Science.gov

Sample records for protein 7a interacts

  1. Charcot-Marie-Tooth type 2B disease-causing RAB7A mutant proteins show altered interaction with the neuronal intermediate filament peripherin.

    PubMed

    Cogli, Laura; Progida, Cinzia; Thomas, Claire L; Spencer-Dene, Bradley; Donno, Claudia; Schiavo, Giampietro; Bucci, Cecilia

    2013-02-01

    Charcot-Marie-Tooth type 2B (CMT2B) is a peripheral ulcero-mutilating neuropathy caused by four missense mutations in the rab7a gene. CMT2B is clinically characterized by prominent sensory loss, distal muscle weakness leading to muscle atrophy, high frequency of foot ulcers and infections that often results in toe amputations. RAB7A is a ubiquitous small GTPase, which controls transport to late endocytic compartments. Although the biochemical and functional properties of disease-causing RAB7A mutant proteins have been investigated, it is not yet clear how the disease originates. To understand how mutations in a ubiquitous protein specifically affect peripheral neurons, we performed a two-hybrid screen using a dorsal root ganglia cDNA library with the purpose of identifying RAB7A interactors specific for these cells. We identified peripherin, an intermediate filament protein expressed primarily in peripheral neurons, as a putative RAB7A interacting protein. The interaction was confirmed by co-immunoprecipitation and pull-down experiments, and established that the interaction is direct using recombinant proteins. Silencing or overexpression of wild type RAB7A changed the soluble/insoluble rate of peripherin indicating that RAB7A is important for peripherin organization and function. In addition, disease-causing RAB7A mutant proteins bind more strongly to peripherin and their expression causes a significant increase in the amount of soluble peripherin. Since peripherin plays a role not only in neurite outgrowth during development but also in axonal regeneration after injury, these data suggest that the altered interaction between disease-causing RAB7A mutants and peripherin could play an important role in CMT2B neuropathy.

  2. Bacteriophage protein-protein interactions.

    PubMed

    Häuser, Roman; Blasche, Sonja; Dokland, Terje; Haggård-Ljungquist, Elisabeth; von Brunn, Albrecht; Salas, Margarita; Casjens, Sherwood; Molineux, Ian; Uetz, Peter

    2012-01-01

    Bacteriophages T7, λ, P22, and P2/P4 (from Escherichia coli), as well as ϕ29 (from Bacillus subtilis), are among the best-studied bacterial viruses. This chapter summarizes published protein interaction data of intraviral protein interactions, as well as known phage-host protein interactions of these phages retrieved from the literature. We also review the published results of comprehensive protein interaction analyses of Pneumococcus phages Dp-1 and Cp-1, as well as coliphages λ and T7. For example, the ≈55 proteins encoded by the T7 genome are connected by ≈43 interactions with another ≈15 between the phage and its host. The chapter compiles published interactions for the well-studied phages λ (33 intra-phage/22 phage-host), P22 (38/9), P2/P4 (14/3), and ϕ29 (20/2). We discuss whether different interaction patterns reflect different phage lifestyles or whether they may be artifacts of sampling. Phages that infect the same host can interact with different host target proteins, as exemplified by E. coli phage λ and T7. Despite decades of intensive investigation, only a fraction of these phage interactomes are known. Technical limitations and a lack of depth in many studies explain the gaps in our knowledge. Strategies to complete current interactome maps are described. Although limited space precludes detailed overviews of phage molecular biology, this compilation will allow future studies to put interaction data into the context of phage biology. PMID:22748812

  3. 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

  4. Cardiolipin Interactions with Proteins.

    PubMed

    Planas-Iglesias, Joan; Dwarakanath, Himal; Mohammadyani, Dariush; Yanamala, Naveena; Kagan, Valerian E; Klein-Seetharaman, Judith

    2015-09-15

    Cardiolipins (CL) represent unique phospholipids of bacteria and eukaryotic mitochondria with four acyl chains and two phosphate groups that have been implicated in numerous functions from energy metabolism to apoptosis. Many proteins are known to interact with CL, and several cocrystal structures of protein-CL complexes exist. In this work, we describe the collection of the first systematic and, to the best of our knowledge, the comprehensive gold standard data set of all known CL-binding proteins. There are 62 proteins in this data set, 21 of which have nonredundant crystal structures with bound CL molecules available. Using binding patch analysis of amino acid frequencies, secondary structures and loop supersecondary structures considering phosphate and acyl chain binding regions together and separately, we gained a detailed understanding of the general structural and dynamic features involved in CL binding to proteins. Exhaustive docking of CL to all known structures of proteins experimentally shown to interact with CL demonstrated the validity of the docking approach, and provides a rich source of information for experimentalists who may wish to validate predictions.

  5. 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.

  6. Cardiolipin Interactions with Proteins

    PubMed Central

    Planas-Iglesias, Joan; Dwarakanath, Himal; Mohammadyani, Dariush; Yanamala, Naveena; Kagan, Valerian E.; Klein-Seetharaman, Judith

    2015-01-01

    Cardiolipins (CL) represent unique phospholipids of bacteria and eukaryotic mitochondria with four acyl chains and two phosphate groups that have been implicated in numerous functions from energy metabolism to apoptosis. Many proteins are known to interact with CL, and several cocrystal structures of protein-CL complexes exist. In this work, we describe the collection of the first systematic and, to the best of our knowledge, the comprehensive gold standard data set of all known CL-binding proteins. There are 62 proteins in this data set, 21 of which have nonredundant crystal structures with bound CL molecules available. Using binding patch analysis of amino acid frequencies, secondary structures and loop supersecondary structures considering phosphate and acyl chain binding regions together and separately, we gained a detailed understanding of the general structural and dynamic features involved in CL binding to proteins. Exhaustive docking of CL to all known structures of proteins experimentally shown to interact with CL demonstrated the validity of the docking approach, and provides a rich source of information for experimentalists who may wish to validate predictions. PMID:26300339

  7. Zebrafish Thsd7a is a neural protein required for angiogenic patterning during development.

    PubMed

    Wang, Chieh-Huei; Chen, I-Hui; Kuo, Meng-Wei; Su, Pei-Tsu; Lai, Zih-Yin; Wang, Chian-Huei; Huang, Wei-Chang; Hoffman, Jana; Kuo, Calvin J; You, May-Su; Chuang, Yung-Jen

    2011-06-01

    Angiogenesis is a highly organized process under the control of guidance cues that direct endothelial cell (EC) migration. Recently, many molecules that were initially described as regulators of neural guidance were subsequently shown to also direct EC migration. Here, we report a novel protein, thrombospondin type I domain containing 7A (Thsd7a), that is a neural molecule required for directed EC migration during embryonic angiogenesis in zebrafish. Thsd7a is a vertebrate conserved protein. Zebrafish thsd7a transcript was detected along the ventral edge of the neural tube in the developing zebrafish embryos, correlating with the growth path of angiogenic intersegmental vessels (ISVs). Morpholino-knockdown of Thsd7a caused a lateral deviation of angiogenic ECs below the thsd7a-expressing sites, resulting in aberrant ISV patterning. Collectively, our study shows that zebrafish Thsd7a is a neural protein required for ISV angiogenesis, and suggests an important role of Thsd7a in the neurovascular interaction during zebrafish development.

  8. Nanobiotechnology: protein-nanomaterial interactions.

    PubMed

    Kane, Ravi S; Stroock, Abraham D

    2007-01-01

    We review recent research that involves the interaction of nanomaterials such as nanoparticles, nanowires, and carbon nanotubes with proteins. We begin with a focus on the fundamentals of the structure and function of proteins on nanomaterials. We then review work in three areas that exploit these interactions: (1) sensing, (2) assembly of nanomaterials by proteins and proteins by nanomaterials, and (3) interactions with cells. We conclude with the identification of challenges and opportunities for the future. PMID:17335286

  9. 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

  10. 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.

  11. 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

  12. 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

  13. Bacteriophage Protein–Protein Interactions

    PubMed Central

    Häuser, Roman; Blasche, Sonja; Dokland, Terje; Haggård-Ljungquist, Elisabeth; von Brunn, Albrecht; Salas, Margarita; Casjens, Sherwood; Molineux, Ian

    2012-01-01

    Bacteriophages T7, λ, P22, and P2/P4 (from Escherichia coli), as well as ϕ29 (from Bacillus subtilis), are among the best-studied bacterial viruses. This chapter summarizes published protein interaction data of intraviral protein interactions, as well as known phage–host protein interactions of these phages retrieved from the literature. We also review the published results of comprehensive protein interaction analyses of Pneumococcus phages Dp-1 and Cp-1, as well as coliphages λ and T7. For example, the ≈55 proteins encoded by the T7 genome are connected by ≈43 interactions with another ≈15 between the phage and its host. The chapter compiles published interactions for the well-studied phages λ (33 intra-phage/22 phage-host), P22 (38/9), P2/P4 (14/3), and ϕ29 (20/2). We discuss whether different interaction patterns reflect different phage lifestyles or whether they may be artifacts of sampling. Phages that infect the same host can interact with different host target proteins, as exemplified by E. coli phage λ and T7. Despite decades of intensive investigation, only a fraction of these phage interactomes are known. Technical limitations and a lack of depth in many studies explain the gaps in our knowledge. Strategies to complete current interactome maps are described. Although limited space precludes detailed overviews of phage molecular biology, this compilation will allow future studies to put interaction data into the context of phage biology. PMID:22748812

  14. Disentangling protein-silica interactions.

    PubMed

    Giussani, Lara; Tabacchi, Gloria; Gianotti, Enrica; Coluccia, Salvatore; Fois, Ettore

    2012-03-28

    We present the results of modelling studies aimed at the understanding of the interaction of a 7 nm sized water droplet containing a negatively charged globular protein with flat silica surfaces. We show how the droplet interaction with the surface depends on the electrostatic surface charge, and that adhesion of the droplet occurs when the surface is negatively charged as well. The key role of water and of the charge-balancing counter ions in mediating the surface-protein adhesion is highlighted. The relevance of the present results with respect to the production of bioinorganic hybrids via encapsulation of proteins inside mesoporous silica materials is discussed.

  15. How to Study Protein-protein Interactions.

    PubMed

    Podobnik, Marjetka; Kraševec, Nada; Bedina Zavec, Apolonija; Naneh, Omar; Flašker, Ajda; Caserman, Simon; Hodnik, Vesna; Anderluh, Gregor

    2016-01-01

    Physical and functional interactions between molecules in living systems are central to all biological processes. Identification of protein complexes therefore is becoming increasingly important to gain a molecular understanding of cells and organisms. Several powerful methodologies and techniques have been developed to study molecular interactions and thus help elucidate their nature and role in biology as well as potential ways how to interfere with them. All different techniques used in these studies have their strengths and weaknesses and since they are mostly employed in in vitro conditions, a single approach can hardly accurately reproduce interactions that happen under physiological conditions. However, complementary usage of as many as possible available techniques can lead to relatively realistic picture of the biological process. Here we describe several proteomic, biophysical and structural tools that help us understand the nature and mechanism of these interactions. PMID:27640371

  16. Interaction Trap/Two-Hybrid System to Identify Interacting Proteins

    PubMed Central

    Golemis, Erica A.; Serebriiskii, Ilya; Finley, Russell L.; Kolonin, Mikhail G.; Gyuris, Jeno; Brent, Roger

    2014-01-01

    The yeast two-hybrid method (or interaction trap) is a powerful technique for detecting protein interactions. The procedure is performed using transcriptional activation of a dual reporter system in yeast to identify interactions between a protein of interest (the bait protein) and the candidate proteins for interaction. The method can be used to screen a protein library for interactions with a bait protein or to test for association between proteins that are expected to interact based on prior evidence. Interaction mating facilitates the screening of a library with multiple bait proteins. PMID:18228339

  17. Energy design for protein-protein interactions

    PubMed Central

    Ravikant, D. V. S.; Elber, Ron

    2011-01-01

    Proteins bind to other proteins efficiently and specifically to carry on many cell functions such as signaling, activation, transport, enzymatic reactions, and more. To determine the geometry and strength of binding of a protein pair, an energy function is required. An algorithm to design an optimal energy function, based on empirical data of protein complexes, is proposed and applied. Emphasis is made on negative design in which incorrect geometries are presented to the algorithm that learns to avoid them. For the docking problem the search for plausible geometries can be performed exhaustively. The possible geometries of the complex are generated on a grid with the help of a fast Fourier transform algorithm. A novel formulation of negative design makes it possible to investigate iteratively hundreds of millions of negative examples while monotonically improving the quality of the potential. Experimental structures for 640 protein complexes are used to generate positive and negative examples for learning parameters. The algorithm designed in this work finds the correct binding structure as the lowest energy minimum in 318 cases of the 640 examples. Further benchmarks on independent sets confirm the significant capacity of the scoring function to recognize correct modes of interactions. PMID:21842951

  18. Interactions of Pathological Hallmark Proteins

    PubMed Central

    Oláh, Judit; Vincze, Orsolya; Virók, Dezső; Simon, Dóra; Bozsó, Zsolt; Tőkési, Natália; Horváth, István; Hlavanda, Emma; Kovács, János; Magyar, Anna; Szűcs, Mária; Orosz, Ferenc; Penke, Botond; Ovádi, Judit

    2011-01-01

    The disordered tubulin polymerization promoting protein (TPPP/p25) was found to be co-enriched in neuronal and glial inclusions with α-synuclein in Parkinson disease and multiple system atrophy, respectively; however, co-occurrence of α-synuclein with β-amyloid (Aβ) in human brain inclusions has been recently reported, suggesting the existence of mixed type pathologies that could result in obstacles in the correct diagnosis and treatment. Here we identified TPPP/p25 as an interacting partner of the soluble Aβ oligomers as major risk factors for Alzheimer disease using ProtoArray human protein microarray. The interactions of oligomeric Aβ with proteins involved in the etiology of neurological disorders were characterized by ELISA, surface plasmon resonance, pelleting experiments, and tubulin polymerization assay. We showed that the Aβ42 tightly bound to TPPP/p25 (Kd = 85 nm) and caused aberrant protein aggregation by inhibiting the physiologically relevant TPPP/p25-derived microtubule assembly. The pair-wise interactions of Aβ42, α-synuclein, and tubulin were found to be relatively weak; however, these three components formed soluble ternary complex exclusively in the absence of TPPP/p25. The aggregation-facilitating activity of TPPP/p25 and its interaction with Aβ was monitored by electron microscopy with purified proteins by pelleting experiments with cell-free extracts as well as by confocal microscopy with CHO cells expressing TPPP/p25 or amyloid. The finding that the interaction of TPPP/p25 with Aβ can produce pathological-like aggregates is tightly coupled with unusual pathology of the Alzheimer disease revealed previously; that is, partial co-localization of Aβ and TPPP/p25 in the case of diffuse Lewy body disease with Alzheimer disease. PMID:21832049

  19. 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.

  20. 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.

  1. ADAMTS-7: a metalloproteinase that directly binds to and degrades cartilage oligomeric matrix protein

    PubMed Central

    Liu, Chuan-ju; Kong, Wei; Ilalov, Kiril; Yu, Shuang; Xu, Ke; Prazak, Lisa; Fajardo, Marc; Sehgal, Bantoo; Di Cesare, Paul E.

    2006-01-01

    Degradative fragments of cartilage oligomeric matrix protein (COMP) have been observed in arthritic patients. The physiological enzyme(s) that degrade COMP, however, remain unknown. We performed a yeast two-hybrid screen (Y2H) to search for proteins that associate with COMP to identify an interaction partner that might degrade it. One screen using the epidermal growth factor (EGF) domain of COMP as bait led to the discovery of ADAMTS-7. Rat ADAMTS-7 is composed of 1595 amino acids, and this protein exhibits higher expression in the musculoskeletal tissues. COMP binds directly to ADAMTS-7 in vitro and in native articular cartilage. ADAMTS-7 selectively interacts with the EGF repeat domain but not with the other three functional domains of COMP, whereas the four C-terminal TSP motifs of ADAMTS-7 are required and sufficient for association with COMP. The recombinant catalytic domain and intact ADAMTS-7 are capable of digesting COMP in vitro. The enzymatic activity of ADAMTS-7 requires the presence of Zn2+ and appropriate pH (7.5-9.5), and the concentration of ADAMTS-7 in cartilage and synovium of patients with rheumatoid arthritis is significantly increased as compared to normal cartilage and synovium. ADAMTS-7 is the first metalloproteinase found to bind directly to and degrade COMP.—Liu, C., Kong, W., Ilalov, K., Yu, S., Xu, K., Prazak, L., Fajardo, M., Sehgal, B., Di Cesare, P. E. ADAMTS-7: a metalloproteinase that directly binds to and degrades cartilage oligomeric matrix protein. FASEB J. 20, E129 -E140 (2006) PMID:16585064

  2. The protein-protein interaction map of Helicobacter pylori.

    PubMed

    Rain, J C; Selig, L; De Reuse, H; Battaglia, V; Reverdy, C; Simon, S; Lenzen, G; Petel, F; Wojcik, J; Schächter, V; Chemama, Y; Labigne, A; Legrain, P

    2001-01-11

    With the availability of complete DNA sequences for many prokaryotic and eukaryotic genomes, and soon for the human genome itself, it is important to develop reliable proteome-wide approaches for a better understanding of protein function. As elementary constituents of cellular protein complexes and pathways, protein-protein interactions are key determinants of protein function. Here we have built a large-scale protein-protein interaction map of the human gastric pathogen Helicobacter pylori. We have used a high-throughput strategy of the yeast two-hybrid assay to screen 261 H. pylori proteins against a highly complex library of genome-encoded polypeptides. Over 1,200 interactions were identified between H. pylori proteins, connecting 46.6% of the proteome. The determination of a reliability score for every single protein-protein interaction and the identification of the actual interacting domains permitted the assignment of unannotated proteins to biological pathways.

  3. 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

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

    PubMed Central

    2009-01-01

    Over the past few years, the number of known protein-protein interactions has increased substantially. To make this information more readily available, a number of publicly available databases have set out to collect and store protein-protein interaction data. Protein-protein interactions have been retrieved from six major databases, integrated and the results compared. The six databases (the Biological General Repository for Interaction Datasets [BioGRID], the Molecular INTeraction database [MINT], the Biomolecular Interaction Network Database [BIND], the Database of Interacting Proteins [DIP], the IntAct molecular interaction database [IntAct] and the Human Protein Reference Database [HPRD]) differ in scope and content; integration of all datasets is non-trivial owing to differences in data annotation. With respect to human protein-protein interaction data, HPRD seems to be the most comprehensive. To obtain a complete dataset, however, interactions from all six databases have to be combined. To overcome this limitation, meta-databases such as the Agile Protein Interaction Database (APID) offer access to integrated protein-protein interaction datasets, although these also currently have certain restrictions. PMID:19403463

  5. High-throughput and multiplexed protein array technology: protein-DNA and protein-protein interactions.

    PubMed

    Sakanyan, Vehary

    2005-02-01

    Miniaturized protein arrays address protein interactions with various types of molecules in a high-throughput and multiplexed fashion. This review focuses on achievements in the analysis of protein-DNA and protein-protein interactions. The technological feasibility of protein arrays depends on the different factors that enable the arrayed proteins to recognize molecular partners and on the specificity of the interactions involved. Proteome-scale studies of molecular interactions require high-throughput approaches for both the production and purification of functionally active proteins. Various solutions have been proposed to avoid non-specific protein interactions on array supports and to monitor low-abundance molecules. The data accumulated indicate that this emerging technology is perfectly suited to resolve networks of protein interactions involved in complex physiological and pathological phenomena in different organisms and to develop sensitive tools for biomedical applications.

  6. Website Review: Protein-Protein Interactions on the Web

    PubMed Central

    Wixon, Jo

    2001-01-01

    We present a brief guide to resources on the Internet relating to Protein-Protein Interactions. These include databases containing experimentally verified and computationally inferred physical and functional interactions. There are also tools for predicting interactions and for extracting information on interactions from the literature, and organism specific databases. PMID:18629244

  7. 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

  8. 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.

  9. 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.

  10. 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.

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

    PubMed Central

    2011-01-01

    Background Protein complexes can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of protein complexes detection algorithms. Methods We have developed novel semantic similarity method, which use Gene Ontology (GO) annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. Following the approach of that of the previously proposed clustering algorithm IPCA which expands clusters starting from seeded vertices, we present a clustering algorithm OIIP based on the new weighted Protein-Protein interaction networks for identifying protein complexes. Results The algorithm OIIP is applied to the protein interaction network of Sacchromyces cerevisiae and identifies many well known complexes. Experimental results show that the algorithm OIIP has higher F-measure and accuracy compared to other competing approaches. PMID:22165991

  12. The protein interaction map of bacteriophage lambda

    PubMed Central

    2011-01-01

    Background Bacteriophage lambda is a model phage for most other dsDNA phages and has been studied for over 60 years. Although it is probably the best-characterized phage there are still about 20 poorly understood open reading frames in its 48-kb genome. For a complete understanding we need to know all interactions among its proteins. We have manually curated the lambda literature and compiled a total of 33 interactions that have been found among lambda proteins. We set out to find out how many protein-protein interactions remain to be found in this phage. Results In order to map lambda's interactions, we have cloned 68 out of 73 lambda open reading frames (the "ORFeome") into Gateway vectors and systematically tested all proteins for interactions using exhaustive array-based yeast two-hybrid screens. These screens identified 97 interactions. We found 16 out of 30 previously published interactions (53%). We have also found at least 18 new plausible interactions among functionally related proteins. All previously found and new interactions are combined into structural and network models of phage lambda. Conclusions Phage lambda serves as a benchmark for future studies of protein interactions among phage, viruses in general, or large protein assemblies. We conclude that we could not find all the known interactions because they require chaperones, post-translational modifications, or multiple proteins for their interactions. The lambda protein network connects 12 proteins of unknown function with well characterized proteins, which should shed light on the functional associations of these uncharacterized proteins. PMID:21943085

  13. 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

  14. Molecular simulations of lipid-mediated protein-protein interactions.

    PubMed

    de Meyer, Frédérick Jean-Marie; Venturoli, Maddalena; Smit, Berend

    2008-08-01

    Recent experimental results revealed that lipid-mediated interactions due to hydrophobic forces may be important in determining the protein topology after insertion in the membrane, in regulating the protein activity, in protein aggregation and in signal transduction. To gain insight into the lipid-mediated interactions between two intrinsic membrane proteins, we developed a mesoscopic model of a lipid bilayer with embedded proteins, which we studied with dissipative particle dynamics. Our calculations of the potential of mean force between transmembrane proteins show that hydrophobic forces drive long-range protein-protein interactions and that the nature of these interactions depends on the length of the protein hydrophobic segment, on the three-dimensional structure of the protein and on the properties of the lipid bilayer. To understand the nature of the computed potentials of mean force, the concept of hydrophilic shielding is introduced. The observed protein interactions are interpreted as resulting from the dynamic reorganization of the system to maintain an optimal hydrophilic shielding of the protein and lipid hydrophobic parts, within the constraint of the flexibility of the components. Our results could lead to a better understanding of several membrane processes in which protein interactions are involved. PMID:18487292

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

    PubMed

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

    2015-01-01

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

  16. Hemoglobin interacting proteins and implications of spectrin hemoglobin interaction.

    PubMed

    Basu, Avik; Chakrabarti, Abhijit

    2015-10-14

    In this report we have analyzed interacting partners of hemoglobin inside erythrocyte and sought possible implications of hemoglobin-spectrin interaction. Our list of identified cytosolic hemoglobin interacting proteins includes redox regulators like peroxiredoxin-2, Cu-Zn superoxide dismutase, catalase, aldehyde dehydrogenase-1, flavin reductase and chaperones like HSP70, α-hemoglobin stabilizing protein. Others include metabolic enzymes like carbonic anhydrase-1, selenium binding protein-1, purine nucleoside phosphorylase and nucleoside diphosphate kinase. Additionally, various membrane proteins like α and β spectrin, ankyrin, band3, protein4.1, actin and glyceraldehyde 3 phosphate dehydrogenase have been shown to interact with hemoglobin. Our result indicates that major membrane skeleton protein spectrin, that also has a chaperone like activity, helps to fold the unstable alpha-globin chains in vitro. Taken together our results could provide insight into a protein network evolved around hemoglobin molecule inside erythrocyte that may add a new perspective in understanding the hemoglobin function and homeostasis.

  17. 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)

  18. 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

  19. Use of protein-protein interactions in affinity chromatography.

    PubMed

    Muronetz, V I; Sholukh, M; Korpela, T

    2001-10-30

    Biospecific recognition between proteins is a phenomenon that can be exploited for designing affinity-chromatographic purification systems for proteins. In principle, the approach is straightforward, and there are usually many alternative ways, since a protein can be always found which binds specifically enough to the desired protein. Routine immunoaffinity chromatography utilizes the recognition of antigenic epitopes by antibodies. However, forces involved in protein-protein interactions as well the forces keeping the three-dimensional structures of proteins intact are complicated, and proteins are easily unfolded by various factors with unpredictable results. Because of this and because of the generally high association strength between proteins, the correct adjustment of binding forces between an immobilized protein and the protein to be purified as well as the release of bound proteins in biologically active form from affinity complexes are the main problem. Affinity systems involving interactions like enzyme-enzyme, subunit-oligomer, protein-antibody, protein-chaperone and the specific features involved in each case are presented as examples. This article also aims to sketch prospects for further development of the use of protein-protein interactions for the purification of proteins. PMID:11694271

  20. NOXclass: prediction of protein-protein interaction types

    PubMed Central

    Zhu, Hongbo; Domingues, Francisco S; Sommer, lngolf; Lengauer, Thomas

    2006-01-01

    Background Structural models determined by X-ray crystallography play a central role in understanding protein-protein interactions at the molecular level. Interpretation of these models requires the distinction between non-specific crystal packing contacts and biologically relevant interactions. This has been investigated previously and classification approaches have been proposed. However, less attention has been devoted to distinguishing different types of biological interactions. These interactions are classified as obligate and non-obligate according to the effect of the complex formation on the stability of the protomers. So far no automatic classification methods for distinguishing obligate, non-obligate and crystal packing interactions have been made available. Results Six interface properties have been investigated on a dataset of 243 protein interactions. The six properties have been combined using a support vector machine algorithm, resulting in NOXclass, a classifier for distinguishing obligate, non-obligate and crystal packing interactions. We achieve an accuracy of 91.8% for the classification of these three types of interactions using a leave-one-out cross-validation procedure. Conclusion NOXclass allows the interpretation and analysis of protein quaternary structures. In particular, it generates testable hypotheses regarding the nature of protein-protein interactions, when experimental results are not available. We expect this server will benefit the users of protein structural models, as well as protein crystallographers and NMR spectroscopists. A web server based on the method and the datasets used in this study are available at . PMID:16423290

  1. 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.

  2. 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

  3. 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

  4. 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…

  5. Analysis of Stable and Transient Protein-Protein Interactions

    PubMed Central

    Byrum, Stephanie; Smart, Sherri K.; Larson, Signe; Tackett, Alan J.

    2012-01-01

    The assembly of proteins into defined complexes drives a plethora of cellular activities. These protein complexes often have a set of more stably interacting proteins as well as more unstable or transient interactions. Studying the in vivo components of these protein complexes is challenging as many of the techniques used for isolation result in the purification of only the most stable components and the transient interactions are lost. A technology called transient isotopic differentiation of interactions as random or targeted (transient I-DIRT) has been developed to identify these transiently interacting proteins as well as the stable interactions. Described here are the detailed methodological approaches used for a transient I-DIRT analysis of a multi-subunit complex, NuA3, that acetylates histone H3 and functions to activate gene transcription. Transcription is known to involve a concert of protein assemblies performing different activities on the chromatin/gene template, thus understanding the less stable or transient protein interactions with NuA3 will shed light onto the protein complexes that function synergistically, or antagonistically, to regulate gene transcription and chromatin remodeling. PMID:22183593

  6. 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.

  7. 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)

  8. Optimization of the electrostatic interactions in protein-protein complexes

    NASA Astrophysics Data System (ADS)

    Alexov, Emil; Brock, Kelly; Kundrotas, Petras

    2007-03-01

    Electrostatic energy is one of the driving forces of protein-protein association. Understanding the role of the energy components on the energetics of protein-protein association will help us in engineering protein-protein interactions and could lead to development of scoring functions that can rank alternative models and decoys. Here we investigate whether the components of the electrostatic energy of protein-protein complexes is optimized in respect to random distribution of the charged residues. We report a clear tendency that coulombic electrostatic interactions are optimized, while the reaction field energy is inversely optimized. It was found that the maximum of the coulombic energy Z-score is shifted 3 units away from the origin and the maximum of the reaction field energy by 2 units. Such a large shift of the Z-score of both coulombic and reaction field energies indicates that wild-type protein-protein interactions are in most cases optimized in terms of coulombic interactions while compromising reaction field energy. Based on these finding a scoring function was developed as a linear combination of the Z-score of the coulombic interactions minus Z-score of the reaction field energy. The scoring function was tested against the decoy sets and it was shown that in majority of the cases we can identify the wild-type complex among hundreds of decoys.

  9. Protein-protein interaction networks (PPI) and complex diseases

    PubMed Central

    Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Rezaei-Tavirani, Mostafa; Goliaei, Bahram

    2014-01-01

    The physical interaction of proteins which lead to compiling them into large densely connected networks is a noticeable subject to investigation. Protein interaction networks are useful because of making basic scientific abstraction and improving biological and biomedical applications. Based on principle roles of proteins in biological function, their interactions determine molecular and cellular mechanisms, which control healthy and diseased states in organisms. Therefore, such networks facilitate the understanding of pathogenic (and physiologic) mechanisms that trigger the onset and progression of diseases. Consequently, this knowledge can be translated into effective diagnostic and therapeutic strategies. Furthermore, the results of several studies have proved that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer and autoimmune disorders. Based on such relationship, a novel paradigm is suggested in order to confirm that the protein interaction networks can be the target of therapy for treatment of complex multi-genic diseases rather than individual molecules with disrespect the network. PMID:25436094

  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. Quantitative interaction proteomics of neurodegenerative disease proteins.

    PubMed

    Hosp, Fabian; Vossfeldt, Hannes; Heinig, Matthias; Vasiljevic, Djordje; Arumughan, Anup; Wyler, Emanuel; Landthaler, Markus; Hubner, Norbert; Wanker, Erich E; Lannfelt, Lars; Ingelsson, Martin; Lalowski, Maciej; Voigt, Aaron; Selbach, Matthias

    2015-05-19

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

  12. How Hofmeister ion interactions affect protein stability.

    PubMed Central

    Baldwin, R L

    1996-01-01

    Model compound studies in the literature show how Hofmeister ion interactions affect protein stability. Although model compound results are typically obtained as salting-out constants, they can be used to find out how the interactions affect protein stability. The null point in the Hofmeister series, which divides protein denaturants from stabilizers, arises from opposite interactions with different classes of groups: Hofmeister ions salt out nonpolar groups and salt in the peptide group. Theories of how Hofmeister ion interactions work need to begin by explaining the mechanisms of these two classes of interactions. Salting-out nonpolar groups has been explained by the cavity model, but its use is controversial. When applied to model compound data, the cavity model 1) uses surface tension increments to predict the observed values of the salting-out constants, within a factor of 3, and 2) predicts that the salting-out constant should increase with the number of carbon atoms in the aliphatic side chain of an amino acid, as observed. The mechanism of interaction between Hofmeister ions and the peptide group is not well understood, and it is controversial whether this interaction is ion-specific, or whether it is nonspecific and the apparent specificity resides in interactions with nearby nonpolar groups. A nonspecific salting-in interaction is known to occur between simple ions and dipolar molecules; it depends on ionic strength, not on position in the Hofmeister series. A theory by Kirkwood predicts the strength of this interaction and indicates that it depends on the first power of the ionic strength. Ions interact with proteins in various ways besides the Hofmeister ion interactions discussed here, especially by charge interactions. Much of what is known about these interactions comes from studies by Serge Timasheff and his co-workers. A general model, suitable for analyzing diverse ion-protein interactions, is provided by the two-domain model of Record and co

  13. Signature Product Code for Predicting Protein-Protein Interactions

    SciTech Connect

    Martin, Shawn B.; Brown, William M.

    2004-09-25

    The SigProdV1.0 software consists of four programs which together allow the prediction of protein-protein interactions using only amino acid sequences and experimental data. The software is based on the use of tensor products of amino acid trimers coupled with classifiers known as support vector machines. Essentially the program looks for amino acid trimer pairs which occur more frequently in protein pairs which are known to interact. These trimer pairs are then used to make predictions about unknown protein pairs. A detailed description of the method can be found in the paper: S. Martin, D. Roe, J.L. Faulon. "Predicting protein-protein interactions using signature products," Bioinformatics, available online from Advance Access, Aug. 19, 2004.

  14. Signature Product Code for Predicting Protein-Protein Interactions

    2004-09-25

    The SigProdV1.0 software consists of four programs which together allow the prediction of protein-protein interactions using only amino acid sequences and experimental data. The software is based on the use of tensor products of amino acid trimers coupled with classifiers known as support vector machines. Essentially the program looks for amino acid trimer pairs which occur more frequently in protein pairs which are known to interact. These trimer pairs are then used to make predictionsmore » about unknown protein pairs. A detailed description of the method can be found in the paper: S. Martin, D. Roe, J.L. Faulon. "Predicting protein-protein interactions using signature products," Bioinformatics, available online from Advance Access, Aug. 19, 2004.« less

  15. Yeast protein-protein interaction assays and screens.

    PubMed

    de Folter, Stefan; Immink, Richard G H

    2011-01-01

    Most transcription factors fulfill their role in protein complexes. As a consequence, information about their interaction capacity sheds light on a protein's function and the molecular mechanism underlying this activity. The yeast two-hybrid GAL4 (Y2H) assay is a powerful method to unravel and identify the composition of protein complexes. This in vivo based system makes use of two functional protein domains of the GAL4 transcription factor, each fused to a protein of interest. Upon interaction between the two proteins under study, a transcriptional activator gets reconstituted and reporter genes get activated, allowing the yeast to grow on selective medium. In this chapter protocols are given for Y2H library screening, directed Y2H screening, Y2H matrix screening, and YnH screening involving more than two proteins. PMID:21720951

  16. 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. PMID:20129649

  17. 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

  18. 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.

  19. 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.

  20. RNA Protein Interaction in Neurons

    PubMed Central

    Darnell, Robert B.

    2013-01-01

    Neurons have their own systems for regulating RNA. Several multigene families encode RNA binding proteins (RNABPs) that are uniquely expressed in neurons, including the well-known neuron-specific markers ELAV and NeuN, and the disease antigen NOVA. New technologies have emerged in recent years to assess the function of these proteins in vivo, and the answers are yielding insights into how and why neurons may regulate RNA in special ways—to increase cellular complexity, to spatially localize mRNA, and to regulate their expression in response to synaptic stimuli. The functions of such restricted neuronal proteins is likely to be complimented by more widely expressed RNABPs that may themselves have developed specialized functions in neurons, including Argonaute/miRNAs. Here we review what is known about such RNABPs, and explore the potential biologic and neurologic significance of neuronal RNA regulatory systems. PMID:23701460

  1. Characterizing carbohydrate-protein interactions by NMR

    PubMed Central

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

    2013-01-01

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

  2. Embryonic stem cells: protein interaction networks*

    PubMed Central

    Ng, Patricia Miang-Lon; Lufkin, Thomas

    2012-01-01

    Embryonic stem cells have the ability to differentiate into nearly all cell types. However, the molecular mechanism of its pluripotency is still unclear. Oct3/4, Sox2 and Nanog are important factors of pluripotency. Oct3/4 (hereafter referred to as Oct4), in particular, has been an irreplaceable factor in the induction of pluripotency in adult cells. Proteins interacting with Oct4 and Nanog have been identified via affinity purification and mass spectrometry. These data, together with iterative purifications of interacting proteins allowed a protein interaction network to be constructed. The network currently includes 77 transcription factors, all of which are interconnected in one network. In-depth studies of some of these transcription factors show that they all recruit the NuRD complex. Hence, transcription factor clustering and chromosomal remodeling are key mechanism used by embryonic stem cells. Studies using RNA interference suggest that more pluripotency genes are yet to be discovered via protein-protein interactions. More work is required to complete and curate the embryonic stem cell protein interaction network. Analysis of a saturated protein interaction network by system biology tools can greatly aid in the understanding of the embryonic stem cell pluripotency network. PMID:22639699

  3. 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).

  4. 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.

  5. Interaction proteomics of synapse protein complexes

    PubMed Central

    Klemmer, Patricia; Smit, August B.

    2010-01-01

    The brain integrates complex types of information, and executes a wide range of physiological and behavioral processes. Trillions of tiny organelles, the synapses, are central to neuronal communication and information processing in the brain. Synaptic transmission involves an intricate network of synaptic proteins that forms the molecular machinery underlying transmitter release, activation, and modulation of transmitter receptors and signal transduction cascades. These processes are dynamically regulated and underlie neuroplasticity, crucial to learning and memory formation. In recent years, interaction proteomics has increasingly been used to elucidate the constituents of synaptic protein complexes. Unlike classic hypothesis-based assays, interaction proteomics detects both known and novel interactors without bias. In this trend article, we focus on the technical aspects of recent proteomics to identify synapse protein complexes, and the complementary methods used to verify the protein–protein interaction. Moreover, we discuss the experimental feasibility of performing global analysis of the synapse protein interactome. PMID:20361179

  6. TSEMA: interactive prediction of protein pairings between interacting families.

    PubMed

    Izarzugaza, José M G; Juan, David; Pons, Carles; Ranea, Juan A G; Valencia, Alfonso; Pazos, Florencio

    2006-07-01

    An entire family of methodologies for predicting protein interactions is based on the observed fact that families of interacting proteins tend to have similar phylogenetic trees due to co-evolution. One application of this concept is the prediction of the mapping between the members of two interacting protein families (which protein within one family interacts with which protein within the other). The idea is that the real mapping would be the one maximizing the similarity between the trees. Since the exhaustive exploration of all possible mappings is not feasible for large families, current approaches use heuristic techniques which do not ensure the best solution to be found. This is why it is important to check the results proposed by heuristic techniques and to manually explore other solutions. Here we present TSEMA, the server for efficient mapping assessment. This system calculates an initial mapping between two families of proteins based on a Monte Carlo approach and allows the user to interactively modify it based on performance figures and/or specific biological knowledge. All the explored mappings are graphically shown over a representation of the phylogenetic trees. The system is freely available at http://pdg.cnb.uam.es/TSEMA. Standalone versions of the software behind the interface are available upon request from the authors.

  7. Ribosomal protein L7a is encoded by a gene (Surf-3) within the tightly clustered mouse surfeit locus.

    PubMed Central

    Giallongo, A; Yon, J; Fried, M

    1989-01-01

    The mouse Surfeit locus, which contains a cluster of at least four genes (Surf-1 to Surf-4), is unusual in that adjacent genes are separated by no more than 73 base pairs (bp). The heterogeneous 5' ends of Surf-1 and Surf-2 are separated by only 15 to 73 bp, the 3' ends of Surf-1 and Surf-3 are only 70 bp apart, and the 3' ends of Surf-2 and Surf-4 overlap by 133 bp. This very tight clustering suggests a cis interaction between adjacent Surfeit genes. The Surf-3 gene (which could code for a basic polypeptide of 266 amino acids) is a highly expressed member of a pseudogene-containing multigene family. By use of an anti-peptide serum (against the C-terminal nine amino acids of the putative Surf-3 protein) for immunofluorescence and immunoblotting of mouse cell components and by in vitro translation of Surf-3 cDNA hybrid-selected mRNA, the Surf-3 gene product was identified as a 32-kilodalton ribosomal protein located in the 60S ribosomal subunit. From its subunit location, gel migration, and homology with a limited rat ribosomal peptide sequence, the Surf-3 gene was shown to encode the mouse L7a ribosomal protein. The Surf-3 gene is highly conserved through evolution and was detected by nucleic acid hybridization as existing in multiple copies (multigene families) in other mammals and as one or a few copies in birds, Xenopus, Drosophila, and Schizosaccharomyces pombe. The Surf-3 C-terminal anti-peptide serum detects a 32-kilodalton protein in other mammals, birds, and Xenopus but not in Drosophila and S. pombe. The possible effect of interaction of the Surf-3 ribosomal protein gene with adjacent genes in the Surfeit locus at the transcriptional or posttranscriptional level or both levels is discussed. Images PMID:2648130

  8. 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.

  9. 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.

  10. 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…

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

    PubMed

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

    2014-09-01

    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.

  12. 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

  13. Non-interacting surface solvation and dynamics in protein-protein interactions.

    PubMed

    Visscher, Koen M; Kastritis, Panagiotis L; Bonvin, Alexandre M J J

    2015-03-01

    Protein-protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure-based drug design methods, as well as design of de novo binders with preferred interaction properties. At a structural and molecular level, interface and rim regions are not enough to fully account for the energetics of protein-protein binding, even for simple lock-and-key rigid binders. As we have recently shown, properties of the global surface might also play a role in protein-protein interactions. Here, we report on molecular dynamics simulations performed to understand solvent effects on protein-protein surfaces. We compare properties of the interface, rim, and non-interacting surface regions for five different complexes and their free components. Interface and rim residues become, as expected, less mobile upon complexation. However, non-interacting surface appears more flexible in the complex. Fluctuations of polar residues are always lower compared with charged ones, independent of the protein state. Further, stable water molecules are often observed around polar residues, in contrast to charged ones. Our analysis reveals that (a) upon complexation, the non-interacting surface can have a direct entropic compensation for the lower interface and rim entropy and (b) the mobility of the first hydration layer, which is linked to the stability of the protein-protein complex, is influenced by the local chemical properties of the surface. These findings corroborate previous hypotheses on the role of the hydration layer in shielding protein-protein complexes from unintended protein-protein interactions. PMID:25524313

  14. Proteomic analysis of SETD6 interacting proteins

    PubMed Central

    Cohn, Ofir; Chen, Ayelet; Feldman, Michal; Levy, Dan

    2016-01-01

    SETD6 (SET-domain-containing protein 6) is a mono-methyltransferase that has been shown to methylate RelA and H2AZ. Using a proteomic approach we recently identified several new SETD6 substrates. To identify novel SETD6 interacting proteins, SETD6 was immunoprecipitated (IP) from Human erythromyeloblastoid leukemia K562 cells. SETD6 binding proteins were subjected to mass-spectrometry analysis resulting in 115 new SETD6 binding candidates. STRING database was used to map the SETD6 interactome network. Network enrichment analysis of biological processes with Gene Ontology (GO) database, identified three major groups; metabolic processes, muscle contraction and protein folding. PMID:26937450

  15. Water-protein interactions from high-resolution protein crystallography.

    PubMed Central

    Nakasako, Masayoshi

    2004-01-01

    To understand the role of water in life at molecular and atomic levels, structures and interactions at the protein-water interface have been investigated by cryogenic X-ray crystallography. The method enabled a much clearer visualization of definite hydration sites on the protein surface than at ambient temperature. Using the structural models of proteins, including several hydration water molecules, the characteristics in hydration structures were systematically analysed for the amount, the interaction geometries between water molecules and proteins, and the local and global distribution of water molecules on the surface of proteins. The tetrahedral hydrogen-bond geometry of water molecules in bulk solvent was retained at the interface and enabled the extension of a three-dimensional chain connection of a hydrogen-bond network among hydration water molecules and polar protein atoms over the entire surface of proteins. Networks of hydrogen bonds were quite flexible to accommodate and/or to regulate the conformational changes of proteins such as domain motions. The present experimental results may have profound implications in the understanding of the physico-chemical principles governing the dynamics of proteins in an aqueous environment and a discussion of why water is essential to life at a molecular level. PMID:15306376

  16. 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).

  17. Karyoplasmic interaction selection strategy: a general strategy to detect protein-protein interactions in mammalian cells.

    PubMed Central

    Fearon, E R; Finkel, T; Gillison, M L; Kennedy, S P; Casella, J F; Tomaselli, G F; Morrow, J S; Van Dang, C

    1992-01-01

    We describe a strategy and reagents for study of protein-protein interactions in mammalian cells, termed the karyoplasmic interaction selection strategy (KISS). With this strategy, specific protein-protein interactions are identified by reconstitution of the functional activity of the yeast transcriptional activator GAL4 and the resultant transcription of a GAL4-regulated reporter gene. Reconstitution of GAL4 function results from specific interaction between two chimeric proteins: one contains the DNA-binding domain of GAL4; the other contains a transcriptional activation domain. Transcription of the reporter gene occurs if the two chimeric proteins can form a complex that reconstitutes the DNA-binding and transcriptional activation functions of GAL4. Using the KISS system, we demonstrate specific interactions for sequences from three different pairs of proteins that complex in the cytoplasm. In addition, we demonstrate that reporter genes encoding cell surface or drug-resistance markers can be specifically activated as a result of protein-protein interactions. With these selectable markers, the KISS system can be used to screen specialized cDNA libraries to identify novel protein interactions. Images PMID:1387709

  18. 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.

  19. Predicting protein-protein interactions in the post synaptic density.

    PubMed

    Bar-shira, Ossnat; Chechik, Gal

    2013-09-01

    The post synaptic density (PSD) is a specialization of the cytoskeleton at the synaptic junction, composed of hundreds of different proteins. Characterizing the protein components of the PSD and their interactions can help elucidate the mechanism of long-term changes in synaptic plasticity, which underlie learning and memory. Unfortunately, our knowledge of the proteome and interactome of the PSD is still partial and noisy. In this study we describe a computational framework to improve the reconstruction of the PSD network. The approach is based on learning the characteristics of PSD protein interactions from a set of trusted interactions, expanding this set with data collected from large scale repositories, and then predicting novel interaction with proteins that are suspected to reside in the PSD. Using this method we obtained thirty predicted interactions, with more than half of which having supporting evidence in the literature. We discuss in details two of these new interactions, Lrrtm1 with PSD-95 and Src with Capg. The first may take part in a mechanism underlying glutamatergic dysfunction in schizophrenia. The second suggests an alternative mechanism to regulate dendritic spines maturation.

  20. The Lumenal Loop M672-P707 of the Menkes Protein (ATP7A) Transfers Copper to Peptidylglycine Monooxygenase

    PubMed Central

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

    2012-01-01

    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. PMID:22577880

  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. Side-Chain Conformational Preferences Govern Protein-Protein Interactions.

    PubMed

    Watkins, Andrew M; Bonneau, Richard; Arora, Paramjit S

    2016-08-24

    Protein secondary structures serve as geometrically constrained scaffolds for the display of key interacting residues at protein interfaces. Given the critical role of secondary structures in protein folding and the dependence of folding propensities on backbone dihedrals, secondary structure is expected to influence the identity of residues that are important for complex formation. Counter to this expectation, we find that a narrow set of residues dominates the binding energy in protein-protein complexes independent of backbone conformation. This finding suggests that the binding epitope may instead be substantially influenced by the side-chain conformations adopted. We analyzed side-chain conformational preferences in residues that contribute significantly to binding. This analysis suggests that preferred rotamers contribute directly to specificity in protein complex formation and provides guidelines for peptidomimetic inhibitor design.

  3. 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.

  4. 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

  5. [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.

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

    PubMed

    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

    2011-07-01

    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

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

    PubMed

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

    2016-06-14

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

  8. 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.

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

    PubMed

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

    2016-07-01

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

  10. Interaction Energy Based Protein Structure Networks

    PubMed Central

    Vijayabaskar, M.S.; Vishveshwara, Saraswathi

    2010-01-01

    The three-dimensional structure of a protein is formed and maintained by the noncovalent interactions among the amino-acid residues of the polypeptide chain. These interactions can be represented collectively in the form of a network. So far, such networks have been investigated by considering the connections based on distances between the amino-acid residues. Here we present a method of constructing the structure network based on interaction energies among the amino-acid residues in the protein. We have investigated the properties of such protein energy-based networks (PENs) and have shown correlations to protein structural features such as the clusters of residues involved in stability, formation of secondary and super-secondary structural units. Further we demonstrate that the analysis of PENs in terms of parameters such as hubs and shortest paths can provide a variety of biologically important information, such as the residues crucial for stabilizing the folded units and the paths of communication between distal residues in the protein. Finally, the energy regimes for different levels of stabilization in the protein structure have clearly emerged from the PEN analysis. PMID:21112295

  11. 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

  12. Dynamic interactions of proteins in complex networks

    SciTech Connect

    Appella, E.; Anderson, C.

    2009-10-01

    Recent advances in techniques such as NMR and EPR spectroscopy have enabled the elucidation of how proteins undergo structural changes to act in concert in complex networks. The three minireviews in this series highlight current findings and the capabilities of new methodologies for unraveling the dynamic changes controlling diverse cellular functions. They represent a sampling of the cutting-edge research presented at the 17th Meeting of Methods in Protein Structure Analysis, MPSA2008, in Sapporo, Japan, 26-29 August, 2008 (http://www.iapsap.bnl.gov). The first minireview, by Christensen and Klevit, reports on a structure-based yeast two-hybrid method for identifying E2 ubiquitin-conjugating enzymes that interact with the E3 BRCA1/BARD1 heterodimer ligase to generate either mono- or polyubiquitinated products. This method demonstrated for the first time that the BRCA1/BARD1 E3 can interact with 10 different E2 enzymes. Interestingly, the interaction with multiple E2 enzymes displayed unique ubiquitin-transfer properties, a feature expected to be common among other RING and U-box E3s. Further characterization of new E3 ligases and the E2 enzymes that interact with them will greatly enhance our understanding of ubiquitin transfer and facilitate studies of roles of ubiquitin and ubiquitin-like proteins in protein processing and trafficking. Stein et al., in the second minireview, describe recent progress in defining the binding specificity of different peptide-binding domains. The authors clearly point out that transient peptide interactions mediated by both post-translational modifications and disordered regions ensure a high level of specificity. They postulate that a regulatory code may dictate the number of combinations of domains and post-translational modifications needed to achieve the required level of interaction specificity. Moreover, recognition alone is not enough to obtain a stable complex, especially in a complex cellular environment. Increasing

  13. Docking and scoring protein interactions: CAPRI 2009.

    PubMed

    Lensink, Marc F; Wodak, Shoshana J

    2010-11-15

    Protein docking algorithms are assessed by evaluating blind predictions performed during 2007-2009 in Rounds 13-19 of the community-wide experiment on critical assessment of predicted interactions (CAPRI). We evaluated the ability of these algorithms to sample docking poses and to single out specific association modes in 14 targets, representing 11 distinct protein complexes. These complexes play important biological roles in RNA maturation, G-protein signal processing, and enzyme inhibition and function. One target involved protein-RNA interactions not previously considered in CAPRI, several others were hetero-oligomers, or featured multiple interfaces between the same protein pair. For most targets, predictions started from the experimentally determined structures of the free (unbound) components, or from models built from known structures of related or similar proteins. To succeed they therefore needed to account for conformational changes and model inaccuracies. In total, 64 groups and 12 web-servers submitted docking predictions of which 4420 were evaluated. Overall our assessment reveals that 67% of the groups, more than ever before, produced acceptable models or better for at least one target, with many groups submitting multiple high- and medium-accuracy models for two to six targets. Forty-one groups including four web-servers participated in the scoring experiment with 1296 evaluated models. Scoring predictions also show signs of progress evidenced from the large proportion of correct models submitted. But singling out the best models remains a challenge, which also adversely affects the ability to correctly rank docking models. With the increased interest in translating abstract protein interaction networks into realistic models of protein assemblies, the growing CAPRI community is actively developing more efficient and reliable docking and scoring methods for everyone to use.

  14. 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

    2007-01-01

    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. PMID:18058715

  15. 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

  16. A single nucleotide polymorphism in the 3'-untranslated region of the KRAS gene disrupts the interaction with let-7a and enhances the metastatic potential of osteosarcoma cells.

    PubMed

    Zhang, Shiqian; Hou, Chunying; Li, Guojun; Zhong, Yang; Zhang, Jie; Guo, Xinzhen; Li, Baoxin; Bi, Zhenggang; Shao, Ming

    2016-09-01

    The objective of the present study was to explore the molecular mechanism with which a single nucleotide polymorphism (rs61764370) interferes with the interaction between the 3'-untranslated region (3'-UTR) of Kirsten rat sarcoma viral oncogene homolog (KRAS) and let-7a, and its association with the metastasis of osteosarcoma (OS). In this study, we confirmed that KRAS is a target of let-7a in OS cells, and the introduction of rs61764370 minor allele into KRAS 3'-UTR significantly compromised the microRNA (miRNA)/mRNA interaction using a luciferase reporter system. Additionally, a total of 36 OS tissue samples of three different genotypes (TT,22; TG,10; GG,4) were obtained, and the expression of let-7a and KRAS was determined. We showed that let-7a mRNA expression was similar between each group whereas the mRNA and protein expression of KRAS in the TT genotype group was significantly lower than that in the GT or GG genotype groups. Moreover, we identified a negative regulatory relationship between let-7a and KRAS. Furthermore, we demonstrated that let-7a and KRAS interfered with the viability, invasiveness and migration of OS cells genotyped as TT. In the OS cells genotyped as TG, let-7a exerted minimal effects, and the effect of KRAS siRNA remained. Taken together, the findings of the present study demonstrated that the KRAS 3'-UTR rs61764370 polymorphism interfered with miRNA/mRNA interaction, and showed that the minor allele was associated with an elevated risk of developing metastatic disease in OS. PMID:27430246

  17. 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.

  18. 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.

  19. Pooled screening for antiproliferative inhibitors of protein-protein interactions.

    PubMed

    Nim, Satra; Jeon, Jouhyun; Corbi-Verge, Carles; Seo, Moon-Hyeong; Ivarsson, Ylva; Moffat, Jason; Tarasova, Nadya; Kim, Philip M

    2016-04-01

    Protein-protein interactions (PPIs) are emerging as a promising new class of drug targets. Here, we present a novel high-throughput approach to screen inhibitors of PPIs in cells. We designed a library of 50,000 human peptide-binding motifs and used a pooled lentiviral system to express them intracellularly and screen for their effects on cell proliferation. We thereby identified inhibitors that drastically reduced the viability of a pancreatic cancer line (RWP1) while leaving a control line virtually unaffected. We identified their target interactions computationally, and validated a subset in experiments. We also discovered their potential mechanisms of action, including apoptosis and cell cycle arrest. Finally, we confirmed that synthetic lipopeptide versions of our inhibitors have similarly specific and dosage-dependent effects on cancer cell growth. Our screen reveals new drug targets and peptide drug leads, and it provides a rich data set covering phenotypes for the inhibition of thousands of interactions. PMID:26900867

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

    PubMed Central

    Wang, Yijie; Qian, Xiaoning

    2014-01-01

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

  1. Pairwise alignment of protein interaction networks.

    PubMed

    Koyutürk, Mehmet; Kim, Yohan; Topkara, Umut; Subramaniam, Shankar; Szpankowski, Wojciech; Grama, Ananth

    2006-03-01

    With an ever-increasing amount of available data on protein-protein interaction (PPI) networks and research revealing that these networks evolve at a modular level, discovery of conserved patterns in these networks becomes an important problem. Although available data on protein-protein interactions is currently limited, recently developed algorithms have been shown to convey novel biological insights through employment of elegant mathematical models. The main challenge in aligning PPI networks is to define a graph theoretical measure of similarity between graph structures that captures underlying biological phenomena accurately. In this respect, modeling of conservation and divergence of interactions, as well as the interpretation of resulting alignments, are important design parameters. In this paper, we develop a framework for comprehensive alignment of PPI networks, which is inspired by duplication/divergence models that focus on understanding the evolution of protein interactions. We propose a mathematical model that extends the concepts of match, mismatch, and gap in sequence alignment to that of match, mismatch, and duplication in network alignment and evaluates similarity between graph structures through a scoring function that accounts for evolutionary events. By relying on evolutionary models, the proposed framework facilitates interpretation of resulting alignments in terms of not only conservation but also divergence of modularity in PPI networks. Furthermore, as in the case of sequence alignment, our model allows flexibility in adjusting parameters to quantify underlying evolutionary relationships. Based on the proposed model, we formulate PPI network alignment as an optimization problem and present fast algorithms to solve this problem. Detailed experimental results from an implementation of the proposed framework show that our algorithm is able to discover conserved interaction patterns very effectively, in terms of both accuracies and computational

  2. A Tool for Interactive Protein Manipulation

    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 visualizationmore » 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« less

  3. Nucleosome assembly proteins and their interacting proteins in neuronal differentiation.

    PubMed

    Attia, Mikaël; Rachez, Christophe; Avner, Philip; Rogner, Ute Christine

    2013-06-01

    Neuronal differentiation from neural stem cells into mature neurons is guided by the concerted action of specific transcription factors that stepwise exercise their role in the context of defined chromatin states. Amongst the classes of proteins that influence chromatin compaction and modification are nucleosome assembly proteins (NAPs). Mammals possess several nucleosome assembly protein 1 like proteins (NAP1L) that show either ubiquitous or neuron-restricted expression. The latter group is presumably involved in the process of neuronal differentiation. Mammalian NAP1Ls can potentially form both homo- and hetero-dimers and octamers, in theory allowing thousands of different combinations to be formed. Detailed studies have been performed on several of the NAP1Ls that point to a range of molecular roles, including transcriptional regulation, nuclear import, and control of cell division. This article aims at summarizing current knowledge of the mammalian NAP1L family and its interactions.

  4. Tools for controlling protein interactions using light.

    PubMed

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

    2014-01-01

    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.

  5. 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

  6. How Structure Defines Affinity in Protein-Protein Interactions

    PubMed Central

    Erijman, Ariel; Rosenthal, Eran; Shifman, Julia M.

    2014-01-01

    Protein-protein interactions (PPI) in nature are conveyed by a multitude of binding modes involving various surfaces, secondary structure elements and intermolecular interactions. This diversity results in PPI binding affinities that span more than nine orders of magnitude. Several early studies attempted to correlate PPI binding affinities to various structure-derived features with limited success. The growing number of high-resolution structures, the appearance of more precise methods for measuring binding affinities and the development of new computational algorithms enable more thorough investigations in this direction. Here, we use a large dataset of PPI structures with the documented binding affinities to calculate a number of structure-based features that could potentially define binding energetics. We explore how well each calculated biophysical feature alone correlates with binding affinity and determine the features that could be used to distinguish between high-, medium- and low- affinity PPIs. Furthermore, we test how various combinations of features could be applied to predict binding affinity and observe a slow improvement in correlation as more features are incorporated into the equation. In addition, we observe a considerable improvement in predictions if we exclude from our analysis low-resolution and NMR structures, revealing the importance of capturing exact intermolecular interactions in our calculations. Our analysis should facilitate prediction of new interactions on the genome scale, better characterization of signaling networks and design of novel binding partners for various target proteins. PMID:25329579

  7. 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

  8. 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.

  9. The interactions of peripheral membrane proteins with biological membranes

    DOE PAGESBeta

    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

  10. The interactions of peripheral membrane proteins with biological membranes.

    PubMed

    Whited, A M; Johs, A

    2015-11-01

    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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Automated nanoscale flow cytometry for assessing protein-protein interactions.

    PubMed

    von Kolontaj, Kerstin; Horvath, Gabor L; Latz, Eicke; Büscher, Martin

    2016-09-01

    Despite their importance for signalling events, protein-protein interactions cannot easily be analyzed on a single cell level. We developed a robust automated FRET measurement system implemented on a commercial flow cytometer allowing for rapid profiling of molecular associations in living cells. We used this method to measure the most proximal signaling events on human T lymphocyte activation, which preceded calcium influx, and could automatically detect T cell receptor/CD3 complex clustering defects in immunocompromised patients. © 2016 International Society for Advancement of Cytometry. PMID:27584593

  17. Transferring network topological knowledge for predicting protein-protein interactions.

    PubMed

    Xu, Qian; Xiang, Evan Wei; Yang, Qiang

    2011-10-01

    Protein-protein interactions (PPIs) play an important role in cellular processes within a cell. An important task is to determine the existence of interactions among proteins. Unfortunately, the existing biological experimental techniques are expensive, time-consuming and labor-intensive. The network structures of many such networks are sparse, incomplete and noisy. Thus, state-of-the-art methods for link prediction in these networks often cannot give satisfactory prediction results, especially when some networks are extremely sparse. Noticing that we typically have more than one PPI network available, we naturally wonder whether it is possible to 'transfer' the linkage knowledge from some existing, relatively dense networks to a sparse network, to improve the prediction performance. Noticing that a network structure can be modeled using a matrix model, we introduce the well-known collective matrix factorization technique to 'transfer' usable linkage knowledge from relatively dense interaction network to a sparse target network. Our approach is to establish a correspondence between a source network and a target network via network-wide similarities. We test this method on two real PPI networks, Helicobacter pylori (as a target network) and human (as a source network). Our experimental results show that our method can achieve higher performance as compared with some baseline methods. PMID:21770035

  18. Schizophrenia interactome with 504 novel protein-protein interactions.

    PubMed

    Ganapathiraju, Madhavi K; Thahir, Mohamed; Handen, Adam; Sarkar, Saumendra N; Sweet, Robert A; Nimgaonkar, Vishwajit L; Loscher, Christine E; Bauer, Eileen M; Chaparala, Srilakshmi

    2016-01-01

    Genome-wide association studies of schizophrenia (GWAS) have revealed the role of rare and common genetic variants, but the functional effects of the risk variants remain to be understood. Protein interactome-based studies can facilitate the study of molecular mechanisms by which the risk genes relate to schizophrenia (SZ) genesis, but protein-protein interactions (PPIs) are unknown for many of the liability genes. We developed a computational model to discover PPIs, which is found to be highly accurate according to computational evaluations and experimental validations of selected PPIs. We present here, 365 novel PPIs of liability genes identified by the SZ Working Group of the Psychiatric Genomics Consortium (PGC). Seventeen genes that had no previously known interactions have 57 novel interactions by our method. Among the new interactors are 19 drug targets that are targeted by 130 drugs. In addition, we computed 147 novel PPIs of 25 candidate genes investigated in the pre-GWAS era. While there is little overlap between the GWAS genes and the pre-GWAS genes, the interactomes reveal that they largely belong to the same pathways, thus reconciling the apparent disparities between the GWAS and prior gene association studies. The interactome including 504 novel PPIs overall, could motivate other systems biology studies and trials with repurposed drugs. The PPIs are made available on a webserver, called Schizo-Pi at http://severus.dbmi.pitt.edu/schizo-pi with advanced search capabilities. PMID:27336055

  19. Notable Aspects of Glycan-Protein Interactions.

    PubMed

    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

  20. 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

  1. NMR studies of protein-ligand interactions.

    PubMed

    Maurer, Till

    2005-01-01

    Interaction between biological macromolecules or of macromolecules with low-molecular-weight ligands is a central paradigm in the understanding of function in biological systems. It is also the major goal in pharmaceutical research to find and optimize ligands that modulate the function of biological macromolecules. Both technological advances and new methods in the field of nuclear magnetic resonance (NMR) have led to the development of several tools by which the interaction of proteins or DNA and low molecular weight-ligands can be characterized at an atomic level. Information can be gained quickly and easily with ligand-based techniques. These need only small amounts of nonisotope labeled, and thus readily available target macromolecules. As the focus is on the signals stemming only from the ligand, no further NMR information regarding the target is needed. Techniques based on the observation of isotopically labeled biological macromolecules open the possibility to observe interactions of proteins with low-molecular-weight ligands, DNA or other proteins. With these techniques, the structure of high-molecular-weight complexes can be determined. Here, the resonance signals of the macromolecule must be identified beforehand, which can be time consuming but with the benefit of obtaining more information with respect to the target ligand complex.

  2. 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

  3. 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

  4. 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

    2015-09-01

    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.

  5. PRASA: an integrated web server that analyzes protein interaction types.

    PubMed

    Fan, Chen-Yu; Bai, Yi-Han; Huang, Cheng-Yi; Yao, Tsung-Ju; Chiang, Wen-Hao; Chang, Darby Tien-Hao

    2013-04-10

    This work presents the Protein Association Analyzer (PRASA) (http://zoro.ee.ncku.edu.tw/prasa/) that predicts protein interactions as well as interaction types. Protein interactions are essential to most biological functions. The existence of diverse interaction types, such as physically contacted or functionally related interactions, makes protein interactions complex. Different interaction types are distinct and should not be confused. However, most existing tools focus on a specific interaction type or mix different interaction types. This work collected 7234058 associations with experimentally verified interaction types from five databases and compiled individual probabilistic models for different interaction types. The PRASA result page shows predicted associations and their related references by interaction type. Experimental results demonstrate the performance difference when distinguishing between different interaction types. The PRASA provides a centralized and organized platform for easy browsing, downloading and comparing of interaction types, which helps reveal insights into the complex roles that proteins play in organisms.

  6. Xylan oligosaccharides and cellobiohydrolase I (TrCel7A) interaction and effect on activity

    PubMed Central

    2011-01-01

    Background The well-studied cellulase mixture secreted by Trichoderma reesei (anamorph to Hypocrea jecorina) contains two cellobiohydolases (CBHs), cellobiohydrolase I (TrCel7A) and cellobiohydrolase II (TrCeI6A), that are core enzymes for the solubilisation of cellulose. This has attracted significant research interest because of the role of the CBHs in the conversion of biomass to fermentable sugars. However, the CHBs are notoriously slow and susceptible to inhibition, which presents a challenge for the commercial utilisation of biomass. The xylans and xylan fragments that are also present in the biomass have been suggested repeatedly as one cause of the reduced activity of CHBs. Yet, the extent and mechanisms of this inhibition remain poorly elucidated. Therefore, we studied xylan oligosaccharides (XOSs) of variable lengths with respect to their binding and inhibition of both TrCel7A and an enzyme variant without the cellulose-binding domain (CBM). Results We studied the binding of XOSs to TrCel7A by isothermal titration calorimetry. We found that XOSs bind to TrCel7A and that the affinity increases commensurate with XOS length. The CBM, on the other hand, did not affect the affinity significantly, which suggests that XOSs may bind to the active site. Activity assays of TrCel7A clearly demonstrated the negative effect of the presence of XOSs on the turnover number. Conclusions On the basis of these binding data and a comparison of XOS inhibition of the activity of the two enzyme variants towards, respectively, soluble and insoluble substrates, we propose a competitive mechanism for XOS inhibition of TrCel7A with phosphoric swollen cellulose as a substrate. PMID:22035059

  7. 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

  8. 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.

  9. Channel-interacting PDZ protein, 'CIPP', interacts with proteins involved in cytoskeletal dynamics.

    PubMed

    Alpi, Emanuele; Landi, Elena; Barilari, Manuela; Serresi, Michela; Salvadori, Piero; Bachi, Angela; Dente, Luciana

    2009-04-15

    Neuronal CIPP (channel-interacting PDZ protein) is a multivalent PDZ protein that interacts with specific channels and receptors highly expressed in the brain. It is composed of four PDZ domains that behave as a scaffold to clusterize functionally connected proteins. In the present study, we selected a set of potential CIPP interactors that are involved directly or indirectly in mechanisms of cytoskeletal remodelling and membrane protrusion formation. For some of these, we first proved the direct binding to specific CIPP PDZ domains considered as autonomous elements, and then confirmed the interaction with the whole protein. In particular, the small G-protein effector IRSp53 (insulin receptor tyrosine kinase substrate protein p53) specifically interacts with the second PDZ domain of CIPP and, when co-transfected in cultured mammalian cells with a tagged full-length CIPP, it induces a marked reorganization of CIPP cytoplasmic localization. Large punctate structures are generated as a consequence of CIPP binding to the IRSp53 C-terminus. Analysis of the puncta nature, using various endocytic markers, revealed that they are not related to cytoplasmic vesicles, but rather represent multi-protein assemblies, where CIPP can tether other potential interactors.

  10. Molecular modeling of protein-glycosaminoglycan interactions.

    PubMed

    Cardin, A D; Weintraub, H J

    1989-01-01

    Forty-nine regions in 21 proteins were identified as potential heparin-binding sites based on the sequence organizations of their basic and nonbasic residues. Twelve known heparin-binding sequences in vitronectin, apolipoproteins E and B-100, and platelet factor 4 were used to formulate two search strings for identifying potential heparin-binding regions in other proteins. Consensus sequences for glycosaminoglycan recognition were determined as [-X-B-B-X-B-X-] and [-X-B-B-B-X-X-B-X-] where B is the probability of a basic residue and X is a hydropathic residue. Predictions were then made as to the heparin-binding domains in endothelial cell growth factor, purpurin, and antithrombin-III. Many of the natural sequences conforming to these consensus motifs show prominent amphipathic periodicities having both alpha-helical and beta-strand conformations as determined by predictive algorithms and circular dichroism studies. The heparin-binding domain of vitronectin was modeled and formed a hydrophilic pocket that wrapped around and folded over a heparin octasaccharide, yielding a complementary structure. We suggest that these consensus sequence elements form potential nucleation sites for the recognition of polyanions in proteins and may provide a useful guide in identifying heparin-binding regions in other proteins. The possible relevance of protein-glycosaminoglycans interactions in atherosclerosis is discussed. PMID:2463827

  11. 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

    2016-08-01

    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

  12. 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

  13. Weakly Stable Regions and Protein-Protein Interactions in Beta-Barrel Membrane Proteins

    PubMed Central

    Naveed, Hammad; Liang, Jie

    2014-01-01

    We briefly discuss recent progress in computational characterization of the sequence and structural properties of β-barrel membrane properties. We discuss the emerging concept of weakly stable regions in β-barrel membrane proteins, computational methods to identify these regions and mechanisms adopted by β-barrel membrane proteins in nature to stabilize them. We further discuss computational methods to identify protein-protein interactions in β-barrel membrane proteins and recent experimental studies that aim at altering the biophysical properties including oligomerization state and stability of β-barrel membrane proteins based on the emerging organization principles of these proteins from recent computational studies. PMID:23713778

  14. Prediction of thermodynamic instabilities of protein solutions from simple protein-protein interactions

    NASA Astrophysics Data System (ADS)

    D'Agostino, Tommaso; Solana, José Ramón; Emanuele, Antonio

    2013-10-01

    Statistical thermodynamics of protein solutions is often studied in terms of simple, microscopic models of particles interacting via pairwise potentials. Such modelling can reproduce the short range structure of protein solutions at equilibrium and predict thermodynamics instabilities of these systems. We introduce a square well model of effective protein-protein interaction that embeds the solvent’s action. We modify an existing model [45] by considering a well depth having an explicit dependence on temperature, i.e. an explicit free energy character, thus encompassing the statistically relevant configurations of solvent molecules around proteins. We choose protein solutions exhibiting demixing upon temperature decrease (lysozyme, enthalpy driven) and upon temperature increase (haemoglobin, entropy driven). We obtain satisfactory fits of spinodal curves for both the two proteins without adding any mean field term, thus extending the validity of the original model. Our results underline the solvent role in modulating or stretching the interaction potential.

  15. 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

  16. Yeast Three-Hybrid System for the Detection of Protein-Protein Interactions.

    PubMed

    Maruta, Natsumi; Trusov, Yuri; Botella, Jose R

    2016-01-01

    Protein-protein interaction studies provide useful insights into biological processes taking place within the living cell. A number of techniques are available to unravel large structural protein complexes, functional protein modules, and temporary protein associations occurring during signal transduction. The choice of method depends on the nature of the proteins and the interaction being studied. Here we present an optimized and simplified yeast three-hybrid method for analysis of protein interactions involving three components.

  17. 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.

  18. 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. PMID:27434096

  19. 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.

  20. 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.

  1. Detection and identification of protein interactions of S100 proteins by ProteinChip technology.

    PubMed

    Lehmann, Roland; Melle, Christian; Escher, Niko; von Eggeling, Ferdinand

    2005-01-01

    The aim of this work was to establish an approach for identification of protein interactions. This assay used an anti-S100A8 antibody coupled on beads and incubated with cell extract. The bead eluates were analyzed using ProteinChip technology and subsequently subjected to an appropriate digestion. Molecular masses of digestion fragments were determined by SELDI-MS, and database analysis revealed S100A10 as interacting protein. This result was confirmed by co-immunoprecipitation and immunocapturing. Using S100A10 as new bait, a specific interaction with S100A7 was detectable. PMID:16212425

  2. 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

  3. Specificity in protein-protein interactions: the structural basis for dual recognition in endonuclease colicin-immunity protein complexes.

    PubMed

    Kühlmann, U C; Pommer, A J; Moore, G R; James, R; Kleanthous, C

    2000-09-01

    Bacteria producing endonuclease colicins are protected against their cytotoxic activity by virtue of a small immunity protein that binds with high affinity and specificity to inactivate the endonuclease. DNase binding by the immunity protein occurs through a "dual recognition" mechanism in which conserved residues from helix III act as the binding-site anchor, while variable residues from helix II define specificity. We now report the 1.7 A crystal structure of the 24.5 kDa complex formed between the endonuclease domain of colicin E9 and its cognate immunity protein Im9, which provides a molecular rationale for this mechanism. Conserved residues of Im9 form a binding-energy hotspot through a combination of backbone hydrogen bonds to the endonuclease, many via buried solvent molecules, and hydrophobic interactions at the core of the interface, while the specificity-determining residues interact with corresponding specificity side-chains on the enzyme. Comparison between the present structure and that reported recently for the colicin E7 endonuclease domain in complex with Im7 highlights how specificity is achieved by very different interactions in the two complexes, predominantly hydrophobic in nature in the E9-Im9 complex but charged in the E7-Im7 complex. A key feature of both complexes is the contact between a conserved tyrosine residue from the immunity proteins (Im9 Tyr54) with a specificity residue on the endonuclease directing it toward the specificity sites of the immunity protein. Remarkably, this tyrosine residue and its neighbour (Im9 Tyr55) are the pivots of a 19 degrees rigid-body rotation that relates the positions of Im7 and Im9 in the two complexes. This rotation does not affect conserved immunity protein interactions with the endonuclease but results in different regions of the specificity helix being presented to the enzyme.

  4. 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.

  5. Ion-dipole interactions and their functions in proteins.

    PubMed

    Sippel, Katherine H; Quiocho, Florante A

    2015-07-01

    Ion-dipole interactions in biological macromolecules are formed between atomic or molecular ions and neutral protein dipolar groups through either hydrogen bond or coordination. Since their discovery 30 years ago, these interactions have proven to be a frequent occurrence in protein structures, appearing in everything from transporters and ion channels to enzyme active sites to protein-protein interfaces. However, their significance and roles in protein functions are largely underappreciated. We performed PDB data mining to identify a sampling of proteins that possess these interactions. In this review, we will define the ion-dipole interaction and discuss several prominent examples of their functional roles in nature.

  6. Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions.

    PubMed

    Fasolo, Joseph; Im, Hogune; Snyder, Michael P

    2015-01-01

    High-density functional protein microarrays containing ~4,200 recombinant yeast proteins are examined for kinase protein-protein interactions using an affinity purified yeast kinase fusion protein containing a V5-epitope tag for read-out. Purified kinase is obtained through culture of a yeast strain optimized for high copy protein production harboring a plasmid containing a Kinase-V5 fusion construct under a GAL inducible promoter. The yeast is grown in restrictive media with a neutral carbon source for 6 hr followed by induction with 2% galactose. Next, the culture is harvested and kinase is purified using standard affinity chromatographic techniques to obtain a highly purified protein kinase for use in the assay. The purified kinase is diluted with kinase buffer to an appropriate range for the assay and the protein microarrays are blocked prior to hybridization with the protein microarray. After the hybridization, the arrays are probed with monoclonal V5 antibody to identify proteins bound by the kinase-V5 protein. Finally, the arrays are scanned using a standard microarray scanner, and data is extracted for downstream informatics analysis to determine a high confidence set of protein interactions for downstream validation in vivo. PMID:26274875

  7. 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.

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

    PubMed Central

    2010-01-01

    Background Elucidating protein-protein interactions (PPIs) is essential to constructing protein interaction networks and facilitating our understanding of the general principles of biological systems. Previous studies have revealed that interacting protein pairs can be predicted by their primary structure. Most of these approaches have achieved satisfactory performance on datasets comprising equal number of interacting and non-interacting protein pairs. However, this ratio is highly unbalanced in nature, and these techniques have not been comprehensively evaluated with respect to the effect of the large number of non-interacting pairs in realistic datasets. Moreover, since highly unbalanced distributions usually lead to large datasets, more efficient predictors are desired when handling such challenging tasks. Results This study presents a method for PPI prediction based only on sequence information, which contributes in three aspects. First, we propose a probability-based mechanism for transforming protein sequences into feature vectors. Second, the proposed predictor is designed with an efficient classification algorithm, where the efficiency is essential for handling highly unbalanced datasets. Third, the proposed PPI predictor is assessed with several unbalanced datasets with different positive-to-negative ratios (from 1:1 to 1:15). This analysis provides solid evidence that the degree of dataset imbalance is important to PPI predictors. Conclusions Dealing with data imbalance is a key issue in PPI prediction since there are far fewer interacting protein pairs than non-interacting ones. This article provides a comprehensive study on this issue and develops a practical tool that achieves both good prediction performance and efficiency using only protein sequence information. PMID:20361868

  9. 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.

  10. Interaction between pregnancy zone protein and plasmin.

    PubMed

    Poulsen, O M; Hau, J

    1988-01-01

    Pregnancy zone protein (PZP, alpha 2-PAG, SP3) was found to bind to plasmin in crossed affino-immunoelectrophoresis using sodium caseinate in the first dimension gel. The plasmin presence in the PZP-plasmin complex was confirmed by addition of antiserum against plasminogen to the gel. In crossed affino-immunoelectrophoresis using plasmin in the first dimension gel a non migrative PZP immunoreactive peak appeared, similar to the peak obtained with casein in the first dimension gel. Incubation of mixtures of PZP and plasmin also demonstrated complex formation between PZP and plasmin. The complex between PZP and plasmin could be precipitated not only by anti-PZP antibodies, but also by anti-plasminogen antibodies, confirming the interaction between the two molecules. The significance of the binding between plasmin and PZP remains to be elucidated, but it is tempting to speculate that PZP, present on the trophoblastic surface, immobilizes plasmin, rendering this molecule able to perform a local fibrinolytic activity.

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

    PubMed Central

    Gell, D; Jackson, S P

    1999-01-01

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

  12. Identification of binary interactions between human cytomegalovirus virion proteins.

    PubMed

    Phillips, Stacia L; Bresnahan, Wade A

    2011-01-01

    Human cytomegalovirus (HCMV) virions are composed of a DNA-containing nucleocapsid surrounded by a tegument layer and host-derived lipid envelope studded with virally encoded glycoproteins. These complex virions are estimated to be composed of more than 50 viral proteins. Assembly of HCMV virions is poorly understood, especially with respect to acquisition of the tegument; however, it is thought to involve the stepwise addition of virion components through protein-protein interactions. We sought to identify interactions among HCMV virion proteins using yeast two-hybrid analysis. Using 33 known capsid and tegument proteins, we tested 1,089 pairwise combinations for binary interaction in the two-hybrid assay. We identified 24 interactions among HCMV virion proteins, including 13 novel interactions among tegument proteins and one novel interaction between capsid proteins. Several of these novel interactions were confirmed by coimmunoprecipitation of protein complexes from transfected cells. In addition, we demonstrate three of these interactions in the context of HCMV infection. This study reveals several new protein-protein interactions among HCMV tegument proteins, some of which are likely important for HCMV replication and pathogenesis. PMID:20962080

  13. 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

  14. 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

  15. Ion–dipole interactions and their functions in proteins

    PubMed Central

    Sippel, Katherine H; Quiocho, Florante A

    2015-01-01

    Ion–dipole interactions in biological macromolecules are formed between atomic or molecular ions and neutral protein dipolar groups through either hydrogen bond or coordination. Since their discovery 30 years ago, these interactions have proven to be a frequent occurrence in protein structures, appearing in everything from transporters and ion channels to enzyme active sites to protein–protein interfaces. However, their significance and roles in protein functions are largely underappreciated. We performed PDB data mining to identify a sampling of proteins that possess these interactions. In this review, we will define the ion–dipole interaction and discuss several prominent examples of their functional roles in nature. PMID:25866296

  16. Methods for the analysis of protein-chromatin interactions.

    PubMed

    Brickwood, Sarah J; Myers, Fiona A; Chandler, Simon P

    2002-01-01

    The analysis of protein interactions with chromatin is vital for the understanding of DNA sequence recognition in vivo. Chromatin binding requires the interaction of proteins with DNA lying on the macromolecular protein surface of nucleosomes, a situation that can alter factor binding characteristics substantially when compared with naked DNA. It is therefore important to study these protein-DNA interactions in the context of a chromatin substrate, the more physiologically relevant binding situation. In this article we review techniques used in the investigation of protein interactions with defined nucleosomal templates. PMID:11876294

  17. Large-scale identification of yeast integral membrane protein interactions

    PubMed Central

    Miller, John P.; Lo, Russell S.; Ben-Hur, Asa; Desmarais, Cynthia; Stagljar, Igor; Noble, William Stafford; Fields, Stanley

    2005-01-01

    We carried out a large-scale screen to identify interactions between integral membrane proteins of Saccharomyces cerevisiae by using a modified split-ubiquitin technique. Among 705 proteins annotated as integral membrane, we identified 1,985 putative interactions involving 536 proteins. To ascribe confidence levels to the interactions, we used a support vector machine algorithm to classify interactions based on the assay results and protein data derived from the literature. Previously identified and computationally supported interactions were used to train the support vector machine, which identified 131 interactions of highest confidence, 209 of the next highest confidence, 468 of the next highest, and the remaining 1,085 of low confidence. This study provides numerous putative interactions among a class of proteins that have been difficult to analyze on a high-throughput basis by other approaches. The results identify potential previously undescribed components of established biological processes and roles for integral membrane proteins of ascribed functions. PMID:16093310

  18. Defining the Protein-Protein Interaction Network of the Human Protein Tyrosine Phosphatase Family.

    PubMed

    Li, Xu; Tran, Kim My; Aziz, Kathryn E; Sorokin, Alexey V; Chen, Junjie; Wang, Wenqi

    2016-09-01

    Protein tyrosine phosphorylation, which plays a vital role in a variety of human cellular processes, is coordinated by protein tyrosine kinases and protein tyrosine phosphatases (PTPs). Genomic studies provide compelling evidence that PTPs are frequently mutated in various human cancers, suggesting that they have important roles in tumor suppression. However, the cellular functions and regulatory machineries of most PTPs are still largely unknown. To gain a comprehensive understanding of the protein-protein interaction network of the human PTP family, we performed a global proteomic study. Using a Minkowski distance-based unified scoring environment (MUSE) for the data analysis, we identified 940 high confidence candidate-interacting proteins that comprise the interaction landscape of the human PTP family. Through a gene ontology analysis and functional validations, we connected the PTP family with several key signaling pathways or cellular functions whose associations were previously unclear, such as the RAS-RAF-MEK pathway, the Hippo-YAP pathway, and cytokinesis. Our study provides the first glimpse of a protein interaction network for the human PTP family, linking it to a number of crucial signaling events, and generating a useful resource for future studies of PTPs.

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

    PubMed

    Kiran, M; Nagarajaram, H A

    2016-08-16

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

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

    PubMed

    Kiran, M; Nagarajaram, H A

    2016-08-16

    Hubs, the highly connected nodes in protein-protein interaction networks (PPINs), are associated with several characteristic properties and are known to perform vital roles in cells. We defined two classes of hubs, global (housekeeping) and local (tissue-specific) hubs. These two categories of hubs are distinct from each other with respect to their abundance, structure and function. However, how distinct are the spatial expression pattern and other characteristics of their interacting partners is still not known. Our investigations revealed that the partners of the local hubs compared with those of global hubs are conserved across the tissues in which they are expressed. Partners of local hubs show diverse subcellular localizations as compared with the partners of global hubs. We examined the nature of interacting domains in both categories of hubs and found that they are promiscuous in global hubs but not so in local hubs. Deletion of some of the local and global hubs has an impact on the characteristic path length of the network indicating that those hubs are inter-modular in nature. Our present study has, therefore, shed further light on the characteristic features of the local and global hubs in human PPIN. This knowledge of different topological aspects of hubs with regard to their types and subtypes is essential as it helps in better understanding of roles of hub proteins in various cellular processes under various conditions including those caused by host-pathogen interactions and therefore useful in prioritizing targets for drug design and repositioning. PMID:27400769

  1. 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. PMID:24853495

  2. The relationship between P2X4 and P2X7: a physiologically important interaction?

    PubMed

    Craigie, Eilidh; Birch, Rebecca E; Unwin, Robert J; Wildman, Scott S

    2013-01-01

    Purinergic signaling within the kidney is becoming an important focus in the study of renal health and disease. The effectors of ATP signaling, the P2Y and P2X receptors, are expressed to varying extents in and along the nephron. There are many studies demonstrating the importance of the P2Y2 receptor on kidney function, and other P2 receptors are now emerging as participants in renal regulation. The P2X4 receptor has been linked to epithelial sodium transport in the nephron and expression levels of the P2X7 receptor are up-regulated in certain pathophysiological states. P2X7 antagonism has been shown to ameliorate rodent models of DOCA salt-induced hypertension and P2X4 null mice are hypertensive. Interestingly, polymorphisms in the genetic loci of P2X4 and P2X7 have been linked to blood pressure variation in human studies. In addition to the increasing evidence linking these two P2X receptors to renal function and health, a number of studies link the two receptors in terms of physical associations between their subunits, demonstrated both in vitro and in vivo. This review will analyze the current literature regarding interactions between P2X4 and P2X7 and assess the potential impact of these with respect to renal function. PMID:23966951

  3. 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.

  4. HOXB7, a homeodomain protein, is overexpressed in breast cancer and confers epithelial-mesenchymal transition.

    PubMed

    Wu, Xinyan; Chen, Hexin; Parker, Belinda; Rubin, Ethel; Zhu, Tao; Lee, Ji Shin; Argani, Pedram; Sukumar, Saraswati

    2006-10-01

    Epithelial-mesenchymal transition (EMT) is increasingly recognized as a mechanism whereby cells in primary noninvasive tumors acquire properties essential for migration and invasion. Microarray analyses of microdissected epithelial cells from bone metastasis revealed a HOXB7 overexpression that was 3-fold higher than in primary breast carcinomas and 18-fold higher compared with normal breast. This led us to investigate the role of HOXB7 in neoplastic transformation of breast cells. Expression of HOXB7 in both MCF10A and Madin-Darby canine kidney (MDCK) epithelial cells resulted in the acquisition of both phenotypic and molecular attributes typical of EMT. Loss of epithelial proteins, claudin 1 and claudin 7, mislocalization of claudin 4 and E-cadherin, and the expression of mesenchymal proteins, vimentin and alpha-smooth muscle actin, were observed. MDCK cells expressing HOXB7 exhibited properties of migration and invasion. Unlike MDCK vector-transfected cells, MDCK-HOXB7 cells formed highly vascularized tumors in mice. MDCK-HOXB7 cells overexpressed basic fibroblast growth factor (bFGF), had more active forms of both Ras and RhoA proteins, and displayed higher levels of phosphorylation of p44 and p42 mitogen-activated protein kinase (MAPK; extracellular signal-regulated kinases 1 and 2). Effects initiated by HOXB7 were reversed by specific inhibitors of FGF receptor and the Ras-MAPK pathways. These data provide support for a function for HOXB7 in promoting tumor invasion through activation of Ras/Rho pathway by up-regulating bFGF, a known transcriptional target of HOXB7. Reversal of these effects by HOXB7-specific siRNA further suggested that these effects were mediated by HOXB7. Thus, HOXB7 overexpression caused EMT in epithelial cells, accompanied by acquisition of aggressive properties of tumorigenicity, migration, and invasion.

  5. Oncogenic activation of the human trk proto-oncogene by recombination with the ribosomal large subunit protein L7a.

    PubMed Central

    Ziemiecki, A; Müller, R G; Fu, X C; Hynes, N E; Kozma, S

    1990-01-01

    The trk-2h oncogene, isolated from the human breast carcinoma cell line MDA-MB 231 by genomic DNA-transfection into NIH3T3 cells, consists of the trk proto-oncogene receptor kinase domain fused to a N-terminal 41 amino acid activating sequence (Kozma, S.C., Redmond, S.M.S., Xiao-Chang, F., Saurer, S.M., Groner, B. and Hynes, N.E. (1988) EMBO J., 7, 147-154). Antibodies raised against a bacterially produced beta gal-trk receptor kinase fusion protein recognized a 44 kd phosphoprotein phosphorylated on serine, threonine and tyrosine in extracts of trk-2h transformed NIH3T3 cells. In vitro, in the presence of Mn2+/gamma ATP, this protein became phosphorylated extensively on tyrosine. Cells transformed by trk-2h did not, however, show an elevation in total phosphotyrosine. We have cloned and sequenced the cDNA encoding the amino terminal activating sequences of trk-2h (Kozma et al., 1988). The encoded protein has a high basic amino acid content and the gene is expressed as an abundant 1.2 kb mRNA in human, rat and mouse cells. Antipeptide antibodies raised against a C-terminal peptide recognized specifically a 30 kd protein on Western blots of human, rat and mouse cell extracts. Immunofluorescence revealed, in addition to granular cytoplasmic fluorescence, intense nucleolar staining. The high basic amino acid content and nucleolar staining prompted us to investigate whether the 30 kd protein could be a ribosomal protein. Western immunoblotting analysis of 2D-electrophoretically resolved ribosomal proteins indicated that the 30 kd protein is the ribosomal large subunit protein L7a.(ABSTRACT TRUNCATED AT 250 WORDS) Images Fig. 1. Fig. 2. Fig. 3. Fig. 4. Fig. 5. Fig. 6. Fig. 7. Fig. 9. PMID:2403926

  6. Predicting the protein-protein interactions using primary structures with predicted protein surface

    PubMed Central

    2010-01-01

    Background Many biological functions involve various protein-protein interactions (PPIs). Elucidating such interactions is crucial for understanding general principles of cellular systems. Previous studies have shown the potential of predicting PPIs based on only sequence information. Compared to approaches that require other auxiliary information, these sequence-based approaches can be applied to a broader range of applications. Results This study presents a novel sequence-based method based on the assumption that protein-protein interactions are more related to amino acids at the surface than those at the core. The present method considers surface information and maintains the advantage of relying on only sequence data by including an accessible surface area (ASA) predictor recently proposed by the authors. This study also reports the experiments conducted to evaluate a) the performance of PPI prediction achieved by including the predicted surface and b) the quality of the predicted surface in comparison with the surface obtained from structures. The experimental results show that surface information helps to predict interacting protein pairs. Furthermore, the prediction performance achieved by using the surface estimated with the ASA predictor is close to that using the surface obtained from protein structures. Conclusion This work presents a sequence-based method that takes into account surface information for predicting PPIs. The proposed procedure of surface identification improves the prediction performance with an F-measure of 5.1%. The extracted surfaces are also valuable in other biomedical applications that require similar information. PMID:20122202

  7. 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…

  8. Ammonium sulfate co-precipitation of SSB and interacting proteins.

    PubMed

    Marceau, Aimee H

    2012-01-01

    Bacterial single-strand DNA-binding protein (SSB) interacts with many proteins involved in the diverse process of genome maintenance. The interactions are mediated by the essential and conserved amphipathic C-terminus (SSB-Ct). SSB plays a critical role in localizing and stimulating the activity of a wide variety of DNA-processing proteins. The interaction partners have been identified and studied using a variety of methods, one of which, ammonium sulfate co-precipitation, is described here.

  9. RNase 7, a novel innate immune defense antimicrobial protein of healthy human skin.

    PubMed

    Harder, Jurgen; Schroder, Jens-Michael

    2002-11-29

    We analyzed healthy human skin for the presence of endogenous antimicrobial proteins that might explain the unusually high resistance of human skin against infections. A novel 14.5-kDa antimicrobial ribonuclease, termed RNase 7, was isolated from skin-derived stratum corneum. RNase 7 exhibited potent ribonuclease activity and thus may contribute to the well known ribonuclease activity of human skin. RNase 7 revealed broad spectrum antimicrobial activity against many pathogenic microorganisms and remarkably potent activity (lethal dose of 90% < 30 nm) against a vancomycin-resistant Enterococcus faecium. Molecular cloning from skin-derived primary keratinocytes and purification of RNase 7 from supernatants of cultured primary keratinocytes indicate that keratinocytes represent the major cellular source in skin and that RNase 7 is secreted. RNase 7 mRNA expression was detected in various epithelial tissues including skin, respiratory tract, genitourinary tract, and at a low level, in the gut. In addition to a constitutive expression, RNase 7 mRNA was induced in cultured primary keratinocytes by interleukin-1beta, interferon-gamma, and bacterial challenge. This is the first report demonstrating RNases as a novel class of epithelial inducible antimicrobial proteins, which may play an important role in the innate immune defense system of human epithelia.

  10. Interactions of proteins in gels, solutions and on surfaces

    NASA Astrophysics Data System (ADS)

    Ramasamy, Radha Perumal

    2006-12-01

    The study of protein interaction, identification and separation has applications in various fields relating to Biotechnology. In this research these aspects were investigated. The proteins albumin, casein, poly-L-lysine were studied. FITC and TRITC were used to fluorescently tag the proteins. Confocal microscopy was used to image the interaction of proteins. The migration of fluorescently tagged protein-salt aggregates on solid surfaces during electrophoresis was investigated using Confocal microscopy. The secondary structural modifications of proteins in solutions were investigated using FTIR micro spectroscopic imaging. The size of the colloids formed due to protein-protein interactions as a function of the protein concentrations were studied using DLS and their charges were found using zeta potential measurements. Based on DL.S and zeta potential measurements, a model is proposed for interactions of oppositely charged proteins. The nature of interaction was found using UV - Visual spectroscopy. It was found that oppositely charged proteins formed ionic bonds. It was also found that FITC molecule influenced the surface charge of albumin more than TRITC molecule. The effects of the influence of cell geometries upon Electro Osmotic Flow (EOF) were studied using neutrally charged fluorescent Polystyrene beads. Results showed that tagging proteins with fluorescent molecules influenced their mobility and interactions with other proteins. However no secondary structural modifications of the proteins were observed when oppositely charged proteins interacted. It was also observed that electrostatic interactions made oppositely charged proteins form large aggregates. The EOF was found to be dependent upon the ionic strength of the buffer, conductivity of the solid surfaces, distance from the surface and position of the electrodes in the electrophoretic cell.

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

    PubMed

    Sultana, Azmiri; Lee, Jeffrey E

    2015-01-01

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

  12. 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. PMID:23281010

  13. 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

  14. Protein-Protein Interactions Inferred from Domain-Domain Interactions in Genogroup II Genotype 4 Norovirus Sequences

    PubMed Central

    Huang, Chuan-Ching

    2013-01-01

    Severe gastroenteritis and foodborne illness caused by Noroviruses (NoVs) during the winter are a worldwide phenomenon. Vulnerable populations including young children and elderly and immunocompromised people often require hospitalization and may die. However, no efficient vaccine for NoVs exists because of their variable genome sequences. This study investigates the infection processes in protein-protein interactions between hosts and NoVs. Protein-protein interactions were collected from related Pfam NoV domains. The related Pfam domains were accumulated incrementally from the protein domain interaction database. To examine the influence of domain intimacy, the 7 NoV domains were grouped by depth. The number of domain-domain interactions increased exponentially as the depth increased. Many protein-protein interactions were relevant; therefore, cloud techniques were used to analyze data because of their computational capacity. The infection relationship between hosts and NoVs should be used in clinical applications and drug design. PMID:23738320

  15. 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.

  16. 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

  17. Direct detection of CH/pi interactions in proteins.

    PubMed

    Plevin, Michael J; Bryce, David L; Boisbouvier, Jérôme

    2010-06-01

    XH/pi interactions make important contributions to biomolecular structure and function. These weakly polar interactions, involving pi-system acceptor groups, are usually identified from the three-dimensional structures of proteins. Here, nuclear magnetic resonance spectroscopy has been used to directly detect methyl/pi (Me/pi) interactions in proteins at atomic resolution. Density functional theory calculations predict the existence of weak scalar (J) couplings between nuclei involved in Me/pi interactions. Using an optimized isotope-labelling strategy, these J couplings have been detected in proteins using nuclear magnetic resonance spectroscopy. The resulting spectra provide direct experimental evidence of Me/pi interactions in proteins and allow a simple and unambiguous assignment of donor and acceptor groups. The use of nuclear magnetic resonance spectroscopy is an elegant way to identify and experimentally characterize Me/pi interactions in proteins without the need for arbitrary geometric descriptions or pre-existing three-dimensional structures. PMID:20489715

  18. VirusMINT: a viral protein interaction database

    PubMed Central

    Chatr-aryamontri, Andrew; Ceol, Arnaud; Peluso, Daniele; Nardozza, Aurelio; Panni, Simona; Sacco, Francesca; Tinti, Michele; Smolyar, Alex; Castagnoli, Luisa; Vidal, Marc; Cusick, Michael E.; Cesareni, Gianni

    2009-01-01

    Understanding the consequences on host physiology induced by viral infection requires complete understanding of the perturbations caused by virus proteins on the cellular protein interaction network. The VirusMINT database (http://mint.bio.uniroma2.it/virusmint/) aims at collecting all protein interactions between viral and human proteins reported in the literature. VirusMINT currently stores over 5000 interactions involving more than 490 unique viral proteins from more than 110 different viral strains. The whole data set can be easily queried through the search pages and the results can be displayed with a graphical viewer. The curation effort has focused on manuscripts reporting interactions between human proteins and proteins encoded by some of the most medically relevant viruses: papilloma viruses, human immunodeficiency virus 1, Epstein–Barr virus, hepatitis B virus, hepatitis C virus, herpes viruses and Simian virus 40. PMID:18974184

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

    PubMed Central

    Teilum, Kaare; Olsen, Johan G.; Kragelund, Birthe B.

    2015-01-01

    In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs) and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol−1. PMID:26217672

  20. Synthetic protein interactions reveal a functional map of the cell

    PubMed Central

    Berry, Lisa K; Ólafsson, Guðjón; Ledesma-Fernández, Elena; Thorpe, Peter H

    2016-01-01

    To understand the function of eukaryotic cells, it is critical to understand the role of protein-protein interactions and protein localization. Currently, we do not know the importance of global protein localization nor do we understand to what extent the cell is permissive for new protein associations – a key requirement for the evolution of new protein functions. To answer this question, we fused every protein in the yeast Saccharomyces cerevisiae with a partner from each of the major cellular compartments and quantitatively assessed the effects upon growth. This analysis reveals that cells have a remarkable and unanticipated tolerance for forced protein associations, even if these associations lead to a proportion of the protein moving compartments within the cell. Furthermore, the interactions that do perturb growth provide a functional map of spatial protein regulation, identifying key regulatory complexes for the normal homeostasis of eukaryotic cells. DOI: http://dx.doi.org/10.7554/eLife.13053.001 PMID:27098839

  1. 14-3-3 proteins in plant-pathogen interactions.

    PubMed

    Lozano-Durán, Rosa; Robatzek, Silke

    2015-05-01

    14-3-3 proteins define a eukaryotic-specific protein family with a general role in signal transduction. Primarily, 14-3-3 proteins act as phosphosensors, binding phosphorylated client proteins and modulating their functions. Since phosphorylation regulates a plethora of different physiological responses in plants, 14-3-3 proteins play roles in multiple signaling pathways, including those controlling metabolism, hormone signaling, cell division, and responses to abiotic and biotic stimuli. Increasing evidence supports a prominent role of 14-3-3 proteins in regulating plant immunity against pathogens at various levels. In this review, potential links between 14-3-3 function and the regulation of plant-pathogen interactions are discussed, with a special focus on the regulation of 14-3-3 proteins in response to pathogen perception, interactions between 14-3-3 proteins and defense-related proteins, and 14-3-3 proteins as targets of pathogen effectors.

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

    PubMed

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

    2014-05-01

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

  3. 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.

  4. 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.

  5. 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

  6. 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.

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

    PubMed Central

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

    2015-01-01

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

  8. 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. PMID:23404287

  9. From networks of protein interactions to networks of functional dependencies

    PubMed Central

    2012-01-01

    Background As protein-protein interactions connect proteins that participate in either the same or different functions, networks of interacting and functionally annotated proteins can be converted into process graphs of inter-dependent function nodes (each node corresponding to interacting proteins with the same functional annotation). However, as proteins have multiple annotations, the process graph is non-redundant, if only proteins participating directly in a given function are included in the related function node. Results Reasoning that topological features (e.g., clusters of highly inter-connected proteins) might help approaching structured and non-redundant understanding of molecular function, an algorithm was developed that prioritizes inclusion of proteins into the function nodes that best overlap protein clusters. Specifically, the algorithm identifies function nodes (and their mutual relations), based on the topological analysis of a protein interaction network, which can be related to various biological domains, such as cellular components (e.g., peroxisome and cellular bud) or biological processes (e.g., cell budding) of the model organism S. cerevisiae. Conclusions The method we have described allows converting a protein interaction network into a non-redundant process graph of inter-dependent function nodes. The examples we have described show that the resulting graph allows researchers to formulate testable hypotheses about dependencies among functions and the underlying mechanisms. PMID:22607727

  10. Design of Protein-Protein Interactions with a Novel Ensemble-Based Scoring Algorithm

    NASA Astrophysics Data System (ADS)

    Roberts, Kyle E.; Cushing, Patrick R.; Boisguerin, Prisca; Madden, Dean R.; Donald, Bruce R.

    Protein-protein interactions (PPIs) are vital for cell signaling, protein trafficking and localization, gene expression, and many other biological functions. Rational modification of PPI targets provides a mechanism to understand their function and importance. However, PPI systems often have many more degrees of freedom and flexibility than the small-molecule binding sites typically targeted by protein design algorithms. To handle these challenging design systems, we have built upon the computational protein design algorithm K * [8,19] to develop a new design algorithm to study protein-protein and protein-peptide interactions. We validated our algorithm through the design and experimental testing of novel peptide inhibitors.

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

    PubMed

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

    2011-12-01

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

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

    PubMed

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

    2013-10-01

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

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

    PubMed

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

    2015-01-01

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

  14. Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing.

    PubMed

    Yang, Xinping; Coulombe-Huntington, Jasmin; Kang, Shuli; Sheynkman, Gloria M; Hao, Tong; Richardson, Aaron; Sun, Song; Yang, Fan; Shen, Yun A; Murray, Ryan R; Spirohn, Kerstin; Begg, Bridget E; Duran-Frigola, Miquel; MacWilliams, Andrew; Pevzner, Samuel J; Zhong, Quan; Trigg, Shelly A; Tam, Stanley; Ghamsari, Lila; Sahni, Nidhi; Yi, Song; Rodriguez, Maria D; Balcha, Dawit; Tan, Guihong; Costanzo, Michael; Andrews, Brenda; Boone, Charles; Zhou, Xianghong J; Salehi-Ashtiani, Kourosh; Charloteaux, Benoit; Chen, Alyce A; Calderwood, Michael A; Aloy, Patrick; Roth, Frederick P; Hill, David E; Iakoucheva, Lilia M; Xia, Yu; Vidal, Marc

    2016-02-11

    While alternative splicing is known to diversify the functional characteristics of some genes, the extent to which protein isoforms globally contribute to functional complexity on a proteomic scale remains unknown. To address this systematically, we cloned full-length open reading frames of alternatively spliced transcripts for a large number of human genes and used protein-protein interaction profiling to functionally compare hundreds of protein isoform pairs. The majority of isoform pairs share less than 50% of their interactions. In the global context of interactome network maps, alternative isoforms tend to behave like distinct proteins rather than minor variants of each other. Interaction partners specific to alternative isoforms tend to be expressed in a highly tissue-specific manner and belong to distinct functional modules. Our strategy, applicable to other functional characteristics, reveals a widespread expansion of protein interaction capabilities through alternative splicing and suggests that many alternative "isoforms" are functionally divergent (i.e., "functional alloforms"). PMID:26871637

  15. Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing.

    PubMed

    Yang, Xinping; Coulombe-Huntington, Jasmin; Kang, Shuli; Sheynkman, Gloria M; Hao, Tong; Richardson, Aaron; Sun, Song; Yang, Fan; Shen, Yun A; Murray, Ryan R; Spirohn, Kerstin; Begg, Bridget E; Duran-Frigola, Miquel; MacWilliams, Andrew; Pevzner, Samuel J; Zhong, Quan; Trigg, Shelly A; Tam, Stanley; Ghamsari, Lila; Sahni, Nidhi; Yi, Song; Rodriguez, Maria D; Balcha, Dawit; Tan, Guihong; Costanzo, Michael; Andrews, Brenda; Boone, Charles; Zhou, Xianghong J; Salehi-Ashtiani, Kourosh; Charloteaux, Benoit; Chen, Alyce A; Calderwood, Michael A; Aloy, Patrick; Roth, Frederick P; Hill, David E; Iakoucheva, Lilia M; Xia, Yu; Vidal, Marc

    2016-02-11

    While alternative splicing is known to diversify the functional characteristics of some genes, the extent to which protein isoforms globally contribute to functional complexity on a proteomic scale remains unknown. To address this systematically, we cloned full-length open reading frames of alternatively spliced transcripts for a large number of human genes and used protein-protein interaction profiling to functionally compare hundreds of protein isoform pairs. The majority of isoform pairs share less than 50% of their interactions. In the global context of interactome network maps, alternative isoforms tend to behave like distinct proteins rather than minor variants of each other. Interaction partners specific to alternative isoforms tend to be expressed in a highly tissue-specific manner and belong to distinct functional modules. Our strategy, applicable to other functional characteristics, reveals a widespread expansion of protein interaction capabilities through alternative splicing and suggests that many alternative "isoforms" are functionally divergent (i.e., "functional alloforms").

  16. Statistical Approaches for the Construction and Interpretation of Human Protein-Protein Interaction Network

    PubMed Central

    Hu, Yang; Zhang, Ying; Ren, Jun

    2016-01-01

    The overall goal is to establish a reliable human protein-protein interaction network and develop computational tools to characterize a protein-protein interaction (PPI) network and the role of individual proteins in the context of the network topology and their expression status. A novel and unique feature of our approach is that we assigned confidence measure to each derived interacting pair and account for the confidence in our network analysis. We integrated experimental data to infer human PPI network. Our model treated the true interacting status (yes versus no) for any given pair of human proteins as a latent variable whose value was not observed. The experimental data were the manifestation of interacting status, which provided evidence as to the likelihood of the interaction. The confidence of interactions would depend on the strength and consistency of the evidence.

  17. Statistical Approaches for the Construction and Interpretation of Human Protein-Protein Interaction Network.

    PubMed

    Hu, Yang; Zhang, Ying; Ren, Jun; Wang, Yadong; Wang, Zhenzhen; Zhang, Jun

    2016-01-01

    The overall goal is to establish a reliable human protein-protein interaction network and develop computational tools to characterize a protein-protein interaction (PPI) network and the role of individual proteins in the context of the network topology and their expression status. A novel and unique feature of our approach is that we assigned confidence measure to each derived interacting pair and account for the confidence in our network analysis. We integrated experimental data to infer human PPI network. Our model treated the true interacting status (yes versus no) for any given pair of human proteins as a latent variable whose value was not observed. The experimental data were the manifestation of interacting status, which provided evidence as to the likelihood of the interaction. The confidence of interactions would depend on the strength and consistency of the evidence. PMID:27648447

  18. Statistical Approaches for the Construction and Interpretation of Human Protein-Protein Interaction Network

    PubMed Central

    Hu, Yang; Zhang, Ying; Ren, Jun

    2016-01-01

    The overall goal is to establish a reliable human protein-protein interaction network and develop computational tools to characterize a protein-protein interaction (PPI) network and the role of individual proteins in the context of the network topology and their expression status. A novel and unique feature of our approach is that we assigned confidence measure to each derived interacting pair and account for the confidence in our network analysis. We integrated experimental data to infer human PPI network. Our model treated the true interacting status (yes versus no) for any given pair of human proteins as a latent variable whose value was not observed. The experimental data were the manifestation of interacting status, which provided evidence as to the likelihood of the interaction. The confidence of interactions would depend on the strength and consistency of the evidence. PMID:27648447

  19. 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.

  20. Structural study of surfactant-dependent interaction with protein

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

    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.

  1. 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.

  2. 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

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

    PubMed

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

    2016-03-01

    In this study, we investigated the interaction of Vaccinium bracteatum Thunb. leaf (VBTL) pigment and rice proteins. In the presence of rice protein, VBTL pigment antioxidant activity and free polyphenol content decreased by 67.19% and 68.11%, respectively, and L(∗) of the protein-pigment complex decreased significantly over time. L(∗) values of albumin, globulin and glutelin during 60-min pigment exposure decreased by 55.00, 57.14, and 54.30%, respectively, indicating that these proteins had bound to the pigment. A significant difference in protein surface hydrophobicity was observed between rice proteins and pigment-protein complexes, indicating that hydrophobic interaction is a major binding mechanism between VBTL pigment and rice proteins. A significant difference in secondary structures between proteins and protein-pigment complexes was also uncovered, indicating that hydrogen bonding may be another mode of interaction between VBTL pigment and rice proteins. Our results indicate that VBTL pigment can stain rice proteins with hydrophobic and hydrogen interactions. PMID:26471554

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

    PubMed Central

    2010-01-01

    Background Extracting and visualizing of protein-protein interaction (PPI) from text literatures are a meaningful topic in protein science. It assists the identification of interactions among proteins. There is a lack of tools to extract PPI, visualize and classify the results. Results We developed a PPI search system, termed PPLook, which automatically extracts and visualizes protein-protein interaction (PPI) from text. Given a query protein name, PPLook can search a dataset for other proteins interacting with it by using a keywords dictionary pattern-matching algorithm, and display the topological parameters, such as the number of nodes, edges, and connected components. The visualization component of PPLook enables us to view the interaction relationship among the proteins in a three-dimensional space based on the OpenGL graphics interface technology. PPLook can also provide the functions of selecting protein semantic class, counting the number of semantic class proteins which interact with query protein, counting the literature number of articles appearing the interaction relationship about the query protein. Moreover, PPLook provides heterogeneous search and a user-friendly graphical interface. Conclusions PPLook is an effective tool for biologists and biosystem developers who need to access PPI information from the literature. PPLook is freely available for non-commercial users at http://meta.usc.edu/softs/PPLook. PMID:20550717

  5. 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

  6. 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.

  7. Searching the MINT database for protein interaction information.

    PubMed

    Cesareni, Gianni; Chatr-aryamontri, Andrew; Licata, Luana; Ceol, Arnaud

    2008-06-01

    The Molecular Interactions Database (MINT) is a relational database designed to store information about protein interactions. Expert curators extract the relevant information from the scientific literature and deposit it in a computer readable form. Currently (April 2008), MINT contains information on almost 29,000 proteins and more than 100,000 interactions from more than 30 model organisms. This unit provides protocols for searching MINT over the Internet, using the MINT Viewer.

  8. 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.

  9. Protein--nanoparticle interaction: identification of the ubiquitin--gold nanoparticle interaction site.

    PubMed

    Calzolai, Luigi; Franchini, Fabio; Gilliland, Douglas; Rossi, François

    2010-08-11

    We demonstrate that it is possible to identify the protein--nanoparticle interaction site at amino acid scale in solution. Using NMR, chemical shift perturbation analysis, and dynamic light scattering we have identified a specific domain of human ubiquitin that interacts with gold nanoparticles. This method allows a detailed structural analysis of proteins absorbed onto surfaces of nanoparticles in physiological conditions and it will provide much needed experimental data for better modeling and prediction of protein--nanoparticle interactions. PMID:20698623

  10. 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.

  11. Potato leafroll virus structural proteins manipulate overlapping, yet distinct protein interaction networks during infection.

    PubMed

    DeBlasio, Stacy L; Johnson, Richard; Sweeney, Michelle M; Karasev, Alexander; Gray, Stewart M; MacCoss, Michael J; Cilia, Michelle

    2015-06-01

    Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a nonincorporated protein in concert with numerous insect and plant proteins to regulate virus movement/transmission and tissue tropism. Affinity purification coupled to quantitative MS was used to generate protein interaction networks for a PLRV mutant that is unable to produce the read through domain (RTD) and compared to the known wild-type PLRV protein interaction network. By quantifying differences in the protein interaction networks, we identified four distinct classes of PLRV-plant interactions: those plant and nonstructural viral proteins interacting with assembled coat protein (category I); plant proteins in complex with both coat protein and RTD (category II); plant proteins in complex with the RTD (category III); and plant proteins that had higher affinity for virions lacking the RTD (category IV). Proteins identified as interacting with the RTD are potential candidates for regulating viral processes that are mediated by the RTP such as phloem retention and systemic movement and can potentially be useful targets for the development of strategies to prevent infection and/or viral transmission of Luteoviridae species that infect important crop species. PMID:25787689

  12. Potato leafroll virus structural proteins manipulate overlapping, yet distinct protein interaction networks during infection.

    PubMed

    DeBlasio, Stacy L; Johnson, Richard; Sweeney, Michelle M; Karasev, Alexander; Gray, Stewart M; MacCoss, Michael J; Cilia, Michelle

    2015-06-01

    Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a nonincorporated protein in concert with numerous insect and plant proteins to regulate virus movement/transmission and tissue tropism. Affinity purification coupled to quantitative MS was used to generate protein interaction networks for a PLRV mutant that is unable to produce the read through domain (RTD) and compared to the known wild-type PLRV protein interaction network. By quantifying differences in the protein interaction networks, we identified four distinct classes of PLRV-plant interactions: those plant and nonstructural viral proteins interacting with assembled coat protein (category I); plant proteins in complex with both coat protein and RTD (category II); plant proteins in complex with the RTD (category III); and plant proteins that had higher affinity for virions lacking the RTD (category IV). Proteins identified as interacting with the RTD are potential candidates for regulating viral processes that are mediated by the RTP such as phloem retention and systemic movement and can potentially be useful targets for the development of strategies to prevent infection and/or viral transmission of Luteoviridae species that infect important crop species.

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

    PubMed

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

    2015-01-01

    Protein-protein docking aims at predicting the three-dimensional structure of a protein complex starting from the free forms of the individual partners. As assessed in the CAPRI community-wide experiment, the most successful docking algorithms combine pure laws of physics with information derived from various experimental or bioinformatics sources. Of these so-called "information-driven" approaches, HADDOCK stands out as one of the most successful representatives. In this chapter, we briefly summarize which experimental information can be used to drive the docking prediction in HADDOCK, and then focus on the docking protocol itself. We discuss and illustrate with a tutorial example a "classical" protein-protein docking prediction, as well as more recent developments for modelling multi-body systems and large conformational changes. PMID:25330973

  14. Lead-protein interactions as a basis for lead toxicity.

    PubMed

    Goering, P L

    1993-01-01

    The interaction of lead (Pb) with proteins may represent a fundamental mechanism by which Pb exerts toxicity. In this overview, various factors which influence the interaction of Pb with proteins will be discussed. Pb interacts with enzyme functional groups, and high-affinity metal-binding proteins, such as Pb-binding proteins and metallothioneins, can mediate this Pb-enzyme interaction. Many other factors influence Pb-protein interactions including ligand competition and binding affinities; protein folding and the nature of the metal-binding site; rates of protein synthesis and degradation; and intracellular localization of the ligand and metal. The remainder of this overview will focus on specific examples of important proteins known to be influenced by Pb or which hypothetically may be influenced by Pb. Gaps in knowledge and important research needs are emphasized. Many of the factors discussed play a role in the relative sensitivity of various enzymes in heme biosynthesis to Pb. Disruption of this critical pathway by Pb may result in neuropathologies and accumulation of neurotoxic heme precursors. High-affinity metal-binding proteins have been shown to play a role in mediating Pb inhibition of the octameric Zn-containing enzyme, ALA dehydratase. Knowledge of regional localization in brain and the postnatal ontogeny of the high-affinity metal-binding proteins may be pivotal in understanding Pb neurotoxicity. Other specific examples related to or potentially related to Pb toxicity which are discussed include nucleic acid binding proteins, calmodulin, protein kinase C, and carbonic anhydrase. These proteins will serve as models to understand some basic principles and differences in Pb-protein interactions.

  15. Actin Interacts with Dengue Virus 2 and 4 Envelope Proteins.

    PubMed

    Jitoboam, Kunlakanya; Phaonakrop, Narumon; Libsittikul, Sirikwan; Thepparit, Chutima; Roytrakul, Sittiruk; Smith, Duncan R

    2016-01-01

    Dengue virus (DENV) remains a significant public health problem in many tropical and sub-tropical countries worldwide. The DENV envelope (E) protein is the major antigenic determinant and the protein that mediates receptor binding and endosomal fusion. In contrast to some other DENV proteins, relatively few cellular interacting proteins have been identified. To address this issue a co-immuoprecipitation strategy was employed. The predominant co-immunoprecipitating proteins identified were actin and actin related proteins, however the results suggested that actin was the only bona fide interacting partner. Actin was shown to interact with the E protein of DENV 2 and 4, and the interaction between actin and DENV E protein was shown to occur in a truncated DENV consisting of only domains I and II. Actin was shown to decrease during infection, but this was not associated with a decrease in gene transcription. Actin-related proteins also showed a decrease in expression during infection that was not transcriptionally regulated. Cytoskeletal reorganization was not observed during infection, suggesting that the interaction between actin and E protein has a cell type specific component. PMID:27010925

  16. Actin Interacts with Dengue Virus 2 and 4 Envelope Proteins

    PubMed Central

    Jitoboam, Kunlakanya; Phaonakrop, Narumon; Libsittikul, Sirikwan; Thepparit, Chutima; Roytrakul, Sittiruk; Smith, Duncan R.

    2016-01-01

    Dengue virus (DENV) remains a significant public health problem in many tropical and sub-tropical countries worldwide. The DENV envelope (E) protein is the major antigenic determinant and the protein that mediates receptor binding and endosomal fusion. In contrast to some other DENV proteins, relatively few cellular interacting proteins have been identified. To address this issue a co-immuoprecipitation strategy was employed. The predominant co-immunoprecipitating proteins identified were actin and actin related proteins, however the results suggested that actin was the only bona fide interacting partner. Actin was shown to interact with the E protein of DENV 2 and 4, and the interaction between actin and DENV E protein was shown to occur in a truncated DENV consisting of only domains I and II. Actin was shown to decrease during infection, but this was not associated with a decrease in gene transcription. Actin-related proteins also showed a decrease in expression during infection that was not transcriptionally regulated. Cytoskeletal reorganization was not observed during infection, suggesting that the interaction between actin and E protein has a cell type specific component. PMID:27010925

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

    PubMed

    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 shaping

  18. 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

    2014-07-01

    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.

  19. 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

  20. 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

  1. 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

  2. Predicting Protein-Protein Interactions from the Molecular to the Proteome Level.

    PubMed

    Keskin, Ozlem; Tuncbag, Nurcan; Gursoy, Attila

    2016-04-27

    Identification of protein-protein interactions (PPIs) is at the center of molecular biology considering the unquestionable role of proteins in cells. Combinatorial interactions result in a repertoire of multiple functions; hence, knowledge of PPI and binding regions naturally serve to functional proteomics and drug discovery. Given experimental limitations to find all interactions in a proteome, computational prediction/modeling of protein interactions is a prerequisite to proceed on the way to complete interactions at the proteome level. This review aims to provide a background on PPIs and their types. Computational methods for PPI predictions can use a variety of biological data including sequence-, evolution-, expression-, and structure-based data. Physical and statistical modeling are commonly used to integrate these data and infer PPI predictions. We review and list the state-of-the-art methods, servers, databases, and tools for protein-protein interaction prediction. PMID:27074302

  3. 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.

  4. Matrix gamma-carboxyglutamic acid protein (MGP) G-7A and T-138C gene polymorphisms in Indian (Mayo and Teenek) and Mestizo populations from Mexico.

    PubMed

    Hernández-Pacheco, Guadalupe; Murguía, Luis Enrique; Rodríguez-Pérez, José Manuel; Fragoso, José Manuel; Pérez-Vielma, Nadia; Martínez-Rodríguez, Nancy; Granados, Julio; Vargas-Alarcón, Gilberto

    2005-06-01

    Matrix gamma-carboxyglutamic acid protein (MGP) genotypes (G-7A and T-138C) were determined in 266 individuals from three Mexican populations. Mexicans showed increased frequencies of the G-7A G allele and the G7-A GG genotype compared to Europeans. For the T-138C genotype, we found differences among the Mexicans. This study could help to define the significance of MGP polymorphisms as genetic markers in Amerindian populations.

  5. Characterization of interactions between inclusion membrane proteins from Chlamydia trachomatis

    PubMed Central

    Gauliard, Emilie; Ouellette, Scot P.; Rueden, Kelsey J.; Ladant, Daniel

    2015-01-01

    Chlamydiae are obligate intracellular pathogens of eukaryotes. The bacteria grow in an intracellular vesicle called an inclusion, the membrane of which is heavily modified by chlamydial proteins called Incs (Inclusion membrane proteins). Incs represent 7–10% of the genomes of Chlamydia and, given their localization at the interface between the host and the pathogen, likely play a key role in the development and pathogenesis of the bacterium. However, their functions remain largely unknown. Here, we characterized the interaction properties between various Inc proteins of C. trachomatis, using a bacterial two-hybrid (BACTH) method suitable for detecting interactions between integral membrane proteins. To validate this approach, we first examined the oligomerization properties of the well-characterized IncA protein and showed that both the cytoplasmic domain and the transmembrane region independently contribute to IncA oligomerization. We then analyzed a set of Inc proteins and identified novel interactions between these components. Two small Incs, IncF, and Ct222, were found here to interact with many other Inc proteins and may thus represent interaction nodes within the inclusion membrane. Our data suggest that the Inc proteins may assemble in the membrane of the inclusion to form specific multi-molecular complexes in an hierarchical and temporal manner. These studies will help to better define the putative functions of the Inc proteins in the infectious process of Chlamydia. PMID:25717440

  6. Predicting the Binding Patterns of Hub Proteins: A Study Using Yeast Protein Interaction Networks

    PubMed Central

    Andorf, Carson M.; Honavar, Vasant; Sen, Taner Z.

    2013-01-01

    Background Protein-protein interactions are critical to elucidating the role played by individual proteins in important biological pathways. Of particular interest are hub proteins that can interact with large numbers of partners and often play essential roles in cellular control. Depending on the number of binding sites, protein hubs can be classified at a structural level as singlish-interface hubs (SIH) with one or two binding sites, or multiple-interface hubs (MIH) with three or more binding sites. In terms of kinetics, hub proteins can be classified as date hubs (i.e., interact with different partners at different times or locations) or party hubs (i.e., simultaneously interact with multiple partners). Methodology Our approach works in 3 phases: Phase I classifies if a protein is likely to bind with another protein. Phase II determines if a protein-binding (PB) protein is a hub. Phase III classifies PB proteins as singlish-interface versus multiple-interface hubs and date versus party hubs. At each stage, we use sequence-based predictors trained using several standard machine learning techniques. Conclusions Our method is able to predict whether a protein is a protein-binding protein with an accuracy of 94% and a correlation coefficient of 0.87; identify hubs from non-hubs with 100% accuracy for 30% of the data; distinguish date hubs/party hubs with 69% accuracy and area under ROC curve of 0.68; and SIH/MIH with 89% accuracy and area under ROC curve of 0.84. Because our method is based on sequence information alone, it can be used even in settings where reliable protein-protein interaction data or structures of protein-protein complexes are unavailable to obtain useful insights into the functional and evolutionary characteristics of proteins and their interactions. Availability We provide a web server for our three-phase approach: http://hybsvm.gdcb.iastate.edu. PMID:23431393

  7. 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.

  8. 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

  9. Visualizing an ultra-weak protein-protein interaction in phosphorylation signaling.

    PubMed

    Xing, Qiong; Huang, Peng; Yang, Ju; Sun, Jian-Qiang; Gong, Zhou; Dong, Xu; Guo, Da-Chuan; Chen, Shao-Min; Yang, Yu-Hong; Wang, Yan; Yang, Ming-Hui; Yi, Ming; Ding, Yi-Ming; Liu, Mai-Li; Zhang, Wei-Ping; Tang, Chun

    2014-10-20

    Proteins interact with each other to fulfill their functions. The importance of weak protein-protein interactions has been increasingly recognized. However, owing to technical difficulties, ultra-weak interactions remain to be characterized. Phosphorylation can take place via a K(D)≈25 mM interaction between two bacterial enzymes. Using paramagnetic NMR spectroscopy and with the introduction of a novel Gd(III)-based probe, we determined the structure of the resulting complex to atomic resolution. The structure accounts for the mechanism of phosphoryl transfer between the two enzymes and demonstrates the physical basis for their ultra-weak interaction. Further, molecular dynamics (MD) simulations suggest that the complex has a lifetime in the micro- to millisecond regimen. Hence such interaction is termed a fleeting interaction. From mathematical modeling, we propose that an ultra-weak fleeting interaction enables rapid flux of phosphoryl signal, providing a high effective protein concentration.

  10. The aromatic stacking interactions between proteins and their macromolecular ligands.

    PubMed

    Rahman, Mohammad Mizanur; Muhseen, Ziyad Tariq; Junaid, Muhammad; Zhang, Houjin

    2015-01-01

    Aromatic stacking interactions arise from the attractive force between the π-electron clouds in the neighboring aromatic groups. The aromatic stacking is common between proteins and small molecules. The stacking interactions at the interfaces of proteins and other macromolecules are relatively rare. However it contributes to a significant portion of the stabilizing forces. In the proteinprotein complexes, aromatic interactions are involved in the protein oligomerization, such as dimer, trimer and tetramer formation. Also, aromatic residues can bind to nanoparticles through stacking interactions which offer them stronger affinity than other residues. These interactions play crucial roles in proteinnanoparticle conjugation. In the protein-nucleotide complexes, the specific recognitions are realized through stacking interactions between aromatic residues and the bases in the nucleotides. Many nucleoproteins use aromatic stacking to recognize binding site on DNA or RNA. Stacking interactions are involved in the process of mismatch repair, strand separation, deadenylation, degradation and RNA cap binding. They are proved to be important for the stability of complexes. The aromatic stacking is also the underlying reasons of many fatal diseases such as Alzheimer, cancer and cardiovascular diseases. The chemicals that can block the stacking interactions could have potential pharmaceutical values. In this review, we summarize recent finding regarding the functions of aromatic stacking interactions in the protein-macromolecule complexes. Our aim is to understand the mechanisms underlying the stacking-mediated complex formation and facilitate the development of drugs and other bio-products.

  11. Metabotropic Glutamate Receptors and Interacting Proteins in Epileptogenesis.

    PubMed

    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

  12. Discovering novel protein-protein interactions by measuring the protein semantic similarity from the biomedical literature.

    PubMed

    Chiang, Jung-Hsien; Ju, Jiun-Huang

    2014-12-01

    Protein-protein interactions (PPIs) are involved in the majority of biological processes. Identification of PPIs is therefore one of the key aims of biological research. Although there are many databases of PPIs, many other unidentified PPIs could be buried in the biomedical literature. Therefore, automated identification of PPIs from biomedical literature repositories could be used to discover otherwise hidden interactions. Search engines, such as Google, have been successfully applied to measure the relatedness among words. Inspired by such approaches, we propose a novel method to identify PPIs through semantic similarity measures among protein mentions. We define six semantic similarity measures as features based on the page counts retrieved from the MEDLINE database. A machine learning classifier, Random Forest, is trained using the above features. The proposed approach achieve an averaged micro-F of 71.28% and an averaged macro-F of 64.03% over five PPI corpora, an improvement over the results of using only the conventional co-occurrence feature (averaged micro-F of 68.79% and an averaged macro-F of 60.49%). A relation-word reinforcement further improves the averaged micro-F to 71.3% and averaged macro-F to 65.12%. Comparing the results of the current work with other studies on the AIMed corpus (ranging from 77.58% to 85.1% in micro-F, 62.18% to 76.27% in macro-F), we show that the proposed approach achieves micro-F of 81.88% and macro-F of 64.01% without the use of sophisticated feature extraction. Finally, we manually examine the newly discovered PPI pairs based on a literature review, and the results suggest that our approach could extract novel protein-protein interactions.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. Improved method for evaluating the dead volume and protein-protein interactions by self-interaction chromatography.

    PubMed

    Binabaji, Elaheh; Rao, Suma; Zydney, Andrew L

    2013-10-01

    Self-interaction chromatography (SIC) is a well-established method for studying protein-protein interactions. The second virial coefficient in SIC is evaluated directly from the measured retention coefficient for the protein using a column packed with resin on which the same protein has been immobilized on the pore surface. One of the challenges in determining the retention coefficient is the evaluation of the dead volume, which is the retention volume that would be measured for a noninteracting solute with the same effective size as the protein of interest. Previous studies of SIC have used a "dead column" packed with the same resin but without the immobilized protein to evaluate the dead volume, but this creates several experimental and theoretical challenges. We have developed a new approach using a dextran standard with effective size equal to that of the protein (as determined by size exclusion chromatography). The second virial coefficient was evaluated for a monoclonal antibody over a range of buffer conditions using this new approach. The data were in good agreement with independent measurements obtained by membrane osmometry under conditions dominated by repulsive interactions. The simplicity and accuracy of this method should facilitate the use of self-interaction chromatography for quantifying protein-protein interactions.

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

    PubMed

    Lacomble, Sylvain; Portman, Neil; Gull, Keith

    2009-01-01

    We have conducted a protein interaction study of components within a specific sub-compartment of a eukaryotic flagellum. The trypanosome flagellum contains a para-crystalline extra-axonemal structure termed the paraflagellar rod (PFR) with around forty identified components. We have used a Gateway cloning approach coupled with yeast two-hybrid, RNAi and 2D DiGE to define a protein-protein interaction network taking place in this structure. We define two clusters of interactions; the first being characterised by two proteins with a shared domain which is not sufficient for maintaining the interaction. The other cohort is populated by eight proteins, a number of which possess a PFR domain and sub-populations of this network exhibit dependency relationships. Finally, we provide clues as to the structural organisation of the PFR at the molecular level. This multi-strand approach shows that protein interactome data can be generated for insoluble protein complexes. PMID:19888464

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

    PubMed

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

    2013-01-18

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

  20. 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

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

    PubMed

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

    2005-06-01

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

  2. Choosing negative examples for the prediction of protein-protein interactions

    PubMed Central

    Ben-Hur, Asa; Noble, William Stafford

    2006-01-01

    The protein-protein interaction networks of even well-studied model organisms are sketchy at best, highlighting the continued need for computational methods to help direct experimentalists in the search for novel interactions. This need has prompted the development of a number of methods for predicting protein-protein interactions based on various sources of data and methodologies. The common method for choosing negative examples for training a predictor of protein-protein interactions is based on annotations of cellular localization, and the observation that pairs of proteins that have different localization patterns are unlikely to interact. While this method leads to high quality sets of non-interacting proteins, we find that this choice can lead to biased estimates of prediction accuracy, because the constraints placed on the distribution of the negative examples makes the task easier. The effects of this bias are demonstrated in the context of both sequence-based and non-sequence based features used for predicting protein-protein interactions. PMID:16723005

  3. 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

  4. 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.

  5. 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.

  6. Characterization of the interactions between protein and carbon black.

    PubMed

    Chen, Tzu-Tao; Chuang, Kai-Jen; Chiang, Ling-Ling; Chen, Chun-Chao; Yeh, Chi-Tai; Wang, Liang-Shun; Gregory, Clive; Jones, Tim; BéruBé, Kelly; Lee, Chun-Nin; Chuang, Hsiao-Chi; Cheng, Tsun-Jen

    2014-01-15

    A considerable amount of studies have been conducted to investigate the interactions of biological fluids with nanoparticle surfaces, which exhibit a high affinity for proteins and particles. However, the mechanisms underlying these interactions have not been elucidated, particularly as they relate to human health. Using bovine serum albumin (BSA) and mice bronchoalveolar lavage fluid (BALF) as models for protein-particle conjugates, we characterized the physicochemical modifications of carbon blacks (CB) with 23nm or 65nm in diameter after protein treatment. Adsorbed BALF-containing proteins were quantified and identified by pathways, biological analyses and protein classification. Significant modifications of the physicochemistry of CB were induced by the addition of BSA. Enzyme modulators and hydrolase predominately interacted with CB, with protein-to-CB interactions that were associated with the coagulation pathways. Additionally, our results revealed that an acute-phase response could be activated by these proteins. With regard to human health, the present study revealed that the CB can react with proteins (∼55kDa and 70kDa) after inhalation and may modify the functional structures of lung proteins, leading to the activation of acute-inflammatory responses in the lungs. PMID:24291665

  7. Scalable prediction of compound-protein interactions using minwise hashing.

    PubMed

    Tabei, Yasuo; Yamanishi, Yoshihiro

    2013-01-01

    The identification of compound-protein interactions plays key roles in the drug development toward discovery of new drug leads and new therapeutic protein targets. There is therefore a strong incentive to develop new efficient methods for predicting compound-protein interactions on a genome-wide scale. In this paper we develop a novel chemogenomic method to make a scalable prediction of compound-protein interactions from heterogeneous biological data using minwise hashing. The proposed method mainly consists of two steps: 1) construction of new compact fingerprints for compound-protein pairs by an improved minwise hashing algorithm, and 2) application of a sparsity-induced classifier to the compact fingerprints. We test the proposed method on its ability to make a large-scale prediction of compound-protein interactions from compound substructure fingerprints and protein domain fingerprints, and show superior performance of the proposed method compared with the previous chemogenomic methods in terms of prediction accuracy, computational efficiency, and interpretability of the predictive model. All the previously developed methods are not computationally feasible for the full dataset consisting of about 200 millions of compound-protein pairs. The proposed method is expected to be useful for virtual screening of a huge number of compounds against many protein targets.

  8. Protein-protein interactions as a target for drugs in proteomics.

    PubMed

    Archakov, Alexander I; Govorun, Vadim M; Dubanov, Alexander V; Ivanov, Yuri D; Veselovsky, Alexander V; Lewi, Paul; Janssen, Paul

    2003-04-01

    Protein-protein interactions play a central role in numerous processes in the cell and are one of the main fields of functional proteomics. This review highlights the methods of bioinformatics and functional proteomics of protein-protein interaction investigation. The structures and properties of contact surfaces, forces involved in protein-protein interactions, kinetic and thermodynamic parameters of these reactions were considered. The properties of protein contact surfaces depend on their functions. The contact surfaces of permanent complexes resemble domain contacts or the protein core and it is reasonable to consider such complex formation as a continuation of protein folding. Characteristics of contact surfaces of temporary protein complexes share some similarities with active sites of enzymes. The contact surfaces of the temporary protein complexes have unique structure and properties and they are more conservative in comparison with active site of enzymes. So they represent prospective targets for a new generation of drugs. During the last decade, numerous investigations were undertaken to find or design small molecules that block protein dimerization or protein(peptide)-receptor interaction, or, on the contrary, to induce protein dimerization. PMID:12687606

  9. 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. .

  10. 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.

  11. 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/.

  12. Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

    DOE PAGESBeta

    Venkatraman, S.; 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.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

  13. 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.

  14. 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

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

    PubMed

    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

  16. 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.

  17. 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

  18. Biophysics of protein-DNA interactions and chromosome organization

    NASA Astrophysics Data System (ADS)

    Marko, John F.

    2015-01-01

    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.

  19. Proteins differentially interact with grapefruit furanocoumarins

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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. PMID:25873628

  5. 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

  6. 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.

  7. Genome-wide protein-protein interaction screening by protein-fragment complementation assay (PCA) in living cells.

    PubMed

    Rochette, Samuel; Diss, Guillaume; Filteau, Marie; Leducq, Jean-Baptiste; Dubé, Alexandre K; Landry, Christian R

    2015-01-01

    Proteins are the building blocks, effectors and signal mediators of cellular processes. A protein's function, regulation and localization often depend on its interactions with other proteins. Here, we describe a protocol for the yeast protein-fragment complementation assay (PCA), a powerful method to detect direct and proximal associations between proteins in living cells. The interaction between two proteins, each fused to a dihydrofolate reductase (DHFR) protein fragment, translates into growth of yeast strains in presence of the drug methotrexate (MTX). Differential fitness, resulting from different amounts of reconstituted DHFR enzyme, can be quantified on high-density colony arrays, allowing to differentiate interacting from non-interacting bait-prey pairs. The high-throughput protocol presented here is performed using a robotic platform that parallelizes mating of bait and prey strains carrying complementary DHFR-fragment fusion proteins and the survival assay on MTX. This protocol allows to systematically test for thousands of protein-protein interactions (PPIs) involving bait proteins of interest and offers several advantages over other PPI detection assays, including the study of proteins expressed from their endogenous promoters without the need for modifying protein localization and for the assembly of complex reporter constructs.

  8. 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

  9. 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

  10. Screening for in planta protein-protein interactions combining bimolecular fluorescence complementation with flow cytometry

    PubMed Central

    2012-01-01

    Understanding protein and gene function requires identifying interaction partners using biochemical, molecular or genetic tools. In plants, searching for novel protein-protein interactions is limited to protein purification assays, heterologous in vivo systems such as the yeast-two-hybrid or mutant screens. Ideally one would be able to search for novel protein partners in living plant cells. We demonstrate that it is possible to screen for novel protein-protein interactions from a random library in protoplasted Arabidopsis plant cells and recover some of the interacting partners. Our screen is based on capturing the bi-molecular complementation of mYFP between an YN-bait fusion partner and a completely random prey YC-cDNA library with FACS. The candidate interactions were confirmed using in planta BiFC assays and in planta FRET-FLIM assays. From this work, we show that the well characterized protein Calcium Dependent Protein Kinase 3 (CPK3) interacts with APX3, HMGB5, ORP2A and a ricin B-related lectin domain containing protein At2g39050. This is one of the first randomin planta screens to be successfully employed. PMID:22789293

  11. 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.

  12. 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 practical…

  13. 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.

  14. Analysis of Lipolytic Protein Trafficking and Interactions in Adipocytes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This work examined the colocalization, trafficking, and interactions of key proteins involved in lipolysis during brief cAMP-dependent protein kinase A (PKA) activation. Double label immunofluorescence analysis of 3T3-L1 adipocytes indicated that PKA activation increases the translocation of hormon...

  15. Relevance Rank Platform (RRP) for Functional Filtering of High Content Protein-Protein Interaction Data.

    PubMed

    Pokharel, Yuba Raj; Saarela, Jani; Szwajda, Agnieszka; Rupp, Christian; Rokka, Anne; Lal Kumar Karna, Shibendra; Teittinen, Kaisa; Corthals, Garry; Kallioniemi, Olli; Wennerberg, Krister; Aittokallio, Tero; Westermarck, Jukka

    2015-12-01

    High content protein interaction screens have revolutionized our understanding of protein complex assembly. However, one of the major challenges in translation of high content protein interaction data is identification of those interactions that are functionally relevant for a particular biological question. To address this challenge, we developed a relevance ranking platform (RRP), which consist of modular functional and bioinformatic filters to provide relevance rank among the interactome proteins. We demonstrate the versatility of RRP to enable a systematic prioritization of the most relevant interaction partners from high content data, highlighted by the analysis of cancer relevant protein interactions for oncoproteins Pin1 and PME-1. We validated the importance of selected interactions by demonstration of PTOV1 and CSKN2B as novel regulators of Pin1 target c-Jun phosphorylation and reveal previously unknown interacting proteins that may mediate PME-1 effects via PP2A-inhibition. The RRP framework is modular and can be modified to answer versatile research problems depending on the nature of the biological question under study. Based on comparison of RRP to other existing filtering tools, the presented data indicate that RRP offers added value especially for the analysis of interacting proteins for which there is no sufficient prior knowledge available. Finally, we encourage the use of RRP in combination with either SAINT or CRAPome computational tools for selecting the candidate interactors that fulfill the both important requirements, functional relevance, and high confidence interaction detection.

  16. 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

  17. 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

  18. Computational Prediction of Protein–Protein Interaction Networks: Algo-rithms and Resources

    PubMed Central

    Zahiri, Javad; Bozorgmehr, Joseph Hannon; Masoudi-Nejad, Ali

    2013-01-01

    Protein interactions play an important role in the discovery of protein functions and pathways in biological processes. This is especially true in case of the diseases caused by the loss of specific protein-protein interactions in the organism. The accuracy of experimental results in finding protein-protein interactions, however, is rather dubious and high throughput experimental results have shown both high false positive beside false negative information for protein interaction. Computational methods have attracted tremendous attention among biologists because of the ability to predict protein-protein interactions and validate the obtained experimental results. In this study, we have reviewed several computational methods for protein-protein interaction prediction as well as describing major databases, which store both predicted and detected protein-protein interactions, and the tools used for analyzing protein interaction networks and improving protein-protein interaction reliability. PMID:24396273

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

    PubMed

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

    2016-01-01

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

  20. Protein fragment bimolecular fluorescence complementation analyses for the in vivo study of protein-protein interactions and cellular protein complex localizations

    PubMed Central

    Waadt, Rainer; Schlücking, Kathrin; Schroeder, Julian I.; Kudla, Jörg

    2014-01-01

    Summary The analyses of protein-protein interactions is crucial for understanding cellular processes including signal transduction, protein trafficking and movement. Protein fragment complementation assays are based on the reconstitution of protein function when non-active protein fragments are brought together by interacting proteins that were genetically fused to these protein fragments. Bimolecular fluorescence complementation (BiFC) relies on the reconstitution of fluorescent proteins and enables both the analysis of protein-protein interactions and the visualization of protein complex formations in vivo. Transient expression of proteins is a convenient approach to study protein functions in planta or in other organisms, and minimizes the need for time-consuming generation of stably expressing transgenic organisms. Here we describe protocols for BiFC analyses in Nicotiana benthamiana and Arabidopsis thaliana leaves transiently transformed by Agrobacterium infiltration. Further we discuss different BiFC applications and provide examples for proper BiFC analyses in planta. PMID:24057390

  1. Mechanisms of Peroxynitrite Interactions with Heme Proteins

    PubMed Central

    Su, Jia; Groves, John T.

    2010-01-01

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

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

    PubMed Central

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

    2015-01-01

    PDZ domains in general, and those of PSD-95 in particular, are emerging as promising drug targets for diseases such as ischemic stroke. We have previously shown that dimeric ligands that simultaneously target PDZ1 and PDZ2 of PSD-95 are highly potent inhibitors of PSD-95. However, PSD-95 and the related MAGUK proteins contain three consecutive PDZ domains, hence we envisioned that targeting all three PDZ domains simultaneously would lead to more potent and potentially more specific interactions with the MAGUK proteins. Here we describe the design, synthesis and characterization of a series of trimeric ligands targeting all three PDZ domains of PSD-95 and the related MAGUK proteins, PSD-93, SAP-97 and SAP-102. Using our dimeric ligands targeting the PDZ1-2 tandem as starting point, we designed novel trimeric ligands by introducing a PDZ3-binding peptide moiety via a cysteine-derivatized NPEG linker. The trimeric ligands generally displayed increased affinities compared to the dimeric ligands in fluorescence polarization binding experiments and optimized trimeric ligands showed low nanomolar inhibition towards the four MAGUK proteins, thus being the most potent inhibitors described. Kinetic experiments using stopped-flow spectrometry showed that the increase in affinity is caused by a decrease in the dissociation rate of the trimeric ligand as compared to the dimeric ligands, likely reflecting the lower probability of simultaneous dissociation of all three PDZ ligands. Thus, we have provided novel inhibitors of the MAGUK proteins with exceptionally high affinity, which can be used to further elucidate the therapeutic potential of these proteins. PMID:25658767

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

    PubMed

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

    2015-01-01

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

  4. Neuronal cell-surface protein neurexin 1 interaction with multi-PDZ domain protein MUPP1.

    PubMed

    Jang, Won Hee; Choi, Sun Hee; Jeong, Joo Young; Park, Jung-Hwa; Kim, Sang-Jin; Seog, Dae-Hyun

    2014-01-01

    Location of membrane proteins is often stabilized by PDZ domain-containing scaffolding proteins. Using the yeast two-hybrid screening, we found that neurexin 1 interacted with multi-PDZ domain protein 1 (MUPP1) through PDZ domain. Neurexin 2 and 3 also interacted with MUPP1. MUPP1 and neurexin 1 were co-localized in cultured cells. These results suggest a novel mechanism for localizing neurexin 1 to synaptic sites.

  5. Computational large-scale mapping of protein-protein interactions using structural complexes.

    PubMed

    Shoemaker, Benjamin; Wuchty, Stefan; Panchenko, Anna R

    2013-01-01

    Although the identification of protein interactions by high-throughput methods progresses at a fast pace, "interactome" datasets still suffer from high rates of false positives and low coverage. To map the interactome of any organism, this unit presents a computational framework to predict protein-protein or gene-gene interactions utilizing experimentally determined evidence of structural complexes, atomic details of binding interfaces and evolutionary conservation.

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

    PubMed

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

    2013-03-01

    Supramolecular chemistry has recently emerged as a promising way to modulate protein functions, but devising molecules that will interact with a protein in the desired manner is difficult as many competing interactions exist in a biological environment (with solvents, salts or different sites for the target biomolecule). We now show that lysine-specific molecular tweezers bind to a 14-3-3 adapter protein and modulate its interaction with partner proteins. The tweezers inhibit binding between the 14-3-3 protein and two partner proteins--a phosphorylated (C-Raf) protein and an unphosphorylated one (ExoS)--in a concentration-dependent manner. Protein crystallography shows that this effect arises from the binding of the tweezers to a single surface-exposed lysine (Lys214) of the 14-3-3 protein in the proximity of its central channel, which normally binds the partner proteins. A combination of structural analysis and computer simulations provides rules for the tweezers' binding preferences, thus allowing us to predict their influence on this type of protein-protein interactions. PMID:23422566

  7. The Rift Valley Fever virus protein NSm and putative cellular protein interactions

    PubMed Central

    2012-01-01

    Rift Valley Fever is an infectious viral disease and an emerging problem in many countries of Africa and on the Arabian Peninsula. The causative virus is predominantly transmitted by mosquitoes and high mortality and abortion rates characterize outbreaks in animals while symptoms ranging from mild to life-threatening encephalitis and hemorrhagic fever are noticed among infected humans. For a better prevention and treatment of the infection, an increased knowledge of the infectious process of the virus is required. The focus of this work was to identify protein-protein interactions between the non-structural protein (NSm), encoded by the M-segment of the virus, and host cell proteins. This study was initiated by screening approximately 26 million cDNA clones of a mouse embryonic cDNA library for interactions with the NSm protein using a yeast two-hybrid system. We have identified nine murine proteins that interact with NSm protein of Rift Valley Fever virus, and the putative protein-protein interactions were confirmed by growth selection procedures and β-gal activity measurements. Our results suggest that the cleavage and polyadenylation specificity factor subunit 2 (Cpsf2), the peptidyl-prolyl cis-trans isomerase (cyclophilin)-like 2 protein (Ppil2), and the synaptosome-associated protein of 25 kDa (SNAP-25) are the most promising targets for the NSm protein of the virus during an infection. PMID:22838834

  8. Quantitative analysis of protein-ligand interactions by NMR.

    PubMed

    Furukawa, Ayako; Konuma, Tsuyoshi; Yanaka, Saeko; Sugase, Kenji

    2016-08-01

    Protein-ligand interactions have been commonly studied through static structures of the protein-ligand complex. Recently, however, there has been increasing interest in investigating the dynamics of protein-ligand interactions both for fundamental understanding of the underlying mechanisms and for drug development. NMR is a versatile and powerful tool, especially because it provides site-specific quantitative information. NMR has widely been used to determine the dissociation constant (KD), in particular, for relatively weak interactions. The simplest NMR method is a chemical-shift titration experiment, in which the chemical-shift changes of a protein in response to ligand titration are measured. There are other quantitative NMR methods, but they mostly apply only to interactions in the fast-exchange regime. These methods derive the dissociation constant from population-averaged NMR quantities of the free and bound states of a protein or ligand. In contrast, the recent advent of new relaxation-based experiments, including R2 relaxation dispersion and ZZ-exchange, has enabled us to obtain kinetic information on protein-ligand interactions in the intermediate- and slow-exchange regimes. Based on R2 dispersion or ZZ-exchange, methods that can determine the association rate, kon, dissociation rate, koff, and KD have been developed. In these approaches, R2 dispersion or ZZ-exchange curves are measured for multiple samples with different protein and/or ligand concentration ratios, and the relaxation data are fitted to theoretical kinetic models. It is critical to choose an appropriate kinetic model, such as the two- or three-state exchange model, to derive the correct kinetic information. The R2 dispersion and ZZ-exchange methods are suitable for the analysis of protein-ligand interactions with a micromolar or sub-micromolar dissociation constant but not for very weak interactions, which are typical in very fast exchange. This contrasts with the NMR methods that are used

  9. [Study of decision tree in the application of predicting protein-protein interactions].

    PubMed

    Guo, Xiaolong; Jiang, Yan; Qui, Lu

    2013-10-01

    Proteins are the final executive actor of cell viability and function. Protein-protein interactions determine the complexity of the organism. Research on the protein interactions can help us understand the function of the protein at the molecular level, learn the cell growth, development, differentiation, apoptosis and understand biological regulation mechanisms and other activities. They are essential for understanding the pathologies of diseases and helpful in the prevention and treatment of diseases, as well as in the development of new drugs. In this paper, we employ the single decision-tree classification model to predict protein-protein interactions in the yeast. The original data came from the existing literature. Using software Clementine, this paper analyzes how these attributes affect the accuracy of the model by adjusting the predicted attributes. The result shows that a single decision tree is a good classification model and it has higher accuracy compared to those in the previous researches.

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

    PubMed

    Duncan, R R

    2006-11-01

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

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

    SciTech Connect

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

    2004-05-25

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

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

    PubMed

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

    2014-05-01

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

  13. AKAP350 Interaction with cdc42 Interacting Protein 4 at the Golgi Apparatus

    PubMed Central

    Larocca, M. Cecilia; Shanks, Ryan A.; Tian, Lan; Nelson, David L.; Stewart, Donn M.; Goldenring, James R.

    2004-01-01

    The A kinase anchoring protein 350 (AKAP350) is a multiply spliced type II protein kinase A anchoring protein that localizes to the centrosomes in most cells and to the Golgi apparatus in epithelial cells. In the present study, we sought to identify AKAP350 interacting proteins that could yield insights into AKAP350 function at the Golgi apparatus. Using yeast two-hybrid and pull-down assays, we found that AKAP350 interacts with a family of structurally related proteins, including FBP17, FBP17b, and cdc42 interacting protein 4 (CIP4). CIP4 interacts with the GTP-bound form of cdc42, with the Wiscott Aldrich Syndrome group of proteins, and with microtubules, and exerts regulatory effects on cytoskeleton and membrane trafficking. CIP4 is phosphorylated by protein kinase A in vitro, and elevation of intracellular cyclic AMP with forskolin stimulates in situ phosphorylation of CIP4. Our results indicate that CIP4 interacts with AKAP350 at the Golgi apparatus and that either disruption of this interaction by expressing the CIP4 binding domain in AKAP350, or reduction of AKAP350 expression by RNA interference leads to changes in Golgi structure. The results suggest that AKAP350 and CIP4 influence the maintenance of normal Golgi apparatus structure. PMID:15047863

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

    PubMed

    Haberkant, Per; van Meer, Gerrit

    2009-08-01

    Photoactivatable groups meeting the criterion of minimal perturbance allow the investigation of interactions in biological samples. Here, we review the application of photoactivatable groups in lipids enabling the study of protein-lipid interactions in (biological) membranes. The chemistry of various photoactivatable groups is summarized and the specificity of the interactions detected is discussed. The recent introduction of 'click chemistry' in photocrosslinking of membrane proteins by photo-activatable lipids opens new possibilities for the analysis of crosslinked products and will help to close the gap between proteomics and lipidomics. PMID:19426134

  15. Interaction of the tobacco lectin with histone proteins.

    PubMed

    Schouppe, Dieter; Ghesquière, Bart; Menschaert, Gerben; De Vos, Winnok H; Bourque, Stéphane; Trooskens, Geert; Proost, Paul; Gevaert, Kris; Van Damme, Els J M

    2011-03-01

    The tobacco (Nicotiana tabacum) agglutinin or Nictaba is a member of a novel class of plant lectins residing in the nucleus and the cytoplasm of tobacco cells. Since tobacco lectin expression is only observed after the plant has been subjected to stress situations such as jasmonate treatment or insect attack, Nictaba is believed to act as a signaling protein involved in the stress physiology of the plant. In this paper, a nuclear proteomics approach was followed to identify the binding partners for Nictaba in the nucleus and the cytoplasm of tobacco cv Xanthi cells. Using lectin affinity chromatography and pull-down assays, it was shown that Nictaba interacts primarily with histone proteins. Binding of Nictaba with histone H2B was confirmed in vitro using affinity chromatography of purified calf thymus histone proteins on a Nictaba column. Elution of Nictaba-interacting histone proteins was achieved with 1 m N-acetylglucosamine (GlcNAc). Moreover, mass spectrometry analyses indicated that the Nictaba-interacting histone proteins are modified by O-GlcNAc. Since the lectin-histone interaction was shown to be carbohydrate dependent, it is proposed that Nictaba might fulfill a signaling role in response to stress by interacting with O-GlcNAcylated proteins in the plant cell nucleus. PMID:21224338

  16. Plasmonics for the study of metal ion-protein interactions.

    PubMed

    Grasso, Giuseppe; Spoto, Giuseppe

    2013-02-01

    The study of metal-protein interactions is an expanding field of research investigated by bioinorganic chemists as it has wide applications in biological systems. Very recently, it has been reported that it is possible to study metal-protein interactions by immobilizing biomolecules on metal surfaces and applying experimental approaches based on plasmonics which have usually been used to investigate protein-protein interactions. This is possible because the electronic structure of metals generates plasmons whose properties can be exploited to obtain information from biomolecules that interact not only with other molecules but also with ions in solution. One major challenge of such approaches is to immobilize the protein to be studied on a metal surface with preserved native structure. This review reports and discusses all the works that deal with such an expanding new field of application of plasmonics with specific attention to surface plasmon resonance, highlighting the advantages and drawbacks of such approaches in comparison with other experimental techniques traditionally used to study metal-protein interactions.

  17. DAXX is a new AIRE-interacting protein.

    PubMed

    Meloni, Alessandra; Meloni, Allesandra; Fiorillo, Edoardo; Corda, Denise; Incani, Federica; Serra, Maria Luisa; Contini, Antonella; Cao, Antonio; Rosatelli, Maria Cristina

    2010-04-23

    The AIRE protein plays a remarkable role as a regulator of central tolerance by controlling the promiscuous expression of tissue-specific antigens in thymic medullary epithelial cells. Defects in the AIRE gene cause the autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy, a rare disease frequent in Iranian Jews, Finns, and Sardinian population. To this day, the precise function of the AIRE protein in regulating transcription and its interacting proteins has yet to be entirely clarified. The knowledge of novel AIRE interactors and their precise role will improve our knowledge of its biological activity and address some of the foremost autoimmunity-related questions. In this study, we have used a yeast two-hybrid system to identify AIRE-interacting proteins. This approach led us to the discovery of a new AIRE-interacting protein called DAXX. The protein is known to be a multifunctional adaptor with functions both in apoptosis and in transcription regulation pathways. The interaction between AIRE and DAXX has been validated by in vivo coimmunoprecipitation analysis and colocalization study in mammalian cells. The interaction has been further confirmed by showing in transactivation assays that DAXX exerts a strong repressive role on the transcriptional activity of AIRE.

  18. Transcriptome-wide ribonuclease-mediated protein footprinting to identify RNA-protein interaction sites.

    PubMed

    Silverman, Ian M; Gregory, Brian D

    2015-01-15

    RNA-binding proteins (RBPs) are intimately involved in all aspects of RNA processing and regulation and are linked to neurodegenerative diseases and cancer. Therefore, investigating the relationship between RBPs and their RNA targets is critical for a broader understanding of post-transcriptional regulation in normal and disease processes. The majority of approaches to study RNA-protein interactions interrogate only individual RBPs. However, there are hundreds of these proteins encoded in the human genome, and each cell type expresses a different repertoire, greatly limiting the ability of current methods to capture the global landscape of RNA-protein interactions. To address this gap, we and others have recently developed methods to globally identify regions of RNAs that are bound by proteins in an unbiased manner. Here, we describe a detailed protocol for performing our ribonuclease-mediated protein footprint sequencing approach, termed protein interaction profile sequencing (PIP-seq). In this protocol, RNA-protein interactions are stabilized by cross-linking, and unbound regions are digested with ribonucleases (RNases), leaving only the protein-bound regions intact. To control for RNase insensitive regions, proteins are first denatured and degraded, then protein-depleted RNAs are subjected to RNase treatment. After high-throughput sequencing of the remaining fragments, peak calling is performed to identify protein-protected sites (PPSs). We describe the application of this protocol to a human embryonic kidney cell line (HEK293T) and perform basic quality control, reproducibility, and benchmarking analyses. Finally, we delineate the landscape of protein-interactions in HEK293T cells, underscoring the value of this approach. Future applications of this method to study the dynamics of RNA-protein interactions in developmental and disease processes will help to further uncover the role of RBPs in post-transcriptional regulation.

  19. Transcriptome-wide ribonuclease-mediated protein footprinting to identify RNA-protein interaction sites.

    PubMed

    Silverman, Ian M; Gregory, Brian D

    2015-01-15

    RNA-binding proteins (RBPs) are intimately involved in all aspects of RNA processing and regulation and are linked to neurodegenerative diseases and cancer. Therefore, investigating the relationship between RBPs and their RNA targets is critical for a broader understanding of post-transcriptional regulation in normal and disease processes. The majority of approaches to study RNA-protein interactions interrogate only individual RBPs. However, there are hundreds of these proteins encoded in the human genome, and each cell type expresses a different repertoire, greatly limiting the ability of current methods to capture the global landscape of RNA-protein interactions. To address this gap, we and others have recently developed methods to globally identify regions of RNAs that are bound by proteins in an unbiased manner. Here, we describe a detailed protocol for performing our ribonuclease-mediated protein footprint sequencing approach, termed protein interaction profile sequencing (PIP-seq). In this protocol, RNA-protein interactions are stabilized by cross-linking, and unbound regions are digested with ribonucleases (RNases), leaving only the protein-bound regions intact. To control for RNase insensitive regions, proteins are first denatured and degraded, then protein-depleted RNAs are subjected to RNase treatment. After high-throughput sequencing of the remaining fragments, peak calling is performed to identify protein-protected sites (PPSs). We describe the application of this protocol to a human embryonic kidney cell line (HEK293T) and perform basic quality control, reproducibility, and benchmarking analyses. Finally, we delineate the landscape of protein-interactions in HEK293T cells, underscoring the value of this approach. Future applications of this method to study the dynamics of RNA-protein interactions in developmental and disease processes will help to further uncover the role of RBPs in post-transcriptional regulation. PMID:25448484

  20. High Throughput Screening Method to Explore Protein Interactions with Nanoparticles

    PubMed Central

    Nasir, Irem; Fatih, Warda; Svensson, Anja; Radu, Dennis; Linse, Sara; Cabaleiro Lago, Celia; Lundqvist, Martin

    2015-01-01

    The interactions of biological macromolecules with nanoparticles underlie a wide variety of current and future applications in the fields of biotechnology, medicine and bioremediation. The same interactions are also responsible for mediating potential biohazards of nanomaterials. Some applications require that proteins adsorb to the nanomaterial and that the protein resists or undergoes structural rearrangements. This article presents a screening method for detecting nanoparticle-protein partners and conformational changes on time scales ranging from milliseconds to days. Mobile fluorophores are used as reporters to study the interaction between proteins and nanoparticles in a high-throughput manner in multi-well format. Furthermore, the screening method may reveal changes in colloidal stability of nanomaterials depending on the physicochemical conditions. PMID:26313757

  1. High Throughput Screening Method to Explore Protein Interactions with Nanoparticles.

    PubMed

    Nasir, Irem; Fatih, Warda; Svensson, Anja; Radu, Dennis; Linse, Sara; Cabaleiro Lago, Celia; Lundqvist, Martin

    2015-01-01

    The interactions of biological macromolecules with nanoparticles underlie a wide variety of current and future applications in the fields of biotechnology, medicine and bioremediation. The same interactions are also responsible for mediating potential biohazards of nanomaterials. Some applications require that proteins adsorb to the nanomaterial and that the protein resists or undergoes structural rearrangements. This article presents a screening method for detecting nanoparticle-protein partners and conformational changes on time scales ranging from milliseconds to days. Mobile fluorophores are used as reporters to study the interaction between proteins and nanoparticles in a high-throughput manner in multi-well format. Furthermore, the screening method may reveal changes in colloidal stability of nanomaterials depending on the physicochemical conditions. PMID:26313757

  2. Molecular beacons for protein-DNA interaction studies.

    PubMed

    Li, Jun; Cao, Zehui Charles; Tang, Zhiwen; Wang, Kemin; Tan, Weihong

    2008-01-01

    Real-time monitoring of DNA-protein interactions involving molecular beacon (MB) and molecular beacon aptamer (MBA) was discussed in this chapter. MBs are single-stranded oligonucleotide probes with a hairpin structure. MBs have been designed for oligonucleotide recognition and protein-DNA interaction studies. Real-time monitoring of enzymatic reactions, such as cleavage, ligation, and phosphorylation of single-stranded DNA by specific enzyme, has been studied using MBs. Meanwhile, a new generation of molecular probes, MBA, was designed by combining the excellent signal transduction properties of MBs with the specificity of aptamers for protein recognition. Two different aptamers, the one for thrombin and that for platelet-derived growth factor, have been successfully used to construct MBA probes. The interaction between the proteins and the MBA probes was investigated by fluorescence resonance energy transfer, fluorescence anisotropy, and time-resolved fluorescence. This chapter has reviewed our recent progress in this area.

  3. Self-interaction chromatography of proteins on a microfluidic monolith

    PubMed Central

    Martin, Cristina; Lenhoff, Abraham M.

    2010-01-01

    A novel miniaturized system has been developed for measuring protein-protein interactions in solution with high efficiency and speed, and minimal use of protein. A chromatographic monolith synthesized in a capillary is used in the method to make interaction measurements by self-interaction chromatography (SIC) in a manner that, compared to column methods, is more efficient as well as more readily practicable even if only small amounts of protein are available. The microfluidic monolith requires much less protein for both column synthesis and the chromatographic measurements than a conventional SIC system, and in addition offers improved mass transfer and hence higher chromatographic efficiency than for previous SIC miniaturization systems. Protein self-interactions for catalase as a model protein, quantified by measurement of second virial coefficients, B22, were determined by SIC and follow trends that are consistent with previously reported values. Different column derivatization conditions were studied in order to optimize the chromatographic behavior of the microfluidic system for SIC measurements. Chromatographic sensitivity can be further increased by using different column synthesis conditions. PMID:21258647

  4. On the surface interactions of proteins with lignin.

    PubMed

    Salas, Carlos; Rojas, Orlando J; Lucia, Lucian A; Hubbe, Martin A; Genzer, Jan

    2013-01-01

    Lignins are used often in formulations involving proteins but little is known about the surface interactions between these important biomacromolecules. In this work, we investigate the interactions at the solid-liquid interface of lignin with the two main proteins in soy, glycinin (11S) and β-conglycinin (7S). The extent of adsorption of 11S and 7S onto lignin films and the degree of hydration of the interfacial layers is quantified via Quartz crystal microgravimetry (QCM) and surface plasmon resonance (SPR). Solution ionic strength and protein denaturation (2-mercaptoethanol and urea) critically affect the adsorption process as protein molecules undergo conformational changes and their hydrophobic or hydrophilic amino acid residues interact with the surrounding medium. In general, the adsorption of the undenatured proteins onto lignin is more extensive compared to that of the denatured biomolecules and a large amount of water is coupled to the adsorbed molecules. The reduction in water contact angle after protein adsorption (by ~40° and 35° for undenatured 11S and 7S, respectively) is explained by strong nonspecific interactions between soy proteins and lignin. PMID:23234476

  5. Evidence for the interaction of the regulatory protein Ki-1/57 with p53 and its interacting proteins

    SciTech Connect

    Nery, Flavia C.; Rui, Edmilson; Kuniyoshi, Tais M.; Kobarg, Joerg . E-mail: jkobarg@lnls.br

    2006-03-17

    Ki-1/57 is a cytoplasmic and nuclear phospho-protein of 57 kDa and interacts with the adaptor protein RACK1, the transcription factor MEF2C, and the chromatin remodeling factor CHD3, suggesting that it might be involved in the regulation of transcription. Here, we describe yeast two-hybrid studies that identified a total of 11 proteins interacting with Ki-1/57, all of which interact or are functionally associated with p53 or other members of the p53 family of proteins. We further found that Ki-1/57 is able to interact with p53 itself in the yeast two-hybrid system when the interaction was tested directly. This interaction could be confirmed by pull down assays with purified proteins in vitro and by reciprocal co-immunoprecipitation assays from the human Hodgkin analogous lymphoma cell line L540. Furthermore, we found that the phosphorylation of p53 by PKC abolishes its interaction with Ki-1/57 in vitro.

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

    PubMed

    Zhang, Shu-Bo; Tang, Qiang-Rong

    2016-07-21

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

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

    PubMed

    Zhang, Shu-Bo; Tang, Qiang-Rong

    2016-07-21

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

  8. Predicting direct protein interactions from affinity purification mass spectrometry data

    PubMed Central

    2010-01-01

    Background Affinity purification followed by mass spectrometry identification (AP-MS) is an increasingly popular approach to observe protein-protein interactions (PPI) in vivo. One drawback of AP-MS, however, is that it is prone to detecting indirect interactions mixed with direct physical interactions. Therefore, the ability to distinguish direct interactions from indirect ones is of much interest. Results We first propose a simple probabilistic model for the interactions captured by AP-MS experiments, under which the problem of separating direct interactions from indirect ones is formulated. Then, given idealized quantitative AP-MS data, we study the problem of identifying the most likely set of direct interactions that produced the observed data. We address this challenging graph theoretical problem by first characterizing signatures that can identify weakly connected nodes as well as dense regions of the network. The rest of the direct PPI network is then inferred using a genetic algorithm. Our algorithm shows good performance on both simulated and biological networks with very high sensitivity and specificity. Then the algorithm is used to predict direct interactions from a set of AP-MS PPI data from yeast, and its performance is measured against a high-quality interaction dataset. Conclusions As the sensitivity of AP-MS pipeline improves, the fraction of indirect interactions detected will also increase, thereby making the ability to distinguish them even more desirable. Despite the simplicity of our model for indirect interactions, our method provides a good performance on the test networks. PMID:21034440

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

    PubMed

    Bornert, Olivier; Møller, Thor C; Boeuf, Julien; Candusso, Marie-Pierre; Wagner, Renaud; Martinez, Karen L; Simonin, Frederic

    2013-01-01

    GPCR desensitization and down-regulation are considered key molecular events underlying the development of tolerance in vivo. Among the many regulatory proteins that are involved in these complex processes, GASP-1 have been shown to participate to the sorting of several receptors toward the degradation pathway. This protein belongs to the recently identified GPCR-associated sorting proteins (GASPs) family that comprises ten members for which structural and functional details are poorly documented. We present here a detailed structure-function relationship analysis of the molecular interaction between GASPs and a panel of GPCRs. In a first step, GST-pull down experiments revealed that all the tested GASPs display significant interactions with a wide range of GPCRs. Importantly, the different GASP members exhibiting the strongest interaction properties were also characterized by the presence of a small, highly conserved and repeated "GASP motif" of 15 amino acids. We further showed using GST-pull down, surface plasmon resonance and co-immunoprecipitation experiments that the central domain of GASP-1, which contains 22 GASP motifs, is essential for the interaction with GPCRs. We then used site directed mutagenesis and competition experiments with synthetic peptides to demonstrate that the GASP motif, and particularly its highly conserved core sequence SWFW, is critically involved in the interaction with GPCRs. Overall, our data show that several members of the GASP family interact with GPCRs and highlight the presence within GASPs of a novel protein-protein interaction motif that might represent a new target to investigate the involvement of GASPs in the modulation of the activity of GPCRs. PMID:23441177

  10. A selection that reports on protein-protein interactions within a thermophilic bacterium.

    PubMed

    Nguyen, Peter Q; Silberg, Jonathan J

    2010-07-01

    Many proteins can be split into fragments that exhibit enhanced function upon fusion to interacting proteins. While this strategy has been widely used to create protein-fragment complementation assays (PCAs) for discovering protein-protein interactions within mesophilic organisms, similar assays have not yet been developed for studying natural and engineered protein complexes at the temperatures where thermophilic microbes grow. We describe the development of a selection for protein-protein interactions within Thermus thermophilus that is based upon growth complementation by fragments of Thermotoga neapolitana adenylate kinase (AK(Tn)). Complementation studies with an engineered thermophile (PQN1) that is not viable above 75 degrees C because its adk gene has been replaced by a Geobacillus stearothermophilus ortholog revealed that growth could be restored at 78 degrees C by a vector that coexpresses polypeptides corresponding to residues 1-79 and 80-220 of AK(Tn). In contrast, PQN1 growth was not complemented by AK(Tn) fragments harboring a C156A mutation within the zinc-binding tetracysteine motif unless these fragments were fused to Thermotoga maritima chemotaxis proteins that heterodimerize (CheA and CheY) or homodimerize (CheX). This enhanced complementation is interpreted as arising from chemotaxis protein-protein interactions, since AK(Tn)-C156A fragments having only one polypeptide fused to a chemotaxis protein did not complement PQN1 to the same extent. This selection increases the maximum temperature where a PCA can be used to engineer thermostable protein complexes and to map protein-protein interactions. PMID:20418388

  11. The zinc fingers of HIV nucleocapsid protein NCp7 direct interactions with the viral regulatory protein Vpr.

    PubMed

    de Rocquigny, H; Petitjean, P; Tanchou, V; Decimo, D; Drouot, L; Delaunay, T; Darlix, J L; Roques, B P

    1997-12-01

    The 96-amino acid protein Vpr functions as a regulator of cellular processes involved in human immunodeficiency virus, type 1 (HIV-1) life cycle, in particular by interrupting cells division in the G2 phase. Incorporation of Vpr in the virion was reported to be mediated by the C-terminal domain of the Pr55(Gag) polyprotein precursor, which includes NCp7, a protein involved in the genomic RNA encapsidation and p6, a protein required for particle budding. To precisely define the Gag and Vpr sequences involved in this protein-protein interaction, NCp7, p6, and Vpr as well as a series of derived peptides were synthesized using Fmoc (N-(9-fluorenyl)methoxycarbonyl) chemistry. Binding assays were carried out by Far Western experiments and by competition studies using (52-96)Vpr immobilized onto agarose beads. The results show that interaction between NCp7 and Vpr occurs in vitro by a recognition mechanism requiring the zinc fingers of NCp7 and the last 16 amino acids of Vpr. Moreover, NCp10, the equivalent of NCp7 in Moloney murine leukemia virus but not polysine inhibits Vpr-NCp7 complexation. Interestingly enough, Vpr was found to interact with Gag, NCp15, and NCp7 but not with mature p6 in vitro. In vivo mutations in NCp7 zinc fingers in an HIV-1 molecular clone led to viruses with important defects in Vpr encapsidation. Together, these results suggest that NCp7 cooperates with p6 to induce Vpr encapsidation in HIV-1 mature particles. The NCp7-Vpr complex could also be important for interaction of Vpr with cellular proteins involved in cell division.

  12. Contextual Specificity in Peptide-Mediated Protein Interactions

    PubMed Central

    Stein, Amelie; Aloy, Patrick

    2008-01-01

    Most biological processes are regulated through complex networks of transient protein interactions where a globular domain in one protein recognizes a linear peptide from another, creating a relatively small contact interface. Although sufficient to ensure binding, these linear motifs alone are usually too short to achieve the high specificity observed, and additional contacts are often encoded in the residues surrounding the motif (i.e. the context). Here, we systematically identified all instances of peptide-mediated protein interactions of known three-dimensional structure and used them to investigate the individual contribution of motif and context to the global binding energy. We found that, on average, the context is responsible for roughly 20% of the binding and plays a crucial role in determining interaction specificity, by either improving the affinity with the native partner or impeding non-native interactions. We also studied and quantified the topological and energetic variability of interaction interfaces, finding a much higher heterogeneity in the context residues than in the consensus binding motifs. Our analysis partially reveals the molecular mechanisms responsible for the dynamic nature of peptide-mediated interactions, and suggests a global evolutionary mechanism to maximise the binding specificity. Finally, we investigated the viability of non-native interactions and highlight cases of potential cross-reaction that might compensate for individual protein failure and establish backup circuits to increase the robustness of cell networks. PMID:18596940

  13. 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

  14. 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

  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. PMID:24014400

  16. Screening for Host Factors Directly Interacting with RSV Protein: Microfluidics.

    PubMed

    Kipper, Sarit; Avrahami, Dorit; Bajorek, Monika; Gerber, Doron

    2016-01-01

    We present a high-throughput microfluidics platform to identify novel host cell binding partners of respiratory syncytial virus (RSV) matrix (M) protein. The device consists of thousands of reaction chambers controlled by micro-mechanical valves. The microfluidic device is mated to a microarray-printed custom-made gene library. These genes are then transcribed and translated on-chip, resulting in a protein array ready for binding to RSV M protein.Even small viral proteome, such as that of RSV, presents a challenge due to the fact that viral proteins are usually multifunctional and thus their interaction with the host is complex. Protein microarrays technology allows the interrogation of protein-protein interactions, which could possibly overcome obstacles by using conventional high throughput methods. Using microfluidics platform we have identified new host interactors of M involved in various cellular pathways. A number of microfluidics based assays have already provided novel insights into the virus-host interactome, and the results have important implications for future antiviral strategies aimed at targets of viral protein interactions with the host. PMID:27464694

  17. Identification of novel CBP interacting proteins in embryonic orofacial tissue

    SciTech Connect

    Yin Xiaolong; Warner, Dennis R.; Roberts, Emily A.; Pisano, M. Michele; Greene, Robert M. . E-mail: greene@louisville.edu

    2005-04-15

    cAMP response element-binding protein (CREB)-binding protein (CBP) plays an important role as a general co-integrator of multiple signaling pathways and interacts with a large number of transcription factors and co-factors, through its numerous protein-binding domains. To identify nuclear factors associated with CBP in developing orofacial tissue, a yeast two-hybrid screen of a cDNA library derived from orofacial tissue from gestational day 11 to 13 mouse embryos was conducted. Using the carboxy terminus (amino acid residues 1676-2441) of CBP as bait, several novel proteins that bind CBP were identified, including an Msx-interacting-zinc finger protein, CDC42 interaction protein 4/thyroid hormone receptor interactor 10, SH3-domain GRB2-like 1, CCR4-NOT transcription complex subunit 3, adaptor protein complex AP-1 {beta}1 subunit, eukaryotic translation initiation factor 2B subunit 1 ({alpha}), and cyclin G-associated kinase. Results of the yeast two-hybrid screen were confirmed by glutathione S-transferase pull-down assays. The identification of these proteins as novel CBP-binding partners allows exploration of new mechanisms by which CBP regulates and integrates diverse cell signaling pathways.

  18. Twenty years of protein interaction studies for biological function deciphering.

    PubMed

    Legrain, Pierre; Rain, Jean-Christophe

    2014-07-31

    Intensive methodological developments and technology innovation have been devoted to protein-protein interaction studies over 20years. Genetic indirect assays and sophisticated large scale biochemical analyses have jointly contributed to the elucidation of protein-protein interactions, still with a lot of drawbacks despite heavy investment in human resources and technologies. With the most recent developments in mass spectrometry and computational tools for studying protein content of complex samples, the initial goal of deciphering molecular bases of biological functions is now within reach. Here, we described the various steps of this process and gave examples of key milestones in this scientific story line. This article is part of a Special Issue entitled: 20years of Proteomics in memory of Viatliano Pallini. Guest Editors: Luca Bini, Juan J. Calvete, Natacha Turck, Denis Hochstrasser and Jean-Charles Sanchez.

  19. Structural approaches to probing metal interaction with proteins.

    PubMed

    Parker, Lorien J; Ascher, David B; Gao, Chen; Miles, Luke A; Harris, Hugh H; Parker, Michael W

    2012-10-01

    In this mini-review we focus on metal interactions with proteins with a particular emphasis on the evident synergism between different biophysical approaches toward understanding metallobiology. We highlight three recent examples from our own laboratory. Firstly, we describe metallodrug interactions with glutathione S-transferases, an enzyme family known to attack commonly used anti-cancer drugs. We then describe a protein target for memory enhancing drugs called insulin-regulated aminopeptidase in which zinc plays a role in catalysis and regulation. Finally we describe our studies on a protein, amyloid precursor protein, that appears to play a central role in Alzheimer's disease. Copper ions have been implicated in playing both beneficial and detrimental roles in the disease by binding to different regions of this protein. PMID:22437159

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

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  2. Inhibition of protein-protein interactions with low molecular weight compounds

    PubMed Central

    Matthews, Marilyn M.; Weber, David J.; Shapiro, Paul S.; Coop, Andrew; MacKerell, Alexander D.

    2010-01-01

    An overview of issues associated with the design and development of low molecular weight inhibitors of protein-protein interactions is presented. Areas discussed include information on the nature of protein-protein interfaces, methods to characterize those interfaces and methods by which that information is applied towards ligand identification and design. Specific examples of the strategy for the identification of inhibitors of protein-protein interactions involving the proteins p56lck kinase, ERK2 and the calcium-binding protein S100B are presented. Physical characterization of the inhibitors identified in those studies shows them to have drug-like and lead-like properties, indicating their potential to be developed into therapeutic agents. PMID:21927717

  3. MEGADOCK: an all-to-all protein-protein interaction prediction system using tertiary structure data.

    PubMed

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

    2014-01-01

    The elucidation of protein-protein interaction (PPI) networks is important for understanding cellular structure and function and structure-based drug design. However, the development of an effective method to conduct exhaustive PPI screening represents a computational challenge. We have been investigating a protein docking approach based on shape complementarity and physicochemical properties. We describe here the development of the protein-protein docking software package "MEGADOCK" that samples an extremely large number of protein dockings at high speed. MEGADOCK reduces the calculation time required for docking by using several techniques such as a novel scoring function called the real Pairwise Shape Complementarity (rPSC) score. We showed that MEGADOCK is capable of exhaustive PPI screening by completing docking calculations 7.5 times faster than the conventional docking software, ZDOCK, while maintaining an acceptable level of accuracy. When MEGADOCK was applied to a subset of a general benchmark dataset to predict 120 relevant interacting pairs from 120 x 120 = 14,400 combinations of proteins, an F-measure value of 0.231 was obtained. Further, we showed that MEGADOCK can be applied to a large-scale protein-protein interaction-screening problem with accuracy better than random. When our approach is combined with parallel high-performance computing systems, it is now feasible to search and analyze protein-protein interactions while taking into account three-dimensional structures at the interactome scale. MEGADOCK is freely available at http://www.bi.cs.titech.ac.jp/megadock. PMID:23855673

  4. 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

  5. MULTIPROSPECTOR: an algorithm for the prediction of protein-protein interactions by multimeric threading.

    PubMed

    Lu, Long; Lu, Hui; Skolnick, Jeffrey

    2002-11-15

    In this postgenomic era, the ability to identify protein-protein interactions on a genomic scale is very important to assist in the assignment of physiological function. Because of the increasing number of solved structures involving protein complexes, the time is ripe to extend threading to the prediction of quaternary structure. In this spirit, a multimeric threading approach has been developed. The approach is comprised of two phases. In the first phase, traditional threading on a single chain is applied to generate a set of potential structures for the query sequences. In particular, we use our recently developed threading algorithm, PROSPECTOR. Then, for those proteins whose template structures are part of a known complex, we rethread on both partners in the complex and now include a protein-protein interfacial energy. To perform this analysis, a database of multimeric protein structures has been constructed, the necessary interfacial pairwise potentials have been derived, and a set of empirical indicators to identify true multimers based on the threading Z-score and the magnitude of the interfacial energy have been established. The algorithm has been tested on a benchmark set comprised of 40 homodimers, 15 heterodimers, and 69 monomers that were scanned against a protein library of 2478 structures that comprise a representative set of structures in the Protein Data Bank. Of these, the method correctly recognized and assigned 36 homodimers, 15 heterodimers, and 65 monomers. This protocol was applied to identify partners and assign quaternary structures of proteins found in the yeast database of interacting proteins. Our multimeric threading algorithm correctly predicts 144 interacting proteins, compared to the 56 (26) cases assigned by PSI-BLAST using a (less) permissive E-value of 1 (0.01). Next, all possible pairs of yeast proteins have been examined. Predictions (n = 2865) of protein-protein interactions are made; 1138 of these 2865 interactions have

  6. Interactions of membranes with coarse-grain proteins: a comparison

    NASA Astrophysics Data System (ADS)

    Neder, Jörg; Nielaba, Peter; West, Beate; Schmid, Friederike

    2012-12-01

    We study the interactions between lipid bilayers and rigid transmembrane proteins by Monte Carlo simulations of generic coarse-grain models. Different popular protein models are considered and compared with each other, and key parameters such as the hydrophobicity and the hydrophobic mismatch are varied systematically. Furthermore, the properties of the membrane are manipulated by applying different tensions. The response of the membrane to the insertion of single proteins is found to be mostly generic and independent of the choice of the protein model. Likewise, the orientational distributions of single proteins depend mainly on the hydrophobic mismatch and the hydrophobicity of the proteins, and are otherwise similar for all protein models. Orientational distributions are generally found to be very broad, i.e. tilt angles fluctuate very much, in agreement with experimental findings. Weakly hydrophobic proteins respond to positive hydrophobic mismatch by tilting. Strongly hydrophobic (strongly bound) proteins distort the surrounding membrane and tend to remain upright. For proteins with intermediate hydrophobicity, the two mechanisms compete, and as a result, the tilt only sets in if the hydrophobic mismatch exceeds a threshold. Clusters of several strongly hydrophobic proteins with negative positive mismatch may nucleate raft-like structures in membranes. This effect is more pronounced for proteins with rough, structured surfaces.

  7. Simulation Studies of Protein and Small Molecule Interactions and Reaction.

    PubMed

    Yang, L; Zhang, J; Che, X; Gao, Y Q

    2016-01-01

    Computational studies of protein and small molecule (protein-ligand/enzyme-substrate) interactions become more and more important in biological science and drug discovery. Computer modeling can provide molecular details of the processes such as conformational change, binding, and transportation of small molecules/proteins, which are not easily to be captured in experiments. In this chapter, we discussed simulation studies of both protein and small molecules from three aspects: conformation sampling, transportations of small molecules in enzymes, and enzymatic reactions involving small molecules. Both methodology developments and examples of simulation studies in this field were presented.

  8. Simulation Studies of Protein and Small Molecule Interactions and Reaction.

    PubMed

    Yang, L; Zhang, J; Che, X; Gao, Y Q

    2016-01-01

    Computational studies of protein and small molecule (protein-ligand/enzyme-substrate) interactions become more and more important in biological science and drug discovery. Computer modeling can provide molecular details of the processes such as conformational change, binding, and transportation of small molecules/proteins, which are not easily to be captured in experiments. In this chapter, we discussed simulation studies of both protein and small molecules from three aspects: conformation sampling, transportations of small molecules in enzymes, and enzymatic reactions involving small molecules. Both methodology developments and examples of simulation studies in this field were presented. PMID:27497167

  9. Screening and analysis on the protein interaction of the protein VP7 in grass carp reovirus.

    PubMed

    Yan, Xiuying; Xie, Jiguo; Li, Jie; Shuanghu, Cai; Wu, Zaohe; Jian, Jichang

    2015-06-01

    Grass carp reovirus (GCRV) has caused serious economic losses for several decades in China. The protein VP7 is one of the important structural proteins in GCRV. Recent studies indicated that the protein VP7 had the commendable antigenicity and immunogenicity. The protein VP7 cooperated with VP5 could change the conformation of the cell membrane and facilitate entry of GCRV into host cells. We speculated that the protein VP7 should play an important role in the pathogenesis of GCRV. In order to explore the function of the protein VP7, the bait protein expression plasmid pGBKT7-vp7 and the cDNA library of CIK cells were constructed. By yeast two-hybrid system, after multiple screening with the high screening rate medium, rotary verification, sequencing and bioinformatics analysis, the interactions of the protein VP7 with ribosomal protein S20 (RPS20) and eukaryotic translation initiation factor 3 subunit b (eIF3b) in CIK cells were identified. RPS20 played the important roles in the generation of influenza B virus and a variety of diseases. eIF3b was relative to the infection of some viruses. This study suggested that the protein VP7 played the role in viral replication and most likely interacted with host proteins by RPS20 and eIF3b. The interaction mechanisms of the protein VP7 with RPS20 and eIF3b, and the subsequent effector mechanisms needed to be further studied. The corresponding protein interaction of the protein VP7 was not acquired in bioinformatics. The protein VP7 and its untranslated region may have the unknown special function. This study laid the foundation for deeply exploring the function of the protein VP7 in GCRV and had the important scientific significance for exploring the pathogenic mechanism of GCRV.

  10. Efficient recovery of recombinant proteins from cereal endosperm is affected by interaction with endogenous storage proteins.

    PubMed

    Peters, Jenny; Sabalza, Maite; Ramessar, Koreen; Christou, Paul; Capell, Teresa; Stöger, Eva; Arcalís, Elsa

    2013-10-01

    Cereal seeds are versatile platforms for the production of recombinant proteins because they provide a stable environment for protein accumulation. Endogenous seed storage proteins, however, include several prolamin-type polypeptides that aggregate and crosslink via intermolecular disulfide bridges, which could potentially interact with multimeric recombinant proteins such as antibodies, which assemble in the same manner. We investigated this possibility by sequentially extracting a human antibody expressed in maize endosperm, followed by precipitation in vitro with zein. We provide evidence that a significant proportion of the antibody pool interacts with zein and therefore cannot be extracted using non-reducing buffers. Immunolocalization experiments demonstrated that antibodies targeted for secretion were instead retained within zein bodies because of such covalent interactions. Our findings suggest that the production of soluble recombinant antibodies in maize could be enhanced by eliminating or minimizing interactions with endogenous storage proteins.

  11. Predicting protein functions from redundancies in large-scale protein interaction networks

    NASA Technical Reports Server (NTRS)

    Samanta, Manoj Pratim; Liang, Shoudan

    2003-01-01

    Interpreting data from large-scale protein interaction experiments has been a challenging task because of the widespread presence of random false positives. Here, we present a network-based statistical algorithm that overcomes this difficulty and allows us to derive functions of unannotated proteins from large-scale interaction data. Our algorithm uses the insight that if two proteins share significantly larger number of common interaction partners than random, they have close functional associations. Analysis of publicly available data from Saccharomyces cerevisiae reveals >2,800 reliable functional associations, 29% of which involve at least one unannotated protein. By further analyzing these associations, we derive tentative functions for 81 unannotated proteins with high certainty. Our method is not overly sensitive to the false positives present in the data. Even after adding 50% randomly generated interactions to the measured data set, we are able to recover almost all (approximately 89%) of the original associations.

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

    PubMed Central

    2014-01-01

    To date, few tools for aligning protein-protein interaction networks have been suggested. These tools typically find conserved interaction patterns using various local or global alignment algorithms. However, the improvement of the speed, scalability, simplification, and accuracy of network alignment tools is still the target of new researches. In this paper, we introduce Pin-Align, a new tool for local alignment of protein-protein interaction networks. Pin-Align accuracy is tested on protein interaction networks from IntAct, DIP, and the Stanford Network Database and the results are compared with other well-known algorithms. It is shown that Pin-Align has higher sensitivity and specificity in terms of KEGG Ortholog groups. PMID:25435900

  13. Arabidopsis scaffold protein RACK1A interacts with diverse environmental stress and photosynthesis related proteins.

    PubMed

    Kundu, Nabanita; Dozier, Uvetta; Deslandes, Laurent; Somssich, Imre E; Ullah, Hemayet

    2013-05-01

    Scaffold proteins are known to regulate important cellular processes by interacting with multiple proteins to modulate molecular responses. RACK1 (Receptor for Activated C Kinase 1) is a WD-40 type scaffold protein, conserved in eukaryotes, from Chlamydymonas to plants and humans, expresses ubiquitously and plays regulatory roles in diverse signal transduction and stress response pathways. Here we present the use of Arabidopsis RACK1A, the predominant isoform of a 3-member family, as a bait to screen a split-ubiquitin based cDNA library. In total 97 proteins from dehydration, salt stress, ribosomal and photosynthesis pathways are found to potentially interact with RACK1A. False positive interactions were eliminated following extensive selection based growth potentials. Confirmation of a sub-set of selected interactions is demonstrated through the co-transformation with individual plasmid containing cDNA and the respective bait. Interaction of diverse proteins points to a regulatory role of RACK1A in the cross-talk between signaling pathways. Promoter analysis of the stress and photosynthetic pathway genes revealed conserved transcription factor binding sites. RACK1A is known to be a multifunctional protein and the current identification of potential interacting proteins and future in vivo elucidations of the physiological basis of such interactions will shed light on the possible molecular mechanisms that RACK1A uses to regulate diverse signaling pathways.

  14. Probing interactions between collagen proteins via microrheology

    NASA Astrophysics Data System (ADS)

    Shayegan, Marjan; Forde, Nancy R.

    2012-10-01

    Collagen is the major structural protein of our connective tissues. It provides integrity and mechanical strength through its hierarchical organization. Defects in collagen can lead to serious connective tissue diseases. Collagen is also widely used as a biomaterial. Given that mechanical properties are related to the structure of materials, the main goal of our research is to understand how molecular structure correlates with microscale mechanical properties of collagen solutions and networks. We use optical tweezers to trap and monitor thermal fluctuations of an embedded probe particle, from which viscoelastic properties of the solution are extracted. We find that elasticity becomes comparable to viscous behavior at collagen concentrations of 5mg/ml. Furthermore, by simultaneously neutralizing pH and adding salt, we observe changes in viscosity and elasticity of the solution over time. We attribute this to the self-assembly process of collagen molecules into fibrils with different mechanical properties. Self-assembly of collagen under these conditions is verified by turbidity measurements as well as electron microscopy. By comparing results from these local studies of viscoelasticity, we can detect spatial heterogeneity of fibril formation throughout the solution.

  15. Multiple protein-protein interactions converging on the Prp38 protein during activation of the human spliceosome.

    PubMed

    Schütze, Tonio; Ulrich, Alexander K C; Apelt, Luise; Will, Cindy L; Bartlick, Natascha; Seeger, Martin; Weber, Gert; Lührmann, Reinhard; Stelzl, Ulrich; Wahl, Markus C

    2016-02-01

    Spliceosomal Prp38 proteins contain a conserved amino-terminal domain, but only higher eukaryotic orthologs also harbor a carboxy-terminal RS domain, a hallmark of splicing regulatory SR proteins. We show by crystal structure analysis that the amino-terminal domain of human Prp38 is organized around three pairs of antiparallel α-helices and lacks similarities to RNA-binding domains found in canonical SR proteins. Instead, yeast two-hybrid analyses suggest that the amino-terminal domain is a versatile protein-protein interaction hub that possibly binds 12 other spliceosomal proteins, most of which are recruited at the same stage as Prp38. By quantitative, alanine surface-scanning two-hybrid screens and biochemical analyses we delineated four distinct interfaces on the Prp38 amino-terminal domain. In vitro interaction assays using recombinant proteins showed that Prp38 can bind at least two proteins simultaneously via two different interfaces. Addition of excess Prp38 amino-terminal domain to in vitro splicing assays, but not of an interaction-deficient mutant, stalled splicing at a precatalytic stage. Our results show that human Prp38 is an unusual SR protein, whose amino-terminal domain is a multi-interface protein-protein interaction platform that might organize the relative positioning of other proteins during splicing. PMID:26673105

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

    SciTech Connect

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

    2015-07-31

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

  17. D-SLIMMER: domain-SLiM interaction motifs miner for sequence based protein-protein interaction data.

    PubMed

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

    2011-12-01

    Many biologically important protein-protein interactions (PPIs) have been found to be mediated by short linear motifs (SLiMs). These interactions are mediated by the binding of a protein domain, often with a nonlinear interaction interface, to a SLiM. We propose a method called D-SLIMMER to mine for SLiMs in PPI data on the basis of the interaction density between a nonlinear motif (i.e., a protein domain) in one protein and a SLiM in the other protein. Our results on a benchmark of 113 experimentally verified reference SLiMs showed that D-SLIMMER outperformed existing methods notably for discovering domain-SLiMs interaction motifs. To illustrate the significance of the SLiMs detected, we highlighted two SLiMs discovered from the PPI data by D-SLIMMER that are variants of the known ELM SLiM, as well as a literature-backed SLiM that is yet to be listed in the reference databases. We also presented a novel SLiM predicted by D-SLIMMER that was strongly supported by existing biological literatures. These examples showed that D-SLIMMER is able to find SLiMs that are biologically relevant.

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

    NASA Astrophysics Data System (ADS)

    Freire, Ernesto

    2010-03-01

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

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

    PubMed

    Li, Jian-Feng; Zhang, Dandan

    2014-07-01

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

  20. Novel folate binding protein-1 interactions in embryonic orofacial tissue

    PubMed Central

    Pisano, M. Michele; Bhattacherjee, Vasker; Wong, Leeyean; Finnell, Richard H.; Greene, Robert M.

    2010-01-01

    Aim To identify proteins with which FolBp1 may interact within lipid rafts in tissue derived from embryonic orofacial tissue. Methods A yeast two-hybrid screen of a cDNA library, derived from orofacial tissue from gestational day 11 to 13 mouse embryos, was conducted. Key Findings Using the full-length FolBp1 protein as bait, two proteins that bind FolBp1 were identified, Bat2d, and a fibronectin type III-containing domain protein. Results were confirmed by glutathione S-transferase pull-down assays. Significance As a component of membrane lipid raft protein complexes, these binding proteins may represent “helper” or chaperone proteins that associate with FolBp1 in order to facilitate the transport of folate across the plasma membrane. The protein-protein interactions detected, while limited in number, may be critical in mediating the role of FolBp1 in folate transport, particularly in the developing embryo. PMID:20045418

  1. Template-Based Modeling of Protein-RNA Interactions

    PubMed Central

    Zheng, Jinfang; Kundrotas, Petras J.; Vakser, Ilya A.

    2016-01-01

    Protein-RNA complexes formed by specific recognition between RNA and RNA-binding proteins play an important role in biological processes. More than a thousand of such proteins in human are curated and many novel RNA-binding proteins are to be discovered. Due to limitations of experimental approaches, computational techniques are needed for characterization of protein-RNA interactions. Although much progress has been made, adequate methodologies reliably providing atomic resolution structural details are still lacking. Although protein-RNA free docking approaches proved to be useful, in general, the template-based approaches provide higher quality of predictions. Templates are key to building a high quality model. Sequence/structure relationships were studied based on a representative set of binary protein-RNA complexes from PDB. Several approaches were tested for pairwise target/template alignment. The analysis revealed a transition point between random and correct binding modes. The results showed that structural alignment is better than sequence alignment in identifying good templates, suitable for generating protein-RNA complexes close to the native structure, and outperforms free docking, successfully predicting complexes where the free docking fails, including cases of significant conformational change upon binding. A template-based protein-RNA interaction modeling protocol PRIME was developed and benchmarked on a representative set of complexes. PMID:27662342

  2. Misfolding of Amyloidogenic Proteins and Their Interactions with Membranes

    PubMed Central

    Relini, Annalisa; Marano, Nadia; Gliozzi, Alessandra

    2013-01-01

    In this paper, we discuss amyloidogenic proteins, their misfolding, resulting structures, and interactions with membranes, which lead to membrane damage and subsequent cell death. Many of these proteins are implicated in serious illnesses such as Alzheimer’s disease and Parkinson’s disease. Misfolding of amyloidogenic proteins leads to the formation of polymorphic oligomers and fibrils. Oligomeric aggregates are widely thought to be the toxic species, however, fibrils also play a role in membrane damage. We focus on the structure of these aggregates and their interactions with model membranes. Study of interactions of amlyoidogenic proteins with model and natural membranes has shown the importance of the lipid bilayer in protein misfolding and aggregation and has led to the development of several models for membrane permeabilization by the resulting amyloid aggregates. We discuss several of these models: formation of structured pores by misfolded amyloidogenic proteins, extraction of lipids, interactions with receptors in biological membranes, and membrane destabilization by amyloid aggregates perhaps analogous to that caused by antimicrobial peptides. PMID:24970204

  3. Phospho-tyrosine dependent protein–protein interaction network

    PubMed Central

    Grossmann, Arndt; Benlasfer, Nouhad; Birth, Petra; Hegele, Anna; Wachsmuth, Franziska; Apelt, Luise; Stelzl, Ulrich

    2015-01-01

    Post-translational protein modifications, such as tyrosine phosphorylation, regulate protein–protein interactions (PPIs) critical for signal processing and cellular phenotypes. We extended an established yeast two-hybrid system employing human protein kinases for the analyses of phospho-tyrosine (pY)-dependent PPIs in a direct experimental, large-scale approach. We identified 292 mostly novel pY-dependent PPIs which showed high specificity with respect to kinases and interacting proteins and validated a large fraction in co-immunoprecipitation experiments from mammalian cells. About one-sixth of the interactions are mediated by known linear sequence binding motifs while the majority of pY-PPIs are mediated by other linear epitopes or governed by alternative recognition modes. Network analysis revealed that pY-mediated recognition events are tied to a highly connected protein module dedicated to signaling and cell growth pathways related to cancer. Using binding assays, protein complementation and phenotypic readouts to characterize the pY-dependent interactions of TSPAN2 (tetraspanin 2) and GRB2 or PIK3R3 (p55γ), we exemplarily provide evidence that the two pY-dependent PPIs dictate cellular cancer phenotypes. PMID:25814554

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

    PubMed

    Schweiger, Regina; Schwenkert, Serena

    2014-03-09

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

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

    PubMed

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

    2016-04-21

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

  6. Protein/Protein Interactions in the Mammalian Heme Degradation Pathway

    PubMed Central

    Spencer, Andrea L. M.; Bagai, Ireena; Becker, Donald F.; Zuiderweg, Erik R. P.; Ragsdale, Stephen W.

    2014-01-01

    Heme oxygenase (HO) catalyzes the rate-limiting step in the O2-dependent degradation of heme to biliverdin, CO, and iron with electrons delivered from NADPH via cytochrome P450 reductase (CPR). Biliverdin reductase (BVR) then catalyzes conversion of biliverdin to bilirubin. We describe mutagenesis combined with kinetic, spectroscopic (fluorescence and NMR), surface plasmon resonance, cross-linking, gel filtration, and analytical ultracentrifugation studies aimed at evaluating interactions of HO-2 with CPR and BVR. Based on these results, we propose a model in which HO-2 and CPR form a dynamic ensemble of complex(es) that precede formation of the productive electron transfer complex. The 1H-15N TROSY NMR spectrum of HO-2 reveals specific residues, including Leu-201, near the heme face of HO-2 that are affected by the addition of CPR, implicating these residues at the HO/CPR interface. Alanine substitutions at HO-2 residues Leu-201 and Lys-169 cause a respective 3- and 22-fold increase in Km values for CPR, consistent with a role for these residues in CPR binding. Sedimentation velocity experiments confirm the transient nature of the HO-2·CPR complex (Kd = 15.1 μm). Our results also indicate that HO-2 and BVR form a very weak complex that is only captured by cross-linking. For example, under conditions where CPR affects the 1H-15N TROSY NMR spectrum of HO-2, BVR has no effect. Fluorescence quenching experiments also suggest that BVR binds HO-2 weakly, if at all, and that the previously reported high affinity of BVR for HO is artifactual, resulting from the effects of free heme (dissociated from HO) on BVR fluorescence. PMID:25196843

  7. A survey of protein interaction data and multigenic inherited disorders

    PubMed Central

    2013-01-01

    Background Multigenic diseases are often associated with protein complexes or interactions involved in the same pathway. We wanted to estimate to what extent this is true given a consolidated protein interaction data set. The study stresses data integration and data representation issues. Results We constructed 497 multigenic disease groups from OMIM and tested for overlaps with interaction and pathway data. A total of 159 disease groups had significant overlaps with protein interaction data consolidated by iRefIndex. A further 68 disease overlaps were found only in the KEGG pathway database. No single database contained all significant overlaps thus stressing the importance of data integration. We also found that disease groups overlapped with all three interaction data types: n-ary, spoke-represented complexes and binary data – thus stressing the importance of considering each of these data types separately. Conclusions Almost half of our multigenic disease groups could potentially be explained by protein complexes and pathways. However, the fact that no database or data type was able to cover all disease groups suggests that no single database has systematically covered all disease groups for potential related complex and pathway data. This survey provides a basis for further curation efforts to confirm and search for overlaps between diseases and interaction data. The accompanying R script can be used to reproduce the work and track progress in this area as databases change. Disease group overlaps can be further explored using the iRefscape plugin for Cytoscape. PMID:23398688

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

    PubMed Central

    Bhat, Riyaz A; Lahaye, Thomas; Panstruga, Ralph

    2006-01-01

    Non-invasive fluorophore-based protein interaction assays like fluorescence resonance energy transfer (FRET) and bimolecular fluorescence complementation (BiFC, also referred to as "split YFP") have been proven invaluable tools to study protein-protein interactions in living cells. Both methods are now frequently used in the plant sciences and are likely to develop into standard techniques for the identification, verification and in-depth analysis of polypeptide interactions. In this review, we address the individual strengths and weaknesses of both approaches and provide an outlook about new directions and possible future developments for both techniques. PMID:16800872

  9. Machine Learning of Protein Interactions in Fungal Secretory Pathways.

    PubMed

    Kludas, Jana; Arvas, Mikko; Castillo, Sandra; Pakula, Tiina; Oja, Merja; Brouard, Céline; Jäntti, Jussi; Penttilä, Merja; Rousu, Juho

    2016-01-01

    In this paper we apply machine learning methods for predicting protein interactions in fungal secretion pathways. We assume an inter-species transfer setting, where training data is obtained from a single species and the objective is to predict protein interactions in other, related species. In our methodology, we combine several state of the art machine learning approaches, namely, multiple kernel learning (MKL), pairwise kernels and kernelized structured output prediction in the supervised graph inference framework. For MKL, we apply recently proposed centered kernel alignment and p-norm path following approaches to integrate several feature sets describing the proteins, demonstrating improved performance. For graph inference, we apply input-output kernel regression (IOKR) in supervised and semi-supervised modes as well as output kernel trees (OK3). In our experiments simulating increasing genetic distance, Input-Output Kernel Regression proved to be the most robust prediction approach. We also show that the MKL approaches improve the predictions compared to uniform combination of the kernels. We evaluate the methods on the task of predicting protein-protein-interactions in the secretion pathways in fungi, S.cerevisiae, baker's yeast, being the source, T. reesei being the target of the inter-species transfer learning. We identify completely novel candidate secretion proteins conserved in filamentous fungi. These proteins could contribute to their unique secretion capabilities. PMID:27441920

  10. Machine Learning of Protein Interactions in Fungal Secretory Pathways.

    PubMed

    Kludas, Jana; Arvas, Mikko; Castillo, Sandra; Pakula, Tiina; Oja, Merja; Brouard, Céline; Jäntti, Jussi; Penttilä, Merja; Rousu, Juho

    2016-01-01

    In this paper we apply machine learning methods for predicting protein interactions in fungal secretion pathways. We assume an inter-species transfer setting, where training data is obtained from a single species and the objective is to predict protein interactions in other, related species. In our methodology, we combine several state of the art machine learning approaches, namely, multiple kernel learning (MKL), pairwise kernels and kernelized structured output prediction in the supervised graph inference framework. For MKL, we apply recently proposed centered kernel alignment and p-norm path following approaches to integrate several feature sets describing the proteins, demonstrating improved performance. For graph inference, we apply input-output kernel regression (IOKR) in supervised and semi-supervised modes as well as output kernel trees (OK3). In our experiments simulating increasing genetic distance, Input-Output Kernel Regression proved to be the most robust prediction approach. We also show that the MKL approaches improve the predictions compared to uniform combination of the kernels. We evaluate the methods on the task of predicting protein-protein-interactions in the secretion pathways in fungi, S.cerevisiae, baker's yeast, being the source, T. reesei being the target of the inter-species transfer learning. We identify completely novel candidate secretion proteins conserved in filamentous fungi. These proteins could contribute to their unique secretion capabilities.

  11. Machine Learning of Protein Interactions in Fungal Secretory Pathways

    PubMed Central

    Kludas, Jana; Arvas, Mikko; Castillo, Sandra; Pakula, Tiina; Oja, Merja; Brouard, Céline; Jäntti, Jussi; Penttilä, Merja

    2016-01-01

    In this paper we apply machine learning methods for predicting protein interactions in fungal secretion pathways. We assume an inter-species transfer setting, where training data is obtained from a single species and the objective is to predict protein interactions in other, related species. In our methodology, we combine several state of the art machine learning approaches, namely, multiple kernel learning (MKL), pairwise kernels and kernelized structured output prediction in the supervised graph inference framework. For MKL, we apply recently proposed centered kernel alignment and p-norm path following approaches to integrate several feature sets describing the proteins, demonstrating improved performance. For graph inference, we apply input-output kernel regression (IOKR) in supervised and semi-supervised modes as well as output kernel trees (OK3). In our experiments simulating increasing genetic distance, Input-Output Kernel Regression proved to be the most robust prediction approach. We also show that the MKL approaches improve the predictions compared to uniform combination of the kernels. We evaluate the methods on the task of predicting protein-protein-interactions in the secretion pathways in fungi, S.cerevisiae, baker’s yeast, being the source, T. reesei being the target of the inter-species transfer learning. We identify completely novel candidate secretion proteins conserved in filamentous fungi. These proteins could contribute to their unique secretion capabilities. PMID:27441920

  12. High affinity DNA-microtubule associated protein interaction.

    PubMed

    Marx, K A

    1992-07-01

    We have isolated the MAP/tau proteins from twice-cycled chick brain microtubule preparations and demonstrated that they are responsible for the nitrocellulose DNA binding activity we and others have measured. Using the isolated MAP/tau proteins we then measured the apparent affinity constant K(app) for the homologous chick DNA interaction and found evidence for two equilibrium affinity classes-a K(app) = 6 x 10(7) M-1, responsible for the bulk of the DNA binding activity and a small (less than 10%) higher affinity K(app) = 10(8) - 10(9) M-1, likely due to sequence specific binding protein species. Using the same chick brain MAP-tau protein, a heterologous interaction with D. melanogaster DNA, was found to possess just the lower affinity class-K(app) = 2 x 10(7) M-1. Under stringent binding conditions we carried out equilibrium nitrocellulose filter binding experiments in a ternary reaction mixture at constant MAP/tau protein and 35S radiolabelled chick DNA concentration using increasing and excess concentrations of competitor DNAs of different sources. The order of competitor strengths found was-chick DNA greater than mouse DNA greater than D. melanogaster = E. coli. DNA. These data and specifically the homologous DNA: protein case being the strongest competitor corroborate our previous studies using total microtubule protein and provide new evidence for a conserved interaction of a small DNA sequence class with MAP/tau protein species. Moreover, these data allow us to conclude that the conserved DNA sequence: MAP/tau protein interactions do not critically depend upon any energetic feature co-involving tubulin for their properties since tubulin is absent from these preparations.

  13. Specific ion and buffer effects on 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

    2015-01-01

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

  14. Specific ion and buffer effects on 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

    2015-01-01

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

  15. IFT-Cargo Interactions and Protein Transport in Cilia.

    PubMed

    Lechtreck, Karl F

    2015-12-01

    The motile and sensory functions of cilia and flagella are indispensable for human health. Cilia assembly requires a dedicated protein shuttle, intraflagellar transport (IFT), a bidirectional motility of multi-megadalton protein arrays along ciliary microtubules. IFT functions as a protein carrier delivering hundreds of distinct proteins into growing cilia. IFT-based protein import and export continue in fully grown cilia and are required for ciliary maintenance and sensing. Large ciliary building blocks might depend on IFT to move through the transition zone, which functions as a ciliary gate. Smaller, freely diffusing proteins, such as tubulin, depend on IFT to be concentrated or removed from cilia. As I discuss here, recent work provides insights into how IFT interacts with its cargoes and how the transport is regulated. PMID:26498262

  16. Dynamics and mechanism of ultrafast water–protein interactions

    PubMed Central

    Qin, Yangzhong; Wang, Lijuan; Zhong, Dongping

    2016-01-01

    Protein hydration is essential to its structure, dynamics, and function, but water–protein interactions have not been directly observed in real time at physiological temperature to our awareness. By using a tryptophan scan with femtosecond spectroscopy, we simultaneously measured the hydration water dynamics and protein side-chain motions with temperature dependence. We observed the heterogeneous hydration dynamics around the global protein surface with two types of coupled motions, collective water/side-chain reorientation in a few picoseconds and cooperative water/side-chain restructuring in tens of picoseconds. The ultrafast dynamics in hundreds of femtoseconds is from the outer-layer, bulk-type mobile water molecules in the hydration shell. We also found that the hydration water dynamics are always faster than protein side-chain relaxations but with the same energy barriers, indicating hydration shell fluctuations driving protein side-chain motions on the picosecond time scales and thus elucidating their ultimate relationship. PMID:27339138

  17. Dynamic multibody protein interactions suggest versatile pathways for copper trafficking.

    PubMed

    Keller, Aaron M; Benítez, Jaime J; Klarin, Derek; Zhong, Linghao; Goldfogel, Matthew; Yang, Feng; Chen, Tai-Yen; Chen, Peng

    2012-05-30

    As part of intracellular copper trafficking pathways, the human copper chaperone Hah1 delivers Cu(+) to the Wilson's Disease Protein (WDP) via weak and dynamic protein-protein interactions. WDP contains six homologous metal binding domains (MBDs) connected by flexible linkers, and these MBDs all can receive Cu(+) from Hah1. The functional roles of the MBD multiplicity in Cu(+) trafficking are not well understood. Building on our previous study of the dynamic interactions between Hah1 and the isolated fourth MBD of WDP, here we study how Hah1 interacts with MBD34, a double-domain WDP construct, using single-molecule fluorescence resonance energy transfer (smFRET) combined with vesicle trapping. By alternating the positions of the smFRET donor and acceptor, we systematically probed Hah1-MBD3, Hah1-MBD4, and MBD3-MBD4 interaction dynamics within the multidomain system. We found that the two interconverting interaction geometries were conserved in both intermolecular Hah1-MBD and intramolecular MBD-MBD interactions. The Hah1-MBD interactions within MBD34 are stabilized by an order of magnitude relative to the isolated single-MBDs, and thermodynamic and kinetic evidence suggest that Hah1 can interact with both MBDs simultaneously. The enhanced interaction stability of Hah1 with the multi-MBD system, the dynamic intramolecular MBD-MBD interactions, and the ability of Hah1 to interact with multiple MBDs simultaneously suggest an efficient and versatile mechanism for the Hah1-to-WDP pathway to transport Cu(+).

  18. Nanoparticle corona for proteins: mechanisms of interaction between dendrimers and proteins.

    PubMed

    Shcharbin, Dzmitry; Ionov, Maksim; Abashkin, Viktar; Loznikova, Svetlana; Dzmitruk, Volha; Shcharbina, Natallia; Matusevich, Ludmila; Milowska, Katarzyna; Gałęcki, Krystian; Wysocki, Stanisław; Bryszewska, Maria

    2015-10-01

    Protein absorption at the surface of big nanoparticles and formation of 'protein corona' can completely change their biological properties. In contrast, we have studied the binding of small nanoparticles - dendrimers - to proteins and the formation of their 'nanoparticle corona'. Three different types of interactions were observed. (1) If proteins have rigid structure and active site buried deeply inside, the 'nanoparticle corona' is unaffected. (2) If proteins have a flexible structure and their active site is also buried deeply inside, the 'nanoparticle corona' affects protein structure, but not enzymatic activity. (3) The 'nanoparticle corona' changes both the structure and enzymatic activity of flexible proteins that have surface-based active centers. These differences are important in understanding interactions taking place at a bio-nanointerface.

  19. Structural Instability Tuning as a Regulatory Mechanism in Protein-Protein Interactions

    PubMed Central

    Chen, Li; Balabanidou, Vassilia; Remeta, David P.; Minetti, Conceição A.S.A.; Portaliou, Athina G.; Economou, Anastassios; Kalodimos, Charalampos G.

    2011-01-01

    SUMMARY Protein-protein interactions mediate a vast number of cellular processes. Here we present a regulatory mechanism in protein-protein interactions mediated by finely-tuned structural instability coupled with molecular mimicry. We show that a set of type III secretion (TTS) autoinhibited homodimeric chaperones adopt a molten-globule-like state that transiently exposes the substrate binding site as a means to become rapidly poised for binding to their cognate protein substrates. Packing defects at the homodimeric interface stimulate binding whereas correction of these defects results in less labile chaperones that give rise to non-functional biological systems. The protein substrates use structural mimicry to offset the “weak spots” in the chaperones and to counteract their autoinhibitory conformation. This regulatory mechanism of protein activity is evolutionary conserved among several TSS systems and presents a lucid example of functional advantage conferred upon a biological system by finely-tuned structural instability. PMID:22152477

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

    PubMed Central

    McLaughlin, B. A.; Spencer, C.; Eberwine, J.

    1996-01-01

    Genes associated with several neurological diseases are characterized by the presence of an abnormally long trinucleotide repeat sequence. By way of example, Huntington's disease (HD), is characterized by selective neuronal degeneration associated with the expansion of a polyglutamine-encoding CAG tract. Normally, this CAG tract is comprised of 11-34 repeats, but in HD it is expanded to > 37 repeats in affected individuals. The mechanism by which CAG repeats cause neuronal degeneration is unknown, but it has been speculated that the expansion primarily causes abnormal protein functioning, which in turn causes HD pathology. Other mechanisms, however, have not been ruled out. Interactions between RNA and RNA-binding proteins have previously been shown to play a role in the expression of several eukaryotic genes. Herein, we report the association of cytoplasmic proteins with normal length and extended CAG repeats, using gel shift and UV crosslinking assays. Cytoplasmic protein extracts from several rat brain regions, including the striatum and cortex, sites of neuronal degeneration in HD, contain a 63-kD RNA-binding protein that specifically interacts with these CAG-repeat sequences. These protein-RNA interactions are dependent on the length of the CAG repeat, with longer repeats binding substantially more protein. Two CAG repeat-binding proteins are present in human cortex and striatum; one comigrates with the rat protein at 63 kD, while the other migrates at 49 kD. These data suggest mechanisms by which RNA-binding proteins may be involved in the pathological course of trinucleotide repeat-associated neurological diseases. Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 PMID:8751857

  1. Glycoarray Technologies: Deciphering Interactions from Proteins to Live Cell Responses.

    PubMed

    Puvirajesinghe, Tania M; Turnbull, Jeremy E

    2016-01-01

    Microarray technologies inspired the development of carbohydrate arrays. Initially, carbohydrate array technology was hindered by the complex structures of glycans and their structural variability. The first designs of glycoarrays focused on the HTP (high throughput) study of protein-glycan binding events, and subsequently more in-depth kinetic analysis of carbohydrate-protein interactions. However, the applications have rapidly expanded and now achieve successful discrimination of selective interactions between carbohydrates and, not only proteins, but also viruses, bacteria and eukaryotic cells, and most recently even live cell responses to immobilized glycans. Combining array technology with other HTP technologies such as mass spectrometry is expected to allow even more accurate and sensitive analysis. This review provides a broad overview of established glycoarray technologies (with a special focus on glycosaminoglycan applications) and their emerging applications to the study of complex interactions between glycans and whole living cells. PMID:27600069

  2. TOWARDS A PROBABILISTIC RECOGNITION CODE FOR PROTEIN-DNA INTERACTIONS

    SciTech Connect

    P. BENOS; ET AL

    2000-09-01

    We are investigating the rules that govern protein-DNA interactions, using a statistical mechanics based formalism that is related to the Boltzmann Machine of the neural net literature. Our approach is data-driven, in which probabilistic algorithms are used to model protein-DNA interactions, given SELEX and phage data as input. Under the ''one-to-one'' model for interactions (i.e. one amino acid contacts one base), we can successfully identify the wild-type binding sites of EGR and MIG protein families. The predictions using our method are the same or better than that of methods existing in the literature, however our methodology offers the potential to capitalize in quantitative detail on more data as it becomes available.

  3. Interaction of milk whey protein with common phenolic acids

    NASA Astrophysics Data System (ADS)

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

    2014-01-01

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

  4. Maleimide photolithography for single-molecule protein-protein interaction analysis in micropatterns.

    PubMed

    Waichman, Sharon; You, Changjiang; Beutel, Oliver; Bhagawati, Maniraj; Piehler, Jacob

    2011-01-15

    Spatial organization of proteins into microscopic structures has important applications in fundamental and applied research. Preserving the function of proteins in such microstructures requires generic methods for site-specific capturing through affinity handles. Here, we present a versatile bottom-up surface micropatterning approach based on surface functionalization with maleimides, which selectively react with organic thiols. Upon UV irradiation through a photomask, the functionality of illuminated maleimide groups was efficiently destroyed. Remaining maleimides in nonilluminated regions were further reacted with different thiol-functionalized groups for site-specific protein immobilization under physiological conditions. Highly selective immobilization of His-tagged proteins into tris(nitrilotriacetic acid) functionalized microstructures with very high contrast was possible even by direct capturing of proteins from crude cell lysates. Moreover, we employed phosphopantetheinyl transfer from surface-immobilized coenzyme A to ybbR-tagged proteins in order to implement site-specific, covalent protein immobilization into microstructures. The functional integrity of the immobilized protein was confirmed by monitoring protein-protein interactions in real time. Moreover, we demonstrate quantitative single-molecule analysis of protein-protein interactions with proteins selectively captured into these high-contrast micropatterns.

  5. A fluorescent reporter for mapping cellular protein-protein interactions in time and space.

    PubMed

    Moreno, Daniel; Neller, Joachim; Kestler, Hans A; Kraus, Johann; Dünkler, Alexander; Johnsson, Nils

    2013-01-01

    We introduce a fluorescent reporter for monitoring protein-protein interactions in living cells. The method is based on the Split-Ubiquitin method and uses the ratio of two auto-fluorescent reporter proteins as signal for interaction (SPLIFF). The mating of two haploid yeast cells initiates the analysis and the interactions are followed online by two-channel time-lapse microscopy of the diploid cells during their first cell cycle. Using this approach we could with high spatio-temporal resolution visualize the differences between the interactions of the microtubule binding protein Stu2p with two of its binding partners, monitor the transient association of a Ran-GTPase with its receptors at the nuclear pore, and distinguish between protein interactions at the polar cortical domain at different phases of polar growth. These examples further demonstrate that protein-protein interactions identified from large-scale screens can be effectively followed up by high-resolution single-cell analysis. PMID:23511205

  6. Evolution and protein interactions of AP2 proteins in Brassicaceae: Evidence linking development and environmental responses.

    PubMed

    Zeng, Liping; Yin, Yue; You, Chenjiang; Pan, Qianli; Xu, Duo; Jin, Taijie; Zhang, Bailong; Ma, Hong

    2016-06-01

    Plants have evolved a large number of transcription factors (TF), which are enriched among duplicate genes, highlighting their roles in complex regulatory networks. The APETALA2/EREBP-like genes constitute a large plant TF family and participate in development and stress responses. To probe the conservation and divergence of AP2/EREBP genes, we analyzed the duplication patterns of this family in Brassicaceae and identified interacting proteins of representative Arabidopsis AP2/EREBP proteins. We found that many AP2/EREBP duplicates generated early in Brassicaceae history were quickly lost, but many others were retained in all tested Brassicaceae species, suggesting early functional divergence followed by persistent conservation. In addition, the sequences of the AP2 domain and exon numbers were highly conserved in rosids. Furthermore, we used 16 A. thaliana AP2/EREBP proteins as baits in yeast screens and identified 1,970 potential AP2/EREBP-interacting proteins, with a small subset of interactions verified in planta. Many AP2 genes also exhibit reduced expression in an anther-defective mutant, providing a possible link to developmental regulation. The putative AP2-interacting proteins participate in many functions in development and stress responses, including photomorphogenesis, flower development, pathogenesis, drought and cold responses, abscisic acid and auxin signaling. Our results present the AP2/EREBP evolution patterns in Brassicaceae, and support a proposed interaction network of AP2/EREBP proteins and their putative interacting proteins for further study. PMID:26472270

  7. Structure and expression of a novel compact myelin protein – Small VCP-interacting protein (SVIP)

    SciTech Connect

    Wu, Jiawen; Peng, Dungeng; Voehler, Markus; Sanders, Charles R.; Li, Jun

    2013-10-11

    Highlights: •SVIP (small p97/VCP-interacting protein) co-localizes with myelin basic protein (MBP) in compact myelin. •We determined that SVIP is an intrinsically disordered protein (IDP). •The helical content of SVIP increases dramatically during its interaction with negatively charged lipid membrane. •This study provides structural insight into interactions between SVIP and myelin membranes. -- Abstract: SVIP (small p97/VCP-interacting protein) was initially identified as one of many cofactors regulating the valosin containing protein (VCP), an AAA+ ATPase involved in endoplasmic-reticulum-associated protein degradation (ERAD). Our previous study showed that SVIP is expressed exclusively in the nervous system. In the present study, SVIP and VCP were seen to be co-localized in neuronal cell bodies. Interestingly, we also observed that SVIP co-localizes with myelin basic protein (MBP) in compact myelin, where VCP was absent. Furthermore, using nuclear magnetic resonance (NMR) and circular dichroism (CD) spectroscopic measurements, we determined that SVIP is an intrinsically disordered protein (IDP). However, upon binding to the surface of membranes containing a net negative charge, the helical content of SVIP increases dramatically. These findings provide structural insight into interactions between SVIP and myelin membranes.

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

    SciTech Connect

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

    2009-12-01

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

  9. Interaction of silver nanoparticles with proteins: a characteristic protein concentration dependent profile of SPR signal.

    PubMed

    Banerjee, Victor; Das, K P

    2013-11-01

    Silver nanoparticles are finding increasing applications in biological systems, for example as antimicrobial agents and potential candidates for control drug release systems. In all such applications, silver nanoparticles interact with proteins and other biomolecules. Hence, the study of such interactions is of considerable importance. While BSA has been extensively used as a model protein for the study of interaction with the silver nanoparticles, studies using other proteins are rather limited. The interaction of silver nanoparticles with light leads to collective oscillation of the conducting electrons giving rise to surface plasmon resonance (SPR). Here, we have studied the protein concentration dependence of the SPR band profiles for a number of proteins. We found that for all the proteins, with increase in concentration, the SPR band intensity initially decreased, reaching minima and then increased again leading to a characteristic "dip and rise" pattern. Minimum point of the pattern appeared to be related to the isoelectric point of the proteins. Detailed dynamic light scattering and transmission electron microscopy studies revealed that the consistency of SPR profile was dependent on the average particle size and state of association of the silver nanoparticles with the change in the protein concentration. Fluorescence spectroscopic studies showed the binding constants of the proteins with the silver nanoparticles were in the nano molar range with more than one nanoparticle binding to protein molecule. Structural studies demonstrate that protein retains its native-like structure on the nanoparticle surface unless the molar ratio of silver nanoparticles to protein exceeds 10. Our study reveals that nature of the protein concentration dependent profile of SPR signal is a general phenomena and mostly independent of the size and structure of the proteins.

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

    PubMed

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

    2015-09-28

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

  11. Spectroscopy reveals that ethyl esters interact with proteins in wine.

    PubMed

    Di Gaspero, Mattia; Ruzza, Paolo; Hussain, Rohanah; Vincenzi, Simone; Biondi, Barbara; Gazzola, Diana; Siligardi, Giuliano; Curioni, Andrea

    2017-02-15

    Impairment of wine aroma after vinification is frequently associated to bentonite treatments and this can be the result of protein removal, as recently demonstrated for ethyl esters. To evaluate the existence of an interaction between wine proteins and ethyl esters, the effects induced by these fermentative aroma compounds on the secondary structure and stability of VVTL1, a Thaumatin-like protein purified from wine, was analyzed by Synchrotron Radiation Circular Dichroism (SRCD) spectroscopy. The secondary structure of wine VVTL1 was not strongly affected by the presence of selected ethyl esters. In contrast, VVTL1 stability was slightly increased by the addition of ethyl-octanoate, -decanoate and -dodecanoate, but decreased by ethyl-hexanoate. This indicates the existence of an interaction between VVTL1 and at least some aroma compounds produced during fermentation. The data suggest that proteins removal from wine by bentonite can result in indirect removal of at least some aroma compounds associated with them. PMID:27664648

  12. Electrostatic interactions as governing the fouling in protein microfiltration

    NASA Astrophysics Data System (ADS)

    Ouammou, M.; Tijani, N.; Calvo, J. I.; Palacio, L.; Prádanos, P.; Hernández, A.

    2005-03-01

    The influence of pH and electrostatic interactions on the fouling mechanism during protein dead-end microfiltration (MF) has been investigated for two charged membranes. Polyethersulfone acidic membranes (ICE-450), being negatively charged, and basic ones (SB-6407), these positively charged, both from Pall Co., have been used in the investigations. BSA and Lysozyme solutions at different pH values (3.0, 5.0, 7.0, 8.5 and 10.0) were microfiltered through the membranes at a constant applied transmembrane pressure. Results have been analysed in terms of usual blocking filtration laws and a substantial change in the fouling behaviour has been observed when solution pH and/or membrane charge as the pressure was changed, this change being clearly related with the specific membrane-protein and protein-protein interactions.

  13. Reconstruction and Application of Protein–Protein Interaction Network

    PubMed Central

    Hao, Tong; Peng, Wei; Wang, Qian; Wang, Bin; Sun, Jinsheng

    2016-01-01

    The protein-protein interaction network (PIN) is a useful tool for systematic investigation of the complex biological activities in the cell. With the increasing interests on the proteome-wide interaction networks, PINs have been reconstructed for many species, including virus, bacteria, plants, animals, and humans. With the development of biological techniques, the reconstruction methods of PIN are further improved. PIN has gradually penetrated many fields in biological research. In this work we systematically reviewed the development of PIN in the past fifteen years, with respect to its reconstruction and application of function annotation, subsystem investigation, evolution analysis, hub protein analysis, and regulation mechanism analysis. Due to the significant role of PIN in the in-depth exploration of biological process mechanisms, PIN will be preferred by more and more researchers for the systematic study of the protein systems in various kinds of organisms. PMID:27338356

  14. [Interaction of two tumor suppressors: Phosphatase CTDSPL and Rb protein].

    PubMed

    Beniaminov, A D; Krasnov, G S; Dmitriev, A A; Puzanov, G A; Snopok, B A; Senchenko, V N; Kashuba, V I

    2016-01-01

    Earlier we established that CTDSPL gene encoding small carboxy-terminal domain serine phosphatase can be considered a classical tumor suppressor gene. Besides, transfection of tumor cell line MCF-7 with CTDSPL led to the content decrease of inactive phosphorylated form of another tumor suppressor, retinoblastoma protein (Rb), and subsequently to cell cycle arrest at the G1/S boundary. This result implied that small phosphatase CTDSPL is able to specifically dephosphorylate and activate Rb protein. In order to add some fuel to this hypothesis, in the present work we studied the interaction of two tumor suppressors CTDSPL and Rb in vitro. GST pool-down assay revealed that CTDSPL is able to precipitate Rb protein from MCF-7 cell extracts, while surface plasmon resonance technique showed that interaction of the two proteins is direct. Results of this study reassert that phosphatase CTDSPL and Rb could be involved in the common mechanism of cell cycle regulation. PMID:27414789

  15. Chaperone-interacting TPR proteins in Caenorhabditis elegans.

    PubMed

    Haslbeck, Veronika; Eckl, Julia M; Kaiser, Christoph J O; Papsdorf, Katharina; Hessling, Martin; Richter, Klaus

    2013-08-23

    The ATP-hydrolyzing molecular chaperones Hsc70/Hsp70 and Hsp90 bind a diverse set of tetratricopeptide repeat (TPR)-containing cofactors via their C-terminal peptide motifs IEEVD and MEEVD. These cochaperones contribute to substrate turnover and confer specific activities to the chaperones. Higher eukaryotic genomes encode a large number of TPR-domain-containing proteins. The human proteome contains more than 200 TPR proteins, and that of Caenorhabditis elegans, about 80. It is unknown how many of them interact with Hsc70 or Hsp90. We systematically screened the C. elegans proteome for TPR-domain-containing proteins that likely interact with Hsc70 and Hsp90 and ranked them due to their similarity with known chaperone-interacting TPRs. We find C. elegans to encode many TPR proteins, which are not present in yeast. All of these have homologs in fruit fly or humans. Highly ranking uncharacterized open reading frames C33H5.8, C34B2.5 and ZK370.8 may encode weakly conserved homologs of the human proteins RPAP3, TTC1 and TOM70. C34B2.5 and ZK370.8 bind both Hsc70 and Hsp90 with low micromolar affinities. Mutation of amino acids involved in EEVD binding disrupts the interaction. In vivo, ZK370.8 is localized to mitochondria in tissues with known chaperone requirements, while C34B2.5 colocalizes with Hsc70 in intestinal cells. The highest-ranking open reading frame with non-conserved EEVD-interacting residues, F52H3.5, did not show any binding to Hsc70 or Hsp90, suggesting that only about 15 of the TPR-domain-containing proteins in C. elegans interact with chaperones, while the many others may have evolved to bind other ligands.

  16. Dynamic imaging of protein-protein interactions by MP-FLIM

    NASA Astrophysics Data System (ADS)

    Ameer-Beg, Simon M.; Peter, Marion; Keppler, Melanie D.; Prag, Soren; Barber, Paul R.; Ng, Tony C.; Vojnovic, Borivoj

    2005-03-01

    The spatio-temporal localization of molecular interactions within cells in situ is of great importance in elucidating the key mechanisms in regulation of fundamental process within the cell. Measurements of such near-field localization of protein complexes may be achieved by the detection of fluorescence (or Forster) resonance energy transfer (FRET) between protein-conjugated fluorophores. We demonstrate the applicability of time-correlated single photon counting multiphoton microscopy to the spatio-temporal localization of protein-protein interactions in live and fixed cell populations. Intramolecular interactions between protein hetero-dimers are investigated using green fluorescent protein variants. We present an improved monomeric form of the red fluorescent protein, mRFP1, as the acceptor in biological fluorescence resonance energy transfer (FRET) experiments using the enhanced green fluorescent protein as donor. We find particular advantage in using this fluorophore pair for quantitative measurements of FRET. The technique was exploited to demonstrate a novel receptor-kinase interaction between the chemokine receptor (CXCR4) and protein kinase C (PKC) α in carcinoma cells for both live and fixed cell experiments.

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

    SciTech Connect

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

    2008-01-01

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

  18. Protein-lipid interactions in bilayer membranes: a lattice model.

    PubMed

    Pink, D A; Chapman, D

    1979-04-01

    A lattice model has been developed to study the effects of intrinsic membrane proteins upon the thermodynamic properties of a lipid bilayer membrane. We assume that only nearest-neighbor van der Waals and steric interactions are important and that the polar group interactions can be represented by effective pressure-area terms. Phase diagrams, the temperature T(0), which locates the gel-fluid melting, the transition enthalpy, and correlations were calculated by mean field and cluster approximations. Average lipid chain areas and chain areas when the lipid is in a given protein environment were obtained. Proteins that have a "smooth" homogeneous surface ("cholesterol-like") and those that have inhomogeneous surfaces or that bind lipids specifically were considered. We find that T(0) can vary depending upon the interactions and that another peak can appear upon the shoulder of the main peak which reflects the melting of a eutectic mixture. The transition enthalpy decreases generally, as was found before, but when a second peak appears departures from this behavior reflect aspects of the eutectic mixture. We find that proteins have significant nonzero probabilities for being adjacent to one another so that no unbroken "annulus" of lipid necessarily exists around a protein. If T(0) does not increase much, or decreases, with increasing c, then lipids adjacent to a protein cannot all be all-trans on the time scale (10(-7) sec) of our system. Around a protein the lipid correlation depth is about one lipid layer, and this increases with c. Possible consequences of ignoring changes in polar group interactions due to clustering of proteins are discussed.

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

    PubMed

    Cui, Di; Ou, Shuching; Patel, Sandeep

    2014-12-01

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

  20. Steric interactions determine side-chain conformations in protein cores.

    PubMed

    Caballero, D; Virrueta, A; O'Hern, C S; Regan, L

    2016-09-01

    We investigate the role of steric interactions in defining side-chain conformations in protein cores. Previously, we explored the strengths and limitations of hard-sphere dipeptide models in defining sterically allowed side-chain conformations and recapitulating key features of the side-chain dihedral angle distributions observed in high-resolution protein structures. Here, we show that modeling residues in the context of a particular protein environment, with both intra- and inter-residue steric interactions, is sufficient to specify which of the allowed side-chain conformations is adopted. This model predicts 97% of the side-chain conformations of Leu, Ile, Val, Phe, Tyr, Trp and Thr core residues to within 20°. Although the hard-sphere dipeptide model predicts the observed side-chain dihedral angle distributions for both Thr and Ser, the model including the protein environment predicts side-chain conformations to within 20° for only 60% of core Ser residues. Thus, this approach can identify the amino acids for which hard-sphere interactions alone are sufficient and those for which additional interactions are necessary to accurately predict side-chain conformations in protein cores. We also show that our approach can predict alternate side-chain conformations of core residues, which are supported by the observed electron density.

  1. Nonlinear dynamics of specific DNA-protein interactions

    NASA Astrophysics Data System (ADS)

    Dwiputra, D.; Hidayat, W.; Khairani, R.; Zen, F. P.

    2016-03-01

    Interactions between DNA binding protein and specific base pairs of nucleic acid is critical for biological process. We propose a new model of DNA-protein interactions to depict the dynamics of specific DNA-protein interactions. Hydrogen bonds (H-bonds) are, among the other intermolecular interactions in DNA, the most distinctive in term of specificity of molecular bonds. As H-bonds account for specificity, we only consider the dynamics affected by H-bonds between DNA base pairs and H-bonds connecting protein side chains and DNA. The H-bonds are modelled by Morse potentials and coupling terms in the Hamiltonian of coupled oscillators resembling a coupling between planar DNA chain and a protein molecule. In this paper we give a perturbative approach as an attempt for a soliton solution. The solution is in the form of nonlinear travelling wave having the amplitudes satisfying coupled nonlinear Schrodinger equations and is interpreted as the mediator for nonlocal transmittance of biological information in DNA.

  2. Interaction of receptor-activity-modifying protein1 with tubulin.

    PubMed

    Kunz, Thomas H; Mueller-Steiner, Sarah; Schwerdtfeger, Kerstin; Kleinert, Peter; Troxler, Heinz; Kelm, Jens M; Ittner, Lars M; Fischer, Jan A; Born, Walter

    2007-08-01

    Receptor-activity-modifying protein (RAMP) 1 is an accessory protein of the G protein-coupled calcitonin receptor-like receptor (CLR). The CLR/RAMP1 heterodimer defines a receptor for the potent vasodilatory calcitonin gene-related peptide. A wider tissue distribution of RAMP1, as compared to that of the CLR, is consistent with additional biological functions. Here, glutathione S-transferase (GST) pull-down, coimmunoprecipitation and yeast two-hybrid experiments identified beta-tubulin as a novel RAMP1-interacting protein. GST pull-down experiments indicated interactions between the N- and C-terminal domains of RAMP1 and beta-tubulin. Yeast two-hybrid experiments confirmed the interaction between the N-terminal region of RAMP1 and beta-tubulin. Interestingly, alpha-tubulin was co-extracted with beta-tubulin in pull-down experiments and immunoprecipitation of RAMP1 coprecipitated alpha- and beta-tubulin. Confocal microscopy indicated colocalization of RAMP1 and tubulin predominantly in axon-like processes of neuronal differentiated human SH-SY5Y neuroblastoma cells. In conclusion, the findings point to biological roles of RAMP1 beyond its established interaction with G protein-coupled receptors. PMID:17493758

  3. REVIEW ARTICLE: DNA protein interactions and bacterial chromosome architecture

    NASA Astrophysics Data System (ADS)

    Stavans, Joel; Oppenheim, Amos

    2006-12-01

    Bacteria, like eukaryotic organisms, must compact the DNA molecule comprising their genome and form a functional chromosome. Yet, bacteria do it differently. A number of factors contribute to genome compaction and organization in bacteria, including entropic effects, supercoiling and DNA-protein interactions. A gamut of new experimental techniques have allowed new advances in the investigation of these factors, and spurred much interest in the dynamic response of the chromosome to environmental cues, segregation, and architecture, during both exponential and stationary phases. We review these recent developments with emphasis on the multifaceted roles that DNA-protein interactions play.

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

    PubMed

    Jakobek, Lidija

    2015-05-15

    Polyphenols are secondary metabolites in plants, investigated intensively because of their potential positive effects on human health. Their bioavailability and mechanism of positive effects have been studied, in vitro and in vivo. Lately, a high number of studies takes into account the interactions of polyphenols with compounds present in foods, like carbohydrates, proteins or lipids, because these food constituents can have significant effects on the activity of phenolic compounds. This paper reviews the interactions between phenolic compounds and lipids, carbohydrates and proteins and their impact on polyphenol activity. PMID:25577120

  5. Kinetic analysis of drug-protein interactions by affinity chromatography.

    PubMed

    Bi, Cong; Beeram, Sandya; Li, Zhao; Zheng, Xiwei; Hage, David S

    2015-10-01

    Information on the kinetics of drug-protein interactions is of crucial importance in drug discovery and development. Several methods based on affinity chromatography have been developed in recent years to examine the association and dissociation rates of these processes. These techniques include band-broadening measurements, the peak decay method, peak fitting methods, the split-peak method, and free fraction analysis. This review will examine the general principles and applications of these approaches and discuss their use in the characterization, screening and analysis of drug-protein interactions in the body. PMID:26724332

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

    PubMed

    Jakobek, Lidija

    2015-05-15

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

  7. Refining literature curated protein interactions using expert opinions.

    PubMed

    Tastan, Oznur; Qi, Yanjun; Carbonell, Jaime G; Klein-Seetharaman, Judith

    2015-01-01

    The availability of high-quality physical interaction datasets is a prerequisite for system-level analysis of interactomes and supervised models to predict protein-protein interactions (PPIs). One source is literature-curated PPI databases in which pairwise associations of proteins published in the scientific literature are deposited. However, PPIs may not be clearly labelled as physical interactions affecting the quality of the entire dataset. In order to obtain a high-quality gold standard dataset for PPIs between human immunodeficiency virus (HIV-1) and its human host, we adopted a crowd-sourcing approach. We collected expert opinions and utilized an expectation-maximization based approach to estimate expert labeling quality. These estimates are used to infer the probability of a reported PPI actually being a direct physical interaction given the set of expert opinions. The effectiveness of our approach is demonstrated through synthetic data experiments and a high quality physical interaction network between HIV and human proteins is obtained. Since many literature-curated databases suffer from similar challenges, the framework described herein could be utilized in refining other databases. The curated data is available at http://www.cs.bilkent.edu.tr/~oznur.tastan/supp/psb2015/.

  8. Membrane interacting regions of Dengue virus NS2A protein.

    PubMed

    Nemésio, Henrique; Villalaín, José

    2014-08-28

    The Dengue virus (DENV) NS2A protein, essential for viral replication, is a poorly characterized membrane protein. NS2A displays both protein/protein and membrane/protein interactions, yet neither its functions in the viral cycle nor its active regions are known with certainty. To highlight the different membrane-active regions of NS2A, we characterized the effects of peptides derived from a peptide library encompassing this protein's full length on different membranes by measuring their membrane leakage induction and modulation of lipid phase behavior. Following this initial screening, one region, peptide dens25, had interesting effects on membranes; therefore, we sought to thoroughly characterize this region's interaction with membranes. This peptide presents an interfacial/hydrophobic pattern characteristic of a membrane-proximal segment. We show that dens25 strongly interacts with membranes that contain a large proportion of lipid molecules with a formal negative charge, and that this effect has a major electrostatic contribution. Considering its membrane modulating capabilities, this region might be involved in membrane rearrangements and thus be important for the viral cycle.

  9. A coarse grain model for protein-surface interactions

    NASA Astrophysics Data System (ADS)

    Wei, Shuai; Knotts, Thomas A.

    2013-09-01

    The interaction of proteins with surfaces is important in numerous applications in many fields—such as biotechnology, proteomics, sensors, and medicine—but fundamental understanding of how protein stability and structure are affected by surfaces remains incomplete. Over the last several years, molecular simulation using coarse grain models has yielded significant insights, but the formalisms used to represent the surface interactions have been rudimentary. We present a new model for protein surface interactions that incorporates the chemical specificity of both the surface and the residues comprising the protein in the context of a one-bead-per-residue, coarse grain approach that maintains computational efficiency. The model is parameterized against experimental adsorption energies for multiple model peptides on different types of surfaces. The validity of the model is established by its ability to quantitatively and qualitatively predict the free energy of adsorption and structural changes for multiple biologically-relevant proteins on different surfaces. The validation, done with proteins not used in parameterization, shows that the model produces remarkable agreement between simulation and experiment.

  10. Influence of homology and node age on the growth of protein-protein interaction networks

    NASA Astrophysics Data System (ADS)

    Bottinelli, Arianna; Bassetti, Bruno; Lagomarsino, Marco Cosentino; Gherardi, Marco

    2012-10-01

    Proteins participating in a protein-protein interaction network can be grouped into homology classes following their common ancestry. Proteins added to the network correspond to genes added to the classes, so the dynamics of the two objects are intrinsically linked. Here we first introduce a statistical model describing the joint growth of the network and the partitioning of nodes into classes, which is studied through a combined mean-field and simulation approach. We then employ this unified framework to address the specific issue of the age dependence of protein interactions through the definition of three different node wiring or divergence schemes. A comparison with empirical data indicates that an age-dependent divergence move is necessary in order to reproduce the basic topological observables together with the age correlation between interacting nodes visible in empirical data. We also discuss the possibility of nontrivial joint partition and topology observables.

  11. Visualization of host-polerovirus interaction topologies using Protein Interaction Reporter technology

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Demonstrating direct interactions between host and virus proteins during infection is a major goal and challenge for the field of virology. The majority of interactions are not binary or easily amenable to structural determination. Using infectious preparations of a polerovirus (Potato leafroll viru...

  12. Comparative analysis of protein-protein interactions in the defense response of rice and wheat

    PubMed Central

    2013-01-01

    Background Despite the importance of wheat as a major staple crop and the negative impact of diseases on its production worldwide, the genetic mechanisms and gene interactions involved in the resistance response in wheat are still poorly understood. The complete sequence of the rice genome has provided an extremely useful parallel road map for genetic and genomics studies in wheat. The recent construction of a defense response interactome in rice has the potential to further enhance the translation of advances in rice to wheat and other grasses. The objective of this study was to determine the degree of conservation in the protein-protein interactions in the rice and wheat defense response interactomes. As entry points we selected proteins that serve as key regulators of the rice defense response: the RAR1/SGT1/HSP90 protein complex, NPR1, XA21, and XB12 (XA21 interacting protein 12). Results Using available wheat sequence databases and phylogenetic analyses we identified and cloned the wheat orthologs of these four rice proteins, including recently duplicated paralogs, and their known direct interactors and tested 86 binary protein interactions using yeast-two-hybrid (Y2H) assays. All interactions between wheat proteins were further tested using in planta bimolecular fluorescence complementation (BiFC). Eighty three percent of the known rice interactions were confirmed when wheat proteins were tested with rice interactors and 76% were confirmed using wheat protein pairs. All interactions in the RAR1/SGT1/ HSP90, NPR1 and XB12 nodes were confirmed for the identified orthologous wheat proteins, whereas only forty four percent of the interactions were confirmed in the interactome node centered on XA21. We hypothesize that this reduction may be associated with a different sub-functionalization history of the multiple duplications that occurred in this gene family after the divergence of the wheat and rice lineages. Conclusions The observed high conservation of

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

    SciTech Connect

    Weiss, Shimon

    2006-08-30

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

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

    PubMed Central

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

    2015-01-01

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

  15. Systematic Analysis of Bacterial Effector-Postsynaptic Density 95/Disc Large/Zonula Occludens-1 (PDZ) Domain Interactions Demonstrates Shigella OspE Protein Promotes Protein Kinase C Activation via PDLIM Proteins*

    PubMed Central

    Yi, Chae-ryun; Allen, John E.; Russo, Brian; Lee, Soo Young; Heindl, Jason E.; Baxt, Leigh A.; Herrera, Bobby Brooke; Kahoud, Emily; MacBeath, Gavin; Goldberg, Marcia B.

    2014-01-01

    Diseases caused by many Gram-negative bacterial pathogens depend on the activities of bacterial effector proteins that are delivered into eukaryotic cells via specialized secretion systems. Effector protein function largely depends on specific subcellular targeting and specific interactions with cellular ligands. PDZ domains are common domains that serve to provide specificity in protein-protein interactions in eukaryotic systems. We show that putative PDZ-binding motifs are significantly enriched among effector proteins delivered into mammalian cells by certain bacterial pathogens. We use PDZ domain microarrays to identify candidate interaction partners of the Shigella flexneri effector proteins OspE1 and OspE2, which contain putative PDZ-binding motifs. We demonstrate in vitro and in cells that OspE proteins interact with PDLIM7, a member of the PDLIM family of proteins, which contain a PDZ domain and one or more LIM domains, protein interaction domains that participate in a wide variety of functions, including activation of isoforms of protein kinase C (PKC). We demonstrate that activation of PKC during S. flexneri infection is attenuated in the absence of PDLIM7 or OspE proteins and that the OspE PDZ-binding motif is required for wild-type levels of PKC activation. These results are consistent with a model in which binding of OspE to PDLIM7 during infection regulates the activity of PKC isoforms that bind to the PDLIM7 LIM domain. PMID:25124035

  16. Systematic analysis of bacterial effector-postsynaptic density 95/disc large/zonula occludens-1 (PDZ) domain interactions demonstrates Shigella OspE protein promotes protein kinase C activation via PDLIM proteins.

    PubMed

    Yi, Chae-ryun; Allen, John E; Russo, Brian; Lee, Soo Young; Heindl, Jason E; Baxt, Leigh A; Herrera, Bobby Brooke; Kahoud, Emily; MacBeath, Gavin; Goldberg, Marcia B

    2014-10-24

    Diseases caused by many Gram-negative bacterial pathogens depend on the activities of bacterial effector proteins that are delivered into eukaryotic cells via specialized secretion systems. Effector protein function largely depends on specific subcellular targeting and specific interactions with cellular ligands. PDZ domains are common domains that serve to provide specificity in protein-protein interactions in eukaryotic systems. We show that putative PDZ-binding motifs are significantly enriched among effector proteins delivered into mammalian cells by certain bacterial pathogens. We use PDZ domain microarrays to identify candidate interaction partners of the Shigella flexneri effector proteins OspE1 and OspE2, which contain putative PDZ-binding motifs. We demonstrate in vitro and in cells that OspE proteins interact with PDLIM7, a member of the PDLIM family of proteins, which contain a PDZ domain and one or more LIM domains, protein interaction domains that participate in a wide variety of functions, including activation of isoforms of protein kinase C (PKC). We demonstrate that activation of PKC during S. flexneri infection is attenuated in the absence of PDLIM7 or OspE proteins and that the OspE PDZ-binding motif is required for wild-type levels of PKC activation. These results are consistent with a model in which binding of OspE to PDLIM7 during infection regulates the activity of PKC isoforms that bind to the PDLIM7 LIM domain.

  17. The Sendai virus V protein interacts with the NP protein to regulate viral genome RNA replication.

    PubMed

    Horikami, S M; Smallwood, S; Moyer, S A

    1996-08-15

    The interactions of Sendai virus proteins required for viral RNA synthesis have been characterized both by the yeast two-hybrid system and through the use of glutathione S-transferase (gst)-viral fusion proteins synthesized in mammalian cells. Using the two-hybrid system we have confirmed the previously identified P-L (RNA polymerase), NPo-P (encapsidation substrate), and P-P complexes and now demonstrate NP-NP and NPo-V protein interactions. Expression of gstP and P proteins and binding to glutathione-Sepharose beads as a measure of complex formation confirmed the P-P interaction. The P-gstP binding occurred only on expression of the proteins in the same cell and was mapped to amino acids 345-411. We also show that full-length and deletion gstV and gstW proteins bound NPo protein when these sets of proteins were coexpressed and have identified one required region from amino acids 78-316. Neither gstV nor gstW bound NP assembled into nucleocapsids. Furthermore, both V and W proteins lacking the N-terminal 77 amino acids inhibited DI-H genome replication in vitro, showing the biological relevance of the remaining region. We propose that the specific inhibition of genome replication by V and W proteins occurs through interference with either the formation or the use of the NPo-P encapsidation substrate.

  18. Regulation of Latent Membrane Protein 1 Signaling through Interaction with Cytoskeletal Proteins

    PubMed Central

    Holthusen, Kirsten; Talaty, Pooja

    2015-01-01

    ABSTRACT Latent membrane protein 1 (LMP1) of Epstein-Barr virus (EBV) induces constitutive signaling in EBV-infected cells to ensure the survival of the latently infected cells. LMP1 is localized to lipid raft domains to induce signaling. In the present study, a genome-wide screen based on bimolecular fluorescence complementation (BiFC) was performed to identify LMP1-binding proteins. Several actin cytoskeleton-associated proteins were identified in the screen. Overexpression of these proteins affected LMP1-induced signaling. BiFC between the identified proteins and LMP1 was localized to lipid raft domains and was dependent on LMP1-induced signaling. Proximity biotinylation assays with LMP1 induced biotinylation of the actin-associated proteins, which were shifted in molecular mass. Together, the findings of this study suggest that the association of LMP1 with lipid rafts is mediated at least in part through interactions with the actin cytoskeleton. IMPORTANCE LMP1 signaling requires oligomerization, lipid raft partitioning, and binding to cellular adaptors. The current study utilized a genome-wide screen to identify several actin-associated proteins as candidate LMP1-binding proteins. The interaction between LMP1 and these proteins was localized to lipid rafts and dependent on LMP1 signaling. This suggests that the association of LMP1 with lipid rafts is mediated through interactions with actin-associated proteins. PMID:25948738

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

    PubMed

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

    2016-06-01

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

  20. Silencing of the Menkes copper-transporting ATPase (Atp7a) gene increases cyclin D1 protein expression and impairs proliferation of rat intestinal epithelial (IEC-6) cells.

    PubMed

    Gulec, Sukru; Collins, James F

    2014-10-01

    The Menkes copper-transporting ATPase (Atp7a) has dual roles in mammalian enterocytes: pumping copper into the trans-Golgi network (to support cuproenzyme synthesis) and across the basolateral membrane (to deliver dietary copper to the blood). Atp7a is strongly induced in the rodent duodenum during iron deprivation, suggesting that copper influences iron homeostasis. To investigate this possibility, Atp7a was silenced in rat intestinal epithelial (IEC-6) cells. Irrespective of its influence on iron homeostasis, an unexpected observation was made in the Atp7a knockdown (KD) cells: the cells grew slower (∼40% fewer cells at 96h) and were larger than negative-control shRNA-transfected cells. Lack of Atp7a activity thus perturbed cell cycle control. To elucidate a possible molecular mechanism, expression of two important cell cycle control proteins was assessed. Cyclin D1 (CD1) protein expression increased in Atp7a KD cells whereas proliferating-cell nuclear antigen (PCNA) expression was unaltered. Increased CD1 expression is consistent with impaired cell cycle progression. Expression of additional cell proliferation marker genes (p21 and Ki67) was also investigated; p21 expression increased, whereas Ki67 decreased, both consistent with diminished cell growth. Further experiments were designed to determine whether increased cellular copper content was the trigger for the altered growth phenotype of the Atp7a KD cells. Copper loading, however, did not influence the expression patterns of CD1, p21 or Ki67. Overall, these findings demonstrate that Atp7a is required for normal proliferation of IEC-6 cells. How Atp7a influences cell growth is unclear, but the underlying mechanism could relate to its roles in intracellular copper distribution or cuproenzyme synthesis.

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

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

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

  2. Key interactions of surfactants in therapeutic protein formulations: A review.

    PubMed

    Khan, Tarik A; Mahler, Hanns-Christian; Kishore, Ravuri S K

    2015-11-01

    Proteins as amphiphilic, surface-active macromolecules, demonstrate substantial interfacial activity, which causes considerable impact on their multifarious applications. A commonly adapted measure to prevent interfacial damage to proteins is the use of nonionic surfactants. Particularly in biotherapeutic formulations, the use of nonionic surfactants is ubiquitous in order to prevent the impact of interfacial stress on drug product stability. The scope of this review is to convey the current understanding of interactions of nonionic surfactants with proteins both at the interface and in solution, with specific focus to their effects on biotherapeutic formulations.

  3. PPI-IRO: a two-stage method for protein-protein interaction extraction based on interaction relation ontology.

    PubMed

    Li, Chuan-Xi; Chen, Peng; Wang, Ru-Jing; Wang, Xiu-Jie; Su, Ya-Ru; Li, Jinyan

    2014-01-01

    Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identification of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifies and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At first, IRO is applied in a binary classifier to determine whether sentences contain a relation or not. Then, IRO is taken to guide PPI extraction by building sentence dependency parse tree. Comprehensive and quantitative evaluations and detailed analyses are used to demonstrate the significant performance of IRO on relation sentences classification and PPI extraction. Our PPI extraction method yielded a recall of around 80% and 90% and an F1 of around 54% and 66% on corpora of AIMed and BioInfer, respectively, which are superior to most existing extraction methods. PMID:25757257

  4. PPI-IRO: a two-stage method for protein-protein interaction extraction based on interaction relation ontology.

    PubMed

    Li, Chuan-Xi; Chen, Peng; Wang, Ru-Jing; Wang, Xiu-Jie; Su, Ya-Ru; Li, Jinyan

    2014-01-01

    Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identification of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifies and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At first, IRO is applied in a binary classifier to determine whether sentences contain a relation or not. Then, IRO is taken to guide PPI extraction by building sentence dependency parse tree. Comprehensive and quantitative evaluations and detailed analyses are used to demonstrate the significant performance of IRO on relation sentences classification and PPI extraction. Our PPI extraction method yielded a recall of around 80% and 90% and an F1 of around 54% and 66% on corpora of AIMed and BioInfer, respectively, which are superior to most existing extraction methods.

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

    PubMed

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

    2015-01-01

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

  6. Improving the Understanding of Pathogenesis of Human Papillomavirus 16 via Mapping Protein-Protein Interaction Network

    PubMed Central

    Dong, Yongcheng; Kuang, Qifan; Dai, Xu; Li, Rong; Wu, Yiming; Leng, Weijia; Li, Yizhou; Li, Menglong

    2015-01-01

    The human papillomavirus 16 (HPV16) has high risk to lead various cancers and afflictions, especially, the cervical cancer. Therefore, investigating the pathogenesis of HPV16 is very important for public health. Protein-protein interaction (PPI) network between HPV16 and human was used as a measure to improve our understanding of its pathogenesis. By adopting sequence and topological features, a support vector machine (SVM) model was built to predict new interactions between HPV16 and human proteins. All interactions were comprehensively investigated and analyzed. The analysis indicated that HPV16 enlarged its scope of influence by interacting with human proteins as much as possible. These interactions alter a broad array of cell cycle progression. Furthermore, not only was HPV16 highly prone to interact with hub proteins and bottleneck proteins, but also it could effectively affect a breadth of signaling pathways. In addition, we found that the HPV16 evolved into high carcinogenicity on the condition that its own reproduction had been ensured. Meanwhile, this work will contribute to providing potential new targets for antiviral therapeutics and help experimental research in the future. PMID:25961044

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

    PubMed

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

    2012-01-01

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

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

    PubMed

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

    2012-01-01

    We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein's neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution. PMID:22768057

  9. STRING v10: protein-protein interaction networks, integrated over the tree of life.

    PubMed

    Szklarczyk, Damian; Franceschini, Andrea; Wyder, Stefan; Forslund, Kristoffer; Heller, Davide; Huerta-Cepas, Jaime; Simonovic, Milan; Roth, Alexander; Santos, Alberto; Tsafou, Kalliopi P; Kuhn, Michael; Bork, Peer; Jensen, Lars J; von Mering, Christian

    2015-01-01

    The many functional partnerships and interactions that occur between proteins are at the core of cellular processing and their systematic characterization helps to provide context in molecular systems biology. However, known and predicted interactions are scattered over multiple resources, and the available data exhibit notable differences in terms of quality and completeness. The STRING database (http://string-db.org) aims to provide a critical assessment and integration of protein-protein interactions, including direct (physical) as well as indirect (functional) associations. The new version 10.0 of STRING covers more than 2000 organisms, which has necessitated novel, scalable algorithms for transferring interaction information between organisms. For this purpose, we have introduced hierarchical and self-consistent orthology annotations for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution. Further improvements in version 10.0 include a completely redesigned prediction pipeline for inferring protein-protein associations from co-expression data, an API interface for the R computing environment and improved statistical analysis for enrichment tests in user-provided networks.

  10. STRING v10: protein-protein interaction networks, integrated over the tree of life.

    PubMed

    Szklarczyk, Damian; Franceschini, Andrea; Wyder, Stefan; Forslund, Kristoffer; Heller, Davide; Huerta-Cepas, Jaime; Simonovic, Milan; Roth, Alexander; Santos, Alberto; Tsafou, Kalliopi P; Kuhn, Michael; Bork, Peer; Jensen, Lars J; von Mering, Christian

    2015-01-01

    The many functional partnerships and interactions that occur between proteins are at the core of cellular processing and their systematic characterization helps to provide context in molecular systems biology. However, known and predicted interactions are scattered over multiple resources, and the available data exhibit notable differences in terms of quality and completeness. The STRING database (http://string-db.org) aims to provide a critical assessment and integration of protein-protein interactions, including direct (physical) as well as indirect (functional) associations. The new version 10.0 of STRING covers more than 2000 organisms, which has necessitated novel, scalable algorithms for transferring interaction information between organisms. For this purpose, we have introduced hierarchical and self-consistent orthology annotations for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution. Further improvements in version 10.0 include a completely redesigned prediction pipeline for inferring protein-protein associations from co-expression data, an API interface for the R computing environment and improved statistical analysis for enrichment tests in user-provided networks. PMID:25352553

  11. Transport, assembly, and dynamics in systems of interacting proteins

    NASA Astrophysics Data System (ADS)

    Elowitz, Michael Bernard

    1999-10-01

    Many of the functions performed by cells are controlled by networks of interacting proteins. This thesis explores optical techniques for monitoring and perturbing protein networks and measuring protein diffusion. In addition, it discusses the design of simple artificial genetic networks. A useful tool for tagging proteins in diverse organisms is the Green Fluorescent Protein (GFP), which absorbs blue light and emits green light. We report the discovery of a new state of this protein in which it absorbs green light and emits red light. It can be switched to this new state with a pulse of blue light. This effect is useful for marking proteins in a certain region and following their subsequent movement. We use this technique to measure diffusion of proteins inside living bacterial cells. The apparent diffusion coefficient we obtain for GFP is about ten times lower than its value in water. This reflects the crowded conditions in bacterial cytoplasm and places a constraint on the response time of diffusion-based signalling networks. We next turn to systems of motor proteins and microtubules. We show how motor protein forces can be estimated from spiral motions of pinned filaments in motility assays. Then we explore spatially and temporally localized inactivation of specific proteins using Chromophore-Assisted Laser Inactivation (CALI). In this method, dyes are attached to target proteins, allowing them to be inactivated by controlled pulses of light. By inactivating motor proteins with this technique, we can locally disrupt an in vitro assembly process. Finally, we address the problem of constructing an artificial genetic network in order to see whether simple, artificial systems behave as expected from detailed modeling of their components. We analyze the expected behavior of an oscillator built of bacterial transcriptional repressors, and lay the groundwork for its actual construction.

  12. Dynamic Protein Acetylation in Plant–Pathogen Interactions

    PubMed Central

    Song, Gaoyuan; Walley, Justin W.

    2016-01-01

    Pathogen infection triggers complex molecular perturbations within host cells that results in either resistance or susceptibility. Protein acetylation is an emerging biochemical modification that appears to play central roles during host–pathogen interactions. To date, research in this area has focused on two main themes linking protein acetylation to plant immune signaling. Firstly, it has been established that proper gene expression during defense responses requires modulation of histone acetylation within target gene promoter regions. Second, some pathogens can deliver effector molecules that encode acetyltransferases directly within the host cell to modify acetylation of specific host proteins. Collectively these findings suggest that the acetylation level for a range of host proteins may be modulated to alter the outcome of pathogen infection. This review will focus on summarizing our current understanding of the roles of protein acetylation in plant defense and highlight the utility of proteomics approaches to uncover the complete repertoire of acetylation changes triggered by pathogen infection. PMID:27066055

  13. Interactions of legionella effector proteins with host phosphoinositide lipids.

    PubMed

    Weber, Stephen; Dolinsky, Stephanie; Hilbi, Hubert

    2013-01-01

    By means of the Icm/Dot type IV secretion system Legionella pneumophila translocates several effector proteins into host cells, where they anchor to the cytoplasmic face of the LCV membrane by binding to phosphoinositide (PI) lipids. Thus, phosphatidylinositol-4-phosphate anchors the effector proteins SidC and SidM, which promote the interaction of LCVs with the ER and the secretory vesicle trafficking -pathway. In this chapter, we describe protocols to (1) identify PI-binding proteins in Legionella lysates using PI-beads, (2) determine PI-binding specificities and affinities of recombinant Legionella effector proteins by protein-lipid overlays, and (3) use Legionella effectors to identify cellular PI lipids.

  14. Structural Analysis of Protein-Protein Interactions in Type I Polyketide Synthases

    PubMed Central

    Xu, Wei; Qiao, Kangjian; Tang, Yi

    2013-01-01

    Polyketide synthases (PKSs) are responsible for synthesizing a myriad of natural products with agricultural, medicinal relevance. The PKSs consist of multiple functional domains of which each can catalyze a specified chemical reaction leading to the synthesis of polyketides. Biochemical studies showed that protein-substrate and protein-protein interactions play crucial roles in these complex regio-/stereo- selective biochemical processes. Recent developments on X-ray crystallography and protein NMR techniques have allowed us to understand the biosynthetic mechanism of these enzymes from their structures. These structural studies have facilitated the elucidation of sequence-function relationship of PKSs and will ultimately contribute to the prediction of product structure. This review will focus on the current knowledge of type I PKS structures and the protein-protein interactions in this system. PMID:23249187

  15. Protein-Phospholipid Interactions in Nonclassical Protein Secretion: Problem and Methods of Study

    PubMed Central

    Prudovsky, Igor; Kumar, Thallapuranam Krishnaswamy Suresh; Sterling, Sarah; Neivandt, David

    2013-01-01

    Extracellular proteins devoid of signal peptides use nonclassical secretion mechanisms for their export. These mechanisms are independent of the endoplasmic reticulum and Golgi. Some nonclassically released proteins, particularly fibroblast growth factors (FGF) 1 and 2, are exported as a result of their direct translocation through the cell membrane. This process requires specific interactions of released proteins with membrane phospholipids. In this review written by a cell biologist, a structural biologist and two membrane engineers, we discuss the following subjects: (i) Phenomenon of nonclassical protein release and its biological significance; (ii) Composition of the FGF1 multiprotein release complex (MRC); (iii) The relationship between FGF1 export and acidic phospholipid externalization; (iv) Interactions of FGF1 MRC components with acidic phospholipids; (v) Methods to study the transmembrane translocation of proteins; (vi) Membrane models to study nonclassical protein release. PMID:23396106

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

    PubMed

    Xu, Wei; Qiao, Kangjian; Tang, Yi

    2013-01-01

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

  17. The tandem affinity purification method: an efficient system for protein complex purification and protein interaction identification.

    PubMed

    Xu, Xiaoli; Song, Yuan; Li, Yuhua; Chang, Jianfeng; Zhang, Hua; An, Lizhe

    2010-08-01

    Isolation and identification of protein partners in multi-protein complexes are important in gaining further insights into the cellular roles of proteins and determining the possible mechanisms by which proteins have an effect in the molecular environment. The tandem affinity purification (TAP) method was originally developed in yeast for the purification of protein complexes and identification of protein-protein interactions. With modifications to this method and many variations in the original tag made over the past few years, the TAP system could be applied in mammalian, plant, bacteria and other systems for protein complex analysis. In this review, we describe the application of the TAP method in various organisms, the modification in the tag, the disadvantages, the developments and the future prospects of the TAP method. PMID:20399864

  18. Identification of a novel nurr1-interacting protein.

    PubMed

    Luo, Yu; Xing, Feng; Guiliano, Rita; Federoff, Howard J

    2008-09-10

    The orphan nuclear receptor Nurr1 is required for the development of ventral mesencephalic dopaminergic neurons in mice. One of the possible mechanisms that might contribute to the regulation activity of Nurr1 is through interaction with other proteins. To identify potential partners of Nurr1, we screened a yeast two-hybrid library from developing mouse embryonic mesencephalon with the Nurr1 ligand-binding domain (NLBD). We identified a novel interacting protein, termed the Nurr1-interacting protein (NuIP). We demonstrate that it specifically interacts with NLBD using the mammalian two-hybrid assay and coimmunoprecipitation studies in MN9D cells. In addition, we show that NuIP interacts with Nurr1 in lysates from substantia nigra. Coexpression of NuIP with Nurr1 results in potentiation of the transcriptional activity of Nurr1 on an nerve growth factor inducible-B response element reporter, as well as reporters driven by the endogenous tyrosine hydroxylase promoter. The mechanism underlying the regulatory action of NuIP on Nurr1 is demonstrated to be through assembly of distinct helical domains of the NLBD. Using a NuIP specific antibody, we show that expression of NuIP protein is mainly colocalized with Nurr1 in adult midbrain dopaminergic neurons. Finally, we demonstrate that suppression of NuIP expression in MN9D cells by NuIP-specific small interfering RNA leads to decreased cell division and decreased expression of a Nurr1 target gene, the dopamine transporter. These results suggest NuIP interacts with and positively regulates the activity of Nurr1 protein and modulates the phenotype of dopaminergic cells. PMID:18784308

  19. Synergistic interactions of lipids and myelin basic protein

    NASA Astrophysics Data System (ADS)

    Hu, Yufang; Doudevski, Ivo; Wood, Denise; Moscarello, Mario; Husted, Cynthia; Genain, Claude; Zasadzinski, Joseph A.; Israelachvili, Jacob

    2004-09-01

    This report describes force measurements and atomic force microscope imaging of lipid-protein interactions that determine the structure of a model membrane system that closely mimics the myelin sheath. Our results suggest that noncovalent, mainly electrostatic and hydrophobic, interactions are responsible for the multilamellar structure and stability of myelin. We find that myelin basic protein acts as a lipid coupler between two apposed bilayers and as a lipid "hole-filler," effectively preventing defect holes from developing. From our protein-mediated-adhesion and force-distance measurements, we develop a simple quantitative model that gives a reasonably accurate picture of the molecular mechanism and adhesion of bilayer-bridging proteins by means of noncovalent interactions. The results and model indicate that optimum myelin adhesion and stability depend on the difference between, rather than the product of, the opposite charges on the lipid bilayers and myelin basic protein, as well as on the repulsive forces associated with membrane fluidity, and that small changes in any of these parameters away from the synergistically optimum values can lead to large changes in the adhesion or even its total elimination. Our results also show that the often-asked question of which membrane species, the lipids or the proteins, are the "important ones" may be misplaced. Both components work synergistically to provide the adhesion and overall structure. A better appreciation of the mechanism of this synergy may allow for a better understanding of stacked and especially myelin membrane structures and may lead to better treatments for demyelinating diseases such as multiple sclerosis. lipid-protein interactions | myelin membrane structure | membrane adhesion | membrane regeneration/healing | demyelinating diseases

  20. Tobacco mosaic virus movement protein interacts with green fluorescent protein-tagged microtubule end-binding protein 1.

    PubMed

    Brandner, Katrin; Sambade, Adrian; Boutant, Emmanuel; Didier, Pascal; Mély, Yves; Ritzenthaler, Christophe; Heinlein, Manfred

    2008-06-01

    The targeting of the movement protein (MP) of Tobacco mosaic virus to plasmodesmata involves the actin/endoplasmic reticulum network and does not require an intact microtubule cytoskeleton. Nevertheless, the ability of MP to facilitate the cell-to-cell spread of infection is tightly correlated with interactions of the protein with microtubules, indicating that the microtubule system is involved in the transport of viral RNA. While the MP acts like a microtubule-associated protein able to stabilize microtubules during late infection stages, the protein was also shown to cause the inactivation of the centrosome upon expression in mammalian cells, thus suggesting that MP may interact with factors involved in microtubule attachment, nucleation, or polymerization. To further investigate the interactions of MP with the microtubule system in planta, we expressed the MP in the presence of green fluorescent protein (GFP)-fused microtubule end-binding protein 1a (EB1a) of Arabidopsis (Arabidopsis thaliana; AtEB1a:GFP). The two proteins colocalize and interact in vivo as well as in vitro and exhibit mutual functional interference. These findings suggest that MP interacts with EB1 and that this interaction may play a role in the associations of MP with the microtubule system during infection.

  1. Understanding Protein-Protein Interactions: Essential Players in (Patho)physiology (Part 2).

    PubMed

    Wilson, Andrew J; Gunning, Patrick T

    2016-04-19

    At the interface: Guest editors Patrick Gunning and Andrew Wilson summarize the collection of ChemMedChem articles that are part of this joint special issue with ChemBioChem focused on protein-protein interactions as targets for therapeutic intervention.

  2. Uncovering viral protein-protein interactions and their role in arenavirus life cycle.

    PubMed

    Loureiro, Maria Eugenia; D'Antuono, Alejandra; Levingston Macleod, Jesica M; López, Nora

    2012-09-01

    The Arenaviridae family includes widely distributed pathogens that cause severe hemorrhagic fever in humans. Replication and packaging of their single-stranded RNA genome involve RNA recognition by viral proteins and a number of key protein-protein interactions. Viral RNA synthesis is directed by the virus-encoded RNA dependent-RNA polymerase (L protein) and requires viral RNA encapsidation by the Nucleoprotein. In addition to the role that the interaction between L and the Nucleoprotein may have in the replication process, polymerase activity appears to be modulated by the association between L and the small multifunctional Z protein. Z is also a structural component of the virions that plays an essential role in viral morphogenesis. Indeed, interaction of the Z protein with the Nucleoprotein is critical for genome packaging. Furthermore, current evidence suggests that binding between Z and the viral envelope glycoprotein complex is required for virion infectivity, and that Z homo-oligomerization is an essential step for particle assembly and budding. Efforts to understand the molecular basis of arenavirus life cycle have revealed important details on these viral protein-protein interactions that will be reviewed in this article. PMID:23170177

  3. Uncovering Viral Protein-Protein Interactions and their Role in Arenavirus Life Cycle

    PubMed Central

    Loureiro, Maria Eugenia; D’Antuono, Alejandra; Levingston Macleod, Jesica M.; López, Nora

    2012-01-01

    The Arenaviridae family includes widely distributed pathogens that cause severe hemorrhagic fever in humans. Replication and packaging of their single-stranded RNA genome involve RNA recognition by viral proteins and a number of key protein-protein interactions. Viral RNA synthesis is directed by the virus-encoded RNA dependent-RNA polymerase (L protein) and requires viral RNA encapsidation by the Nucleoprotein. In addition to the role that the interaction between L and the Nucleoprotein may have in the replication process, polymerase activity appears to be modulated by the association between L and the small multifunctional Z protein. Z is also a structural component of the virions that plays an essential role in viral morphogenesis. Indeed, interaction of the Z protein with the Nucleoprotein is critical for genome packaging. Furthermore, current evidence suggests that binding between Z and the viral envelope glycoprotein complex is required for virion infectivity, and that Z homo-oligomerization is an essential step for particle assembly and budding. Efforts to understand the molecular basis of arenavirus life cycle have revealed important details on these viral protein-protein interactions that will be reviewed in this article. PMID:23170177

  4. Uncovering viral protein-protein interactions and their role in arenavirus life cycle.

    PubMed

    Loureiro, Maria Eugenia; D'Antuono, Alejandra; Levingston Macleod, Jesica M; López, Nora

    2012-09-01

    The Arenaviridae family includes widely distributed pathogens that cause severe hemorrhagic fever in humans. Replication and packaging of their single-stranded RNA genome involve RNA recognition by viral proteins and a number of key protein-protein interactions. Viral RNA synthesis is directed by the virus-encoded RNA dependent-RNA polymerase (L protein) and requires viral RNA encapsidation by the Nucleoprotein. In addition to the role that the interaction between L and the Nucleoprotein may have in the replication process, polymerase activity appears to be modulated by the association between L and the small multifunctional Z protein. Z is also a structural component of the virions that plays an essential role in viral morphogenesis. Indeed, interaction of the Z protein with the Nucleoprotein is critical for genome packaging. Furthermore, current evidence suggests that binding between Z and the viral envelope glycoprotein complex is required for virion infectivity, and that Z homo-oligomerization is an essential step for particle assembly and budding. Efforts to understand the molecular basis of arenavirus life cycle have revealed important details on these viral protein-protein interactions that will be reviewed in this article.

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

    PubMed Central

    Torres, Jaume; Surya, Wahyu; Li, Yan; Liu, Ding Xiang

    2015-01-01

    Viroporins are members of a rapidly growing family of channel-forming small polypeptides found in viruses. The present review will be focused on recent structural and protein-protein interaction information involving two viroporins found in enveloped viruses that target the respiratory tract; (i) the envelope protein in coronaviruses and (ii) the small hydrophobic protein in paramyxoviruses. Deletion of these two viroporins leads to viral attenuation in vivo, whereas data from cell culture shows involvement in the regulation of stress and inflammation. The channel activity and structure of some representative members of these viroporins have been recently characterized in some detail. In addition, searches for protein-protein interactions using yeast-two hybrid techniques have shed light on possible functional roles for their exposed cytoplasmic domains. A deeper analysis of these interactions should not only provide a more complete overview of the multiple functions of these viroporins, but also suggest novel strategies that target protein-protein interactions as much needed antivirals. These should complement current efforts to block viroporin channel activity. PMID:26053927

  6. Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

    PubMed

    Yen, Eric A; Tsay, Aaron; Waldispuhl, Jerome; Vogel, Jackie

    2014-05-01

    Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and visualization of the hidden

  7. Fabrication of Molecular Strain Probes for Illuminating Protein-Protein Interactions.

    PubMed

    Kim, Sung-Bae; Fujii, Rika

    2016-01-01

    A unique bioluminescent imaging probe is introduced for illuminating molecular tension appended by protein-protein interactions (PPIs) of interest. A full-length luciferase is sandwiched between two proteins of interest via minimal flexible linkers. The ligand-activated PPIs append intramolecular tension to the sandwiched luciferase, boosting or dropping the enzymatic activity in a quantitative manner. This method guides construction of a new lineage of bioassays for ligand-activated PPIs. PMID:27424904

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

    PubMed Central

    Peri, Claudio; Morra, Giulia; Colombo, Giorgio

    2016-01-01

    Understanding protein-protein interactions (PPI) at the molecular level is a fundamental task in the design of new drugs, the prediction of protein function and the clarification of the mechanisms of (dis)regulation of biochemical pathways. In this study, we use a novel computational approach to investigate the energetics of aminoacid networks located on the surface of proteins, isolated and in complex with their respective partners. Interestingly, the analysis of individual proteins identifies patches of surface residues that, when mapped on the structure of their respective complexes, reveal regions of residue-pair couplings that extend across the binding interfaces, forming continuous motifs. An enhanced effect is visible across the proteins of the dataset forming larger quaternary assemblies. The method indicates the presence of energetic signatures in the isolated proteins that are retained in the bound form, which we hypothesize to determine binding orientation upon complex formation. We propose our method, BLUEPRINT, as a complement to different approaches ranging from the ab-initio characterization of PPIs, to protein-protein docking algorithms, for the physico-chemical and functional investigation of protein-protein interactions. PMID:27050828

  9. Efficient extraction of protein-protein interactions from full-text articles.

    PubMed

    Hakenberg, Jörg; Leaman, Robert; Vo, Nguyen Ha; Jonnalagadda, Siddhartha; Sullivan, Ryan; Miller, Christopher; Tari, Luis; Baral, Chitta; Gonzalez, Graciela

    2010-01-01

    Proteins and their interactions govern virtually all cellular processes, such as regulation, signaling, metabolism, and structure. Most experimental findings pertaining to such interactions are discussed in research papers, which, in turn, get curated by protein interaction databases. Authors, editors, and publishers benefit from efforts to alleviate the tasks of searching for relevant papers, evidence for physical interactions, and proper identifiers for each protein involved. The BioCreative II.5 community challenge addressed these tasks in a competition-style assessment to evaluate and compare different methodologies, to make aware of the increasing accuracy of automated methods, and to guide future implementations. In this paper, we present our approaches for protein-named entity recognition, including normalization, and for extraction of protein-protein interactions from full text. Our overall goal is to identify efficient individual components, and we compare various compositions to handle a single full-text article in between 10 seconds and 2 minutes. We propose strategies to transfer document-level annotations to the sentence-level, which allows for the creation of a more fine-grained training corpus; we use this corpus to automatically derive around 5,000 patterns. We rank sentences by relevance to the task of finding novel interactions with physical evidence, using a sentence classifier built from this training corpus. Heuristics for paraphrasing sentences help to further remove unnecessary information that might interfere with patterns, such as additional adjectives, clauses, or bracketed expressions. In BioCreative II.5, we achieved an f-score of 22 percent for finding protein interactions, and 43 percent for mapping proteins to UniProt IDs; disregarding species, f-scores are 30 percent and 55 percent, respectively. On average, our best-performing setup required around 2 minutes per full text. All data and pattern sets as well as Java classes that

  10. Balanced Protein–Water Interactions Improve Properties of Disordered Proteins and Non-Specific Protein Association

    PubMed Central

    2015-01-01

    Some frequently encountered deficiencies in all-atom molecular simulations, such as nonspecific protein–protein interactions being too strong, and unfolded or disordered states being too collapsed, suggest that proteins are insufficiently well solvated in simulations using current state-of-the-art force fields. To address these issues, we make the simplest possible change, by modifying the short-range protein–water pair interactions, and leaving all the water–water and protein–protein parameters unchanged. We find that a modest strengthening of protein–water interactions is sufficient to recover the correct dimensions of intrinsically disordered or unfolded proteins, as determined by direct comparison with small-angle X-ray scattering (SAXS) and Förster resonance energy transfer (FRET) data. The modification also results in more realistic protein-protein affinities, and average solvation free energies of model compounds which are more consistent with experiment. Most importantly, we show that this scaling is small enough not to affect adversely the stability of the folded state, with only a modest effect on the stability of model peptides forming α-helix and β-sheet structures. The proposed adjustment opens the way to more accurate atomistic simulations of proteins, particularly for intrinsically disordered proteins, protein–protein association, and crowded cellular environments. PMID:25400522

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

    PubMed

    Cao, Huaiqing; Huang, Yongqi; Liu, Zhirong

    2016-07-01

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

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

    PubMed

    Cao, Huaiqing; Huang, Yongqi; Liu, Zhirong

    2016-07-01

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

  13. Connecting Protein Structure to Intermolecular Interactions: A Computer Modeling Laboratory

    ERIC Educational Resources Information Center

    Abualia, Mohammed; Schroeder, Lianne; Garcia, Megan; Daubenmire, Patrick L.; Wink, Donald J.; Clark, Ginevra A.

    2016-01-01

    An understanding of protein folding relies on a solid foundation of a number of critical chemical concepts, such as molecular structure, intra-/intermolecular interactions, and relating structure to function. Recent reports show that students struggle on all levels to achieve these understandings and use them in meaningful ways. Further, several…

  14. Pharmacological interference with protein-protein interactions mediated by coiled-coil motifs.

    PubMed

    Strauss, H M; Keller, S

    2008-01-01

    Coiled coils are bundles of intertwined alpha-helices that provide protein-protein interaction sites for the dynamic assembly and disassembly of protein complexes. The coiled-coil motif combines structural versatility and adaptability with mechanical strength and specificity. Multimeric proteins that rely on coiled-coil interactions are structurally and functionally very diverse, ranging from simple homodimeric transcription factors to elaborate heteromultimeric scaffolding clusters. Several coiled-coil-bearing proteins are of outstanding pharmacological importance, most notably SNARE proteins involved in vesicular trafficking of neurotransmitters and viral fusion proteins. Together with their crucial roles in many physiological and pathological processes, the structural simplicity and reversible nature of coiled-coil associations render them a promising target for pharmacological interference, as successfully exemplified by botulinum toxins and viral fusion inhibitors. The alpha-helical coiled coil is a ubiquitous protein domain that mediates highly specific homo- and heteromeric protein-protein interactions among a wide range of proteins. The coiled-coil motif was first proposed by Crick on the basis of X-ray diffraction data on alpha-keratin more than 50 years ago (Crick 1952, 1953) and nowadays belongs to the best-characterized protein interaction modules. By definition, a coiled coil is an oligomeric protein assembly consisting of several right-handed amphipathic alpha-helices that wind around each other into a superhelix (or a supercoil) in which the hydrophobic surfaces of the constituent helices are in continuous contact, forming a hydrophobic core. Both homomeric and heteromeric coiled coils with different stoichiometries are possible, and the helices can be aligned in either a parallel or an antiparallel topology (Harbury et al. 1993, 1994). Stoichiometry and topology are governed by the primary structure, that is, the sequence of the polypeptide chains

  15. Interactions of apomorphine with serum and tissue proteins

    SciTech Connect

    Smith, R.V.; Velagapudi, R.B.; McLean, A.M.; Wilcox, R.E.

    1985-05-01

    Physical and covalent interactions of apomorphine with serum and tissue proteins could influence the drug's disposition and pharmacological activities in mammals. Ultrafiltration, equilibrium dialysis, and ultraviolet spectrophotometric methods have been used to study the reversible binding of apomorphine to bovine, human, rat, and swine plasma proteins. The degree of binding was generally greater than 90%, but variations were noted in some instances on the basis of drug concentrations and pH over the range of 6.8-7.8. Incubation of (8,9-/sup 3/H2)apomorphine with bovine serum albumin led to retention of radioactivity and a stoichiometrically controlled released of tritium which arose from the reaction of an electrophilic drug oxidation product and protein, producing drug-protein conjugates. In vitro experiments with mouse striatal brain preparations indicated parallel covalent binding reactions. In vivo experiments in mice indicated accumulation of radioactivity in brain regions and other tissues following daily injections of (8,9-/sup 3/H2)apomorphine for 14 days. The physical and covalent interactions of apomorphine with mammalian tissue proteins could be the cause of longer disposition half-lives in mammals than those previously reported. The covalent interactions, in particular, may be important in elucidating the mechanism of apomorphine-induced behavioral effects in mice.

  16. Pooled-matrix protein interaction screens using Barcode Fusion Genetics.

    PubMed

    Yachie, Nozomu; Petsalaki, Evangelia; Mellor, Joseph C; Weile, Jochen; Jacob, Yves; Verby, Marta; Ozturk, Sedide B; Li, Siyang; Cote, Atina G; Mosca, Roberto; Knapp, Jennifer J; Ko, Minjeong; Yu, Analyn; Gebbia, Marinella; Sahni, Nidhi; Yi, Song; Tyagi, Tanya; Sheykhkarimli, Dayag; Roth, Jonathan F; Wong, Cassandra; Musa, Louai; Snider, Jamie; Liu, Yi-Chun; Yu, Haiyuan; Braun, Pascal; Stagljar, Igor; Hao, Tong; Calderwood, Michael A; Pelletier, Laurence; Aloy, Patrick; Hill, David E; Vidal, Marc; Roth, Frederick P

    2016-04-01

    High-throughput binary protein interaction mapping is continuing to extend our understanding of cellular function and disease mechanisms. However, we remain one or two orders of magnitude away from a complete interaction map for humans and other major model organisms. Completion will require screening at substantially larger scales with many complementary assays, requiring further efficiency gains in proteome-scale interaction mapping. Here, we report Barcode Fusion Genetics-Yeast Two-Hybrid (BFG-Y2H), by which a full matrix of protein pairs can be screened in a single multiplexed strain pool. BFG-Y2H uses Cre recombination to fuse DNA barcodes from distinct plasmids, generating chimeric protein-pair barcodes that can be quantified via next-generation sequencing. We applied BFG-Y2H to four different matrices ranging in scale from ~25 K to 2.5 M protein pairs. The results show that BFG-Y2H increases the efficiency of protein matrix screening, with quality that is on par with state-of-the-art Y2H methods. PMID:27107012

  17. Eimeria tenella: 14-3-3 protein interacts with telomerase.

    PubMed

    Zhao, Na; Gong, Pengtao; Cheng, Baiqi; Li, Jianhua; Yang, Zhengtao; Li, He; Yang, Ju; Zhang, Guocai; Zhang, Xichen

    2014-10-01

    Telomerase, consisting of telomerase RNA and telomerase reverse transcriptase (TERT), is responsible for the maintenance of the end of linear chromosomes. TERT, as the catalytic subunit of telomerase, plays a critical role in telomerase activity. Researches indicate TERT-associated proteins participate in the regulation of telomerase assembly, posttranslational modification, localization, and enzymatic function. Here, the telomerase RNA-binding domain of Eimeria tenella TERT (EtTRBD) was cloned into pGBKT7 and performed as the bait. α-Galactosidase assay showed that the bait plasmid did not activate Gal4 reporter gene. Further, we isolated an EtTRBD-associated protein, 14-3-3, by yeast two-hybrid screening using the constructed bait plasmid. To confirm the interaction, EtTRBD and 14-3-3 were expressed by prokaryotic and eukaryotic expression systems. Pull-down assays by purified proteins demonstrated a direct bind between EtTRBD and 14-3-3. Co-immunoprecipitation techniques successfully validated that 14-3-3 interacted with EtTRBD in 293T cells. The protein-protein interaction provides a starting point for more in-depth studies on telomerase and telomere regulation in E. tenella.

  18. The specificity of interactions between proteins and sulfated polysaccharides.

    PubMed

    Mulloy, Barbara

    2005-12-01

    Sulfated polysaccharides are capable of binding with proteins at several levels of specificity. As highly acidic macromolecules, they can bind non-specifically to any basic patch on a protein surface at low ionic strength, and such interactions are not likely to be physiologically significant. On the other hand, several systems have been identified in which very specific substructures of sulfated polysaccharides confer high affinity for particular proteins; the best-known example of this is the pentasaccharide in heparin with high affinity for antithrombin, but other examples may be taken from the study of marine invertebrates: the importance of the fine structure of dermatan sulfate (DS) to its interaction with heparin cofactor II (HCII), and the involvement of sea urchin egg-jelly fucans in species specific fertilization. A third, intermediate, kind of specific interaction is described for the cell-surface glycosaminoglycan heparan sulfate (HS), in which patterns of sulfate substitution can show differential affinities for cytokines, growth factors, and morphogens at cell surfaces and in the intracellular matrix. This complex interplay of proteins and glycans is capable of influencing the diffusion of such proteins through tissue, as well as modulating cellular responses to them. PMID:16341442

  19. The specificity of interactions between proteins and sulfated polysaccharides.

    PubMed

    Mulloy, Barbara

    2005-12-01

    Sulfated polysaccharides are capable of binding with proteins at several levels of specificity. As highly acidic macromolecules, they can bind non-specifically to any basic patch on a protein surface at low ionic strength, and such interactions are not likely to be physiologically significant. On the other hand, several systems have been identified in which very specific substructures of sulfated polysaccharides confer high affinity for particular proteins; the best-known example of this is the pentasaccharide in heparin with high affinity for antithrombin, but other examples may be taken from the study of marine invertebrates: the importance of the fine structure of dermatan sulfate (DS) to its interaction with heparin cofactor II (HCII), and the involvement of sea urchin egg-jelly fucans in species specific fertilization. A third, intermediate, kind of specific interaction is described for the cell-surface glycosaminoglycan heparan sulfate (HS), in which patterns of sulfate substitution can show differential affinities for cytokines, growth factors, and morphogens at cell surfaces and in the intracellular matrix. This complex interplay of proteins and glycans is capable of influencing the diffusion of such proteins through tissue, as well as modulating cellular responses to them.

  20. Drug-drug plasma protein binding interactions of ivacaftor.

    PubMed

    Schneider, Elena K; Huang, Johnny X; Carbone, Vincenzo; Baker, Mark; Azad, Mohammad A K; Cooper, Matthew A; Li, Jian; Velkov, Tony

    2015-06-01

    Ivacaftor is a novel cystic fibrosis (CF) transmembrane conductance regulator (CFTR) potentiator that improves the pulmonary function for patients with CF bearing a G551D CFTR-protein mutation. Because ivacaftor is highly bound (>97%) to plasma proteins, there is the strong possibility that co-administered CF drugs may compete for the same plasma protein binding sites and impact the free drug concentration. This, in turn, could lead to drastic changes in the in vivo efficacy of ivacaftor and therapeutic outcomes. This biochemical study compares the binding affinity of ivacaftor and co-administered CF drugs for human serum albumin (HSA) and α1 -acid glycoprotein (AGP) using surface plasmon resonance and fluorimetric binding assays that measure the displacement of site-selective probes. Because of their ability to strongly compete for the ivacaftor binding sites on HSA and AGP, drug-drug interactions between ivacaftor are to be expected with ducosate, montelukast, ibuprofen, dicloxacillin, omeprazole, and loratadine. The significance of these plasma protein drug-drug interactions is also interpreted in terms of molecular docking simulations. This in vitro study provides valuable insights into the plasma protein drug-drug interactions of ivacaftor with co-administered CF drugs. The data may prove useful in future clinical trials for a staggered treatment that aims to maximize the effective free drug concentration and clinical efficacy of ivacaftor. PMID:25707701

  1. Membrane Interacting Regions of Dengue Virus NS2A Protein

    PubMed Central

    2015-01-01

    The Dengue virus (DENV) NS2A protein, essential for viral replication, is a poorly characterized membrane protein. NS2A displays both protein/protein and membrane/protein interactions, yet neither its functions in the viral cycle nor its active regions are known with certainty. To highlight the different membrane-active regions of NS2A, we characterized the effects of peptides derived from a peptide library encompassing this protein’s full length on different membranes by measuring their membrane leakage induction and modulation of lipid phase behavior. Following this initial screening, one region, peptide dens25, had interesting effects on membranes; therefore, we sought to thoroughly characterize this region’s interaction with membranes. This peptide presents an interfacial/hydrophobic pattern characteristic of a membrane-proximal segment. We show that dens25 strongly interacts with membranes that contain a large proportion of lipid molecules with a formal negative charge, and that this effect has a major electrostatic contribution. Considering its membrane modulating capabilities, this region might be involved in membrane rearrangements and thus be important for the viral cycle. PMID:25119664

  2. Mitochondrial Protein Interaction Mapping Identifies Regulators of Respiratory Chain Function.

    PubMed

    Floyd, Brendan J; Wilkerson, Emily M; Veling, Mike T; Minogue, Catie E; Xia, Chuanwu; Beebe, Emily T; Wrobel, Russell L; Cho, Holly; Kremer, Laura S; Alston, Charlotte L; Gromek, Katarzyna A; Dolan, Brendan K; Ulbrich, Arne; Stefely, Jonathan A; Bohl, Sarah L; Werner, Kelly M; Jochem, Adam; Westphall, Michael S; Rensvold, Jarred W; Taylor, Robert W; Prokisch, Holger; Kim, Jung-Ja P; Coon, Joshua J; Pagliarini, David J

    2016-08-18

    Mitochondria are essential for numerous cellular processes, yet hundreds of their proteins lack robust functional annotation. To reveal functions for these proteins (termed MXPs), we assessed condition-specific protein-protein interactions for 50 select MXPs using affinity enrichment mass spectrometry. Our data connect MXPs to diverse mitochondrial processes, including multiple aspects of respiratory chain function. Building upon these observations, we validated C17orf89 as a complex I (CI) assembly factor. Disruption of C17orf89 markedly reduced CI activity, and its depletion is found in an unresolved case of CI deficiency. We likewise discovered that LYRM5 interacts with and deflavinates the electron-transferring flavoprotein that shuttles electrons to coenzyme Q (CoQ). Finally, we identified a dynamic human CoQ biosynthetic complex involving multiple MXPs whose topology we map using purified components. Collectively, our data lend mechanistic insight into respiratory chain-related activities and prioritize hundreds of additional interactions for further exploration of mitochondrial protein function. PMID:27499296

  3. Anti-citrullinated protein antibodies suppress let-7a expression in monocytes from patients with rheumatoid arthritis and facilitate the inflammatory responses in rheumatoid arthritis.

    PubMed

    Lai, Ning-Sheng; Yu, Hui-Chun; Yu, Chia-Li; Koo, Malcolm; Huang, Hsien-Bin; Lu, Ming-Chi

    2015-12-01

    We hypothesized that anti-citrullinated protein antibodies (ACPAs) could affect the expression of miRNAs in monocytes and contribute to the inflammatory responses in rheumatoid arthritis (RA). The expression profiles of 270 human miRNAs, co-cultured with ACPAs or human immunoglobulin G (IgG), were analyzed using real-time polymerase chain reaction. Ten miRNAs exhibited differential expression in U937 cells after co-cultured with ACPAs compared with human IgG. The expression levels of these miRNAs were investigated in monocytes from 21 ACPA-positive RA patients and 13 controls. Among these miRNAs, the expression levels of let-7a was decreased in monocytes from ACPA-positive RA patients. The expression levels of let-7a showed a negative correlation with positivity of rheumatoid factor in patients sampled. We found that transfection of U937 cells with let-7a mimic suppressed K-Ras protein expression. In the ACPA-mediated signaling pathway, transfection of U937 cells with let-7a mimic suppressed the ACPA-enhanced phosphorylation of c-Jun N-terminal kinase (JNK), extracellular signal-regulated kinase 1/2 (ERK1/2), and the expression and secretion of interleukin (IL)-1β. In conclusion, ACPA-mediated decreased let-7a expression in monocytes from ACPA-positive RA patients. Decreased let-7a expression was associated with the positivity of RF in ACPA-positive RA patients. The decreased expression of let-7a could facilitate the inflammatory pathway via enhanced ACPA-mediated phosphorylation of ERK1/2 and JNK and increased expression of IL-1β through an increase in the expression of Ras proteins.

  4. Screening a cDNA library for protein-protein interactions directly in planta.

    PubMed

    Lee, Lan-Ying; Wu, Fu-Hui; Hsu, Chen-Tran; Shen, Shu-Chen; Yeh, Hsuan-Yu; Liao, De-Chih; Fang, Mei-Jane; Liu, Nien-Tze; Yen, Yu-Chen; Dokládal, Ladislav; Sykorová, Eva; Gelvin, Stanton B; Lin, Choun-Sea

    2012-05-01

    Screening cDNA libraries for genes encoding proteins that interact with a bait protein is usually performed in yeast. However, subcellular compartmentation and protein modification may differ in yeast and plant cells, resulting in misidentification of protein partners. We used bimolecular fluorescence complementation technology to screen a plant cDNA library against a bait protein directly in plants. As proof of concept, we used the N-terminal fragment of yellow fluorescent protein- or nVenus-tagged Agrobacterium tumefaciens VirE2 and VirD2 proteins and the C-terminal extension (CTE) domain of Arabidopsis thaliana telomerase reverse transcriptase as baits to screen an Arabidopsis cDNA library encoding proteins tagged with the C-terminal fragment of yellow fluorescent protein. A library of colonies representing ~2 × 10(5) cDNAs was arrayed in 384-well plates. DNA was isolated from pools of 10 plates, individual plates, and individual rows and columns of the plates. Sequential screening of subsets of cDNAs in Arabidopsis leaf or tobacco (Nicotiana tabacum) Bright Yellow-2 protoplasts identified single cDNA clones encoding proteins that interact with either, or both, of the Agrobacterium bait proteins, or with CTE. T-DNA insertions in the genes represented by some cDNAs revealed five novel Arabidopsis proteins important for Agrobacterium-mediated plant transformation. We also used this cDNA library to confirm VirE2-interacting proteins in orchid (Phalaenopsis amabilis) flowers. Thus, this technology can be applied to several plant species. PMID:22623495

  5. HIV-1 Tat interacts with LIS1 protein

    PubMed Central

    Epie, Nicolas; Ammosova, Tatyana; Sapir, Tamar; Voloshin, Yaroslav; Lane, William S; Turner, Willie; Reiner, Orly; Nekhai, Sergei

    2005-01-01

    Background HIV-1 Tat activates transcription of HIV-1 viral genes by inducing phosphorylation of the C-terminal domain (CTD) of RNA polymerase II (RNAPII). Tat can also disturb cellular metabolism by inhibiting proliferation of antigen-specific T lymphocytes and by inducing cellular apoptosis. Tat-induced apoptosis of T-cells is attributed, in part, to the distortion of microtubules polymerization. LIS1 is a microtubule-associated protein that facilitates microtubule polymerization. Results We identified here LIS1 as a Tat-interacting protein during extensive biochemical fractionation of T-cell extracts. We found several proteins to co-purify with a Tat-associated RNAPII CTD kinase activity including LIS1, CDK7, cyclin H, and MAT1. Tat interacted with LIS1 but not with CDK7, cyclin H or MAT1 in vitro. LIS1 also co-immunoprecipitated with Tat expressed in HeLa cells. Further, LIS1 interacted with Tat in a yeast two-hybrid system. Conclusion Our results indicate that Tat interacts with LIS1 in vitro and in vivo and that this interaction might contribute to the effect of Tat on microtubule formation. PMID:15698475

  6. Beyond hairballs: the use of quantitative mass spectrometry data to understand protein-protein interactions

    PubMed Central

    Gingras, Anne-Claude; Raught, Brian

    2012-01-01

    The past 10 years have witnessed a dramatic proliferation in the availability of protein interaction data. However, for interaction mapping based on affinity purification coupled with mass spectrometry (AP-MS), there is a wealth of information present in the datasets that often goes unrecorded in public repositories, and as such remains largely unexplored. Further, how this type of data is represented and used by bioinformaticians has not been well established. Here, we point out some common mistakes in how AP-MS data are handled, and describe how protein complex organization and interaction dynamics can be inferred using quantitative AP-MS approaches. PMID:22710165

  7. MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data

    PubMed Central

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

    2014-01-01

    The elucidation of protein-protein interaction (PPI) networks is important for understanding cellular structure and function and structure-based drug design. However, the development of an effective method to conduct exhaustive PPI screening represents a computational challenge. We have been investigating a protein docking approach based on shape complementarity and physicochemical properties. We describe here the development of the protein-protein docking software package “MEGADOCK” that samples an extremely large number of protein dockings at high speed. MEGADOCK reduces the calculation time required for docking by using several techniques such as a novel scoring function called the real Pairwise Shape Complementarity (rPSC) score. We showed that MEGADOCK is capable of exhaustive PPI screening by completing docking calculations 7.5 times faster than the conventional docking software, ZDOCK, while maintaining an acceptable level of accuracy. When MEGADOCK was applied to a subset of a general benchmark dataset to predict 120 relevant interacting pairs from 120 x 120 = 14,400 combinations of proteins, an F-measure value of 0.231 was obtained. Further, we showed that MEGADOCK can be applied to a large-scale protein-protein interaction-screening problem with accuracy better than random. When our approach is combined with parallel high-performance computing systems, it is now feasible to search and analyze protein-protein interactions while taking into account three-dimensional structures at the interactome scale. MEGADOCK is freely available at http://www.bi.cs.titech.ac.jp/megadock. PMID:23855673

  8. Glycoarray Technologies: Deciphering Interactions from Proteins to Live Cell Responses

    PubMed Central

    Puvirajesinghe, Tania M.; Turnbull, Jeremy. E.

    2016-01-01

    Microarray technologies inspired the development of carbohydrate arrays. Initially, carbohydrate array technology was hindered by the complex structures of glycans and their structural variability. The first designs of glycoarrays focused on the HTP (high throughput) study of protein–glycan binding events, and subsequently more in-depth kinetic analysis of carbohydrate–protein interactions. However, the applications have rapidly expanded and now achieve successful discrimination of selective interactions between carbohydrates and, not only proteins, but also viruses, bacteria and eukaryotic cells, and most recently even live cell responses to immobilized glycans. Combining array technology with other HTP technologies such as mass spectrometry is expected to allow even more accurate and sensitive analysis. This review provides a broad overview of established glycoarray technologies (with a special focus on glycosaminoglycan applications) and their emerging applications to the study of complex interactions between glycans and whole living cells. PMID:27600069

  9. Glycoarray Technologies: Deciphering Interactions from Proteins to Live Cell Responses

    PubMed Central

    Puvirajesinghe, Tania M.; Turnbull, Jeremy. E.

    2016-01-01

    Microarray technologies inspired the development of carbohydrate arrays. Initially, carbohydrate array technology was hindered by the complex structures of glycans and their structural variability. The first designs of glycoarrays focused on the HTP (high throughput) study of protein–glycan binding events, and subsequently more in-depth kinetic analysis of carbohydrate–protein interactions. However, the applications have rapidly expanded and now achieve successful discrimination of selective interactions between carbohydrates and, not only proteins, but also viruses, bacteria and eukaryotic cells, and most recently even live cell responses to immobilized glycans. Combining array technology with other HTP technologies such as mass spectrometry is expected to allow even more accurate and sensitive analysis. This review provides a broad overview of established glycoarray technologies (with a special focus on glycosaminoglycan applications) and their emerging applications to the study of complex interactions between glycans and whole living cells.

  10. Screening and verification of proteins that interact with HSPC238.

    PubMed

    Tan, Jia-Yu; Chen, Jing-Lin; Huang, Xiang; Yuan, Chun-Lei

    2015-12-01

    HSPC238 is a recently identified tumor suppressor and demonstrates ubiquitin ligase E3 enzyme activity. HSPC238 was found to be significantly downregulated in human hepatocellular carcinoma (HCC) in vivo and to inhibit the proliferation and invasion of hepatoma cells in vitro; however, the underlying molecular mechanism is largely unknown. In the present study, we screened for and identified proteins that physically interact with HSPC238. A bait vector for yeast two-hybrid was constructed with human HSPC238 gene cDNA. Yeast two-hybrid screening was performed using a human fetal liver cDNA library. Multiple reporter gene assays, DNA sequencing and BLAST comparison analysis were performed on positive clones. Protein interaction of screened candidates with HSPC238 was further validated by confocal microscopy, co-immunoprecipitation and pull-down assays. Yeast two-hybrid screening demonstrated 124 positive clones. Multiple reporter gene assays with LacZ, HIS and ADE2 selective media identified 12 genes. Further co-localization, co-immunoprecipitation and pull-down assays demonstrated that HMOX1, RPS27A, ubiquitinB and MT2A interacted with HSPC238. These four proteins are involved in tumor development and progression, and are associated with the ubiquitin-proteasome pathway. Our results suggest that HSPC238 may play a tumor suppressor role and interact with these proteins via the ubiquitin-proteasome pathway. The identification and validation of proteins interacting with HSP238 may lead to the discovery of novel mechanisms through which HSPC238 suppresses tumorigenesis in human hepatocellular carcinoma.

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

    PubMed Central

    De Bodt, Stefanie; Proost, Sebastian; Vandepoele, Klaas; Rouzé, Pierre; Van de Peer, Yves

    2009-01-01

    Background Large-scale identification of the interrelationships between different components of the cell, such as the interactions between proteins, has recently gained great interest. However, unraveling large-scale protein-protein interaction maps is laborious and expensive. Moreover, assessing the reliability of the interactions can be cumbersome. Results In this study, we have developed a computational method that exploits the existing knowledge on protein-protein interactions in diverse species through orthologous relations on the one hand, and functional association data on the other hand to predict and filter protein-protein interactions in Arabidopsis thaliana. A highly reliable set of protein-protein interactions is predicted through this integrative approach making use of existing protein-protein interaction data from yeast, human, C. elegans and D. melanogaster. Localization, biological process, and co-expression data are used as powerful indicators for protein-protein interactions. The functional repertoire of the identified interactome reveals interactions between proteins functioning in well-conserved as well as plant-specific biological processes. We observe that although common mechanisms (e.g. actin polymerization) and components (e.g. ARPs, actin-related proteins) exist between different lineages, they are active in specific processes such as growth, cancer metastasis and trichome development in yeast, human and Arabidopsis, respectively. Conclusion We conclude that the integration of orthology with functional association data is adequate to predict protein-protein interactions. Through this approach, a high number of novel protein-protein interactions with diverse biological roles is discovered. Overall, we have predicted a reliable set of protein-protein interactions suitable for further computational as well as experimental analyses. PMID:19563678

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

    PubMed

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

    2013-03-01

    Essentially all biological processes depend on protein-protein interactions (PPIs). Timing of such interactions is crucial for regulatory function. Although circadian (~24-hour) clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression) suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc.) contributing to temporal organization of cellular physiology in an unprecedented manner. PMID:23555304

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

    PubMed

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

    2012-12-01

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

  14. A general system for studying protein-protein interactions in gram-negative bacteria

    SciTech Connect

    Pelletier, Dale A.; Hurst, G. B.; Foote, Linda J.; Lankford, Patricia K.; McKeown, Cathy K.; Lu, Tse-Yuan S.; Schmoyer, Denise D.; Shah, Manesh B.; Hervey IV, W. J.; McDonald, W. Hayes; Hooker, Brian S.; Cannon, William R.; Daly, Don S.; Gilmore, Jason M.; Wiley, H. S.; Auberry, Deanna L.; Wang, Yisong; Larimer, Frank; Kennel, S. J.; Doktycz, M. J.; Morrell-Falvey, Jennifer; Owens, Elizabeth T.; Buchanan, M. V.

    2008-08-01

    One of the most promising of the emerging methods for large-scale studies of interactions among proteins is co-isolation of an affinity-tagged protein and its interaction partners, followed by mass spectrometric identification of the co-purifying proteins. We describe a methodology for systematically identifying the proteins that interact with affinity-tagged “bait” proteins expressed from a medium copy plasmid, which are based on a broad host range (pBBR1MCS5) vector backbone that has been modified to incorporate the Gateway DEST plasmid multiple cloning region. This construct was designed to facilitate expression of fusion proteins bearing an affinity tag, across a range of Gram negative bacterial hosts. We demonstrate the performance of this methodology by characterizing interactions among subunits of the DNA-dependent RNA polymerase complex in two metabolically versatile Gram negative microbial species of environmental interest, Rhodopseudomonas palustris CGA010 and Shewanella oneidensis MR-1. Results from the RNA polymerase complex from these two species compared favorably with those for both plasmid- and chromosomally-encoded affinity-tagged fusion proteins expressed in a model organism, E. coli.

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

    PubMed Central

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

    2016-01-01

    Posttranslational regulation of protein function is an ubiquitous mechanism in eukaryotic cells. Here, we analyzed biological properties of nodes and edges of a human protein-protein interaction phosphorylation-based network, especially of those nodes critical for the network controllability. We found that the minimal number of critical nodes needed to control the whole network is 29%, which is considerably lower compared to other real networks. These critical nodes are more regulated by posttranslational modifications and contain more binding domains to these modifications than other kinds of nodes in the network, suggesting an intra-group fast regulation. Also, when we analyzed the edges characteristics that connect critical and non-critical nodes, we found that the former are enriched in domain-to-eukaryotic linear motif interactions, whereas the later are enriched in domain-domain interactions. Our findings suggest a possible structure for protein-protein interaction networks with a densely interconnected and self-regulated central core, composed of critical nodes with a high participation in the controllability of the full network, and less regulated peripheral nodes. Our study offers a deeper understanding of complex network control and bridges the controllability theorems for complex networks and biological protein-protein interaction phosphorylation-based networked systems. PMID:27195976

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

    PubMed

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

    2016-05-19

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

  17. Moonlighting Proteins and Protein–Protein Interactions as Neurotherapeutic Targets in the G Protein-Coupled Receptor Field

    PubMed Central

    Fuxe, Kjell; Borroto-Escuela, Dasiel O; Romero-Fernandez, Wilber; Palkovits, Miklós; Tarakanov, Alexander O; Ciruela, Francisco; Agnati, Luigi F

    2014-01-01

    There is serious interest in understanding the dynamics of the receptor–receptor and receptor–protein interactions in space and time and their integration in GPCR heteroreceptor complexes of the CNS. Moonlighting proteins are special multifunctional proteins because they perform multiple autonomous, often unrelated, functions without partitioning into different protein domains. Moonlighting through receptor oligomerization can be operationally defined as an allosteric receptor–receptor interaction, which leads to novel functions of at least one receptor protomer. GPCR-mediated signaling is a more complicated process than previously described as every GPCR and GPCR heteroreceptor complex requires a set of G protein interacting proteins, which interacts with the receptor in an orchestrated spatio-temporal fashion. GPCR heteroreceptor complexes with allosteric receptor–receptor interactions operating through the receptor interface have become major integrative centers at the molecular level and their receptor protomers act as moonlighting proteins. The GPCR heteroreceptor complexes in the CNS have become exciting new targets for neurotherapeutics in Parkinson's disease, schizophrenia, drug addiction, and anxiety and depression opening a new field in neuropsychopharmacology. PMID:24105074

  18. Strong Ligand-Protein Interactions Derived from Diffuse Ligand Interactions with Loose Binding Sites.

    PubMed

    Marsh, Lorraine

    2015-01-01

    Many systems in biology rely on binding of ligands to target proteins in a single high-affinity conformation with a favorable ΔG. Alternatively, interactions of ligands with protein regions that allow diffuse binding, distributed over multiple sites and conformations, can exhibit favorable ΔG because of their higher entropy. Diffuse binding may be biologically important for multidrug transporters and carrier proteins. A fine-grained computational method for numerical integration of total binding ΔG arising from diffuse regional interaction of a ligand in multiple conformations using a Markov Chain Monte Carlo (MCMC) approach is presented. This method yields a metric that quantifies the influence on overall ligand affinity of ligand binding to multiple, distinct sites within a protein binding region. This metric is essentially a measure of dispersion in equilibrium ligand binding and depends on both the number of potential sites of interaction and the distribution of their individual predicted affinities. Analysis of test cases indicates that, for some ligand/protein pairs involving transporters and carrier proteins, diffuse binding contributes greatly to total affinity, whereas in other cases the influence is modest. This approach may be useful for studying situations where "nonspecific" interactions contribute to biological function. PMID:26064949

  19. Strong Ligand-Protein Interactions Derived from Diffuse Ligand Interactions with Loose Binding Sites

    PubMed Central

    2015-01-01

    Many systems in biology rely on binding of ligands to target proteins in a single high-affinity conformation with a favorable ΔG. Alternatively, interactions of ligands with protein regions that allow diffuse binding, distributed over multiple sites and conformations, can exhibit favorable ΔG because of their higher entropy. Diffuse binding may be biologically important for multidrug transporters and carrier proteins. A fine-grained computational method for numerical integration of total binding ΔG arising from diffuse regional interaction of a ligand in multiple conformations using a Markov Chain Monte Carlo (MCMC) approach is presented. This method yields a metric that quantifies the influence on overall ligand affinity of ligand binding to multiple, distinct sites within a protein binding region. This metric is essentially a measure of dispersion in equilibrium ligand binding and depends on both the number of potential sites of interaction and the distribution of their individual predicted affinities. Analysis of test cases indicates that, for some ligand/protein pairs involving transporters and carrier proteins, diffuse binding contributes greatly to total affinity, whereas in other cases the influence is modest. This approach may be useful for studying situations where “nonspecific” interactions contribute to biological function. PMID:26064949

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

    PubMed

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

    2016-01-01

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

  1. Interactions of signaling proteins, growth factors and other proteins with heparan sulfate: mechanisms and mysteries.

    PubMed

    Billings, Paul C; Pacifici, Maurizio

    2015-01-01

    Heparan sulfate (HS) is a component of cell surface and matrix-associated proteoglycans (HSPGs) that, collectively, play crucial roles in many physiologic processes including cell differentiation, organ morphogenesis and cancer. A key function of HS is to bind and interact with signaling proteins, growth factors, plasma proteins, immune-modulators and other factors. In doing so, the HS chains and HSPGs are able to regulate protein distribution, bio-availability and action on target cells and can also serve as cell surface co-receptors, facilitating ligand-receptor interactions. These proteins contain an HS/heparin-binding domain (HBD) that mediates their association and contacts with HS. HBDs are highly diverse in sequence and predicted structure, contain clusters of basic amino acids (Lys and Arg) and possess an overall net positive charge, most often within a consensus Cardin-Weintraub (CW) motif. Interestingly, other domains and residues are now known to influence protein-HS interactions, as well as interactions with other glycosaminoglycans, such as chondroitin sulfate. In this review, we provide a description and analysis of HBDs in proteins including amphiregulin, fibroblast growth factor family members, heparanase, sclerostin and hedgehog protein family members. We discuss HBD structural and functional features and important roles carried out by other protein domains, and also provide novel conformational insights into the diversity of CW motifs present in Sonic, Indian and Desert hedgehogs. Finally, we review progress in understanding the pathogenesis of a rare pediatric skeletal disorder, Hereditary Multiple Exostoses (HME), characterized by HS deficiency and cartilage tumor formation. Advances in understanding protein-HS interactions will have broad implications for basic biology and translational medicine as well as for the development of HS-based therapeutics.

  2. Detecting Protein Complexes in Protein Interaction Networks Modeled as Gene Expression Biclusters

    PubMed Central

    Hanna, Eileen Marie; Zaki, Nazar; Amin, Amr

    2015-01-01

    Developing suitable methods for the detection of protein complexes in protein interaction networks continues to be an intriguing area of research. The importance of this objective originates from the fact that protein complexes are key players in most cellular processes. The more complexes we identify, the better we can understand normal as well as abnormal molecular events. Up till now, various computational methods were designed for this purpose. However, despite their notable performance, questions arise regarding potential ways to improve them, in addition to ameliorative guidelines to introduce novel approaches. A close interpretation leads to the assent that the way in which protein interaction networks are initially viewed should be adjusted. These networks are dynamic in reality and it is necessary to consider this fact to enhance the detection of protein complexes. In this paper, we present “DyCluster”, a framework to model the dynamic aspect of protein interaction networks by incorporating gene expression data, through biclustering techniques, prior to applying complex-detection algorithms. The experimental results show that DyCluster leads to higher numbers of correctly-detected