

    Heparan sulfate (HS) polysaccharides are ubiquitous components of the cell surface and extracellular matrix of all multicellular animals, whereas heparin is present within mast cells and can be viewed as a more sulfated, tissue-specific, HS variant. HS and heparin regulate biological processes through interactions with a large repertoire of proteins. Owing to these interactions and diverse effects observed during in vitro, ex vivo and in vivo experiments, manifold biological/pharmacological activities have been attributed to them. The properties that have been thought to bestow protein binding and biological activity upon HS and heparin vary from high levels of sequence specificity to a dependence on charge. In contrast to these opposing opinions, we will argue that the evidence supports both a level of redundancy and a degree of selectivity in the structure-activity relationship. The relationship between this apparent redundancy, the multi-dentate nature of heparin and HS polysaccharide chains, their involvement in protein networks and the multiple binding sites on proteins, each possessing different properties, will also be considered. Finally, the role of cations in modulating HS/heparin activity will be reviewed and some of the implications for structure-activity relationships and regulation will be discussed.

  17. Stabilization of protein-protein interactions by small molecules.

    PubMed

    Giordanetto, Fabrizio; Schäfer, Anja; Ottmann, Christian

    2014-11-01

    Protein-protein interactions (PPIs) are implicated in every disease and mastering the ability to influence PPIs with small molecules would considerably enlarge the druggable genome. Whereas inhibition of PPIs has repeatedly been shown to work successfully, targeted stabilization of PPIs is underrepresented in the literature. This is all the more surprising because natural products like FK506, rapamycin, brefeldin, forskolin and fusicoccin confer their physiological activity by stabilizing specific PPIs. However, recently a number of very interesting synthetic molecules have been reported from drug discovery projects that indeed achieve their desired activities by stabilizing either homo- or hetero-oligomeric complexes of their target proteins. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Free energy decomposition of protein-protein interactions.

    PubMed Central

    Noskov, S Y; Lim, C

    2001-01-01

    A free energy decomposition scheme has been developed and tested on antibody-antigen and protease-inhibitor binding for which accurate experimental structures were available for both free and bound proteins. Using the x-ray coordinates of the free and bound proteins, the absolute binding free energy was computed assuming additivity of three well-defined, physical processes: desolvation of the x-ray structures, isomerization of the x-ray conformation to a nearby local minimum in the gas-phase, and subsequent noncovalent complex formation in the gas phase. This free energy scheme, together with the Generalized Born model for computing the electrostatic solvation free energy, yielded binding free energies in remarkable agreement with experimental data. Two assumptions commonly used in theoretical treatments; viz., the rigid-binding approximation (which assumes no conformational change upon complexation) and the neglect of vdW interactions, were found to yield large errors in the binding free energy. Protein-protein vdW and electrostatic interactions between complementary surfaces over a relatively large area (1400--1700 A(2)) were found to drive antibody-antigen and protease-inhibitor binding. PMID:11463622

  19. Amino acid interaction preferences in proteins

    PubMed Central

    Nath Jha, Anupam; Vishveshwara, Saraswathi; Banavar, Jayanth R

    2010-01-01

    Understanding the key factors that influence the interaction preferences of amino acids in the folding of proteins have remained a challenge. Here we present a knowledge-based approach for determining the effective interactions between amino acids based on amino acid type, their secondary structure, and the contact based environment that they find themselves in the native state structure as measured by their number of neighbors. We find that the optimal information is approximately encoded in a 60 × 60 matrix describing the 20 types of amino acids in three distinct secondary structures (helix, beta strand, and loop). We carry out a clustering scheme to understand the similarity between these interactions and to elucidate a nonredundant set. We demonstrate that the inferred energy parameters can be used for assessing the fit of a given sequence into a putative native state structure. PMID:20073083

  20. Turning the spotlight on protein-lipid interactions in cells

    PubMed Central

    Peng, Tao; Yuan, Xiaoqiu; Hang, Howard C.

    2014-01-01

    Protein function is largely dependent on coordinated and dynamic interactions of the protein with biomolecules including other proteins, nucleic acids and lipids. While powerful methods for global profiling of protein-protein and protein-nucleic acid interactions are available, proteome-wide mapping of protein-lipid interactions is still challenging and rarely performed. The emergence of bifunctional lipid probes with photoactivatable and clickable groups offers new chemical tools for globally profiling protein-lipid interactions under cellular contexts. In this review, we summarize recent advances in the development of bifunctional lipid probes for studying protein-lipid interactions. We also highlight how in vivo photocrosslinking reactions contribute to the characterization of lipid-binding proteins and lipidation-mediated protein-protein interactions. PMID:25129056

  1. Comprehensive peptidomimetic libraries targeting protein-protein interactions.

    PubMed

    Whitby, Landon R; Boger, Dale L

    2012-10-16

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

  2. The 7a accessory protein of severe acute respiratory syndrome coronavirus acts as an RNA silencing suppressor.

    PubMed

    Karjee, Sumona; Minhas, Ankita; Sood, Vikas; Ponia, Sanket S; Banerjea, Akhil C; Chow, Vincent T K; Mukherjee, Sunil K; Lal, Sunil K

    2010-10-01

    RNA silencing suppressors (RSSs) are well studied for plant viruses but are not well defined to date for animal viruses. Here, we have identified an RSS from a medically important positive-sense mammalian virus, Severe acute respiratory syndrome coronavirus. The viral 7a accessory protein suppressed both transgene and virus-induced gene silencing by reducing the levels of small interfering RNA (siRNA). The suppression of silencing was analyzed by two independent assays, and the middle region (amino acids [aa] 32 to 89) of 7a was responsible for suppression. Finally, the RNA suppression property and the enhancement of heterologous replicon activity by the 7a protein were confirmed for animal cell lines.

  3. The Activity of Menkes Disease Protein ATP7A Is Essential for Redox Balance in Mitochondria.

    PubMed

    Bhattacharjee, Ashima; Yang, Haojun; Duffy, Megan; Robinson, Emily; Conrad-Antoville, Arianrhod; Lu, Ya-Wen; Capps, Tony; Braiterman, Lelita; Wolfgang, Michael; Murphy, Michael P; Yi, Ling; Kaler, Stephen G; Lutsenko, Svetlana; Ralle, Martina

    2016-08-05

    Copper-transporting ATPase ATP7A is essential for mammalian copper homeostasis. Loss of ATP7A activity is associated with fatal Menkes disease and various other pathologies. In cells, ATP7A inactivation disrupts copper transport from the cytosol into the secretory pathway. Using fibroblasts from Menkes disease patients and mouse 3T3-L1 cells with a CRISPR/Cas9-inactivated ATP7A, we demonstrate that ATP7A dysfunction is also damaging to mitochondrial redox balance. In these cells, copper accumulates in nuclei, cytosol, and mitochondria, causing distinct changes in their redox environment. Quantitative imaging of live cells using GRX1-roGFP2 and HyPer sensors reveals highest glutathione oxidation and elevation of H2O2 in mitochondria, whereas the redox environment of nuclei and the cytosol is much less affected. Decreasing the H2O2 levels in mitochondria with MitoQ does not prevent glutathione oxidation; i.e. elevated copper and not H2O2 is a primary cause of glutathione oxidation. Redox misbalance does not significantly affect mitochondrion morphology or the activity of respiratory complex IV but markedly increases cell sensitivity to even mild glutathione depletion, resulting in loss of cell viability. Thus, ATP7A activity protects mitochondria from excessive copper entry, which is deleterious to redox buffers. Mitochondrial redox misbalance could significantly contribute to pathologies associated with ATP7A inactivation in tissues with paradoxical accumulation of copper (i.e. renal epithelia). © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

  4. Identification of essential proteins based on ranking edge-weights in protein-protein interaction networks.

    PubMed

    Wang, Yan; Sun, Huiyan; Du, Wei; Blanzieri, Enrico; Viero, Gabriella; Xu, Ying; Liang, Yanchun

    2014-01-01

    Essential proteins are those that are indispensable to cellular survival and development. Existing methods for essential protein identification generally rely on knock-out experiments and/or the relative density of their interactions (edges) with other proteins in a Protein-Protein Interaction (PPI) network. Here, we present a computational method, called EW, to first rank protein-protein interactions in terms of their Edge Weights, and then identify sub-PPI-networks consisting of only the highly-ranked edges and predict their proteins as essential proteins. We have applied this method to publicly-available PPI data on Saccharomyces cerevisiae (Yeast) and Escherichia coli (E. coli) for essential protein identification, and demonstrated that EW achieves better performance than the state-of-the-art methods in terms of the precision-recall and Jackknife measures. The highly-ranked protein-protein interactions by our prediction tend to be biologically significant in both the Yeast and E. coli PPI networks. Further analyses on systematically perturbed Yeast and E. coli PPI networks through randomly deleting edges demonstrate that the proposed method is robust and the top-ranked edges tend to be more associated with known essential proteins than the lowly-ranked edges.

  5. Module organization and variance in protein-protein interaction networks

    NASA Astrophysics Data System (ADS)

    Lin, Chun-Yu; Lee, Tsai-Ling; Chiu, Yi-Yuan; Lin, Yi-Wei; Lo, Yu-Shu; Lin, Chih-Ta; Yang, Jinn-Moon

    2015-03-01

    A module is a group of closely related proteins that act in concert to perform specific biological functions through protein-protein interactions (PPIs) that occur in time and space. However, the underlying module organization and variance remain unclear. In this study, we collected module templates to infer respective module families, including 58,041 homologous modules in 1,678 species, and PPI families using searches of complete genomic database. We then derived PPI evolution scores and interface evolution scores to describe the module elements, including core and ring components. Functions of core components were highly correlated with those of essential genes. In comparison with ring components, core proteins/PPIs were conserved across multiple species. Subsequently, protein/module variance of PPI networks confirmed that core components form dynamic network hubs and play key roles in various biological functions. Based on the analyses of gene essentiality, module variance, and gene co-expression, we summarize the observations of module organization and variance as follows: 1) a module consists of core and ring components; 2) core components perform major biological functions and collaborate with ring components to execute certain functions in some cases; 3) core components are more conserved and essential during organizational changes in different biological states or conditions.

  6. Protein Complex Identification by Integrating Protein-Protein Interaction Evidence from Multiple Sources

    PubMed Central

    Xu, Bo; Lin, Hongfei; Chen, Yang; Yang, Zhihao; Liu, Hongfang

    2013-01-01

    Background Understanding protein complexes is important for understanding the science of cellular organization and function. Many computational methods have been developed to identify protein complexes from experimentally obtained protein-protein interaction (PPI) networks. However, interaction information obtained experimentally can be unreliable and incomplete. Reconstructing these PPI networks with PPI evidences from other sources can improve protein complex identification. Results We combined PPI information from 6 different sources and obtained a reconstructed PPI network for yeast through machine learning. Some popular protein complex identification methods were then applied to detect yeast protein complexes using the new PPI networks. Our evaluation indicates that protein complex identification algorithms using the reconstructed PPI network significantly outperform ones on experimentally verified PPI networks. Conclusions We conclude that incorporating PPI information from other sources can improve the effectiveness of protein complex identification. PMID:24386289

  7. Parallel Force Assay for Protein-Protein Interactions

    PubMed Central

    Aschenbrenner, Daniela; Pippig, Diana A.; Klamecka, Kamila; Limmer, Katja; Leonhardt, Heinrich; Gaub, Hermann E.

    2014-01-01

    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. PMID:25546146

  8. Deciphering Supramolecular Structures with Protein-Protein Interaction Network Modeling

    PubMed Central

    Tsuji, Toshiyuki; Yoda, Takao; Shirai, Tsuyoshi

    2015-01-01

    Many biological molecules are assembled into supramolecules that are essential to perform complicated functions in the cell. However, experimental information about the structures of supramolecules is not sufficient at this point. We developed a method of predicting and modeling the structures of supramolecules in a biological network by combining structural data of the Protein Data Bank (PDB) and interaction data in IntAct databases. Templates for binary complexes in IntAct were extracted from PDB. Modeling was attempted by assembling binary complexes with superposed shared subunits. A total of 3,197 models were constructed, and 1,306 (41% of the total) contained at least one subunit absent from experimental structures. The models also suggested 970 (25% of the total) experimentally undetected subunit interfaces, and 41 human disease-related amino acid variants were mapped onto these model-suggested interfaces. The models demonstrated that protein-protein interaction network modeling is useful to fill the information gap between biological networks and structures. PMID:26549015

  9. Targeting protein-protein interactions as an anticancer strategy.

    PubMed

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

    2013-07-01

    The emergence and convergence of cancer genomics, targeted therapies, and network oncology have significantly expanded the landscape of protein-protein interaction (PPI) networks in cancer for therapeutic discovery. Extensive biological and clinical investigations have led to the identification of protein interaction hubs and nodes that are critical for the acquisition and maintenance of characteristics of cancer essential for cell transformation. Such cancer-enabling PPIs have become promising therapeutic targets. With technological advances in PPI modulator discovery and validation of PPI-targeting agents in clinical settings, targeting of PPI interfaces as an anticancer strategy has become a reality. Future research directed at genomics-based PPI target discovery, PPI interface characterization, PPI-focused chemical library design, and patient-genomic subpopulation-driven clinical studies is expected to accelerate the development of the next generation of PPI-based anticancer agents for personalized precision medicine. Here we briefly review prominent PPIs that mediate cancer-acquired properties, highlight recognized challenges and promising clinical results in targeting PPIs, and outline emerging opportunities. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

    PubMed Central

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

    2013-01-01

    Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on 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. PMID:23696727

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

    NASA Astrophysics Data System (ADS)

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

    2017-05-01

    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.

  12. Tetramer formation in Arabidopsis MADS domain proteins: analysis of a protein-protein interaction network

    PubMed Central

    2014-01-01

    Background MADS domain proteins are transcription factors that coordinate several important developmental processes in plants. These proteins interact with other MADS domain proteins to form dimers, and it has been proposed that they are able to associate as tetrameric complexes that regulate transcription of target genes. Whether the formation of functional tetramers is a widespread property of plant MADS domain proteins, or it is specific to few of these transcriptional regulators remains unclear. Results We analyzed the structure of the network of physical interactions among MADS domain proteins in Arabidopsis thaliana. We determined the abundance of subgraphs that represent the connection pattern expected for a MADS domain protein heterotetramer. These subgraphs were significantly more abundant in the MADS domain protein interaction network than in randomized analogous networks. Importantly, these subgraphs are not significantly frequent in a protein interaction network of TCP plant transcription factors, when compared to expectation by chance. In addition, we found that MADS domain proteins in tetramer-like subgraphs are more likely to be expressed jointly than proteins in other subgraphs. This effect is mainly due to proteins in the monophyletic MIKC clade, as there is no association between tetramer-like subgraphs and co-expression for proteins outside this clade. Conclusions Our results support that the tendency to form functional tetramers is widespread in the MADS domain protein-protein interaction network. Our observations also suggest that this trend is prevalent, or perhaps exclusive, for proteins in the MIKC clade. Because it is possible to retrodict several experimental results from our analyses, our work can be an important aid to make new predictions and facilitates experimental research on plant MADS domain proteins. PMID:24468197

  13. Improving the prediction of yeast protein function using weighted protein-protein interactions

    PubMed Central

    2011-01-01

    Background Bioinformatics can be used to predict protein function, leading to an understanding of cellular activities, and equally-weighted protein-protein interactions (PPI) are normally used to predict such protein functions. The present study provides a weighting strategy for PPI to improve the prediction of protein functions. The weights are dependent on the local and global network topologies and the number of experimental verification methods. The proposed methods were applied to the yeast proteome and integrated with the neighbour counting method to predict the functions of unknown proteins. Results A new technique to weight interactions in the yeast proteome is presented. The weights are related to the network topology (local and global) and the number of identified methods, and the results revealed improvement in the sensitivity and specificity of prediction in terms of cellular role and cellular locations. This method (new weights) was compared with a method that utilises interactions with the same weight and it was shown to be superior. Conclusions A new method for weighting the interactions in protein-protein interaction networks is presented. Experimental results concerning yeast proteins demonstrated that weighting interactions integrated with the neighbor counting method improved the sensitivity and specificity of prediction in terms of two functional categories: cellular role and cell locations. PMID:21524280

  14. Controlling Directed Protein Interaction Networks in Cancer.

    PubMed

    Kanhaiya, Krishna; Czeizler, Eugen; Gratie, Cristian; Petre, Ion

    2017-09-04

    Control theory is a well-established approach in network science, with applications in bio-medicine and cancer research. We build on recent results for structural controllability of directed networks, which identifies a set of driver nodes able to control an a-priori defined part of the network. We develop a novel and efficient approach for the (targeted) structural controllability of cancer networks and demonstrate it for the analysis of breast, pancreatic, and ovarian cancer. We build in each case a protein-protein interaction network and focus on the survivability-essential proteins specific to each cancer type. We show that these essential proteins are efficiently controllable from a relatively small computable set of driver nodes. Moreover, we adjust the method to find the driver nodes among FDA-approved drug-target nodes. We find that, while many of the drugs acting on the driver nodes are part of known cancer therapies, some of them are not used for the cancer types analyzed here; some drug-target driver nodes identified by our algorithms are not known to be used in any cancer therapy. Overall we show that a better understanding of the control dynamics of cancer through computational modelling can pave the way for new efficient therapeutic approaches and personalized medicine.

  15. From Topology to Phenotype in Protein-Protein Interaction Networks

    NASA Astrophysics Data System (ADS)

    Pržulj, Nataša

    We have recently witnessed an explosion in biological network data along with the development of computational approaches for their analyses. This new interdisciplinary research area is an integral part of systems biology, promising to provide new insights into organizational principles of life, as well as into evolution and disease. However, there is a danger that the area might become hindered by several emerging issues. In particular, there is typically a weak link between biological and computational scientists, resulting in the use of simple computational techniques of limited potential to explain these complex biological data. Hence, there is a danger that the community might view the topological features of network data as mere statistics, ignoring the value of the information contained in these data. This might result in the imposition of scientific doctrines, such as scale-free-centric (on the modelling side) and genome-centric (on the biological side) opinions onto this nascent research area. In this chapter, we take a network science perspective and present a brief, high-level overview of the area, commenting on possible challenges ahead. We focus on protein-protein interaction networks (PINs) in which nodes correspond to proteins in a cell and edges to physical bindings between the proteins.

  16. Interaction of Protein Inhibitor of Activated STAT (PIAS) Proteins with the TATA-binding Protein, TBP*

    PubMed Central

    Prigge, Justin R.; Schmidt, Edward E.

    2007-01-01

    Transcription activators often recruit promoter-targeted assembly of a pre-initiation complex; many repressors antagonize recruitment. These activities can involve direct interactions with proteins in the pre-initiation complex. We used an optimized yeast two-hybrid system to screen mouse pregnancy-associated libraries for proteins that interact with TATA-binding protein (TBP). Screens revealed an interaction between TBP and a single member of the zinc finger family of transcription factors, ZFP523. Two members of the protein inhibitor of activated STAT (PIAS) family, PIAS1 and PIAS3, also interacted with TBP in screens. Endogenous PIAS1 and TBP co-immunoprecipitated from nuclear extracts, suggesting the interaction occurred in vivo. In vitro-translated PIAS1 and TBP coimmunopreciptated, which indicated that other nuclear proteins were not required for the interaction. Deletion analysis mapped the PIAS-interacting domain of TBP to the conserved TBPCORE and the TBP-interacting domain on PIAS1 to a 39-amino acid C-terminal region. Mammals issue seven known PIAS proteins from four pias genes, pias1, pias3, piasx, and piasy, each with different cell type-specific expression patterns; the TBP-interacting domain reported here is the only part of the PIAS C-terminal region shared by all seven PIAS proteins. Direct analyses indicated that PIASx and PIASy also interacted with TBP. Our results suggest that all PIAS proteins might mediate situation-specific regulatory signaling at the TBP interface and that previously unknown levels of complexity could exist in the gene regulatory interplay between TBP, PIAS proteins, ZFP523, and other transcription factors. PMID:16522640

  17. Comparative analysis of five protein-protein interaction corpora.

    PubMed

    Pyysalo, Sampo; Airola, Antti; Heimonen, Juho; Björne, Jari; Ginter, Filip; Salakoski, Tapio

    2008-04-11

    Growing interest in the application of natural language processing methods to biomedical text has led to an increasing number of corpora and methods targeting protein-protein interaction (PPI) extraction. However, there is no general consensus regarding PPI annotation and consequently resources are largely incompatible and methods are difficult to evaluate. We present the first comparative evaluation of the diverse PPI corpora, performing quantitative evaluation using two separate information extraction methods as well as detailed statistical and qualitative analyses of their properties. For the evaluation, we unify the corpus PPI annotations to a shared level of information, consisting of undirected, untyped binary interactions of non-static types with no identification of the words specifying the interaction, no negations, and no interaction certainty. We find that the F-score performance of a state-of-the-art PPI extraction method varies on average 19 percentage units and in some cases over 30 percentage units between the different evaluated corpora. The differences stemming from the choice of corpus can thus be substantially larger than differences between the performance of PPI extraction methods, which suggests definite limits on the ability to compare methods evaluated on different resources. We analyse a number of potential sources for these differences and identify factors explaining approximately half of the variance. We further suggest ways in which the difficulty of the PPI extraction tasks codified by different corpora can be determined to advance comparability. Our analysis also identifies points of agreement and disagreement in PPI corpus annotation that are rarely explicitly stated by the authors of the corpora. Our comparative analysis uncovers key similarities and differences between the diverse PPI corpora, thus taking an important step towards standardization. In the course of this study we have created a major practical contribution in

  18. Glutathione-S-transferase (GST)-fusion based assays for studying protein-protein interactions.

    PubMed

    Vikis, Haris G; Guan, Kun-Liang

    2015-01-01

    Glutathione-S-transferase (GST)-fusion proteins have become an effective reagent to use in the study of protein-protein interactions. GST-fusion proteins can be produced in bacterial and mammalian cells in large quantities and purified rapidly. GST can be coupled to a glutathione matrix, which permits its use as an effective affinity column to study interactions in vitro or to purify protein complexes in cells expressing the GST-fusion protein. Here, we provide a technical description of the utilization of GST-fusion proteins as both a tool to study protein-protein interactions and also as a means to purify interacting proteins.

  19. Fluorescence Studies of Protein Crystallization Interactions

    NASA Technical Reports Server (NTRS)

    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.

  20. Fluorescence Studies of Protein Crystallization Interactions

    NASA Technical Reports Server (NTRS)

    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. Protein-protein interactions of tandem affinity purification-tagged protein kinases in rice.

    PubMed

    Rohila, Jai S; Chen, Mei; Chen, Shuo; Chen, Johann; Cerny, Ronald; Dardick, Chris; Canlas, Patrick; Xu, Xia; Gribskov, Michael; Kanrar, Siddhartha; Zhu, Jian-Kang; Ronald, Pamela; Fromm, Michael E

    2006-04-01

    Forty-one rice cDNAs encoding protein kinases were fused to the tandem affinity purification (TAP) tag and expressed in transgenic rice plants. The TAP-tagged kinases and interacting proteins were purified from the T1 progeny of the transgenic rice plants and identified by mass spectrometry. Ninety-five percent of the TAP-tagged kinases were recovered. Fifty-six percent of the TAP-tagged kinases were found to interact with other rice proteins. A number of these interactions were consistent with known protein complexes found in other species, validating the TAP-tag method in rice plants. Phosphorylation sites were identified on four of the kinases that interacted with either 14-3-3 proteins or cyclins.

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

    PubMed

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

    2010-03-01

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

  3. Protein-protein interactions of tandem affinity purified protein kinases from rice.

    PubMed

    Rohila, Jai S; Chen, Mei; Chen, Shuo; Chen, Johann; Cerny, Ronald L; Dardick, Christopher; Canlas, Patrick; Fujii, Hiroaki; Gribskov, Michael; Kanrar, Siddhartha; Knoflicek, Lucas; Stevenson, Becky; Xie, Mingtang; Xu, Xia; Zheng, Xianwu; Zhu, Jian-Kang; Ronald, Pamela; Fromm, Michael E

    2009-08-19

    Eighty-eight rice (Oryza sativa) cDNAs encoding rice leaf expressed protein kinases (PKs) were fused to a Tandem Affinity Purification tag (TAP-tag) and expressed in transgenic rice plants. The TAP-tagged PKs and interacting proteins were purified from the T1 progeny of the transgenic rice plants and identified by tandem mass spectrometry. Forty-five TAP-tagged PKs were recovered in this study and thirteen of these were found to interact with other rice proteins with a high probability score. In vivo phosphorylated sites were found for three of the PKs. A comparison of the TAP-tagged data from a combined analysis of 129 TAP-tagged rice protein kinases with a concurrent screen using yeast two hybrid methods identified an evolutionarily new rice protein that interacts with the well conserved cell division cycle 2 (CDC2) protein complex.

  4. Protein-Protein Interactions of Tandem Affinity Purified Protein Kinases from Rice

    PubMed Central

    Rohila, Jai S.; Chen, Mei; Chen, Shuo; Chen, Johann; Cerny, Ronald L.; Dardick, Christopher; Canlas, Patrick; Fujii, Hiroaki; Gribskov, Michael; Kanrar, Siddhartha; Knoflicek, Lucas; Stevenson, Becky; Xie, Mingtang; Xu, Xia; Zheng, Xianwu; Zhu, Jian-Kang; Ronald, Pamela; Fromm, Michael E.

    2009-01-01

    Eighty-eight rice (Oryza sativa) cDNAs encoding rice leaf expressed protein kinases (PKs) were fused to a Tandem Affinity Purification tag (TAP-tag) and expressed in transgenic rice plants. The TAP-tagged PKs and interacting proteins were purified from the T1 progeny of the transgenic rice plants and identified by tandem mass spectrometry. Forty-five TAP-tagged PKs were recovered in this study and thirteen of these were found to interact with other rice proteins with a high probability score. In vivo phosphorylated sites were found for three of the PKs. A comparison of the TAP-tagged data from a combined analysis of 129 TAP-tagged rice protein kinases with a concurrent screen using yeast two hybrid methods identified an evolutionarily new rice protein that interacts with the well conserved cell division cycle 2 (CDC2) protein complex. PMID:19690613

  5. Glycosphingolipid–Protein Interaction in Signal Transduction

    PubMed Central

    Russo, Domenico; Parashuraman, Seetharaman; D’Angelo, Giovanni

    2016-01-01

    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. PMID:27754465

  6. Interaction graph mining for protein complexes using local clique merging.

    PubMed

    Li, Xiao-Li; Tan, Soon-Heng; Foo, Chuan-Sheng; Ng, See-Kiong

    2005-01-01

    While recent technological advances have made available large datasets of experimentally-detected pairwise protein-protein interactions, there is still a lack of experimentally-determined protein complex data. To make up for this lack of protein complex data, we explore the mining of existing protein interaction graphs for protein complexes. This paper proposes a novel graph mining algorithm to detect the dense neighborhoods (highly connected regions) in an interaction graph which may correspond to protein complexes. Our algorithm first locates local cliques for each graph vertex (protein) and then merge the detected local cliques according to their affinity to form maximal dense regions. We present experimental results with yeast protein interaction data to demonstrate the effectiveness of our proposed method. Compared with other existing techniques, our predicted complexes can match or overlap significantly better with the known protein complexes in the MIPS benchmark database. Novel protein complexes were also predicted to help biologists in their search for new protein complexes.

  7. Protein-Protein Interaction Network and Gene Ontology

    NASA Astrophysics Data System (ADS)

    Choi, Yunkyu; Kim, Seok; Yi, Gwan-Su; Park, Jinah

    Evolution of computer technologies makes it possible to access a large amount and various kinds of biological data via internet such as DNA sequences, proteomics data and information discovered about them. It is expected that the combination of various data could help researchers find further knowledge about them. Roles of a visualization system are to invoke human abilities to integrate information and to recognize certain patterns in the data. Thus, when the various kinds of data are examined and analyzed manually, an effective visualization system is an essential part. One instance of these integrated visualizations can be combination of protein-protein interaction (PPI) data and Gene Ontology (GO) which could help enhance the analysis of PPI network. We introduce a simple but comprehensive visualization system that integrates GO and PPI data where GO and PPI graphs are visualized side-by-side and supports quick reference functions between them. Furthermore, the proposed system provides several interactive visualization methods for efficiently analyzing the PPI network and GO directedacyclic- graph such as context-based browsing and common ancestors finding.

  8. Insights from protein-protein interaction studies on bacterial pathogenesis.

    PubMed

    Gagarinova, Alla; Phanse, Sadhna; Cygler, Miroslaw; Babu, Mohan

    2017-09-01

    The threat bacterial pathogens pose to human health is increasing with the number and distribution of antibiotic-resistant bacteria, while the rate of discovery of new antimicrobials dwindles. Proteomics is playing key roles in understanding the molecular mechanisms of bacterial pathogenesis, and in identifying disease outcome determinants. The physical associations identified by proteomics can provide the means to develop pathogen-specific treatment methods that reduce the spread of antibiotic resistance and alleviate the negative effects of broad-spectrum antibiotics on beneficial bacteria. Areas covered: This review discusses recent trends in proteomics and introduces new and developing approaches that can be applied to the study of protein-protein interactions (PPIs) underlying bacterial pathogenesis. The approaches examined encompass options for mapping proteomes as well as stable and transient interactions in vivo and in vitro. We also explored the coverage of bacterial and human-bacterial PPIs, knowledge gaps in this area, and how they can be filled. Expert commentary: Identifying potential antimicrobial candidates is confounded by the complex molecular biology of bacterial pathogenesis and the lack of knowledge about PPIs underlying this process. Proteomics approaches can offer new perspectives for mechanistic insights and identify essential targets for guiding the discovery of next generation antimicrobials.

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

    PubMed

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

    2016-08-16

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

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

    SciTech Connect

    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.

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

    PubMed

    Kodama, Yutaka; Suetsugu, Noriyuki; Wada, Masamitsu

    2011-04-01

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

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

    PubMed

    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.

  13. The Foundations of Protein-Ligand Interaction

    NASA Astrophysics Data System (ADS)

    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.

  14. Sedimentation Patterns of Rapidly Reversible Protein Interactions

    PubMed Central

    Schuck, Peter

    2010-01-01

    Abstract The transport behavior of macromolecular mixtures with rapidly reversible complex formation is of great interest in the study of protein interactions by many different methods. Complicated transport patterns arise even for simple bimolecular reactions, when all species exhibit different migration velocities. Although partial differential equations are available to describe the spatial and temporal evolution of the interacting system given particular initial conditions, a general overview of the phase behavior of the systems in parameter space has not yet been reported. In the case of sedimentation of two-component mixtures, this study presents simple analytical solutions that solve the underlying equations in the diffusion-free limit previously subject to Gilbert-Jenkins theory. The new expressions describe, with high precision, the average sedimentation coefficients and composition of each boundary, which allow the examination of features of the whole parameter space at once, and may be used for experimental design and robust analysis of experimental boundary patterns to derive the stoichiometry and affinity of the complex. This study finds previously unrecognized features, including a phase transition between boundary patterns. The model reveals that the time-average velocities of all components in the reaction mixture must match—a condition that suggests an intuitive physical picture of an effective particle of the coupled cosedimentation of an interacting system. Adding to the existing numerical solutions of the relevant partial differential equations, the effective particle model provides physical insights into the relationships of the parameters that govern sedimentation patterns. PMID:20441765

  15. Structure of Ocr from bacteriophage T7, a protein that mimics B-form DNA.

    PubMed

    Walkinshaw, M D; Taylor, P; Sturrock, S S; Atanasiu, C; Berge, T; Henderson, R M; Edwardson, J M; Dryden, D T F

    2002-01-01

    We have solved, by X-ray crystallography to a resolution of 1.8 A, the structure of a protein capable of mimicking approximately 20 base pairs of B-form DNA. This ocr protein, encoded by gene 0.3 of bacteriophage T7, mimics the size and shape of a bent DNA molecule and the arrangement of negative charges along the phosphate backbone of B-form DNA. We also demonstrate that ocr is an efficient inhibitor in vivo of all known families of the complex type I DNA restriction enzymes. Using atomic force microscopy, we have also observed that type I enzymes induce a bend in DNA of similar magnitude to the bend in the ocr molecule. This first structure of an antirestriction protein demonstrates the construction of structural mimetics of long segments of B-form DNA.

  16. Detection of peptides, proteins, and drugs that selectively interact with protein targets.

    PubMed

    Serebriiskii, Ilya G; Mitina, Olga; Pugacheva, Elena N; Benevolenskaya, Elizaveta; Kotova, Elena; Toby, Garabet G; Khazak, Vladimir; Kaelin, William G; Chernoff, Jonathan; Golemis, Erica A

    2002-11-01

    Genome sequencing has been completed for multiple organisms, and pilot proteomic analyses reported for yeast and higher eukaryotes. This work has emphasized the facts that proteins are frequently engaged in multiple interactions, and that governance of protein interaction specificity is a primary means of regulating biological systems. In particular, the ability to deconvolute complex protein interaction networks to identify which interactions govern specific signaling pathways requires the generation of biological tools that allow the distinction of critical from noncritical interactions. We report the application of an enhanced Dual Bait two-hybrid system to allow detection and manipulation of highly specific protein-protein interactions. We summarize the use of this system to detect proteins and peptides that target well-defined specific motifs in larger protein structures, to facilitate rapid identification of specific interactors from a pool of putative interacting proteins obtained in a library screen, and to score specific drug-mediated disruption of protein-protein interaction.

  17. Methods for Mapping of Interaction Networks Involving Membrane Proteins

    SciTech Connect

    Hooker, Brian S.; Bigelow, Diana J.; Lin, Chiann Tso

    2007-11-23

    Numerous approaches have been taken to study protein interactions, such as tagged protein complex isolation followed by mass spectrometry, yeast two-hybrid methods, fluorescence resonance energy transfer, surface plasmon resonance, site-directed mutagenesis, and crystallography. Membrane protein interactions pose significant challenges due to the need to solubilize membranes without disrupting protein-protein interactions. Traditionally, analysis of isolated protein complexes by high-resolution 2D gel electrophoresis has been the main method used to obtain an overall picture of proteome constituents and interactions. However, this method is time consuming, labor intensive, detects only abundant proteins and is not suitable for the coverage required to elucidate large interaction networks. In this review, we discuss the application of various methods to elucidate interactions involving membrane proteins. These techniques include methods for the direct isolation of single complexes or interactors as well as methods for characterization of entire subcellular and cellular interactomes.

  18. Directional interactions and cooperativity between mechanosensitive membrane proteins

    NASA Astrophysics Data System (ADS)

    Haselwandter, Christoph A.; Phillips, Rob

    2013-03-01

    While modern structural biology has provided us with a rich and diverse picture of membrane proteins, the biological function of membrane proteins is often influenced by the mechanical properties of the surrounding lipid bilayer. Here we explore the relation between the shape of membrane proteins and the cooperative function of membrane proteins induced by membrane-mediated elastic interactions. For the experimental model system of mechanosensitive ion channels we find that the sign and strength of elastic interactions depend on the protein shape, yielding distinct cooperative gating curves for distinct protein orientations. Our approach predicts how directional elastic interactions affect the molecular structure, organization, and biological function of proteins in crowded membranes.

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

    PubMed

    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.

  20. Mechanisms of peroxynitrite interactions with heme proteins.

    PubMed

    Su, Jia; Groves, John T

    2010-07-19

    Oxygenated heme proteins 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. PN 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 interactions 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 NO and PN. We have recently described direct evidence that ferrylmyolgobin (ferrylMb) and nitrogen dioxide (NO(2)) are both produced during the reaction of PN and metmyolgobin (metMb) (Su, J.; Groves, J. T. J. Am. Chem. Soc. 2009, 131, 12979-12988). Kinetic evidence indicates that these products evolve from the initial formation of a caged radical intermediate [Fe(IV) horizontal lineO.NO(2)]. This caged pair reacts mainly via internal return with a rate constant k(r) 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, k(obs), of heme-mediated PN decomposition. Freely diffusing NO(2), which is liberated concomitantly from the radical pair (k(e)), preferentially nitrates myoglobin Tyr103 and added fluorescein. For cytochrome c, Raman spectroscopy has revealed that a substantial fraction of cytochrome c converts to a beta-sheet structure, at the expense of turns and helices at low pH (Balakrishnan, G.; Hu, Y.; Oyerinde, O. F.; Su, J.; Groves, J. T.; Spiro, T. G. J. Am. Chem. Soc., 2007, 129, 504-505). It is proposed that a short beta-sheet segment, comprising residues 37-39 and 58

  1. Yields of projectile fragments in sulphur-emulsion interactions at 3.7 A GeV

    NASA Astrophysics Data System (ADS)

    Kamel, S.; Osman, W.; Fayed, M.

    2017-05-01

    This work presents the basic characteristics of singly, doubly and heavily charged projectile fragments (PFs) emitted in inelastic interactions of 32S ions with photo-emulsion nuclei at Dubna energy (3.7 A GeV). Our experimental data are compared with the corresponding data for other projectiles at the same incident energy. The study of mean multiplicities of different charged PFs against the projectile mass shows a power-law relationship. The multiplicity distributions of singly and doubly charged PFs have been fitted well with a Gaussian distribution function. The yields of PFs broken up from the interactions of 32S projectile nuclei with different target nuclei are studied. The beam energy dependence in terms of the various order moments is studied as well.

  2. Essential protein identification based on essential protein-protein interaction prediction by Integrated Edge Weights.

    PubMed

    Jiang, Yuexu; Wang, Yan; Pang, Wei; Chen, Liang; Sun, Huiyan; Liang, Yanchun; Blanzieri, Enrico

    2015-07-15

    Essential proteins play a crucial role in cellular survival and development process. Experimentally, essential proteins are identified by gene knockouts or RNA interference, which are expensive and often fatal to the target organisms. Regarding this, an alternative yet important approach to essential protein identification is through computational prediction. Existing computational methods predict essential proteins based on their relative densities in a protein-protein interaction (PPI) network. Degree, betweenness, and other appropriate criteria are often used to measure the relative density. However, no matter what criterion is used, a protein is actually ordered by the attributes of this protein per se. In this research, we presented a novel computational method, Integrated Edge Weights (IEW), to first rank protein-protein interactions by integrating their edge weights, and then identified sub PPI networks consisting of those highly-ranked edges, and finally regarded the nodes in these sub networks as essential proteins. We evaluated IEW on three model organisms: Saccharomyces cerevisiae (S. cerevisiae), Escherichia coli (E. coli), and Caenorhabditis elegans (C. elegans). The experimental results showed that IEW achieved better performance than the state-of-the-art methods in terms of precision-recall and Jackknife measures. We had also demonstrated that IEW is a robust and effective method, which can retrieve biologically significant modules by its highly-ranked protein-protein interactions for S. cerevisiae, E. coli, and C. elegans. We believe that, with sufficient data provided, IEW can be used to any other organisms' essential protein identification. A website about IEW can be accessed from http://digbio.missouri.edu/IEW/index.html.

  3. Testing ancient RNA–protein interactions

    PubMed Central

    Landweber, Laura F.

    1999-01-01

    The past decade in molecular biology has seen remarkable advances in the study of the origin and early evolution of life. The mathematical tools for analyzing DNA and protein sequences, coupled with the availability of complete microbial genome sequences, provide insight almost as far back as the age of the nucleic acids themselves. Experimental evolution in the laboratory and especially in vitro evolution of RNA provide insight into a hypothetical world where RNA, or a close relative, may have debuted as a primary functional and informational molecule. The ability to isolate new functional RNAs from random sequences now ultimately makes the world of possible primitive chemical interactions accessible even when the molecules or reactions are no longer present in modern species. Thus we can at last form direct experimental tests of specific models for the origin of RNA–protein associations, such as those that influenced the genetic code. This marks a turning point for probing the origin and early history of life at the molecular level. PMID:10500126

  4. Fundamentals of protein interaction network mapping.

    PubMed

    Snider, Jamie; Kotlyar, Max; Saraon, Punit; Yao, Zhong; Jurisica, Igor; Stagljar, Igor

    2015-12-17

    Studying protein interaction networks of all proteins in an organism ("interactomes") remains one of the major challenges in modern biomedicine. Such information is crucial to understanding cellular pathways and developing effective therapies for the treatment of human diseases. Over the past two decades, diverse biochemical, genetic, and cell biological methods have been developed to map interactomes. In this review, we highlight basic principles of interactome mapping. Specifically, we discuss the strengths and weaknesses of individual assays, how to select a method appropriate for the problem being studied, and provide general guidelines for carrying out the necessary follow-up analyses. In addition, we discuss computational methods to predict, map, and visualize interactomes, and provide a summary of some of the most important interactome resources. We hope that this review serves as both a useful overview of the field and a guide to help more scientists actively employ these powerful approaches in their research. © 2015 The Authors. Published under the terms of the CC BY 4.0 license.

  5. Linguistic feature analysis for protein interaction extraction

    PubMed Central

    2009-01-01

    Background The rapid growth of the amount of publicly available reports on biomedical experimental results has recently caused a boost of text mining approaches for protein interaction extraction. Most approaches rely implicitly or explicitly on linguistic, i.e., lexical and syntactic, data extracted from text. However, only few attempts have been made to evaluate the contribution of the different feature types. In this work, we contribute to this evaluation by studying the relative importance of deep syntactic features, i.e., grammatical relations, shallow syntactic features (part-of-speech information) and lexical features. For this purpose, we use a recently proposed approach that uses support vector machines with structured kernels. Results Our results reveal that the contribution of the different feature types varies for the different data sets on which the experiments were conducted. The smaller the training corpus compared to the test data, the more important the role of grammatical relations becomes. Moreover, deep syntactic information based classifiers prove to be more robust on heterogeneous texts where no or only limited common vocabulary is shared. Conclusion Our findings suggest that grammatical relations play an important role in the interaction extraction task. Moreover, the net advantage of adding lexical and shallow syntactic features is small related to the number of added features. This implies that efficient classifiers can be built by using only a small fraction of the features that are typically being used in recent approaches. PMID:19909518

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

    PubMed

    Hall, Randy A

    2015-01-01

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

  7. Interaction of Proteins Identified in Human Thyroid Cells

    PubMed Central

    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

  8. Conditional random field approach to prediction of protein-protein interactions using domain information.

    PubMed

    Hayashida, Morihiro; Kamada, Mayumi; Song, Jiangning; Akutsu, Tatsuya

    2011-06-20

    For understanding cellular systems and biological networks, it is important to analyze functions and interactions of proteins and domains. Many methods for predicting protein-protein interactions have been developed. It is known that mutual information between residues at interacting sites can be higher than that at non-interacting sites. It is based on the thought that amino acid residues at interacting sites have coevolved with those at the corresponding residues in the partner proteins. Several studies have shown that such mutual information is useful for identifying contact residues in interacting proteins. We propose novel methods using conditional random fields for predicting protein-protein interactions. We focus on the mutual information between residues, and combine it with conditional random fields. In the methods, protein-protein interactions are modeled using domain-domain interactions. We perform computational experiments using protein-protein interaction datasets for several organisms, and calculate AUC (Area Under ROC Curve) score. The results suggest that our proposed methods with and without mutual information outperform EM (Expectation Maximization) method proposed by Deng et al., which is one of the best predictors based on domain-domain interactions. We propose novel methods using conditional random fields with and without mutual information between domains. Our methods based on domain-domain interactions are useful for predicting protein-protein interactions.

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

    PubMed Central

    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

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

    PubMed

    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

  11. Specificity and non-specificity in RNA–protein interactions

    PubMed Central

    Jankowsky, Eckhard; Harris, Michael E.

    2016-01-01

    Gene expression is regulated by complex networks of interactions between RNAs and proteins. Proteins that interact with RNA have been traditionally viewed as either specific or non-specific; specific proteins interact preferentially with defined RNA sequence or structure motifs, whereas non-specific proteins interact with RNA sites devoid of such characteristics. Recent studies indicate that the binary “specific vs. non-specific” classification is insufficient to describe the full spectrum of RNA–protein interactions. Here, we review new methods that enable quantitative measurements of protein binding to large numbers of RNA variants, and the concepts aimed as describing resulting binding spectra: affinity distributions, comprehensive binding models and free energy landscapes. We discuss how these new methodologies and associated concepts enable work towards inclusive, quantitative models for specific and non-specific RNA–protein interactions. PMID:26285679

  12. RNA polymerase II conserved protein domains as platforms for protein-protein interactions

    PubMed Central

    García-López, M Carmen

    2011-01-01

    RNA polymerase II establishes many protein-protein interactions with transcriptional regulators to coordinate gene expression, but little is known about protein domains involved in the contact with them. We use a new approach to look for conserved regions of the RNA pol II of S. cerevisiae located at the surface of the structure of the complex, hypothesizing that they might be involved in the interaction with transcriptional regulators. We defined five different conserved domains and demonstrate that all of them make contact with transcriptional regulators. PMID:21922063

  13. Oncogenic EWS-Fli1 interacts with hsRPB7, a subunit of human RNA polymerase II.

    PubMed

    Petermann, R; Mossier, B M; Aryee, D N; Khazak, V; Golemis, E A; Kovar, H

    1998-08-06

    As a result of the t(11;22)(q24;q12) chromosomal translocation characterizing the Ewing family of tumors (ET), the amino terminal portion of EWS, an RNA binding protein of unknown function, is fused to the DNA-binding domain of the ets transcription factor Fli1. The hybrid EWS-Fli1 protein acts as a strong transcriptional activator and, in contrast to wildtype Fli1, is a potent transforming agent. Similar rearrangements involving EWS or the highly homologous TLS with various transcription factors have been found in several types of human tumors. Employing yeast two-hybrid cloning we isolated the seventh largest subunit of human RNA polymerase II (hsRPB7) as a protein that specifically interacts with the amino terminus of EWS. This association was confirmed by in vitro immunocoprecipitation. In nuclear extracts, hsRPB7 was found to copurify with EWS-Fli1 but not with Fli1. Overexpression of recombinant hsRPB7 specifically increased gene activation by EWS-chimeric transcription factors. Replacement of the EWS portion by hsRPB7 in the oncogenic fusion protein restored the transactivating potential of the chimera. Our results suggest that the interaction of the amino terminus of EWS with hsRPB7 contributes to the transactivation function of EWS-Fli1 and, since hsRPB7 has characteristics of a regulatory subunit of RNA polymerase II, may influence promoter selectivity.

  14. Nanoparticle-target interactions parallel antibody-protein interactions.

    PubMed

    Koh, Isaac; Hong, Rui; Weissleder, Ralph; Josephson, Lee

    2009-05-01

    Magnetic particles can act as magnetic relaxation switches (MRSw's) when they bind to target analytes, and switch between their dispersed and aggregated states resulting in changes in the spin-spin relaxation time (T(2)) of their surrounding water protons. Both nanoparticles (NPs, 10-100 nm) and micrometer-sized particles (MPs) have been employed as MRSw's, to sense drugs, metabolites, oligonucleotides, proteins, bacteria, and mammalian cells. To better understand how NPs or MPs interact with targets, we employed as a molecular recognition system the reaction between the Tag peptide of the influenza virus hemagglutinin and a monoclonal antibody to that peptide (anti-Tag). To obtain targets of different size and valency, we attached the Tag peptide to BSA (M(w)= 65000 Daltons, diameter = 8 nm) and to Latex spheres (diameter = 900 nm). To obtain magnetic probes of very different sizes, anti-Tag was conjugated to 40 nm NPs and 1 microm MPs. MP and NP probes reacted with Tag peptide targets in a manner similar to antibody/antigen reactions in solution, exhibiting so-called Prozone effects. MPs detected all types of targets with higher sensitivity than NPs with targets of higher valency being better detected than those of lower valency. The Tag/anti Tag recognition system can be used to synthesize combinations of molecular targets and magnetic probes, to more fully understand the aggregation reaction that occurs when probes bind targets in solution and the ensuing changes in water relaxation times that result.

  15. Lipid demixing and protein-protein interactions in the adsorption of charged proteins on mixed membranes.

    PubMed Central

    May, S; Harries, D; Ben-Shaul, A

    2000-01-01

    The adsorption free energy of charged proteins on mixed membranes, containing varying amounts of (oppositely) charged lipids, is calculated based on a mean-field free energy expression that accounts explicitly for the ability of the lipids to demix locally, and for lateral interactions between the adsorbed proteins. Minimization of this free energy functional yields the familiar nonlinear Poisson-Boltzmann equation and the boundary condition at the membrane surface that allows for lipid charge rearrangement. These two self-consistent equations are solved simultaneously. The proteins are modeled as uniformly charged spheres and the (bare) membrane as an ideal two-dimensional binary mixture of charged and neutral lipids. Substantial variations in the lipid charge density profiles are found when highly charged proteins adsorb on weakly charged membranes; the lipids, at a certain demixing entropy penalty, adjust their concentration in the vicinity of the adsorbed protein to achieve optimal charge matching. Lateral repulsive interactions between the adsorbed proteins affect the lipid modulation profile and, at high densities, result in substantial lowering of the binding energy. Adsorption isotherms demonstrating the importance of lipid mobility and protein-protein interactions are calculated using an adsorption equation with a coverage-dependent binding constant. Typically, at bulk-surface equilibrium (i.e., when the membrane surface is "saturated" by adsorbed proteins), the membrane charges are "overcompensated" by the protein charges, because only about half of the protein charges (those on the hemispheres facing the membrane) are involved in charge neutralization. Finally, it is argued that the formation of lipid-protein domains may be enhanced by electrostatic adsorption of proteins, but its origin (e.g., elastic deformations associated with lipid demixing) is not purely electrostatic. PMID:11023883

  16. Engineering modular protein interaction switches by sequence overlap.

    PubMed

    Sallee, Nathan A; Yeh, Brian J; Lim, Wendell A

    2007-04-18

    Many cellular signaling pathways contain proteins whose interactions change in response to upstream inputs, allowing for conditional activation or repression of the interaction based on the presence of the input molecule. The ability to engineer similar regulation into protein interaction elements would provide us with powerful tools for controlling cell signaling. Here we describe an approach for engineering diverse synthetic protein interaction switches. Specifically, by overlapping the sequences of pairs of protein interaction domains and peptides, we have been able to generate mutually exclusive regulation over their interactions. Thus, the hybrid protein (which is composed of the two overlapped interaction modules) can bind to either of the two respective ligands for those modules, but not to both simultaneously. We show that these synthetic switch proteins can be used to regulate specific protein-protein interactions in vivo. These switches allow us to disrupt an interaction with the addition or activation of a protein input that has no natural connection to the interaction in question. Therefore, they give us the ability to make novel connections between normally unrelated signaling pathways and to rewire the input/output relationships of cellular behaviors. Our experiments also suggest a possible mechanism by which complex regulatory proteins might have evolved from simpler components.

  17. Development of small molecules designed to modulate protein-protein interactions.

    PubMed

    Che, Ye; Brooks, Bernard R; Marshall, Garland R

    2006-02-01

    Protein-protein interactions are ubiquitous, essential to almost all known biological processes, and offer attractive opportunities for therapeutic intervention. Developing small molecules that modulate protein-protein interactions is challenging, owing to the large size of protein-complex interface, the lack of well-defined binding pockets, etc. We describe a general approach based on the "privileged-structure hypothesis" [Che, Ph.D. Thesis, Washington University, 2003] - that any organic templates capable of mimicking surfaces of protein-recognition motifs are potential privileged scaffolds as protein-complex antagonists--to address the challenges inherent in the discovery of small-molecule inhibitors of protein-protein interactions.

  18. The nonstructural protein 8 (nsp8) of the SARS coronavirus interacts with its ORF6 accessory protein

    SciTech Connect

    Kumar, Purnima; Gunalan, Vithiagaran; Liu Boping; Chow, Vincent T.K.; Druce, Julian; Birch, Chris; Catton, Mike; Fielding, Burtram C.; Tan, Yee-Joo; Lal, Sunil K.

    2007-09-30

    Severe acute respiratory syndrome (SARS) coronavirus (SARS-CoV) caused a severe outbreak in several regions of the world in 2003. The SARS-CoV genome is predicted to contain 14 functional open reading frames (ORFs). The first ORF (1a and 1b) encodes a large polyprotein that is cleaved into nonstructural proteins (nsp). The other ORFs encode for four structural proteins (spike, membrane, nucleocapsid and envelope) as well as eight SARS-CoV-specific accessory proteins (3a, 3b, 6, 7a, 7b, 8a, 8b and 9b). In this report we have cloned the predicted nsp8 gene and the ORF6 gene of the SARS-CoV and studied their abilities to interact with each other. We expressed the two proteins as fusion proteins in the yeast two-hybrid system to demonstrate protein-protein interactions and tested the same using a yeast genetic cross. Further the strength of the interaction was measured by challenging growth of the positive interaction clones on increasing gradients of 2-amino trizole. The interaction was then verified by expressing both proteins separately in-vitro in a coupled-transcription translation system and by coimmunoprecipitation in mammalian cells. Finally, colocalization experiments were performed in SARS-CoV infected Vero E6 mammalian cells to confirm the nsp8-ORF6 interaction. To the best of our knowledge, this is the first report of the interaction between a SARS-CoV accessory protein and nsp8 and our findings suggest that ORF6 protein may play a role in virus replication.

  19. Evolution of protein interactions: from interactomes to interfaces.

    PubMed

    Andreani, Jessica; Guerois, Raphael

    2014-07-15

    Protein-protein interactions lie at the heart of most cellular processes. Many experimental and computational studies aim to deepen our understanding of these interactions and improve our capacity to predict them. In this respect, the evolutionary perspective is most interesting, since the preservation of structure and function puts constraints on the evolution of proteins and their interactions. However, uncovering these constraints remains a challenge, and the description and detection of evolutionary signals in protein-protein interactions is currently a very active field of research. Here, we review recent works dissecting the mechanisms of protein-protein interaction evolution and exploring how to use evolutionary information to predict interactions, both at the global level of the interactome and at the detailed level of protein-protein interfaces. We first present to what extent protein-protein interactions are found to be conserved within interactomes and which properties can influence their conservation. We then discuss the evolutionary and co-evolutionary pressures applied on protein-protein interfaces. Finally, we describe how the computational prediction of interfaces can benefit from evolutionary inputs. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. Defining subdomains of the K domain important for protein-protein interactions of plant MADS proteins.

    PubMed

    Yang, Yingzhen; Jack, Thomas

    2004-05-01

    The MADS proteins APETALA3 (AP3), PISTILLATA (PI), SEPALLATAI (SEPI), SEP2, SEP3, AGAMOUS, and APETALA are required for proper floral organ identity in Arabidopsis flowers. All of these floral MADS proteins conserve two domains: the MADS domain that mediates DNA binding and dimerization, and the K domain that mediates protein protein interaction. The K domain is postulated to form a several amphipathic c-helices referred to as K1, K2, and K3. The K1 and K2 helicies are located entirely within the K domain while the K3 helix spans the K domain-C domain boundary. Here we report on our studies on the interactions of the B class MADS proteins AP3 and PI with the E class MADS proteins SEP1, SEP2, and SEP3. A comparative analysis of mutants in the K domain reveals that the subdomains mediating the PI/AP3 interaction are different from the subdomains mediating the PI/SEP3 (or PI/SEP1) interaction. The strong PI/SEP3 (or PI/SEP1) interaction requires K2, part of K3, and the interhelical region between K1 and K2. By contrast, K1, K2 and the region between K1 and K2 are important for strong AP3/PI interaction. Most of the K3 helix does not appear to be important for either the PI/AP3 or the PI/SEP3 (or PI/SEP1) interaction. Conserved hydrophobic positions are most important for the strength of both PI/AP3 and PI/SEP3 dimerization, though ionic and/or polar interactions appear to play a secondary role.

  1. MCLIP Detection of Novel Protein-Protein Interactions at the Nuclear Envelope.

    PubMed

    Jafferali, Mohammed Hakim; Figueroa, Ricardo A; Hallberg, Einar

    2016-01-01

    The organization and function of the nuclear envelope (NE) involves hundreds of nuclear membrane proteins and myriad protein-protein interactions, most of which are still uncharacterized. Many NE proteins interact stably or dynamically with the nuclear lamina or chromosomes. This can make them difficult to extract under nondenaturing conditions, and greatly limits our ability to explore and identify functional protein interactions at the NE. This knowledge is needed to understand nuclear envelope structure and the mechanisms of human laminopathy diseases. This chapter provides detailed protocols for MCLIP (membrane cross-linking immunoprecipitation) identification of novel protein-protein interactions in mammalian cells.

  2. Protein-Protein Interactions Suggest Novel Activities of Human Cytomegalovirus Tegument Protein pUL103

    PubMed Central

    Ortiz, Daniel A.; Glassbrook, James E.

    2016-01-01

    ABSTRACT Human cytomegalovirus (HCMV) is an enveloped double-stranded DNA virus that causes severe disease in newborns and immunocompromised patients. During infection, the host cell endosecretory system is remodeled to form the cytoplasmic virion assembly complex (cVAC). We and others previously identified the conserved, multifunctional HCMV virion tegument protein pUL103 as important for cVAC biogenesis and efficient secondary envelopment. To help define its mechanisms of action and predict additional functions, we used two complementary methods, coimmunoprecipitation (co-IP) and proximity biotinylation (BioID), to identify viral and cellular proteins that interact with pUL103. By using the two methods in parallel and applying stringent selection criteria, we identified potentially high-value interactions of pUL103 with 13 HCMV and 18 cellular proteins. Detection of the previously identified pUL103-pUL71 interaction, as well as verification of several interactions by reverse co-IP, supports the specificity of our screening process. As might be expected for a tegument protein, interactions were identified that suggest distinct roles for pUL103 across the arc of lytic infection, including interactions with proteins involved in cellular antiviral responses, nuclear activities, and biogenesis and transport of cytoplasmic vesicles. Further analysis of some of these interactions expands our understanding of the multifunctional repertoire of pUL103: we detected HCMV pUL103 in nuclei of infected cells and identified an ALIX-binding domain within the pUL103 sequence. IMPORTANCE Human cytomegalovirus (HCMV) is able to reconfigure the host cell machinery to establish a virion production factory, the cytoplasmic virion assembly complex (cVAC). cVAC biogenesis and operation represent targets for development of novel HCMV antivirals. We previously showed that the HCMV tegument protein pUL103 is required for cVAC biogenesis. Using pUL103 as bait, we investigated viral and

  3. Cryptic protein-protein interaction motifs in the cytoplasmic domain of MHCI proteins.

    PubMed

    Frietze, Karla K; Pappy, Adlai L; Melson, Jack W; O'Driscoll, Emily E; Tyler, Carolyn M; Perlman, David H; Boulanger, Lisa M

    2016-07-19

    Major histocompatibility complex class I (MHCI) proteins present antigenic peptides for immune surveillance and play critical roles in nervous system development and plasticity. Most MHCI are transmembrane proteins. The extracellular domain of MHCI interacts with immunoreceptors, peptides, and co-receptors to mediate immune signaling. While the cytoplasmic domain also plays important roles in endocytic trafficking, cross-presentation of extracellularly derived antigens, and CTL priming, the molecular mediators of cytoplasmic signaling by MHCI remain largely unknown. Here we show that the cytoplasmic domain of MHCI contains putative protein-protein interaction domains known as PDZ (PSD95/disc large/zonula occludens-1) ligands. PDZ ligands are motifs that bind to PDZ domains to organize and mediate signaling at cell-cell contacts. PDZ ligands are short, degenerate motifs, and are therefore difficult to identify via sequence homology alone, but several lines of evidence suggest that putative PDZ ligand motifs in MHCI are under positive selective pressure. Putative PDZ ligands are found in all of the 99 MHCI proteins examined from diverse species, and are enriched in the cytoplasmic domain, where PDZ interactions occur. Both the position of the PDZ ligand and the class of ligand motif are conserved across species, as well as among genes within a species. Non-synonymous substitutions, when they occur, frequently preserve the motif. Of the many specific possible PDZ ligand motifs, a handful are strikingly and selectively overrepresented in MHCI's cytoplasmic domain, but not elsewhere in the same proteins. Putative PDZ ligands in MHCI encompass conserved serine and tyrosine residues that are targets of phosphorylation, a post-translational modification that can regulate PDZ interactions. Finally, proof-of-principle in vitro interaction assays demonstrate that the cytoplasmic domains of particular MHCI proteins can bind directly and specifically to PDZ1 and PDZ4&5 of MAGI

  4. S-linked protein homocysteinylation: identifying targets based on structural, physicochemical and protein-protein interactions of homocysteinylated proteins.

    PubMed

    Silla, Yumnam; Sundaramoorthy, Elayanambi; Talwar, Puneet; Sengupta, Shantanu

    2013-05-01

    An elevated level of homocysteine, a thiol-containing amino acid is associated with a wide spectrum of disease conditions. A majority (>80 %) of the circulating homocysteine exist in protein-bound form. Homocysteine can bind to free cysteine residues in the protein or could cleave accessible cysteine disulfide bonds via thiol disulfide exchange reaction. Binding of homocysteine to proteins could potentially alter the structure and/or function of the protein. To date only 21 proteins have been experimentally shown to bind homocysteine. In this study we attempted to identify other proteins that could potentially bind to homocysteine based on the criteria that such proteins will have significant 3D structural homology with the proteins that have been experimentally validated and have solvent accessible cysteine residues either with high dihedral strain energy (for cysteine-cysteine disulfide bonds) or low pKa (for free cysteine residues). This analysis led us to the identification of 78 such proteins of which 68 proteins had 154 solvent accessible disulfide cysteine pairs with high dihedral strain energy and 10 proteins had free cysteine residues with low pKa that could potentially bind to homocysteine. Further, protein-protein interaction network was built to identify the interacting partners of these putative homocysteine binding proteins. We found that the 21 experimentally validated proteins had 174 interacting partners while the 78 proteins identified in our analysis had 445 first interacting partners. These proteins are mainly involved in biological activities such as complement and coagulation pathway, focal adhesion, ECM-receptor, ErbB signalling and cancer pathways, etc. paralleling the disease-specific attributes associated with hyperhomocysteinemia.

  5. Improved understanding of pathogenesis from protein interactions in Mycobacterium tuberculosis.

    PubMed

    Cui, Tao; He, Zheng-Guo

    2014-12-01

    Comprehensive mapping and analysis of protein-protein interactions provide not only systematic approaches for dissecting the infection and survival mechanisms of pathogens but also clues for discovering new antibacterial drug targets. Protein interaction data on Mycobacterium tuberculosis have rapidly accumulated over the past several years. This review summarizes the current progress of protein interaction studies on M. tuberculosis, the causative agent of tuberculosis. These efforts improve our knowledge on the stress response, signaling regulation, protein secretion and drug resistance of the bacteria. M. tuberculosis-host protein interaction studies, although still limited, have recently opened a new door for investigating the pathogenesis of the bacteria. Finally, this review discusses the importance of protein interaction data on identifying and screening new anti-tuberculosis targets and drugs, respectively.

  6. 7A projection map of the S-layer protein sbpA obtained with trehalose-embedded monolayer crystals.

    PubMed

    Norville, Julie E; Kelly, Deborah F; Knight, Thomas F; Belcher, Angela M; Walz, Thomas

    2007-12-01

    Two-dimensional crystallization on lipid monolayers is a versatile tool to obtain structural information of proteins by electron microscopy. An inherent problem with this approach is to prepare samples in a way that preserves the crystalline order of the protein array and produces specimens that are sufficiently flat for high-resolution data collection at high tilt angles. As a test specimen to optimize the preparation of lipid monolayer crystals for electron microscopy imaging, we used the S-layer protein sbpA, a protein with potential for designing arrays of both biological and inorganic materials with engineered properties for a variety of nanotechnology applications. Sugar embedding is currently considered the best method to prepare two-dimensional crystals of membrane proteins reconstituted into lipid bilayers. We found that using a loop to transfer lipid monolayer crystals to an electron microscopy grid followed by embedding in trehalose and quick-freezing in liquid ethane also yielded the highest resolution images for sbpA lipid monolayer crystals. Using images of specimens prepared in this way we could calculate a projection map of sbpA at 7A resolution, one of the highest resolution projection structures obtained with lipid monolayer crystals to date.

  7. Resolution of the structure of the allergenic and antifungal banana fruit thaumatin-like protein at 1.7-A.

    PubMed

    Leone, Philippe; Menu-Bouaouiche, Laurence; Peumans, Willy J; Payan, Françoise; Barre, Annick; Roussel, Alain; Van Damme, Els J M; Rougé, Pierre

    2006-01-01

    The structure of a thaumatin-like protein from banana (Musa acuminata) fruit, an allergen with antifungal properties, was solved at 1.7-A-resolution, by X-ray crystallography. Though the banana protein exhibits a very similar overall fold as thaumatin it markedly differs from the sweet-tasting protein by the presence of a surface exposed electronegative cleft. Due to the presence of this electronegative cleft, the banana thaumatin-like protein (Ban-TLP) acquires a strong (local) electronegative character that eventually explains the observed antifungal activity. Our structural analysis also revealed the presence of conserved residues of exposed epitopic determinants that are presumably responsible for the allergenic properties of banana fruit towards susceptible individuals, and provided evidence that the Ban-TLP shares some structurally highly conserved IgE-binding epitopes with thaumatin-like proteins from fruits or pollen from other plants. In addition, some overlap was detected between the predicted IgE-binding epitopes of the Ban-TLP and IgE-binding epitopes previously identified in the mountain cedar Jun a 3 TLP aeroallergen. The presence of these common epitopes offers a molecular basis for the cross-reactivity between aeroallergens and fruit allergens.

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

    PubMed

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

    2014-04-01

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

  9. Protein-Protein Interaction (PPI) Network: Recent Advances in Drug Discovery.

    PubMed

    Athanasios, Alexiou; Charalampos, Vairaktarakis; Vasileios, Tsiamis; Ashraf, Ghulam Md

    2017-01-01

    The investigation of the cellular components, their interactions and related functions constitute the major conditions in order to understand the cell as an integrated system. More specifically, the Protein-Protein Interactions and the obtained networks are very important in the majority of biological functions and processes, while most of the proteins appear to activate their functionalities through their interaction. Our in depth review analysis, include Sixty-five peer-reviewed research and review studies from several bibliographic databases. The most significant components were fully described, filtered, combined and analyzed in order to provide documented proofs on the Protein-Protein Interaction Network' applications in biomedicine. The Protein-Protein Interaction Network' alignment and mapping give the opportunity of further knowledge extraction concerning the evolutionary relationships between the species through conserved pathways and protein complexes. Additionally, Protein-Protein Interaction Network information has been demonstrated to be able to predict functionally orthologous proteins within sequence homology clusters. Our review analysis concluded that, while Protein- Protein Interaction was used to be characterized just by their large and plain interacting surfaces, they were considered inapplicable for drug discovery studies for a long time. The present review explores multiple technologies implicated in Protein-Protein Interaction Networks, implicating their potential role in drug discovery mechanisms. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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

    ERIC Educational Resources Information Center

    Witherow, D. Scott; Carson, Sue

    2011-01-01

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

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

    ERIC Educational Resources Information Center

    Witherow, D. Scott; Carson, Sue

    2011-01-01

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

  12. Computational approaches for detecting protein complexes from protein interaction networks: a survey

    PubMed Central

    2010-01-01

    Background Most proteins form macromolecular complexes to perform their biological functions. However, experimentally determined protein complex data, especially of those involving more than two protein partners, are relatively limited in the current state-of-the-art high-throughput experimental techniques. Nevertheless, many techniques (such as yeast-two-hybrid) have enabled systematic screening of pairwise protein-protein interactions en masse. Thus computational approaches for detecting protein complexes from protein interaction data are useful complements to the limited experimental methods. They can be used together with the experimental methods for mapping the interactions of proteins to understand how different proteins are organized into higher-level substructures to perform various cellular functions. Results Given the abundance of pairwise protein interaction data from high-throughput genome-wide experimental screenings, a protein interaction network can be constructed from protein interaction data by considering individual proteins as the nodes, and the existence of a physical interaction between a pair of proteins as a link. This binary protein interaction graph can then be used for detecting protein complexes using graph clustering techniques. In this paper, we review and evaluate the state-of-the-art techniques for computational detection of protein complexes, and discuss some promising research directions in this field. Conclusions Experimental results with yeast protein interaction data show that the interaction subgraphs discovered by various computational methods matched well with actual protein complexes. In addition, the computational approaches have also improved in performance over the years. Further improvements could be achieved if the quality of the underlying protein interaction data can be considered adequately to minimize the undesirable effects from the irrelevant and noisy sources, and the various biological evidences can be better

  13. Three-dimensional visualization of protein interaction networks.

    PubMed

    Han, Kyungsook; Byun, Yanga

    2004-03-01

    Protein interaction networks provide us with contextual information within which protein function can be interpreted and will assist many biomedical studies. We have developed a new force-directed layout algorithm for visualizing protein interactions in three-dimensional space. Our algorithm divides nodes into three groups based on their interacting properties: bi-connected sub-graph in the center, terminal nodes at the outermost region, and the rest in between them. Experimental results show that our algorithm efficiently generates a clear and aesthetically pleasing drawing of large-scale protein interaction networks and that it is an order of magnitude faster than other force-directed layouts.

  14. Phage display library screening for identification of interacting protein partners.

    PubMed

    Addepalli, Balasubrahmanyam; Rao, Suryadevara; Hunt, Arthur G

    2015-01-01

    Phage display is a versatile high-throughput screening method employed to understand and improve the chemical biology, be it production of human monoclonal antibodies or identification of interacting protein partners. A majority of cell proteins operate in a concerted fashion either by stable or transient interactions. Such interactions can be mediated by recognition of small amino acid sequence motifs on the protein surface. Phage display can play a crucial role in identification of such motifs. This report describes the use of phage display for the identification of high affinity sequence motifs that could be responsible for interactions with a target (bait) protein.

  15. Human enterovirus 71 protein interaction network prompts antiviral drug repositioning.

    PubMed

    Han, Lu; Li, Kang; Jin, Chaozhi; Wang, Jian; Li, Qingjun; Zhang, Qiling; Cheng, Qiyue; Yang, Jing; Bo, Xiaochen; Wang, Shengqi

    2017-02-21

    As a predominant cause of human hand, foot, and mouth disease, enterovirus 71 (EV71) infection may lead to serious diseases and result in severe consequences that threaten public health and cause widespread panic. Although the systematic identification of physical interactions between viral proteins and host proteins provides initial information for the recognition of the cellular mechanism involved in viral infection and the development of new therapies, EV71-host protein interactions have not been explored. Here, we identified interactions between EV71 proteins and host cellular proteins and confirmed the functional relationships of EV71-interacting proteins (EIPs) with virus proliferation and infection by integrating a human protein interaction network and by functional annotation. We found that most EIPs had known interactions with other viruses. We also predicted ATP6V0C as a broad-spectrum essential host factor and validated its essentiality for EV71 infection in vitro. EIPs and their interacting proteins were more likely to be targets of anti-inflammatory and neurological drugs, indicating their potential to serve as host-oriented antiviral targets. Thus, we used a connectivity map to find drugs that inhibited EIP expression. We predicted tanespimycin as a candidate and demonstrated its antiviral efficiency in vitro. These findings provide the first systematic identification of EV71-host protein interactions, an analysis of EIP protein characteristics and a demonstration of their value in developing host-oriented antiviral therapies.

  16. Human enterovirus 71 protein interaction network prompts antiviral drug repositioning

    PubMed Central

    Han, Lu; Li, Kang; Jin, Chaozhi; Wang, Jian; Li, Qingjun; Zhang, Qiling; Cheng, Qiyue; Yang, Jing; Bo, Xiaochen; Wang, Shengqi

    2017-01-01

    As a predominant cause of human hand, foot, and mouth disease, enterovirus 71 (EV71) infection may lead to serious diseases and result in severe consequences that threaten public health and cause widespread panic. Although the systematic identification of physical interactions between viral proteins and host proteins provides initial information for the recognition of the cellular mechanism involved in viral infection and the development of new therapies, EV71-host protein interactions have not been explored. Here, we identified interactions between EV71 proteins and host cellular proteins and confirmed the functional relationships of EV71-interacting proteins (EIPs) with virus proliferation and infection by integrating a human protein interaction network and by functional annotation. We found that most EIPs had known interactions with other viruses. We also predicted ATP6V0C as a broad-spectrum essential host factor and validated its essentiality for EV71 infection in vitro. EIPs and their interacting proteins were more likely to be targets of anti-inflammatory and neurological drugs, indicating their potential to serve as host-oriented antiviral targets. Thus, we used a connectivity map to find drugs that inhibited EIP expression. We predicted tanespimycin as a candidate and demonstrated its antiviral efficiency in vitro. These findings provide the first systematic identification of EV71-host protein interactions, an analysis of EIP protein characteristics and a demonstration of their value in developing host-oriented antiviral therapies. PMID:28220872

  17. Examining post-translational modification-mediated protein-protein interactions using a chemical proteomics approach.

    PubMed

    Li, Xiang; Foley, Emily A; Kawashima, Shigehiro A; Molloy, Kelly R; Li, Yinyin; Chait, Brian T; Kapoor, Tarun M

    2013-03-01

    Post-translational modifications (PTM) of proteins can control complex and dynamic cellular processes via regulating interactions between key proteins. To understand these regulatory mechanisms, it is critical that we can profile the PTM-dependent protein-protein interactions. However, identifying these interactions can be very difficult using available approaches, as PTMs can be dynamic and often mediate relatively weak protein-protein interactions. We have recently developed CLASPI (cross-linking-assisted and stable isotope labeling in cell culture-based protein identification), a chemical proteomics approach to examine protein-protein interactions mediated by methylation in human cell lysates. Here, we report three extensions of the CLASPI approach. First, we show that CLASPI can be used to analyze methylation-dependent protein-protein interactions in lysates of fission yeast, a genetically tractable model organism. For these studies, we examined trimethylated histone H3 lysine-9 (H3K9Me₃)-dependent protein-protein interactions. Second, we demonstrate that CLASPI can be used to examine phosphorylation-dependent protein-protein interactions. In particular, we profile proteins recognizing phosphorylated histone H3 threonine-3 (H3T3-Phos), a mitotic histone "mark" appearing exclusively during cell division. Our approach identified survivin, the only known H3T3-Phos-binding protein, as well as other proteins, such as MCAK and KIF2A, that are likely to be involved in weak but selective interactions with this histone phosphorylation "mark". Finally, we demonstrate that the CLASPI approach can be used to study the interplay between histone H3T3-Phos and trimethylation on the adjacent residue lysine 4 (H3K4Me₃). Together, our findings indicate the CLASPI approach can be broadly applied to profile protein-protein interactions mediated by PTMs. Copyright © 2013 The Protein Society.

  18. Detecting remotely related proteins by their interactions and sequence similarity

    PubMed Central

    Espadaler, Jordi; Aragüés, Ramón; Eswar, Narayanan; Marti-Renom, Marc A.; Querol, Enrique; Avilés, Francesc X.; Sali, Andrej; Oliva, Baldomero

    2005-01-01

    The function of an uncharacterized protein is usually inferred either from its homology to, or its interactions with, characterized proteins. Here, we use both sequence similarity and protein interactions to identify relationships between remotely related protein sequences. We rely on the fact that homologous sequences share similar interactions, and, therefore, the set of interacting partners of the partners of a given protein is enriched by its homologs. The approach was benchmarked by assigning the fold and functional family to test sequences of known structure. Specifically, we relied on 1,434 proteins with known folds, as defined in the Structural Classification of Proteins (SCOP) database, and with known interacting partners, as defined in the Database of Interacting Proteins (DIP). For this subset, the specificity of fold assignment was increased from 54% for position-specific iterative blast to 75% for our approach, with a concomitant increase in sensitivity for a few percentage points. Similarly, the specificity of family assignment at the e-value threshold of 10-8 was increased from 70% to 87%. The proposed method would be a useful tool for large-scale automated discovery of remote relationships between protein sequences, given its unique reliance on sequence similarity and protein-protein interactions. PMID:15883372

  19. Encoding protein-ligand interaction patterns in fingerprints and graphs.

    PubMed

    Desaphy, Jérémy; Raimbaud, Eric; Ducrot, Pierre; Rognan, Didier

    2013-03-25

    We herewith present a novel and universal method to convert protein-ligand coordinates into a simple fingerprint of 210 integers registering the corresponding molecular interaction pattern. Each interaction (hydrophobic, aromatic, hydrogen bond, ionic bond, metal complexation) is detected on the fly and physically described by a pseudoatom centered either on the interacting ligand atom, the interacting protein atom, or the geometric center of both interacting atoms. Counting all possible triplets of interaction pseudoatoms within six distance ranges, and pruning the full integer vector to keep the most frequent triplets enables the definition of a simple (210 integers) and coordinate frame-invariant interaction pattern descriptor (TIFP) that can be applied to compare any pair of protein-ligand complexes. TIFP fingerprints have been calculated for ca. 10,000 druggable protein-ligand complexes therefore enabling a wide comparison of relationships between interaction pattern similarity and ligand or binding site pairwise similarity. We notably show that interaction pattern similarity strongly depends on binding site similarity. In addition to the TIFP fingerprint which registers intermolecular interactions between a ligand and its target protein, we developed two tools (Ishape, Grim) to align protein-ligand complexes from their interaction patterns. Ishape is based on the overlap of interaction pseudoatoms using a smooth Gaussian function, whereas Grim utilizes a standard clique detection algorithm to match interaction pattern graphs. Both tools are complementary and enable protein-ligand complex alignments capitalizing on both global and local pattern similarities. The new fingerprint and companion alignment tools have been successfully used in three scenarios: (i) interaction-biased alignment of protein-ligand complexes, (ii) postprocessing docking poses according to known interaction patterns for a particular target, and (iii) virtual screening for bioisosteric

  20. Discovering patterns to extract protein-protein interactions from full texts.

    PubMed

    Huang, Minlie; Zhu, Xiaoyan; Hao, Yu; Payan, Donald G; Qu, Kunbin; Li, Ming

    2004-12-12

    Although there are several databases storing protein-protein interactions, most such data still exist only in the scientific literature. They are scattered in scientific literature written in natural languages, defying data mining efforts. Much time and labor have to be spent on extracting protein pathways from literature. Our aim is to develop a robust and powerful methodology to mine protein-protein interactions from biomedical texts. We present a novel and robust approach for extracting protein-protein interactions from literature. Our method uses a dynamic programming algorithm to compute distinguishing patterns by aligning relevant sentences and key verbs that describe protein interactions. A matching algorithm is designed to extract the interactions between proteins. Equipped only with a dictionary of protein names, our system achieves a recall rate of 80.0% and precision rate of 80.5%. The program is available on request from the authors.

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

    PubMed

    Kandel, Sylvie E; Lampe, Jed N

    2014-09-15

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

  2. Modularity in the evolution of yeast protein interaction network

    PubMed Central

    Ogishima, Soichi; Tanaka, Hiroshi; Nakaya, Jun

    2015-01-01

    Protein interaction networks are known to exhibit remarkable structures: scale-free and small-world and modular structures. To explain the evolutionary processes of protein interaction networks possessing scale-free and small-world structures, preferential attachment and duplication-divergence models have been proposed as mathematical models. Protein interaction networks are also known to exhibit another remarkable structural characteristic, modular structure. How the protein interaction networks became to exhibit modularity in their evolution? Here, we propose a hypothesis of modularity in the evolution of yeast protein interaction network based on molecular evolutionary evidence. We assigned yeast proteins into six evolutionary ages by constructing a phylogenetic profile. We found that all the almost half of hub proteins are evolutionarily new. Examining the evolutionary processes of protein complexes, functional modules and topological modules, we also found that member proteins of these modules tend to appear in one or two evolutionary ages. Moreover, proteins in protein complexes and topological modules show significantly low evolutionary rates than those not in these modules. Our results suggest a hypothesis of modularity in the evolution of yeast protein interaction network as systems evolution. PMID:25914446

  3. Large-scale mapping of human protein-protein interactions by mass spectrometry.

    PubMed

    Ewing, Rob M; Chu, Peter; Elisma, Fred; Li, Hongyan; Taylor, Paul; Climie, Shane; McBroom-Cerajewski, Linda; Robinson, Mark D; O'Connor, Liam; Li, Michael; Taylor, Rod; Dharsee, Moyez; Ho, Yuen; Heilbut, Adrian; Moore, Lynda; Zhang, Shudong; Ornatsky, Olga; Bukhman, Yury V; Ethier, Martin; Sheng, Yinglun; Vasilescu, Julian; Abu-Farha, Mohamed; Lambert, Jean-Philippe; Duewel, Henry S; Stewart, Ian I; Kuehl, Bonnie; Hogue, Kelly; Colwill, Karen; Gladwish, Katharine; Muskat, Brenda; Kinach, Robert; Adams, Sally-Lin; Moran, Michael F; Morin, Gregg B; Topaloglou, Thodoros; Figeys, Daniel

    2007-01-01

    Mapping protein-protein interactions is an invaluable tool for understanding protein function. Here, we report the first large-scale study of protein-protein interactions in human cells using a mass spectrometry-based approach. The study maps protein interactions for 338 bait proteins that were selected based on known or suspected disease and functional associations. Large-scale immunoprecipitation of Flag-tagged versions of these proteins followed by LC-ESI-MS/MS analysis resulted in the identification of 24,540 potential protein interactions. False positives and redundant hits were filtered out using empirical criteria and a calculated interaction confidence score, producing a data set of 6463 interactions between 2235 distinct proteins. This data set was further cross-validated using previously published and predicted human protein interactions. In-depth mining of the data set shows that it represents a valuable source of novel protein-protein interactions with relevance to human diseases. In addition, via our preliminary analysis, we report many novel protein interactions and pathway associations.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

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

    2016-11-16

    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.

  6. Effects of pH on protein-protein interactions and implications for protein phase behavior.

    PubMed

    Dumetz, André C; Chockla, Aaron M; Kaler, Eric W; Lenhoff, Abraham M

    2008-04-01

    The effects of pH on protein interactions and protein phase behavior were investigated by measuring the reduced second osmotic virial coefficient (b2) for ovalbumin and catalase, and the aggregate and crystal solubilities for ovalbumin, beta-lactoglobulin A and B, ribonuclease A and lysozyme. The b2 trends observed for ovalbumin and catalase show that protein interactions become increasingly attractive with decreasing pH. This trend is in good agreement with ovalbumin phase behavior, which was observed to evolve progressively with decreasing pH, leading to formation of amorphous aggregates instead of gel bead-like aggregates, and spherulites instead of needle-like crystals. For both acidic and basic proteins, the aggregate solubility during protein salting-out decreased with decreasing pH, and contrary to what is commonly believed, neither aggregate nor crystal solubility had a minimum at the isoelectric point. beta-Lactoglobulin B was the only protein investigated to show salting-in behavior, and crystals were obtained at low salt concentrations in the vicinity of its isoelectric point. The physical origin of the different trends observed during protein salting-in and salting-out is discussed, and the implications for protein crystallization are emphasized.

  7. Folding superfunnel to describe cooperative folding of interacting proteins.

    PubMed

    Smeller, László

    2016-07-01

    This paper proposes a generalization of the well-known folding funnel concept of proteins. In the funnel model the polypeptide chain is treated as an individual object not interacting with other proteins. Since biological systems are considerably crowded, protein-protein interaction is a fundamental feature during the life cycle of proteins. The folding superfunnel proposed here describes the folding process of interacting proteins in various situations. The first example discussed is the folding of the freshly synthesized protein with the aid of chaperones. Another important aspect of protein-protein interactions is the folding of the recently characterized intrinsically disordered proteins, where binding to target proteins plays a crucial role in the completion of the folding process. The third scenario where the folding superfunnel is used is the formation of aggregates from destabilized proteins, which is an important factor in case of several conformational diseases. The folding superfunnel constructed here with the minimal assumption about the interaction potential explains all three cases mentioned above. Proteins 2016; 84:1009-1016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  8. Identification of SLC7A7, encoding y+LAT-1, as the lysinuric protein intolerance gene.

    PubMed

    Torrents, D; Mykkänen, J; Pineda, M; Feliubadaló, L; Estévez, R; de Cid, R; Sanjurjo, P; Zorzano, A; Nunes, V; Huoponen, K; Reinikainen, A; Simell, O; Savontaus, M L; Aula, P; Palacín, M

    1999-03-01

    Lysinuric protein intolerance (LPI; OMIM 222700) is a rare, recessive disorder with a worldwide distribution, but with a high prevalence in the Finnish population; symptoms include failure to thrive, growth retardation, muscle hypotonia and hepatosplenomegaly. A defect in the plasma membrane transport of dibasic amino acids has been demonstrated at the baso-lateral membrane of epithelial cells in small intestine and in renal tubules and in plasma membrane of cultured skin fibroblasts from LPI patients. The gene causing LPI has been assigned by linkage analysis to 14q11-13. Here we report mutations in SLC7A7 cDNA (encoding y+L amino acid transporter-1, y+LAT-1), which expresses dibasic amino-acid transport activity and is located in the LPI region, in 31 Finnish LPI patients and 1 Spanish patient. The Finnish patients are homozygous for a founder missense mutation leading to a premature stop codon. The Spanish patient is a compound heterozygote with a missense mutation in one allele and a frameshift mutation in the other. The frameshift mutation generates a premature stop codon, eliminating the last one-third of the protein. The missense mutation abolishes y+LAT-1 amino-acid transport activity when co-expressed with the heavy chain of the cell-surface antigen 4F2 (4F2hc, also known as CD98) in Xenopus laevis oocytes. Our data establish that mutations in SLC7A7 cause LPI.

  9. Recent advances in clustering methods for protein interaction networks

    PubMed Central

    2010-01-01

    The increasing availability of large-scale protein-protein interaction data has made it possible to understand the basic components and organization of cell machinery from the network level. The arising challenge is how to analyze such complex interacting data to reveal the principles of cellular organization, processes and functions. Many studies have shown that clustering protein interaction network is an effective approach for identifying protein complexes or functional modules, which has become a major research topic in systems biology. In this review, recent advances in clustering methods for protein interaction networks will be presented in detail. The predictions of protein functions and interactions based on modules will be covered. Finally, the performance of different clustering methods will be compared and the directions for future research will be discussed. PMID:21143777

  10. What Evidence Is There for the Homology of Protein-Protein Interactions?

    PubMed Central

    Lewis, Anna C. F.; Jones, Nick S.; Porter, Mason A.; Deane, Charlotte M.

    2012-01-01

    The notion that sequence homology implies functional similarity underlies much of computational biology. In the case of protein-protein interactions, an interaction can be inferred between two proteins on the basis that sequence-similar proteins have been observed to interact. The use of transferred interactions is common, but the legitimacy of such inferred interactions is not clear. Here we investigate transferred interactions and whether data incompleteness explains the lack of evidence found for them. Using definitions of homology associated with functional annotation transfer, we estimate that conservation rates of interactions are low even after taking interactome incompleteness into account. For example, at a blastp -value threshold of , we estimate the conservation rate to be about between S. cerevisiae and H. sapiens. Our method also produces estimates of interactome sizes (which are similar to those previously proposed). Using our estimates of interaction conservation we estimate the rate at which protein-protein interactions are lost across species. To our knowledge, this is the first such study based on large-scale data. Previous work has suggested that interactions transferred within species are more reliable than interactions transferred across species. By controlling for factors that are specific to within-species interaction prediction, we propose that the transfer of interactions within species might be less reliable than transfers between species. Protein-protein interactions appear to be very rarely conserved unless very high sequence similarity is observed. Consequently, inferred interactions should be used with care. PMID:23028270

  11. Computer-aided design of functional protein interactions.

    PubMed

    Mandell, Daniel J; Kortemme, Tanja

    2009-11-01

    Predictive methods for the computational design of proteins search for amino acid sequences adopting desired structures that perform specific functions. Typically, design of 'function' is formulated as engineering new and altered binding activities into proteins. Progress in the design of functional protein-protein interactions is directed toward engineering proteins to precisely control biological processes by specifically recognizing desired interaction partners while avoiding competitors. The field is aiming for strategies to harness recent advances in high-resolution computational modeling-particularly those exploiting protein conformational variability-to engineer new functions and incorporate many functional requirements simultaneously.

  12. Protein interactions in genome maintenance as novel antibacterial targets.

    PubMed

    Marceau, Aimee H; Bernstein, Douglas A; Walsh, Brian W; Shapiro, Walker; Simmons, Lyle A; Keck, James L

    2013-01-01

    Antibacterial compounds typically act by directly inhibiting essential bacterial enzyme activities. Although this general mechanism of action has fueled traditional antibiotic discovery efforts for decades, new antibiotic development has not kept pace with the emergence of drug resistant bacterial strains. These limitations have severely restricted the therapeutic tools available for treating bacterial infections. Here we test an alternative antibacterial lead-compound identification strategy in which essential protein-protein interactions are targeted rather than enzymatic activities. Bacterial single-stranded DNA-binding proteins (SSBs) form conserved protein interaction "hubs" that are essential for recruiting many DNA replication, recombination, and repair proteins to SSB/DNA nucleoprotein substrates. Three small molecules that block SSB/protein interactions are shown to have antibacterial activity against diverse bacterial species. Consistent with a model in which the compounds target multiple SSB/protein interactions, treatment of Bacillus subtilis cultures with the compounds leads to rapid inhibition of DNA replication and recombination, and ultimately to cell death. The compounds also have unanticipated effects on protein synthesis that could be due to a previously unknown role for SSB/protein interactions in translation or to off-target effects. Our results highlight the potential of targeting protein-protein interactions, particularly those that mediate genome maintenance, as a powerful approach for identifying new antibacterial compounds.

  13. A web-based protein interaction network visualizer

    PubMed Central

    2014-01-01

    Background Interaction between proteins is one of the most important mechanisms in the execution of cellular functions. The study of these interactions has provided insight into the functioning of an organism’s processes. As of October 2013, Homo sapiens had over 170000 Protein-Protein interactions (PPI) registered in the Interologous Interaction Database, which is only one of the many public resources where protein interactions can be accessed. These numbers exemplify the volume of data that research on the topic has generated. Visualization of large data sets is a well known strategy to make sense of information, and protein interaction data is no exception. There are several tools that allow the exploration of this data, providing different methods to visualize protein network interactions. However, there is still no native web tool that allows this data to be explored interactively online. Results Given the advances that web technologies have made recently it is time to bring these interactive views to the web to provide an easily accessible forum to visualize PPI. We have created a Web-based Protein Interaction Network Visualizer: PINV, an open source, native web application that facilitates the visualization of protein interactions (http://biosual.cbio.uct.ac.za/pinv.html). We developed PINV as a set of components that follow the protocol defined in BioJS and use the D3 library to create the graphic layouts. We demonstrate the use of PINV with multi-organism interaction networks for a predicted target from Mycobacterium tuberculosis, its interacting partners and its orthologs. Conclusions The resultant tool provides an attractive view of complex, fully interactive networks with components that allow the querying, filtering and manipulation of the visible subset. Moreover, as a web resource, PINV simplifies sharing and publishing, activities which are vital in today’s research collaborative environments. The source code is freely available for download at

  14. The simulation approach to lipid-protein interactions.

    PubMed

    Paramo, Teresa; Garzón, Diana; Holdbrook, Daniel A; Khalid, Syma; Bond, Peter J

    2013-01-01

    The interactions between lipids and proteins are crucial for a range of biological processes, from the folding and stability of membrane proteins to signaling and metabolism facilitated by lipid-binding proteins. However, high-resolution structural details concerning functional lipid/protein interactions are scarce due to barriers in both experimental isolation of native lipid-bound complexes and subsequent biophysical characterization. The molecular dynamics (MD) simulation approach provides a means to complement available structural data, yielding dynamic, structural, and thermodynamic data for a protein embedded within a physiologically realistic, modelled lipid environment. In this chapter, we provide a guide to current methods for setting up and running simulations of membrane proteins and soluble, lipid-binding proteins, using standard atomistically detailed representations, as well as simplified, coarse-grained models. In addition, we outline recent studies that illustrate the power of the simulation approach in the context of biologically relevant lipid/protein interactions.

  15. Generating mammalian sirtuin tools for protein-interaction analysis.

    PubMed

    Hershberger, Kathleen A; Motley, Jonathan; Hirschey, Matthew D; Anderson, Kristin A

    2013-01-01

    The sirtuins are a family of NAD(+)-dependent deacylases with important effects on aging, cancer, and metabolism. Sirtuins exert their biological effects by catalyzing deacetylation and/or deacylation reactions in which Acyl groups are removed from lysine residues of specific proteins. A current challenge is to identify specific sirtuin target proteins against the high background of acetylated proteins recently identified by proteomic surveys. New evidence indicates that bona fide sirtuin substrate proteins form stable physical associations with their sirtuin regulator. Therefore, identification of sirtuin interacting proteins could be a useful aid in focusing the search for substrates. Described here is a method for identifying sirtuin protein interactors. Employing basic techniques of molecular cloning and immunochemistry, the method describes the generation of mammalian sirtuin protein expression plasmids and their use to overexpress and immunoprecipitate sirtuins with their interacting partners. Also described is the use of the Database for Annotation, Visualization, and Integrated Discovery for interpreting the sirtuin protein-interaction data obtained.

  16. Computational design of protein interactions: designing proteins that neutralize influenza by inhibiting its hemagglutinin surface protein

    NASA Astrophysics Data System (ADS)

    Fleishman, Sarel

    2012-02-01

    Molecular recognition underlies all life processes. Design of interactions not seen in nature is a test of our understanding of molecular recognition and could unlock the vast potential of subtle control over molecular interaction networks, allowing the design of novel diagnostics and therapeutics for basic and applied research. We developed the first general method for designing protein interactions. The method starts by computing a region of high affinity interactions between dismembered amino acid residues and the target surface and then identifying proteins that can harbor these residues. Designs are tested experimentally for binding the target surface and successful ones are affinity matured using yeast cell surface display. Applied to the conserved stem region of influenza hemagglutinin we designed two unrelated proteins that, following affinity maturation, bound hemagglutinin at subnanomolar dissociation constants. Co-crystal structures of hemagglutinin bound to the two designed binders were within 1Angstrom RMSd of their models, validating the accuracy of the design strategy. One of the designed proteins inhibits the conformational changes that underlie hemagglutinin's cell-invasion functions and blocks virus infectivity in cell culture, suggesting that such proteins may in future serve as diagnostics and antivirals against a wide range of pathogenic influenza strains. We have used this method to obtain experimentally validated binders of several other target proteins, demonstrating the generality of the approach. We discuss the combination of modeling and high-throughput characterization of design variants which has been key to the success of this approach, as well as how we have used the data obtained in this project to enhance our understanding of molecular recognition. References: Science 332:816 JMB, in press Protein Sci 20:753

  17. Interactions of nanoparticles with proteins: determination of equilibrium constants.

    PubMed

    Treuel, Lennart; Malissek, Marcelina

    2013-01-01

    The behavior of nanoparticles towards proteins is an important aspect across wide areas of nanotoxicology and nanomedicine. In this chapter, we describe a procedure to study the adsorption of proteins onto nanoparticle surfaces. Circular dichroism (CD) spectroscopy is utilized to quantify the amount of free protein in a solution, and the experimental information is evaluated to derive equilibrium constants for the protein adsorption/desorption equilibrium. These equilibrium constants are comparable parameters in describing the interactions between proteins and nanoparticles.

  18. Proteomic profiling of cellular proteins interacting with the hepatitis C virus core protein.

    PubMed

    Kang, Su-Min; Shin, Min-Jung; Kim, Jung-Hee; Oh, Jong-Won

    2005-05-01

    Hepatitis C virus (HCV) is a causative agent of chronic hepatitis and hepatocellular carcinoma. The core protein of HCV packages the viral RNA genome to form a nucleocapsid. In addition to its function as a structural protein, core protein is involved in regulation of cellular transcription, virus-induced transformation, and pathogenesis. To gain insights into cellular functions of the core protein by identification of cellular proteins interacting with the core protein, we employed a proteomic approach. Hepatocytes soluble cytoplasmic proteins were applied to the core proteins immobilized on Ni-nitrilotriacetic resin and total bound cellular proteins were resolved by 2-DE. Analyses of interacting proteins by matrix-assisted laser desorption/ionization-time of flight mass spectrometry allowed identification of 14 cellular proteins binding to the core protein. These proteins include DEAD-box polypeptide 5, similar in function to a known protein identified previously by yeast two-hybrid screening and 13 newly identified cellular proteins. Interestingly, nine protein spots were identified as intermediate microfilament proteins, including cytokeratins (five spots for cytokeratin 8, two for cytokeratin 19, and one for cytokeratin 18) and vimentin. Cytokeratin 8 and vimentin, which were previously shown to be involved in the infection processes of other viruses, were further analyzed to confirm their in vivo interactions with the core protein by immunoblotting and immunofluorescence microscopy. We discuss the functional implications of the interactions of the core protein with newly identified cellular proteins in HCV infection and pathogenesis.

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

    PubMed

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

    2015-10-22

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

  20. Conserved Cysteine Residues Provide a Protein-Protein Interaction Surface in Dual Oxidase (DUOX) Proteins*

    PubMed Central

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

    2013-01-01

    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. PMID:23362256

  1. Visualization and targeted disruption of protein interactions in living cells.

    PubMed

    Herce, Henry D; Deng, Wen; Helma, Jonas; Leonhardt, Heinrich; Cardoso, M Cristina

    2013-01-01

    Protein-protein interactions are the basis of all processes in living cells, but most studies of these interactions rely on biochemical in vitro assays. Here we present a simple and versatile fluorescent-three-hybrid (F3H) strategy to visualize and target protein-protein interactions. A high-affinity nanobody anchors a GFP-fusion protein of interest at a defined cellular structure and the enrichment of red-labelled interacting proteins is measured at these sites. With this approach, we visualize the p53-HDM2 interaction in living cells and directly monitor the disruption of this interaction by Nutlin 3, a drug developed to boost p53 activity in cancer therapy. We further use this approach to develop a cell-permeable vector that releases a highly specific peptide disrupting the p53 and HDM2 interaction. The availability of multiple anchor sites and the simple optical readout of this nanobody-based capture assay enable systematic and versatile analyses of protein-protein interactions in practically any cell type and species.

  2. PPIevo: protein-protein interaction prediction from PSSM based evolutionary information.

    PubMed

    Zahiri, Javad; Yaghoubi, Omid; Mohammad-Noori, Morteza; Ebrahimpour, Reza; Masoudi-Nejad, Ali

    2013-10-01

    Protein-protein interactions regulate a variety of cellular processes. There is a great need for computational methods as a complement to experimental methods with which to predict protein interactions due to the existence of many limitations involved in experimental techniques. Here, we introduce a novel evolutionary based feature extraction algorithm for protein-protein interaction (PPI) prediction. The algorithm is called PPIevo and extracts the evolutionary feature from Position-Specific Scoring Matrix (PSSM) of protein with known sequence. The algorithm does not depend on the protein annotations, and the features are based on the evolutionary history of the proteins. This enables the algorithm to have more power for predicting protein-protein interaction than many sequence based algorithms. Results on the HPRD database show better performance and robustness of the proposed method. They also reveal that the negative dataset selection could lead to an acute performance overestimation which is the principal drawback of the available methods.

  3. Roles of intrinsic disorder in protein-nucleic acid interactions.

    PubMed

    Dyson, H Jane

    2012-01-01

    Interactions between proteins and nucleic acids typify the role of disordered segments, linkers, tails and other entities in the function of complexes that must form with high affinity and specificity but which must be capable of dissociating when no longer needed. While much of the emphasis in the literature has been on the interactions of disordered proteins with other proteins, disorder is also frequently observed in nucleic acids (particularly RNA) and in the proteins that interact with them. The interactions of disordered proteins with DNA most often manifest as molding of the protein onto the B-form DNA structure, although some well-known instances involve remodeling of the DNA structure that seems to require that the interacting proteins be disordered to various extents in the free state. By contrast, induced fit in RNA-protein interactions has been recognized for many years-the existence and prevalence of this phenomenon provides the clearest possible evidence that RNA and its interactions with proteins must be considered as highly dynamic, and the dynamic nature of RNA and its multiplicity of folded and unfolded states is an integral part of its nature and function.

  4. Protein-protein interactions and protein modules in the control of neurotransmitter release.

    PubMed Central

    Benfenati, F; Onofri, F; Giovedí, S

    1999-01-01

    Information transfer among neurons is operated by neurotransmitters stored in synaptic vesicles and released to the extracellular space by an efficient process of regulated exocytosis. Synaptic vesicles are organized into two distinct functional pools, a large reserve pool in which vesicles are restrained by the actin-based cytoskeleton, and a quantitatively smaller releasable pool in which vesicles approach the presynaptic membrane and eventually fuse with it on stimulation. Both synaptic vesicle trafficking and neurotransmitter release depend on a precise sequence of events that include release from the reserve pool, targeting to the active zone, docking, priming, fusion and endocytotic retrieval of synaptic vesicles. These steps are mediated by a series of specific interactions among cytoskeletal, synaptic vesicle, presynaptic membrane and cytosolic proteins that, by acting in concert, promote the spatial and temporal regulation of the exocytotic machinery. The majority of these interactions are mediated by specific protein modules and domains that are found in many proteins and are involved in numerous intracellular processes. In this paper, the possible physiological role of these multiple protein-protein interactions is analysed, with ensuing updating and clarification of the present molecular model of the process of neurotransmitter release. PMID:10212473

  5. Protein–Protein Interactions in Virus–Host Systems

    PubMed Central

    Brito, Anderson F.; Pinney, John W.

    2017-01-01

    To study virus–host protein interactions, knowledge about viral and host protein architectures and repertoires, their particular evolutionary mechanisms, and information on relevant sources of biological data is essential. The purpose of this review article is to provide a thorough overview about these aspects. Protein domains are basic units defining protein interactions, and the uniqueness of viral domain repertoires, their mode of evolution, and their roles during viral infection make viruses interesting models of study. Mutations at protein interfaces can reduce or increase their binding affinities by changing protein electrostatics and structural properties. During the course of a viral infection, both pathogen and cellular proteins are constantly competing for binding partners. Endogenous interfaces mediating intraspecific interactions—viral–viral or host–host interactions—are constantly targeted and inhibited by exogenous interfaces mediating viral–host interactions. From a biomedical perspective, blocking such interactions is the main mechanism underlying antiviral therapies. Some proteins are able to bind multiple partners, and their modes of interaction define how fast these “hub proteins” evolve. “Party hubs” have multiple interfaces; they establish simultaneous/stable (domain–domain) interactions, and tend to evolve slowly. On the other hand, “date hubs” have few interfaces; they establish transient/weak (domain–motif) interactions by means of short linear peptides (15 or fewer residues), and can evolve faster. Viral infections are mediated by several protein–protein interactions (PPIs), which can be represented as networks (protein interaction networks, PINs), with proteins being depicted as nodes, and their interactions as edges. It has been suggested that viral proteins tend to establish interactions with more central and highly connected host proteins. In an evolutionary arms race, viral and host proteins are constantly

  6. Specificity of broad protein interaction surfaces for proteins with multiple binding partners.

    PubMed

    Uchikoga, Nobuyuki; Matsuzaki, Yuri; Ohue, Masahito; Akiyama, Yutaka

    2016-01-01

    Analysis of protein-protein interaction networks has revealed the presence of proteins with multiple interaction ligand proteins, such as hub proteins. For such proteins, multiple ligands would be predicted as interacting partners when predicting all-to-all protein-protein interactions (PPIs). In this work, to obtain a better understanding of PPI mechanisms, we focused on protein interaction surfaces, which differ between protein pairs. We then performed rigid-body docking to obtain information of interfaces of a set of decoy structures, which include many possible interaction surfaces between a certain protein pair. Then, we investigated the specificity of sets of decoy interactions between true binding partners in each case of alpha-chymotrypsin, actin, and cyclin-dependent kinase 2 as test proteins having multiple true binding partners. To observe differences in interaction surfaces of docking decoys, we introduced broad interaction profiles (BIPs), generated by assembling interaction profiles of decoys for each protein pair. After cluster analysis, the specificity of BIPs of true binding partners was observed for each receptor. We used two types of BIPs: those involved in amino acid sequences (BIP-seqs) and those involved in the compositions of interacting amino acid residue pairs (BIP-AAs). The specificity of a BIP was defined as the number of group members including all true binding partners. We found that BIP-AA cases were more specific than BIP-seq cases. These results indicated that the composition of interacting amino acid residue pairs was sufficient for determining the properties of protein interaction surfaces.

  7. Protein-Protein Interactions in Transcription: A Fertile Ground for Helix Mimetics

    PubMed Central

    Guarracino, Danielle A.; Bullock, Brooke N.; Arora, Paramjit S.

    2010-01-01

    Designed ligands that inhibit protein-protein interactions involved in gene expression are valuable as reagents for genomics research and as leads for drug discovery efforts. Selective modulation of protein-protein interactions has proven to be a daunting task for synthetic ligands; however, the last decade has seen significant advances in inhibitor design, especially for helical protein interfaces. This review discusses examples of transcriptional complexes targeted by designer helices. PMID:20882600

  8. Mini review: protein-protein interactions in transcription: a fertile ground for helix mimetics.

    PubMed

    Guarracino, Danielle A; Bullock, Brooke N; Arora, Paramjit S

    2011-01-01

    Designed ligands that inhibit protein-protein interactions involved in gene expression are valuable as reagents for genomics research and as leads for drug discovery efforts. Selective modulation of protein-protein interactions has proven to be a daunting task for synthetic ligands; however, the last decade has seen significant advances in inhibitor design, especially for helical protein interfaces. This review discusses examples of transcriptional complexes targeted by designer helices. 2010 Wiley Periodicals, Inc.

  9. Structural study of surfactant-dependent interaction with protein

    SciTech Connect

    Mehan, Sumit; Aswal, Vinod K.; Kohlbrecher, Joachim

    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.

  10. Mitochondrial nucleoid interacting proteins support mitochondrial protein synthesis.

    PubMed

    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.

  11. Mitochondrial nucleoid interacting proteins support mitochondrial protein synthesis

    PubMed Central

    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.

    2012-01-01

    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. PMID:22453275

  12. Molecular interactions between proteins and synthetic membrane polymer films

    SciTech Connect

    Pincet, F.; Perez, E.; Belfort, G.

    1995-04-01

    To help understand the effects of protein adsorption on membrane filtration performance, we have measured the molecular interactions between cellulose acetate films and two proteins with different properties (ribonuclease A and human serum albumin) with a surface force apparatus. Comparison of forces between two protein layers with those between a protein layer and a cellulose acetate (CA) film shows that, at high pH, both proteins retained their native conformation on interacting with the CA film while at the isoelectric point (pI) or below the tertiary structure of proteins was disturbed. These measurements provide the first molecular evidence that disruption of protein tertiary structure could be responsible for the reduced permeation flows observed during membrane filtration of protein solutions and suggest that operating at high pH values away from the pI of proteins will reduce such fouling. 60 refs., 9 figs., 5 tabs.

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

    PubMed

    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.

  14. RAIN: RNA–protein Association and Interaction Networks

    PubMed Central

    Junge, Alexander; Refsgaard, Jan C.; Garde, Christian; Pan, Xiaoyong; Santos, Alberto; Alkan, Ferhat; Anthon, Christian; von Mering, Christian; Workman, Christopher T.; Jensen, Lars Juhl; Gorodkin, Jan

    2017-01-01

    Protein association networks can be inferred from a range of resources including experimental data, literature mining and computational predictions. These types of evidence are emerging for non-coding RNAs (ncRNAs) as well. However, integration of ncRNAs into protein association networks is challenging due to data heterogeneity. Here, we present a database of ncRNA–RNA and ncRNA–protein interactions and its integration with the STRING database of protein–protein interactions. These ncRNA associations cover four organisms and have been established from curated examples, experimental data, interaction predictions and automatic literature mining. RAIN uses an integrative scoring scheme to assign a confidence score to each interaction. We demonstrate that RAIN outperforms the underlying microRNA-target predictions in inferring ncRNA interactions. RAIN can be operated through an easily accessible web interface and all interaction data can be downloaded. Database URL: http://rth.dk/resources/rain PMID:28077569

  15. Protein Interactions between Fe65, the LDL receptor-related protein and the amyloid precursor protein

    PubMed Central

    Mulvihill, Melinda; Guttman, Miklos; Komives, Elizabeth A.

    2011-01-01

    The adapter protein, Fe65 has been proposed to be the link between the intracellular domains of the amyloid precursor protein, APP (AICD) and the LDL receptor-related protein (LRP-CT). Functional linkage between these two proteins has been established and mutations within LRP-CT affect the amount of Aβ produced from APP. Previous work showed that the AICD binds to the protein interaction domain 2 (PID2) of Fe65. Although the structure of PID1 was solved recently all attempts to demonstrate LRP-CT binding to this domain failed. We used biophysical experiments and binding studies to investigate the binding between these three proteins. Full-length Fe65 bound more weakly to AICD than did N-terminally truncated forms, however the intramolecular domain-domain interactions that had been proposed to inhibit binding could not be observed using amide H/D exchange. Surprisingly, when the LRP-CT is phosphorylated at Tyr4507, it bound to Fe65-PID1 despite the fact that this domain belongs to the Dab-like subclass of PIDs that is not supposed to be phosphorylation dependent. Mutation of a critical arginine abolished binding providing further proof of the phosphorylation-dependence. The Fe65-PID1 domain thus provides a link between the Dab-like class and the IRS-like class of PID domains and is the first Dab-like family member to show phosphorylation-dependent binding. PMID:21650223

  16. Host–pathogen protein interactions predicted by comparative modeling

    PubMed Central

    Davis, Fred P.; Barkan, David T.; Eswar, Narayanan; McKerrow, James H.; Sali, Andrej

    2007-01-01

    Pathogens have evolved numerous strategies to infect their hosts, while hosts have evolved immune responses and other defenses to these foreign challenges. The vast majority of host–pathogen interactions involve protein–protein recognition, yet our current understanding of these interactions is limited. Here, we present and apply a computational whole-genome protocol that generates testable predictions of host–pathogen protein interactions. The protocol first scans the host and pathogen genomes for proteins with similarity to known protein complexes, then assesses these putative interactions, using structure if available, and, finally, filters the remaining interactions using biological context, such as the stage-specific expression of pathogen proteins and tissue expression of host proteins. The technique was applied to 10 pathogens, including species of Mycobacterium, apicomplexa, and kinetoplastida, responsible for “neglected” human diseases. The method was assessed by (1) comparison to a set of known host–pathogen interactions, (2) comparison to gene expression and essentiality data describing host and pathogen genes involved in infection, and (3) analysis of the functional properties of the human proteins predicted to interact with pathogen proteins, demonstrating an enrichment for functionally relevant host–pathogen interactions. We present several specific predictions that warrant experimental follow-up, including interactions from previously characterized mechanisms, such as cytoadhesion and protease inhibition, as well as suspected interactions in hypothesized networks, such as apoptotic pathways. Our computational method provides a means to mine whole-genome data and is complementary to experimental efforts in elucidating networks of host–pathogen protein interactions. PMID:17965183

  17. Making the LINC: SUN and KASH protein interactions

    PubMed Central

    Kim, Dae In; Birendra, KC; Roux, Kyle J.

    2015-01-01

    Cell nuclei are physically integrated with the cytoskeleton through the LINC complex (for LInker of Nucleoskeleton and Cytoskeleton), a structure that spans the nuclear envelope to link the nucleoskeleton and cytoskeleton. Outer nuclear membrane KASH domain proteins and inner nuclear membrane SUN domain proteins interact to form the core of the LINC complex. In this review we provide a comprehensive analysis of the reported protein-protein interactions for KASH and SUN domain proteins. This critical structure, directly connecting the genome with the rest of the cell, contributes to a myriad of cellular functions and, when perturbed, is associated with human disease. PMID:25720065

  18. Protein interaction discovery using parallel analysis of translated ORFs (PLATO).

    PubMed

    Zhu, Jian; Larman, H Benjamin; Gao, Geng; Somwar, Romel; Zhang, Zijuan; Laserson, Uri; Ciccia, Alberto; Pavlova, Natalya; Church, George; Zhang, Wei; Kesari, Santosh; Elledge, Stephen J

    2013-04-01

    Identifying physical interactions between proteins and other molecules is a critical aspect of biological analysis. Here we describe PLATO, an in vitro method for mapping such interactions by affinity enrichment of a library of full-length open reading frames displayed on ribosomes, followed by massively parallel analysis using DNA sequencing. We demonstrate the broad utility of the method for human proteins by identifying known and previously unidentified interacting partners of LYN kinase, patient autoantibodies, and the small-molecules gefitinib and dasatinib.

  19. Directional interactions and cooperativity between mechanosensitive membrane proteins

    PubMed Central

    Haselwandter, Christoph A.; Phillips, Rob

    2013-01-01

    While modern structural biology has provided us with a rich and diverse picture of membrane proteins, the biological function of membrane proteins is often influenced by the mechanical properties of the surrounding lipid bilayer. Here we explore the relation between the shape of membrane proteins and the cooperative function of membrane proteins induced by membrane-mediated elastic interactions. For the experimental model system of mechanosensitive ion channels we find that the sign and strength of elastic interactions depend on the protein shape, yielding distinct cooperative gating curves for distinct protein orientations. Our approach predicts how directional elastic interactions affect the molecular structure, organization, and biological function of proteins in crowded membranes. PMID:25309021

  20. IRView: a database and viewer for protein interacting regions

    PubMed Central

    Fujimori, Shigeo; Hirai, Naoya; Masuoka, Kazuyo; Oshikubo, Tomohiro; Yamashita, Tatsuhiro; Washio, Takanori; Saito, Ayumu; Nagasaki, Masao; Miyano, Satoru; Miyamoto-Sato, Etsuko

    2012-01-01

    Summary: Protein–protein interactions (PPIs) are mediated through specific regions on proteins. Some proteins have two or more protein interacting regions (IRs) and some IRs are competitively used for interactions with different proteins. IRView currently contains data for 3417 IRs in human and mouse proteins. The data were obtained from different sources and combined with annotated region data from InterPro. Information on non-synonymous single nucleotide polymorphism sites and variable regions owing to alternative mRNA splicing is also included. The IRView web interface displays all IR data, including user-uploaded data, on reference sequences so that the positional relationship between IRs can be easily understood. IRView should be useful for analyzing underlying relationships between the proteins behind the PPI networks. Availability: IRView is publicly available on the web at http://ir.hgc.jp/. Contact: nekoneko@ims.u-tokyo.ac.jp PMID:22592381

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

    PubMed

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

    2011-06-01

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

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

    PubMed Central

    Park, Kyunghyun; Kim, Docyong; Ha, Suhyun; Lee, Doheon

    2015-01-01

    As pharmacodynamic drug-drug interactions (PD DDIs) could lead to severe adverse effects in patients, it is important to identify potential PD DDIs in drug development. The signaling starting from drug targets is propagated through protein-protein interaction (PPI) networks. PD DDIs could occur by close interference on the same targets or within the same pathways as well as distant interference through cross-talking pathways. However, most of the previous approaches have considered only close interference by measuring distances between drug targets or comparing target neighbors. We have applied a random walk with restart algorithm to simulate signaling propagation from drug targets in order to capture the possibility of their distant interference. Cross validation with DrugBank and Kyoto Encyclopedia of Genes and Genomes DRUG shows that the proposed method outperforms the previous methods significantly. We also provide a web service with which PD DDIs for drug pairs can be analyzed at http://biosoft.kaist.ac.kr/targetrw. PMID:26469276

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

    PubMed

    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.

  4. H-7, a protein kinase C inhibitor, inhibits spontaneous tone and spasmogenic responses in normal and sensitized guinea pig trachea.

    PubMed

    de Diego, A; Cortijo, J; Villagrasa, V; Perpina, M; Morcillo, E J

    1995-12-01

    1. H-7, a protein kinase C inhibitor, fully inhibited the spontaneous and stimulated (KCl 20 mM or histamine 0.5 mM) tone of trachea from normal and sensitized guinea pig. 2. H-7 depressed the concentration-contraction curves to KCl, histamine or 5-hydroxytryptamine in epithelium-denuded, indomethacin-treated, trachea from normal and sensitized guinea pigs while responses to CaCl2 (in Ca2+ -free, K+ -depolarized tissues) and acetylcholine were not affected. 3. H-7 (100 microM did not depress Ca2+ (20 microM-induced contraction of Triton X-100 skinned trachea. 4. These results suggest the involvement of PKC in the maintenance of spontaneous tone and spasmogenic responses of guinea pig trachea.

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

    NASA Astrophysics Data System (ADS)

    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.

  6. Proteins interacting with Membranes: Protein Sorting and Membrane Shaping

    NASA Astrophysics Data System (ADS)

    Callan-Jones, Andrew

    2015-03-01

    Membrane-bound transport in cells requires generating membrane curvature. In addition, transport is selective, in order to establish spatial gradients of membrane components in the cell. The mechanisms underlying cell membrane shaping by proteins and the influence of curvature on membrane composition are active areas of study in cell biophysics. In vitro approaches using Giant Unilamellar Vesicles (GUVs) are a useful tool to identify the physical mechanisms that drive sorting of membrane components and membrane shape change by proteins. I will present recent work on the curvature sensing and generation of IRSp53, a protein belonging to the BAR family, whose members, sharing a banana-shaped backbone, are involved in endocytosis. Pulling membrane tubes with 10-100 nm radii from GUVs containing encapsulated IRSp53 have, unexpectedly, revealed a non-monotonic dependence of the protein concentration on the tube as a function of curvature. Experiments also show that bound proteins alter the tube mechanics and that protein phase separation along the tube occurs at low tensions. I will present accompanying theoretical work that can explain these findings based on the competition between the protein's intrinsic curvature and the effective rigidity of a membrane-protein patch.

  7. A Microfluidic Platform for Characterization of Protein—Protein Interactions

    PubMed Central

    Javanmard, Mehdi; Talasaz, Amirali H.; Nemat-Gorgani, Mohsen; Huber, David E.; Pease, Fabian; Ronaghi, Mostafa; Davis, Ronald W.

    2010-01-01

    Traditionally, expensive and time consuming techniques such as mass spectrometry and Western Blotting have been used for characterization of protein–protein interactions. In this paper, we describe the design, fabrication, and testing of a rapid and inexpensive sensor, involving the use of microelectrodes in a microchannel, which can be used for real-time electrical detection of specific interactions between proteins. We have successfully demonstrated detection of target glycoprotein–glycoprotein interactions, antigen-antibody interactions, and glycoprotein-antigen interactions. We have also demonstrated the ability of this technique to distinguish between strong and weak interactions. Using this approach, it may be possible to multiplex an array of these sensors onto a chip and probe a complex mixture for various types of interactions involving protein molecules. PMID:20467571

  8. Dynamic proteomics in modeling of the living cell. Protein-protein interactions.

    PubMed

    Terentiev, A A; Moldogazieva, N T; Shaitan, K V

    2009-12-01

    This review is devoted to describing, summarizing, and analyzing of dynamic proteomics data obtained over the last few years and concerning the role of protein-protein interactions in modeling of the living cell. Principles of modern high-throughput experimental methods for investigation of protein-protein interactions are described. Systems biology approaches based on integrative view on cellular processes are used to analyze organization of protein interaction networks. It is proposed that finding of some proteins in different protein complexes can be explained by their multi-modular and polyfunctional properties; the different protein modules can be located in the nodes of protein interaction networks. Mathematical and computational approaches to modeling of the living cell with emphasis on molecular dynamics simulation are provided. The role of the network analysis in fundamental medicine is also briefly reviewed.

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

    PubMed Central

    2010-01-01

    Background 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. Results 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. Conclusion 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. PMID:20122195

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

    PubMed

    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.

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

    SciTech Connect

    Zhou, C; Zemla, A

    2009-02-25

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

  12. Differential Occurrence of Interactions and Interaction Domains in Proteins Containing Homopolymeric Amino Acid Repeats

    PubMed Central

    Pelassa, Ilaria; Fiumara, Ferdinando

    2015-01-01

    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 domains, in

  13. Host-microbe protein interactions during bacterial infection

    PubMed Central

    Schweppe, Devin K.; Harding, Christopher; Chavez, Juan D.; Wu, Xia; Ramage, Elizabeth; Singh, Pradeep K.; Manoil, Colin; Bruce, James E.

    2015-01-01

    Summary Interspecies protein-protein interactions are essential mediators of infection. While bacterial proteins required for host cell invasion and infection can be identified through bacterial mutant library screens, information about host target proteins and interspecies complex structures has been more difficult to acquire. Using an unbiased chemical cross-linking/mass spectrometry approach, we identified interspecies protein-protein interactions in human lung epithelial cells infected with Acinetobacter baumannii. These efforts resulted in identification of 3076 total cross-linked peptide pairs and 46 interspecies protein-protein interactions. Most notably, the key A. baumannii virulence factor, OmpA, was identified cross-linked to host proteins involved in desmosomes, specialized structures that mediate host cell-to-cell adhesion. Co-immunoprecipitation and transposon mutant experiments were used to verify these interactions and demonstrate relevance for host cell invasion and acute murine lung infection. These results shed new light on A. baumannii-host protein interactions and their structural features and the presented approach is generally applicable to other systems. PMID:26548613

  14. Rosetta stone method for detecting protein function and protein-protein interactions from genome sequences

    DOEpatents

    Eisenberg, David; Marcotte, Edward M.; Pellegrini, Matteo; Thompson, Michael J.; Yeates, Todd O.

    2002-10-15

    A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

  15. Endothelial monocyte activating polypeptide-II modulates endothelial cell responses by degrading hypoxia-inducible factor-1alpha through interaction with PSMA7, a component of the proteasome

    SciTech Connect

    Tandle, Anita T.; Calvani, Maura; Uranchimeg, Badarch; Zahavi, David; Melillo, Giovanni; Libutti, Steven K.

    2009-07-01

    The majority of human tumors are angiogenesis dependent. Understanding the specific mechanisms that contribute to angiogenesis may offer the best approach to develop therapies to inhibit angiogenesis in cancer. Endothelial monocyte activating polypeptide-II (EMAP-II) is an anti-angiogenic cytokine with potent effects on endothelial cells (ECs). It inhibits EC proliferation and cord formation, and it suppresses primary and metastatic tumor growth in-vivo. However, very little is known about the molecular mechanisms behind the anti-angiogenic activity of EMAP-II. In the present study, we explored the molecular mechanism behind the anti-angiogenic activity exerted by this protein on ECs. Our results demonstrate that EMAP-II binds to the cell surface {alpha}5{beta}1 integrin receptor. The cell surface binding of EMAP-II results in its internalization into the cytoplasmic compartment where it interacts with its cytoplasmic partner PSMA7, a component of the proteasome degradation pathway. This interaction increases hypoxia-inducible factor 1-alpha (HIF-1{alpha}) degradation under hypoxic conditions. The degradation results in the inhibition of HIF-1{alpha} mediated transcriptional activity as well as HIF-1{alpha} mediated angiogenic sprouting of ECs. HIF-1{alpha} plays a critical role in angiogenesis by activating a variety of angiogenic growth factors. Our results suggest that one of the major anti-angiogenic functions of EMAP-II is exerted through its inhibition of the HIF-1{alpha} activities.

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

    PubMed

    Brand, Luise H; Henneges, Carsten; Schüssler, Axel; Kolukisaoglu, H Üner; Koch, Grit; Wallmeroth, Niklas; Hecker, Andreas; Thurow, Kerstin; Zell, Andreas; Harter, Klaus; Wanke, Dierk

    2013-01-01

    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 deeper understanding

  17. Screening for Protein-DNA Interactions by Automatable DNA-Protein Interaction ELISA

    PubMed Central

    Schüssler, Axel; Kolukisaoglu, H. Üner; Koch, Grit; Wallmeroth, Niklas; Hecker, Andreas; Thurow, Kerstin; Zell, Andreas; Harter, Klaus; Wanke, Dierk

    2013-01-01

    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 deeper understanding

  18. Integrated protein function prediction by mining function associations, sequences, and protein-protein and gene-gene interaction networks.

    PubMed

    Cao, Renzhi; Cheng, Jianlin

    2016-01-15

    Protein function prediction is an important and challenging problem in bioinformatics and computational biology. Functionally relevant biological information such as protein sequences, gene expression, and protein-protein interactions has been used mostly separately for protein function prediction. One of the major challenges is how to effectively integrate multiple sources of both traditional and new information such as spatial gene-gene interaction networks generated from chromosomal conformation data together to improve protein function prediction. In this work, we developed three different probabilistic scores (MIS, SEQ, and NET score) to combine protein sequence, function associations, and protein-protein interaction and spatial gene-gene interaction networks for protein function prediction. The MIS score is mainly generated from homologous proteins found by PSI-BLAST search, and also association rules between Gene Ontology terms, which are learned by mining the Swiss-Prot database. The SEQ score is generated from protein sequences. The NET score is generated from protein-protein interaction and spatial gene-gene interaction networks. These three scores were combined in a new Statistical Multiple Integrative Scoring System (SMISS) to predict protein function. We tested SMISS on the data set of 2011 Critical Assessment of Function Annotation (CAFA). The method performed substantially better than three base-line methods and an advanced method based on protein profile-sequence comparison, profile-profile comparison, and domain co-occurrence networks according to the maximum F-measure. Copyright © 2015 Elsevier Inc. All rights reserved.

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

    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.

  1. ComPPI: a cellular compartment-specific database for protein-protein interaction network analysis.

    PubMed

    Veres, Daniel V; Gyurkó, Dávid M; Thaler, Benedek; Szalay, Kristóf Z; Fazekas, Dávid; Korcsmáros, Tamás; Csermely, Peter

    2015-01-01

    Here we present ComPPI, a cellular compartment-specific database of proteins and their interactions enabling an extensive, compartmentalized protein-protein interaction network analysis (URL: http://ComPPI.LinkGroup.hu). ComPPI enables the user to filter biologically unlikely interactions, where the two interacting proteins have no common subcellular localizations and to predict novel properties, such as compartment-specific biological functions. ComPPI is an integrated database covering four species (S. cerevisiae, C. elegans, D. melanogaster and H. sapiens). The compilation of nine protein-protein interaction and eight subcellular localization data sets had four curation steps including a manually built, comprehensive hierarchical structure of >1600 subcellular localizations. ComPPI provides confidence scores for protein subcellular localizations and protein-protein interactions. ComPPI has user-friendly search options for individual proteins giving their subcellular localization, their interactions and the likelihood of their interactions considering the subcellular localization of their interacting partners. Download options of search results, whole-proteomes, organelle-specific interactomes and subcellular localization data are available on its website. Due to its novel features, ComPPI is useful for the analysis of experimental results in biochemistry and molecular biology, as well as for proteome-wide studies in bioinformatics and network science helping cellular biology, medicine and drug design.

  2. Determination Quantification of Molecular Interactions in Protein Films: A Review

    PubMed Central

    Hammann, Felicia; Schmid, Markus

    2014-01-01

    Protein based films are nowadays also prepared with the aim of replacing expensive, crude oil-based polymers as environmentally friendly and renewable alternatives. The protein structure determines the ability of protein chains to form intra- and intermolecular bonds, whereas the degree of cross-linking depends on the amino acid composition and molecular weight of the protein, besides the conditions used in film preparation and processing. The functionality varies significantly depending on the type of protein and affects the resulting film quality and properties. This paper reviews the methods used in examination of molecular interactions in protein films and discusses how these intermolecular interactions can be quantified. The qualitative determination methods can be distinguished by structural analysis of solutions (electrophoretic analysis, size exclusion chromatography) and analysis of solid films (spectroscopy techniques, X-ray scattering methods). To quantify molecular interactions involved, two methods were found to be the most suitable: protein film swelling and solubility. The importance of non-covalent and covalent interactions in protein films can be investigated using different solvents. The research was focused on whey protein, whereas soy protein and wheat gluten were included as further examples of proteins. PMID:28788285

  3. Core and periphery structures in protein interaction networks

    PubMed Central

    Luo, Feng; Li, Bo; Wan, Xiu-Feng; Scheuermann, Richard H

    2009-01-01

    Background Characterizing the structural properties of protein interaction networks will help illuminate the organizational and functional relationships among elements in biological systems. Results In this paper, we present a systematic exploration of the core/periphery structures in protein interaction networks (PINs). First, the concepts of cores and peripheries in PINs are defined. Then, computational methods are proposed to identify two types of cores, k-plex cores and star cores, from PINs. Application of these methods to a yeast protein interaction network has identified 110 k-plex cores and 109 star cores. We find that the k-plex cores consist of either "party" proteins, "date" proteins, or both. We also reveal that there are two classes of 1-peripheral proteins: "party" peripheries, which are more likely to be part of protein complex, and "connector" peripheries, which are more likely connected to different proteins or protein complexes. Our results also show that, besides connectivity, other variations in structural properties are related to the variation in biological properties. Furthermore, the negative correlation between evolutionary rate and connectivity are shown toysis. Moreover, the core/periphery structures help to reveal the existence of multiple levels of protein expression dynamics. Conclusion Our results show that both the structure and connectivity can be used to characterize topological properties in protein interaction networks, illuminating the functional organization of cellular systems. PMID:19426456

  4. The nature of protein domain evolution: shaping the interaction network.

    PubMed

    Bagowski, Christoph P; Bruins, Wouter; Te Velthuis, Aartjan J W

    2010-08-01

    The proteomes that make up the collection of proteins in contemporary organisms evolved through recombination and duplication of a limited set of domains. These protein domains are essentially the main components of globular proteins and are the most principal level at which protein function and protein interactions can be understood. An important aspect of domain evolution is their atomic structure and biochemical function, which are both specified by the information in the amino acid sequence. Changes in this information may bring about new folds, functions and protein architectures. With the present and still increasing wealth of sequences and annotation data brought about by genomics, new evolutionary relationships are constantly being revealed, unknown structures modeled and phylogenies inferred. Such investigations not only help predict the function of newly discovered proteins, but also assist in mapping unforeseen pathways of evolution and reveal crucial, co-evolving inter- and intra-molecular interactions. In turn this will help us describe how protein domains shaped cellular interaction networks and the dynamics with which they are regulated in the cell. Additionally, these studies can be used for the design of new and optimized protein domains for therapy. In this review, we aim to describe the basic concepts of protein domain evolution and illustrate recent developments in molecular evolution that have provided valuable new insights in the field of comparative genomics and protein interaction networks.

  5. The Nature of Protein Domain Evolution: Shaping the Interaction Network

    PubMed Central

    Bagowski, Christoph P; Bruins, Wouter; te Velthuis, Aartjan J.W

    2010-01-01

    The proteomes that make up the collection of proteins in contemporary organisms evolved through recombination and duplication of a limited set of domains. These protein domains are essentially the main components of globular proteins and are the most principal level at which protein function and protein interactions can be understood. An important aspect of domain evolution is their atomic structure and biochemical function, which are both specified by the information in the amino acid sequence. Changes in this information may bring about new folds, functions and protein architectures. With the present and still increasing wealth of sequences and annotation data brought about by genomics, new evolutionary relationships are constantly being revealed, unknown structures modeled and phylogenies inferred. Such investigations not only help predict the function of newly discovered proteins, but also assist in mapping unforeseen pathways of evolution and reveal crucial, co-evolving inter- and intra-molecular interactions. In turn this will help us describe how protein domains shaped cellular interaction networks and the dynamics with which they are regulated in the cell. Additionally, these studies can be used for the design of new and optimized protein domains for therapy. In this review, we aim to describe the basic concepts of protein domain evolution and illustrate recent developments in molecular evolution that have provided valuable new insights in the field of comparative genomics and protein interaction networks. PMID:21286315

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

    PubMed

    Li, Yan; Liu, Zhihai; Han, Li; Li, Chengke; Wang, Renxiao

    2013-09-23

    Protein-protein interactions are observed in various biological processes. They are important for understanding the underlying molecular mechanisms and can be potential targets for developing small-molecule regulators of such processes. Previous studies suggest that certain residues on protein-protein binding interfaces are "hot spots". As an extension to this concept, we have developed a residue-based method to identify the characteristic interaction patterns (CIPs) on protein-protein binding interfaces, in which each pattern is a cluster of four contacting residues. Systematic analysis was conducted on a nonredundant set of 1,222 protein-protein binding interfaces selected out of the entire Protein Data Bank. Favored interaction patterns across different protein-protein binding interfaces were retrieved by considering both geometrical and chemical conservations. As demonstrated on two test tests, our method was able to predict hot spot residues on protein-protein binding interfaces with good recall scores and acceptable precision scores. By analyzing the function annotations and the evolutionary tree of the protein-protein complexes in our data set, we also observed that protein-protein interfaces sharing common characteristic interaction patterns are normally associated with identical or similar biological functions.

  7. Investigating protein-protein interactions in live cells using bioluminescence resonance energy transfer.

    PubMed

    Deriziotis, Pelagia; Graham, Sarah A; Estruch, Sara B; Fisher, Simon E

    2014-05-26

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

  8. Trifunctional cross-linker for mapping protein-protein interaction networks and comparing protein conformational states

    PubMed Central

    Tan, Dan; Li, Qiang; Zhang, Mei-Jun; Liu, Chao; Ma, Chengying; Zhang, Pan; Ding, Yue-He; Fan, Sheng-Bo; Tao, Li; Yang, Bing; Li, Xiangke; Ma, Shoucai; Liu, Junjie; Feng, Boya; Liu, Xiaohui; Wang, Hong-Wei; He, Si-Min; Gao, Ning; Ye, Keqiong; Dong, Meng-Qiu; Lei, Xiaoguang

    2016-01-01

    To improve chemical cross-linking of proteins coupled with mass spectrometry (CXMS), we developed a lysine-targeted enrichable cross-linker containing a biotin tag for affinity purification, a chemical cleavage site to separate cross-linked peptides away from biotin after enrichment, and a spacer arm that can be labeled with stable isotopes for quantitation. By locating the flexible proteins on the surface of 70S ribosome, we show that this trifunctional cross-linker is effective at attaining structural information not easily attainable by crystallography and electron microscopy. From a crude Rrp46 immunoprecipitate, it helped identify two direct binding partners of Rrp46 and 15 protein-protein interactions (PPIs) among the co-immunoprecipitated exosome subunits. Applying it to E. coli and C. elegans lysates, we identified 3130 and 893 inter-linked lysine pairs, representing 677 and 121 PPIs. Using a quantitative CXMS workflow we demonstrate that it can reveal changes in the reactivity of lysine residues due to protein-nucleic acid interaction. DOI: http://dx.doi.org/10.7554/eLife.12509.001 PMID:26952210

  9. Evolution of biomolecular networks: lessons from metabolic and protein interactions.

    PubMed

    Yamada, Takuji; Bork, Peer

    2009-11-01

    Despite only becoming popular at the beginning of this decade, biomolecular networks are now frameworks that facilitate many discoveries in molecular biology. The nodes of these networks are usually proteins (specifically enzymes in metabolic networks), whereas the links (or edges) are their interactions with other molecules. These networks are made up of protein-protein interactions or enzyme-enzyme interactions through shared metabolites in the case of metabolic networks. Evolutionary analysis has revealed that changes in the nodes and links in protein-protein interaction and metabolic networks are subject to different selection pressures owing to distinct topological features. However, many evolutionary constraints can be uncovered only if temporal and spatial aspects are included in the network analysis.

  10. Multitask Matrix Completion for Learning Protein Interactions Across Diseases.

    PubMed

    Kshirsagar, Meghana; Murugesan, Keerthiram; Carbonell, Jaime G; Klein-Seetharaman, Judith

    2017-01-27

    Disease-causing pathogens such as viruses introduce their proteins into the host cells in which they interact with the host's proteins, enabling the virus to replicate inside the host. These interactions between pathogen and host proteins are key to understanding infectious diseases. Often multiple diseases involve phylogenetically related or biologically similar pathogens. Here we present a multitask learning method to jointly model interactions between human proteins and three different but related viruses: Hepatitis C, Ebola virus, and Influenza A. Our multitask matrix completion-based model uses a shared low-rank structure in addition to a task-specific sparse structure to incorporate the various interactions. We obtain between 7 and 39 percentage points improvement in predictive performance over prior state-of-the-art models. We show how our model's parameters can be interpreted to reveal both general and specific interaction-relevant characteristics of the viruses. Our code is available online.()

  11. The thermodynamic analysis of weak protein interactions using sedimentation equilibrium

    PubMed Central

    Dolinska, Monika B.; Wingfield, Paul T.

    2014-01-01

    Proteins self-associate to form dimers and tetramers. Purified proteins are used to study the thermodynamics of protein interactions using the analytical ultracentrifuge. In this approach, monomer – dimer equilibrium constants are directly measured at various temperatures. Data analysis is used to derive thermodynamic parameters such as Gibbs free energy, enthalpy and entropy which can predict which major forces are involved in protein association. PMID:25081741

  12. Protein-surface interaction maps for ion-exchange chromatography.

    PubMed

    Freed, Alexander S; Cramer, Steven M

    2011-04-05

    In this paper, protein-surface interaction maps were generated by performing coarse-grained protein-surface calculations. This approach allowed for the rapid determination of the protein-surface interaction energies at a range of orientations and distances. Interaction maps of lysozyme indicated that there was a contiguous series of orientations corresponding to several adjacent preferred binding regions on the protein surface. Examination of these orientations provided insight into the residues involved in surface interactions, which qualitatively agreed with the retention data for single-site mutants. Interaction maps of lysozyme single-site mutants were also generated and provided significant insight into why these variants exhibited significant differences in their chromatographic behavior. This approach was also employed to study the binding behavior of CspB and related mutants. The results indicated that, in addition to describing general trends in the data, these maps provided significant insight into retention data of the single-site mutants. In particular, subtle retention trends observed with the K12 and K13 mutants were well-described using this interaction map approach. Finally, the number of interaction points with energies stronger than -2 kcal/mol was shown to be able to semi-quantitatively predict the behavior of most of the mutants. This rapid approach for calculating protein-surface interaction maps is expected to facilitate future method development for separating closely related protein variants in ion-exchange systems.

  13. Visualization of Host-Polerovirus Interaction Topologies Using Protein Interaction Reporter Technology

    PubMed Central

    DeBlasio, Stacy L.; Chavez, Juan D.; Alexander, Mariko M.; Ramsey, John; Eng, Jimmy K.; Mahoney, Jaclyn; Gray, Stewart M.; Bruce, James E.

    2015-01-01

    ABSTRACT Demonstrating direct interactions between host and virus proteins during infection is a major goal and challenge for the field of virology. Most protein interactions are not binary or easily amenable to structural determination. Using infectious preparations of a polerovirus (Potato leafroll virus [PLRV]) and protein interaction reporter (PIR), a revolutionary technology that couples a mass spectrometric-cleavable chemical cross-linker with high-resolution mass spectrometry, we provide the first report of a host-pathogen protein interaction network that includes data-derived, topological features for every cross-linked site that was identified. We show that PLRV virions have hot spots of protein interaction and multifunctional surface topologies, revealing how these plant viruses maximize their use of binding interfaces. Modeling data, guided by cross-linking constraints, suggest asymmetric packing of the major capsid protein in the virion, which supports previous epitope mapping studies. Protein interaction topologies are conserved with other species in the Luteoviridae and with unrelated viruses in the Herpesviridae and Adenoviridae. Functional analysis of three PLRV-interacting host proteins in planta using a reverse-genetics approach revealed a complex, molecular tug-of-war between host and virus. Structural mimicry and diversifying selection—hallmarks of host-pathogen interactions—were identified within host and viral binding interfaces predicted by our models. These results illuminate the functional diversity of the PLRV-host protein interaction network and demonstrate the usefulness of PIR technology for precision mapping of functional host-pathogen protein interaction topologies. IMPORTANCE The exterior shape of a plant virus and its interacting host and insect vector proteins determine whether a virus will be transmitted by an insect or infect a specific host. Gaining this information is difficult and requires years of experimentation. We used

  14. Efficiency of the immunome protein interaction network increases during evolution.

    PubMed

    Ortutay, Csaba; Vihinen, Mauno

    2008-04-22

    Details of the mechanisms and selection pressures that shape the emergence and development of complex biological systems, such as the human immune system, are poorly understood. A recent definition of a reference set of proteins essential for the human immunome, combined with information about protein interaction networks for these proteins, facilitates evolutionary study of this biological machinery. Here, we present a detailed study of the development of the immunome protein interaction network during eight evolutionary steps from Bilateria ancestors to human. New nodes show preferential attachment to high degree proteins. The efficiency of the immunome protein interaction network increases during the evolutionary steps, whereas the vulnerability of the network decreases. Our results shed light on selective forces acting on the emergence of biological networks. It is likely that the high efficiency and low vulnerability are intrinsic properties of many biological networks, which arise from the effects of evolutionary processes yet to be uncovered.

  15. Multifunctionality of the linker histones: an emerging role for protein-protein interactions.

    PubMed

    McBryant, Steven J; Lu, Xu; Hansen, Jeffrey C

    2010-05-01

    Linker histones, e.g., H1, are best known for their ability to bind to nucleosomes and stabilize both nucleosome structure and condensed higher-order chromatin structures. However, over the years many investigators have reported specific interactions between linker histones and proteins involved in important cellular processes. The purpose of this review is to highlight evidence indicating an important alternative mode of action for H1, namely protein-protein interactions. We first review key aspects of the traditional view of linker histone action, including the importance of the H1 C-terminal domain. We then discuss the current state of knowledge of linker histone interactions with other proteins, and, where possible, highlight the mechanism of linker histone-mediated protein-protein interactions. Taken together, the data suggest a combinatorial role for the linker histones, functioning both as primary chromatin architectural proteins and simultaneously as recruitment hubs for proteins involved in accessing and modifying the chromatin fiber.

  16. Multifunctionality of the linker histones: an emerging role for protein-protein interactions

    PubMed Central

    McBryant, Steven J; Lu, Xu; Hansen, Jeffrey C

    2010-01-01

    Linker histones, e.g., H1, are best known for their ability to bind to nucleosomes and stabilize both nucleosome structure and condensed higher-order chromatin structures. However, over the years many investigators have reported specific interactions between linker histones and proteins involved in important cellular processes. The purpose of this review is to highlight evidence indicating an important alternative mode of action for H1, namely protein-protein interactions. We first review key aspects of the traditional view of linker histone action, including the importance of the H1 C-terminal domain. We then discuss the current state of knowledge of linker histone interactions with other proteins, and, where possible, highlight the mechanism of linker histone-mediated protein-protein interactions. Taken together, the data suggest a combinatorial role for the linker histones, functioning both as primary chromatin architectural proteins and simultaneously as recruitment hubs for proteins involved in accessing and modifying the chromatin fiber. PMID:20309017

  17. Crosslinking Studies of Protein-Protein Interactions in Nonribosomal Peptide Biosynthesis

    PubMed Central

    Hur, Gene H.; Meier, Jordan L.; Baskin, Jeremy; Codelli, Julian A.; Bertozzi, Carolyn R.; Marahiel, Mohamed A.; Burkart, Michael D.

    2009-01-01

    Summary Selective protein-protein interactions between nonribosomal peptide synthetase (NRPS) proteins, governed by communication-mediating (COM) domains, are responsible for proper translocation of biosynthetic intermediates to produce the natural product. In this study, we developed a crosslinking assay, utilizing bioorthogonal probes compatible with carrier protein modification, for probing the protein interactions between COM domains of NRPS enzymes. Employing the Huisgen 1,3-dipolar cycloaddition of azides and alkynes, we examined crosslinking of cognate NRPS modules within the tyrocidine pathway and demonstrated the sensitivity of our panel of crosslinking probes towards the selective protein interactions of compatible COM domains. These studies indicate that copper-free crosslinking substrates uniquely offer a diagnostic probe for protein-protein interactions. Likewise, these crosslinking probes serve as ideal chemical tools for structural studies between NRPS modules where functional assays are lacking. PMID:19345117

  18. Crosslinking studies of protein-protein interactions in nonribosomal peptide biosynthesis.

    PubMed

    Hur, Gene H; Meier, Jordan L; Baskin, Jeremy; Codelli, Julian A; Bertozzi, Carolyn R; Marahiel, Mohamed A; Burkart, Michael D

    2009-04-24

    Selective protein-protein interactions between nonribosomal peptide synthetase (NRPS) proteins, governed by communication-mediating (COM) domains, are responsible for proper translocation of biosynthetic intermediates to produce the natural product. In this study, we developed a crosslinking assay, utilizing bioorthogonal probes compatible with carrier protein modification, for probing the protein interactions between COM domains of NRPS enzymes. Employing the Huisgen 1,3-dipolar cycloaddition of azides and alkynes, we examined crosslinking of cognate NRPS modules within the tyrocidine pathway and demonstrated the sensitivity of our panel of crosslinking probes toward the selective protein interactions of compatible COM domains. These studies indicate that copper-free crosslinking substrates uniquely offer a diagnostic probe for protein-protein interactions. Likewise, these crosslinking probes serve as ideal chemical tools for structural studies between NRPS modules where functional assays are lacking.

  19. Single-Molecule Study of Protein-Protein Interaction Dynamics in a Cell Signaling System

    SciTech Connect

    Tan, Xin; Nalbant, Perihan; Toutchkine, Alexei; Hu, Dehong; Vorpagel, Erich R.; Hahn, Klaus M.; Lu, H PETER.

    2004-01-15

    We report a combined single-molecule fluorescence and molecular dynamics (MD) simulation study of protein-protein interactions in a GTP-binding intracellular signaling protein Cdc42 in complex with a downstream effector protein WASP. A 13- kDa WASP fragment which binds only the activated GTP-loaded Cdc42 was labeled with a novel solvatochromic dye and used to probe hydrophobic interactions significant to Cdc42/WASP recognition. Our single-molecule fluorescence measurements have shown conformational fluctuations of the protein complex and suggested multiple conformational states at a wide range of time scales might be involved in protein interaction dynamics. Single-molecule experiments have revealed the dynamic disorder or protein-protein interactions within the Cdc42/WASP complex, which may be important for regulating downstream signaling events.

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

    PubMed Central

    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

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

    PubMed Central

    La, David; Kihara, Daisuke

    2011-01-01

    Protein-protein binding events mediate many critical biological functions in the cell. Typically, functionally important sites in proteins can be well identified by considering sequence conservation. However, protein-protein interaction sites exhibit higher sequence variation than other functional regions, such as catalytic sites of enzymes. Consequently, the mutational behavior leading to weak sequence conservation poses significant challenges to the protein-protein interaction site prediction. Here, we present a phylogenetic framework to capture critical sequence variations that favor the selection of residues essential for protein-protein binding. Through the comprehensive analysis of diverse protein families, we show that protein binding interfaces exhibit distinct amino acid substitution as compared with other surface residues. Based on this analysis, we have developed a novel method, BindML, which utilizes the substitution models to predict protein-protein binding sites of protein with unknown interacting partners. BindML estimates the likelihood that a phylogenetic tree of a local surface region in a query protein structure follows the substitution patterns of protein binding interface and non-binding surfaces. BindML is shown to perform well compared to alternative methods for protein binding interface prediction. The methodology developed in this study is very versatile in the sense that it can be generally applied for predicting other types of functional sites, such as DNA, RNA, and membrane binding sites in proteins. PMID:21989996

  2. Metabotropic Glutamate Receptors and Interacting Proteins in Epileptogenesis

    PubMed Central

    Qian, Feng; Tang, Feng-Ru

    2016-01-01

    Neurotransmitter and receptor systems are involved in different neurological and neuropsychological disorders such as Parkinson's disease, depression, Alzheimer’s disease and epilepsy. Recent advances in studies of signal transduction pathways or interacting proteins of neurotransmitter receptor systems suggest that different receptor systems may share the common signal transduction pathways or interacting proteins which may be better therapeutic targets for development of drugs to effectively control brain diseases. In this paper, we reviewed metabotropic glutamate receptors (mGluRs) and their related signal transduction pathways or interacting proteins in status epilepticus and temporal lobe epilepsy, and proposed some novel therapeutical drug targets for controlling epilepsy and epileptogenesis. PMID:27030135

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

    PubMed

    Klein, Mark A

    2014-08-14

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

  4. M-Track: detecting short-lived protein-protein interactions in vivo

    PubMed Central

    Zuzuarregui, Aurora; Kupka, Thomas; Bhatt, Bhumika; Dohnal, Ilse; Mudrak, Ingrid; Friedmann, Christina; Schüchner, Stefan; Frohner, Ingrid E.; Ammerer, Gustav; Ogris, Egon

    2012-01-01

    We developed a protein-proximity assay in yeast based on fusing a histone lysine methyltransferase onto a bait and its substrate onto a prey. Upon binding, the prey is stably methylated and detected by methylation-specific antibodies. We applied this approach to detect varying interaction affinities among proteins in a mitogen-activated protein kinase pathway and to detect short-lived interactions between protein phosphatase 2A and its substrates that have so far escaped direct detection. PMID:22581371

  5. Prediction of protein-protein interaction sites by means of ensemble learning and weighted feature descriptor.

    PubMed

    Du, Xiuquan; Sun, Shiwei; Hu, Changlin; Li, Xinrui; Xia, Junfeng

    2016-05-01

    Reliable prediction of protein-protein interaction sites is an important goal in the field of bioinformatics. Many computational methods have been explored for the large-scale prediction of protein-protein interaction sites based on various data types, including protein sequence, structural and genomic data. Although much progress has been achieved in recent years, the problem has not yet been satisfactorily solved. In this work, we presented an efficient approach that uses ensemble learning algorithm with weighted feature descriptor (EL-WFD) to predict protein-protein interaction sites. Moreover, weighted feature descriptor was designed to describe the distance influence of neighboring residues on interaction sites. The results on two dataset (Hetero and Homo), show that the proposed method yields a satisfactory accuracy with 83.8 % recall and 96.3 % precision on the Hetero dataset and 84.2 % recall and 96.3 % precision on the Homo dataset, respectively. In both datasets, our method tend to obtain high Mathews correlation coefficient compared with state-of-the-art technique random forest method. The experimental results show that the EL-WFD method is quite effective in predicting protein-protein interaction sites. The novel weighted feature descriptor was proved to be promising in discovering interaction sites. Overall, the proposed method can be considered as a new powerful tool for predicting protein-protein interaction sites with excellence performance.

  6. History of protein-protein interactions: from egg-white to complex networks.

    PubMed

    Braun, Pascal; Gingras, Anne-Claude

    2012-05-01

    Today, it is widely appreciated that protein-protein interactions play a fundamental role in biological processes. This was not always the case. The study of protein interactions started slowly and evolved considerably, together with conceptual and technological progress in different areas of research through the late 19th and the 20th centuries. In this review, we present some of the key experiments that have introduced major conceptual advances in biochemistry and molecular biology, and review technological breakthroughs that have paved the way for today's systems-wide approaches to protein-protein interaction analysis. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Studying Protein-Protein Interactions In Planta Using Advanced Fluorescence Microscopy.

    PubMed

    Somssich, Marc; Simon, Rüdiger

    2017-01-01

    The formation of protein complexes through direct protein-protein interaction is essential for virtually every biological process, and accordingly the ability to determine the interaction properties of specific proteins is important to understand these processes. Förster resonance energy transfer (FRET) measurements are state-of-the-art confocal fluorescence microscopy- and imaging-based techniques that allow the analysis of protein interactions in vivo and in planta, in specific compartments of single cells or tissues. Here we provide a step-by-step guide to perform FRET measurements by acceptor photobleaching (APB) and fluorescence lifetime imaging microscopy (FLIM) in the plant expression system Nicotiana benthamiana.

  8. Interaction networks: from protein functions to drug discovery. A review.

    PubMed

    Chautard, E; Thierry-Mieg, N; Ricard-Blum, S

    2009-06-01

    Most genes, proteins and other components carry out their functions within a complex network of interactions and a single molecule can affect a wide range of other cell components. A global, integrative, approach has been developed for several years, including protein-protein interaction networks (interactomes). In this review, we describe the high-throughput methods used to identify new interactions and to build large interaction datasets. The minimum information required for reporting a molecular interaction experiment (MIMIx) has been defined as a standard for storing data in publicly available interaction databases. Several examples of interaction networks from molecular machines (proteasome) or organelles (phagosome, mitochondrion) to whole organisms (viruses, bacteria, yeast, fly, and worm) are given and attempts to cover the entire human interaction network are discussed. The methods used to perform the topological analysis of interaction networks and to extract biological information from them are presented. These investigations have provided clues on protein functions, signalling and metabolic pathways, and physiological processes, unraveled the molecular basis of some diseases (cancer, infectious diseases), and will be very useful to identify new therapeutic targets and for drug discovery. A major challenge is now to integrate data from different sources (interactome, transcriptome, phenome, localization) to switch from static to dynamic interaction networks. The merging of a viral interactome and the human interactome has been used to simulate viral infection, paving the way for future studies aiming at providing molecular basis of human diseases.

  9. Mutual diffusion of interacting membrane proteins.

    PubMed Central

    Abney, J R; Scalettar, B A; Owicki, J C

    1989-01-01

    The generalized Stokes-Einstein equation is used, together with the two-dimensional pressure equation, to analyze mutual diffusion in concentrated membrane systems. These equations can be used to investigate the role that both direct and hydrodynamic interactions play in determining diffusive behavior. Here only direct interactions are explicitly incorporated into the theory at high densities; however, both direct and hydrodynamic interactions are analyzed for some dilute solutions. We look at diffusion in the presence of weak attractions, soft repulsions, and hard-core repulsions. It is found that, at low densities, attractions retard mutual diffusion while repulsions enhance it. Mechanistically, attractions tend to tether particles together and oppose the dissipation of gradients or fluctuations in concentration, while repulsions provide a driving force that pushes particles apart. At higher concentrations, changes in the structure of the fluid enhance mutual diffusion even in the presence of attractions. It is shown that the theoretical description of postelectrophoresis relaxation and fluorescence correlation spectroscopy experiments must be modified if interacting systems are studied. The effects of interactions on mutual diffusion coefficients have probably already been seen in postelectrophoresis relaxation experiments. PMID:2775829

  10. A credit-card library approach for disrupting protein-protein interactions.

    PubMed

    Xu, Yang; Shi, Jin; Yamamoto, Noboru; Moss, Jason A; Vogt, Peter K; Janda, Kim D

    2006-04-15

    Protein-protein interfaces are prominent in many therapeutically important targets. Using small organic molecules to disrupt protein-protein interactions is a current challenge in chemical biology. An important example of protein-protein interactions is provided by the Myc protein, which is frequently deregulated in human cancers. Myc belongs to the family of basic helix-loop-helix leucine zipper (bHLH-ZIP) transcription factors. It is biologically active only as heterodimer with the bHLH-ZIP protein Max. Herein, we report a new strategy for the disruption of protein-protein interactions that has been corroborated through the design and synthesis of a small parallel library composed of 'credit-card' compounds. These compounds are derived from a planar, aromatic scaffold and functionalized with four points of diversity. From a 285 membered library, several hits were obtained that disrupted the c-Myc-Max interaction and cellular functions of c-Myc. The IC50 values determined for this small focused library for the disruption of Myc-Max dimerization are quite potent, especially since small molecule antagonists of protein-protein interactions are notoriously difficult to find. Furthermore, several of the compounds were active at the cellular level as shown by their biological effects on Myc action in chicken embryo fibroblast assays. In light of our findings, this approach is considered a valuable addition to the armamentarium of new molecules being developed to interact with protein-protein interfaces. Finally, this strategy for disrupting protein-protein interactions should prove applicable to other families of proteins.

  11. Integrating protein-protein interactions and text mining for protein function prediction

    PubMed Central

    Jaeger, Samira; Gaudan, Sylvain; Leser, Ulf; Rebholz-Schuhmann, Dietrich

    2008-01-01

    Background Functional annotation of proteins remains a challenging task. Currently the scientific literature serves as the main source for yet uncurated functional annotations, but curation work is slow and expensive. Automatic techniques that support this work are still lacking reliability. We developed a method to identify conserved protein interaction graphs and to predict missing protein functions from orthologs in these graphs. To enhance the precision of the results, we furthermore implemented a procedure that validates all predictions based on findings reported in the literature. Results Using this procedure, more than 80% of the GO annotations for proteins with highly conserved orthologs that are available in UniProtKb/Swiss-Prot could be verified automatically. For a subset of proteins we predicted new GO annotations that were not available in UniProtKb/Swiss-Prot. All predictions were correct (100% precision) according to the verifications from a trained curator. Conclusion Our method of integrating CCSs and literature mining is thus a highly reliable approach to predict GO annotations for weakly characterized proteins with orthologs. PMID:18673526

  12. Identification of brain-specific angiogenesis inhibitor 2 as an interaction partner of glutaminase interacting protein

    SciTech Connect

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

    2011-08-12

    Highlights: {yields} Brain-specific angiogenesis inhibitor 2 (BAI2) is a new partner protein for GIP. {yields} BAI2 interaction with GIP was revealed by yeast two-hybrid assay. {yields} Binding of BAI2 to GIP was characterized by NMR, CD and fluorescence. {yields} BAI2 and GIP binding was mediated through the C-terminus of BAI2. -- Abstract: 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 signaling, protein scaffolding and modulation of tumor growth and interacts with a number of physiological partner proteins, including Glutaminase L, {beta}-Catenin, FAS, HTLV-1 Tax, HPV16 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.

  13. Circumventing the problems caused by protein diversity in microarrays: implications for protein interaction networks.

    PubMed

    Gordus, Andrew; MacBeath, Gavin

    2006-10-25

    Protein microarrays provide a well-controlled, high-throughput way to uncover protein-protein interactions. One problem with this and other standardized assays, however, is that proteins vary considerably with respect to their physical properties. If a simple threshold-based approach is used to define protein-protein interactions, the resulting binary networks can be strongly biased. Here, we investigate the extent to which even closely related protein interaction domains vary when printed as microarrays. We find that, when a collection of well behaved, monomeric Src homology 2 (SH2) domains are printed at the same concentration, they vary by up to 50-fold with respect to the resulting surface density of active protein. When a threshold-based binding assay is performed on these domains using fluorescently labeled phosphopeptides, a misleading picture of the underlying biophysical interactions emerges. This problem can be circumvented, however, by obtaining saturation binding curves for each protein-peptide interaction. Importantly, the equilibrium dissociation constants obtained from these curves are independent of the surface density of active protein. We submit that an increased emphasis should be placed on obtaining quantitative information from protein microarrays and that this should serve as a more general goal in all efforts to define large-scale protein interaction networks.

  14. Prediction of virus-host protein-protein interactions mediated by short linear motifs.

    PubMed

    Becerra, Andrés; Bucheli, Victor A; Moreno, Pedro A

    2017-03-09

    Short linear motifs in host organisms proteins can be mimicked by viruses to create protein-protein interactions that disable or control metabolic pathways. Given that viral linear motif instances of host motif regular expressions can be found by chance, it is necessary to develop filtering methods of functional linear motifs. We conduct a systematic comparison of linear motifs filtering methods to develop a computational approach for predicting motif-mediated protein-protein interactions between human and the human immunodeficiency virus 1 (HIV-1). We implemented three filtering methods to obtain linear motif sets: 1) conserved in viral proteins (C), 2) located in disordered regions (D) and 3) rare or scarce in a set of randomized viral sequences (R). The sets C,D,R are united and intersected. The resulting sets are compared by the number of protein-protein interactions correctly inferred with them - with experimental validation. The comparison is done with HIV-1 sequences and interactions from the National Institute of Allergy and Infectious Diseases (NIAID). The number of correctly inferred interactions allows to rank the interactions by the sets used to deduce them: D∪R and C. The ordering of the sets is descending on the probability of capturing functional interactions. With respect to HIV-1, the sets C∪R, D∪R, C∪D∪R infer all known interactions between HIV1 and human proteins mediated by linear motifs. We found that the majority of conserved linear motifs in the virus are located in disordered regions. We have developed a method for predicting protein-protein interactions mediated by linear motifs between HIV-1 and human proteins. The method only use protein sequences as inputs. We can extend the software developed to any other eukaryotic virus and host in order to find and rank candidate interactions. In future works we will use it to explore possible viral attack mechanisms based on linear motif mimicry.

  15. ORF7-encoded accessory protein 7a of feline infectious peritonitis virus as a counteragent against IFN-α-induced antiviral response.

    PubMed

    Dedeurwaerder, Annelike; Olyslaegers, Dominique A J; Desmarets, Lowiese M B; Roukaerts, Inge D M; Theuns, Sebastiaan; Nauwynck, Hans J

    2014-02-01

    The type I IFN-mediated immune response is the first line of antiviral defence. Coronaviruses, like many other viruses, have evolved mechanisms to evade this innate response, ensuring their survival. Several coronavirus accessory genes play a central role in these pathways, but for feline coronaviruses this has never to our knowledge been studied. As it has been demonstrated previously that ORF7 is essential for efficient replication in vitro and virulence in vivo of feline infectious peritonitis virus (FIPV), the role of this ORF in the evasion of the IFN-α antiviral response was investigated. Deletion of ORF7 from FIPV strain 79-1146 (FIPV-Δ7) rendered the virus more susceptible to IFN-α treatment. Given that ORF7 encodes two proteins, 7a and 7b, it was further explored which of these proteins is active in this mechanism. Providing 7a protein in trans rescued the mutant FIPV-Δ7 from IFN sensitivity, which was not achieved by addition of 7b protein. Nevertheless, addition of protein 7a to FIPV-Δ3Δ7, a FIPV mutant deleted in both ORF3 and ORF7, could no longer increase the replication capacity of this mutant in the presence of IFN. These results indicate that FIPV 7a protein is a type I IFN antagonist and protects the virus from the antiviral state induced by IFN, but it needs the presence of ORF3-encoded proteins to exert its antagonistic function.

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

    PubMed

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

    2014-11-20

    One of the central interests of Virology is the identification of host factors that contribute to virus infection. Despite tremendous efforts, the list of factors identified remains limited. With omics techniques, the focus has changed from identifying and thoroughly characterizing individual host factors to the simultaneous analysis of thousands of interactions, framing them on the context of protein-protein interaction networks and of transcriptional regulatory networks. This new perspective is allowing the identification of direct and indirect viral targets. Such information is available for several members of the Potyviridae family, one of the largest and more important families of plant viruses. After collecting information on virus protein-protein interactions from different potyviruses, we have processed it and used it for inferring a protein-protein interaction network. All proteins are connected into a single network component. Some proteins show a high degree and are highly connected while others are much less connected, with the network showing a significant degree of dissortativeness. We have attempted to integrate this virus protein-protein interaction network into the largest protein-protein interaction network of Arabidopsis thaliana, a susceptible laboratory host. To make the interpretation of data and results easier, we have developed a new approach for visualizing and analyzing the dynamic spread on the host network of the local perturbations induced by viral proteins. We found that local perturbations can reach the entire host protein-protein interaction network, although the efficiency of this spread depends on the particular viral proteins. By comparing the spread dynamics among viral proteins, we found that some proteins spread their effects fast and efficiently by attacking hubs in the host network while other proteins exert more local effects. Our findings confirm that potyvirus protein-protein interaction networks are highly connected, with

  17. Evolutionary analysis and interaction prediction for protein-protein interaction network in geometric space.

    PubMed

    Huang, Lei; Liao, Li; Wu, Cathy H

    2017-01-01

    Prediction of protein-protein interaction (PPI) remains a central task in systems biology. With more PPIs identified, forming PPI networks, it has become feasible and also imperative to study PPIs at the network level, such as evolutionary analysis of the networks, for better understanding of PPI networks and for more accurate prediction of pairwise PPIs by leveraging the information gained at the network level. In this work we developed a novel method that enables us to incorporate evolutionary information into geometric space to improve PPI prediction, which in turn can be used to select and evaluate various evolutionary models. The method is tested with cross-validation using human PPI network and yeast PPI network data. The results show that the accuracy of PPI prediction measured by ROC score is increased by up to 14.6%, as compared to a baseline without using evolutionary information. The results also indicate that our modified evolutionary model DANEOsf-combining a gene duplication/neofunctionalization model and scale-free model-has a better fitness and prediction efficacy for these two PPI networks. The improved PPI prediction performance may suggest that our DANEOsf evolutionary model can uncover the underlying evolutionary mechanism for these two PPI networks better than other tested models. Consequently, of particular importance is that our method offers an effective way to select evolutionary models that best capture the underlying evolutionary mechanisms, evaluating the fitness of evolutionary models from the perspective of PPI prediction on real PPI networks.

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

    PubMed

    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.

  19. Protein Interactions during the Flavivirus and Hepacivirus Life Cycle.

    PubMed

    Gerold, Gisa; Bruening, Janina; Weigel, Bettina; Pietschmann, Thomas

    2017-04-01

    Protein-protein interactions govern biological functions in cells, in the extracellular milieu, and at the border between cells and extracellular space. Viruses are small intracellular parasites and thus rely on protein interactions to produce progeny inside host cells and to spread from cell to cell. Usage of host proteins by viruses can have severe consequences e.g. apoptosis, metabolic disequilibria, or altered cell proliferation and mobility. Understanding protein interactions during virus infection can thus educate us on viral infection and pathogenesis mechanisms. Moreover, it has led to important clinical translations, including the development of new therapeutic and vaccination strategies. Here, we will discuss protein interactions of members of the Flaviviridae family, which are small enveloped RNA viruses. Dengue virus, Zika virus and hepatitis C virus belong to the most prominent human pathogenic Flaviviridae With a genome of roughly ten kilobases encoding only ten viral proteins, Flaviviridae display intricate mechanisms to engage the host cell machinery for their purpose. In this review, we will highlight how dengue virus, hepatitis C virus, Japanese encephalitis virus, tick-borne encephalitis virus, West Nile virus, yellow fever virus, and Zika virus proteins engage host proteins and how this knowledge helps elucidate Flaviviridae infection. We will specifically address the protein composition of the virus particle as well as the protein interactions during virus entry, replication, particle assembly, and release from the host cell. Finally, we will give a perspective on future challenges in Flaviviridae interaction proteomics and why we believe these challenges should be met. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  20. From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

    PubMed Central

    Gao, Mu; Skolnick, Jeffrey

    2009-01-01

    DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Cα deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein. PMID:19343221

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

    PubMed

    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

  2. Proteins differentially interact with grapefruit furanocoumarins

    USDA-ARS?s Scientific Manuscript database

    Grapefruit juice (GFJ) interferes with the cytochrome P450 3A4 activity responsible for metabolizing certain medications. This interference is referred to as the "grapefruit-drug interaction". Grapefruit furanocoumarins (FCs), such as 6', 7'-dihydroxybergamottin (DHB) and bergamottin (BM), have been...

  3. Protein function prediction using guilty by association from interaction networks.

    PubMed

    Piovesan, Damiano; Giollo, Manuel; Ferrari, Carlo; Tosatto, Silvio C E

    2015-12-01

    Protein function prediction from sequence using the Gene Ontology (GO) classification is useful in many biological problems. It has recently attracted increasing interest, thanks in part to the Critical Assessment of Function Annotation (CAFA) challenge. In this paper, we introduce Guilty by Association on STRING (GAS), a tool to predict protein function exploiting protein-protein interaction networks without sequence similarity. The assumption is that whenever a protein interacts with other proteins, it is part of the same biological process and located in the same cellular compartment. GAS retrieves interaction partners of a query protein from the STRING database and measures enrichment of the associated functional annotations to generate a sorted list of putative functions. A performance evaluation based on CAFA metrics and a fair comparison with optimized BLAST similarity searches is provided. The consensus of GAS and BLAST is shown to improve overall performance. The PPI approach is shown to outperform similarity searches for biological process and cellular compartment GO predictions. Moreover, an analysis of the best practices to exploit protein-protein interaction networks is also provided.

  4. Multiplex single-molecule interaction profiling of DNA barcoded proteins

    PubMed Central

    Gu, Liangcai; Li, Chao; Aach, John; Hill, David E.; Vidal, Marc; Church, George M.

    2014-01-01

    In contrast with advances in massively parallel DNA sequencing1, high-throughput protein analyses2-4 are often limited by ensemble measurements, individual analyte purification and hence compromised quality and cost-effectiveness. Single-molecule (SM) protein detection achieved using optical methods5 is limited by the number of spectrally nonoverlapping chromophores. Here, we introduce a single molecular interaction-sequencing (SMI-Seq) technology for parallel protein interaction profiling leveraging SM advantages. DNA barcodes are attached to proteins collectively via ribosome display6 or individually via enzymatic conjugation. Barcoded proteins are assayed en masse in aqueous solution and subsequently immobilized in a polyacrylamide (PAA) thin film to construct a random SM array, where barcoding DNAs are amplified into in situ polymerase colonies (polonies)7 and analyzed by DNA sequencing. This method allows precise quantification of various proteins with a theoretical maximum array density of over one million polonies per square millimeter. Furthermore, protein interactions can be measured based on the statistics of colocalized polonies arising from barcoding DNAs of interacting proteins. Two demanding applications, G-protein coupled receptor (GPCR) and antibody binding profiling, were demonstrated. SMI-Seq enables “library vs. library” screening in a one-pot assay, simultaneously interrogating molecular binding affinity and specificity. PMID:25252978

  5. TIMBAL v2: update of a database holding small molecules modulating protein-protein interactions.

    PubMed

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

    2013-01-01

    TIMBAL is a database holding molecules of molecular weight <1200 Daltons that modulate protein-protein interactions. Since its first release, the database has been extended to cover 50 known protein-protein interactions drug targets, including protein complexes that can be stabilized by small molecules with therapeutic effect. The resource contains 14 890 data points for 6896 distinct small molecules. UniProt codes and Protein Data Bank entries are also included. Database URL: http://www-cryst.bioc.cam.ac.uk/timbal

  6. Intermolecular interactions between natural polysaccharides and silk fibroin protein.

    PubMed

    Shang, Songmin; Zhu, Lei; Fan, Jintu

    2013-04-02

    Fabricating novel functional and structural materials from natural renewable and degradable materials has attracted much attention. Natural polysaccharides and proteins are the right natural candidates due to their unique structures and properties. The polysaccharide-protein composites or blends were widely investigated, however, there are few systematical studies on the interactions between natural polysaccharides and silk fibroin protein at the molecular level. Among various interactions, hydrogen bonding, electrostatic interactions and covalent bonding play important roles in the structure and properties of the corresponding materials. Therefore, the focus is placed on the three interactions types in this review. A future challenge is to create polysaccharide and protein composites or blends with tailored structure and properties for the wide applications. Copyright © 2012 Elsevier Ltd. All rights reserved.

  7. Detecting Protein-Protein Interactions in Vesicular Stomatitis Virus Using a Cytoplasmic Yeast Two Hybrid System

    PubMed Central

    Moerdyk-Schauwecker, Megan; DeStephanis, Darla; Hastie, Eric; Grdzelishvili, Valery Z.

    2011-01-01

    Summary Protein-protein interactions play an important role in many virus-encoded functions and in virus-host interactions. While a “classical” yeast two-hybrid system (Y2H) is one of the most common techniques to detect such interactions, it has a number of limitations, including a requirement for the proteins of interest to be relocated to the nucleus. Modified Y2H, such as the Sos recruitment system (SRS), which detect interactions occurring in the cytoplasm rather than the nucleus, allow proteins from viruses replicating in the cytoplasm to be tested in a more natural context. In this study, a SRS was used to detect interactions involving proteins from vesicular stomatitis virus (VSV), a prototypic non-segmented negative strand RNA (NNS) virus. All five full-length VSV proteins, as well as several truncated proteins, were screened against each other. Using the SRS, most interactions demonstrated previously involving VSV phosphoprotein, nucleocapsid (N) and large polymerase proteins were confirmed independently, while difficulties were encountered using the membrane associated matrix and glycoproteins. A human cDNA library was also screened against VSV N protein and one cellular protein, SFRS18, was identified which interacted with N in this context. The system presented can be redesigned easily for studies in other less tractable NNS viruses. PMID:21320532

  8. A rapid method for detecting protein-nucleic acid interactions by protein induced fluorescence enhancement

    PubMed Central

    Valuchova, Sona; Fulnecek, Jaroslav; Petrov, Alexander P.; Tripsianes, Konstantinos; Riha, Karel

    2016-01-01

    Many fundamental biological processes depend on intricate networks of interactions between proteins and nucleic acids and a quantitative description of these interactions is important for understanding cellular mechanisms governing DNA replication, transcription, or translation. Here we present a versatile method for rapid and quantitative assessment of protein/nucleic acid (NA) interactions. This method is based on protein induced fluorescence enhancement (PIFE), a phenomenon whereby protein binding increases the fluorescence of Cy3-like dyes. PIFE has mainly been used in single molecule studies to detect protein association with DNA or RNA. Here we applied PIFE for steady state quantification of protein/NA interactions by using microwell plate fluorescence readers (mwPIFE). We demonstrate the general applicability of mwPIFE for examining various aspects of protein/DNA interactions with examples from the restriction enzyme BamHI, and the DNA repair complexes Ku and XPF/ERCC1. These include determination of sequence and structure binding specificities, dissociation constants, detection of weak interactions, and the ability of a protein to translocate along DNA. mwPIFE represents an easy and high throughput method that does not require protein labeling and can be applied to a wide range of applications involving protein/NA interactions. PMID:28008962

  9. A Yeast Two-Hybrid approach for probing protein-protein interactions at the centrosome

    PubMed Central

    Galletta, Brian J.; Rusan, Nasser M.

    2016-01-01

    As a large, non-membrane bound organelle, the centrosome must rely heavily on protein-protein interactions to assemble itself in the cytoplasm and perform its functions as a microtubule-organizing center. Therefore, to understand how this organelle is built and functions, one must understand the protein-protein interactions made by each centrosome protein. Unfortunately, the highly interconnected nature of the centrosome, combined with its predicted unstructured, coil-rich proteins, has made the use of many standard approaches to studying protein-protein interactions very challenging. The yeast-two hybrid (Y2H) system is well suited for studying the centrosome and is an important complement to other biochemical approaches. In this chapter we describe how to carry out a directed Y2H screen to identify the direct interactions between a given centrosome protein and a library of others. Specifically, we detail using a bioinformatics based approach (structure prediction programs) to subdivide proteins and screen for interactions using an array-based Y2H approach. We also describe how to use the interaction information garnered from this screen to generate mutations to disrupt specific interactions using mutagenic-PCR and a “reverse” Y2H screen. Finally, we discuss how information from such a screen can be integrated into existing models of centrosome assembly and how it can initiate and guide extensive in vitro and in vivo experimentation to test these models. PMID:26175443

  10. Finding the evidence for protein-protein interactions from PubMed abstracts.

    PubMed

    Jang, Hyunchul; Lim, Jaesoo; Lim, Joon-Ho; Park, Soo-Jun; Lee, Kyu-Chul; Park, Seon-Hee

    2006-07-15

    Protein-protein interactions play critical roles in biological processes, and many biologists try to find or to predict crucial information concerning these interactions. Before verifying interactions in biological laboratory work, validating them from previous research is necessary. Although many efforts have been made to create databases that store verified information in a structured form, much interaction information still remains as unstructured text. As the amount of new publications has increased rapidly, a large amount of research has sought to extract interactions from the text automatically. However, there remain various difficulties associated with the process of applying automatically generated results into manually annotated databases. For interactions that are not found in manually stored databases, researchers attempt to search for abstracts or full papers. As a result of a search for two proteins, PubMed frequently returns hundreds of abstracts. In this paper, a method is introduced that validates protein-protein interactions from PubMed abstracts. A query is generated from two given proteins automatically and abstracts are then collected from PubMed. Following this, target proteins and their synonyms are recognized and their interaction information is extracted from the collection. It was found that 67.37% of the interactions from DIP-PPI corpus were found from the PubMed abstracts and 87.37% of interactions were found from the given full texts. Contact authors.

  11. Neurodegenerative diseases: quantitative predictions of protein-RNA interactions.

    PubMed

    Cirillo, Davide; Agostini, Federico; Klus, Petr; Marchese, Domenica; Rodriguez, Silvia; Bolognesi, Benedetta; Tartaglia, Gian Gaetano

    2013-02-01

    Increasing evidence indicates that RNA plays an active role in a number of neurodegenerative diseases. We recently introduced a theoretical framework, catRAPID, to predict the binding ability of protein and RNA molecules. Here, we use catRAPID to investigate ribonucleoprotein interactions linked to inherited intellectual disability, amyotrophic lateral sclerosis, Creutzfeuld-Jakob, Alzheimer's, and Parkinson's diseases. We specifically focus on (1) RNA interactions with fragile X mental retardation protein FMRP; (2) protein sequestration caused by CGG repeats; (3) noncoding transcripts regulated by TAR DNA-binding protein 43 TDP-43; (4) autogenous regulation of TDP-43 and FMRP; (5) iron-mediated expression of amyloid precursor protein APP and α-synuclein; (6) interactions between prions and RNA aptamers. Our results are in striking agreement with experimental evidence and provide new insights in processes associated with neuronal function and misfunction.

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

    PubMed Central

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

    2006-01-01

    The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction. Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors. PMID:23165043

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

    DOE PAGES

    Venkatraman, S.; Doktycz, M. J.; Qi, H.; ...

    2006-01-01

    The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction.more » Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors.« less

  14. Protein surface-distribution and protein-protein interactions in the binding of peripheral proteins to charged lipid membranes.

    PubMed Central

    Heimburg, T; Marsh, D

    1995-01-01

    The binding of native cytochrome c to negatively charged lipid dispersions of dioleoyl phosphatidylglycerol has been studied over a wide range of ionic strengths. Not only is the strength of protein binding found to decrease rapidly with increasing ionic strength, but also the binding curves reach an apparent saturation level that decreases rapidly with increasing ionic strength. Analysis of the binding isotherms with a general statistical thermodynamic model that takes into account not only the free energy of the electrostatic double layer, but also the free energy of the surface distribution of the protein, demonstrates that the apparent saturation effects could arise from a competition between the out-of-plane binding reaction and the lateral in-plane interactions between proteins at the surface. It is found that association with nonlocalized sites results in binding isotherms that display the apparent saturation effect to a much more pronounced extent than does the Langmuir adsorption isotherm for binding to localized sites. With the model for nonlocalized sites, the binding isotherms of native cytochrome c can be described adequately by taking into account only the entropy of the surface distribution of the protein, without appreciable enthalpic interactions between the bound proteins. The binding of cytochrome c to dioleoyl phosphatidylglycerol dispersions at a temperature at which the bound protein is denatured on the lipid surface, but is nondenatured when free in solution, has also been studied. The binding curves for the surface-denatured protein differ from those for the native protein in that the apparent saturation at high ionic strength is less pronounced. This indicates the tendency of the denatured protein to aggregate on the lipid surface, and can be described by the binding isotherms for nonlocalized sites only if attractive interactions between the surface-bound proteins are included in addition to the distributional entropic terms. Additionally

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

    NASA Astrophysics Data System (ADS)

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

    2004-04-01

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

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

    PubMed

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

    2013-01-01

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

  17. Direct AKAP-mediated protein-protein interactions as potential drug targets.

    PubMed

    Hundsrucker, C; Klussmann, E

    2008-01-01

    A-kinase-anchoring proteins (AKAPs) are a diverse family of about 50 scaffolding proteins. They are defined by the presence of a structurally conserved protein kinase A (PKA)-binding domain. AKAPs tether PKA and other signalling proteins such as further protein kinases, protein phosphatases and phosphodiesterases by direct protein-protein interactions to cellular compartments. Thus, AKAPs form the basis of signalling modules that integrate cellular signalling processes and limit these to defined sites. Disruption of AKAP functions by gene targeting, knockdown approaches and, in particular, pharmacological disruption of defined AKAP-dependent protein-protein interactions has revealed key roles of AKAPs in numerous processes, including the regulation of cardiac myocyte contractility and vasopressin-mediated water reabsorption in the kidney. Dysregulation of such processes causes diseases, including cardiovascular and renal disorders. In this review, we discuss AKAP functions elucidated by gene targeting and knockdown approaches, but mainly focus on studies utilizing peptides for disruption of direct AKAP-mediated protein-protein interactions. The latter studies point to direct AKAP-mediated protein-protein interactions as targets for novel drugs.

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

    SciTech Connect

    Chowdhury, Saiful M.; Shi, Liang; Yoon, Hyunjin; Ansong, Charles; Rommereim, Leah M.; Norbeck, Angela D.; Auberry, Kenneth J.; Moore, R. J.; Adkins, Joshua N.; Heffron, Fred; Smith, Richard D.

    2009-02-10

    We successfully modified an existing method to investigate protein-protein interactions in the pathogenic bacterium Salmonella typhimurium (STM). This method includes i) addition of a histidine-biotin-histidine tag to the bait proteins via recombinant DNA techniques; ii) in vivo cross-linking with formaldehyde; iii) tandem affinity purification of bait proteins under fully denaturing conditions; and iv) identification of the proteins cross-linked to the bait proteins by liquid-chromatography in conjunction with tandem mass-spectrometry. In vivo cross-linking stabilized protein interactions permitted the subsequent two-step purification step conducted under denaturing conditions. The two-step purification greatly reduced nonspecific binding of non-cross-linked proteins to bait proteins. Two different negative controls were employed to reduce false-positive identification. In an initial demonstration of this approach, we tagged three selected STM proteins- HimD, PduB and PhoP- with known binding partners that ranged from stable (e.g., HimD) to transient (i.e., PhoP). Distinct sets of interacting proteins were identified with each bait protein, including the known binding partners such as HimA for HimD, as well as anticipated and unexpected binding partners. Our results suggest that novel protein-protein interactions may be critical to pathogenesis by Salmonella typhimurium. .

  19. Biophysics of protein-DNA interactions and chromosome organization

    PubMed Central

    Marko, John F.

    2014-01-01

    The function of DNA in cells depends on its interactions with protein molecules, which recognize and act on base sequence patterns along the double helix. These notes aim to introduce basic polymer physics of DNA molecules, biophysics of protein-DNA interactions and their study in single-DNA experiments, and some aspects of large-scale chromosome structure. Mechanisms for control of chromosome topology will also be discussed. PMID:25419039

  20. Interaction of decavanadate polyanions with proteins.

    PubMed

    Ashraf, S M; Rajesh; Kaleem, S

    1995-09-01

    The binding of polymeric decavanadate anion [V10O28]6- with bovine serum albumin and gelatin was studied at pH 4.0 and 3.0, the region of thermodynamic stability of oligomeric vanadate anion. The binding of decavanadate anion at pH 4.0 with bovine serum albumin (BSA) and gelatin was found to be 9 and 32 gmol of decavanadate per gram mole of the proteins. The binding at pH 3.0 was found to be 12 and 38 gmol, respectively. Freshly formed BSA decavanadate precipitate was particulate in nature while that of gelatin-decavanadate made a gummy mass. This indicates a different mode of binding of decavanadate anions with globular and fibrillar proteins. Infrared spectra of the adducts endorses electrostatic binding between proteins and decavanadate. Scanning electron microscopy micrographs reveal extended crosslinked binding between decavanadate and gelatin and aggregation of the uncharged BSA-decavanadate molecules to make a granular adduct. The mode of binding was also correlated with the structure of decavanadate anions, BSA, and gelatin.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed Central

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

    2016-01-01

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

  3. Single-Molecule Study of Protein-Protein Interaction Dynamics in a Cell Signaling System

    SciTech Connect

    Tan, Xin; Nalbant, Perihan; Toutchkine, Alexei; Hu, Dehong; Vorpagel, Erich R.; Hahn, Klaus M.; Lu, H. Peter

    2004-01-01

    We report a study on protein-protein noncovalent interactions in an intracellular signaling protein complex, using single-molecule spectroscopy and molecular dynamics (MD) simulations. A Wiskott-Aldrich Syndrome Protein (WASP) fragment that binds only the activated intracellular signaling protein Cdc42 was labeled with a novel solvatochromic dye and used to probe hydrophobic interactions significant to Cdc42/WASP recognition. The study shows static and dynamic inhomogeneous conformational fluctuations of the protein complex that involve bound and loosely bound states. A two-coupled, two-state Markovian kinetic model is proposed for the conformational dynamics. Finally, the MD simulations explore the origin of these conformational states and associated conformational fluctuations in this protein-protein interaction system.

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

    PubMed

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

    2013-01-01

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

  5. Assessing Energetic Contributions to Binding from a Disordered Region in a Protein-Protein Interaction

    SciTech Connect

    S Cho; C Swaminathan; D Bonsor; M Kerzic; R Guan; J Yang; C Kieke; P Anderson; D Kranz; et al.

    2011-12-31

    Many functional proteins are at least partially disordered prior to binding. Although the structural transitions upon binding of disordered protein regions can influence the affinity and specificity of protein complexes, their precise energetic contributions to binding are unknown. Here, we use a model protein-protein interaction system in which a locally disordered region has been modified by directed evolution to quantitatively assess the thermodynamic and structural contributions to binding of disorder-to-order transitions. Through X-ray structure determination of the protein binding partners before and after complex formation and isothermal titration calorimetry of the interactions, we observe a correlation between protein ordering and binding affinity for complexes along this affinity maturation pathway. Additionally, we show that discrepancies between observed and calculated heat capacities based on buried surface area changes in the protein complexes can be explained largely by heat capacity changes that would result solely from folding the locally disordered region. Previously developed algorithms for predicting binding energies of protein-protein interactions, however, are unable to correctly model the energetic contributions of the structural transitions in our model system. While this highlights the shortcomings of current computational methods in modeling conformational flexibility, it suggests that the experimental methods used here could provide training sets of molecular interactions for improving these algorithms and further rationalizing molecular recognition in protein-protein interactions.

  6. Stabilization and inhibition of protein-protein interactions: the 14-3-3 case study.

    PubMed

    Milroy, Lech-Gustav; Brunsveld, Luc; Ottmann, Christian

    2013-01-18

    Small-molecule modulation of protein-protein interactions (PPIs) is one of the most exciting but also difficult fields in chemical biology and drug development. As one of the most important "hub" proteins with at least 200-300 interaction partners, the 14-3-3 proteins are an especially fruitful case for PPI intervention. Here, we summarize recent success stories in small-molecule modulation, both inhibition and stabilization, of 14-3-3 PPIs. The chemical breath of modulators includes natural products such as fusicoccin A and derivatives but also compounds identified via high-throughput and in silico screening, which has yielded a toolbox of useful inhibitors and stabilizers for this interesting class of adapter proteins. Protein-protein interactions (PPIs) are involved in almost all biological processes, with any given protein typically engaged in complexes with other proteins for the majority of its lifetime. Hence, proteins function not simply as single, isolated entities but display their roles by interacting with other cellular components. These different interaction patterns are presumably as important as the intrinsic biochemical activity status of the protein itself. The biological role of a protein is therefore decisively dependent on the underlying PPI network that furthermore can show great spatial and temporal variations. A thorough appreciation and understanding of this concept and its regulation mechanisms could help to develop new therapeutic agents and concepts.

  7. Evolutionary diversification of protein-protein interactions by interface add-ons.

    PubMed

    Plach, Maximilian G; Semmelmann, Florian; Busch, Florian; Busch, Markus; Heizinger, Leonhard; Wysocki, Vicki H; Merkl, Rainer; Sterner, Reinhard

    2017-09-18

    Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein-protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein-protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein-protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein-protein interactions.

  8. Quantification of protein interaction kinetics in a micro droplet

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

    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.

  9. PLIP: fully automated protein-ligand interaction profiler.

    PubMed

    Salentin, Sebastian; Schreiber, Sven; Haupt, V Joachim; Adasme, Melissa F; Schroeder, Michael

    2015-07-01

    The characterization of interactions in protein-ligand complexes is essential for research in structural bioinformatics, drug discovery and biology. However, comprehensive tools are not freely available to the research community. Here, we present the protein-ligand interaction profiler (PLIP), a novel web service for fully automated detection and visualization of relevant non-covalent protein-ligand contacts in 3D structures, freely available at projects.biotec.tu-dresden.de/plip-web. The input is either a Protein Data Bank structure, a protein or ligand name, or a custom protein-ligand complex (e.g. from docking). In contrast to other tools, the rule-based PLIP algorithm does not require any structure preparation. It returns a list of detected interactions on single atom level, covering seven interaction types (hydrogen bonds, hydrophobic contacts, pi-stacking, pi-cation interactions, salt bridges, water bridges and halogen bonds). PLIP stands out by offering publication-ready images, PyMOL session files to generate custom images and parsable result files to facilitate successive data processing. The full python source code is available for download on the website. PLIP's command-line mode allows for high-throughput interaction profiling. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  10. Quantification of protein interaction kinetics in a micro droplet

    SciTech Connect

    Yin, L. L.; Wang, S. P. E-mail: njtao@asu.edu; Shan, X. N.; Tao, N. J. E-mail: njtao@asu.edu; Zhang, S. T.

    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.

  11. 2D depiction of nonbonding interactions for protein complexes.

    PubMed

    Zhou, Peng; Tian, Feifei; Shang, Zhicai

    2009-04-30

    A program called the 2D-GraLab is described for automatically generating schematic representation of nonbonding interactions across the protein binding interfaces. The input file of this program takes the standard PDB format, and the outputs are two-dimensional PostScript diagrams giving intuitive and informative description of the protein-protein interactions and their energetics properties, including hydrogen bond, salt bridge, van der Waals interaction, hydrophobic contact, pi-pi stacking, disulfide bond, desolvation effect, and loss of conformational entropy. To ensure these interaction information are determined accurately and reliably, methods and standalone programs employed in the 2D-GraLab are all widely used in the chemistry and biology community. The generated diagrams allow intuitive visualization of the interaction mode and binding specificity between two subunits in protein complexes, and by providing information on nonbonding energetics and geometric characteristics, the program offers the possibility of comparing different protein binding profiles in a detailed, objective, and quantitative manner. We expect that this 2D molecular graphics tool could be useful for the experimentalists and theoreticians interested in protein structure and protein engineering.

  12. Evolution of a protein domain interaction network

    NASA Astrophysics Data System (ADS)

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

    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.

  13. Trimeric Transmembrane Domain Interactions in Paramyxovirus Fusion Proteins

    PubMed Central

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

    2013-01-01

    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. PMID:24178297

  14. Diffusing Colloidal Probes of Protein and Synthetic Macromolecule Interactions

    PubMed Central

    Everett, W. Neil; Wu, Hung-Jen; Anekal, Samartha G.; Sue, Hung-Jue; Bevan, Michael A.

    2007-01-01

    A new approach is described for measuring kT and nanometer scale protein-protein and protein-synthetic macromolecule interactions. The utility of this method is demonstrated by measuring interactions of bovine serum albumin (BSA) and copolymers with exposed polyethyleneoxide (PEO) moieties adsorbed to hydrophobically modified colloids and surfaces. Total internal reflection and video microscopy are used to track three-dimensional trajectories of many single diffusing colloids that are analyzed to yield interaction potentials, mean-square displacements, and colloid-surface association lifetimes. A criterion is developed to identify colloids as being levitated, associated, or deposited based on energetic, spatial, statistical, and temporal information. Whereas levitation and deposition occur for strongly repulsive or attractive potentials, association is exponentially sensitive to weak interactions influenced by adsorbed layer architectures and surface heterogeneity. Systematic experiments reveal how BSA orientation and PEO molecular weight produce adsorbed layers that either conceal or expose substrate heterogeneities to generate a continuum of colloid-surface association lifetimes. These measurements provide simultaneous access to a broad range of information that consistently indicates purely repulsive BSA and PEO interactions and a role for surface heterogeneity in colloid-surface association. The demonstrated capability to measure nonspecific protein interactions provides a basis for future measurements of specific protein interactions. PMID:17098785

  15. Imaging mRNA and protein interactions within neurons

    PubMed Central

    Eliscovich, Carolina; Shenoy, Shailesh M.

    2017-01-01

    RNA–protein interactions are essential for proper gene expression regulation, particularly in neurons with unique spatial constraints. Currently, these interactions are defined biochemically, but a method is needed to evaluate them quantitatively within morphological context. Colocalization of two-color labels using wide-field microscopy is a method to infer these interactions. However, because of chromatic aberrations in the objective lens, this approach lacks the resolution to determine whether two molecules are physically in contact or simply nearby by chance. Here, we developed a robust super registration methodology that corrected the chromatic aberration across the entire image field to within 10 nm, which is capable of determining whether two molecules are physically interacting or simply in proximity by random chance. We applied this approach to image single-molecule FISH in combination with immunofluorescence (smFISH-IF) and determined whether the association between an mRNA and binding protein(s) within a neuron was significant or accidental. We evaluated several mRNA-binding proteins identified from RNA pulldown assays to determine which of these exhibit bona fide interactions. Surprisingly, many known mRNA-binding proteins did not bind the mRNA in situ, indicating that adventitious interactions are significant using existing technology. This method provides an ability to evaluate two-color registration compatible with the scale of molecular interactions. PMID:28223507

  16. Identification of Redox and Glucose-Dependent Txnip Protein Interactions

    PubMed Central

    Neuharth, Skyla; Kim, Dae In; Motamedchaboki, Khatereh; Roux, Kyle J.

    2016-01-01

    Thioredoxin-interacting protein (Txnip) acts as a negative regulator of thioredoxin function and is a critical modulator of several diseases including, but not limited to, diabetes, ischemia-reperfusion cardiac injury, and carcinogenesis. Therefore, Txnip has become an attractive therapeutic target to alleviate disease pathologies. Although Txnip has been implicated with numerous cellular processes such as proliferation, fatty acid and glucose metabolism, inflammation, and apoptosis, the molecular mechanisms underlying these processes are largely unknown. The objective of these studies was to identify Txnip interacting proteins using the proximity-based labeling method, BioID, to understand differential regulation of pleiotropic Txnip cellular functions. The BioID transgene fused to Txnip expressed in HEK293 identified 31 interacting proteins. Many protein interactions were redox-dependent and were disrupted through mutation of a previously described reactive cysteine (C247S). Furthermore, we demonstrate that this model can be used to identify dynamic Txnip interactions due to known physiological regulators such as hyperglycemia. These data identify novel Txnip protein interactions and demonstrate dynamic interactions dependent on redox and glucose perturbations, providing clarification to the pleiotropic cellular functions of Txnip. PMID:27437069

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

    PubMed

    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.

  18. Mutant analysis, protein-protein interactions and subcellular localization of the Arabidopsis B sister (ABS) protein.

    PubMed

    Kaufmann, Kerstin; Anfang, Nicole; Saedler, Heinz; Theissen, Günter

    2005-09-01

    Recently, close relatives of class B floral homeotic genes, termed B(sister) genes, have been identified in both angiosperms and gymnosperms. In contrast to the B genes themselves, B(sister) genes are exclusively expressed in female reproductive organs, especially in the envelopes or integuments surrounding the ovules. This suggests an important ancient function in ovule or seed development for B(sister) genes, which has been conserved for about 300 million years. However, investigation of the first loss-of-function mutant for a B(sister) gene (ABS/TT16 from Arabidopsis) revealed only a weak phenotype affecting endothelium formation. Here, we present an analysis of two additional mutant alleles, which corroborates this weak phenotype. Transgenic plants that ectopically express ABS show changes in the growth and identity of floral organs, suggesting that ABS can interact with floral homeotic proteins. Yeast-two-hybrid and three-hybrid analyses indicated that ABS can form dimers with SEPALLATA (SEP) floral homeotic proteins and multimeric complexes that also include the AGAMOUS-like proteins SEEDSTICK (STK) or SHATTERPROOF1/2 (SHP1, SHP2). These data suggest that the formation of multimeric transcription factor complexes might be a general phenomenon among MIKC-type MADS-domain proteins in angiosperms. Heterodimerization of ABS with SEP3 was confirmed by gel retardation assays. Fusion proteins tagged with CFP (Cyan Fluorescent Protein) and YFP (Yellow Fluorescent Protein) in Arabidopsis protoplasts showed that ABS is localized in the nucleus. Phylogenetic analysis revealed the presence of a structurally deviant, but closely related, paralogue of ABS in the Arabidopsis genome. Thus the evolutionary developmental genetics of B(sister) genes can probably only be understood as part of a complex and redundant gene network that may govern ovule formation in a conserved manner, which has yet to be fully explored.

  19. Detecting Overlapping Protein Complexes by Rough-Fuzzy Clustering in Protein-Protein Interaction Networks

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2004-11-01

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

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

    PubMed

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

    2016-10-01

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

  2. Understanding Protein Synthesis: An Interactive Card Game Discussion

    ERIC Educational Resources Information Center

    Lewis, Alison; Peat, Mary; Franklin, Sue

    2005-01-01

    Protein synthesis is a complex process and students find it difficult to understand. This article describes an interactive discussion "game" used by first year biology students at the University of Sydney. The students, in small groups, use the game in which the processes of protein synthesis are actioned by the students during a…

  3. NMR-based analysis of protein-ligand interactions.

    PubMed

    Cala, Olivier; Guillière, Florence; Krimm, Isabelle

    2014-02-01

    Physiological processes are mainly controlled by intermolecular recognition mechanisms involving protein-protein and protein-ligand (low molecular weight molecules) interactions. One of the most important tools for probing these interactions is high-field solution nuclear magnetic resonance (NMR) through protein-observed and ligand-observed experiments, where the protein receptor or the organic compounds are selectively detected. NMR binding experiments rely on comparison of NMR parameters of the free and bound states of the molecules. Ligand-observed methods are not limited by the protein molecular size and therefore have great applicability for analysing protein-ligand interactions. The use of these NMR techniques has considerably expanded in recent years, both in chemical biology and in drug discovery. We review here three major ligand-observed NMR methods that depend on the nuclear Overhauser effect-transferred nuclear Overhauser effect spectroscopy, saturation transfer difference spectroscopy and water-ligand interactions observed via gradient spectroscopy experiments-with the aim of reporting recent developments and applications for the characterization of protein-ligand complexes, including affinity measurements and structural determination.

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

    PubMed

    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.

  5. Understanding Protein Synthesis: An Interactive Card Game Discussion

    ERIC Educational Resources Information Center

    Lewis, Alison; Peat, Mary; Franklin, Sue

    2005-01-01

    Protein synthesis is a complex process and students find it difficult to understand. This article describes an interactive discussion "game" used by first year biology students at the University of Sydney. The students, in small groups, use the game in which the processes of protein synthesis are actioned by the students during a…

  6. Use and application of hydrophobic interaction chromatography for protein purification.

    PubMed

    McCue, Justin T

    2014-01-01

    The objective of this section is to provide the reader with guidelines and background on the use and experimental application of Hydrophobic Interaction chromatography (HIC) for the purification of proteins. The section will give step by step instructions on how to use HIC in the laboratory to purify proteins. General guidelines and relevant background information is also provided.

  7. Protein-Protein Interactions: Gene Acronym Redundancies and Current Limitations Precluding Automated Data Integration.

    PubMed

    Casado-Vela, Juan; Matthiesen, Rune; Sellés, Susana; Naranjo, José Ramón

    2013-05-31

    Understanding protein interaction networks and their dynamic changes is a major challenge in modern biology. Currently, several experimental and in silico approaches allow the screening of protein interactors in a large-scale manner. Therefore, the bulk of information on protein interactions deposited in databases and peer-reviewed published literature is constantly growing. Multiple databases interfaced from user-friendly web tools recently emerged to facilitate the task of protein interaction data retrieval and data integration. Nevertheless, as we evidence in this report, despite the current efforts towards data integration, the quality of the information on protein interactions retrieved by in silico approaches is frequently incomplete and may even list false interactions. Here we point to some obstacles precluding confident data integration, with special emphasis on protein interactions, which include gene acronym redundancies and protein synonyms. Three human proteins (choline kinase, PPIase and uromodulin) and three different web-based data search engines focused on protein interaction data retrieval (PSICQUIC, DASMI and BIPS) were used to explain the potential occurrence of undesired errors that should be considered by researchers in the field. We demonstrate that, despite the recent initiatives towards data standardization, manual curation of protein interaction networks based on literature searches are still required to remove potential false positives. A three-step workflow consisting of: (i) data retrieval from multiple databases, (ii) peer-reviewed literature searches, and (iii) data curation and integration, is proposed as the best strategy to gather updated information on protein interactions. Finally, this strategy was applied to compile bona fide information on human DREAM protein interactome, which constitutes liable training datasets that can be used to improve computational predictions.

  8. Protein-Protein Interactions: Gene Acronym Redundancies and Current Limitations Precluding Automated Data Integration

    PubMed Central

    Casado-Vela, Juan; Matthiesen, Rune; Sellés, Susana; Naranjo, José Ramón

    2013-01-01

    Understanding protein interaction networks and their dynamic changes is a major challenge in modern biology. Currently, several experimental and in silico approaches allow the screening of protein interactors in a large-scale manner. Therefore, the bulk of information on protein interactions deposited in databases and peer-reviewed published literature is constantly growing. Multiple databases interfaced from user-friendly web tools recently emerged to facilitate the task of protein interaction data retrieval and data integration. Nevertheless, as we evidence in this report, despite the current efforts towards data integration, the quality of the information on protein interactions retrieved by in silico approaches is frequently incomplete and may even list false interactions. Here we point to some obstacles precluding confident data integration, with special emphasis on protein interactions, which include gene acronym redundancies and protein synonyms. Three human proteins (choline kinase, PPIase and uromodulin) and three different web-based data search engines focused on protein interaction data retrieval (PSICQUIC, DASMI and BIPS) were used to explain the potential occurrence of undesired errors that should be considered by researchers in the field. We demonstrate that, despite the recent initiatives towards data standardization, manual curation of protein interaction networks based on literature searches are still required to remove potential false positives. A three-step workflow consisting of: (i) data retrieval from multiple databases, (ii) peer-reviewed literature searches, and (iii) data curation and integration, is proposed as the best strategy to gather updated information on protein interactions. Finally, this strategy was applied to compile bona fide information on human DREAM protein interactome, which constitutes liable training datasets that can be used to improve computational predictions. PMID:28250396

  9. Sequence Motifs in MADS Transcription Factors Responsible for Specificity and Diversification of Protein-Protein Interaction

    PubMed Central

    van Dijk, Aalt D. J.; Morabito, Giuseppa; Fiers, Martijn; van Ham, Roeland C. H. J.; Angenent, Gerco C.; Immink, Richard G. H.

    2010-01-01

    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 network evolution. PMID

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

    PubMed

    Dukare, Sandeep; Klempnauer, Karl-Heinz

    2016-07-01

    The transcription factor c-Myb plays a key role in the control of proliferation and differentiation in hematopoietic progenitor cells and has been implicated in the development of leukemia and certain non-hematopoietic tumors. c-Myb activity is highly dependent on the interaction with the coactivator p300 which is mediated by the transactivation domain of c-Myb and the KIX domain of p300. We have previously observed that conservative valine-to-isoleucine amino acid substitutions in a conserved stretch of hydrophobic amino acids have a profound effect on Myb activity. Here, we have explored the function of the hydrophobic region as a mediator of protein-protein interactions. We show that the hydrophobic region facilitates Myb self-interaction and binding of the histone acetyl transferase Tip60, a previously identified Myb interacting protein. We show that these interactions are affected by the valine-to-isoleucine amino acid substitutions and suppress Myb activity by interfering with the interaction of Myb and the KIX domain of p300. Taken together, our work identifies the hydrophobic region in the Myb transactivation domain as a binding site for homo- and heteromeric protein interactions and leads to a picture of the c-Myb transactivation domain as a composite protein binding region that facilitates interdependent protein-protein interactions of Myb with regulatory proteins. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Detection of Peptides, Proteins, and Drugs That Selectively Interact With Protein Targets

    PubMed Central

    Serebriiskii, Ilya G.; Mitina, Olga; Pugacheva, Elena N.; Benevolenskaya, Elizaveta; Kotova, Elena; Toby, Garabet G.; Khazak, Vladimir; Kaelin, William G.; Chernoff, Jonathan; Golemis, Erica A.

    2002-01-01

    Genome sequencing has been completed for multiple organisms, and pilot proteomic analyses reported for yeast and higher eukaryotes. This work has emphasized the facts that proteins are frequently engaged in multiple interactions, and that governance of protein interaction specificity is a primary means of regulating biological systems. In particular, the ability to deconvolute complex protein interaction networks to identify which interactions govern specific signaling pathways requires the generation of biological tools that allow the distinction of critical from noncritical interactions. We report the application of an enhanced Dual Bait two-hybrid system to allow detection and manipulation of highly specific protein–protein interactions. We summarize the use of this system to detect proteins and peptides that target well-defined specific motifs in larger protein structures, to facilitate rapid identification of specific interactors from a pool of putative interacting proteins obtained in a library screen, and to score specific drug-mediated disruption of protein–protein interaction. [Supplemental material is available online at http://www.genome.org. The following individuals kindly provided reagents, samples, or unpublished information as indicated in the paper: A. Taliana, M. Russell, M. Berman, and R. Finley.] PMID:12421766

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

    PubMed

    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.

  13. The Role of Protein-Protein and Protein-Membrane Interactions on P450 Function.

    PubMed

    Scott, Emily E; Wolf, C Roland; Otyepka, Michal; Humphreys, Sara C; Reed, James R; Henderson, Colin J; McLaughlin, Lesley A; Paloncýová, Markéta; Navrátilová, Veronika; Berka, Karel; Anzenbacher, Pavel; Dahal, Upendra P; Barnaba, Carlo; Brozik, James A; Jones, Jeffrey P; Estrada, D Fernando; Laurence, Jennifer S; Park, Ji Won; Backes, Wayne L

    2016-04-01

    This symposium summary, sponsored by the ASPET, was held at Experimental Biology 2015 on March 29, 2015, in Boston, Massachusetts. The symposium focused on: 1) the interactions of cytochrome P450s (P450s) with their redox partners; and 2) the role of the lipid membrane in their orientation and stabilization. Two presentations discussed the interactions of P450s with NADPH-P450 reductase (CPR) and cytochrome b5. First, solution nuclear magnetic resonance was used to compare the protein interactions that facilitated either the hydroxylase or lyase activities of CYP17A1. The lyase interaction was stimulated by the presence of b5 and 17α-hydroxypregnenolone, whereas the hydroxylase reaction was predominant in the absence of b5. The role of b5 was also shown in vivo by selective hepatic knockout of b5 from mice expressing CYP3A4 and CYP2D6; the lack of b5 caused a decrease in the clearance of several substrates. The role of the membrane on P450 orientation was examined using computational methods, showing that the proximal region of the P450 molecule faced the aqueous phase. The distal region, containing the substrate-access channel, was associated with the membrane. The interaction of NADPH-P450 reductase (CPR) with the membrane was also described, showing the ability of CPR to "helicopter" above the membrane. Finally, the endoplasmic reticulum (ER) was shown to be heterogeneous, having ordered membrane regions containing cholesterol and more disordered regions. Interestingly, two closely related P450s, CYP1A1 and CYP1A2, resided in different regions of the ER. The structural characteristics of their localization were examined. These studies emphasize the importance of P450 protein organization to their function. Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

  14. The Role of Protein-Protein and Protein-Membrane Interactions on P450 Function

    PubMed Central

    Scott, Emily E.; Wolf, C. Roland; Otyepka, Michal; Humphreys, Sara C.; Reed, James R.; Henderson, Colin J.; McLaughlin, Lesley A.; Paloncýová, Markéta; Navrátilová, Veronika; Berka, Karel; Anzenbacher, Pavel; Dahal, Upendra P.; Barnaba, Carlo; Brozik, James A.; Jones, Jeffrey P.; Estrada, D. Fernando; Laurence, Jennifer S.; Park, Ji Won

    2016-01-01

    This symposium summary, sponsored by the ASPET, was held at Experimental Biology 2015 on March 29, 2015, in Boston, Massachusetts. The symposium focused on: 1) the interactions of cytochrome P450s (P450s) with their redox partners; and 2) the role of the lipid membrane in their orientation and stabilization. Two presentations discussed the interactions of P450s with NADPH-P450 reductase (CPR) and cytochrome b5. First, solution nuclear magnetic resonance was used to compare the protein interactions that facilitated either the hydroxylase or lyase activities of CYP17A1. The lyase interaction was stimulated by the presence of b5 and 17α-hydroxypregnenolone, whereas the hydroxylase reaction was predominant in the absence of b5. The role of b5 was also shown in vivo by selective hepatic knockout of b5 from mice expressing CYP3A4 and CYP2D6; the lack of b5 caused a decrease in the clearance of several substrates. The role of the membrane on P450 orientation was examined using computational methods, showing that the proximal region of the P450 molecule faced the aqueous phase. The distal region, containing the substrate-access channel, was associated with the membrane. The interaction of NADPH-P450 reductase (CPR) with the membrane was also described, showing the ability of CPR to “helicopter” above the membrane. Finally, the endoplasmic reticulum (ER) was shown to be heterogeneous, having ordered membrane regions containing cholesterol and more disordered regions. Interestingly, two closely related P450s, CYP1A1 and CYP1A2, resided in different regions of the ER. The structural characteristics of their localization were examined. These studies emphasize the importance of P450 protein organization to their function. PMID:26851242

  15. Interacting protein partners of Arabidopsis RNA-binding protein AtRBP45b.

    PubMed

    Muthuramalingam, M; Wang, Y; Li, Y; Mahalingam, R

    2017-05-01

    RNA binding proteins, important players in post-transcriptional gene regulation, usually exist in ribonuclear complexes. However, even in model systems like Arabidopsis characterisation of RBP associated proteins is limited. In this study, we investigated the interacting proteins of the Arabidopsis AtRBP45b, which is involved in stress signalling. In vivo localisation of AtRBP45b was conducted using 35S-GFP. FLAG-tagged AtRBP45b under control of the 35S promoter in the Atrbp45b-1 mutant background was used to pull down AtRBP45b interacting proteins. Yeast two-hybrid analysis, fluorescence energy resonance transfer assays were used to confirm the veracity of the AtRBP45b interacting proteins. In planta GFP-tagging indicated AtRBP45b is localised to the nucleus and the cytosol. AtRBP45b protein has a N-terminal proline-rich region and a C-terminal glutamine-rich domain that are usually involved in protein-protein interactions. Co-immunoprecipitation followed by mass spectrometry-based protein sequencing led to identification of 30 proteins that interacted with AtRBP45b. Using information from interactome databases (BIOGRID, INTACT and STRING), pull-down assays and localisation data, 12 putative interacting proteins were selected for yeast two-hybrid analysis. Cap-binding protein (CBP20, At5g44200) and polyA-binding protein (PAB8, At1g49760) were shown to interact with AtRBP45b. Based on its interacting partners we speculate that AtRBP45b may play an important role in RNA metabolism, especially in aspects related to mRNA stability and translation initiation during stress conditions in plants.

  16. The RNA-binding protein SERBP1 interacts selectively with the signaling protein RACK1.

    PubMed

    Bolger, Graeme B

    2017-03-04

    The RACK1 protein interacts with numerous proteins involved in signal transduction, the cytoskeleton, and mRNA splicing and translation. We used the 2-hybrid system to identify additional proteins interacting with RACK1 and isolated the RNA-binding protein SERBP1. SERPB1 shares amino acid sequence homology with HABP4 (also known as Ki-1/57), a component of the RNA spicing machinery that has been shown previously to interact with RACK1. Several different isoforms of SERBP1, generated by alternative mRNA splicing, interacted with RACK1 with indistinguishable interaction strength, as determined by a 2-hybrid beta-galactosidase assay. Analysis of deletion constructs of SERBP1 showed that the C-terminal third of the SERBP1 protein, which contains one of its two substrate sites for protein arginine N-methyltransferase 1 (PRMT1), is necessary and sufficient for it to interact with RACK1. Analysis of single amino acid substitutions in RACK1, identified in a reverse 2-hybrid screen, showed very substantial overlap with those implicated in the interaction of RACK1 with the cAMP-selective phosphodiesterase PDE4D5. These data are consistent with SERBP1 interacting selectively with RACK1, mediated by an extensive interaction surface on both proteins.

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

    PubMed Central

    Luo, Jiawei; Qi, Yi

    2015-01-01

    Background 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. Method 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. Results 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). Conclusions LIDC is more effective for the prediction of essential proteins than other recently developed methods. PMID:26125187

  18. Identification of DIM-7, a protein required to target the DIM-5 H3 methyltransferase to chromatin

    PubMed Central

    Lewis, Zachary A.; Adhvaryu, Keyur K.; Honda, Shinji; Shiver, Anthony L.; Selker, Eric U.

    2010-01-01

    Functionally distinct chromatin domains are delineated by distinct posttranslational modifications of histones, and in some organisms by differences in DNA methylation. Proper establishment and maintenance of chromatin domains is critical but not well understood. We previously demonstrated that heterochromatin in the filamentous fungus Neurospora crassa is marked by cytosine methylation directed by trimethylated Lysine 9 on histone H3 (H3K9me3). H3K9me3 is the product of the DIM-5 Lysine methyltransferase and is recognized by a protein complex containing heterochromatin protein-1 and the DIM-2 DNA methyltransferase. To identify additional components that control the establishment and function of DNA methylation and heterochromatin, we built a strain harboring two selectable reporter genes that are silenced by DNA methylation and employed this strain to select for mutants that are defective in DNA methylation (dim). We report a previously unidentified gene (dim-7) that is essential for H3K9me3 and DNA methylation. DIM-7 homologs are found only in fungi and are highly divergent. We found that DIM-7 interacts with DIM-5 in vivo and demonstrated that a conserved domain near the N terminus of DIM-7 is required for its stability. In addition, we found that DIM-7 is essential for recruitment of DIM-5 to form heterochromatin. PMID:20404183

  19. A Protein Interaction Map of the Kalimantacin Biosynthesis Assembly Line

    PubMed Central

    Uytterhoeven, Birgit; Lathouwers, Thomas; Voet, Marleen; Michiels, Chris W.; Lavigne, Rob

    2016-01-01

    The antimicrobial secondary metabolite kalimantacin (also called batumin) 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. PMID:27853452

  20. Differential scanning calorimetry of protein-lipid interactions.

    PubMed

    Cañadas, Olga; Casals, Cristina

    2013-01-01

    Differential scanning calorimetry (DSC) is a highly sensitive non-perturbing technique for measuring the thermodynamic properties of thermally induced transitions. This technique is particularly useful for the characterization of lipid/protein interactions. This chapter presents an introduction to DSC instrumentation, basic theory, and methods and describes DSC applications for characterizing protein effects on model lipid membranes. Examples of the use of DSC for the evaluation of protein effects on modulation of membrane domains and membrane stability are given.

  1. Examination of Interactions of Oppositely Charged Proteins in Gels

    SciTech Connect

    Ramasamy,P.; El-Maghrabi, M.; Halada, G.; Miller, L.; Rafailovich, M.

    2007-01-01

    Understanding the interactions of proteins with one another serves as an important step for developing faster protein separation methods. To examine protein-protein interactions of oppositely charged proteins, fluorescently labeled albumin and poly-L-lysine were subjected to electrophoresis in agarose gels, in which the cationic albumin and the anionic poly-L-lysine were allowed to migrate toward each other and interact. Fluorescence microscopy was used to image fluorescently tagged proteins in the gel. The secondary structure of the proteins in solution was studied using conventional FTIR spectroscopy. Results showed that sharp interfaces were formed where FITC tagged albumin met poly-L-lysine and that the interfaces did not migrate after they had been formed. The position of the interface in the gel was found to be linearly dependent upon the relative concentration of the proteins. The formation of the interface also depended upon the fluorescent tag attached to the protein. The size of the aggregates at the interface, the fluorescence intensity modifications, and the mobility of the interface for different pore sizes of the gel were investigated. It was observed that the interface was made up of aggregates of about 1 {mu}m in size. Using dynamic light scattering, it was observed that the size of the aggregates that formed due to interactions of oppositely charged proteins depended upon the fluorescent tags attached to the proteins. The addition of small amounts of poly-L-lysine to solutions containing FITC albumin decreased the zeta potential drastically. For this, we propose a model suggesting that adding small amounts of poly-L-lysine to solutions containing FITC -albumin favors the formation of macromolecular complexes having FITC albumin molecules on its surface. Although oppositely charged FITC tagged poly-L-lysine and FITC tagged albumin influence each other's migration velocities by forming aggregates, there were no observable secondary structural

  2. Protein-protein interactions in the regulation of WRKY transcription factors.

    PubMed

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

    2013-03-01

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

  3. Screening for in planta protein-protein interactions combining bimolecular fluorescence complementation with flow cytometry

    PubMed Central

    2012-01-01