Sample records for factor interacting protein

  1. Protein-protein interactions in the regulation of WRKY transcription factors.

    PubMed

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

    2013-03-01

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

  2. Dissecting protein:protein interactions between transcription factors with an RNA aptamer.

    PubMed Central

    Tian, Y; Adya, N; Wagner, S; Giam, C Z; Green, M R; Ellington, A D

    1995-01-01

    Nucleic acid aptamers isolated from random sequence pools have generally proven useful at inhibiting the interactions of nucleic acid binding proteins with their cognate nucleic acids. In order to develop reagents that could also be used to study protein:protein interactions, we have used in vitro selection to search for RNA aptamers that could interact with the transactivating protein Tax from human T-cell leukemia virus. Tax does not normally bind to nucleic acids, but instead stimulates transcription by interacting with a variety of cellular transcription factors, including the cyclic AMP-response element binding protein (CREB), NF-kappa B, and the serum response factor (SRF). Starting from a pool of greater than 10(13) different RNAs with a core of 120 random sequence positions, RNAs were selected for their ability to be co-retained on nitrocellulose filters with Tax. After five cycles of selection and amplification, a single nucleic acid species remained. This aptamer was found to bind Tax with high affinity and specificity, and could disrupt complex formation between Tax and NF-kappa B, but not with SRF. The differential effects of our aptamer probe on protein:protein interactions suggest a model for how the transcription factor binding sites on the surface of the Tax protein are organized. This model is consistent with data from a variety of other studies. PMID:7489503

  3. 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.

  4. Using host-pathogen protein interactions to identify and characterize Francisella tularensis virulence factors.

    PubMed

    Wallqvist, Anders; Memišević, Vesna; Zavaljevski, Nela; Pieper, Rembert; Rajagopala, Seesandra V; Kwon, Keehwan; Yu, Chenggang; Hoover, Timothy A; Reifman, Jaques

    2015-12-29

    Francisella tularensis is a select bio-threat agent and one of the most virulent intracellular pathogens known, requiring just a few organisms to establish an infection. Although several virulence factors are known, we lack an understanding of virulence factors that act through host-pathogen protein interactions to promote infection. To address these issues in the highly infectious F. tularensis subsp. tularensis Schu S4 strain, we deployed a combined in silico, in vitro, and in vivo analysis to identify virulence factors and their interactions with host proteins to characterize bacterial infection mechanisms. We initially used comparative genomics and literature to identify and select a set of 49 putative and known virulence factors for analysis. Each protein was then subjected to proteome-scale yeast two-hybrid (Y2H) screens with human and murine cDNA libraries to identify potential host-pathogen protein-protein interactions. Based on the bacterial protein interaction profile with both hosts, we selected seven novel putative virulence factors for mutant construction and animal validation experiments. We were able to create five transposon insertion mutants and used them in an intranasal BALB/c mouse challenge model to establish 50 % lethal dose estimates. Three of these, ΔFTT0482c, ΔFTT1538c, and ΔFTT1597, showed attenuation in lethality and can thus be considered novel F. tularensis virulence factors. The analysis of the accompanying Y2H data identified intracellular protein trafficking between the early endosome to the late endosome as an important component in virulence attenuation for these virulence factors. Furthermore, we also used the Y2H data to investigate host protein binding of two known virulence factors, showing that direct protein binding was a component in the modulation of the inflammatory response via activation of mitogen-activated protein kinases and in the oxidative stress response. Direct interactions with specific host proteins and the

  5. Structural and functional analysis of VQ motif-containing proteins in Arabidopsis as interacting proteins of WRKY transcription factors.

    PubMed

    Cheng, Yuan; Zhou, Yuan; Yang, Yan; Chi, Ying-Jun; Zhou, Jie; Chen, Jian-Ye; Wang, Fei; Fan, Baofang; Shi, Kai; Zhou, Yan-Hong; Yu, Jing-Quan; Chen, Zhixiang

    2012-06-01

    WRKY transcription factors are encoded by a large gene superfamily with a broad range of roles in plants. Recently, several groups have reported that proteins containing a short VQ (FxxxVQxLTG) motif interact with WRKY proteins. We have recently discovered that two VQ proteins from Arabidopsis (Arabidopsis thaliana), SIGMA FACTOR-INTERACTING PROTEIN1 and SIGMA FACTOR-INTERACTING PROTEIN2, act as coactivators of WRKY33 in plant defense by specifically recognizing the C-terminal WRKY domain and stimulating the DNA-binding activity of WRKY33. In this study, we have analyzed the entire family of 34 structurally divergent VQ proteins from Arabidopsis. Yeast (Saccharomyces cerevisiae) two-hybrid assays showed that Arabidopsis VQ proteins interacted specifically with the C-terminal WRKY domains of group I and the sole WRKY domains of group IIc WRKY proteins. Using site-directed mutagenesis, we identified structural features of these two closely related groups of WRKY domains that are critical for interaction with VQ proteins. Quantitative reverse transcription polymerase chain reaction revealed that expression of a majority of Arabidopsis VQ genes was responsive to pathogen infection and salicylic acid treatment. Functional analysis using both knockout mutants and overexpression lines revealed strong phenotypes in growth, development, and susceptibility to pathogen infection. Altered phenotypes were substantially enhanced through cooverexpression of genes encoding interacting VQ and WRKY proteins. These findings indicate that VQ proteins play an important role in plant growth, development, and response to environmental conditions, most likely by acting as cofactors of group I and IIc WRKY transcription factors.

  6. The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

    PubMed Central

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

    2009-01-01

    We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

  7. Analysis of In Vivo Chromatin and Protein Interactions of Arabidopsis Transcript Elongation Factors.

    PubMed

    Pfab, Alexander; Antosz, Wojciech; Holzinger, Philipp; Bruckmann, Astrid; Griesenbeck, Joachim; Grasser, Klaus D

    2017-01-01

    A central step to elucidate the function of proteins commonly comprises the analysis of their molecular interactions in vivo. For nuclear regulatory proteins this involves determining protein-protein interactions as well as mapping of chromatin binding sites. Here, we present two protocols to identify protein-protein and chromatin interactions of transcript elongation factors (TEFs) in Arabidopsis. The first protocol (Subheading 3.1) describes protein affinity-purification coupled to mass spectrometry (AP-MS) that utilizes suspension cultured cells as experimental system. This approach provides an unbiased view of proteins interacting with epitope-tagged TEFs. The second protocol (Subheading 3.2) depicts details about a chromatin immunoprecipitation (ChIP) procedure to characterize genomic binding sites of TEFs. These methods should be valuable tools for the analysis of a broad variety of nuclear proteins.

  8. Molecular interactions between chondroitin-dermatan sulfate and growth factors/receptors/matrix proteins.

    PubMed

    Mizumoto, Shuji; Yamada, Shuhei; Sugahara, Kazuyuki

    2015-10-01

    Recent functional studies on chondroitin sulfate-dermatan sulfate (CS-DS) demonstrated its indispensable roles in various biological events including brain development and cancer. CS-DS proteoglycans exert their physiological activity through interactions with specific proteins including growth factors, cell surface receptors, and matrix proteins. The characterization of these interactions is essential for regulating the biological functions of CS-DS proteoglycans. Although amino acid sequences on the bioactive proteins required for these interactions have already been elucidated, the specific saccharide sequences involved in the binding of CS-DS to target proteins have not yet been sufficiently identified. In this review, recent findings are described on the interaction between CS-DS and some proteins which are especially involved in the central nervous system and cancer development/metastasis. Copyright © 2015. Published by Elsevier Ltd.

  9. Structural and Functional Analysis of VQ Motif-Containing Proteins in Arabidopsis as Interacting Proteins of WRKY Transcription Factors1[W][OA

    PubMed Central

    Cheng, Yuan; Zhou, Yuan; Yang, Yan; Chi, Ying-Jun; Zhou, Jie; Chen, Jian-Ye; Wang, Fei; Fan, Baofang; Shi, Kai; Zhou, Yan-Hong; Yu, Jing-Quan; Chen, Zhixiang

    2012-01-01

    WRKY transcription factors are encoded by a large gene superfamily with a broad range of roles in plants. Recently, several groups have reported that proteins containing a short VQ (FxxxVQxLTG) motif interact with WRKY proteins. We have recently discovered that two VQ proteins from Arabidopsis (Arabidopsis thaliana), SIGMA FACTOR-INTERACTING PROTEIN1 and SIGMA FACTOR-INTERACTING PROTEIN2, act as coactivators of WRKY33 in plant defense by specifically recognizing the C-terminal WRKY domain and stimulating the DNA-binding activity of WRKY33. In this study, we have analyzed the entire family of 34 structurally divergent VQ proteins from Arabidopsis. Yeast (Saccharomyces cerevisiae) two-hybrid assays showed that Arabidopsis VQ proteins interacted specifically with the C-terminal WRKY domains of group I and the sole WRKY domains of group IIc WRKY proteins. Using site-directed mutagenesis, we identified structural features of these two closely related groups of WRKY domains that are critical for interaction with VQ proteins. Quantitative reverse transcription polymerase chain reaction revealed that expression of a majority of Arabidopsis VQ genes was responsive to pathogen infection and salicylic acid treatment. Functional analysis using both knockout mutants and overexpression lines revealed strong phenotypes in growth, development, and susceptibility to pathogen infection. Altered phenotypes were substantially enhanced through cooverexpression of genes encoding interacting VQ and WRKY proteins. These findings indicate that VQ proteins play an important role in plant growth, development, and response to environmental conditions, most likely by acting as cofactors of group I and IIc WRKY transcription factors. PMID:22535423

  10. Cross-regulatory protein-protein interactions between Hox and Pax transcription factors.

    PubMed

    Plaza, Serge; Prince, Frederic; Adachi, Yoshitsugu; Punzo, Claudio; Cribbs, David L; Gehring, Walter J

    2008-09-09

    Homeotic Hox selector genes encode highly conserved transcriptional regulators involved in the differentiation of multicellular organisms. Ectopic expression of the Antennapedia (ANTP) homeodomain protein in Drosophila imaginal discs induces distinct phenotypes, including an antenna-to-leg transformation and eye reduction. We have proposed that the eye loss phenotype is a consequence of a negative posttranslational control mechanism because of direct protein-protein interactions between ANTP and Eyeless (EY). In the present work, we analyzed the effect of various ANTP homeodomain mutations for their interaction with EY and for head development. Contrasting with the eye loss phenotype, we provide evidence that the antenna-to-leg transformation involves ANTP DNA-binding activity. In a complementary genetic screen performed in yeast, we isolated mutations located in the N terminus of the ANTP homeodomain that inhibit direct interactions with EY without abolishing DNA binding in vitro and in vivo. In a bimolecular fluorescence complementation assay, we detected the ANTP-EY interaction in vivo, these interactions occurring through the paired domain and/or the homeodomain of EY. These results demonstrate that the homeodomain supports multiple molecular regulatory functions in addition to protein-DNA and protein-RNA interactions; it is also involved in protein-protein interactions.

  11. Novel Burkholderia mallei Virulence Factors Linked to Specific Host-Pathogen Protein Interactions*

    PubMed Central

    Memišević, Vesna; Zavaljevski, Nela; Pieper, Rembert; Rajagopala, Seesandra V.; Kwon, Keehwan; Townsend, Katherine; Yu, Chenggang; Yu, Xueping; DeShazer, David; Reifman, Jaques; Wallqvist, Anders

    2013-01-01

    Burkholderia mallei is an infectious intracellular pathogen whose virulence and resistance to antibiotics makes it a potential bioterrorism agent. Given its genetic origin as a commensal soil organism, it is equipped with an extensive and varied set of adapted mechanisms to cope with and modulate host-cell environments. One essential virulence mechanism constitutes the specialized secretion systems that are designed to penetrate host-cell membranes and insert pathogen proteins directly into the host cell's cytosol. However, the secretion systems' proteins and, in particular, their host targets are largely uncharacterized. Here, we used a combined in silico, in vitro, and in vivo approach to identify B. mallei proteins required for pathogenicity. We used bioinformatics tools, including orthology detection and ab initio predictions of secretion system proteins, as well as published experimental Burkholderia data to initially select a small number of proteins as putative virulence factors. We then used yeast two-hybrid assays against normalized whole human and whole murine proteome libraries to detect and identify interactions among each of these bacterial proteins and host proteins. Analysis of such interactions provided both verification of known virulence factors and identification of three new putative virulence proteins. We successfully created insertion mutants for each of these three proteins using the virulent B. mallei ATCC 23344 strain. We exposed BALB/c mice to mutant strains and the wild-type strain in an aerosol challenge model using lethal B. mallei doses. In each set of experiments, mice exposed to mutant strains survived for the 21-day duration of the experiment, whereas mice exposed to the wild-type strain rapidly died. Given their in vivo role in pathogenicity, and based on the yeast two-hybrid interaction data, these results point to the importance of these pathogen proteins in modulating host ubiquitination pathways, phagosomal escape, and actin

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

    PubMed

    Park, Byungkyu; Han, Kyungsook

    2010-01-18

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

  13. Structural Insights into Helicobacter pylori Cag Protein Interactions with Host Cell Factors.

    PubMed

    Bergé, Célia; Terradot, Laurent

    2017-01-01

    The most virulent strains of Helicobacter pylori carry a genomic island (cagPAI) containing a set of 27-31 genes. The encoded proteins assemble a syringe-like apparatus to inject the cytotoxin-associated gene A (CagA) protein into gastric cells. This molecular device belongs to the type IV secretion system (T4SS) family albeit with unique characteristics. The cagPAI-encoded T4SS and its effector protein CagA have an intricate relationship with the host cell, with multiple interactions that only start to be deciphered from a structural point of view. On the one hand, the major roles of the interactions between CagL and CagA (and perhaps CagI and CagY) and host cell factors are to facilitate H. pylori adhesion and to mediate the injection of the CagA oncoprotein. On the other hand, CagA interactions with host cell partners interfere with cellular pathways to subvert cell defences and to promote H. pylori infection. Although a clear mechanism for CagA translocation is still lacking, the structural definition of CagA and CagL domains involved in interactions with signalling proteins are progressively coming to light. In this chapter, we will focus on the structural aspects of Cag protein interactions with host cell molecules, critical molecular events precluding H. pylori-mediated gastric cancer development.

  14. 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

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

    PubMed

    Campbell, Melody G; Karbstein, Katrin

    2011-01-20

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

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

    PubMed

    Raut, Ashlesha S; Kalonia, Devendra S

    2015-09-08

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

  17. Protein-Protein Interactions within Late Pre-40S Ribosomes

    PubMed Central

    Campbell, Melody G.; Karbstein, Katrin

    2011-01-01

    Ribosome assembly in eukaryotic organisms requires more than 200 assembly factors to facilitate and coordinate rRNA transcription, processing, and folding with the binding of the ribosomal proteins. Many of these assembly factors bind and dissociate at defined times giving rise to discrete assembly intermediates, some of which have been partially characterized with regards to their protein and RNA composition. Here, we have analyzed the protein-protein interactions between the seven assembly factors bound to late cytoplasmic pre-40S ribosomes using recombinant proteins in binding assays. Our data show that these factors form two modules: one comprising Enp1 and the export adaptor Ltv1 near the beak structure, and the second comprising the kinase Rio2, the nuclease Nob1, and a regulatory RNA binding protein Dim2/Pno1 on the front of the head. The GTPase-like Tsr1 and the universally conserved methylase Dim1 are also peripherally connected to this second module. Additionally, in an effort to further define the locations for these essential proteins, we have analyzed the interactions between these assembly factors and six ribosomal proteins: Rps0, Rps3, Rps5, Rps14, Rps15 and Rps29. Together, these results and previous RNA-protein crosslinking data allow us to propose a model for the binding sites of these seven assembly factors. Furthermore, our data show that the essential kinase Rio2 is located at the center of the pre-ribosomal particle and interacts, directly or indirectly, with every other assembly factor, as well as three ribosomal proteins required for cytoplasmic 40S maturation. These data suggest that Rio2 could play a central role in regulating cytoplasmic maturation steps. PMID:21283762

  18. Expression and Protein Interaction Analyses Reveal Combinatorial Interactions of LBD Transcription Factors During Arabidopsis Pollen Development.

    PubMed

    Kim, Mirim; Kim, Min-Jung; Pandey, Shashank; Kim, Jungmook

    2016-11-01

    LATERAL ORGAN BOUNDARIES DOMAIN (LBD) transcription factor gene family members play key roles in diverse aspects of plant development. LBD10 and LBD27 have been shown to be essential for pollen development in Arabidopsis thaliana. From the previous RNA sequencing (RNA-Seq) data set of Arabidopsis pollen, we identified the mRNAs of LBD22, LBD25 and LBD36 in addition to LBD10 and LBD27 in Arabidopsis pollen. Here we conducted expression and cellular analysis using GFP:GUS (green fluorescent protein:β-glucuronidase) reporter gene and subcellular localization assays using LBD:GFP fusion proteins expressed under the control of their own promoters in Arabidopsis. We found that these LBD proteins display spatially and temporally distinct and overlapping expression patterns during pollen development. Bimolecular fluorescence complementation and GST (glutathione S-transferase) pull-down assays demonstrated that protein-protein interactions occur among the LBDs exhibiting overlapping expression during pollen development. We further showed that LBD10, LBD22, LBD25, LBD27 and LBD36 interact with each other to form heterodimers, which are localized to the nucleus in Arabidopsis protoplasts. Taken together, these results suggest that combinatorial interactions among LBD proteins may be important for their function in pollen development in Arabidopsis. © The Author 2016. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Nery, Flavia C.; Departamento de Genetica e Evolucao, Universidade Estadual de Campinas, Campinas, SP; Rui, Edmilson

    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 bemore » 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.« less

  20. Selection of peptides interfering with protein-protein interaction.

    PubMed

    Gaida, Annette; Hagemann, Urs B; Mattay, Dinah; Räuber, Christina; Müller, Kristian M; Arndt, Katja M

    2009-01-01

    Cell physiology depends on a fine-tuned network of protein-protein interactions, and misguided interactions are often associated with various diseases. Consequently, peptides, which are able to specifically interfere with such adventitious interactions, are of high interest for analytical as well as medical purposes. One of the most abundant protein interaction domains is the coiled-coil motif, and thus provides a premier target. Coiled coils, which consist of two or more alpha-helices wrapped around each other, have one of the simplest interaction interfaces, yet they are able to confer highly specific homo- and heterotypic interactions involved in virtually any cellular process. While there are several ways to generate interfering peptides, the combination of library design with a powerful selection system seems to be one of the most effective and promising approaches. This chapter guides through all steps of such a process, starting with library options and cloning, detailing suitable selection techniques and ending with purification for further down-stream characterization. Such generated peptides will function as versatile tools to interfere with the natural function of their targets thereby illuminating their down-stream signaling and, in general, promoting understanding of factors leading to specificity and stability in protein-protein interactions. Furthermore, peptides interfering with medically relevant proteins might become important diagnostics and therapeutics.

  1. Interaction of AIM with insulin-like growth factor-binding protein-4

    PubMed Central

    YOU, QIANG; WU, YAN; YAO, NANNAN; SHEN, GUANNAN; ZHANG, YING; XU, LIANGGUO; LI, GUIYING; JU, CYNTHIA

    2015-01-01

    Apoptosis inhibitor of macrophages (AIM/cluster of differentiation 5 antigen-like/soluble protein α) has been shown to inhibit cellular apoptosis; however, the underlying molecular mechanism has not been elucidated. Using yeast two-hybrid screening, the present study uncovered that AIM binds to insulin-like growth factor binding protein-4 (IGFBP-4). AIM interaction with IGFBP-4, as well as IGFBP-2 and -3, but not with IGFBP-1, -5 and -6, was further confirmed by co-immunoprecipitation (co-IP) using 293 cells. The binding activity and affinity between AIM and IGFBP-4 in vitro were analyzed by co-IP and biolayer interferometry. Serum depletion-induced cellular apoptosis was attenuated by insulin-like growth factor-I (IGF-I), and this effect was abrogated by IGFBP-4. Of note, in the presence of AIM, the inhibitory effect of IGFBP-4 on the anti-apoptosis function of IGF-I was attenuated, possibly through binding of AIM with IGFBP-4. In conclusion, to the best of our knowledge, the present study provides the first evidence that AIM binds to IGFBP-2, -3 and -4. The data suggest that this interaction may contribute to the mechanism of AIM-mediated anti-apoptosis function. PMID:26135353

  2. Evolutionary Dynamics of Floral Homeotic Transcription Factor Protein–Protein Interactions

    PubMed Central

    Bartlett, Madelaine; Thompson, Beth; Brabazon, Holly; Del Gizzi, Robert; Zhang, Thompson; Whipple, Clinton

    2016-01-01

    Protein–protein interactions (PPIs) have widely acknowledged roles in the regulation of development, but few studies have addressed the timing and mechanism of shifting PPIs over evolutionary history. The B-class MADS-box transcription factors, PISTILLATA (PI) and APETALA3 (AP3) are key regulators of floral development. PI-like (PIL) and AP3-like (AP3L) proteins from a number of plants, including Arabidopsis thaliana (Arabidopsis) and the grass Zea mays (maize), bind DNA as obligate heterodimers. However, a PIL protein from the grass relative Joinvillea can bind DNA as a homodimer. To ascertain whether Joinvillea PIL homodimerization is an anomaly or indicative of broader trends, we characterized PIL dimerization across the Poales and uncovered unexpected evolutionary lability. Both obligate B-class heterodimerization and PIL homodimerization have evolved multiple times in the order, by distinct molecular mechanisms. For example, obligate B-class heterodimerization in maize evolved very recently from PIL homodimerization. A single amino acid change, fixed during domestication, is sufficient to toggle one maize PIL protein between homodimerization and obligate heterodimerization. We detected a signature of positive selection acting on residues preferentially clustered in predicted sites of contact between MADS-box monomers and dimers, and in motifs that mediate MADS PPI specificity in Arabidopsis. Changing one positively selected residue can alter PIL dimerization activity. Furthermore, ectopic expression of a Joinvillea PIL homodimer in Arabidopsis can homeotically transform sepals into petals. Our results provide a window into the evolutionary remodeling of PPIs, and show that novel interactions have the potential to alter plant form in a context-dependent manner. PMID:26908583

  3. The Role of Shape Complementarity in the Protein-Protein Interactions

    NASA Astrophysics Data System (ADS)

    Li, Ye; Zhang, Xianren; Cao, Dapeng

    2013-11-01

    We use a dissipative particle dynamic simulation to investigate the effects of shape complementarity on the protein-protein interactions. By monitoring different kinds of protein shape-complementarity modes, we gave a clear mechanism to reveal the role of the shape complementarity in the protein-protein interactions, i.e., when the two proteins with shape complementarity approach each other, the conformation of lipid chains between two proteins would be restricted significantly. The lipid molecules tend to leave the gap formed by two proteins to maximize the configuration entropy, and therefore yield an effective entropy-induced protein-protein attraction, which enhances the protein aggregation. In short, this work provides an insight into understanding the importance of the shape complementarity in the protein-protein interactions especially for protein aggregation and antibody-antigen complexes. Definitely, the shape complementarity is the third key factor affecting protein aggregation and complex, besides the electrostatic-complementarity and hydrophobic complementarity.

  4. Monitoring protein-protein interactions using split synthetic renilla luciferase protein-fragment-assisted complementation.

    PubMed

    Paulmurugan, R; Gambhir, S S

    2003-04-01

    In this study we developed an inducible synthetic renilla luciferase protein-fragment-assisted complementation-based bioluminescence assay to quantitatively measure real time protein-protein interactions in mammalian cells. We identified suitable sites to generate fragments of N and C portions of the protein that yield significant recovered activity through complementation. We validate complementation-based activation of split synthetic renilla luciferase protein driven by the interaction of two strongly interacting proteins, MyoD and Id, in five different cell lines utilizing transient transfection studies. The expression level of the system was also modulated by tumor necrosis factor alpha through NFkappaB-promoter/enhancer elements used to drive expression of the N portion of synthetic renilla luciferase reporter gene. This new system should help in studying protein-protein interactions and when used with other split reporters (e.g., split firefly luciferase) should help to monitor different components of an intracellular network.

  5. Promoter Recognition by Extracytoplasmic Function σ Factors: Analyzing DNA and Protein Interaction Motifs

    PubMed Central

    Guzina, Jelena

    2016-01-01

    ABSTRACT Extracytoplasmic function (ECF) σ factors are the largest and the most diverse group of alternative σ factors, but their mechanisms of transcription are poorly studied. This subfamily is considered to exhibit a rigid promoter structure and an absence of mixing and matching; both −35 and −10 elements are considered necessary for initiating transcription. This paradigm, however, is based on very limited data, which bias the analysis of diverse ECF σ subgroups. Here we investigate DNA and protein recognition motifs involved in ECF σ factor transcription by a computational analysis of canonical ECF subfamily members, much less studied ECF σ subgroups, and the group outliers, obtained from recently sequenced bacteriophages. The analysis identifies an extended −10 element in promoters for phage ECF σ factors; a comparison with bacterial σ factors points to a putative 6-amino-acid motif just C-terminal of domain σ2, which is responsible for the interaction with the identified extension of the −10 element. Interestingly, a similar protein motif is found C-terminal of domain σ2 in canonical ECF σ factors, at a position where it is expected to interact with a conserved motif further upstream of the −10 element. Moreover, the phiEco32 ECF σ factor lacks a recognizable −35 element and σ4 domain, which we identify in a homologous phage, 7-11, indicating that the extended −10 element can compensate for the lack of −35 element interactions. Overall, the results reveal greater flexibility in promoter recognition by ECF σ factors than previously recognized and raise the possibility that mixing and matching also apply to this group, a notion that remains to be biochemically tested. IMPORTANCE ECF σ factors are the most numerous group of alternative σ factors but have been little studied. Their promoter recognition mechanisms are obscured by the large diversity within the ECF σ factor group and the limited similarity with the well

  6. Molecular imaging of drug-modulated protein-protein interactions in living subjects.

    PubMed

    Paulmurugan, Ramasamy; Massoud, Tarik F; Huang, Jing; Gambhir, Sanjiv S

    2004-03-15

    Networks of protein interactions mediate cellular responses to environmental stimuli and direct the execution of many different cellular functional pathways. Small molecules synthesized within cells or recruited from the external environment mediate many protein interactions. The study of small molecule-mediated interactions of proteins is important to understand abnormal signal transduction pathways in cancer and in drug development and validation. In this study, we used split synthetic renilla luciferase (hRLUC) protein fragment-assisted complementation to evaluate heterodimerization of the human proteins FRB and FKBP12 mediated by the small molecule rapamycin. The concentration of rapamycin required for efficient dimerization and that of its competitive binder ascomycin required for dimerization inhibition were studied in cell lines. The system was dually modulated in cell culture at the transcription level, by controlling nuclear factor kappaB promoter/enhancer elements using tumor necrosis factor alpha, and at the interaction level, by controlling the concentration of the dimerizer rapamycin. The rapamycin-mediated dimerization of FRB and FKBP12 also was studied in living mice by locating, quantifying, and timing the hRLUC complementation-based bioluminescence imaging signal using a cooled charged coupled device camera. This split reporter system can be used to efficiently screen small molecule drugs that modulate protein-protein interactions and also to assess drugs in living animals. Both are essential steps in the preclinical evaluation of candidate pharmaceutical agents targeting protein-protein interactions, including signaling pathways in cancer cells.

  7. Interaction of Leptospira Elongation Factor Tu with Plasminogen and Complement Factor H: A Metabolic Leptospiral Protein with Moonlighting Activities

    PubMed Central

    Abe, Cecília M.; Monaris, Denize; Morais, Zenaide M.; Souza, Gisele O.; Vasconcellos, Sílvio A.; Isaac, Lourdes; Abreu, Patrícia A. E.; Barbosa, Angela S.

    2013-01-01

    The elongation factor Tu (EF-Tu), an abundant bacterial protein involved in protein synthesis, has been shown to display moonlighting activities. Known to perform more than one function at different times or in different places, it is found in several subcellular locations in a single organism, and may serve as a virulence factor in a range of important human pathogens. Here we demonstrate that Leptospira EF-Tu is surface-exposed and performs additional roles as a cell-surface receptor for host plasma proteins. It binds plasminogen in a dose-dependent manner, and lysine residues are critical for this interaction. Bound plasminogen is converted to active plasmin, which, in turn, is able to cleave the natural substrates C3b and fibrinogen. Leptospira EF-Tu also acquires the complement regulator Factor H (FH). FH bound to immobilized EF-Tu displays cofactor activity, mediating C3b degradation by Factor I (FI). In this manner, EF-Tu may contribute to leptospiral tissue invasion and complement inactivation. To our knowledge, this is the first description of a leptospiral protein exhibiting moonlighting activities. PMID:24312361

  8. Factors affecting interactions between sulphonate-terminated dendrimers and proteins: A three case study.

    PubMed

    González-García, Estefanía; Maly, Marek; de la Mata, Francisco Javier; Gómez, Rafael; Marina, María Luisa; García, María Concepción

    2017-01-01

    This work proposes a deep study on the interactions between sulphonate-terminated carbosilane dendrimers and proteins. Three different proteins with different molecular weights and isoelectric points were employed and different pHs, dendrimer concentrations and generations were tested. Variations in fluorescence intensity and emission wavelength were used as protein-dendrimer interaction probes. Interaction between dendrimers and proteins greatly depended on the protein itself and pH. Other important issues were the dendrimer concentration and generation. Protein-dendrimer interactions were favored under acidic working conditions when proteins were positively charged. Moreover, in general, high dendrimer generations promoted these interactions. Modeling of protein-dendrimer interactions allowed to understand the different behaviors observed for every protein. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. The Role of Shape Complementarity in the Protein-Protein Interactions

    PubMed Central

    Li, Ye; Zhang, Xianren; Cao, Dapeng

    2013-01-01

    We use a dissipative particle dynamic simulation to investigate the effects of shape complementarity on the protein-protein interactions. By monitoring different kinds of protein shape-complementarity modes, we gave a clear mechanism to reveal the role of the shape complementarity in the protein-protein interactions, i.e., when the two proteins with shape complementarity approach each other, the conformation of lipid chains between two proteins would be restricted significantly. The lipid molecules tend to leave the gap formed by two proteins to maximize the configuration entropy, and therefore yield an effective entropy-induced protein-protein attraction, which enhances the protein aggregation. In short, this work provides an insight into understanding the importance of the shape complementarity in the protein-protein interactions especially for protein aggregation and antibody–antigen complexes. Definitely, the shape complementarity is the third key factor affecting protein aggregation and complex, besides the electrostatic-complementarity and hydrophobic complementarity. PMID:24253561

  10. Mammalian splicing factor SF1 interacts with SURP domains of U2 snRNP-associated proteins

    PubMed Central

    Crisci, Angela; Raleff, Flore; Bagdiul, Ivona; Raabe, Monika; Urlaub, Henning; Rain, Jean-Christophe; Krämer, Angela

    2015-01-01

    Splicing factor 1 (SF1) recognizes the branch point sequence (BPS) at the 3′ splice site during the formation of early complex E, thereby pre-bulging the BPS adenosine, thought to facilitate subsequent base-pairing of the U2 snRNA with the BPS. The 65-kDa subunit of U2 snRNP auxiliary factor (U2AF65) interacts with SF1 and was shown to recruit the U2 snRNP to the spliceosome. Co-immunoprecipitation experiments of SF1-interacting proteins from HeLa cell extracts shown here are consistent with the presence of SF1 in early splicing complexes. Surprisingly almost all U2 snRNP proteins were found associated with SF1. Yeast two-hybrid screens identified two SURP domain-containing U2 snRNP proteins as partners of SF1. A short, evolutionarily conserved region of SF1 interacts with the SURP domains, stressing their role in protein–protein interactions. A reduction of A complex formation in SF1-depleted extracts could be rescued with recombinant SF1 containing the SURP-interaction domain, but only partial rescue was observed with SF1 lacking this sequence. Thus, SF1 can initially recruit the U2 snRNP to the spliceosome during E complex formation, whereas U2AF65 may stabilize the association of the U2 snRNP with the spliceosome at later times. In addition, these findings may have implications for alternative splicing decisions. PMID:26420826

  11. Specificity of molecular interactions in transient protein-protein interaction interfaces.

    PubMed

    Cho, Kyu-il; Lee, KiYoung; Lee, Kwang H; Kim, Dongsup; Lee, Doheon

    2006-11-15

    In this study, we investigate what types of interactions are specific to their biological function, and what types of interactions are persistent regardless of their functional category in transient protein-protein heterocomplexes. This is the first approach to analyze protein-protein interfaces systematically at the molecular interaction level in the context of protein functions. We perform systematic analysis at the molecular interaction level using classification and feature subset selection technique prevalent in the field of pattern recognition. To represent the physicochemical properties of protein-protein interfaces, we design 18 molecular interaction types using canonical and noncanonical interactions. Then, we construct input vector using the frequency of each interaction type in protein-protein interface. We analyze the 131 interfaces of transient protein-protein heterocomplexes in PDB: 33 protease-inhibitors, 52 antibody-antigens, 46 signaling proteins including 4 cyclin dependent kinase and 26 G-protein. Using kNN classification and feature subset selection technique, we show that there are specific interaction types based on their functional category, and such interaction types are conserved through the common binding mechanism, rather than through the sequence or structure conservation. The extracted interaction types are C(alpha)-- H...O==C interaction, cation...anion interaction, amine...amine interaction, and amine...cation interaction. With these four interaction types, we achieve the classification success rate up to 83.2% with leave-one-out cross-validation at k = 15. Of these four interaction types, C(alpha)--H...O==C shows binding specificity for protease-inhibitor complexes, while cation-anion interaction is predominant in signaling complexes. The amine ... amine and amine...cation interaction give a minor contribution to the classification accuracy. When combined with these two interactions, they increase the accuracy by 3.8%. In the case of

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

    PubMed

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

    2006-04-15

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

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Beers, Eric; Brunner, Amy; Helm, Richard

    -depth characterizations. Characterizations involved both in vivo and in vitro independent methods to confirm protein-protein interactions and the evaluation of novel phenotypes resulting from creation of transgenic poplar and Arabidopsis plants engineered for increased or decreased expression of the selected genes. Transgenic poplar trees were studied in growth chamber, greenhouse, and two separate replicated field trials involving over 25 distinct wood-associated proteins. In-depth characterizations yielding positive results include the following. First, a NAC domain transcription factor (NAC154) that is a promoter of stress response and dormancy in trees was discovered. Increasing expression of NAC154 caused stunted growth and premature senescence, while decreasing expression led to both delayed bud and leaf expansion in spring and delayed leaf drop (i.e., prolonged leaf retention) in fall. Second, we discovered and characterized a new connection between a negative regulator of wood formation, the NAC domain transcription factor XND1, and an important regulator of cell division and cell differentiation, RBR. Third, we identified a new network of interacting wood-associated transcription factors belonging to the MYB and HD families. One of the HD family proteins, WOX13, was used to prepare transgenic poplar for high-level expression, resulting in significantly increased lateral branch growth. Finally, we modeled and performed in vitro analyses of the insect protein rubber resilin and we prepared transgenic Arabidopsis plants for expression of resilin to test the feasibility of using resilin to modify lignin cross-linking in wood and reduce recalcitrance and improve yield of fermentable sugars for biofuels production. Analysis of these and additional transgenics created with this support is continuing.« less

  14. Protein Kinase A Modulates Transforming Growth Factor-β Signaling through a Direct Interaction with Smad4 Protein*

    PubMed Central

    Yang, Huibin; Li, Gangyong; Wu, Jing-Jiang; Wang, Lidong; Uhler, Michael; Simeone, Diane M.

    2013-01-01

    Transforming growth factor β (TGFβ) signaling normally functions to regulate embryonic development and cellular homeostasis. It is increasingly recognized that TGFβ signaling is regulated by cross-talk with other signaling pathways. We previously reported that TGFβ activates protein kinase A (PKA) independent of cAMP through an interaction of an activated Smad3-Smad4 complex and the regulatory subunit of the PKA holoenzyme (PKA-R). Here we define the interaction domains of Smad4 and PKA-R and the functional consequences of this interaction. Using a series of Smad4 and PKA-R truncation mutants, we identified amino acids 290–300 of the Smad4 linker region as critical for the specific interaction of Smad4 and PKA-R. Co-immunoprecipitation assays showed that the B cAMP binding domain of PKA-R was sufficient for interaction with Smad4. Targeting of B domain regions conserved among all PKA-R isoforms and exposed on the molecular surface demonstrated that amino acids 281–285 and 320–329 were required for complex formation with Smad4. Interactions of these specific regions of Smad4 and PKA-R were necessary for TGFβ-mediated increases in PKA activity, CREB (cAMP-response element-binding protein) phosphorylation, induction of p21, and growth inhibition. Moreover, this Smad4-PKA interaction was required for TGFβ-induced epithelial mesenchymal transition, invasion of pancreatic tumor cells, and regulation of tumor growth in vivo. PMID:23362281

  15. Rsd family proteins make simultaneous interactions with regions 2 and 4 of the primary sigma factor

    PubMed Central

    Yuan, Andy H.; Gregory, Brian D.; Sharp, Josh S.; McCleary, Katherine D.; Dove, Simon L.; Hochschild, Ann

    2008-01-01

    Summary Bacterial anti-σ factors typically regulate σ factor function by restricting the access of their cognate σ factors to the RNA polymerase (RNAP) core enzyme. The E. coli Rsd protein forms a complex with the primary σ factor, σ70, inhibits σ70-dependent transcription in vitro, and has been proposed to function as a σ70-specific anti-σ factor, thereby facilitating the utilization of alternative σ factors. In prior work, Rsd has been shown to interact with conserved region 4 of σ70, but it is not known whether this interaction suffices to account for the regulatory functions of Rsd. Here we show that Rsd and the Rsd ortholog AlgQ, a global regulator of gene expression in P. aeruginosa, interact with conserved region 2 of σ70. We show further that Rsd and AlgQ can interact simultaneously with regions 2 and 4 of σ70. Our findings establish that the abilities of Rsd and AlgQ to interact with σ70 region 2 are important determinants of their in vitro and in vivo activities. PMID:18826409

  16. Rsd family proteins make simultaneous interactions with regions 2 and 4 of the primary sigma factor.

    PubMed

    Yuan, Andy H; Gregory, Brian D; Sharp, Josh S; McCleary, Katherine D; Dove, Simon L; Hochschild, Ann

    2008-12-01

    Bacterial anti-sigma factors typically regulate sigma factor function by restricting the access of their cognate sigma factors to the RNA polymerase (RNAP) core enzyme. The Escherichia coli Rsd protein forms a complex with the primary sigma factor, sigma(70), inhibits sigma(70)-dependent transcription in vitro, and has been proposed to function as a sigma(70)-specific anti-sigma factor, thereby facilitating the utilization of alternative sigma factors. In prior work, Rsd has been shown to interact with conserved region 4 of sigma(70), but it is not known whether this interaction suffices to account for the regulatory functions of Rsd. Here we show that Rsd and the Rsd orthologue AlgQ, a global regulator of gene expression in Pseudomonas aeruginosa, interact with conserved region 2 of sigma(70). We show further that Rsd and AlgQ can interact simultaneously with regions 2 and 4 of sigma(70). Our findings establish that the abilities of Rsd and AlgQ to interact with sigma(70) region 2 are important determinants of their in vitro and in vivo activities.

  17. Mapping protein-DNA and protein-protein interactions of ATP-dependent chromatin remodelers.

    PubMed

    Hota, Swetansu K; Dechassa, Mekonnen Lemma; Prasad, Punit; Bartholomew, Blaine

    2012-01-01

    Chromatin plays a key regulatory role in several DNA-dependent processes as it regulates DNA access to different protein factors. Several multisubunit protein complexes interact, modify, or mobilize nucleosomes: the basic unit of chromatin, from its original location in an ATP-dependent manner to facilitate processes, such as transcription, replication, repair, and recombination. Knowledge of the interactions of chromatin remodelers with nucleosomes is a crucial requirement to understand the mechanism of chromatin remodeling. Here, we describe several methods to analyze the interactions of multisubunit chromatin-remodeling enzymes with nucleosomes.

  18. Direct interaction between the tobacco mosaic virus helicase domain and the ATP-bound resistance protein, N factor during the hypersensitive response in tobacco plants.

    PubMed

    Ueda, Hirokazu; Yamaguchi, Yube; Sano, Hiroshi

    2006-05-01

    Plants cope with pathogens with distinct mechanisms. One example is a gene-for-gene system, in which plants recognize the pathogen molecule by specified protein(s), this being called the R factor. However, mechanisms of interaction between proteins from the host and the pathogen are not completely understood. Here, we analyzed the mode of interaction between the N factor, a tobacco R factor, and the helicase domain (p50) of tobacco mosaic virus (TMV). To this end, domain dissected proteins were prepared and subjected to Agroinfiltration into intact leaves, followed by yeast two hybrid and pull-down assays. The results pointed to three novel features. First, the N factor was found to directly bind to the p50 of TMV, second, ATP was pre-requisite for this interaction, with formation of an ATP/N factor complex, and third, the N factor was shown to possess ATPase activity, which is enhanced by the p50. Moreover, we found that intra- and/or inter-molecular interactions take place in the N factor molecule. This interaction required ATP, and was disrupted by the p50. Based on these results, we propose a following model for the TMV recognition mechanism in tobacco plants. The N factor forms a complex with ATP, to which the helicase domain interacts, and enhances ATP hydrolysis. The resulting ADP/N factor complex then changes its conformation, thereby facilitating further interaction with the down-stream signaling factor(s). This model is consistent with the idea of 'protein machine'.

  19. Profiling lethal factor interacting proteins from human stomach using T7 phage display screening.

    PubMed

    Cardona-Correa, Albin; Rios-Velazquez, Carlos

    2016-05-01

    The anthrax lethal factor (LF) is a zinc dependent metalloproteinase that cleaves the majority of mitogen-activated protein kinase kinases and a member of NOD-like receptor proteins, inducing cell apoptosis. Despite efforts to fully understand the Bacillus anthracis toxin components, the gastrointestinal (GI) anthrax mechanisms have not been fully elucidated. Previous studies demonstrated gastric ulceration, and a substantial bacterial growth rate in Peyer's patches. However, the complete molecular pathways of the disease that results in tissue damage by LF proteolytic activity remains unclear. In the present study, to identify the profile of the proteins potentially involved in GI anthrax, protein‑protein interactions were investigated using human stomach T7 phage display (T7PD) cDNA libraries. T7PD is a high throughput technique that allows the expression of cloned DNA sequences as peptides on the phage surface, enabling the selection and identification of protein ligands. A wild type and mutant LF (E687A) were used to differentiate interaction sites. A total of 124 clones were identified from 194 interacting‑phages, at both the DNA and protein level, by in silico analysis. Databases revealed that the selected candidates were proteins from different families including lipase, peptidase‑A1 and cation transport families, among others. Furthermore, individual T7PD candidates were tested against LF in order to detect their specificity to the target molecule, resulting in 10 LF‑interacting peptides. With a minimum concentration of LF for interaction at 1 µg/ml, the T7PD isolated pepsin A3 pre‑protein (PAP) demonstrated affinity to both types of LF. In addition, PAP was isolated in various lengths for the same protein, exhibiting common regions following PRALINE alignment. These findings will help elucidate and improve the understanding of the molecular pathogenesis of GI anthrax, and aid in the development of potential therapeutic agents.

  20. 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. © 2014 Wiley Periodicals, Inc.

  1. Construction of reliable protein-protein interaction networks with a new interaction generality measure.

    PubMed

    Saito, Rintaro; Suzuki, Harukazu; Hayashizaki, Yoshihide

    2003-04-12

    Recent screening techniques have made large amounts of protein-protein interaction data available, from which biologically important information such as the function of uncharacterized proteins, the existence of novel protein complexes, and novel signal-transduction pathways can be discovered. However, experimental data on protein interactions contain many false positives, making these discoveries difficult. Therefore computational methods of assessing the reliability of each candidate protein-protein interaction are urgently needed. We developed a new 'interaction generality' measure (IG2) to assess the reliability of protein-protein interactions using only the topological properties of their interaction-network structure. Using yeast protein-protein interaction data, we showed that reliable protein-protein interactions had significantly lower IG2 values than less-reliable interactions, suggesting that IG2 values can be used to evaluate and filter interaction data to enable the construction of reliable protein-protein interaction networks.

  2. Characterization of protein-protein interaction domains within the baculovirus Autographa californica multiple nucleopolyhedrovirus late expression factor LEF-3.

    PubMed

    Downie, Kelsey; Adetola, Gbolagade; Carstens, Eric B

    2013-11-01

    Autographa californica nucleopolyhedrovirus late expression factor 3 (LEF-3) is required for late viral gene expression probably through its numerous functions related to DNA replication, including nuclear localization of the virus helicase P143 and binding to ssDNA. LEF-3 appears to interact with itself as a homo-oligomer, although the details of this oligomeric structure are not yet known. To examine LEF-3-LEF-3 interactions, a bimolecular fluorescent protein complementation assay was used. Pairs of recombinant plasmids expressing full-length LEF-3 fused to one of two complementary fragments (V1 or V2) of a variant of yellow fluorescent protein named 'Venus' were constructed. Plasmids expressing fusions with complementary fragments of Venus were co-transfected into Sf21 cells and analysed by fluorescence microscopy. Co-transfected plasmids expressing full-length V1-LEF-3 and V2-LEF-3 showed positive fluorescence, confirming the formation of homo-oligomers. A series of truncated V1/V2-LEF-3 fusions was constructed and used to investigate interactions with one another as well as with full-length LEF-3.

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

    PubMed Central

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

    2013-01-01

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

  4. Interaction entropy for protein-protein binding

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  5. Building blocks for protein interaction devices

    PubMed Central

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

    2010-01-01

    Here, we propose a framework for the design of synthetic protein networks from modular protein–protein or protein–peptide interactions and provide a starter toolkit of protein building blocks. Our proof of concept experiments outline a general work flow for part–based protein systems engineering. We streamlined the iterative BioBrick cloning protocol and assembled 25 synthetic multidomain proteins each from seven standardized DNA fragments. A systematic screen revealed two main factors controlling protein expression in Escherichia coli: obstruction of translation initiation by mRNA secondary structure or toxicity of individual domains. Eventually, 13 proteins were purified for further characterization. Starting from well-established biotechnological tools, two general–purpose interaction input and two readout devices were built and characterized in vitro. Constitutive interaction input was achieved with a pair of synthetic leucine zippers. The second interaction was drug-controlled utilizing the rapamycin-induced binding of FRB(T2098L) to FKBP12. The interaction kinetics of both devices were analyzed by surface plasmon resonance. Readout was based on Förster resonance energy transfer between fluorescent proteins and was quantified for various combinations of input and output devices. Our results demonstrate the feasibility of parts-based protein synthetic biology. Additionally, we identify future challenges and limitations of modular design along with approaches to address them. PMID:20215443

  6. Accumulation of transcription factors and cell signaling-related proteins in the nucleus during citrus-Xanthomonas interaction.

    PubMed

    Rani, T Swaroopa; Durgeshwar, P; Podile, Appa Rao

    2015-07-20

    The nucleus is the maestro of the cell and is involved in the modulation of cell signaling during stress. We performed a comprehensive nuclear proteome analysis of Citrus sinensis during interaction with host (Xanthomonas citri pv. citri-Xcc) and non-host (Xanthomonas oryzae pv. oryzae-Xoo) pathogens. The nuclear proteome was obtained using a sequential method of organelle enrichment and determined by nano-LC-MS/MS analysis. A total of 243 proteins accumulated differentially during citrus-Xanthomonas interaction, belonging to 11 functional groups, with signaling and transcription-related proteins dominating. MADS-box transcription factors, DEAD-box RNA helicase and leucine aminopeptidase, mainly involved in jasmonic acid (JA) responses, were in high abundance during non-host interaction (Xoo). Signaling-related proteins like serine/threonine kinase, histones (H3.2, H2A), phosphoglycerate kinase, dynamin, actin and aldolase showed increased accumulation early during Xoo interaction. Our results suggest that there is a possible involvement of JA-triggered defense responses during non-host resistance, with early recognition of the non-host pathogen. Copyright © 2015. Published by Elsevier GmbH.

  7. 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

  8. Gradient elution behavior of proteins in hydrophobic interaction chromatography with U-shaped retention factor curves.

    PubMed

    Creasy, Arch; Lomino, Joseph; Barker, Gregory; Khetan, Anurag; Carta, Giorgio

    2018-04-27

    Protein retention in hydrophobic interaction chromatography is described by the solvophobic theory as a function of the kosmostropic salt concentration. In general, an increase in salt concentration drives protein partitioning to the hydrophobic surface while a decrease reduces it. In some cases, however, protein retention also increases at low salt concentrations resulting in a U-shaped retention factor curve. During gradient elution the salt concentration is gradually decreased from a high value thereby reducing the retention factor and increasing the protein chromatographic velocity. For these conditions, a steep gradient can overtake the protein in the column, causing it to rebind. Two dynamic models, one based on the local equilibrium theory and the other based on the linear driving force approximation, are presented. We show that the normalized gradient slope determines whether the protein elutes in the gradient, partially elutes, or is trapped in the column. Experimental results are presented for two different monoclonal antibodies and for lysozyme on Capto Phenyl (High Sub) resin. One of the mAbs and lysozyme exhibit U-shaped retention factor curves and for each, we determine the critical gradient slope beyond which 100% recovery is no longer possible. Elution with a reverse gradient is also demonstrated at low salt concentrations for these proteins. Understanding this behavior has implications in the design of gradient elution since the gradient slope impacts protein recovery. Copyright © 2018 Elsevier B.V. All rights reserved.

  9. Hypoxia inducible factor (HIF) as a model for studying inhibition of protein–protein interactions

    PubMed Central

    Burslem, George M.; Kyle, Hannah F.; Nelson, Adam; Edwards, Thomas A.

    2017-01-01

    The modulation of protein–protein interactions (PPIs) represents a major challenge in modern chemical biology. Current approaches (e.g. high-throughput screening, computer aided ligand design) are recognised as having limitations in terms of identification of hit matter. Considerable success has been achieved in terms of developing new approaches to PPI modulator discovery using the p53/hDM2 and Bcl-2 family of PPIs. However these important targets in oncology might be considered as “low-hanging-fruit”. Hypoxia inducible factor (HIF) is an emerging, but not yet fully validated target for cancer chemotherapy. Its role is to regulate the hypoxic response and it does so through a plethora of protein–protein interactions of varying topology, topography and complexity: its modulation represents an attractive approach to prevent development of new vasculature by hypoxic tumours. PMID:28878873

  10. Cross-regulatory protein–protein interactions between Hox and Pax transcription factors

    PubMed Central

    Plaza, Serge; Prince, Frederic; Adachi, Yoshitsugu; Punzo, Claudio; Cribbs, David L.; Gehring, Walter J.

    2008-01-01

    Homeotic Hox selector genes encode highly conserved transcriptional regulators involved in the differentiation of multicellular organisms. Ectopic expression of the Antennapedia (ANTP) homeodomain protein in Drosophila imaginal discs induces distinct phenotypes, including an antenna-to-leg transformation and eye reduction. We have proposed that the eye loss phenotype is a consequence of a negative posttranslational control mechanism because of direct protein–protein interactions between ANTP and Eyeless (EY). In the present work, we analyzed the effect of various ANTP homeodomain mutations for their interaction with EY and for head development. Contrasting with the eye loss phenotype, we provide evidence that the antenna-to-leg transformation involves ANTP DNA-binding activity. In a complementary genetic screen performed in yeast, we isolated mutations located in the N terminus of the ANTP homeodomain that inhibit direct interactions with EY without abolishing DNA binding in vitro and in vivo. In a bimolecular fluorescence complementation assay, we detected the ANTP–EY interaction in vivo, these interactions occurring through the paired domain and/or the homeodomain of EY. These results demonstrate that the homeodomain supports multiple molecular regulatory functions in addition to protein–DNA and protein–RNA interactions; it is also involved in protein–protein interactions. PMID:18755899

  11. Mapping transcription factor interactome networks using HaloTag protein arrays.

    PubMed

    Yazaki, Junshi; Galli, Mary; Kim, Alice Y; Nito, Kazumasa; Aleman, Fernando; Chang, Katherine N; Carvunis, Anne-Ruxandra; Quan, Rosa; Nguyen, Hien; Song, Liang; Alvarez, José M; Huang, Shao-Shan Carol; Chen, Huaming; Ramachandran, Niroshan; Altmann, Stefan; Gutiérrez, Rodrigo A; Hill, David E; Schroeder, Julian I; Chory, Joanne; LaBaer, Joshua; Vidal, Marc; Braun, Pascal; Ecker, Joseph R

    2016-07-19

    Protein microarrays enable investigation of diverse biochemical properties for thousands of proteins in a single experiment, an unparalleled capacity. Using a high-density system called HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we created high-density protein arrays comprising 12,000 Arabidopsis ORFs. We used these arrays to query protein-protein interactions for a set of 38 transcription factors and transcriptional regulators (TFs) that function in diverse plant hormone regulatory pathways. The resulting transcription factor interactome network, TF-NAPPA, contains thousands of novel interactions. Validation in a benchmarked in vitro pull-down assay revealed that a random subset of TF-NAPPA validated at the same rate of 64% as a positive reference set of literature-curated interactions. Moreover, using a bimolecular fluorescence complementation (BiFC) assay, we confirmed in planta several interactions of biological interest and determined the interaction localizations for seven pairs. The application of HaloTag-NAPPA technology to plant hormone signaling pathways allowed the identification of many novel transcription factor-protein interactions and led to the development of a proteome-wide plant hormone TF interactome network.

  12. Genome-Wide Protein Interaction Screens Reveal Functional Networks Involving Sm-Like Proteins

    PubMed Central

    Fromont-Racine, Micheline; Mayes, Andrew E.; Brunet-Simon, Adeline; Rain, Jean-Christophe; Colley, Alan; Dix, Ian; Decourty, Laurence; Joly, Nicolas; Ricard, Florence; Beggs, Jean D.

    2000-01-01

    A set of seven structurally related Sm proteins forms the core of the snRNP particles containing the spliceosomal U1, U2, U4 and U5 snRNAs. A search of the genomic sequence of Saccharomyces cerevisiae has identified a number of open reading frames that potentially encode structurally similar proteins termed Lsm (Like Sm) proteins. With the aim of analysing all possible interactions between the Lsm proteins and any protein encoded in the yeast genome, we performed exhaustive and iterative genomic two-hybrid screens, starting with the Lsm proteins as baits. Indeed, extensive interactions amongst eight Lsm proteins were found that suggest the existence of a Lsm complex or complexes. These Lsm interactions apparently involve the conserved Sm domain that also mediates interactions between the Sm proteins. The screens also reveal functionally significant interactions with splicing factors, in particular with Prp4 and Prp24, compatible with genetic studies and with the reported association of Lsm proteins with spliceosomal U6 and U4/U6 particles. In addition, interactions with proteins involved in mRNA turnover, such as Mrt1, Dcp1, Dcp2 and Xrn1, point to roles for Lsm complexes in distinct RNA metabolic processes, that are confirmed in independent functional studies. These results provide compelling evidence that two-hybrid screens yield functionally meaningful information about protein–protein interactions and can suggest functions for uncharacterized proteins, especially when they are performed on a genome-wide scale. PMID:10900456

  13. Soybean TCP transcription factors: Evolution, classification, protein interaction and stress and hormone responsiveness.

    PubMed

    Feng, Zhi-Juan; Xu, Sheng-Chun; Liu, Na; Zhang, Gu-Wen; Hu, Qi-Zan; Gong, Ya-Ming

    2018-06-01

    TEOSINTE-BRANCHED1/CYCLOIDEA/PCF (TCP) transcription factors, a family of plant-specific proteins, play crucial roles in plant growth and development and stress response. However, systematical information is unknown regarding the TCP gene family in soybean. In the present study, a total of 54 GmTCPs were identified in soybean, which were grouped into 11 groups with the typical TCP conserved domains. Phylogenetic relationship, protein motif and gene structure analyses distinguished the GmTCPs into two homology classes: Class I and Class II. Class II was then differentiated into two subclasses: CIN and CYC/TB1. Unique cis-element number and composition existed in the promoter regions which might be involved in the gene transcriptional regulation of different GmTCPs. Tissue expression analysis demonstrated the diverse spatiotemporal expression profiles of GmTCPs. Furthermore, the interaction protein of one previously functionally unknown TCP protein-GmTCP8 was investigated. Yeast two-hybrid assay showed the interaction between GmTCP8 and an abscisic acid receptor (GmPYL10). QRT-PCR assays indicated the distinct expression profiles of GmTCPs in response to abiotic stresses (heat, drought and salt) and stress-related signals (abscisic acid, brassinolide, salicylicacid and methyl jasmonate). These results will facilitate to uncover the possible roles of GmTCPs under abiotic stress and hormone signal responses in soybean. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

  14. Survey of rice proteins interacting with OsFCA and OsFY proteins which are homologous to the Arabidopsis flowering time proteins, FCA and FY.

    PubMed

    Jang, Yun Hee; Park, Hyo-Young; Kim, Soon-Kap; Lee, Jeong Hwan; Suh, Mi Chung; Chung, Young Soo; Paek, Kyung-Hee; Kim, Jeong-Kook

    2009-08-01

    The FCA protein is involved in controlling flowering time and plays more general roles in RNA-mediated chromatin silencing in Arabidopsis. It contains two RNA-binding domains and a WW domain. The FCA protein interacts with FY, a polyadenylation factor, via its WW domain. We previously characterized a rice gene, OsFCA, which was homologous to FCA. Here, we found that the OsFCA protein could interact through its WW domain with the following proteins: OsFY, a protein containing a CID domain present in RNA-processing factors such as Pcf11 and Nrd1; a protein similar to splicing factor SF1; a protein similar to FUSE splicing factor; and OsMADS8. The FY protein is associated with the 3' end processing machinery in Arabidopsis. Thus, we examined interactions between OsFY and the rice homologs (OsCstF-50, -64 and -77) of the AtCstF-50, -64 and -77 proteins. We found that OsFY could bind OsCstF50, whereas the OsCstF77 protein could bridge the interaction between OsCstF50 and OsCstF64. Taken together, our data suggest that OsFCA could interact with several proteins other than OsFY through its WW domain and may play several roles in rice.

  15. Luciferase Complementation Imaging Assay in Nicotiana benthamiana Leaves for Transiently Determining Protein-protein Interaction Dynamics.

    PubMed

    Sun, Kaiwen; Zheng, Yuyu; Zhu, Ziqiang

    2017-11-20

    Protein-protein interactions are fundamental mechanisms for relaying signal transduction in most cellular processes; therefore, identification of novel protein-protein interaction pairs and monitoring protein interaction dynamics are of particular interest for revealing how plants respond to environmental factors and/or developmental signals. A plethora of approaches have been developed to examine protein-protein interactions, either in vitro or in vivo. Among them, the recently established luciferase complementation imaging (LCI) assay is the simplest and fastest method for demonstrating in vivo protein-protein interactions. In this assay, protein A or protein B is fused with the amino-terminal or carboxyl-terminal half of luciferase, respectively. When protein A interacts with protein B, the two halves of luciferase will be reconstituted to form a functional and active luciferase enzyme. Luciferase activity can be recorded with a luminometer or CCD-camera. Compared with other approaches, the LCI assay shows protein-protein interactions both qualitatively and quantitatively. Agrobacterium infiltration in Nicotiana benthamiana leaves is a widely used system for transient protein expression. With the combination of LCI and transient expression, these approaches show that the physical interaction between COP1 and SPA1 was gradually reduced after jasmonate treatment.

  16. Electrostatic Forces as Dominant Interactions Between Proteins and Polyanions: an ESI MS Study of Fibroblast Growth Factor Binding to Heparin Oligomers

    NASA Astrophysics Data System (ADS)

    Minsky, Burcu Baykal; Dubin, Paul L.; Kaltashov, Igor A.

    2017-04-01

    The interactions between fibroblast growth factors (FGFs) and their receptors (FGFRs) are facilitated by heparan sulfate (HS) and heparin (Hp), highly sulfated biological polyelectrolytes. The molecular basis of FGF interactions with these polyelectrolytes is highly complex due to the structural heterogeneity of HS/Hp, and many details still remain elusive, especially the significance of charge density and minimal chain length of HS/Hp in growth factor recognition and multimerization. In this work, we use electrospray ionization mass spectrometry (ESI MS) to investigate the association of relatively homogeneous oligoheparins (octamer, dp8, and decamer, dp10) with acidic fibroblast growth factor (FGF-1). This growth factor forms 1:1, 2:1, and 3:1 protein/heparinoid complexes with both dp8 and dp10, and the fraction of bound protein is highly dependent on protein/heparinoid molar ratio. Multimeric complexes are preferentially formed on the highly sulfated Hp oligomers. Although a variety of oligomers appear to be binding-competent, there is a strong correlation between the affinity and the overall level of sulfation (the highest charge density polyanions binding FGF most strongly via multivalent interactions). These results show that the interactions between FGF-1 and Hp oligomers are primarily directed by electrostatics, and also demonstrate the power of ESI MS as a tool to study multiple binding equilibria between proteins and structurally heterogeneous polyanions.

  17. A mammalian germ cell-specific RNA-binding protein interacts with ubiquitously expressed proteins involved in splice site selection

    NASA Astrophysics Data System (ADS)

    Elliott, David J.; Bourgeois, Cyril F.; Klink, Albrecht; Stévenin, James; Cooke, Howard J.

    2000-05-01

    RNA-binding motif (RBM) genes are found on all mammalian Y chromosomes and are implicated in spermatogenesis. Within human germ cells, RBM protein shows a similar nuclear distribution to components of the pre-mRNA splicing machinery. To address the function of RBM, we have used protein-protein interaction assays to test for possible physical interactions between these proteins. We find that RBM protein directly interacts with members of the SR family of splicing factors and, in addition, strongly interacts with itself. We have mapped the protein domains responsible for mediating these interactions and expressed the mouse RBM interaction region as a bacterial fusion protein. This fusion protein can pull-down several functionally active SR protein species from cell extracts. Depletion and add-back experiments indicate that these SR proteins are the only splicing factors bound by RBM which are required for the splicing of a panel of pre-mRNAs. Our results suggest that RBM protein is an evolutionarily conserved mammalian splicing regulator which operates as a germ cell-specific cofactor for more ubiquitously expressed pre-mRNA splicing activators.

  18. 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.

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

    PubMed Central

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

    2015-01-01

    A common approach for exploring the interactome, the network of protein-protein interactions in cells, uses a commercially available ORF library to express affinity tagged bait proteins; these can be expressed in cells and endogenous cellular proteins that copurify with the bait can be identified as putative interacting proteins using mass spectrometry. Control experiments can be used to limit false-positive results, but in many cases, there are still a surprising number of prey proteins that appear to copurify specifically with the bait. Here, we have identified one source of false-positive interactions in such studies. We have found that a combination of: 1) the variable sequence of the C-terminus of the bait with 2) a C-terminal valine “cloning scar” present in a commercially available ORF library, can in some cases create a peptide motif that results in the aberrant co-purification of endogenous cellular proteins. Control experiments may not identify false positives resulting from such artificial motifs, as aberrant binding depends on sequences that vary from one bait to another. It is possible that such cryptic protein binding might occur in other systems using affinity tagged proteins; this study highlights the importance of conducting careful follow-up studies where novel protein-protein interactions are suspected. PMID:25704442

  20. Optimization of rhodanine scaffold for the development of protein-protein interaction inhibitors.

    PubMed

    Ferro, Stefania; De Luca, Laura; Agharbaoui, Fatima Ezzahra; Christ, Frauke; Debyser, Zeger; Gitto, Rosaria

    2015-07-01

    Searching for novel protein-protein interactions inhibitors (PPIs) herein we describe the identification of a new series of rhodanine derivatives. The selection was performed by means virtual-screening, docking studies, Molecular Dynamic (MD) simulations and synthetic approaches. All the new obtained compounds were tested in order to evaluate their ability to inhibit the interaction between the HIV-1 integrase (IN) enzyme and the nuclear protein lens epithelium growth factor LEDGF/p75. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

    PubMed Central

    Khor, Susan

    2014-01-01

    Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains. PMID:24586450

  2. 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

  3. Monitoring Protein–Protein Interactions Using Split Synthetic Renilla Luciferase Protein-Fragment-Assisted Complementation

    PubMed Central

    Paulmurugan, R.; Gambhir, S. S.

    2014-01-01

    In this study we developed an inducible synthetic renilla luciferase protein-fragment-assisted complementation-based bioluminescence assay to quantitatively measure real time protein–protein interactions in mammalian cells. We identified suitable sites to generate fragments of N and C portions of the protein that yield significant recovered activity through complementation. We validate complementation-based activation of split synthetic renilla luciferase protein driven by the interaction of two strongly interacting proteins, MyoD and Id, in five different cell lines utilizing transient transfection studies. The expression level of the system was also modulated by tumor necrosis factor α through NFκB-promoter/enhancer elements used to drive expression of the N portion of synthetic renilla luciferase reporter gene. This new system should help in studying protein–protein interactions and when used with other split reporters (e.g., split firefly luciferase) should help to monitor different components of an intracellular network. PMID:12705589

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

    PubMed

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

    2002-11-01

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

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

    PubMed

    Smeller, László

    2016-07-01

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

  6. Huntingtin interacting protein 1 is a novel brain tumor marker that associates with epidermal growth factor receptor.

    PubMed

    Bradley, Sarah V; Holland, Eric C; Liu, Grace Y; Thomas, Dafydd; Hyun, Teresa S; Ross, Theodora S

    2007-04-15

    Huntingtin interacting protein 1 (HIP1) is a multidomain oncoprotein whose expression correlates with increased epidermal growth factor receptor (EGFR) levels in certain tumors. For example, HIP1-transformed fibroblasts and HIP1-positive breast cancers have elevated EGFR protein levels. The combined association of HIP1 with huntingtin, the protein that is mutated in Huntington's disease, and the known overexpression of EGFR in glial brain tumors prompted us to explore HIP1 expression in a group of patients with different types of brain cancer. We report here that HIP1 is overexpressed with high frequency in brain cancers and that this overexpression correlates with EGFR and platelet-derived growth factor beta receptor expression. Furthermore, serum samples from patients with brain cancer contained anti-HIP1 antibodies more frequently than age-matched brain cancer-free controls. Finally, we report that HIP1 physically associates with EGFR and that this association is independent of the lipid, clathrin, and actin interacting domains of HIP1. These findings suggest that HIP1 may up-regulate or maintain EGFR overexpression in primary brain tumors by directly interacting with the receptor. This novel HIP1-EGFR interaction may work with or independent of HIP1 modulation of EGFR degradation via clathrin-mediated membrane trafficking pathways. Further investigation of HIP1 function in brain cancer biology and validation of its use as a prognostic or predictive brain tumor marker are now warranted.

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

    PubMed Central

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

    2011-01-01

    Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. PMID:21666777

  8. Capturing the Interaction Potential of Amyloidogenic Proteins

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Javid, Nadeem; Vogtt, Karsten; Winter, Roland

    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.

  9. Apple FLOWERING LOCUS T proteins interact with transcription factors implicated in cell growth and organ development.

    PubMed

    Mimida, Naozumi; Kidou, Shin-Ichiro; Iwanami, Hiroshi; Moriya, Shigeki; Abe, Kazuyuki; Voogd, Charlotte; Varkonyi-Gasic, Erika; Kotoda, Nobuhiro

    2011-05-01

    Understanding the flowering process in apple (Malus × domestica Borkh.) is essential for developing methods to shorten the breeding period and regulate fruit yield. It is known that FLOWERING LOCUS T (FT) acts as a transmissible floral inducer in the Arabidopsis flowering network system. To clarify the molecular network of two apple FT orthologues, MdFT1 and MdFT2, we performed a yeast two-hybrid screen to identify proteins that interact with MdFT1. We identified several transcription factors, including two members of the TCP (TEOSINTE BRANCHED1, CYCLOIDEA and PROLIFERATING CELL FACTORs) family, designated MdTCP2 and MdTCP4, and an Arabidopsis thaliana VOZ1 (Vascular plant One Zinc finger protein1)-like protein, designated MdVOZ1. MdTCP2 and MdVOZ1 also interacted with MdFT2 in yeast. The expression domain of MdTCP2 and MdVOZ1 partially overlapped with that of MdFT1 and MdFT2, most strikingly in apple fruit tissue, further suggesting a potential interaction in vivo. Constitutive expression of MdTCP2, MdTCP4 and MdVOZ1 in Arabidopsis affected plant size, leaf morphology and the formation of leaf primordia on the adaxial side of cotyledons. On the other hand, chimeric MdTCP2, MdTCP4 and MdVOZ1 repressors that included the ethylene-responsive transcription factors (ERF)-associated amphiphilic repression (EAR) domain motif influenced reproduction and inflorescence architecture in transgenic Arabidopsis. These results suggest that MdFT1 and/or MdFT2 might be involved in the regulation of cellular proliferation and the formation of new tissues and that they might affect leaf and fruit development by interacting with TCP- and VOZ-family proteins. DDBJ accession nos. AB531019 (MdTCP2a mRNA), AB531020 (MdTCP2b mRNA), AB531021 (MdTCP4a mRNA), AB531022 (MdTCP4b mRNA) and AB531023 (MdVOZ1a mRNA). © The Author 2011. Published by Oxford University Press. All rights reserved.

  10. Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein⁻Protein Interaction Network.

    PubMed

    Cao, Buwen; Deng, Shuguang; Qin, Hua; Ding, Pingjian; Chen, Shaopeng; Li, Guanghui

    2018-06-15

    High-throughput technology has generated large-scale protein interaction data, which is crucial in our understanding of biological organisms. Many complex identification algorithms have been developed to determine protein complexes. However, these methods are only suitable for dense protein interaction networks, because their capabilities decrease rapidly when applied to sparse protein⁻protein interaction (PPI) networks. In this study, based on penalized matrix decomposition ( PMD ), a novel method of penalized matrix decomposition for the identification of protein complexes (i.e., PMD pc ) was developed to detect protein complexes in the human protein interaction network. This method mainly consists of three steps. First, the adjacent matrix of the protein interaction network is normalized. Second, the normalized matrix is decomposed into three factor matrices. The PMD pc method can detect protein complexes in sparse PPI networks by imposing appropriate constraints on factor matrices. Finally, the results of our method are compared with those of other methods in human PPI network. Experimental results show that our method can not only outperform classical algorithms, such as CFinder, ClusterONE, RRW, HC-PIN, and PCE-FR, but can also achieve an ideal overall performance in terms of a composite score consisting of F-measure, accuracy (ACC), and the maximum matching ratio (MMR).

  11. Interaction entropy for protein-protein binding.

    PubMed

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

    2017-03-28

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

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

    PubMed

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

    2011-06-01

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

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

    PubMed

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

    2016-12-01

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

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

    DTIC Science & Technology

    2011-01-01

    may partially explain why we did not observe any of the interactions between RNA polymerase II compo- nents in any of the Y2H set (11). Methodological...DNA. Fig. 5 shows that RNA syn- thesis complexes formed a highly interconnected cluster, in- cluding RNA polymerases I, II , and III, Transcription...factor complexes II F (TFIIF) and III C (TFIIIC), which were connected via direct protein-protein interactions with many other func- tional complexes. Fig

  15. Interaction between bacterial outer membrane proteins and periplasmic quality control factors: a kinetic partitioning mechanism.

    PubMed

    Wu, Si; Ge, Xi; Lv, Zhixin; Zhi, Zeyong; Chang, Zengyi; Zhao, Xin Sheng

    2011-09-15

    The OMPs (outer membrane proteins) of Gram-negative bacteria have to be translocated through the periplasmic space before reaching their final destination. The aqueous environment of the periplasmic space and high permeability of the outer membrane engender such a translocation process inevitably challenging. In Escherichia coli, although SurA, Skp and DegP have been identified to function in translocating OMPs across the periplasm, their precise roles and their relationship remain to be elucidated. In the present paper, by using fluorescence resonance energy transfer and single-molecule detection, we have studied the interaction between the OMP OmpC and these periplasmic quality control factors. The results of the present study reveal that the binding rate of OmpC to SurA or Skp is much faster than that to DegP, which may lead to sequential interaction between OMPs and different quality control factors. Such a kinetic partitioning mechanism for the chaperone-substrate interaction may be essential for the quality control of the biogenesis of OMPs.

  16. Recovering Protein-Protein and Domain-Domain Interactions from Aggregation of IP-MS Proteomics of Coregulator Complexes

    PubMed Central

    Mazloom, Amin R.; Dannenfelser, Ruth; Clark, Neil R.; Grigoryan, Arsen V.; Linder, Kathryn M.; Cardozo, Timothy J.; Bond, Julia C.; Boran, Aislyn D. W.; Iyengar, Ravi; Malovannaya, Anna; Lanz, Rainer B.; Ma'ayan, Avi

    2011-01-01

    Coregulator proteins (CoRegs) are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP) followed by mass spectrometry (MS) applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/. PMID:22219718

  17. Nuclear Export Factor CRM1 Interacts with Nonstructural Proteins NS2 from Parvovirus Minute Virus of Mice

    PubMed Central

    Bodendorf, Ursula; Cziepluch, Celina; Jauniaux, Jean-Claude; Rommelaere, Jean; Salomé, Nathalie

    1999-01-01

    The nonstructural NS2 proteins of autonomous parvoviruses are known to act in a host cell-dependent manner and to play a role in viral DNA replication, efficient translation of viral mRNA, and/or encapsidation. Their exact function during the parvovirus life cycle remains, however, still obscure. We report here the characterization of the interaction with the NS2 proteins from the parvovirus minute virus of mice (MVM) and rat as well as mouse homologues of the human CRM1 protein, a member of the importin-beta family recently identified as an essential nuclear export factor. Using the two-hybrid system, we could detect the interaction between the carboxy-terminal region of rat CRM1 and each of the three isoforms of NS2 (P [or major], Y [or minor], and L [or rare]). NS2 proteins were further shown to interact with the full-length CRM1 by coimmunoprecipitation experiments using extracts from both mouse and rat cell lines. Our data show that CRM1 preferentially binds to the nonphosphorylated isoforms of NS2. Moreover, we observed that the treatment of MVM-infected cells with leptomycin B, a drug that specifically inhibits the CRM1-dependent nuclear export pathway, leads to a drastic accumulation of NS2 proteins in the nucleus. Both NS2 interaction with CRM1 and nuclear accumulation upon leptomycin B treatment strongly suggest that these nonstructural viral proteins are actively exported out of the nuclei of infected cells via a CRM1-mediated nuclear export pathway. PMID:10438867

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

    PubMed Central

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

    2012-01-01

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

  19. Transforming properties of the Huntingtin interacting protein 1/ platelet-derived growth factor beta receptor fusion protein.

    PubMed

    Ross, T S; Gilliland, D G

    1999-08-06

    We have previously reported that the Huntingtin interacting protein 1 (HIP1) gene is fused to the platelet-derived growth factor beta receptor (PDGFbetaR) gene in a patient with chronic myelomonocytic leukemia. We now show that HIP1/PDGFbetaR oligomerizes, is constitutively tyrosine-phosphorylated, and transforms the murine hematopoietic cell line, Ba/F3, to interleukin-3-independent growth. A kinase-inactive mutant is neither tyrosine-phosphorylated nor able to transform Ba/F3 cells. Oligomerization and kinase activation required the 55-amino acid carboxyl-terminal TALIN homology region but not the leucine zipper domain. Tyrosine phosphorylation of a 130-kDa protein and STAT5 correlates with transformation in cells expressing HIP1/PDGFbetaR and related mutants. A deletion mutant fusion protein that contains only the TALIN homology region of HIP1 fused to PDGFbetaR is incapable of transforming Ba/F3 cells and does not tyrosine-phosphorylate p130 or STAT5, although it is itself constitutively tyrosine-phosphorylated. We have also analyzed cells expressing Tyr --> Phe mutants of HIP1/PDGFbetaR in the known PDGFbetaR SH2 docking sites and report that none of these sites are necessary for STAT5 activation, p130 phosphorylation, or Ba/F3 transformation. The correlation of factor-independent growth of hematopoietic cells with p130 and STAT5 phosphorylation/activation in both the HIP1/PDGFbetaR Tyr --> Phe and deletion mutational variants suggests that both STAT5 and p130 are important for transformation mediated by HIP1/PDGFbetaR.

  20. NOXclass: prediction of protein-protein interaction types.

    PubMed

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

    2006-01-19

    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. 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. 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 http://noxclass.bioinf.mpi-inf.mpg.de/.

  1. Characterization of host proteins interacting with the lymphocytic choriomeningitis virus L protein.

    PubMed

    Khamina, Kseniya; Lercher, Alexander; Caldera, Michael; Schliehe, Christopher; Vilagos, Bojan; Sahin, Mehmet; Kosack, Lindsay; Bhattacharya, Anannya; Májek, Peter; Stukalov, Alexey; Sacco, Roberto; James, Leo C; Pinschewer, Daniel D; Bennett, Keiryn L; Menche, Jörg; Bergthaler, Andreas

    2017-12-01

    RNA-dependent RNA polymerases (RdRps) play a key role in the life cycle of RNA viruses and impact their immunobiology. The arenavirus lymphocytic choriomeningitis virus (LCMV) strain Clone 13 provides a benchmark model for studying chronic infection. A major genetic determinant for its ability to persist maps to a single amino acid exchange in the viral L protein, which exhibits RdRp activity, yet its functional consequences remain elusive. To unravel the L protein interactions with the host proteome, we engineered infectious L protein-tagged LCMV virions by reverse genetics. A subsequent mass-spectrometric analysis of L protein pulldowns from infected human cells revealed a comprehensive network of interacting host proteins. The obtained LCMV L protein interactome was bioinformatically integrated with known host protein interactors of RdRps from other RNA viruses, emphasizing interconnected modules of human proteins. Functional characterization of selected interactors highlighted proviral (DDX3X) as well as antiviral (NKRF, TRIM21) host factors. To corroborate these findings, we infected Trim21-/- mice with LCMV and found impaired virus control in chronic infection. These results provide insights into the complex interactions of the arenavirus LCMV and other viral RdRps with the host proteome and contribute to a better molecular understanding of how chronic viruses interact with their host.

  2. Discovery and Development of Kelch-like ECH-Associated Protein 1. Nuclear Factor Erythroid 2-Related Factor 2 (KEAP1:NRF2) Protein-Protein Interaction Inhibitors: Achievements, Challenges, and Future Directions.

    PubMed

    Jiang, Zheng-Yu; Lu, Meng-Chen; You, Qi-Dong

    2016-12-22

    The transcription factor Nrf2 is the primary regulator of the cellular defense system, and enhancing Nrf2 activity has potential usages in various diseases, especially chronic age-related and inflammatory diseases. Recently, directly targeting Keap1-Nrf2 protein-protein interaction (PPI) has been an emerging strategy to selectively and effectively activate Nrf2. This Perspective summarizes the progress in the discovery and development of Keap1-Nrf2 PPI inhibitors, including the Keap1-Nrf2 regulatory mechanisms, biochemical techniques for inhibitor identification, and approaches for identifying peptide and small-molecule inhibitors, as well as discusses privileged structures and future directions for further development of Keap1-Nrf2 PPI inhibitors.

  3. Position Matters: Network Centrality Considerably Impacts Rates of Protein Evolution in the Human Protein-Protein Interaction Network.

    PubMed

    Alvarez-Ponce, David; Feyertag, Felix; Chakraborty, Sandip

    2017-06-01

    The proteins of any organism evolve at disparate rates. A long list of factors affecting rates of protein evolution have been identified. However, the relative importance of each factor in determining rates of protein evolution remains unresolved. The prevailing view is that evolutionary rates are dominantly determined by gene expression, and that other factors such as network centrality have only a marginal effect, if any. However, this view is largely based on analyses in yeasts, and accurately measuring the importance of the determinants of rates of protein evolution is complicated by the fact that the different factors are often correlated with each other, and by the relatively poor quality of available functional genomics data sets. Here, we use correlation, partial correlation and principal component regression analyses to measure the contributions of several factors to the variability of the rates of evolution of human proteins. For this purpose, we analyzed the entire human protein-protein interaction data set and the human signal transduction network-a network data set of exceptionally high quality, obtained by manual curation, which is expected to be virtually free from false positives. In contrast with the prevailing view, we observe that network centrality (measured as the number of physical and nonphysical interactions, betweenness, and closeness) has a considerable impact on rates of protein evolution. Surprisingly, the impact of centrality on rates of protein evolution seems to be comparable, or even superior according to some analyses, to that of gene expression. Our observations seem to be independent of potentially confounding factors and from the limitations (biases and errors) of interactomic data sets. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  4. 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.

  5. Mass spectrometric identification of proteins that interact through specific domains of the poly(A) binding protein

    PubMed Central

    Zhang, Chongxu; Nielsen, Maria E. O.; Chiang, Yueh-Chin; Kierkegaard, Morten; Wang, Xin; Lee, Darren J.; Andersen, Jens S.; Yao, Gang

    2013-01-01

    Poly(A) binding protein (PAB1) is involved in a number of RNA metabolic functions in eukaryotic cells and correspondingly is suggested to associate with a number of proteins. We have used mass spectrometric analysis to identify 55 non-ribosomal proteins that specifically interact with PAB1 from Saccharomyces cerevisiae. Because many of these factors may associate only indirectly with PAB1 by being components of the PAB1-mRNP structure, we additionally conducted mass spectrometric analyses on seven metabolically defined PAB1 deletion derivatives to delimit the interactions between these proteins and PAB1. These latter analyses identified 13 proteins whose associations with PAB1 were reduced by deleting one or another of PAB1’s defined domains. Included in this list of 13 proteins were the translation initiation factors eIF4G1 and eIF4G2, translation termination factor eRF3, and PBP2, all of whose previously known direct interactions with specific PAB1 domains were either confirmed, delimited, or extended. The remaining nine proteins that interacted through a specific PAB1 domain were CBF5, SLF1, UPF1, CBC1, SSD1, NOP77, yGR250c, NAB6, and GBP2. In further study, UPF1, involved in nonsense-mediated decay, was confirmed to interact with PAB1 through the RRM1 domain. We additionally established that while the RRM1 domain of PAB1 was required for UPF1-induced acceleration of deadenylation during nonsense-mediated decay, it was not required for the more critical step of acceleration of mRNA decapping. These results begin to identify the proteins most likely to interact with PAB1 and the domains of PAB1 through which these contacts are made. PMID:22836166

  6. Mass spectrometric identification of proteins that interact through specific domains of the poly(A) binding protein.

    PubMed

    Richardson, Roy; Denis, Clyde L; Zhang, Chongxu; Nielsen, Maria E O; Chiang, Yueh-Chin; Kierkegaard, Morten; Wang, Xin; Lee, Darren J; Andersen, Jens S; Yao, Gang

    2012-09-01

    Poly(A) binding protein (PAB1) is involved in a number of RNA metabolic functions in eukaryotic cells and correspondingly is suggested to associate with a number of proteins. We have used mass spectrometric analysis to identify 55 non-ribosomal proteins that specifically interact with PAB1 from Saccharomyces cerevisiae. Because many of these factors may associate only indirectly with PAB1 by being components of the PAB1-mRNP structure, we additionally conducted mass spectrometric analyses on seven metabolically defined PAB1 deletion derivatives to delimit the interactions between these proteins and PAB1. These latter analyses identified 13 proteins whose associations with PAB1 were reduced by deleting one or another of PAB1's defined domains. Included in this list of 13 proteins were the translation initiation factors eIF4G1 and eIF4G2, translation termination factor eRF3, and PBP2, all of whose previously known direct interactions with specific PAB1 domains were either confirmed, delimited, or extended. The remaining nine proteins that interacted through a specific PAB1 domain were CBF5, SLF1, UPF1, CBC1, SSD1, NOP77, yGR250c, NAB6, and GBP2. In further study, UPF1, involved in nonsense-mediated decay, was confirmed to interact with PAB1 through the RRM1 domain. We additionally established that while the RRM1 domain of PAB1 was required for UPF1-induced acceleration of deadenylation during nonsense-mediated decay, it was not required for the more critical step of acceleration of mRNA decapping. These results begin to identify the proteins most likely to interact with PAB1 and the domains of PAB1 through which these contacts are made.

  7. Flow Cytometric Analysis of Bimolecular Fluorescence Complementation: A High Throughput Quantitative Method to Study Protein-protein Interaction

    PubMed Central

    Wang, Li; Carnegie, Graeme K.

    2013-01-01

    Among methods to study protein-protein interaction inside cells, Bimolecular Fluorescence Complementation (BiFC) is relatively simple and sensitive. BiFC is based on the production of fluorescence using two non-fluorescent fragments of a fluorescent protein (Venus, a Yellow Fluorescent Protein variant, is used here). Non-fluorescent Venus fragments (VN and VC) are fused to two interacting proteins (in this case, AKAP-Lbc and PDE4D3), yielding fluorescence due to VN-AKAP-Lbc-VC-PDE4D3 interaction and the formation of a functional fluorescent protein inside cells. BiFC provides information on the subcellular localization of protein complexes and the strength of protein interactions based on fluorescence intensity. However, BiFC analysis using microscopy to quantify the strength of protein-protein interaction is time-consuming and somewhat subjective due to heterogeneity in protein expression and interaction. By coupling flow cytometric analysis with BiFC methodology, the fluorescent BiFC protein-protein interaction signal can be accurately measured for a large quantity of cells in a short time. Here, we demonstrate an application of this methodology to map regions in PDE4D3 that are required for the interaction with AKAP-Lbc. This high throughput methodology can be applied to screening factors that regulate protein-protein interaction. PMID:23979513

  8. Flow cytometric analysis of bimolecular fluorescence complementation: a high throughput quantitative method to study protein-protein interaction.

    PubMed

    Wang, Li; Carnegie, Graeme K

    2013-08-15

    Among methods to study protein-protein interaction inside cells, Bimolecular Fluorescence Complementation (BiFC) is relatively simple and sensitive. BiFC is based on the production of fluorescence using two non-fluorescent fragments of a fluorescent protein (Venus, a Yellow Fluorescent Protein variant, is used here). Non-fluorescent Venus fragments (VN and VC) are fused to two interacting proteins (in this case, AKAP-Lbc and PDE4D3), yielding fluorescence due to VN-AKAP-Lbc-VC-PDE4D3 interaction and the formation of a functional fluorescent protein inside cells. BiFC provides information on the subcellular localization of protein complexes and the strength of protein interactions based on fluorescence intensity. However, BiFC analysis using microscopy to quantify the strength of protein-protein interaction is time-consuming and somewhat subjective due to heterogeneity in protein expression and interaction. By coupling flow cytometric analysis with BiFC methodology, the fluorescent BiFC protein-protein interaction signal can be accurately measured for a large quantity of cells in a short time. Here, we demonstrate an application of this methodology to map regions in PDE4D3 that are required for the interaction with AKAP-Lbc. This high throughput methodology can be applied to screening factors that regulate protein-protein interaction.

  9. Cotton and Protein Interactions

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Goheen, Steven C.; Edwards, J. V.; Rayburn, Alfred R.

    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, itmore » 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.« less

  10. Prediction of physical protein protein interactions

    NASA Astrophysics Data System (ADS)

    Szilágyi, András; Grimm, Vera; Arakaki, Adrián K.; Skolnick, Jeffrey

    2005-06-01

    Many essential cellular processes such as signal transduction, transport, cellular motion and most regulatory mechanisms are mediated by protein-protein interactions. In recent years, new experimental techniques have been developed to discover the protein-protein interaction networks of several organisms. However, the accuracy and coverage of these techniques have proven to be limited, and computational approaches remain essential both to assist in the design and validation of experimental studies and for the prediction of interaction partners and detailed structures of protein complexes. Here, we provide a critical overview of existing structure-independent and structure-based computational methods. Although these techniques have significantly advanced in the past few years, we find that most of them are still in their infancy. We also provide an overview of experimental techniques for the detection of protein-protein interactions. Although the developments are promising, false positive and false negative results are common, and reliable detection is possible only by taking a consensus of different experimental approaches. The shortcomings of experimental techniques affect both the further development and the fair evaluation of computational prediction methods. For an adequate comparative evaluation of prediction and high-throughput experimental methods, an appropriately large benchmark set of biophysically characterized protein complexes would be needed, but is sorely lacking.

  11. Nck-2, a Novel Src Homology2/3-containing Adaptor Protein That Interacts with the LIM-only Protein PINCH and Components of Growth Factor Receptor Kinase-signaling Pathways

    PubMed Central

    Tu, Yizeng; Li, Fugang; Wu, Chuanyue

    1998-01-01

    Many of the protein–protein interactions that are essential for eukaryotic intracellular signal transduction are mediated by protein binding modules including SH2, SH3, and LIM domains. Nck is a SH3- and SH2-containing adaptor protein implicated in coordinating various signaling pathways, including those of growth factor receptors and cell adhesion receptors. We report here the identification, cloning, and characterization of a widely expressed, Nck-related adaptor protein termed Nck-2. Nck-2 comprises primarily three N-terminal SH3 domains and one C-terminal SH2 domain. We show that Nck-2 interacts with PINCH, a LIM-only protein implicated in integrin-linked kinase signaling. The PINCH-Nck-2 interaction is mediated by the fourth LIM domain of PINCH and the third SH3 domain of Nck-2. Furthermore, we show that Nck-2 is capable of recognizing several key components of growth factor receptor kinase-signaling pathways including EGF receptors, PDGF receptor-β, and IRS-1. The association of Nck-2 with EGF receptors was regulated by EGF stimulation and involved largely the SH2 domain of Nck-2, although the SH3 domains of Nck-2 also contributed to the complex formation. The association of Nck-2 with PDGF receptor-β was dependent on PDGF activation and was mediated solely by the SH2 domain of Nck-2. Additionally, we have detected a stable association between Nck-2 and IRS-1 that was mediated primarily via the second and third SH3 domain of Nck-2. Thus, Nck-2 associates with PINCH and components of different growth factor receptor-signaling pathways via distinct mechanisms. Finally, we provide evidence indicating that a fraction of the Nck-2 and/or Nck-1 proteins are associated with the cytoskeleton. These results identify a novel Nck-related SH2- and SH3-domain–containing protein and suggest that it may function as an adaptor protein connecting the growth factor receptor-signaling pathways with the integrin-signaling pathways. PMID:9843575

  12. Rigid-Docking Approaches to Explore Protein-Protein Interaction Space.

    PubMed

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

    Protein-protein interactions play core roles in living cells, especially in the regulatory systems. As information on proteins has rapidly accumulated on publicly available databases, much effort has been made to obtain a better picture of protein-protein interaction networks using protein tertiary structure data. Predicting relevant interacting partners from their tertiary structure is a challenging task and computer science methods have the potential to assist with this. Protein-protein rigid docking has been utilized by several projects, docking-based approaches having the advantages that they can suggest binding poses of predicted binding partners which would help in understanding the interaction mechanisms and that comparing docking results of both non-binders and binders can lead to understanding the specificity of protein-protein interactions from structural viewpoints. In this review we focus on explaining current computational prediction methods to predict pairwise direct protein-protein interactions that form protein complexes.

  13. 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

  14. The Myb-domain protein ULTRAPETALA1 INTERACTING FACTOR 1 controls floral meristem activities in Arabidopsis.

    PubMed

    Moreau, Fanny; Thévenon, Emmanuel; Blanvillain, Robert; Lopez-Vidriero, Irene; Franco-Zorrilla, Jose Manuel; Dumas, Renaud; Parcy, François; Morel, Patrice; Trehin, Christophe; Carles, Cristel C

    2016-04-01

    Higher plants continuously and iteratively produce new above-ground organs in the form of leaves, stems and flowers. These organs arise from shoot apical meristems whose homeostasis depends on coordination between self-renewal of stem cells and their differentiation into organ founder cells. This coordination is stringently controlled by the central transcription factor WUSCHEL (WUS), which is both necessary and sufficient for stem cell specification in Arabidopsis thaliana ULTRAPETALA1 (ULT1) was previously identified as a plant-specific, negative regulator of WUS expression. However, molecular mechanisms underlying this regulation remain unknown. ULT1 protein contains a SAND putative DNA-binding domain and a B-box, previously proposed as a protein interaction domain in eukaryotes. Here, we characterise a novel partner of ULT1, named ULT1 INTERACTING FACTOR 1 (UIF1), which contains a Myb domain and an EAR motif. UIF1 and ULT1 function in the same pathway for regulation of organ number in the flower. Moreover, UIF1 displays DNA-binding activity and specifically binds to WUS regulatory elements. We thus provide genetic and molecular evidence that UIF1 and ULT1 work together in floral meristem homeostasis, probably by direct repression of WUS expression. © 2016. Published by The Company of Biologists Ltd.

  15. Phosphorylation of Tat-interactive protein 60 kDa by protein kinase C epsilon is important for its subcellular localisation.

    PubMed

    Sapountzi, Vasileia; Logan, Ian R; Nelson, Glyn; Cook, Susan; Robson, Craig N

    2008-01-01

    Tat-interactive protein 60 kDa is a nuclear acetyltransferase that both coactivates and corepresses transcription factors and has a definitive function in the DNA damage response. Here, we provide evidence that Tat-interactive protein 60 kDa is phosphorylated by protein kinase C epsilon. In vitro, protein kinase C epsilon phosphorylates Tat-interactive protein 60 kDa on at least two sites within the acetyltransferase domain. In whole cells, activation of protein kinase C increases the levels of phosphorylated Tat-interactive protein 60 kDa and the interaction of Tat-interactive protein 60 kDa with protein kinase C epsilon. A phosphomimetic mutant Tat-interactive protein 60 kDa has distinct subcellular localisation compared to the wild-type protein in whole cells. Taken together, these findings suggest that the protein kinase C epsilon phosphorylation sites on Tat-interactive protein 60 kDa are important for its subcellular localisation. Regulation of the subcellular localisation of Tat-interactive protein 60 kDa via phosphorylation provides a novel means of controlling Tat-interactive protein 60 kDa function.

  16. Transient protein-protein interactions perturb E. coli metabolome and cause gene dosage toxicity

    PubMed Central

    Bhattacharyya, Sanchari; Bershtein, Shimon; Yan, Jin; Argun, Tijda; Gilson, Amy I; Trauger, Sunia A; Shakhnovich, Eugene I

    2016-01-01

    Gene dosage toxicity (GDT) is an important factor that determines optimal levels of protein abundances, yet its molecular underpinnings remain unknown. Here, we demonstrate that overexpression of DHFR in E. coli causes a toxic metabolic imbalance triggered by interactions with several functionally related enzymes. Though deleterious in the overexpression regime, surprisingly, these interactions are beneficial at physiological concentrations, implying their functional significance in vivo. Moreover, we found that overexpression of orthologous DHFR proteins had minimal effect on all levels of cellular organization – molecular, systems, and phenotypic, in sharp contrast to E. coli DHFR. Dramatic difference of GDT between ‘E. coli’s self’ and ‘foreign’ proteins suggests the crucial role of evolutionary selection in shaping protein-protein interaction (PPI) networks at the whole proteome level. This study shows how protein overexpression perturbs a dynamic metabolon of weak yet potentially functional PPI, with consequences for the metabolic state of cells and their fitness. DOI: http://dx.doi.org/10.7554/eLife.20309.001 PMID:27938662

  17. Exploiting Amino Acid Composition for Predicting Protein-Protein Interactions

    PubMed Central

    Roy, Sushmita; Martinez, Diego; Platero, Harriett; Lane, Terran; Werner-Washburne, Margaret

    2009-01-01

    Background Computational prediction of protein interactions typically use protein domains as classifier features because they capture conserved information of interaction surfaces. However, approaches relying on domains as features cannot be applied to proteins without any domain information. In this paper, we explore the contribution of pure amino acid composition (AAC) for protein interaction prediction. This simple feature, which is based on normalized counts of single or pairs of amino acids, is applicable to proteins from any sequenced organism and can be used to compensate for the lack of domain information. Results AAC performed at par with protein interaction prediction based on domains on three yeast protein interaction datasets. Similar behavior was obtained using different classifiers, indicating that our results are a function of features and not of classifiers. In addition to yeast datasets, AAC performed comparably on worm and fly datasets. Prediction of interactions for the entire yeast proteome identified a large number of novel interactions, the majority of which co-localized or participated in the same processes. Our high confidence interaction network included both well-studied and uncharacterized proteins. Proteins with known function were involved in actin assembly and cell budding. Uncharacterized proteins interacted with proteins involved in reproduction and cell budding, thus providing putative biological roles for the uncharacterized proteins. Conclusion AAC is a simple, yet powerful feature for predicting protein interactions, and can be used alone or in conjunction with protein domains to predict new and validate existing interactions. More importantly, AAC alone performs at par with existing, but more complex, features indicating the presence of sequence-level information that is predictive of interaction, but which is not necessarily restricted to domains. PMID:19936254

  18. DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network.

    PubMed

    Mistry, Divya; Wise, Roger P; Dickerson, Julie A

    2017-01-01

    Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures helped identify critical genes and proteins in biomolecular networks. The proposed centrality measure, DiffSLC, combines the number of interactions of a protein and the gene coexpression values of genes from which those proteins were translated, as a weighting factor to bias the identification of essential proteins in a protein interaction network. Potentially essential proteins with low node degree are promoted through eigenvector centrality. Thus, the gene coexpression values are used in conjunction with the eigenvector of the network's adjacency matrix and edge clustering coefficient to improve essentiality prediction. The outcome of this prediction is shown using three variations: (1) inclusion or exclusion of gene co-expression data, (2) impact of different coexpression measures, and (3) impact of different gene expression data sets. For a total of seven networks, DiffSLC is compared to other centrality measures using Saccharomyces cerevisiae protein interaction networks and gene expression data. Comparisons are also performed for the top ranked proteins against the known essential genes from the Saccharomyces Gene Deletion Project, which show that DiffSLC detects more essential proteins and has a higher area under the ROC curve than other compared methods. This makes DiffSLC a stronger alternative to other centrality methods for detecting essential genes using a protein-protein interaction network that obeys centrality-lethality principle. DiffSLC is implemented using the igraph package in R, and networkx package in Python. The python package can be

  19. batman Interacts with polycomb and trithorax group genes and encodes a BTB/POZ protein that is included in a complex containing GAGA factor.

    PubMed

    Faucheux, M; Roignant, J-Y; Netter, S; Charollais, J; Antoniewski, C; Théodore, L

    2003-02-01

    Polycomb and trithorax group genes maintain the appropriate repressed or activated state of homeotic gene expression throughout Drosophila melanogaster development. We have previously identified the batman gene as a Polycomb group candidate since its function is necessary for the repression of Sex combs reduced. However, our present genetic analysis indicates functions of batman in both activation and repression of homeotic genes. The 127-amino-acid Batman protein is almost reduced to a BTB/POZ domain, an evolutionary conserved protein-protein interaction domain found in a large protein family. We show that this domain is involved in the interaction between Batman and the DNA binding GAGA factor encoded by the Trithorax-like gene. The GAGA factor and Batman codistribute on polytene chromosomes, coimmunoprecipitate from nuclear embryonic and larval extracts, and interact in the yeast two-hybrid assay. Batman, together with the GAGA factor, binds to MHS-70, a 70-bp fragment of the bithoraxoid Polycomb response element. This binding, like that of the GAGA factor, requires the presence of d(GA)n sequences. Together, our results suggest that batman belongs to a subset of the Polycomb/trithorax group of genes that includes Trithorax-like, whose products are involved in both activation and repression of homeotic genes.

  20. batman Interacts with Polycomb and trithorax Group Genes and Encodes a BTB/POZ Protein That Is Included in a Complex Containing GAGA Factor

    PubMed Central

    Faucheux, M.; Roignant, J.-Y.; Netter, S.; Charollais, J.; Antoniewski, C.; Théodore, L.

    2003-01-01

    Polycomb and trithorax group genes maintain the appropriate repressed or activated state of homeotic gene expression throughout Drosophila melanogaster development. We have previously identified the batman gene as a Polycomb group candidate since its function is necessary for the repression of Sex combs reduced. However, our present genetic analysis indicates functions of batman in both activation and repression of homeotic genes. The 127-amino-acid Batman protein is almost reduced to a BTB/POZ domain, an evolutionary conserved protein-protein interaction domain found in a large protein family. We show that this domain is involved in the interaction between Batman and the DNA binding GAGA factor encoded by the Trithorax-like gene. The GAGA factor and Batman codistribute on polytene chromosomes, coimmunoprecipitate from nuclear embryonic and larval extracts, and interact in the yeast two-hybrid assay. Batman, together with the GAGA factor, binds to MHS-70, a 70-bp fragment of the bithoraxoid Polycomb response element. This binding, like that of the GAGA factor, requires the presence of d(GA)n sequences. Together, our results suggest that batman belongs to a subset of the Polycomb/trithorax group of genes that includes Trithorax-like, whose products are involved in both activation and repression of homeotic genes. PMID:12556479

  1. A Protein Preparation Method for the High-throughput Identification of Proteins Interacting with a Nuclear Cofactor Using LC-MS/MS Analysis.

    PubMed

    Tsuchiya, Megumi; Karim, M Rezaul; Matsumoto, Taro; Ogawa, Hidesato; Taniguchi, Hiroaki

    2017-01-24

    Transcriptional coregulators are vital to the efficient transcriptional regulation of nuclear chromatin structure. Coregulators play a variety of roles in regulating transcription. These include the direct interaction with transcription factors, the covalent modification of histones and other proteins, and the occasional chromatin conformation alteration. Accordingly, establishing relatively quick methods for identifying proteins that interact within this network is crucial to enhancing our understanding of the underlying regulatory mechanisms. LC-MS/MS-mediated protein binding partner identification is a validated technique used to analyze protein-protein interactions. By immunoprecipitating a previously-identified member of a protein complex with an antibody (occasionally with an antibody for a tagged protein), it is possible to identify its unknown protein interactions via mass spectrometry analysis. Here, we present a method of protein preparation for the LC-MS/MS-mediated high-throughput identification of protein interactions involving nuclear cofactors and their binding partners. This method allows for a better understanding of the transcriptional regulatory mechanisms of the targeted nuclear factors.

  2. Predicting protein-protein interactions from protein domains using a set cover approach.

    PubMed

    Huang, Chengbang; Morcos, Faruck; Kanaan, Simon P; Wuchty, Stefan; Chen, Danny Z; Izaguirre, Jesús A

    2007-01-01

    One goal of contemporary proteome research is the elucidation of cellular protein interactions. Based on currently available protein-protein interaction and domain data, we introduce a novel method, Maximum Specificity Set Cover (MSSC), for the prediction of protein-protein interactions. In our approach, we map the relationship between interactions of proteins and their corresponding domain architectures to a generalized weighted set cover problem. The application of a greedy algorithm provides sets of domain interactions which explain the presence of protein interactions to the largest degree of specificity. Utilizing domain and protein interaction data of S. cerevisiae, MSSC enables prediction of previously unknown protein interactions, links that are well supported by a high tendency of coexpression and functional homogeneity of the corresponding proteins. Focusing on concrete examples, we show that MSSC reliably predicts protein interactions in well-studied molecular systems, such as the 26S proteasome and RNA polymerase II of S. cerevisiae. We also show that the quality of the predictions is comparable to the Maximum Likelihood Estimation while MSSC is faster. This new algorithm and all data sets used are accessible through a Web portal at http://ppi.cse.nd.edu.

  3. An efficient way of studying protein-protein interactions involving HIF-α, c-Myc, and Sp1.

    PubMed

    To, Kenneth K-W; Huang, L Eric

    2013-01-01

    Protein-protein interaction is an essential biochemical event that mediates various cellular processes including gene expression, intracellular signaling, and intercellular interaction. Understanding such interaction is key to the elucidation of mechanisms of cellular processes in biology and diseases. The hypoxia-inducible transcription factor HIF-1α possesses a non-transcriptional activity that competes with c-Myc for Sp1 binding, whereas its isoform HIF-2α lacks Sp1-binding activity due to phosphorylation. Here, we describe the use of in vitro translation to effectively investigate the dynamics of protein-protein interactions among HIF-1α, c-Myc, and Sp1 and to demonstrate protein phosphorylation as a molecular determinant that functionally distinguishes HIF-2α from HIF-1α.

  4. 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.

  5. A cysteine-rich plant protein potentiates Potyvirus movement through an interaction with the virus genome-linked protein VPg.

    PubMed

    Dunoyer, P; Thomas, C; Harrison, S; Revers, F; Maule, A

    2004-03-01

    We have identified a cellular factor that interacts with the virus genome-linked proteins (VPgs) of a diverse range of potyviruses. The factor, called Potyvirus VPg-interacting protein (PVIP), is a plant-specific protein with homologues in all the species examined, i.e., pea, Arabidopsis thaliana, and Nicotiana benthamiana. The sequence of PVIP does not identify a specific function, although the existence of a "PHD finger" domain may implicate the protein in transcriptional control through chromatin remodeling. Deletion analysis using the yeast two-hybrid system showed that the determinants of the interaction lay close to the N terminus of VPg; indeed, the N-terminal 16 amino acids were shown to be both necessary and sufficient for the interaction with at least one PVIP protein. From a sequence comparison of different potyvirus VPg proteins, a specific amino acid at position 12 was directly implicated in the interaction. This part of VPg is distinct from regions associated with other functional roles of VPg. Through mutation of Turnip mosaic virus (TuMV) at VPg position 12, we showed that the interaction with PVIP affected systemic symptoms in infected plants. This resulted from reduced cell-to-cell and systemic movement more than reduced virus replication, as visualized by comparing green fluorescent protein-tagged wild-type and mutant viruses. Furthermore, by using RNA interference of PVIP in Arabidopsis, we showed that reduced expression of PVIP genes reduced susceptibility to TuMV infection. We conclude that PVIP functions as an ancillary factor to support potyvirus movement in plants.

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

    NASA Astrophysics Data System (ADS)

    Luchko, Tyler

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

  7. Quantifying protein-protein interactions in high throughput using protein domain microarrays.

    PubMed

    Kaushansky, Alexis; Allen, John E; Gordus, Andrew; Stiffler, Michael A; Karp, Ethan S; Chang, Bryan H; MacBeath, Gavin

    2010-04-01

    Protein microarrays provide an efficient way to identify and quantify protein-protein interactions in high throughput. One drawback of this technique is that proteins show a broad range of physicochemical properties and are often difficult to produce recombinantly. To circumvent these problems, we have focused on families of protein interaction domains. Here we provide protocols for constructing microarrays of protein interaction domains in individual wells of 96-well microtiter plates, and for quantifying domain-peptide interactions in high throughput using fluorescently labeled synthetic peptides. As specific examples, we will describe the construction of microarrays of virtually every human Src homology 2 (SH2) and phosphotyrosine binding (PTB) domain, as well as microarrays of mouse PDZ domains, all produced recombinantly in Escherichia coli. For domains that mediate high-affinity interactions, such as SH2 and PTB domains, equilibrium dissociation constants (K(D)s) for their peptide ligands can be measured directly on arrays by obtaining saturation binding curves. For weaker binding domains, such as PDZ domains, arrays are best used to identify candidate interactions, which are then retested and quantified by fluorescence polarization. Overall, protein domain microarrays provide the ability to rapidly identify and quantify protein-ligand interactions with minimal sample consumption. Because entire domain families can be interrogated simultaneously, they provide a powerful way to assess binding selectivity on a proteome-wide scale and provide an unbiased perspective on the connectivity of protein-protein interaction networks.

  8. Viscosity Analysis of Dual Variable Domain Immunoglobulin Protein Solutions: Role of Size, Electroviscous Effect and Protein-Protein Interactions.

    PubMed

    Raut, Ashlesha S; Kalonia, Devendra S

    2016-01-01

    Increased solution viscosity results in difficulties in manufacturing and delivery of therapeutic protein formulations, increasing both the time and production costs, and leading to patient inconvenience. The solution viscosity is affected by the molecular properties of both the solute and the solvent. The purpose of this work was to investigate the effect of size, charge and protein-protein interactions on the viscosity of Dual Variable Domain Immunoglobulin (DVD-Ig(TM)) protein solutions. The effect of size of the protein molecule on solution viscosity was investigated by measuring intrinsic viscosity and excluded volume calculations for monoclonal antibody (mAb) and DVD-Ig(TM) protein solutions. The role of the electrostatic charge resulting in electroviscous effects for DVD-Ig(TM) protein was assessed by measuring zeta potential. Light scattering measurements were performed to detect protein-protein interactions affecting solution viscosity. DVD-Ig(TM) protein exhibited significantly higher viscosity compared to mAb. Intrinsic viscosity and excluded volume calculations indicated that the size of the molecule affects viscosity significantly at higher concentrations, while the effect was minimal at intermediate concentrations. Electroviscous contribution to the viscosity of DVD-Ig(TM) protein varied depending on the presence or absence of ions in the solution. In buffered solutions, negative k D and B 2 values indicated the presence of attractive interactions which resulted in high viscosity for DVD-Ig(TM) protein at certain pH and ionic strength conditions. Results show that more than one factor contributes to the increased viscosity of DVD-Ig(TM) protein and interplay of these factors modulates the overall viscosity behavior of the solution, especially at higher concentrations.

  9. Integrated web visualizations for protein-protein interaction databases.

    PubMed

    Jeanquartier, Fleur; Jean-Quartier, Claire; Holzinger, Andreas

    2015-06-16

    Understanding living systems is crucial for curing diseases. To achieve this task we have to understand biological networks based on protein-protein interactions. Bioinformatics has come up with a great amount of databases and tools that support analysts in exploring protein-protein interactions on an integrated level for knowledge discovery. They provide predictions and correlations, indicate possibilities for future experimental research and fill the gaps to complete the picture of biochemical processes. There are numerous and huge databases of protein-protein interactions used to gain insights into answering some of the many questions of systems biology. Many computational resources integrate interaction data with additional information on molecular background. However, the vast number of diverse Bioinformatics resources poses an obstacle to the goal of understanding. We present a survey of databases that enable the visual analysis of protein networks. We selected M=10 out of N=53 resources supporting visualization, and we tested against the following set of criteria: interoperability, data integration, quantity of possible interactions, data visualization quality and data coverage. The study reveals differences in usability, visualization features and quality as well as the quantity of interactions. StringDB is the recommended first choice. CPDB presents a comprehensive dataset and IntAct lets the user change the network layout. A comprehensive comparison table is available via web. The supplementary table can be accessed on http://tinyurl.com/PPI-DB-Comparison-2015. Only some web resources featuring graph visualization can be successfully applied to interactive visual analysis of protein-protein interaction. Study results underline the necessity for further enhancements of visualization integration in biochemical analysis tools. Identified challenges are data comprehensiveness, confidence, interactive feature and visualization maturing.

  10. Xanthomonas filamentous hemagglutinin-like protein Fha1 interacts with pepper hypersensitive-induced reaction protein CaHIR1 and functions as a virulence factor in host plants.

    PubMed

    Choi, Hyong Woo; Kim, Dae Sung; Kim, Nak Hyun; Jung, Ho Won; Ham, Jong Hyun; Hwang, Byung Kook

    2013-12-01

    Pathogens have evolved a variety of virulence factors to infect host plants successfully. We previously identified the pepper plasma-membrane-resident hypersensitive-induced reaction protein (CaHIR1) as a regulator of plant disease- and immunity-associated cell death. Here, we identified the small filamentous hemagglutinin-like protein (Fha1) of Xanthomonas campestris pv. vesicatoria as an interacting partner of CaHIR1 using yeast two-hybrid screening. Coimmunoprecipitation and bimolecular fluorescence complementation experiments revealed that Fha1 specifically interacts with CaHIR1 in planta. The endocytic tracker FM4-64 staining showed that the CaHIR1-Fha1 complex localizes in the endocytic vesicle-like structure. The X. campestris pv. vesicatoria Δfha1 mutant strain exhibited significantly increased surface adherence but reduced swarming motility. Mutation of fha1 inhibited the growth of X. campestris pv. vesicatoria and X. campestris pv. vesicatoria ΔavrBsT in tomato and pepper leaves, respectively, suggesting that Fha1 acts as a virulence factor in host plants. Transient expression of fha1 and also infiltration with purified Fha1 proteins induced disease-associated cell death response through the interaction with CaHIR1 and suppressed the expression of pathogenesis-related (PR) genes. Silencing of CaHIR1 in pepper significantly reduced ΔavrBsT growth and Fha1-triggered susceptibility cell death. Overexpression of fha1 in Arabidopsis retarded plant growth and triggered disease-associated cell death, resulting in altered disease susceptibility. Taken together, these results suggest that the X. campestris pv. vesicatoria virulence factor Fha1 interacts with CaHIR1, induces susceptibility cell death, and suppresses PR gene expression in host plants.

  11. 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.

  12. Protein-protein interactions: an application of Tus-Ter mediated protein microarray system.

    PubMed

    Sitaraman, Kalavathy; Chatterjee, Deb K

    2011-01-01

    In this chapter, we present a novel, cost-effective microarray strategy that utilizes expression-ready plasmid DNAs to generate protein arrays on-demand and its use to validate protein-protein interactions. These expression plasmids were constructed in such a way so as to serve a dual purpose of synthesizing the protein of interest as well as capturing the synthesized protein. The microarray system is based on the high affinity binding of Escherichia coli "Tus" protein to "Ter," a 20 bp DNA sequence involved in the regulation of DNA replication. The protein expression is carried out in a cell-free protein synthesis system, with rabbit reticulocyte lysates, and the target proteins are detected either by labeled incorporated tag specific or by gene-specific antibodies. This microarray system has been successfully used for the detection of protein-protein interaction because both the target protein and the query protein can be transcribed and translated simultaneously in the microarray slides. The utility of this system for detecting protein-protein interaction is demonstrated by a few well-known examples: Jun/Fos, FRB/FKBP12, p53/MDM2, and CDK4/p16. In all these cases, the presence of protein complexes resulted in the localization of fluorophores at the specific sites of the immobilized target plasmids. Interestingly, during our interactions studies we also detected a previously unknown interaction between CDK2 and p16. Thus, this Tus-Ter based system of protein microarray can be used for the validation of known protein interactions as well as for identifying new protein-protein interactions. In addition, it can be used to examine and identify targets of nucleic acid-protein, ligand-receptor, enzyme-substrate, and drug-protein interactions.

  13. Topology and weights in a protein domain interaction network--a novel way to predict protein interactions.

    PubMed

    Wuchty, Stefan

    2006-05-23

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

  14. Molecular Modeling of Structures and Interaction of Human Corticotropin-Releasing Factor (CRF) Binding Protein and CRF Type-2 Receptor

    PubMed Central

    Slater, Paula G.; Gutierrez-Maldonado, Sebastian E.; Gysling, Katia; Lagos, Carlos F.

    2018-01-01

    The corticotropin-releasing factor (CRF) system is a key mediator of the stress response and addictive behavior. The CRF system includes four peptides: The CRF system includes four peptides: CRF, urocortins I–III, CRF binding protein (CRF-BP) that binds CRF with high affinity, and two class B G-protein coupled receptors CRF1R and CRF2R. CRF-BP is a secreted protein without significant sequence homology to CRF receptors or to any other known class of protein. Recently, it has been described a potentiation role of CRF-BP over CRF signaling through CRF2R in addictive-related neuronal plasticity and behavior. In addition, it has been described that CRF-BP is capable to physically interact specifically with the α isoform of CRF2R and acts like an escort protein increasing the amount of the receptor in the plasma membrane. At present, there are no available structures for CRF-BP or for full-length CRFR. Knowing and studying the structure of these proteins could be beneficial in order to characterize the CRF-BP/CRF2αR interaction. In this work, we report the modeling of CRF-BP and of full-length CRF2αR and CRF2βR based on the recently solved crystal structures of the transmembrane domains of the human glucagon receptor and human CRF1R, in addition with the resolved N-terminal extracellular domain of CRFRs. These models were further studied using molecular dynamics simulations and protein–protein docking. The results predicted a higher possibility of interaction of CRF-BP with CRF2αR than CRF2βR and yielded the possible residues conforming the interacting interface. Thus, the present study provides a framework for further investigation of the CRF-BP/CRF2αR interaction. PMID:29515519

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

    PubMed

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

    2018-03-06

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

  16. Computational prediction of host-pathogen protein-protein interactions.

    PubMed

    Dyer, Matthew D; Murali, T M; Sobral, Bruno W

    2007-07-01

    Infectious diseases such as malaria result in millions of deaths each year. An important aspect of any host-pathogen system is the mechanism by which a pathogen can infect its host. One method of infection is via protein-protein interactions (PPIs) where pathogen proteins target host proteins. Developing computational methods that identify which PPIs enable a pathogen to infect a host has great implications in identifying potential targets for therapeutics. We present a method that integrates known intra-species PPIs with protein-domain profiles to predict PPIs between host and pathogen proteins. Given a set of intra-species PPIs, we identify the functional domains in each of the interacting proteins. For every pair of functional domains, we use Bayesian statistics to assess the probability that two proteins with that pair of domains will interact. We apply our method to the Homo sapiens-Plasmodium falciparum host-pathogen system. Our system predicts 516 PPIs between proteins from these two organisms. We show that pairs of human proteins we predict to interact with the same Plasmodium protein are close to each other in the human PPI network and that Plasmodium pairs predicted to interact with same human protein are co-expressed in DNA microarray datasets measured during various stages of the Plasmodium life cycle. Finally, we identify functionally enriched sub-networks spanned by the predicted interactions and discuss the plausibility of our predictions. Supplementary data are available at http://staff.vbi.vt.edu/dyermd/publications/dyer2007a.html. Supplementary data are available at Bioinformatics online.

  17. The eukaryotic translation initiation factor 3 subunit L protein interacts with Flavivirus NS5 and may modulate yellow fever virus replication

    PubMed Central

    2013-01-01

    Background Yellow fever virus (YFV) belongs to the Flavivirus genus and causes an important disease. An alarming resurgence of viral circulation and the expansion of YFV-endemic zones have been detected in Africa and South America in recent years. NS5 is a viral protein that contains methyltransferase and RNA-dependent RNA polymerase (RdRp) domains, which are essential for viral replication, and the interactions between NS5 and cellular proteins have been studied to better understand viral replication. The aim of this study was to characterize the interaction of the NS5 protein with eukaryotic translation initiation factor 3 subunit L (eIF3L) and to evaluate the role of eIF3L in yellow fever replication. Methods To identify interactions of YFV NS5 with cellular proteins, we performed a two-hybrid screen using the YFV NS5 RdRp domain as bait with a human cDNA library, and RNApol deletion mutants were generated and analyzed using the two-hybrid system for mapping the interactions. The RNApol region involved was segmented into three fragments and analyzed using an eIF3L-expressing yeast strain. To map the NS5 residues that are critical for the interactions, we performed site-direct mutagenesis in segment 3 of the interaction domain (ID) and confirmed the interaction using in vitro assays and in vivo coimmunoprecipitation. The significance of eIF3L for YFV replication was investigated using eIF3L overexpression and RNA interference. Results In this work, we describe and characterize the interaction of NS5 with the translation factor eIF3L. The interaction between NS5 and eIF3L was confirmed using in vitro binding and in vivo coimmunoprecipitation assays. This interaction occurs at a region (the interaction domain of the RNApol domain) that is conserved in several flaviviruses and that is, therefore, likely to be relevant to the genus. eIF3L overexpression and plaque reduction assays showed a slight effect on YFV replication, indicating that the interaction of eIF3L

  18. The eukaryotic translation initiation factor 3 subunit L protein interacts with Flavivirus NS5 and may modulate yellow fever virus replication.

    PubMed

    Morais, Ana Ts; Terzian, Ana Cb; Duarte, Danilo Vb; Bronzoni, Roberta Vm; Madrid, Maria Cfs; Gavioli, Arieli F; Gil, Laura Hvg; Oliveira, Amanda G; Zanelli, Cleslei F; Valentini, Sandro R; Rahal, Paula; Nogueira, Mauricio L

    2013-06-22

    Yellow fever virus (YFV) belongs to the Flavivirus genus and causes an important disease. An alarming resurgence of viral circulation and the expansion of YFV-endemic zones have been detected in Africa and South America in recent years. NS5 is a viral protein that contains methyltransferase and RNA-dependent RNA polymerase (RdRp) domains, which are essential for viral replication, and the interactions between NS5 and cellular proteins have been studied to better understand viral replication. The aim of this study was to characterize the interaction of the NS5 protein with eukaryotic translation initiation factor 3 subunit L (eIF3L) and to evaluate the role of eIF3L in yellow fever replication. To identify interactions of YFV NS5 with cellular proteins, we performed a two-hybrid screen using the YFV NS5 RdRp domain as bait with a human cDNA library, and RNApol deletion mutants were generated and analyzed using the two-hybrid system for mapping the interactions. The RNApol region involved was segmented into three fragments and analyzed using an eIF3L-expressing yeast strain. To map the NS5 residues that are critical for the interactions, we performed site-direct mutagenesis in segment 3 of the interaction domain (ID) and confirmed the interaction using in vitro assays and in vivo coimmunoprecipitation. The significance of eIF3L for YFV replication was investigated using eIF3L overexpression and RNA interference. In this work, we describe and characterize the interaction of NS5 with the translation factor eIF3L. The interaction between NS5 and eIF3L was confirmed using in vitro binding and in vivo coimmunoprecipitation assays. This interaction occurs at a region (the interaction domain of the RNApol domain) that is conserved in several flaviviruses and that is, therefore, likely to be relevant to the genus. eIF3L overexpression and plaque reduction assays showed a slight effect on YFV replication, indicating that the interaction of eIF3L with YFV NS5 may play a role

  19. A protein interaction network analysis for yeast integral membrane protein.

    PubMed

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

    2008-01-01

    Although the yeast Saccharomyces cerevisiae is the best exemplified single-celled eukaryote, the vast number of protein-protein interactions of integral membrane proteins of Saccharomyces cerevisiae have not been characterized by experiments. Here, based on the kernel method of Greedy Kernel Principal Component analysis plus Linear Discriminant Analysis, we identify 300 protein-protein interactions involving 189 membrane proteins and get the outcome of a highly connected protein-protein interactions network. Furthermore, we study the global topological features of integral membrane proteins network of Saccharomyces cerevisiae. These results give the comprehensive description of protein-protein interactions of integral membrane proteins and reveal global topological and robustness of the interactome network at a system level. This work represents an important step towards a comprehensive understanding of yeast protein interactions.

  20. Modulating surface rheology by electrostatic protein/polysaccharide interactions.

    PubMed

    Ganzevles, Renate A; Zinoviadou, Kyriaki; van Vliet, Ton; Cohen, Martien A; de Jongh, Harmen H

    2006-11-21

    There is a large interest in mixed protein/polysaccharide layers at air-water and oil-water interfaces because of their ability to stabilize foams and emulsions. Mixed protein/polysaccharide adsorbed layers at air-water interfaces can be prepared either by adsorption of soluble protein/polysaccharide complexes or by sequential adsorption of complexes or polysaccharides to a previously formed protein layer. Even though the final protein and polysaccharide bulk concentrations are the same, the behavior of the adsorbed layers can be very different, depending on the method of preparation. The surface shear modulus of a sequentially formed beta-lactoglobulin/pectin layer can be up to a factor of 6 higher than that of a layer made by simultaneous adsorption. Furthermore, the surface dilatational modulus and surface shear modulus strongly (up to factors of 2 and 7, respectively) depend on the bulk -lactoglobulin/pectin mixing ratio. On the basis of the surface rheological behavior, a mechanistic understanding of how the structure of the adsorbed layers depends on the protein/polysaccharide interaction in bulk solution, mixing ratio, ionic strength, and order of adsorption to the interface (simultaneous or sequential) is derived. Insight into the effect of protein/polysaccharide interactions on the properties of adsorbed layers provides a solid basis to modulate surface rheological behavior.

  1. 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

  2. Interaction of AIM with insulin-like growth factor-binding protein-4.

    PubMed

    You, Qiang; Wu, Yan; Yao, Nannan; Shen, Guannan; Zhang, Ying; Xu, Liangguo; Li, Guiying; Ju, Cynthia

    2015-09-01

    Apoptosis inhibitor of macrophages (AIM/cluster of differentiation 5 antigen-like/soluble protein α) has been shown to inhibit cellular apoptosis; however, the underlying molecular mechanism has not been elucidated. Using yeast two‑hybrid screening, the present study uncovered that AIM binds to insulin‑like growth factor binding protein‑4 (IGFBP‑4). AIM interaction with IGFBP‑4, as well as IGFBP‑2 and ‑3, but not with IGFBP‑1, ‑5 and ‑6, was further confirmed by co‑immunoprecipitation (co‑IP) using 293 cells. The binding activity and affinity between AIM and IGFBP‑4 in vitro were analyzed by co‑IP and biolayer interferometry. Serum depletion‑induced cellular apoptosis was attenuated by insulin‑like growth factor‑I (IGF‑I), and this effect was abrogated by IGFBP‑4. Of note, in the presence of AIM, the inhibitory effect of IGFBP‑4 on the anti‑apoptosis function of IGF‑I was attenuated, possibly through binding of AIM with IGFBP‑4. In conclusion, to the best of our knowledge, the present study provides the first evidence that AIM binds to IGFBP‑2, ‑3 and ‑4. The data suggest that this interaction may contribute to the mechanism of AIM-mediated anti-apoptosis function.

  3. Regulation of myeloid leukemia factor-1 interacting protein (MLF1IP) expression in glioblastoma.

    PubMed

    Hanissian, Silva H; Teng, Bin; Akbar, Umar; Janjetovic, Zorica; Zhou, Qihong; Duntsch, Christopher; Robertson, Jon H

    2005-06-14

    The myelodysplasia/myeloid leukemia factor 1-interacting protein MLF1IP is a novel gene which encodes for a putative transcriptional repressor. It is localized to human chromosome 4q35.1 and is expressed in both the nuclei and cytoplasm of cells. Northern and Western blot analyses have revealed MLF1IP to be present at very low amounts in normal brain tissues, whereas a number of human and rat glioblastoma (GBM) cell lines demonstrated a high level expression of the MLF1IP protein. Immunohistochemical analysis of rat F98 and C6 GBM tumor models showed that MLF1IP was highly expressed in the tumor core where it was co-localized with MLF1 and nestin. Moreover, MLF1IP expression was elevated in the contralateral brain where no tumor cells were detected. These observations, together with previous data demonstrating a role for MLF1IP in erythroleukemias, suggest a possible function for this protein in glioma pathogenesis and potentially in other types of malignancies.

  4. 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

    the same time reversibility and diversity in their interactions. Interestingly, as is shown in the paper by Mészáros et al, even though some disordered regions and proteins have a tendency to fold upon binding, the structures of their complexes still reveal their inherent flexibility. Indeed, disordered proteins and their complexes have certain properties which distinguish them from proteins with well-defined structures. This is evident from the papers by Lobanov and Galzitskaya, and Mészáros et al, which show that such characteristic features of disordered proteins allow their successful computational prediction from the sequence alone. Computational prediction of protein disorder has been used in another study by Takeda et al where the authors investigate the role of disorder in the function of a specific actin capping protein. The paper presents normal mode analysis with the elastic network model to examine the mechanisms of intrinsic flexibility and its biological role in actin function. Analysis of the underlying mechanisms and key factors in protein recognition might be essential for the prediction of protein-protein interactions. The papers by Tuncbag et al and Hashimoto et al demonstrate how incorporating the physico-chemical properties of binding interfaces and their atomic details obtained from protein crystal structures might be used to increase the accuracy of predicted protein-protein interactions and provide data on relative orientations of interacting proteins and on the locations of binding sites. Moreover, analysis of protein-protein interactions might require further fine-tuning for different types of assemblies, like that shown in the example of homooligomers by Hashimoto et al. Studies of protein-protein interactions at the molecular level have contributed considerably to understanding the principles of large-scale organization of the cellular interactome. Using graph theory as a unifying language, many characteristic properties of bimolecular

  5. Mining Host-Pathogen Protein Interactions to Characterize Burkholderia mallei Infectivity Mechanisms

    PubMed Central

    Memišević, Vesna; Zavaljevski, Nela; Rajagopala, Seesandra V.; Kwon, Keehwan; Pieper, Rembert; DeShazer, David; Reifman, Jaques; Wallqvist, Anders

    2015-01-01

    Burkholderia pathogenicity relies on protein virulence factors to control and promote bacterial internalization, survival, and replication within eukaryotic host cells. We recently used yeast two-hybrid (Y2H) screening to identify a small set of novel Burkholderia proteins that were shown to attenuate disease progression in an aerosol infection animal model using the virulent Burkholderia mallei ATCC 23344 strain. Here, we performed an extended analysis of primarily nine B. mallei virulence factors and their interactions with human proteins to map out how the bacteria can influence and alter host processes and pathways. Specifically, we employed topological analyses to assess the connectivity patterns of targeted host proteins, identify modules of pathogen-interacting host proteins linked to processes promoting infectivity, and evaluate the effect of crosstalk among the identified host protein modules. Overall, our analysis showed that the targeted host proteins generally had a large number of interacting partners and interacted with other host proteins that were also targeted by B. mallei proteins. We also introduced a novel Host-Pathogen Interaction Alignment (HPIA) algorithm and used it to explore similarities between host-pathogen interactions of B. mallei, Yersinia pestis, and Salmonella enterica. We inferred putative roles of B. mallei proteins based on the roles of their aligned Y. pestis and S. enterica partners and showed that up to 73% of the predicted roles matched existing annotations. A key insight into Burkholderia pathogenicity derived from these analyses of Y2H host-pathogen interactions is the identification of eukaryotic-specific targeted cellular mechanisms, including the ubiquitination degradation system and the use of the focal adhesion pathway as a fulcrum for transmitting mechanical forces and regulatory signals. This provides the mechanisms to modulate and adapt the host-cell environment for the successful establishment of host infections

  6. Mining host-pathogen protein interactions to characterize Burkholderia mallei infectivity mechanisms.

    PubMed

    Memišević, Vesna; Zavaljevski, Nela; Rajagopala, Seesandra V; Kwon, Keehwan; Pieper, Rembert; DeShazer, David; Reifman, Jaques; Wallqvist, Anders

    2015-03-01

    Burkholderia pathogenicity relies on protein virulence factors to control and promote bacterial internalization, survival, and replication within eukaryotic host cells. We recently used yeast two-hybrid (Y2H) screening to identify a small set of novel Burkholderia proteins that were shown to attenuate disease progression in an aerosol infection animal model using the virulent Burkholderia mallei ATCC 23344 strain. Here, we performed an extended analysis of primarily nine B. mallei virulence factors and their interactions with human proteins to map out how the bacteria can influence and alter host processes and pathways. Specifically, we employed topological analyses to assess the connectivity patterns of targeted host proteins, identify modules of pathogen-interacting host proteins linked to processes promoting infectivity, and evaluate the effect of crosstalk among the identified host protein modules. Overall, our analysis showed that the targeted host proteins generally had a large number of interacting partners and interacted with other host proteins that were also targeted by B. mallei proteins. We also introduced a novel Host-Pathogen Interaction Alignment (HPIA) algorithm and used it to explore similarities between host-pathogen interactions of B. mallei, Yersinia pestis, and Salmonella enterica. We inferred putative roles of B. mallei proteins based on the roles of their aligned Y. pestis and S. enterica partners and showed that up to 73% of the predicted roles matched existing annotations. A key insight into Burkholderia pathogenicity derived from these analyses of Y2H host-pathogen interactions is the identification of eukaryotic-specific targeted cellular mechanisms, including the ubiquitination degradation system and the use of the focal adhesion pathway as a fulcrum for transmitting mechanical forces and regulatory signals. This provides the mechanisms to modulate and adapt the host-cell environment for the successful establishment of host infections

  7. Dynamic nuclear protein interactions investigated using fluorescence lifetime and fluorescence fluctuation spectroscopy

    NASA Astrophysics Data System (ADS)

    Siegel, Amanda P.; Hays, Nicole M.; Day, Richard N.

    2012-03-01

    The discovery and engineering of novel fluorescent proteins (FPs) from diverse organisms is yielding fluorophores with exceptional characteristics for live-cell imaging. In particular, the development of FPs for Förster resonance energy transfer (FRET) microscopy and fluorescence fluctuation spectroscopy (FFS) provide important tools for monitoring dynamic protein interactions inside living cells. Fluorescence lifetime imaging microscopy (FLIM) quantitatively maps changes in the spatial distribution of donor FP lifetimes that result from FRET with acceptor FPs. FFS probes dynamic protein associations through its capacity to monitor localized protein diffusion. Here, we use FRET-FLIM combined with FFS in living cells to investigate changes in protein mobility due to protein-protein interactions involving transcription factors and chromatin modifying proteins that function in anterior pituitary gene regulation. The heterochromatin protein 1 alpha (HP1α) plays a key role in the establishment and maintenance of heterochromatin through its interactions with histone methyltransferases. Recent studies, however, also highlight the importance of HP1α as a positive regulator of active transcription in euchromatin. Intriguingly, we observed that the transcription factor CCAAT/enhancer-binding protein alpha (C/EBPα) interacts with HP1α in regions of pericentromeric heterochromatin in mouse pituitary cells. These observations prompted us to investigate the relationship between HP1α dynamic interactions in pituitary specific gene regulation.

  8. Co-evolutionary Analysis of Domains in Interacting Proteins Reveals Insights into Domain–Domain Interactions Mediating Protein–Protein Interactions

    PubMed Central

    Jothi, Raja; Cherukuri, Praveen F.; Tasneem, Asba; Przytycka, Teresa M.

    2006-01-01

    Recent advances in functional genomics have helped generate large-scale high-throughput protein interaction data. Such networks, though extremely valuable towards molecular level understanding of cells, do not provide any direct information about the regions (domains) in the proteins that mediate the interaction. Here, we performed co-evolutionary analysis of domains in interacting proteins in order to understand the degree of co-evolution of interacting and non-interacting domains. Using a combination of sequence and structural analysis, we analyzed protein–protein interactions in F1-ATPase, Sec23p/Sec24p, DNA-directed RNA polymerase and nuclear pore complexes, and found that interacting domain pair(s) for a given interaction exhibits higher level of co-evolution than the noninteracting domain pairs. Motivated by this finding, we developed a computational method to test the generality of the observed trend, and to predict large-scale domain–domain interactions. Given a protein–protein interaction, the proposed method predicts the domain pair(s) that is most likely to mediate the protein interaction. We applied this method on the yeast interactome to predict domain–domain interactions, and used known domain–domain interactions found in PDB crystal structures to validate our predictions. Our results show that the prediction accuracy of the proposed method is statistically significant. Comparison of our prediction results with those from two other methods reveals that only a fraction of predictions are shared by all the three methods, indicating that the proposed method can detect known interactions missed by other methods. We believe that the proposed method can be used with other methods to help identify previously unrecognized domain–domain interactions on a genome scale, and could potentially help reduce the search space for identifying interaction sites. PMID:16949097

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

    PubMed

    Bengali, Aditya N; Tessier, Peter M

    2009-10-01

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

  10. Interaction of nanoparticles with proteins: relation to bio-reactivity of the nanoparticle.

    PubMed

    Saptarshi, Shruti R; Duschl, Albert; Lopata, Andreas L

    2013-07-19

    Interaction of nanoparticles with proteins is the basis of nanoparticle bio-reactivity. This interaction gives rise to the formation of a dynamic nanoparticle-protein corona. The protein corona may influence cellular uptake, inflammation, accumulation, degradation and clearance of the nanoparticles. Furthermore, the nanoparticle surface can induce conformational changes in adsorbed protein molecules which may affect the overall bio-reactivity of the nanoparticle. In depth understanding of such interactions can be directed towards generating bio-compatible nanomaterials with controlled surface characteristics in a biological environment. The main aim of this review is to summarise current knowledge on factors that influence nanoparticle-protein interactions and their implications on cellular uptake.

  11. A Discontinuous Potential Model for Protein-Protein Interactions.

    PubMed

    Shao, Qing; Hall, Carol K

    2016-01-01

    Protein-protein interactions play an important role in many biologic and industrial processes. In this work, we develop a two-bead-per-residue model that enables us to account for protein-protein interactions in a multi-protein system using discontinuous molecular dynamics simulations. This model deploys discontinuous potentials to describe the non-bonded interactions and virtual bonds to keep proteins in their native state. The geometric and energetic parameters are derived from the potentials of mean force between sidechain-sidechain, sidechain-backbone, and backbone-backbone pairs. The energetic parameters are scaled with the aim of matching the second virial coefficient of lysozyme reported in experiment. We also investigate the performance of several bond-building strategies.

  12. Assessment of the reliability of protein-protein interactions and protein function prediction.

    PubMed

    Deng, Minghua; Sun, Fengzhu; Chen, Ting

    2003-01-01

    As more and more high-throughput protein-protein interaction data are collected, the task of estimating the reliability of different data sets becomes increasingly important. In this paper, we present our study of two groups of protein-protein interaction data, the physical interaction data and the protein complex data, and estimate the reliability of these data sets using three different measurements: (1) the distribution of gene expression correlation coefficients, (2) the reliability based on gene expression correlation coefficients, and (3) the accuracy of protein function predictions. We develop a maximum likelihood method to estimate the reliability of protein interaction data sets according to the distribution of correlation coefficients of gene expression profiles of putative interacting protein pairs. The results of the three measurements are consistent with each other. The MIPS protein complex data have the highest mean gene expression correlation coefficients (0.256) and the highest accuracy in predicting protein functions (70% sensitivity and specificity), while Ito's Yeast two-hybrid data have the lowest mean (0.041) and the lowest accuracy (15% sensitivity and specificity). Uetz's data are more reliable than Ito's data in all three measurements, and the TAP protein complex data are more reliable than the HMS-PCI data in all three measurements as well. The complex data sets generally perform better in function predictions than do the physical interaction data sets. Proteins in complexes are shown to be more highly correlated in gene expression. The results confirm that the components of a protein complex can be assigned to functions that the complex carries out within a cell. There are three interaction data sets different from the above two groups: the genetic interaction data, the in-silico data and the syn-express data. Their capability of predicting protein functions generally falls between that of the Y2H data and that of the MIPS protein complex

  13. Coevolution study of mitochondria respiratory chain proteins: toward the understanding of protein--protein interaction.

    PubMed

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

    2011-05-20

    Coevolution can be seen as the interdependency between evolutionary histories. In the context of protein evolution, functional correlation proteins are ever-present coordinated evolutionary characters without disruption of organismal integrity. As to complex system, there are two forms of protein--protein interactions in vivo, which refer to inter-complex interaction and intra-complex interaction. In this paper, we studied the difference of coevolution characters between inter-complex interaction and intra-complex interaction using "Mirror tree" method on the respiratory chain (RC) proteins. We divided the correlation coefficients of every pairwise RC proteins into two groups corresponding to the binary protein--protein interaction in intra-complex and the binary protein--protein interaction in inter-complex, respectively. A dramatical discrepancy is detected between the coevolution characters of the two sets of protein interactions (Wilcoxon test, p-value = 4.4 × 10(-6)). Our finding reveals some critical information on coevolutionary study and assists the mechanical investigation of protein--protein interaction. Furthermore, the results also provide some unique clue for supramolecular organization of protein complexes in the mitochondrial inner membrane. More detailed binding sites map and genome information of nuclear encoded RC proteins will be extraordinary valuable for the further mitochondria dynamics study. Copyright © 2011. Published by Elsevier Ltd.

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

    PubMed

    Garner, Amanda L; Janda, Kim D

    2011-01-01

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

  15. Dynamic Fluctuations of Protein-Carbohydrate Interactions Promote Protein Aggregation

    PubMed Central

    Voynov, Vladimir; Chennamsetty, Naresh; Kayser, Veysel; Helk, Bernhard; Forrer, Kurt; Zhang, Heidi; Fritsch, Cornelius; Heine, Holger; Trout, Bernhardt L.

    2009-01-01

    Protein-carbohydrate interactions are important for glycoprotein structure and function. Antibodies of the IgG class, with increasing significance as therapeutics, are glycosylated at a conserved site in the constant Fc region. We hypothesized that disruption of protein-carbohydrate interactions in the glycosylated domain of antibodies leads to the exposure of aggregation-prone motifs. Aggregation is one of the main problems in protein-based therapeutics because of immunogenicity concerns and decreased efficacy. To explore the significance of intramolecular interactions between aromatic amino acids and carbohydrates in the IgG glycosylated domain, we utilized computer simulations, fluorescence analysis, and site-directed mutagenesis. We find that the surface exposure of one aromatic amino acid increases due to dynamic fluctuations. Moreover, protein-carbohydrate interactions decrease upon stress, while protein-protein and carbohydrate-carbohydrate interactions increase. Substitution of the carbohydrate-interacting aromatic amino acids with non-aromatic residues leads to a significantly lower stability than wild type, and to compromised binding to Fc receptors. Our results support a mechanism for antibody aggregation via decreased protein-carbohydrate interactions, leading to the exposure of aggregation-prone regions, and to aggregation. PMID:20037630

  16. An AT-hook protein DEPRESSED PALEA1 physically interacts with the TCP Family transcription factor RETARDED PALEA1 in rice.

    PubMed

    Yin, Dedong; Liu, Xue; Shi, Zhenying; Li, Dayong; Zhu, Lihuang

    2018-01-01

    The cereal crops (such as rice and maize) which belong to the grass family, are the most important grain crops for human beings, and the development of their flower and inflorescence architecture has attracted extensive attention. Although multiple genes involved in the regulation of floral and inflorescence organogenesis have been identified, the underlying molecular mechanisms are largely unknown. Previously, we identified rice depressed palea1 (dp1) mutants with defects in main structure of palea and its enhancer RETARDED PALEA1 (REP1). DP1 is an AT-hook protein while REP1 is a TCP transcription factor, both of which are important regulators of palea development. However, the relationship of these two proteins has not been elucidated yet. Here, we demonstrated that DP1 interacts physically with REP1 both in yeast and in rice protoplasts. Considering the close phylogenetic relationship between maize and rice, we further hypothesize that their orthologs in maize, BARREN STALK FASTIGIATE (BAF1) and BRANCH ANGLE DEFECTIVE 1 (BAD1), may interact physically. Subsequently, we verified their physical interaction, indicating that the interaction between AT-hook proteins and TCP proteins is conserved in rice and maize. Our findings may reveal a novel molecular mechanism of floral and inflorescence development in grasses. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Enhancer of rudimentary homologue interacts with scaffold attachment factor B at the nuclear matrix to regulate SR protein phosphorylation.

    PubMed

    Drakouli, Sotiria; Lyberopoulou, Aggeliki; Papathanassiou, Maria; Mylonis, Ilias; Georgatsou, Eleni

    2017-08-01

    Scaffold attachment factor B1 (SAFB1) is an integral component of the nuclear matrix of vertebrate cells. It binds to DNA on scaffold/matrix attachment region elements, as well as to RNA and a multitude of different proteins, affecting basic cellular activities such as transcription, splicing and DNA damage repair. In the present study, we show that enhancer of rudimentary homologue (ERH) is a new molecular partner of SAFB1 and its 70% homologous paralogue, scaffold attachment factor B2 (SAFB2). ERH interacts directly in the nucleus with the C-terminal Arg-Gly-rich region of SAFB1/2 and co-localizes with it in the insoluble nuclear fraction. ERH, a small ubiquitous protein with striking homology among species and a unique structure, has also been implicated in fundamental cellular mechanisms. Our functional analyses suggest that the SAFB/ERH interaction does not affect SAFB1/2 function in transcription (e.g. as oestrogen receptor α co-repressors), although it reverses the inhibition exerted by SAFB1/2 on the splicing kinase SR protein kinase 1 (SRPK1), which also binds on the C-terminus of SAFB1/2. Accordingly, ERH silencing decreases lamin B receptor and SR protein phosphorylation, which are major SRPK1 substrates, further substantiating the role of SAFB1 and SAFB2 in the co-ordination of nuclear function. © 2017 Federation of European Biochemical Societies.

  18. Quality control methodology for high-throughput protein-protein interaction screening.

    PubMed

    Vazquez, Alexei; Rual, Jean-François; Venkatesan, Kavitha

    2011-01-01

    Protein-protein interactions are key to many aspects of the cell, including its cytoskeletal structure, the signaling processes in which it is involved, or its metabolism. Failure to form protein complexes or signaling cascades may sometimes translate into pathologic conditions such as cancer or neurodegenerative diseases. The set of all protein interactions between the proteins encoded by an organism constitutes its protein interaction network, representing a scaffold for biological function. Knowing the protein interaction network of an organism, combined with other sources of biological information, can unravel fundamental biological circuits and may help better understand the molecular basics of human diseases. The protein interaction network of an organism can be mapped by combining data obtained from both low-throughput screens, i.e., "one gene at a time" experiments and high-throughput screens, i.e., screens designed to interrogate large sets of proteins at once. In either case, quality controls are required to deal with the inherent imperfect nature of experimental assays. In this chapter, we discuss experimental and statistical methodologies to quantify error rates in high-throughput protein-protein interactions screens.

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

    PubMed

    Rosell, Mireia; Fernández-Recio, Juan

    2018-04-01

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

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

    PubMed

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

    2015-03-01

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

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

    PubMed Central

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

    2011-01-01

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

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

    PubMed Central

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

    2013-01-01

    Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on the thermodynamic principles of preferential interaction theory and the quantitative characterization of local protein solvation from molecular dynamics simulations. We find that changes of preferential solvent interactions at the protein-protein interface quantitatively account for the opposite effects of glycerol on the antibody-antigen association constants. Detailed characterization of local protein solvation in the free and associated protein states reveals how opposite solvent effects on protein-protein interactions depend on the extent of dewetting of the protein-protein contact region and on structural changes that alter cooperative solvent-protein interactions at the periphery of the protein-protein interface. These results demonstrate the direct relationship between macroscopic solvent effects on protein-protein interactions and atom-scale solvent-protein interactions, and establish a general methodology for predicting and understanding solvent effects on protein-protein interactions in diverse biological environments. PMID:23696727

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

    PubMed

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

    2013-01-01

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

  4. Intracellular Localization and Cellular Factors Interaction of HTLV-1 and HTLV-2 Tax Proteins: Similarities and Functional Differences

    PubMed Central

    Bertazzoni, Umberto; Turci, Marco; Avesani, Francesca; Di Gennaro, Gianfranco; Bidoia, Carlo; Romanelli, Maria Grazia

    2011-01-01

    Human T-lymphotropic viruses type 1 (HTLV-1) and type 2 (HTLV-2) present very similar genomic structures but HTLV-1 is more pathogenic than HTLV-2. Is this difference due to their transactivating Tax proteins, Tax-1 and Tax-2, which are responsible for viral and cellular gene activation? Do Tax-1 and Tax-2 differ in their cellular localization and in their interaction pattern with cellular factors? In this review, we summarize Tax-1 and Tax-2 structural and phenotypic properties, their interaction with factors involved in signal transduction and their localization-related behavior within the cell. Special attention will be given to the distinctions between Tax-1 and Tax-2 that likely play an important role in their transactivation activity. PMID:21994745

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

    NASA Astrophysics Data System (ADS)

    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.

  6. Predicting Physical Interactions between Protein Complexes*

    PubMed Central

    Clancy, Trevor; Rødland, Einar Andreas; Nygard, Ståle; Hovig, Eivind

    2013-01-01

    Protein complexes enact most biochemical functions in the cell. Dynamic interactions between protein complexes are frequent in many cellular processes. As they are often of a transient nature, they may be difficult to detect using current genome-wide screens. Here, we describe a method to computationally predict physical interactions between protein complexes, applied to both humans and yeast. We integrated manually curated protein complexes and physical protein interaction networks, and we designed a statistical method to identify pairs of protein complexes where the number of protein interactions between a complex pair is due to an actual physical interaction between the complexes. An evaluation against manually curated physical complex-complex interactions in yeast revealed that 50% of these interactions could be predicted in this manner. A community network analysis of the highest scoring pairs revealed a biologically sensible organization of physical complex-complex interactions in the cell. Such analyses of proteomes may serve as a guide to the discovery of novel functional cellular relationships. PMID:23438732

  7. Influence of Protein Abundance on High-Throughput Protein-Protein Interaction Detection

    DTIC Science & Technology

    2009-06-05

    the interaction data sets we determined, via comparisons with strict randomized simulations , the propensity for essential proteins to selectively...and analysis of high- quality PPI data sets. Materials and Methods We analyzed protein interaction networks for yeast and E. coli determined from Y2H...we reinvestigated the centrality-lethality rule, which implies that proteins having more interactions are more likely to be essential. From analysis

  8. 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

  9. Cooperative DNA Recognition Modulated by an Interplay between Protein-Protein Interactions and DNA-Mediated Allostery

    PubMed Central

    Merino, Felipe; Bouvier, Benjamin; Cojocaru, Vlad

    2015-01-01

    Highly specific transcriptional regulation depends on the cooperative association of transcription factors into enhanceosomes. Usually, their DNA-binding cooperativity originates from either direct interactions or DNA-mediated allostery. Here, we performed unbiased molecular simulations followed by simulations of protein-DNA unbinding and free energy profiling to study the cooperative DNA recognition by OCT4 and SOX2, key components of enhanceosomes in pluripotent cells. We found that SOX2 influences the orientation and dynamics of the DNA-bound configuration of OCT4. In addition SOX2 modifies the unbinding free energy profiles of both DNA-binding domains of OCT4, the POU specific and POU homeodomain, despite interacting directly only with the first. Thus, we demonstrate that the OCT4-SOX2 cooperativity is modulated by an interplay between protein-protein interactions and DNA-mediated allostery. Further, we estimated the change in OCT4-DNA binding free energy due to the cooperativity with SOX2, observed a good agreement with experimental measurements, and found that SOX2 affects the relative DNA-binding strength of the two OCT4 domains. Based on these findings, we propose that available interaction partners in different biological contexts modulate the DNA exploration routes of multi-domain transcription factors such as OCT4. We consider the OCT4-SOX2 cooperativity as a paradigm of how specificity of transcriptional regulation is achieved through concerted modulation of protein-DNA recognition by different types of interactions. PMID:26067358

  10. Cooperative DNA Recognition Modulated by an Interplay between Protein-Protein Interactions and DNA-Mediated Allostery.

    PubMed

    Merino, Felipe; Bouvier, Benjamin; Cojocaru, Vlad

    2015-06-01

    Highly specific transcriptional regulation depends on the cooperative association of transcription factors into enhanceosomes. Usually, their DNA-binding cooperativity originates from either direct interactions or DNA-mediated allostery. Here, we performed unbiased molecular simulations followed by simulations of protein-DNA unbinding and free energy profiling to study the cooperative DNA recognition by OCT4 and SOX2, key components of enhanceosomes in pluripotent cells. We found that SOX2 influences the orientation and dynamics of the DNA-bound configuration of OCT4. In addition SOX2 modifies the unbinding free energy profiles of both DNA-binding domains of OCT4, the POU specific and POU homeodomain, despite interacting directly only with the first. Thus, we demonstrate that the OCT4-SOX2 cooperativity is modulated by an interplay between protein-protein interactions and DNA-mediated allostery. Further, we estimated the change in OCT4-DNA binding free energy due to the cooperativity with SOX2, observed a good agreement with experimental measurements, and found that SOX2 affects the relative DNA-binding strength of the two OCT4 domains. Based on these findings, we propose that available interaction partners in different biological contexts modulate the DNA exploration routes of multi-domain transcription factors such as OCT4. We consider the OCT4-SOX2 cooperativity as a paradigm of how specificity of transcriptional regulation is achieved through concerted modulation of protein-DNA recognition by different types of interactions.

  11. [Detection of protein-protein interactions by FRET and BRET methods].

    PubMed

    Matoulková, E; Vojtěšek, B

    2014-01-01

    Nowadays, in vivo protein-protein interaction studies have become preferable detecting meth-ods that enable to show or specify (already known) protein interactions and discover their inhibitors. They also facilitate detection of protein conformational changes and discovery or specification of signaling pathways in living cells. One group of in vivo methods enabling these findings is based on fluorescent resonance energy transfer (FRET) and its bio-luminescent modification (BRET). They are based on visualization of protein-protein interactions via light or enzymatic excitation of fluorescent or bio-luminescent proteins. These methods allow not only protein localization within the cell or its organelles (or small animals) but they also allow us to quantify fluorescent signals and to discover weak or strong interaction partners. In this review, we explain the principles of FRET and BRET, their applications in the characterization of protein-protein interactions and we describe several findings using these two methods that clarify molecular and cellular mechanisms and signals related to cancer biology.

  12. The Citrus transcription factor, CitERF13, regulates citric acid accumulation via a protein-protein interaction with the vacuolar proton pump, CitVHA-c4

    PubMed Central

    Li, Shao-jia; Yin, Xue-ren; Xie, Xiu-lan; Allan, Andrew C.; Ge, Hang; Shen, Shu-ling; Chen, Kun-song

    2016-01-01

    Organic acids are essential to fruit flavor. The vacuolar H+ transporting adenosine triphosphatase (V-ATPase) plays an important role in organic acid transport and accumulation. However, less is known of V-ATPase interacting proteins and their relationship with organic acid accumulation. The relationship between V-ATPase and citric acid was investigated, using the citrus tangerine varieties ‘Ordinary Ponkan (OPK)’ and an early maturing mutant ‘Zaoshu Ponkan (ZPK)’. Five V-ATPase genes (CitVHA) were predicted as important to citric acid accumulation. Among the genes, CitVHA-c4 was observed, using a yeast two-hybrid screen, to interact at the protein level with an ethylene response factor, CitERF13. This was verified using bimolecular fluorescence complementation assays. A similar interaction was also observed between Arabidopsis AtERF017 (a CitERF13 homolog) and AtVHA-c4 (a CitVHA-c4 homolog). A synergistic effect on citric acid levels was observed between V-ATPase proteins and interacting ERFs when analyzed using transient over-expression in tobacco and Arabidopsis mutants. Furthermore, the transcript abundance of CitERF13 was concomitant with CitVHA-c4. CitERF13 or AtERF017 over-expression leads to significant citric acid accumulation. This accumulation was abolished in an AtVHA-c4 mutant background. ERF-VHA interactions appear to be involved in citric acid accumulation, which was observed in both citrus and Arabidopsis. PMID:26837571

  13. The Citrus transcription factor, CitERF13, regulates citric acid accumulation via a protein-protein interaction with the vacuolar proton pump, CitVHA-c4.

    PubMed

    Li, Shao-jia; Yin, Xue-ren; Xie, Xiu-lan; Allan, Andrew C; Ge, Hang; Shen, Shu-ling; Chen, Kun-song

    2016-02-03

    Organic acids are essential to fruit flavor. The vacuolar H(+) transporting adenosine triphosphatase (V-ATPase) plays an important role in organic acid transport and accumulation. However, less is known of V-ATPase interacting proteins and their relationship with organic acid accumulation. The relationship between V-ATPase and citric acid was investigated, using the citrus tangerine varieties 'Ordinary Ponkan (OPK)' and an early maturing mutant 'Zaoshu Ponkan (ZPK)'. Five V-ATPase genes (CitVHA) were predicted as important to citric acid accumulation. Among the genes, CitVHA-c4 was observed, using a yeast two-hybrid screen, to interact at the protein level with an ethylene response factor, CitERF13. This was verified using bimolecular fluorescence complementation assays. A similar interaction was also observed between Arabidopsis AtERF017 (a CitERF13 homolog) and AtVHA-c4 (a CitVHA-c4 homolog). A synergistic effect on citric acid levels was observed between V-ATPase proteins and interacting ERFs when analyzed using transient over-expression in tobacco and Arabidopsis mutants. Furthermore, the transcript abundance of CitERF13 was concomitant with CitVHA-c4. CitERF13 or AtERF017 over-expression leads to significant citric acid accumulation. This accumulation was abolished in an AtVHA-c4 mutant background. ERF-VHA interactions appear to be involved in citric acid accumulation, which was observed in both citrus and Arabidopsis.

  14. 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. Copyright © 2012 Elsevier Ltd. All rights reserved.

  15. 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.

  16. 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

  17. An Interaction with Ewing's Sarcoma Breakpoint Protein EWS Defines a Specific Oncogenic Mechanism of ETS Factors Rearranged in Prostate Cancer.

    PubMed

    Kedage, Vivekananda; Selvaraj, Nagarathinam; Nicholas, Taylor R; Budka, Justin A; Plotnik, Joshua P; Jerde, Travis J; Hollenhorst, Peter C

    2016-10-25

    More than 50% of prostate tumors have a chromosomal rearrangement resulting in aberrant expression of an oncogenic ETS family transcription factor. However, mechanisms that differentiate the function of oncogenic ETS factors expressed in prostate tumors from non-oncogenic ETS factors expressed in normal prostate are unknown. Here, we find that four oncogenic ETS (ERG, ETV1, ETV4, and ETV5), and no other ETS, interact with the Ewing's sarcoma breakpoint protein, EWS. This EWS interaction was necessary and sufficient for oncogenic ETS functions including gene activation, cell migration, clonogenic survival, and transformation. Significantly, the EWS interacting region of ERG has no homology with that of ETV1, ETV4, and ETV5. Therefore, this finding may explain how divergent ETS factors have a common oncogenic function. Strikingly, EWS is fused to various ETS factors by the chromosome translocations that cause Ewing's sarcoma. Therefore, these findings link oncogenic ETS function in both prostate cancer and Ewing's sarcoma. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

  18. In silico prediction of protein-protein interactions in human macrophages

    PubMed Central

    2014-01-01

    Background Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. Results We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. Conclusion Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level. PMID:24636261

  19. Prediction of the Ebola Virus Infection Related Human Genes Using Protein-Protein Interaction Network.

    PubMed

    Cao, HuanHuan; Zhang, YuHang; Zhao, Jia; Zhu, Liucun; Wang, Yi; Li, JiaRui; Feng, Yuan-Ming; Zhang, Ning

    2017-01-01

    Ebola hemorrhagic fever (EHF) is caused by Ebola virus (EBOV). It is reported that human could be infected by EBOV with a high fatality rate. However, association factors between EBOV and host still tend to be ambiguous. According to the "guilt by association" (GBA) principle, proteins interacting with each other are very likely to function similarly or the same. Based on this assumption, we tried to obtain EBOV infection-related human genes in a protein-protein interaction network using Dijkstra algorithm. We hope it could contribute to the discovery of novel effective treatments. Finally, 15 genes were selected as potential EBOV infection-related human genes. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  20. Detection of protein-protein interactions by ribosome display and protein in situ immobilisation.

    PubMed

    He, Mingyue; Liu, Hong; Turner, Martin; Taussig, Michael J

    2009-12-31

    We describe a method for identification of protein-protein interactions by combining two cell-free protein technologies, namely ribosome display and protein in situ immobilisation. The method requires only PCR fragments as the starting material, the target proteins being made through cell-free protein synthesis, either associated with their encoding mRNA as ribosome complexes or immobilised on a solid surface. The use of ribosome complexes allows identification of interacting protein partners from their attached coding mRNA. To demonstrate the procedures, we have employed the lymphocyte signalling proteins Vav1 and Grb2 and confirmed the interaction between Grb2 and the N-terminal SH3 domain of Vav1. The method has promise for library screening of pairwise protein interactions, down to the analytical level of individual domain or motif mapping.

  1. Position Matters: Network Centrality Considerably Impacts Rates of Protein Evolution in the Human Protein–Protein Interaction Network

    PubMed Central

    Feyertag, Felix; Chakraborty, Sandip

    2017-01-01

    Abstract The proteins of any organism evolve at disparate rates. A long list of factors affecting rates of protein evolution have been identified. However, the relative importance of each factor in determining rates of protein evolution remains unresolved. The prevailing view is that evolutionary rates are dominantly determined by gene expression, and that other factors such as network centrality have only a marginal effect, if any. However, this view is largely based on analyses in yeasts, and accurately measuring the importance of the determinants of rates of protein evolution is complicated by the fact that the different factors are often correlated with each other, and by the relatively poor quality of available functional genomics data sets. Here, we use correlation, partial correlation and principal component regression analyses to measure the contributions of several factors to the variability of the rates of evolution of human proteins. For this purpose, we analyzed the entire human protein–protein interaction data set and the human signal transduction network—a network data set of exceptionally high quality, obtained by manual curation, which is expected to be virtually free from false positives. In contrast with the prevailing view, we observe that network centrality (measured as the number of physical and nonphysical interactions, betweenness, and closeness) has a considerable impact on rates of protein evolution. Surprisingly, the impact of centrality on rates of protein evolution seems to be comparable, or even superior according to some analyses, to that of gene expression. Our observations seem to be independent of potentially confounding factors and from the limitations (biases and errors) of interactomic data sets. PMID:28854629

  2. Understanding the mechanisms of protein-DNA interactions

    NASA Astrophysics Data System (ADS)

    Lavery, Richard

    2004-03-01

    Structural, biochemical and thermodynamic data on protein-DNA interactions show that specific recognition cannot be reduced to a simple set of binary interactions between the partners (such as hydrogen bonds, ion pairs or steric contacts). The mechanical properties of the partners also play a role and, in the case of DNA, variations in both conformation and flexibility as a function of base sequence can be a significant factor in guiding a protein to the correct binding site. All-atom molecular modeling offers a means of analyzing the role of different binding mechanisms within protein-DNA complexes of known structure. This however requires estimating the binding strengths for the full range of sequences with which a given protein can interact. Since this number grows exponentially with the length of the binding site it is necessary to find a method to accelerate the calculations. We have achieved this by using a multi-copy approach (ADAPT) which allows us to build a DNA fragment with a variable base sequence. The results obtained with this method correlate well with experimental consensus binding sequences. They enable us to show that indirect recognition mechanisms involving the sequence dependent properties of DNA play a significant role in many complexes. This approach also offers a means of predicting protein binding sites on the basis of binding energies, which is complementary to conventional lexical techniques.

  3. Evolutionary diversification of protein-protein interactions by interface add-ons.

    PubMed

    Plach, Maximilian G; Semmelmann, Florian; Busch, Florian; Busch, Markus; Heizinger, Leonhard; Wysocki, Vicki H; Merkl, Rainer; Sterner, Reinhard

    2017-10-03

    Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein-protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein-protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein-protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein-protein interactions.

  4. Polyamines: naturally occurring small molecule modulators of electrostatic protein-protein interactions.

    PubMed

    Berwanger, Anja; Eyrisch, Susanne; Schuster, Inge; Helms, Volkhard; Bernhardt, Rita

    2010-02-01

    Modulations of protein-protein interactions are a key step in regulating protein function, especially in networks. Modulators of these interactions are supposed to be candidates for the development of novel drugs. Here, we describe the role of the small, polycationic and highly abundant natural polyamines that could efficiently bind to charged spots at protein interfaces as modulators of such protein-protein interactions. Using the mitochondrial cytochrome P45011A1 (CYP11A1) electron transfer system as a model, we have analyzed the capability of putrescine, spermidine, and spermine at physiologically relevant concentrations to affect the protein-protein interactions between adrenodoxin reductase (AdR), adrenodoxin (Adx), and CYP11A1. The actions of polyamines on the individual components, on their association/dissociation, on electron transfer, and on substrate conversion were examined. These studies revealed modulating effects of polyamines on distinct interactions and on the entire system in a complex way. Modulation via changed protein-protein interactions appeared plausible from docking experiments that suggested favourable high-affinity binding sites of polyamines (spermine>spermidine>putrescine) at the AdR-Adx interface. Our findings imply for the first time that small endogenous compounds are capable of interfering with distinct components of transient protein complexes and might control protein functions by modulating electrostatic protein-protein interactions.

  5. Visualization of RNA–protein interactions in living cells: FMRP and IMP1 interact on mRNAs

    PubMed Central

    Rackham, Oliver; Brown, Chris M

    2004-01-01

    Protein expression depends significantly on the stability, translation efficiency and localization of mRNA. These qualities are largely dictated by the RNA-binding proteins associated with an mRNA. Here, we report a method to visualize and localize RNA–protein interactions in living mammalian cells. Using this method, we found that the fragile X mental retardation protein (FMRP) isoform 18 and the human zipcode-binding protein 1 ortholog IMP1, an RNA transport factor, were present on common mRNAs. These interactions occurred predominantly in the cytoplasm, in granular structures. In addition, FMRP and IMP1 interacted independently of RNA. Tethering of FMRP to an mRNA caused IMP1 to be recruited to the same mRNA and resulted in granule formation. The intimate association of FMRP and IMP1 suggests a link between mRNA transport and translational repression in mammalian cells. PMID:15282548

  6. Direct interaction of SRY-related protein SOX9 and steroidogenic factor 1 regulates transcription of the human anti-Müllerian hormone gene.

    PubMed

    De Santa Barbara, P; Bonneaud, N; Boizet, B; Desclozeaux, M; Moniot, B; Sudbeck, P; Scherer, G; Poulat, F; Berta, P

    1998-11-01

    For proper male sexual differentiation, anti-Müllerian hormone (AMH) must be tightly regulated during embryonic development to promote regression of the Müllerian duct. However, the molecular mechanisms specifying the onset of AMH in male mammals are not yet clearly defined. A DNA-binding element for the steroidogenic factor 1 (SF-1), a member of the orphan nuclear receptor family, located in the AMH proximal promoter has recently been characterized and demonstrated as being essential for AMH gene activation. However, the requirement for a specific promoter environment for SF-1 activation as well as the presence of conserved cis DNA-binding elements in the AMH promoter suggest that SF-1 is a member of a combinatorial protein-protein and protein-DNA complex. In this study, we demonstrate that the canonical SOX-binding site within the human AMH proximal promoter can bind the transcription factor SOX9, a Sertoli cell factor closely associated with Sertoli cell differentiation and AMH expression. Transfection studies with COS-7 cells revealed that SOX9 can cooperate with SF-1 in this activation process. In vitro and in vivo protein-binding studies indicate that SOX9 and SF-1 interact directly via the SOX9 DNA-binding domain and the SF-1 C-terminal region, respectively. We propose that the two transcription factors SOX9 and SF-1 could both be involved in the expression of the AMH gene, in part as a result of their respective binding to the AMH promoter and in part because of their ability to interact with each other. Our work thus identifies SOX9 as an interaction partner of SF-1 that could be involved in the Sertoli cell-specific expression of AMH during embryogenesis.

  7. Direct Interaction of SRY-Related Protein SOX9 and Steroidogenic Factor 1 Regulates Transcription of the Human Anti-Müllerian Hormone Gene

    PubMed Central

    De Santa Barbara, Pascal; Bonneaud, Nathalie; Boizet, Brigitte; Desclozeaux, Marion; Moniot, Brigitte; Sudbeck, Peter; Scherer, Gerd; Poulat, Francis; Berta, Philippe

    1998-01-01

    For proper male sexual differentiation, anti-Müllerian hormone (AMH) must be tightly regulated during embryonic development to promote regression of the Müllerian duct. However, the molecular mechanisms specifying the onset of AMH in male mammals are not yet clearly defined. A DNA-binding element for the steroidogenic factor 1 (SF-1), a member of the orphan nuclear receptor family, located in the AMH proximal promoter has recently been characterized and demonstrated as being essential for AMH gene activation. However, the requirement for a specific promoter environment for SF-1 activation as well as the presence of conserved cis DNA-binding elements in the AMH promoter suggest that SF-1 is a member of a combinatorial protein-protein and protein-DNA complex. In this study, we demonstrate that the canonical SOX-binding site within the human AMH proximal promoter can bind the transcription factor SOX9, a Sertoli cell factor closely associated with Sertoli cell differentiation and AMH expression. Transfection studies with COS-7 cells revealed that SOX9 can cooperate with SF-1 in this activation process. In vitro and in vivo protein-binding studies indicate that SOX9 and SF-1 interact directly via the SOX9 DNA-binding domain and the SF-1 C-terminal region, respectively. We propose that the two transcription factors SOX9 and SF-1 could both be involved in the expression of the AMH gene, in part as a result of their respective binding to the AMH promoter and in part because of their ability to interact with each other. Our work thus identifies SOX9 as an interaction partner of SF-1 that could be involved in the Sertoli cell-specific expression of AMH during embryogenesis. PMID:9774680

  8. Druggable orthosteric and allosteric hot spots to target protein-protein interactions.

    PubMed

    Ma, Buyong; Nussinov, Ruth

    2014-01-01

    Drug designing targeting protein-protein interactions is challenging. Because structural elucidation and computational analysis have revealed the importance of hot spot residues in stabilizing these interactions, there have been on-going efforts to develop drugs which bind the hot spots and out-compete the native protein partners. The question arises as to what are the key 'druggable' properties of hot spots in protein-protein interactions and whether these mimic the general hot spot definition. Identification of orthosteric (at the protein- protein interaction site) and allosteric (elsewhere) druggable hot spots is expected to help in discovering compounds that can more effectively modulate protein-protein interactions. For example, are there any other significant features beyond their location in pockets in the interface? The interactions of protein-protein hot spots are coupled with conformational dynamics of protein complexes. Currently increasing efforts focus on the allosteric drug discovery. Allosteric drugs bind away from the native binding site and can modulate the native interactions. We propose that identification of allosteric hot spots could similarly help in more effective allosteric drug discovery. While detection of allosteric hot spots is challenging, targeting drugs to these residues has the potential of greatly increasing the hot spot and protein druggability.

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

    PubMed

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

    2016-02-15

    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. 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 protein interaction

  10. Mining protein-protein interaction networks: denoising effects

    NASA Astrophysics Data System (ADS)

    Marras, Elisabetta; Capobianco, Enrico

    2009-01-01

    A typical instrument to pursue analysis in complex network studies is the analysis of the statistical distributions. They are usually computed for measures which characterize network topology, and are aimed at capturing both structural and dynamics aspects. Protein-protein interaction networks (PPIN) have also been studied through several measures. It is in general observed that a power law is expected to characterize scale-free networks. However, mixing the original noise cover with outlying information and other system-dependent fluctuations makes the empirical detection of the power law a difficult task. As a result the uncertainty level increases when looking at the observed sample; in particular, one may wonder whether the computed features may be sufficient to explain the interactome. We then address noise problems by implementing both decomposition and denoising techniques that reduce the impact of factors known to affect the accuracy of power law detection.

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

    PubMed Central

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

    2011-01-01

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

  12. Identification of Modules in Protein-Protein Interaction Networks

    NASA Astrophysics Data System (ADS)

    Erten, Sinan; Koyutürk, Mehmet

    In biological systems, most processes are carried out through orchestration of multiple interacting molecules. These interactions are often abstracted using network models. A key feature of cellular networks is their modularity, which contributes significantly to the robustness, as well as adaptability of biological systems. Therefore, modularization of cellular networks is likely to be useful in obtaining insights into the working principles of cellular systems, as well as building tractable models of cellular organization and dynamics. A common, high-throughput source of data on molecular interactions is in the form of physical interactions between proteins, which are organized into protein-protein interaction (PPI) networks. This chapter provides an overview on identification and analysis of functional modules in PPI networks, which has been an active area of research in the last decade.

  13. Revealing protein functions based on relationships of interacting proteins and GO terms.

    PubMed

    Teng, Zhixia; Guo, Maozu; Liu, Xiaoyan; Tian, Zhen; Che, Kai

    2017-09-20

    In recent years, numerous computational methods predicted protein function based on the protein-protein interaction (PPI) network. These methods supposed that two proteins share the same function if they interact with each other. However, it is reported by recent studies that the functions of two interacting proteins may be just related. It will mislead the prediction of protein function. Therefore, there is a need for investigating the functional relationship between interacting proteins. In this paper, the functional relationship between interacting proteins is studied and a novel method, called as GoDIN, is advanced to annotate functions of interacting proteins in Gene Ontology (GO) context. It is assumed that the functional difference between interacting proteins can be expressed by semantic difference between GO term and its relatives. Thus, the method uses GO term and its relatives to annotate the interacting proteins separately according to their functional roles in the PPI network. The method is validated by a series of experiments and compared with the concerned method. The experimental results confirm the assumption and suggest that GoDIN is effective on predicting functions of protein. This study demonstrates that: (1) interacting proteins are not equal in the PPI network, and their function may be same or similar, or just related; (2) functional difference between interacting proteins can be measured by their degrees in the PPI network; (3) functional relationship between interacting proteins can be expressed by relationship between GO term and its relatives.

  14. Structural principles within the human-virus protein-protein interaction network

    PubMed Central

    Franzosa, Eric A.; Xia, Yu

    2011-01-01

    General properties of the antagonistic biomolecular interactions between viruses and their hosts (exogenous interactions) remain poorly understood, and may differ significantly from known principles governing the cooperative interactions within the host (endogenous interactions). Systems biology approaches have been applied to study the combined interaction networks of virus and human proteins, but such efforts have so far revealed only low-resolution patterns of host-virus interaction. Here, we layer curated and predicted 3D structural models of human-virus and human-human protein complexes on top of traditional interaction networks to reconstruct the human-virus structural interaction network. This approach reveals atomic resolution, mechanistic patterns of host-virus interaction, and facilitates systematic comparison with the host’s endogenous interactions. We find that exogenous interfaces tend to overlap with and mimic endogenous interfaces, thereby competing with endogenous binding partners. The endogenous interfaces mimicked by viral proteins tend to participate in multiple endogenous interactions which are transient and regulatory in nature. While interface overlap in the endogenous network results largely from gene duplication followed by divergent evolution, viral proteins frequently achieve interface mimicry without any sequence or structural similarity to an endogenous binding partner. Finally, while endogenous interfaces tend to evolve more slowly than the rest of the protein surface, exogenous interfaces—including many sites of endogenous-exogenous overlap—tend to evolve faster, consistent with an evolutionary “arms race” between host and pathogen. These significant biophysical, functional, and evolutionary differences between host-pathogen and within-host protein-protein interactions highlight the distinct consequences of antagonism versus cooperation in biological networks. PMID:21680884

  15. Towards Inferring Protein Interactions: Challenges and Solutions

    NASA Astrophysics Data System (ADS)

    Zhang, Ya; Zha, Hongyuan; Chu, Chao-Hsien; Ji, Xiang

    2006-12-01

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

  16. 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

  17. 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

  18. Protein conformational modifications and kinetics of water-protein interactions in milk protein concentrate powder upon aging: effect on solubility.

    PubMed

    Haque, Enamul; Bhandari, Bhesh R; Gidley, Michael J; Deeth, Hilton C; Møller, Sandie M; Whittaker, Andrew K

    2010-07-14

    Protein conformational modifications and water-protein interactions are two major factors believed to induce instability of protein and eventually affect the solubility of milk protein concentrate (MPC) powder. To test these hypotheses, MPC was stored at different water activities (a(w) 0.0-0.85) and temperatures (25 and 45 degrees C) for up to 12 weeks. Samples were examined periodically to determine solubility, change in protein conformation by Fourier transform infrared (FTIR) spectroscopy and principal component analysis (PCA), and water status (interaction of water with the protein molecule/surface) by measuring the transverse relaxation time (T(2)) with proton nuclear magnetic resonance ((1)H NMR). The solubility of MPC decreased significantly with aging, and this process was enhanced by increasing water activity (a(w)) and storage temperature. Minor changes in protein secondary structure were observed with FTIR, which indicated some degree of unfolding of protein molecules. PCA of the FTIR data was able to discriminate samples according to moisture content and storage period. Partial least-squares (PLS) analysis showed some correlation between FTIR spectral feature and solubility. The NMR T(2) results indicated the presence of three distinct populations of water molecules, and the proton signal intensity and T(2) values of proton fractions varied with storage conditions (humidity, temperature) and aging. Results suggest that protein/protein interactions may be initiated by unfolding of protein molecules that eventually affects solubility.

  19. The antituberculosis antibiotic capreomycin inhibits protein synthesis by disrupting interaction between ribosomal proteins L12 and L10.

    PubMed

    Lin, Yuan; Li, Yan; Zhu, Ningyu; Han, Yanxing; Jiang, Wei; Wang, Yanchang; Si, Shuyi; Jiang, Jiandong

    2014-01-01

    Capreomycin is a second-line drug for multiple-drug-resistant tuberculosis (TB). However, with increased use in clinics, the therapeutic efficiency of capreomycin is decreasing. To better understand TB resistance to capreomycin, we have done research to identify the molecular target of capreomycin. Mycobacterium tuberculosis ribosomal proteins L12 and L10 interact with each other and constitute the stalk of the 50S ribosomal subunit, which recruits initiation and elongation factors during translation. Hence, the L12-L10 interaction is considered to be essential for ribosomal function and protein synthesis. Here we provide evidence showing that capreomycin inhibits the L12-L10 interaction by using an established L12-L10 interaction assay. Overexpression of L12 and/or L10 in M. smegmatis, a species close to M. tuberculosis, increases the MIC of capreomycin. Moreover, both elongation factor G-dependent GTPase activity and ribosome-mediated protein synthesis are inhibited by capreomycin. When protein synthesis was blocked with thiostrepton, however, the bactericidal activity of capreomycin was restrained. All of these results suggest that capreomycin seems to inhibit TB by interrupting the L12-L10 interaction. This finding might provide novel clues for anti-TB drug discovery.

  20. Mapping the Complement Factor H-Related Protein 1 (CFHR1):C3b/C3d Interactions

    PubMed Central

    Laskowski, Jennifer; Thurman, Joshua M.; Hageman, Gregory S.; Holers, V. Michael

    2016-01-01

    Complement factor H-related protein 1 (CFHR1) is a complement regulator which has been reported to regulate complement by blocking C5 convertase activity and interfering with C5b surface association. CFHR1 also competes with complement factor H (CFH) for binding to C3b, and may act as an antagonist of CFH-directed regulation on cell surfaces. We have employed site-directed mutagenesis in conjunction with ELISA-based and functional assays to isolate the binding interaction that CFHR1 undertakes with complement components C3b and C3d to a single shared interface. The C3b/C3d:CFHR1 interface is identical to that which occurs between the two C-terminal domains (SCR19-20) of CFH and C3b. Moreover, we have been able to corroborate that dimerization of CFHR1 is necessary for this molecule to bind effectively to C3b and C3d, or compete with CFH. Finally, we have established that CFHR1 competes with complement factor H-like protein 1 (CFHL-1) for binding to C3b. CFHL-1 is a CFH gene splice variant, which is almost identical to the N-terminal 7 domains of CFH (SCR1-7). CFHR1, therefore, not only competes with the C-terminus of CFH for binding to C3b, but also sterically blocks the interaction that the N-terminus of CFH undertakes with C3b, and which is required for CFH-regulation. PMID:27814381

  1. Nuclear Protein Sam68 Interacts with the Enterovirus 71 Internal Ribosome Entry Site and Positively Regulates Viral Protein Translation.

    PubMed

    Zhang, Hua; Song, Lei; Cong, Haolong; Tien, Po

    2015-10-01

    Enterovirus 71 (EV71) recruits various cellular factors to assist in the replication and translation of its genome. Identification of the host factors involved in the EV71 life cycle not only will enable a better understanding of the infection mechanism but also has the potential to be of use in the development of antiviral therapeutics. In this study, we demonstrated that the cellular factor 68-kDa Src-associated protein in mitosis (Sam68) acts as an internal ribosome entry site (IRES) trans-acting factor (ITAF) that binds specifically to the EV71 5' untranslated region (5'UTR). Interaction sites in both the viral IRES (stem-loops IV and V) and the heterogeneous nuclear ribonucleoprotein K homology (KH) domain of Sam68 protein were further mapped using an electrophoretic mobility shift assay (EMSA) and biotin RNA pulldown assay. More importantly, dual-luciferase (firefly) reporter analysis suggested that overexpression of Sam68 positively regulated IRES-dependent translation of virus proteins. In contrast, both IRES activity and viral protein translation significantly decreased in Sam68 knockdown cells compared with the negative-control cells treated with short hairpin RNA (shRNA). However, downregulation of Sam68 did not have a significant inhibitory effect on the accumulation of the EV71 genome. Moreover, Sam68 was redistributed from the nucleus to the cytoplasm and interacts with cellular factors, such as poly(rC)-binding protein 2 (PCBP2) and poly(A)-binding protein (PABP), during EV71 infection. The cytoplasmic relocalization of Sam68 in EV71-infected cells may be involved in the enhancement of EV71 IRES-mediated translation. Since Sam68 is known to be a RNA-binding protein, these results provide direct evidence that Sam68 is a novel ITAF that interacts with EV71 IRES and positively regulates viral protein translation. The nuclear protein Sam68 is found as an additional new host factor that interacts with the EV71 IRES during infection and could potentially

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

    PubMed Central

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

    2014-01-01

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

  3. Norovirus translation requires an interaction between the C Terminus of the genome-linked viral protein VPg and eukaryotic translation initiation factor 4G.

    PubMed

    Chung, Liliane; Bailey, Dalan; Leen, Eoin N; Emmott, Edward P; Chaudhry, Yasmin; Roberts, Lisa O; Curry, Stephen; Locker, Nicolas; Goodfellow, Ian G

    2014-08-01

    Viruses have evolved a variety of mechanisms to usurp the host cell translation machinery to enable translation of the viral genome in the presence of high levels of cellular mRNAs. Noroviruses, a major cause of gastroenteritis in man, have evolved a mechanism that relies on the interaction of translation initiation factors with the virus-encoded VPg protein covalently linked to the 5' end of the viral RNA. To further characterize this novel mechanism of translation initiation, we have used proteomics to identify the components of the norovirus translation initiation factor complex. This approach revealed that VPg binds directly to the eIF4F complex, with a high affinity interaction occurring between VPg and eIF4G. Mutational analyses indicated that the C-terminal region of VPg is important for the VPg-eIF4G interaction; viruses with mutations that alter or disrupt this interaction are debilitated or non-viable. Our results shed new light on the unusual mechanisms of protein-directed translation initiation. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

  4. Prediction of protein-peptide interactions: application of the XPairIt API to anthrax lethal factor and substrates

    NASA Astrophysics Data System (ADS)

    Hurley, Margaret M.; Sellers, Michael S.

    2013-05-01

    As software and methodology develop, key aspects of molecular interactions such as detailed energetics and flexibility are continuously better represented in docking simulations. In the latest iteration of the XPairIt API and Docking Protocol, we perform a blind dock of a peptide into the cleavage site of the Anthrax lethal factor (LF) metalloprotein. Molecular structures are prepared from RCSB:1JKY and we demonstrate a reasonably accurate docked peptide through analysis of protein motion and, using NCI Plot, visualize and characterize the forces leading to binding. We compare our docked structure to the 1JKY crystal structure and the more recent 1PWV structure, and discuss both captured and overlooked interactions. Our results offer a more detailed look at secondary contact and show that both van der Waals and electrostatic interactions from peptide residues further from the enzyme's catalytic site are significant.

  5. Functional and Structural Properties of a Novel Protein and Virulence Factor (Protein sHIP) in Streptococcus pyogenes *

    PubMed Central

    Wisniewska, Magdalena; Happonen, Lotta; Kahn, Fredrik; Varjosalo, Markku; Malmström, Lars; Rosenberger, George; Karlsson, Christofer; Cazzamali, Giuseppe; Pozdnyakova, Irina; Frick, Inga-Maria; Björck, Lars; Streicher, Werner; Malmström, Johan; Wikström, Mats

    2014-01-01

    Streptococcus pyogenes is a significant bacterial pathogen in the human population. The importance of virulence factors for the survival and colonization of S. pyogenes is well established, and many of these factors are exposed to the extracellular environment, enabling bacterial interactions with the host. In the present study, we quantitatively analyzed and compared S. pyogenes proteins in the growth medium of a strain that is virulent to mice with a non-virulent strain. Particularly, one of these proteins was present at significantly higher levels in stationary growth medium from the virulent strain. We determined the three-dimensional structure of the protein that showed a unique tetrameric organization composed of four helix-loop-helix motifs. Affinity pull-down mass spectrometry analysis in human plasma demonstrated that the protein interacts with histidine-rich glycoprotein (HRG), and the name sHIP (streptococcal histidine-rich glycoprotein-interacting protein) is therefore proposed. HRG has antibacterial activity, and when challenged by HRG, sHIP was found to rescue S. pyogenes bacteria. This and the finding that patients with invasive S. pyogenes infection respond with antibody production against sHIP suggest a role for the protein in S. pyogenes pathogenesis. PMID:24825900

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

    PubMed

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

    2017-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-05-01

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

  8. Potential Interference of Protein-Protein Interactions by Graphyne.

    PubMed

    Luan, Binquan; Huynh, Tien; Zhou, Ruhong

    2016-03-10

    Graphyne has attracted tremendous attention recently due to its many potentially superior properties relative to those of graphene. Although extensive efforts have been devoted to explore the applicability of graphyne as an alternative nanomaterial for state-of-the-art nanotechnology (including biomedical applications), knowledge regarding its possible adverse effects to biological cells is still lacking. Here, using large-scale all-atom molecular dynamics simulations, we investigate the potential toxicity of graphyne by interfering a protein-protein interaction (ppI). We found that graphyne could indeed disrupt the ppIs by cutting through the protein-protein interface and separating the protein complex into noncontacting ones, due to graphyne's dispersive and hydrophobic interaction with the hydrophobic residues residing at the dimer interface. Our results help to elucidate the mechanism of interaction between graphyne and ppI networks within a biological cell and provide insights for its hazard reduction.

  9. Direct Interaction between Scaffolding Proteins RACK1 and 14-3-3ζ Regulates Brain-derived Neurotrophic Factor (BDNF) Transcription*

    PubMed Central

    Neasta, Jérémie; Kiely, Patrick A.; He, Dao-Yao; Adams, David R.; O'Connor, Rosemary; Ron, Dorit

    2012-01-01

    RACK1 is a scaffolding protein that spatially and temporally regulates numerous signaling cascades. We previously found that activation of the cAMP signaling pathway induces the translocation of RACK1 to the nucleus. We further showed that nuclear RACK1 is required to promote the transcription of the brain-derived neurotrophic factor (BDNF). Here, we set out to elucidate the mechanism underlying cAMP-dependent RACK1 nuclear translocation and BDNF transcription. We identified the scaffolding protein 14-3-3ζ as a direct binding partner of RACK1. Moreover, we found that 14-3-3ζ was necessary for the cAMP-dependent translocation of RACK1 to the nucleus. We further observed that the disruption of RACK1/14-3-3ζ interaction with a peptide derived from the RACK1/14-3-3ζ binding site or shRNA-mediated 14-3-3ζ knockdown inhibited cAMP induction of BDNF transcription. Together, these data reveal that the function of nuclear RACK1 is mediated through its interaction with 14-3-3ζ. As RACK1 and 14-3-3ζ are two multifunctional scaffolding proteins that coordinate a wide variety of signaling events, their interaction is likely to regulate other essential cellular functions. PMID:22069327

  10. Clustering coefficients of protein-protein interaction networks

    NASA Astrophysics Data System (ADS)

    Miller, Gerald A.; Shi, Yi Y.; Qian, Hong; Bomsztyk, Karol

    2007-05-01

    The properties of certain networks are determined by hidden variables that are not explicitly measured. The conditional probability (propagator) that a vertex with a given value of the hidden variable is connected to k other vertices determines all measurable properties. We study hidden variable models and find an averaging approximation that enables us to obtain a general analytical result for the propagator. Analytic results showing the validity of the approximation are obtained. We apply hidden variable models to protein-protein interaction networks (PINs) in which the hidden variable is the association free energy, determined by distributions that depend on biochemistry and evolution. We compute degree distributions as well as clustering coefficients of several PINs of different species; good agreement with measured data is obtained. For the human interactome two different parameter sets give the same degree distributions, but the computed clustering coefficients differ by a factor of about 2. This shows that degree distributions are not sufficient to determine the properties of PINs.

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

    PubMed Central

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

    2013-01-01

    Intramolecular disulfide bond formation is promoted in oxidizing extracellular and endoplasmic reticulum compartments and often contributes to protein stability and function. DUOX1 and DUOX2 are distinguished from other members of the NOX protein family by the presence of a unique extracellular N-terminal region. These peroxidase-like domains lack the conserved cysteines that confer structural stability to mammalian peroxidases. Sequence-based structure predictions suggest that the thiol groups present are solvent-exposed on a single protein surface and are too distant to support intramolecular disulfide bond formation. To investigate the role of these thiol residues, we introduced four individual cysteine to glycine mutations in the peroxidase-like domains of both human DUOXs and purified the recombinant proteins. The mutations caused little change in the stabilities of the monomeric proteins, supporting the hypothesis that the thiol residues are solvent-exposed and not involved in disulfide bonds that are critical for structural integrity. However, the ability of the isolated hDUOX1 peroxidase-like domain to dimerize was altered, suggesting a role for these cysteines in protein-protein interactions that could facilitate homodimerization of the peroxidase-like domain or, in the full-length protein, heterodimeric interactions with a maturation protein. When full-length hDUOX1 was expressed in HEK293 cells, the mutations resulted in decreased H2O2 production that correlated with a decreased amount of the enzyme localized to the membrane surface rather than with a loss of activity or with a failure to synthesize the mutant proteins. These results support a role for the cysteine residues in intermolecular disulfide bond formation with the DUOX maturation factor DUOXA1. PMID:23362256

  12. Actin Interacting Protein1 and Actin Depolymerizing Factor Drive Rapid Actin Dynamics in Physcomitrella patens[W

    PubMed Central

    Augustine, Robert C.; Pattavina, Kelli A.; Tüzel, Erkan; Vidali, Luis; Bezanilla, Magdalena

    2011-01-01

    The remodeling of actin networks is required for a variety of cellular processes in eukaryotes. In plants, several actin binding proteins have been implicated in remodeling cortical actin filaments (F-actin). However, the extent to which these proteins support F-actin dynamics in planta has not been tested. Using reverse genetics, complementation analyses, and cell biological approaches, we assessed the in vivo function of two actin turnover proteins: actin interacting protein1 (AIP1) and actin depolymerizing factor (ADF). We report that AIP1 is a single-copy gene in the moss Physcomitrella patens. AIP1 knockout plants are viable but have reduced expansion of tip-growing cells. AIP1 is diffusely cytosolic and functions in a common genetic pathway with ADF to promote tip growth. Specifically, ADF can partially compensate for loss of AIP1, and AIP1 requires ADF for function. Consistent with a role in actin remodeling, AIP1 knockout lines accumulate F-actin bundles, have fewer dynamic ends, and have reduced severing frequency. Importantly, we demonstrate that AIP1 promotes and ADF is essential for cortical F-actin dynamics. PMID:22003077

  13. Thioredoxin-interacting protein regulates protein disulfide isomerases and endoplasmic reticulum stress.

    PubMed

    Lee, Samuel; Min Kim, Soo; Dotimas, James; Li, Letitia; Feener, Edward P; Baldus, Stephan; Myers, Ronald B; Chutkow, William A; Patwari, Parth; Yoshioka, Jun; Lee, Richard T

    2014-06-01

    The endoplasmic reticulum (ER) is responsible for protein folding, modification, and trafficking. Accumulation of unfolded or misfolded proteins represents the condition of ER stress and triggers the unfolded protein response (UPR), a key mechanism linking supply of excess nutrients to insulin resistance and type 2 diabetes in obesity. The ER harbors proteins that participate in protein folding including protein disulfide isomerases (PDIs). Changes in PDI activity are associated with protein misfolding and ER stress. Here, we show that thioredoxin-interacting protein (Txnip), a member of the arrestin protein superfamily and one of the most strongly induced proteins in diabetic patients, regulates PDI activity and UPR signaling. We found that Txnip binds to PDIs and increases their enzymatic activity. Genetic deletion of Txnip in cells and mice led to increased protein ubiquitination and splicing of the UPR regulated transcription factor X-box-binding protein 1 (Xbp1s) at baseline as well as under ER stress. Our results reveal Txnip as a novel direct regulator of PDI activity and a feedback mechanism of UPR signaling to decrease ER stress. © 2014 Brigham and Women's Hospital. Published under the terms of the CC BY 4.0 license.

  14. Context-based retrieval of functional modules in protein-protein interaction networks.

    PubMed

    Dobay, Maria Pamela; Stertz, Silke; Delorenzi, Mauro

    2017-03-27

    Various techniques have been developed for identifying the most probable interactants of a protein under a given biological context. In this article, we dissect the effects of the choice of the protein-protein interaction network (PPI) and the manipulation of PPI settings on the network neighborhood of the influenza A virus (IAV) network, as well as hits in genome-wide small interfering RNA screen results for IAV host factors. We investigate the potential of context filtering, which uses text mining evidence linked to PPI edges, as a complement to the edge confidence scores typically provided in PPIs for filtering, for obtaining more biologically relevant network neighborhoods. Here, we estimate the maximum performance of context filtering to isolate a Kyoto Encyclopedia of Genes and Genomes (KEGG) network Ki from a union of KEGG networks and its network neighborhood. The work gives insights on the use of human PPIs in network neighborhood approaches for functional inference. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  15. Protein–Protein Interactions in Dilute to Concentrated Solutions: α-Chymotrypsinogen in Acidic Conditions

    PubMed Central

    2015-01-01

    Protein–protein interactions were investigated for α-chymotrypsinogen by static and dynamic light scattering (SLS and DLS, respectively), as well as small-angle neutron scattering (SANS), as a function of protein and salt concentration at acidic conditions. Net protein–protein interactions were probed via the Kirkwood–Buff integral G22 and the static structure factor S(q) from SLS and SANS data. G22 was obtained by regressing the Rayleigh ratio versus protein concentration with a local Taylor series approach, which does not require one to assume the underlying form or nature of intermolecular interactions. In addition, G22 and S(q) were further analyzed by traditional methods involving fits to effective interaction potentials. Although the fitted model parameters were not always physically realistic, the numerical values for G22 and S(q → 0) were in good agreement from SLS and SANS as a function of protein concentration. In the dilute regime, fitted G22 values agreed with those obtained via the osmotic second virial coefficient B22 and showed that electrostatic interactions are the dominant contribution for colloidal interactions in α-chymotrypsinogen solutions. However, as protein concentration increases, the strength of protein–protein interactions decreases, with a more pronounced decrease at low salt concentrations. The results are consistent with an effective “crowding” or excluded volume contribution to G22 due to the long-ranged electrostatic repulsions that are prominent even at the moderate range of protein concentrations used here (<40 g/L). These apparent crowding effects were confirmed and quantified by assessing the hydrodynamic factor H(q → 0), which is obtained by combining measurements of the collective diffusion coefficient from DLS data with measurements of S(q → 0). H(q → 0) was significantly less than that for a corresponding hard-sphere system and showed that hydrodynamic nonidealities can lead to qualitatively incorrect

  16. Interaction of Arabidopsis Trihelix-Domain Transcription Factors VFP3 and VFP5 with Agrobacterium Virulence Protein VirF

    PubMed Central

    García-Cano, Elena; Magori, Shimpei; Sun, Qi; Ding, Zehong; Lazarowitz, Sondra G.; Citovsky, Vitaly

    2015-01-01

    Agrobacterium is a natural genetic engineer of plants that exports several virulence proteins into host cells in order to take advantage of the cell machinery to facilitate transformation and support bacterial growth. One of these effectors is the F-box protein VirF, which presumably uses the host ubiquitin/proteasome system (UPS) to uncoat the packaging proteins from the invading bacterial T-DNA. By analogy to several other bacterial effectors, VirF most likely has several functions in the host cell and, therefore, several interacting partners among host proteins. Here we identify one such interactor, an Arabidopsis trihelix-domain transcription factor VFP3, and further show that its very close homolog VFP5 also interacted with VirF. Interestingly, interactions of VirF with either VFP3 or VFP5 did not activate the host UPS, suggesting that VirF might play other UPS-independent roles in bacterial infection. To better understand the potential scope of VFP3 function, we used RNAi to reduce expression of the VFP3 gene. Transcriptome profiling of these VFP3-silenced plants using high-throughput cDNA sequencing (RNA-seq) revealed that VFP3 substantially affected plant gene expression; specifically, 1,118 genes representing approximately 5% of all expressed genes were significantly either up- or down-regulated in the VFP3 RNAi line compared to wild-type Col-0 plants. Among the 507 up-regulated genes were genes implicated in the regulation of transcription, protein degradation, calcium signaling, and hormone metabolism, whereas the 611 down-regulated genes included those involved in redox regulation, light reactions of photosynthesis, and metabolism of lipids, amino acids, and cell wall. Overall, this pattern of changes in gene expression is characteristic of plants under stress. Thus, VFP3 likely plays an important role in controlling plant homeostasis. PMID:26571494

  17. Molecular simulation of the effect of cholesterol on lipid-mediated protein-protein interactions.

    PubMed

    de Meyer, Frédérick J-M; Rodgers, Jocelyn M; Willems, Thomas F; Smit, Berend

    2010-12-01

    Experiments and molecular simulations have shown that the hydrophobic mismatch between proteins and membranes contributes significantly to lipid-mediated protein-protein interactions. In this article, we discuss the effect of cholesterol on lipid-mediated protein-protein interactions as function of hydrophobic mismatch, protein diameter and protein cluster size, lipid tail length, and temperature. To do so, we study a mesoscopic model of a hydrated bilayer containing lipids and cholesterol in which proteins are embedded, with a hybrid dissipative particle dynamics-Monte Carlo method. We propose a mechanism by which cholesterol affects protein interactions: protein-induced, cholesterol-enriched, or cholesterol-depleted lipid shells surrounding the proteins affect the lipid-mediated protein-protein interactions. Our calculations of the potential of mean force between proteins and protein clusters show that the addition of cholesterol dramatically reduces repulsive lipid-mediated interactions between proteins (protein clusters) with positive mismatch, but does not affect attractive interactions between proteins with negative mismatch. Cholesterol has only a modest effect on the repulsive interactions between proteins with different mismatch. Copyright © 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  18. 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.

  19. Use of Phage Display to Identify Novel Mineralocorticoid Receptor-Interacting Proteins

    PubMed Central

    Yang, Jun; Fuller, Peter J.; Morgan, James; Shibata, Hirotaka; McDonnell, Donald P.; Clyne, Colin D.

    2014-01-01

    The mineralocorticoid receptor (MR) plays a central role in salt and water homeostasis via the kidney; however, inappropriate activation of the MR in the heart can lead to heart failure. A selective MR modulator that antagonizes MR signaling in the heart but not the kidney would provide the cardiovascular protection of current MR antagonists but allow for normal electrolyte balance. The development of such a pharmaceutical requires an understanding of coregulators and their tissue-selective interactions with the MR, which is currently limited by the small repertoire of MR coregulators described in the literature. To identify potential novel MR coregulators, we used T7 phage display to screen tissue-selective cDNA libraries for MR-interacting proteins. Thirty MR binding peptides were identified, from which three were chosen for further characterization based on their nuclear localization and their interaction with other MR-interacting proteins or, in the case of x-ray repair cross-complementing protein 6, its known status as an androgen receptor coregulator. Eukaryotic elongation factor 1A1, structure-specific recognition protein 1, and x-ray repair cross-complementing protein 6 modulated MR-mediated transcription in a ligand-, cell- and/or promoter-specific manner and colocalized with the MR upon agonist treatment when imaged using immunofluorescence microscopy. These results highlight the utility of phage display for rapid and sensitive screening of MR binding proteins and suggest that eukaryotic elongation factor 1A1, structure-specific recognition protein 1, and x-ray repair cross-complementing protein 6 may be potential MR coactivators whose activity is dependent on the ligand, cellular context, and target gene promoter. PMID:25000480

  20. 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. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    PubMed Central

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

    2006-01-01

    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 . Standalone versions of the software behind the interface are available upon request from the authors. PMID:16845017

  2. InterPred: A pipeline to identify and model protein-protein interactions.

    PubMed

    Mirabello, Claudio; Wallner, Björn

    2017-06-01

    Protein-protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time-consuming. The fact that the number of PPIs is vastly larger than the number of individual proteins makes it practically impossible to characterize all interactions experimentally. Computational approaches that can bridge this gap and predict PPIs and model the interactions in molecular detail are greatly needed. Here we present InterPred, a fully automated pipeline that predicts and model PPIs from sequence using structural modeling combined with massive structural comparisons and molecular docking. A key component of the method is the use of a novel random forest classifier that integrate several structural features to distinguish correct from incorrect protein-protein interaction models. We show that InterPred represents a major improvement in protein-protein interaction detection with a performance comparable or better than experimental high-throughput techniques. We also show that our full-atom protein-protein complex modeling pipeline performs better than state of the art protein docking methods on a standard benchmark set. In addition, InterPred was also one of the top predictors in the latest CAPRI37 experiment. InterPred source code can be downloaded from http://wallnerlab.org/InterPred Proteins 2017; 85:1159-1170. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  3. Scoring functions for protein-protein interactions.

    PubMed

    Moal, Iain H; Moretti, Rocco; Baker, David; Fernández-Recio, Juan

    2013-12-01

    The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Identification of compound-protein interactions through the analysis of gene ontology, KEGG enrichment for proteins and molecular fragments of compounds.

    PubMed

    Chen, Lei; Zhang, Yu-Hang; Zheng, Mingyue; Huang, Tao; Cai, Yu-Dong

    2016-12-01

    Compound-protein interactions play important roles in every cell via the recognition and regulation of specific functional proteins. The correct identification of compound-protein interactions can lead to a good comprehension of this complicated system and provide useful input for the investigation of various attributes of compounds and proteins. In this study, we attempted to understand this system by extracting properties from both proteins and compounds, in which proteins were represented by gene ontology and KEGG pathway enrichment scores and compounds were represented by molecular fragments. Advanced feature selection methods, including minimum redundancy maximum relevance, incremental feature selection, and the basic machine learning algorithm random forest, were used to analyze these properties and extract core factors for the determination of actual compound-protein interactions. Compound-protein interactions reported in The Binding Databases were used as positive samples. To improve the reliability of the results, the analytic procedure was executed five times using different negative samples. Simultaneously, five optimal prediction methods based on a random forest and yielding maximum MCCs of approximately 77.55 % were constructed and may be useful tools for the prediction of compound-protein interactions. This work provides new clues to understanding the system of compound-protein interactions by analyzing extracted core features. Our results indicate that compound-protein interactions are related to biological processes involving immune, developmental and hormone-associated pathways.

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

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

  6. Protein-protein recognition control by modulating electrostatic interactions.

    PubMed

    Han, Song; Yin, Shijin; Yi, Hong; Mouhat, Stéphanie; Qiu, Su; Cao, Zhijian; Sabatier, Jean-Marc; Wu, Yingliang; Li, Wenxin

    2010-06-04

    Protein-protein control recognition remains a huge challenge, and its development depends on understanding the chemical and biological mechanisms by which these interactions occur. Here we describe a protein-protein control recognition technique based on the dominant electrostatic interactions occurring between the proteins. We designed a potassium channel inhibitor, BmP05-T, that was 90.32% identical to wild-type BmP05. Negatively charged residues were translocated from the nonbinding interface to the binding interface of BmP05 inhibitor, such that BmP05-T now used BmP05 nonbinding interface as the binding interface. This switch demonstrated that nonbinding interfaces were able to control the orientation of protein binding interfaces in the process of protein-protein recognition. The novel function findings of BmP05-T peptide suggested that the control recognition technique described here had the potential for use in designing and utilizing functional proteins in many biological scenarios.

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

    PubMed

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

    2014-07-07

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

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

    PubMed

    Li, Jian-Feng; Bush, Jenifer; Xiong, Yan; Li, Lei; McCormack, Matthew

    2011-01-01

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

  9. Structural Model for the Interaction of a Designed Ankyrin Repeat Protein with the Human Epidermal Growth Factor Receptor 2

    PubMed Central

    Epa, V. Chandana; Dolezal, Olan; Doughty, Larissa; Xiao, Xiaowen; Jost, Christian; Plückthun, Andreas; Adams, Timothy E.

    2013-01-01

    Designed Ankyrin Repeat Proteins are a class of novel binding proteins that can be selected and evolved to bind to targets with high affinity and specificity. We are interested in the DARPin H10-2-G3, which has been evolved to bind with very high affinity to the human epidermal growth factor receptor 2 (HER2). HER2 is found to be over-expressed in 30% of breast cancers, and is the target for the FDA-approved therapeutic monoclonal antibodies trastuzumab and pertuzumab and small molecule tyrosine kinase inhibitors. Here, we use computational macromolecular docking, coupled with several interface metrics such as shape complementarity, interaction energy, and electrostatic complementarity, to model the structure of the complex between the DARPin H10-2-G3 and HER2. We analyzed the interface between the two proteins and then validated the structural model by showing that selected HER2 point mutations at the putative interface with H10-2-G3 reduce the affinity of binding up to 100-fold without affecting the binding of trastuzumab. Comparisons made with a subsequently solved X-ray crystal structure of the complex yielded a backbone atom root mean square deviation of 0.84–1.14 Ångstroms. The study presented here demonstrates the capability of the computational techniques of structural bioinformatics in generating useful structural models of protein-protein interactions. PMID:23527120

  10. Light-scattering studies of protein solutions: role of hydration in weak protein-protein interactions.

    PubMed

    Paliwal, A; Asthagiri, D; Abras, D; Lenhoff, A M; Paulaitis, M E

    2005-09-01

    We model the hydration contribution to short-range electrostatic/dispersion protein interactions embodied in the osmotic second virial coefficient, B(2), by adopting a quasi-chemical description in which water molecules associated with the protein are identified through explicit molecular dynamics simulations. These water molecules reduce the surface complementarity of highly favorable short-range interactions, and therefore can play an important role in mediating protein-protein interactions. Here we examine this quasi-chemical view of hydration by predicting the interaction part of B(2) and comparing our results with those derived from light-scattering measurements of B(2) for staphylococcal nuclease, lysozyme, and chymotrypsinogen at 25 degrees C as a function of solution pH and ionic strength. We find that short-range protein interactions are influenced by water molecules strongly associated with a relatively small fraction of the protein surface. However, the effect of these strongly associated water molecules on the surface complementarity of short-range protein interactions is significant, and must be taken into account for an accurate description of B(2). We also observe remarkably similar hydration behavior for these proteins despite substantial differences in their three-dimensional structures and spatial charge distributions, suggesting a general characterization of protein hydration.

  11. Carbohydrate-Aromatic Interactions in Proteins.

    PubMed

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

    2015-12-09

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

  12. Mapping protein-protein interactions using yeast two-hybrid assays.

    PubMed

    Mehla, Jitender; Caufield, J Harry; Uetz, Peter

    2015-05-01

    Yeast two-hybrid (Y2H) screens are an efficient system for mapping protein-protein interactions and whole interactomes. The screens can be performed using random libraries or collections of defined open reading frames (ORFs) called ORFeomes. This protocol describes both library and array-based Y2H screening, with an emphasis on array-based assays. Array-based Y2H is commonly used to test a number of "prey" proteins for interactions with a single "bait" (target) protein or pool of proteins. The advantage of this approach is the direct identification of interacting protein pairs without further downstream experiments: The identity of the preys is known and does not require further confirmation. In contrast, constructing and screening a random prey library requires identification of individual prey clones and systematic retesting. Retesting is typically performed in an array format. © 2015 Cold Spring Harbor Laboratory Press.

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

    PubMed

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

    2015-03-01

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

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

    PubMed

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

    2017-04-01

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

  15. Functional and structural properties of a novel protein and virulence factor (Protein sHIP) in Streptococcus pyogenes.

    PubMed

    Wisniewska, Magdalena; Happonen, Lotta; Kahn, Fredrik; Varjosalo, Markku; Malmström, Lars; Rosenberger, George; Karlsson, Christofer; Cazzamali, Giuseppe; Pozdnyakova, Irina; Frick, Inga-Maria; Björck, Lars; Streicher, Werner; Malmström, Johan; Wikström, Mats

    2014-06-27

    Streptococcus pyogenes is a significant bacterial pathogen in the human population. The importance of virulence factors for the survival and colonization of S. pyogenes is well established, and many of these factors are exposed to the extracellular environment, enabling bacterial interactions with the host. In the present study, we quantitatively analyzed and compared S. pyogenes proteins in the growth medium of a strain that is virulent to mice with a non-virulent strain. Particularly, one of these proteins was present at significantly higher levels in stationary growth medium from the virulent strain. We determined the three-dimensional structure of the protein that showed a unique tetrameric organization composed of four helix-loop-helix motifs. Affinity pull-down mass spectrometry analysis in human plasma demonstrated that the protein interacts with histidine-rich glycoprotein (HRG), and the name sHIP (streptococcal histidine-rich glycoprotein-interacting protein) is therefore proposed. HRG has antibacterial activity, and when challenged by HRG, sHIP was found to rescue S. pyogenes bacteria. This and the finding that patients with invasive S. pyogenes infection respond with antibody production against sHIP suggest a role for the protein in S. pyogenes pathogenesis. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

  16. Patterns of HIV-1 Protein Interaction Identify Perturbed Host-Cellular Subsystems

    PubMed Central

    MacPherson, Jamie I.; Dickerson, Jonathan E.; Pinney, John W.; Robertson, David L.

    2010-01-01

    Human immunodeficiency virus type 1 (HIV-1) exploits a diverse array of host cell functions in order to replicate. This is mediated through a network of virus-host interactions. A variety of recent studies have catalogued this information. In particular the HIV-1, Human Protein Interaction Database (HHPID) has provided a unique depth of protein interaction detail. However, as a map of HIV-1 infection, the HHPID is problematic, as it contains curation error and redundancy; in addition, it is based on a heterogeneous set of experimental methods. Based on identifying shared patterns of HIV-host interaction, we have developed a novel methodology to delimit the core set of host-cellular functions and their associated perturbation from the HHPID. Initially, using biclustering, we identify 279 significant sets of host proteins that undergo the same types of interaction. The functional cohesiveness of these protein sets was validated using a human protein-protein interaction network, gene ontology annotation and sequence similarity. Next, using a distance measure, we group host protein sets and identify 37 distinct higher-level subsystems. We further demonstrate the biological significance of these subsystems by cross-referencing with global siRNA screens that have been used to detect host factors necessary for HIV-1 replication, and investigate the seemingly small intersect between these data sets. Our results highlight significant host-cell subsystems that are perturbed during the course of HIV-1 infection. Moreover, we characterise the patterns of interaction that contribute to these perturbations. Thus, our work disentangles the complex set of HIV-1-host protein interactions in the HHPID, reconciles these with siRNA screens and provides an accessible and interpretable map of infection. PMID:20686668

  17. Hydrophobic environment is a key factor for the stability of thermophilic proteins.

    PubMed

    Gromiha, M Michael; Pathak, Manish C; Saraboji, Kadhirvel; Ortlund, Eric A; Gaucher, Eric A

    2013-04-01

    The stability of thermophilic proteins has been viewed from different perspectives and there is yet no unified principle to understand this stability. It would be valuable to reveal the most important interactions for designing thermostable proteins for such applications as industrial protein engineering. In this work, we have systematically analyzed the importance of various interactions by computing different parameters such as surrounding hydrophobicity, inter-residue interactions, ion-pairs and hydrogen bonds. The importance of each interaction has been determined by its predicted relative contribution in thermophiles versus the same contribution in mesophilic homologues based on a dataset of 373 protein families. We predict that hydrophobic environment is the major factor for the stability of thermophilic proteins and found that 80% of thermophilic proteins analyzed showed higher hydrophobicity than their mesophilic counterparts. Ion pairs, hydrogen bonds, and interaction energy are also important and favored in 68%, 50%, and 62% of thermophilic proteins, respectively. Interestingly, thermophilic proteins with decreased hydrophobic environments display a greater number of hydrogen bonds and/or ion pairs. The systematic elimination of mesophilic proteins based on surrounding hydrophobicity, interaction energy, and ion pairs/hydrogen bonds, led to correctly identifying 95% of the thermophilic proteins in our analyses. Our analysis was also applied to another, more refined set of 102 thermophilic-mesophilic pairs, which again identified hydrophobicity as a dominant property in 71% of the thermophilic proteins. Further, the notion of surrounding hydrophobicity, which characterizes the hydrophobic behavior of residues in a protein environment, has been applied to the three-dimensional structures of elongation factor-Tu proteins and we found that the thermophilic proteins are enriched with a hydrophobic environment. The results obtained in this work highlight the

  18. RNA-protein interactions in an unstructured context.

    PubMed

    Zagrovic, Bojan; Bartonek, Lukas; Polyansky, Anton A

    2018-05-31

    Despite their importance, our understanding of noncovalent RNA-protein interactions is incomplete. This especially concerns the binding between RNA and unstructured protein regions, a widespread class of such interactions. Here, we review the recent experimental and computational work on RNA-protein interactions in an unstructured context with a particular focus on how such interactions may be shaped by the intrinsic interaction affinities between individual nucleobases and protein side chains. Specifically, we articulate the claim that the universal genetic code reflects the binding specificity between nucleobases and protein side chains and that, in turn, the code may be seen as the Rosetta stone for understanding RNA-protein interactions in general. © 2018 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

  19. 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.

  20. 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. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. The tight junction protein ZO-1 and an interacting transcription factor regulate ErbB-2 expression

    PubMed Central

    Balda, Maria S.; Matter, Karl

    2000-01-01

    Epithelial tight junctions regulate paracellular diffusion and restrict the intermixing of apical and basolateral plasma membrane components. We now identify a Y-box transcription factor, ZONAB (ZO-1-associated nucleic acid-binding protein), that binds to the SH3 domain of ZO-1, a submembrane protein of tight junctions. ZONAB localizes to the nucleus and at tight junctions, and binds to sequences of specific promoters containing an inverted CCAAT box. In reporter assays, ZONAB and ZO-1 functionally interact in the regulation of the ErbB-2 promoter in a cell density-dependent manner. In stably transfected overexpressing cells, ZO-1 and ZONAB control expression of endogenous ErbB-2 and function in the regulation of paracellular permeability. These data indicate that tight junctions directly participate in the control of gene expression and suggest that they function in the regulation of epithelial cell differentiation. PMID:10790369

  2. Identification of Protein-Protein Interactions with Glutathione-S-Transferase (GST) Fusion Proteins.

    PubMed

    Einarson, Margret B; Pugacheva, Elena N; Orlinick, Jason R

    2007-08-01

    INTRODUCTIONGlutathione-S-transferase (GST) fusion proteins have had a wide range of applications since their introduction as tools for synthesis of recombinant proteins in bacteria. GST was originally selected as a fusion moiety because of several desirable properties. First and foremost, when expressed in bacteria alone, or as a fusion, GST is not sequestered in inclusion bodies (in contrast to previous fusion protein systems). Second, GST can be affinity-purified without denaturation because it binds to immobilized glutathione, which provides the basis for simple purification. Consequently, GST fusion proteins are routinely used for antibody generation and purification, protein-protein interaction studies, and biochemical analysis. This article describes the use of GST fusion proteins as probes for the identification of protein-protein interactions.

  3. Interactions between whey proteins and salivary proteins as related to astringency of whey protein beverages at low pH.

    PubMed

    Ye, A; Streicher, C; Singh, H

    2011-12-01

    Whey protein beverages have been shown to be astringent at low pH. In the present study, the interactions between model whey proteins (β-lactoglobulin and lactoferrin) and human saliva in the pH range from 7 to 2 were investigated using particle size, turbidity, and ζ-potential measurements and sodium dodecyl sulfate-PAGE. The correlation between the sensory results of astringency and the physicochemical data was discussed. Strong interactions between β-lactoglobulin and salivary proteins led to an increase in the particle size and turbidity of mixtures of both unheated and heated β-lactoglobulin and human saliva at pH ∼3.4. However, the large particle size and high turbidity that occurred at pH 2.0 were the result of aggregation of human salivary proteins. The intense astringency in whey protein beverages may result from these increases in particle size and turbidity at these pH values and from the aggregation and precipitation of human salivary proteins alone at pH <3.0. The involvement of salivary proteins in the interaction is a key factor in the perception of astringency in whey protein beverages. At any pH, the increases in particle size and turbidity were much smaller in mixtures of lactoferrin and saliva, which suggests that aggregation and precipitation may not be the only mechanism linked to the perception of astringency in whey protein. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  4. Over-expression and purification strategies for recombinant multi-protein oligomers: a case study of Mycobacterium tuberculosis σ/anti-σ factor protein complexes.

    PubMed

    Thakur, Krishan Gopal; Jaiswal, Ravi Kumar; Shukla, Jinal K; Praveena, T; Gopal, B

    2010-12-01

    The function of a protein in a cell often involves coordinated interactions with one or several regulatory partners. It is thus imperative to characterize a protein both in isolation as well as in the context of its complex with an interacting partner. High resolution structural information determined by X-ray crystallography and Nuclear Magnetic Resonance offer the best route to characterize protein complexes. These techniques, however, require highly purified and homogenous protein samples at high concentration. This requirement often presents a major hurdle for structural studies. Here we present a strategy based on co-expression and co-purification to obtain recombinant multi-protein complexes in the quantity and concentration range that can enable hitherto intractable structural projects. The feasibility of this strategy was examined using the σ factor/anti-σ factor protein complexes from Mycobacterium tuberculosis. The approach was successful across a wide range of σ factors and their cognate interacting partners. It thus appears likely that the analysis of these complexes based on variations in expression constructs and procedures for the purification and characterization of these recombinant protein samples would be widely applicable for other multi-protein systems. Copyright © 2010 Elsevier Inc. All rights reserved.

  5. A novel microfluidics-based method for probing weak protein-protein interactions.

    PubMed

    Tan, Darren Cherng-wen; Wijaya, I Putu Mahendra; Andreasson-Ochsner, Mirjam; Vasina, Elena Nikolaevna; Nallani, Madhavan; Hunziker, Walter; Sinner, Eva-Kathrin

    2012-08-07

    We report the use of a novel microfluidics-based method to detect weak protein-protein interactions between membrane proteins. The tight junction protein, claudin-2, synthesised in vitro using a cell-free expression system in the presence of polymer vesicles as membrane scaffolds, was used as a model membrane protein. Individual claudin-2 molecules interact weakly, although the cumulative effect of these interactions is significant. This effect results in a transient decrease of average vesicle dispersivity and reduction in transport speed of claudin-2-functionalised vesicles. Polymer vesicles functionalised with claudin-2 were perfused through a microfluidic channel and the time taken to traverse a defined distance within the channel was measured. Functionalised vesicles took 1.19 to 1.69 times longer to traverse this distance than unfunctionalised ones. Coating the channel walls with protein A and incubating the vesicles with anti-claudin-2 antibodies prior to perfusion resulted in the functionalised vesicles taking 1.75 to 2.5 times longer to traverse this distance compared to the controls. The data show that our system is able to detect weak as well as strong protein-protein interactions. This system offers researchers a portable, easily operated and customizable platform for the study of weak protein-protein interactions, particularly between membrane proteins.

  6. 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.

  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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Feng, Mei; Kang, Hongsuk; Luan, Binquan

    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 andmore » 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.« less

  9. PodNet, a protein-protein interaction network of the podocyte.

    PubMed

    Warsow, Gregor; Endlich, Nicole; Schordan, Eric; Schordan, Sandra; Chilukoti, Ravi K; Homuth, Georg; Moeller, Marcus J; Fuellen, Georg; Endlich, Karlhans

    2013-07-01

    Interactions between proteins crucially determine cellular structure and function. Differential analysis of the interactome may help elucidate molecular mechanisms during disease development; however, this analysis necessitates mapping of expression data on protein-protein interaction networks. These networks do not exist for the podocyte; therefore, we built PodNet, a literature-based mouse podocyte network in Cytoscape format. Using database protein-protein interactions, we expanded PodNet to XPodNet with enhanced connectivity. In order to test the performance of XPodNet in differential interactome analysis, we examined podocyte developmental differentiation and the effect of cell culture. Transcriptomes of podocytes in 10 different states were mapped on XPodNet and analyzed with the Cytoscape plugin ExprEssence, based on the law of mass action. Interactions between slit diaphragm proteins are most significantly upregulated during podocyte development and most significantly downregulated in culture. On the other hand, our analysis revealed that interactions lost during podocyte differentiation are not regained in culture, suggesting a loss rather than a reversal of differentiation for podocytes in culture. Thus, we have developed PodNet as a valuable tool for differential interactome analysis in podocytes, and we have identified established and unexplored regulated interactions in developing and cultured podocytes.

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

    PubMed

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

    2013-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-05-01

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

  12. An accurate binding interaction model in de novo computational protein design of interactions: if you build it, they will bind.

    PubMed

    London, Nir; Ambroggio, Xavier

    2014-02-01

    Computational protein design efforts aim to create novel proteins and functions in an automated manner and, in the process, these efforts shed light on the factors shaping natural proteins. The focus of these efforts has progressed from the interior of proteins to their surface and the design of functions, such as binding or catalysis. Here we examine progress in the development of robust methods for the computational design of non-natural interactions between proteins and molecular targets such as other proteins or small molecules. This problem is referred to as the de novo computational design of interactions. Recent successful efforts in de novo enzyme design and the de novo design of protein-protein interactions open a path towards solving this problem. We examine the common themes in these efforts, and review recent studies aimed at understanding the nature of successes and failures in the de novo computational design of interactions. While several approaches culminated in success, the use of a well-defined structural model for a specific binding interaction in particular has emerged as a key strategy for a successful design, and is therefore reviewed with special consideration. Copyright © 2013 Elsevier Inc. All rights reserved.

  13. Predicting Protein-Protein Interactions by Combing Various Sequence-Derived.

    PubMed

    Zhao, Xiao-Wei; Ma, Zhi-Qiang; Yin, Ming-Hao

    2011-09-20

    Knowledge of protein-protein interactions (PPIs) plays an important role in constructing protein interaction networks and understanding the general machineries of biological systems. In this study, a new method is proposed to predict PPIs using a comprehensive set of 930 features based only on sequence information, these features measure the interactions between residues a certain distant apart in the protein sequences from different aspects. To achieve better performance, the principal component analysis (PCA) is first employed to obtain an optimized feature subset. Then, the resulting 67-dimensional feature vectors are fed to Support Vector Machine (SVM). Experimental results on Drosophila melanogaster and Helicobater pylori datasets show that our method is very promising to predict PPIs and may at least be a useful supplement tool to existing methods.

  14. Role of water mediated interactions in protein-protein recognition landscapes.

    PubMed

    Papoian, Garegin A; Ulander, Johan; Wolynes, Peter G

    2003-07-30

    The energy landscape picture of protein folding and binding is employed to optimize a number of pair potentials for direct and water-mediated interactions in protein complex interfaces. We find that water-mediated interactions greatly complement direct interactions in discriminating against various types of trap interactions that model those present in the cell. We highlight the context dependent nature of knowledge-based binding potentials, as contrasted with the situation for autonomous folding. By performing a Principal Component Analysis (PCA) of the corresponding interaction matrixes, we rationalize the strength of the recognition signal for each combination of the contact type and reference trap states using the differential in the idealized "canonical" amino acid compositions of native and trap layers. The comparison of direct and water-mediated contact potential matrixes emphasizes the importance of partial solvation in stabilizing charged groups in the protein interfaces. Specific water-mediated interresidue interactions are expected to influence significantly the kinetics as well as thermodynamics of protein association.

  15. hPDI: a database of experimental human protein-DNA interactions.

    PubMed

    Xie, Zhi; Hu, Shaohui; Blackshaw, Seth; Zhu, Heng; Qian, Jiang

    2010-01-15

    The human protein DNA Interactome (hPDI) database holds experimental protein-DNA interaction data for humans identified by protein microarray assays. The unique characteristics of hPDI are that it contains consensus DNA-binding sequences not only for nearly 500 human transcription factors but also for >500 unconventional DNA-binding proteins, which are completely uncharacterized previously. Users can browse, search and download a subset or the entire data via a web interface. This database is freely accessible for any academic purposes. http://bioinfo.wilmer.jhu.edu/PDI/.

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

    PubMed

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

    2018-01-05

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

  17. Regulation of RE1 Protein Silencing Transcription Factor (REST) Expression by HIP1 Protein Interactor (HIPPI)*

    PubMed Central

    Datta, Moumita; Bhattacharyya, Nitai P.

    2011-01-01

    Earlier we have shown that the proapoptotic protein HIPPI (huntingtin interacting protein 1 (HIP1) protein interactor) along with its molecular partner HIP1 could regulate transcription of the caspase-1 gene. Here we report that RE1-silencing transcription factor/neuron-restrictive silencer factor (REST/NRSF) is a new transcriptional target of HIPPI. HIPPI could bind to the promoter of REST and increased its expression in neuronal as well as non-neuronal cells. Such activation of REST down-regulated expression of REST target genes, such as brain-derived neurotrophic factor (BDNF) or proenkephalin (PENK). The ability of HIPPI to activate REST gene transcription was dependent on HIP1, the nuclear transporter of HIPPI. Using a Huntington disease cell model, we have demonstrated that feeble interaction of HIP1 with mutant huntingtin protein resulted in increased nuclear accumulation of HIPPI and HIP1, leading to higher occupancy of HIPPI at the REST promoter, triggering its transcriptional activation and consequent repression of REST target genes. This novel transcription regulatory mechanism of REST by HIPPI may contribute to the deregulation of transcription observed in the cell model of Huntington disease. PMID:21832040

  18. Regulation of RE1 protein silencing transcription factor (REST) expression by HIP1 protein interactor (HIPPI).

    PubMed

    Datta, Moumita; Bhattacharyya, Nitai P

    2011-09-30

    Earlier we have shown that the proapoptotic protein HIPPI (huntingtin interacting protein 1 (HIP1) protein interactor) along with its molecular partner HIP1 could regulate transcription of the caspase-1 gene. Here we report that RE1-silencing transcription factor/neuron-restrictive silencer factor (REST/NRSF) is a new transcriptional target of HIPPI. HIPPI could bind to the promoter of REST and increased its expression in neuronal as well as non-neuronal cells. Such activation of REST down-regulated expression of REST target genes, such as brain-derived neurotrophic factor (BDNF) or proenkephalin (PENK). The ability of HIPPI to activate REST gene transcription was dependent on HIP1, the nuclear transporter of HIPPI. Using a Huntington disease cell model, we have demonstrated that feeble interaction of HIP1 with mutant huntingtin protein resulted in increased nuclear accumulation of HIPPI and HIP1, leading to higher occupancy of HIPPI at the REST promoter, triggering its transcriptional activation and consequent repression of REST target genes. This novel transcription regulatory mechanism of REST by HIPPI may contribute to the deregulation of transcription observed in the cell model of Huntington disease.

  19. 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

    2014-09-07

    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.

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

    DOE PAGES

    Venkatraman, S.; Doktycz, M. J.; Qi, H.; ...

    2006-01-01

    The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction.more » Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors.« less

  1. 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.

  2. Yeast two-hybrid cloning of a novel zinc finger protein that interacts with the multifunctional transcription factor YY1.

    PubMed Central

    Kalenik, J L; Chen, D; Bradley, M E; Chen, S J; Lee, T C

    1997-01-01

    Muscle-restricted transcription of sarcomeric actin genes is negatively controlled by the zinc finger protein YY1, which is down-regulated at the protein level during myogenic differentiation. To identify cellular proteins that might mediate the function/stability of YY1 in muscle cells, we screened an adult human muscle cDNA library using the yeast two-hybrid cloning system. We report the isolation and characterization of a novel protein termed YAF2 (YY1- associated factor 2) that interacts with YY1. The YAF2 cDNA encodes a 180 amino acid basic protein (pI 10.5) containing a single N-terminal C2-X10-C2 zinc finger. Lysine clusters are present that may function as a nuclear localization signal. Domain mapping analysis shows that the first and second zinc fingers of YY1 are targeted for YAF2 protein interaction. In contrast to the down-regulation of YY1, YAF2 message levels increase during in vitro differentiation of both rat skeletal and cardiac muscle cells. YAF2 appears to have a promyogenic regulatory role, since overexpression of YAF2 in C2 myoblasts stimulates myogenic promoter activity normally restricted by YY1. Co-transfection of YY1 reverses the stimulatory effect of YAF2. YAF2 also greatly potentiates proteolytic cleavage of YY1 by the calcium- activated protease m-calpain. The isolation of YAF2 may help in understanding the mechanisms through which inhibitors of myogenic transcription may be antagonized or eliminated by proteolysis during muscle development. PMID:9016636

  3. Identifying cooperative transcriptional regulations using protein–protein interactions

    PubMed Central

    Nagamine, Nobuyoshi; Kawada, Yuji; Sakakibara, Yasubumi

    2005-01-01

    Cooperative transcriptional activations among multiple transcription factors (TFs) are important to understand the mechanisms of complex transcriptional regulations in eukaryotes. Previous studies have attempted to find cooperative TFs based on gene expression data with gene expression profiles as a measure of similarity of gene regulations. In this paper, we use protein–protein interaction data to infer synergistic binding of cooperative TFs. Our fundamental idea is based on the assumption that genes contributing to a similar biological process are regulated under the same control mechanism. First, the protein–protein interaction networks are used to calculate the similarity of biological processes among genes. Second, we integrate this similarity and the chromatin immuno-precipitation data to identify cooperative TFs. Our computational experiments in yeast show that predictions made by our method have successfully identified eight pairs of cooperative TFs that have literature evidences but could not be identified by the previous method. Further, 12 new possible pairs have been inferred and we have examined the biological relevances for them. However, since a typical problem using protein–protein interaction data is that many false-positive data are contained, we propose a method combining various biological data to increase the prediction accuracy. PMID:16126847

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

    PubMed

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

    2017-03-09

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

  5. Identification of structural protein-protein interactions of herpes simplex virus type 1.

    PubMed

    Lee, Jin H; Vittone, Valerio; Diefenbach, Eve; Cunningham, Anthony L; Diefenbach, Russell J

    2008-09-01

    In this study we have defined protein-protein interactions between the structural proteins of herpes simplex virus type 1 (HSV-1) using a LexA yeast two-hybrid system. The majority of the capsid, tegument and envelope proteins of HSV-1 were screened in a matrix approach. A total of 40 binary interactions were detected including 9 out of 10 previously identified tegument-tegument interactions (Vittone, V., Diefenbach, E., Triffett, D., Douglas, M.W., Cunningham, A.L., and Diefenbach, R.J., 2005. Determination of interactions between tegument proteins of herpes simplex virus type 1. J. Virol. 79, 9566-9571). A total of 12 interactions involving the capsid protein pUL35 (VP26) and 11 interactions involving the tegument protein pUL46 (VP11/12) were identified. The most significant novel interactions detected in this study, which are likely to play a role in viral assembly, include pUL35-pUL37 (capsid-tegument), pUL46-pUL37 (tegument-tegument) and pUL49 (VP22)-pUS9 (tegument-envelope). This information will provide further insights into the pathways of HSV-1 assembly and the identified interactions are potential targets for new antiviral drugs.

  6. Understanding protein-nanoparticle interaction: a new gateway to disease therapeutics.

    PubMed

    Giri, Karuna; Shameer, Khader; Zimmermann, Michael T; Saha, Sounik; Chakraborty, Prabir K; Sharma, Anirudh; Arvizo, Rochelle R; Madden, Benjamin J; Mccormick, Daniel J; Kocher, Jean-Pierre A; Bhattacharya, Resham; Mukherjee, Priyabrata

    2014-06-18

    Molecular identification of protein molecules surrounding nanoparticles (NPs) may provide useful information that influences NP clearance, biodistribution, and toxicity. Hence, nanoproteomics provides specific information about the environment that NPs interact with and can therefore report on the changes in protein distribution that occurs during tumorigenesis. Therefore, we hypothesized that characterization and identification of protein molecules that interact with 20 nm AuNPs from cancer and noncancer cells may provide mechanistic insights into the biology of tumor growth and metastasis and identify new therapeutic targets in ovarian cancer. Hence, in the present study, we systematically examined the interaction of the protein molecules with 20 nm AuNPs from cancer and noncancerous cell lysates. Time-resolved proteomic profiles of NP-protein complexes demonstrated electrostatic interaction to be the governing factor in the initial time-points which are dominated by further stabilization interaction at longer time-points as determined by ultraviolet-visible spectroscopy (UV-vis), dynamic light scattering (DLS), ζ-potential measurements, transmission electron microscopy (TEM), and tandem mass spectrometry (MS/MS). Reduction in size, charge, and number of bound proteins were observed as the protein-NP complex stabilized over time. Interestingly, proteins related to mRNA processing were overwhelmingly represented on the NP-protein complex at all times. More importantly, comparative proteomic analyses revealed enrichment of a number of cancer-specific proteins on the AuNP surface. Network analyses of these proteins highlighted important hub nodes that could potentially be targeted for maximal therapeutic advantage in the treatment of ovarian cancer. The importance of this methodology and the biological significance of the network proteins were validated by a functional study of three hubs that exhibited variable connectivity, namely, PPA1, SMNDC1, and PI15. Western

  7. The Intrinsically Disordered Regions of the Drosophila melanogaster Hox Protein Ultrabithorax Select Interacting Proteins Based on Partner Topology

    PubMed Central

    Hsiao, Hao-Ching; Gonzalez, Kim L.; Catanese, Daniel J.; Jordy, Kristopher E.; Matthews, Kathleen S.; Bondos, Sarah E.

    2014-01-01

    Interactions between structured proteins require a complementary topology and surface chemistry to form sufficient contacts for stable binding. However, approximately one third of protein interactions are estimated to involve intrinsically disordered regions of proteins. The dynamic nature of disordered regions before and, in some cases, after binding calls into question the role of partner topology in forming protein interactions. To understand how intrinsically disordered proteins identify the correct interacting partner proteins, we evaluated interactions formed by the Drosophila melanogaster Hox transcription factor Ultrabithorax (Ubx), which contains both structured and disordered regions. Ubx binding proteins are enriched in specific folds: 23 of its 39 partners include one of 7 folds, out of the 1195 folds recognized by SCOP. For the proteins harboring the two most populated folds, DNA-RNA binding 3-helical bundles and α-α superhelices, the regions of the partner proteins that exhibit these preferred folds are sufficient for Ubx binding. Three disorder-containing regions in Ubx are required to bind these partners. These regions are either alternatively spliced or multiply phosphorylated, providing a mechanism for cellular processes to regulate Ubx-partner interactions. Indeed, partner topology correlates with the ability of individual partner proteins to bind Ubx spliceoforms. Partners bind different disordered regions within Ubx to varying extents, creating the potential for competition between partners and cooperative binding by partners. The ability of partners to bind regions of Ubx that activate transcription and regulate DNA binding provides a mechanism for partners to modulate transcription regulation by Ubx, and suggests that one role of disorder in Ubx is to coordinate multiple molecular functions in response to tissue-specific cues. PMID:25286318

  8. Interaction of Proteins Identified in Human Thyroid Cells

    PubMed Central

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

    2013-01-01

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

  9. On the Importance of Polar Interactions for Complexes Containing Intrinsically Disordered Proteins

    PubMed Central

    Wong, Eric T. C.; Na, Dokyun; Gsponer, Jörg

    2013-01-01

    There is a growing recognition for the importance of proteins with large intrinsically disordered (ID) segments in cell signaling and regulation. ID segments in these proteins often harbor regions that mediate molecular recognition. Coupled folding and binding of the recognition regions has been proposed to confer high specificity to interactions involving ID segments. However, researchers recently questioned the origin of the interaction specificity of ID proteins because of the overrepresentation of hydrophobic residues in their interaction interfaces. Here, we focused on the role of polar and charged residues in interactions mediated by ID segments. Making use of the extended nature of most ID segments when in complex with globular proteins, we first identified large numbers of complexes between globular proteins and ID segments by using radius-of-gyration-based selection criteria. Consistent with previous studies, we found the interfaces of these complexes to be enriched in hydrophobic residues, and that these residues contribute significantly to the stability of the interaction interface. However, our analyses also show that polar interactions play a larger role in these complexes than in structured protein complexes. Computational alanine scanning and salt-bridge analysis indicate that interfaces in ID complexes are highly complementary with respect to electrostatics, more so than interfaces of globular proteins. Follow-up calculations of the electrostatic contributions to the free energy of binding uncovered significantly stronger Coulombic interactions in complexes harbouring ID segments than in structured protein complexes. However, they are counter-balanced by even higher polar-desolvation penalties. We propose that polar interactions are a key contributing factor to the observed high specificity of ID segment-mediated interactions. PMID:23990768

  10. 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. © 2016 Wiley Periodicals, Inc.

  11. Functional interaction of the DNA-binding transcription factor Sp1 through its DNA-binding domain with the histone chaperone TAF-I.

    PubMed

    Suzuki, Toru; Muto, Shinsuke; Miyamoto, Saku; Aizawa, Kenichi; Horikoshi, Masami; Nagai, Ryozo

    2003-08-01

    Transcription involves molecular interactions between general and regulatory transcription factors with further regulation by protein-protein interactions (e.g. transcriptional cofactors). Here we describe functional interaction between DNA-binding transcription factor and histone chaperone. Affinity purification of factors interacting with the DNA-binding domain of the transcription factor Sp1 showed Sp1 to interact with the histone chaperone TAF-I, both alpha and beta isoforms. This interaction was specific as Sp1 did not interact with another histone chaperone CIA nor did other tested DNA-binding regulatory factors (MyoD, NFkappaB, p53) interact with TAF-I. Interaction of Sp1 and TAF-I occurs both in vitro and in vivo. Interaction with TAF-I results in inhibition of DNA-binding, and also likely as a result of such, inhibition of promoter activation by Sp1. Collectively, we describe interaction between DNA-binding transcription factor and histone chaperone which results in negative regulation of the former. This novel regulatory interaction advances our understanding of the mechanisms of eukaryotic transcription through DNA-binding regulatory transcription factors by protein-protein interactions, and also shows the DNA-binding domain to mediate important regulatory interactions.

  12. Relevance of protein-protein interactions on the biological identity of nanoparticles.

    PubMed

    Vasti, Cecilia; Bonnet, Laura V; Galiano, Mauricio R; Rojas, Ricardo; Giacomelli, Carla E

    2018-06-01

    Considering that the use of nanoparticles (NPs) as carriers of therapeutic or theranostic agents has increased in the last years, it is mandatory to understand the interaction between NPs and living systems. In contact with biological fluids, the NPs (synthetic identity) are covered with biomolecules that form a protein corona, which defines the biological identity. It is well known that the protein corona formation is mediated by non-specific physical interactions, but protein-protein interactions (PPI), involving specific recognition sites of the polypeptides, are also involved. This work explores the relationship between the synthetic and biological identities of layered double hydroxides nanoparticles (LDH-NPs) and the effect of the protein corona on the cellular response. With such a purpose, the synthetic identity was modified by coating LDH-NPs with either a single protein or a complex mixture of them, followed by the characterization of the protein corona formed in a commonly used cell culture medium. A proteomic approach was used to identify the protein corona molecules and the PPI network was constructed with a novel bioinformatic tool. The coating on LDH-NPs defines the biological identity in such a way that the composition of the protein corona as well as PPI are changed. Electrostatic interactions appear not to be the only driving force regulating the interactions between NPs, proteins and cells since the specific recognition also play a fundamental role. However, the biological identity of LDH-NPs does not affect the interactions with cells that shows negligible cytotoxicity and high internalization levels. Copyright © 2018 Elsevier B.V. All rights reserved.

  13. DNAproDB: an interactive tool for structural analysis of DNA–protein complexes

    PubMed Central

    Sagendorf, Jared M.

    2017-01-01

    Abstract Many biological processes are mediated by complex interactions between DNA and proteins. Transcription factors, various polymerases, nucleases and histones recognize and bind DNA with different levels of binding specificity. To understand the physical mechanisms that allow proteins to recognize DNA and achieve their biological functions, it is important to analyze structures of DNA–protein complexes in detail. DNAproDB is a web-based interactive tool designed to help researchers study these complexes. DNAproDB provides an automated structure-processing pipeline that extracts structural features from DNA–protein complexes. The extracted features are organized in structured data files, which are easily parsed with any programming language or viewed in a browser. We processed a large number of DNA–protein complexes retrieved from the Protein Data Bank and created the DNAproDB database to store this data. Users can search the database by combining features of the DNA, protein or DNA–protein interactions at the interface. Additionally, users can upload their own structures for processing privately and securely. DNAproDB provides several interactive and customizable tools for creating visualizations of the DNA–protein interface at different levels of abstraction that can be exported as high quality figures. All functionality is documented and freely accessible at http://dnaprodb.usc.edu. PMID:28431131

  14. Phthalic acid chemical probes synthesized for protein-protein interaction analysis.

    PubMed

    Liang, Shih-Shin; Liao, Wei-Ting; Kuo, Chao-Jen; Chou, Chi-Hsien; Wu, Chin-Jen; Wang, Hui-Min

    2013-06-24

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

  15. COUP-TF (chicken ovalbumin upstream promoter transcription factor)-interacting protein 1 (CTIP1) is a sequence-specific DNA binding protein.

    PubMed Central

    Avram, Dorina; Fields, Andrew; Senawong, Thanaset; Topark-Ngarm, Acharawan; Leid, Mark

    2002-01-01

    Chicken ovalbumin upstream promoter transcription factor (COUP-TF)-interacting proteins 1 and 2 [CTIP1/Evi9/B cell leukaemia (Bcl) l1a and CTIP2/Bcl11b respectively] are highly related C(2)H(2) zinc finger proteins that are abundantly expressed in brain and the immune system, and are associated with immune system malignancies. A selection procedure was employed to isolate high-affinity DNA binding sites for CTIP1. The core binding site on DNA identified in these studies, 5'-GGCCGG-3' (upper strand), is highly related to the canonical GC box and was bound by a CTIP1 oligomeric complex(es) in vitro. Furthermore, both CTIP1 and CTIP2 repressed transcription of a reporter gene harbouring a multimerized CTIP binding site, and this repression was neither reversed by trichostatin A (an inhibitor of known class I and II histone deacetylases) nor stimulated by co-transfection of a COUP-TF family member. These results demonstrate that CTIP1 is a sequence-specific DNA binding protein and a bona fide transcriptional repressor that is capable of functioning independently of COUP-TF family members. These findings may be relevant to the physiological and/or pathological action(s) of CTIPs in cells that do not express COUP-TF family members, such as cells of the haematopoietic and immune systems. PMID:12196208

  16. Computational Prediction of Protein-Protein Interactions

    PubMed Central

    Ehrenberger, Tobias; Cantley, Lewis C.; Yaffe, Michael B.

    2015-01-01

    The prediction of protein-protein interactions and kinase-specific phosphorylation sites on individual proteins is critical for correctly placing proteins within signaling pathways and networks. The importance of this type of annotation continues to increase with the continued explosion of genomic and proteomic data, particularly with emerging data categorizing posttranslational modifications on a large scale. A variety of computational tools are available for this purpose. In this chapter, we review the general methodologies for these types of computational predictions and present a detailed user-focused tutorial of one such method and computational tool, Scansite, which is freely available to the entire scientific community over the Internet. PMID:25859943

  17. Bioluminescence Resonance Energy Transfer System for Measuring Dynamic Protein-Protein Interactions in Bacteria

    PubMed Central

    Cui, Boyu; Wang, Yao; Song, Yunhong; Wang, Tietao; Li, Changfu; Wei, Yahong

    2014-01-01

    ABSTRACT Protein-protein interactions are important for virtually every biological process, and a number of elegant approaches have been designed to detect and evaluate such interactions. However, few of these methods allow the detection of dynamic and real-time protein-protein interactions in bacteria. Here we describe a bioluminescence resonance energy transfer (BRET) system based on the bacterial luciferase LuxAB. We found that enhanced yellow fluorescent protein (eYFP) accepts the emission from LuxAB and emits yellow fluorescence. Importantly, BRET occurred when LuxAB and eYFP were fused, respectively, to the interacting protein pair FlgM and FliA. Furthermore, we observed sirolimus (i.e., rapamycin)-inducible interactions between FRB and FKBP12 and a dose-dependent abolishment of such interactions by FK506, the ligand of FKBP12. Using this system, we showed that osmotic stress or low pH efficiently induced multimerization of the regulatory protein OmpR and that the multimerization induced by low pH can be reversed by a neutralizing agent, further indicating the usefulness of this system in the measurement of dynamic interactions. This method can be adapted to analyze dynamic protein-protein interactions and the importance of such interactions in bacterial processes such as development and pathogenicity. PMID:24846380

  18. Modeling and simulating networks of interdependent protein interactions.

    PubMed

    Stöcker, Bianca K; Köster, Johannes; Zamir, Eli; Rahmann, Sven

    2018-05-21

    Protein interactions are fundamental building blocks of biochemical reaction systems underlying cellular functions. The complexity and functionality of these systems emerge not only from the protein interactions themselves but also from the dependencies between these interactions, as generated by allosteric effects or mutual exclusion due to steric hindrance. Therefore, formal models for integrating and utilizing information about interaction dependencies are of high interest. Here, we describe an approach for endowing protein networks with interaction dependencies using propositional logic, thereby obtaining constrained protein interaction networks ("constrained networks"). The construction of these networks is based on public interaction databases as well as text-mined information about interaction dependencies. We present an efficient data structure and algorithm to simulate protein complex formation in constrained networks. The efficiency of the model allows fast simulation and facilitates the analysis of many proteins in large networks. In addition, this approach enables the simulation of perturbation effects, such as knockout of single or multiple proteins and changes of protein concentrations. We illustrate how our model can be used to analyze a constrained human adhesome protein network, which is responsible for the formation of diverse and dynamic cell-matrix adhesion sites. By comparing protein complex formation under known interaction dependencies versus without dependencies, we investigate how these dependencies shape the resulting repertoire of protein complexes. Furthermore, our model enables investigating how the interplay of network topology with interaction dependencies influences the propagation of perturbation effects across a large biochemical system. Our simulation software CPINSim (for Constrained Protein Interaction Network Simulator) is available under the MIT license at http://github.com/BiancaStoecker/cpinsim and as a Bioconda package

  19. Time-gated detection of protein-protein interactions with transcriptional readout

    PubMed Central

    Sanchez, Mateo I; Coukos, Robert; von Zastrow, Mark

    2017-01-01

    Transcriptional assays, such as yeast two-hybrid and TANGO, that convert transient protein-protein interactions (PPIs) into stable expression of transgenes are powerful tools for PPI discovery, screens, and analysis of cell populations. However, such assays often have high background and lose information about PPI dynamics. We have developed SPARK (Specific Protein Association tool giving transcriptional Readout with rapid Kinetics), in which proteolytic release of a membrane-tethered transcription factor (TF) requires both a PPI to deliver a protease proximal to its cleavage peptide and blue light to uncage the cleavage site. SPARK was used to detect 12 different PPIs in mammalian cells, with 5 min temporal resolution and signal ratios up to 37. By shifting the light window, we could reconstruct PPI time-courses. Combined with FACS, SPARK enabled 51 fold enrichment of PPI-positive over PPI-negative cells. Due to its high specificity and sensitivity, SPARK has the potential to advance PPI analysis and discovery. PMID:29189201

  20. The Ser/Thr Protein Kinase Protein-Protein Interaction Map of M. tuberculosis.

    PubMed

    Wu, Fan-Lin; Liu, Yin; Jiang, He-Wei; Luan, Yi-Zhao; Zhang, Hai-Nan; He, Xiang; Xu, Zhao-Wei; Hou, Jing-Li; Ji, Li-Yun; Xie, Zhi; Czajkowsky, Daniel M; Yan, Wei; Deng, Jiao-Yu; Bi, Li-Jun; Zhang, Xian-En; Tao, Sheng-Ce

    2017-08-01

    Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, the leading cause of death among all infectious diseases. There are 11 eukaryotic-like serine/threonine protein kinases (STPKs) in Mtb, which are thought to play pivotal roles in cell growth, signal transduction and pathogenesis. However, their underlying mechanisms of action remain largely uncharacterized. In this study, using a Mtb proteome microarray, we have globally identified the binding proteins in Mtb for all of the STPKs, and constructed the first STPK protein interaction (KPI) map that includes 492 binding proteins and 1,027 interactions. Bioinformatics analysis showed that the interacting proteins reflect diverse functions, including roles in two-component system, transcription, protein degradation, and cell wall integrity. Functional investigations confirmed that PknG regulates cell wall integrity through key components of peptidoglycan (PG) biosynthesis, e.g. MurC. The global STPK-KPIs network constructed here is expected to serve as a rich resource for understanding the key signaling pathways in Mtb, thus facilitating drug development and effective control of Mtb. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  1. Global Quantitative Modeling of Chromatin Factor Interactions

    PubMed Central

    Zhou, Jian; Troyanskaya, Olga G.

    2014-01-01

    Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896

  2. 3DProIN: Protein-Protein Interaction Networks and Structure Visualization.

    PubMed

    Li, Hui; Liu, Chunmei

    2014-06-14

    3DProIN is a computational tool to visualize protein-protein interaction networks in both two dimensional (2D) and three dimensional (3D) view. It models protein-protein interactions in a graph and explores the biologically relevant features of the tertiary structures of each protein in the network. Properties such as color, shape and name of each node (protein) of the network can be edited in either 2D or 3D views. 3DProIN is implemented using 3D Java and C programming languages. The internet crawl technique is also used to parse dynamically grasped protein interactions from protein data bank (PDB). It is a java applet component that is embedded in the web page and it can be used on different platforms including Linux, Mac and Window using web browsers such as Firefox, Internet Explorer, Chrome and Safari. It also was converted into a mac app and submitted to the App store as a free app. Mac users can also download the app from our website. 3DProIN is available for academic research at http://bicompute.appspot.com.

  3. Conservation of hot regions in protein-protein interaction in evolution.

    PubMed

    Hu, Jing; Li, Jiarui; Chen, Nansheng; Zhang, Xiaolong

    2016-11-01

    The hot regions of protein-protein interactions refer to the active area which formed by those most important residues to protein combination process. With the research development on protein interactions, lots of predicted hot regions can be discovered efficiently by intelligent computing methods, while performing biology experiments to verify each every prediction is hardly to be done due to the time-cost and the complexity of the experiment. This study based on the research of hot spot residue conservations, the proposed method is used to verify authenticity of predicted hot regions that using machine learning algorithm combined with protein's biological features and sequence conservation, though multiple sequence alignment, module substitute matrix and sequence similarity to create conservation scoring algorithm, and then using threshold module to verify the conservation tendency of hot regions in evolution. This research work gives an effective method to verify predicted hot regions in protein-protein interactions, which also provides a useful way to deeply investigate the functional activities of protein hot regions. Copyright © 2016. Published by Elsevier Inc.

  4. 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

  5. Manipulating Protein-Protein Interactions in Nonribosomal Peptide Synthetase Type II Peptidyl Carrier Proteins.

    PubMed

    Jaremko, Matt J; Lee, D John; Patel, Ashay; Winslow, Victoria; Opella, Stanley J; McCammon, J Andrew; Burkart, Michael D

    2017-10-10

    In an effort to elucidate and engineer interactions in type II nonribosomal peptide synthetases, we analyzed biomolecular recognition between the essential peptidyl carrier proteins and adenylation domains using nuclear magnetic resonance (NMR) spectroscopy, molecular dynamics, and mutational studies. Three peptidyl carrier proteins, PigG, PltL, and RedO, in addition to their cognate adenylation domains, PigI, PltF, and RedM, were investigated for their cross-species activity. Of the three peptidyl carrier proteins, only PigG showed substantial cross-pathway activity. Characterization of the novel NMR solution structure of holo-PigG and molecular dynamics simulations of holo-PltL and holo-PigG revealed differences in structures and dynamics of these carrier proteins. NMR titration experiments revealed perturbations of the chemical shifts of the loop 1 residues of these peptidyl carrier proteins upon their interaction with the adenylation domain. These experiments revealed a key region for the protein-protein interaction. Mutational studies supported the role of loop 1 in molecular recognition, as mutations to this region of the peptidyl carrier proteins significantly modulated their activities.

  6. Assessing reliability of protein-protein interactions by integrative analysis of data in model organisms.

    PubMed

    Lin, Xiaotong; Liu, Mei; Chen, Xue-wen

    2009-04-29

    Protein-protein interactions play vital roles in nearly all cellular processes and are involved in the construction of biological pathways such as metabolic and signal transduction pathways. Although large-scale experiments have enabled the discovery of thousands of previously unknown linkages among proteins in many organisms, the high-throughput interaction data is often associated with high error rates. Since protein interaction networks have been utilized in numerous biological inferences, the inclusive experimental errors inevitably affect the quality of such prediction. Thus, it is essential to assess the quality of the protein interaction data. In this paper, a novel Bayesian network-based integrative framework is proposed to assess the reliability of protein-protein interactions. We develop a cross-species in silico model that assigns likelihood scores to individual protein pairs based on the information entirely extracted from model organisms. Our proposed approach integrates multiple microarray datasets and novel features derived from gene ontology. Furthermore, the confidence scores for cross-species protein mappings are explicitly incorporated into our model. Applying our model to predict protein interactions in the human genome, we are able to achieve 80% in sensitivity and 70% in specificity. Finally, we assess the overall quality of the experimentally determined yeast protein-protein interaction dataset. We observe that the more high-throughput experiments confirming an interaction, the higher the likelihood score, which confirms the effectiveness of our approach. This study demonstrates that model organisms certainly provide important information for protein-protein interaction inference and assessment. The proposed method is able to assess not only the overall quality of an interaction dataset, but also the quality of individual protein-protein interactions. We expect the method to continually improve as more high quality interaction data from more

  7. Interactions of the α-subunits of heterotrimeric G-proteins with GPCRs, effectors and RGS proteins: a critical review and analysis of interacting surfaces, conformational shifts, structural diversity and electrostatic potentials.

    PubMed

    Baltoumas, Fotis A; Theodoropoulou, Margarita C; Hamodrakas, Stavros J

    2013-06-01

    G-protein coupled receptors (GPCRs) are one of the largest families of membrane receptors in eukaryotes. Heterotrimeric G-proteins, composed of α, β and γ subunits, are important molecular switches in the mediation of GPCR signaling. Receptor stimulation after the binding of a suitable ligand leads to G-protein heterotrimer activation and dissociation into the Gα subunit and Gβγ heterodimer. These subunits then interact with a large number of effectors, leading to several cell responses. We studied the interactions between Gα subunits and their binding partners, using information from structural, mutagenesis and Bioinformatics studies, and conducted a series of comparisons of sequence, structure, electrostatic properties and intermolecular energies among different Gα families and subfamilies. We identified a number of Gα surfaces that may, in several occasions, participate in interactions with receptors as well as effectors. The study of Gα interacting surfaces in terms of sequence, structure and electrostatic potential reveals features that may account for the Gα subunit's behavior towards its interacting partners. The electrostatic properties of the Gα subunits, which in some cases differ greatly not only between families but also between subfamilies, as well as the G-protein interacting surfaces of effectors and regulators of G-protein signaling (RGS) suggest that electrostatic complementarity may be an important factor in G-protein interactions. Energy calculations also support this notion. This information may be useful in future studies of G-protein interactions with GPCRs and effectors. Copyright © 2013 Elsevier Inc. All rights reserved.

  8. Bioluminescence resonance energy transfer system for measuring dynamic protein-protein interactions in bacteria.

    PubMed

    Cui, Boyu; Wang, Yao; Song, Yunhong; Wang, Tietao; Li, Changfu; Wei, Yahong; Luo, Zhao-Qing; Shen, Xihui

    2014-05-20

    Protein-protein interactions are important for virtually every biological process, and a number of elegant approaches have been designed to detect and evaluate such interactions. However, few of these methods allow the detection of dynamic and real-time protein-protein interactions in bacteria. Here we describe a bioluminescence resonance energy transfer (BRET) system based on the bacterial luciferase LuxAB. We found that enhanced yellow fluorescent protein (eYFP) accepts the emission from LuxAB and emits yellow fluorescence. Importantly, BRET occurred when LuxAB and eYFP were fused, respectively, to the interacting protein pair FlgM and FliA. Furthermore, we observed sirolimus (i.e., rapamycin)-inducible interactions between FRB and FKBP12 and a dose-dependent abolishment of such interactions by FK506, the ligand of FKBP12. Using this system, we showed that osmotic stress or low pH efficiently induced multimerization of the regulatory protein OmpR and that the multimerization induced by low pH can be reversed by a neutralizing agent, further indicating the usefulness of this system in the measurement of dynamic interactions. This method can be adapted to analyze dynamic protein-protein interactions and the importance of such interactions in bacterial processes such as development and pathogenicity. Real-time measurement of protein-protein interactions in prokaryotes is highly desirable for determining the roles of protein complex in the development or virulence of bacteria, but methods that allow such measurement are not available. Here we describe the development of a bioluminescence resonance energy transfer (BRET) technology that meets this need. The use of endogenous excitation light in this strategy circumvents the requirement for the sophisticated instrument demanded by standard fluorescence resonance energy transfer (FRET). Furthermore, because the LuxAB substrate decanal is membrane permeable, the assay can be performed without lysing the bacterial cells

  9. A force-based, parallel assay for the quantification of protein-DNA interactions.

    PubMed

    Limmer, Katja; Pippig, Diana A; Aschenbrenner, Daniela; Gaub, Hermann E

    2014-01-01

    Analysis of transcription factor binding to DNA sequences is of utmost importance to understand the intricate regulatory mechanisms that underlie gene expression. Several techniques exist that quantify DNA-protein affinity, but they are either very time-consuming or suffer from possible misinterpretation due to complicated algorithms or approximations like many high-throughput techniques. We present a more direct method to quantify DNA-protein interaction in a force-based assay. In contrast to single-molecule force spectroscopy, our technique, the Molecular Force Assay (MFA), parallelizes force measurements so that it can test one or multiple proteins against several DNA sequences in a single experiment. The interaction strength is quantified by comparison to the well-defined rupture stability of different DNA duplexes. As a proof-of-principle, we measured the interaction of the zinc finger construct Zif268/NRE against six different DNA constructs. We could show the specificity of our approach and quantify the strength of the protein-DNA interaction.

  10. 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).

  11. Characterization of a unique motif in LIM mineralization protein-1 that interacts with jun activation-domain-binding protein 1.

    PubMed

    Sangadala, Sreedhara; Yoshioka, Katsuhito; Enyo, Yoshio; Liu, Yunshan; Titus, Louisa; Boden, Scott D

    2014-01-01

    Development and repair of the skeletal system and other organs are highly dependent on precise regulation of the bone morphogenetic protein (BMP) pathway. The use of BMPs clinically to induce bone formation has been limited in part by the requirement of much higher doses of recombinant proteins in primates than were needed in cell culture or rodents. Therefore, increasing cellular responsiveness to BMPs has become our focus. We determined that an osteogenic LIM mineralization protein, LMP-1 interacts with Smurf1 (Smad ubiquitin regulatory factor 1) and prevents ubiquitination of Smads resulting in potentiation of BMP activity. In the region of LMP-1 responsible for bone formation, there is a motif that directly interacts with the Smurf1 WW2 domain and thus effectively competes for binding with Smad1 and Smad5, key signaling proteins in the BMP pathway. Here we show that the same region also contains a motif that interacts with Jun activation-domain-binding protein 1 (Jab1) which targets a common Smad, Smad4, shared by both the BMP and transforming growth factor-β (TGF-β) pathways, for proteasomal degradation. Jab1 was first identified as a coactivator of the transcription factor c-Jun. Jab1 binds to Smad4, Smad5, and Smad7, key intracellular signaling molecules of the TGF-β superfamily, and causes ubiquitination and/or degradation of these Smads. We confirmed a direct interaction of Jab1 with LMP-1 using recombinantly expressed wild-type and mutant proteins in slot-blot-binding assays. We hypothesized that LMP-1 binding to Jab1 prevents the binding and subsequent degradation of these Smads causing increased accumulation of osteogenic Smads in cells. We identified a sequence motif in LMP-1 that was predicted to interact with Jab1 based on the MAME/MAST sequence analysis of several cellular signaling molecules that are known to interact with Jab-1. We further mutated the potential key interacting residues in LMP-1 and showed loss of binding to Jab1 in binding

  12. Interactions of cullin3/KCTD5 complexes with both cytoplasmic and nuclear proteins: Evidence for a role in protein stabilization

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rutz, Natalja; Heilbronn, Regine; Weger, Stefan, E-mail: stefan.weger@charite.de

    2015-08-28

    Based on its specific interaction with cullin3 mediated by an N-terminal BTB/POZ homologous domain, KCTD5 has been proposed to function as substrate adapter for cullin3 based ubiquitin E3 ligases. In the present study we tried to validate this hypothesis through identification and characterization of additional KCTD5 interaction partners. For the replication protein MCM7, the zinc finger protein ZNF711 and FAM193B, a yet poorly characterized cytoplasmic protein, we could demonstrate specific interaction with KCTD5 both in yeast two-hybrid and co-precipitation studies in mammalian cells. Whereas trimeric complexes of cullin3 and KCTD5 with the respective KCTD5 binding partner were formed, KCTD5/cullin3 inducedmore » polyubiquitylation and/or proteasome-dependent degradation of these binding partners could not be demonstrated. On the contrary, KCTD5 or Cullin3 overexpression increased ZNF711 protein stability. - Highlights: • KCTD5 nuclear translocation depends upon M phase and protein oligomerization. • Identification of MCM7, ZNF711 and FAM193 as KCTD5 interaction partners. • Formation of trimeric complexes of KCTD5/cullin3 with MCM7, ZNF711 and FAM193B. • KCTD5 is not involved in polyubiquitylation of MCM7 replication factor. • The KCTD5/cullin3 complex stabilizes ZNF711 transcription factor.« less

  13. The interactions of peripheral membrane proteins with biological membranes

    DOE PAGES

    Johs, Alexander; Whited, A. M.

    2015-07-29

    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

  14. [Regulation on EGFR function via its interacting proteins and its potential application].

    PubMed

    Zheng, Jun-Fang; Chen, Hui-Min; He, Jun-Qi

    2013-12-01

    Epidermal growth factor receptor (EGFR) is imptortant for cell activities, oncogenesis and cell migration, and EGFR inhibitor can treat cancer efficiently, but its side effects, for example, in skin, limited its usage. On the other hand, EGFR interacting proteins may also lead to oncogenesis and its interacting protein as drug targets can avoid cutaneous side effect, which implies possibly a better outcome and life quality of cancer patients. For the multiple EGFR interaction proteins, B1R enhances Erk/MAPK signaling, while PTPN12, Kek1, CEACAM1 and NHERF repress Erk/MAPK signaling. CaM may alter charge of EGFR juxamembrane domain and regulate activation of PI3K/Akt and PLC-gamma/PKC. STAT1, STAT5b are widely thought to be activated by EGFR, while there is unexpectedly inhibiting sequence within EGFR to repress the activity of STATs. LRIG1 and ACK1 enhance the internalization and degration of EGFR, while NHERF and HIP1 repress it. In this article, proteins interacting with EGFR, their interacting sites and their regulation on EGFR signal transduction will be reviewed.

  15. New paradigm in ankyrin repeats: Beyond protein-protein interaction module.

    PubMed

    Islam, Zeyaul; Nagampalli, Raghavendra Sashi Krishna; Fatima, Munazza Tamkeen; Ashraf, Ghulam Md

    2018-04-01

    Classically, ankyrin repeat (ANK) proteins are built from tandems of two or more repeats and form curved solenoid structures that are associated with protein-protein interactions. These are short, widespread structural motif of around 33 amino acids repeats in tandem, having a canonical helix-loop-helix fold, found individually or in combination with other domains. The multiplicity of structural pattern enables it to form assemblies of diverse sizes, required for their abilities to confer multiple binding and structural roles of proteins. Three-dimensional structures of these repeats determined to date reveal a degree of structural variability that translates into the considerable functional versatility of this protein superfamily. Recent work on the ANK has proposed novel structural information, especially protein-lipid, protein-sugar and protein-protein interaction. Self-assembly of these repeats was also shown to prevent the associated protein in forming filaments. In this review, we summarize the latest findings and how the new structural information has increased our understanding of the structural determinants of ANK proteins. We discussed latest findings on how these proteins participate in various interactions to diversify the ANK roles in numerous biological processes, and explored the emerging and evolving field of designer ankyrins and its framework for protein engineering emphasizing on biotechnological applications. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. 3-Phosphoinositide-dependent PDK1 negatively regulates transforming growth factor-beta-induced signaling in a kinase-dependent manner through physical interaction with Smad proteins.

    PubMed

    Seong, Hyun-A; Jung, Haiyoung; Kim, Kyong-Tai; Ha, Hyunjung

    2007-04-20

    We have reported previously that PDK1 physically interacts with STRAP, a transforming growth factor-beta (TGF-beta) receptor-interacting protein, and enhances STRAP-induced inhibition of TGF-beta signaling. In this study we show that PDK1 coimmunoprecipitates with Smad proteins, including Smad2, Smad3, Smad4, and Smad7, and that this association is mediated by the pleckstrin homology domain of PDK1. The association between PDK1 and Smad proteins is increased by insulin treatment but decreased by TGF-beta treatment. Analysis of the interacting proteins shows that Smad proteins enhance PDK1 kinase activity by removing 14-3-3, a negative regulator of PDK1, from the PDK1-14-3-3 complex. Knockdown of endogenous Smad proteins, including Smad3 and Smad7, by transfection with small interfering RNA produced the opposite trend and decreased PDK1 activity, protein kinase B/Akt phosphorylation, and Bad phosphorylation. Moreover, coexpression of Smad proteins and wild-type PDK1 inhibits TGF-beta-induced transcription, as well as TGF-beta-mediated biological functions, such as apoptosis and cell growth arrest. Inhibition was dose-dependent on PDK1, but no inhibition was observed in the presence of an inactive kinase-dead PDK1 mutant. In addition, confocal microscopy showed that wild-type PDK1 prevents translocation of Smad3 and Smad4 from the cytoplasm to the nucleus, as well as the redistribution of Smad7 from the nucleus to the cytoplasm in response to TGF-beta. Taken together, our results suggest that PDK1 negatively regulates TGF-beta-mediated signaling in a PDK1 kinase-dependent manner via a direct physical interaction with Smad proteins and that Smad proteins can act as potential positive regulators of PDK1.

  17. A tandem affinity purification tag of TGA2 for isolation of interacting proteins in Arabidopsis thaliana

    PubMed Central

    Stotz, Henrik U; Findling, Simone; Nukarinen, Ella; Weckwerth, Wolfram; Mueller, Martin J; Berger, Susanne

    2014-01-01

    Tandem affinity purification (TAP) tagging provides a powerful tool for isolating interacting proteins in vivo. TAP-tag purification offers particular advantages for the identification of stimulus-induced protein interactions. Type II bZIP transcription factors (TGA2, TGA5 and TGA6) play key roles in pathways that control salicylic acid, ethylene, xenobiotic and reactive oxylipin signaling. Although proteins interacting with these transcription factors have been identified through genetic and yeast 2-hybrid screening, others are still elusive. We have therefore generated a C-terminal TAP-tag of TGA2 to isolate additional proteins that interact with this transcription factor. Three lines most highly expressing TAP-tagged TGA2 were functional in that they partially complemented reactive oxylipin-responsive gene expression in a tga2 tga5 tga6 triple mutant. TAP-tagged TGA2 in the most strongly overexpressing line was proteolytically less stable than in the other 2 lines. Only this overexpressing line could be used in a 2-step purification process, resulting in isolation of co-purifying bands of larger molecular weight than TGA2. TAP-tagged TGA2 was used to pull down NPR1, a protein known to interact with this transcription factor. Mass spectrometry was used to identify peptides that co-purified with TAP-tagged TGA2. Having generated this TGA2 TAP-tag line will therefore be an asset to researchers interested in stimulus-induced signal transduction processes. PMID:25482810

  18. A rice kinase-protein interaction map.

    PubMed

    Ding, Xiaodong; Richter, Todd; Chen, Mei; Fujii, Hiroaki; Seo, Young Su; Xie, Mingtang; Zheng, Xianwu; Kanrar, Siddhartha; Stevenson, Rebecca A; Dardick, Christopher; Li, Ying; Jiang, Hao; Zhang, Yan; Yu, Fahong; Bartley, Laura E; Chern, Mawsheng; Bart, Rebecca; Chen, Xiuhua; Zhu, Lihuang; Farmerie, William G; Gribskov, Michael; Zhu, Jian-Kang; Fromm, Michael E; Ronald, Pamela C; Song, Wen-Yuan

    2009-03-01

    Plants uniquely contain large numbers of protein kinases, and for the vast majority of the 1,429 kinases predicted in the rice (Oryza sativa) genome, little is known of their functions. Genetic approaches often fail to produce observable phenotypes; thus, new strategies are needed to delineate kinase function. We previously developed a cost-effective high-throughput yeast two-hybrid system. Using this system, we have generated a protein interaction map of 116 representative rice kinases and 254 of their interacting proteins. Overall, the resulting interaction map supports a large number of known or predicted kinase-protein interactions from both plants and animals and reveals many new functional insights. Notably, we found a potential widespread role for E3 ubiquitin ligases in pathogen defense signaling mediated by receptor-like kinases, particularly by the kinases that may have evolved from recently expanded kinase subfamilies in rice. We anticipate that the data provided here will serve as a foundation for targeted functional studies in rice and other plants. The application of yeast two-hybrid and TAPtag analyses for large-scale plant protein interaction studies is also discussed.

  19. NPIDB: Nucleic acid-Protein Interaction DataBase.

    PubMed

    Kirsanov, Dmitry D; Zanegina, Olga N; Aksianov, Evgeniy A; Spirin, Sergei A; Karyagina, Anna S; Alexeevski, Andrei V

    2013-01-01

    The Nucleic acid-Protein Interaction DataBase (http://npidb.belozersky.msu.ru/) contains information derived from structures of DNA-protein and RNA-protein complexes extracted from the Protein Data Bank (3846 complexes in October 2012). It provides a web interface and a set of tools for extracting biologically meaningful characteristics of nucleoprotein complexes. The content of the database is updated weekly. The current version of the Nucleic acid-Protein Interaction DataBase is an upgrade of the version published in 2007. The improvements include a new web interface, new tools for calculation of intermolecular interactions, a classification of SCOP families that contains DNA-binding protein domains and data on conserved water molecules on the DNA-protein interface.

  20. 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.

  1. A Luciferase-fragment Complementation Assay to Detect Lipid Droplet-associated Protein-Protein Interactions*

    PubMed Central

    Kolkhof, Petra; Werthebach, Michael; van de Venn, Anna; Poschmann, Gereon; Chen, Lili; Welte, Michael; Stühler, Kai; Beller, Mathias

    2017-01-01

    A critical challenge for all organisms is to carefully control the amount of lipids they store. An important node for this regulation is the protein coat present at the surface of lipid droplets (LDs), the intracellular organelles dedicated to lipid storage. Only limited aspects of this regulation are understood so far. For the probably best characterized case, the regulation of lipolysis in mammals, some of the major protein players have been identified, and it has been established that this process crucially depends on an orchestrated set of protein-protein interactions. Proteomic analysis has revealed that LDs are associated with dozens, if not hundreds, of different proteins, most of them poorly characterized, with even fewer data regarding which of them might physically interact. To comprehensively understand the mechanism of lipid storage regulation, it will likely be essential to define the interactome of LD-associated proteins. Previous studies of such interactions were hampered by technical limitations. Therefore, we have developed a split-luciferase based protein-protein interaction assay and test for interactions among 47 proteins from Drosophila and from mouse. We confirmed previously described interactions and identified many new ones. In 1561 complementation tests, we assayed for interactions among 487 protein pairs of which 92 (19%) resulted in a successful luciferase complementation. These results suggest that a prominent fraction of the LD-associated proteome participates in protein-protein interactions. In targeted experiments, we analyzed the two proteins Jabba and CG9186 in greater detail. Jabba mediates the sequestration of histones to LDs. We successfully applied our split luciferase complementation assay to learn more about this function as we were e.g. able to map the interaction between Jabba and histones. For CG9186, expression levels affect the positioning of LDs. Here, we reveal the ubiquitination of CG9186, and link this

  2. Course 1: Physics of Protein-DNA Interaction

    NASA Astrophysics Data System (ADS)

    Bruinsma, R. F.

    1 Introduction 1.1 The central dogma and bacterial gene expression 1.2 Molecular structure 2 Thermodynamics and kinetics of repressor-DNA interaction 2.1 Thermodynamics and the lac repressor 2.2 Kinetics of repressor-DNA interaction 3 DNA deformability and protein-DNA interaction 3.1 Introduction 3.2 The worm-like chain 3.3 The RST model 4 Electrostatics in water and protein-DNA interaction 4.1 Macro-ions and aqueous electrostatics 4.2 The primitive model 4.3 Manning condensation 4.4 Counter-ion release and non-specific protein-DNA interaction

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

    PubMed

    Rezende, Antonio M; Folador, Edson L; Resende, Daniela de M; Ruiz, Jeronimo C

    2012-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  5. Defining the Protein–Protein Interaction Network of the Human Hippo Pathway*

    PubMed Central

    Wang, Wenqi; Li, Xu; Huang, Jun; Feng, Lin; Dolinta, Keithlee G.; Chen, Junjie

    2014-01-01

    The Hippo pathway, which is conserved from Drosophila to mammals, has been recognized as a tumor suppressor signaling pathway governing cell proliferation and apoptosis, two key events involved in organ size control and tumorigenesis. Although several upstream regulators, the conserved kinase cascade and key downstream effectors including nuclear transcriptional factors have been defined, the global organization of this signaling pathway is not been fully understood. Thus, we conducted a proteomic analysis of human Hippo pathway, which revealed the involvement of an extensive protein–protein interaction network in this pathway. The mass spectrometry data were deposited to ProteomeXchange with identifier PXD000415. Our data suggest that 550 interactions within 343 unique protein components constitute the central protein–protein interaction landscape of human Hippo pathway. Our study provides a glimpse into the global organization of Hippo pathway, reveals previously unknown interactions within this pathway, and uncovers new potential components involved in the regulation of this pathway. Understanding these interactions will help us further dissect the Hippo signaling-pathway and extend our knowledge of organ size control. PMID:24126142

  6. Identification of proteins interacting with Toxoplasma SRCAP by yeast two-hybrid screening.

    PubMed

    Nallani, Karuna C; Sullivan, William J

    2005-03-01

    Toxoplasma gondii is an opportunistic protozoan parasite that differentiates into latent cysts (bradyzoite) that can be reactivated during immunosuppression. TgSRCAP (Toxoplasma gondii Snf2-related CBP activator protein) is a SWI2/SNF2 family chromatin remodeler whose expression increases during cyst development. Identifying the proteins associating with TgSRCAP during the pre-cyst stage (tachyzoite) will increase our understanding of how parasite differentiation is initiated. We employed the yeast two-hybrid system to identify proteins that may interact directly with TgSRCAP. A stretch of 1,060 amino acids between ATPase subdomains IV and V of TgSRCAP was chosen as "bait" since the corresponding region in human SRCAP interacts with other proteins, including CREB binding protein. We have identified several novel parasite-specific transcription factors predicted to be in the T. gondii genome. Metabolic enzymes that may participate in cyst development were also identified as interacting with TgSRCAP.

  7. BindML/BindML+: Detecting Protein-Protein Interaction Interface Propensity from Amino Acid Substitution Patterns.

    PubMed

    Wei, Qing; La, David; Kihara, Daisuke

    2017-01-01

    Prediction of protein-protein interaction sites in a protein structure provides important information for elucidating the mechanism of protein function and can also be useful in guiding a modeling or design procedures of protein complex structures. Since prediction methods essentially assess the propensity of amino acids that are likely to be part of a protein docking interface, they can help in designing protein-protein interactions. Here, we introduce BindML and BindML+ protein-protein interaction sites prediction methods. BindML predicts protein-protein interaction sites by identifying mutation patterns found in known protein-protein complexes using phylogenetic substitution models. BindML+ is an extension of BindML for distinguishing permanent and transient types of protein-protein interaction sites. We developed an interactive web-server that provides a convenient interface to assist in structural visualization of protein-protein interactions site predictions. The input data for the web-server are a tertiary structure of interest. BindML and BindML+ are available at http://kiharalab.org/bindml/ and http://kiharalab.org/bindml/plus/ .

  8. 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. © 2015 The Protein Society.

  9. Energetics of protein-DNA interactions.

    PubMed

    Donald, Jason E; Chen, William W; Shakhnovich, Eugene I

    2007-01-01

    Protein-DNA interactions are vital for many processes in living cells, especially transcriptional regulation and DNA modification. To further our understanding of these important processes on the microscopic level, it is necessary that theoretical models describe the macromolecular interaction energetics accurately. While several methods have been proposed, there has not been a careful comparison of how well the different methods are able to predict biologically important quantities such as the correct DNA binding sequence, total binding free energy and free energy changes caused by DNA mutation. In addition to carrying out the comparison, we present two important theoretical models developed initially in protein folding that have not yet been tried on protein-DNA interactions. In the process, we find that the results of these knowledge-based potentials show a strong dependence on the interaction distance and the derivation method. Finally, we present a knowledge-based potential that gives comparable or superior results to the best of the other methods, including the molecular mechanics force field AMBER99.

  10. Single Molecule Approaches in RNA-Protein Interactions.

    PubMed

    Serebrov, Victor; Moore, Melissa J

    RNA-protein interactions govern every aspect of RNA metabolism, and aberrant RNA-binding proteins are the cause of hundreds of genetic diseases. Quantitative measurements of these interactions are necessary in order to understand mechanisms leading to diseases and to develop efficient therapies. Existing methods of RNA-protein interactome capture can afford a comprehensive snapshot of RNA-protein interaction networks but lack the ability to characterize the dynamics of these interactions. As all ensemble methods, their resolution is also limited by statistical averaging. Here we discuss recent advances in single molecule techniques that have the potential to tackle these challenges. We also provide a thorough overview of single molecule colocalization microscopy and the essential protein and RNA tagging and detection techniques.

  11. 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.

  12. Monitoring Ligand-Activated Protein-Protein Interactions Using Bioluminescent Resonance Energy Transfer (BRET) Assay.

    PubMed

    Coriano, Carlos; Powell, Emily; Xu, Wei

    2016-01-01

    The bioluminescent resonance energy transfer (BRET) assay has been extensively used in cell-based and in vivo imaging systems for detecting protein-protein interactions in the native environment of living cells. These protein-protein interactions are essential for the functional response of many signaling pathways to environmental chemicals. BRET has been used as a toxicological tool for identifying chemicals that either induce or inhibit these protein-protein interactions. This chapter focuses on describing the toxicological applications of BRET and its optimization as a high-throughput detection system in live cells. Here we review the construction of BRET fusion proteins, describe the BRET methodology, and outline strategies to overcome obstacles that may arise. Furthermore, we describe the advantage of BRET over other resonance energy transfer methods for monitoring protein-protein interactions.

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

    PubMed Central

    García-López, M Carmen

    2011-01-01

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

  14. TPPII, MYBBP1A and CDK2 form a protein-protein interaction network.

    PubMed

    Nahálková, Jarmila; Tomkinson, Birgitta

    2014-12-15

    Tripeptidyl-peptidase II (TPPII) is an aminopeptidase with suggested regulatory effects on cell cycle, apoptosis and senescence. A protein-protein interaction study revealed that TPPII physically interacts with the tumor suppressor MYBBP1A and the cell cycle regulator protein CDK2. Mutual protein-protein interaction was detected between MYBBP1A and CDK2 as well. In situ Proximity Ligation Assay (PLA) using HEK293 cells overexpressing TPPII forming highly enzymatically active oligomeric complexes showed that the cytoplasmic interaction frequency of TPPII with MYBBP1A increased with the protein expression of TPPII and using serum-free cell growth conditions. A specific reversible inhibitor of TPPII, butabindide, suppressed the cytoplasmic interactions of TPPII and MYBBP1A both in control HEK293 and the cells overexpressing murine TPPII. The interaction of MYBBP1A with CDK2 was confirmed by in situ PLA in two different mammalian cell lines. Functional link between TPPII and MYBBP1A has been verified by gene expression study during anoikis, where overexpression of TPP II decreased mRNA expression level of MYBBP1A at the cell detachment conditions. All three interacting proteins TPPII, MYBBP1A and CDK2 have been previously implicated in the research for development of tumor-suppressing agents. This is the first report presenting mutual protein-protein interaction network of these proteins. Copyright © 2014 Elsevier Inc. All rights reserved.

  15. Interactions of phosphatidylinositol kinase, GTPase-activating protein (GAP), and GAP-associated proteins with the colony-stimulating factor 1 receptor.

    PubMed Central

    Reedijk, M; Liu, X Q; Pawson, T

    1990-01-01

    The interactions of the macrophage colony-stimulating factor 1 (CSF-1) receptor with potential targets were investigated after ligand stimulation either of mouse macrophages or of fibroblasts that ectopically express mouse CSF-1 receptors. In Rat-2 cells expressing the mouse CSF-1 receptor, full activation of the receptor and cellular transformation require exogenous CSF-1, whereas NIH 3T3 cells expressing mouse c-fms are transformed by autocrine stimulation. Activated CSF-1 receptors physically associate with a phosphatidylinositol (PI) 3'-kinase. A mutant CSF-1 receptor with a deletion of the kinase insert region was deficient in its ability to bind functional PI 3'-kinase and to induce PI 3'-kinase activity precipitable with antiphosphotyrosine antibodies. In fibroblasts, CSF-1 stimulation also induced the phosphorylation of the GTPase-activating protein (GAP)-associated protein p62 on tyrosine, although GAP itself was a relatively poor substrate. In contrast to PI 3'-kinase association, phosphorylation of p62 and GAP was not markedly affected by deletion of the kinase insert region. These results indicate that the kinase insert region selectively enhances the CSF-1-dependent association of the CSF-1 receptor with active PI 3'-kinase. The insert deletion mutant retains considerable transforming activity in NIH 3T3 cells (G. Taylor, M. Reedijk, V. Rothwell, L. Rohrschneider, and T. Pawson, EMBO J. 8:2029-2037, 1989). This mutant was more seriously impaired in Rat-2 cell transformation, although mutant-expressing Rat-2 cells still formed small colonies in soft agar in the presence of CSF-1. Therefore, phosphorylation of GAP and p62 through activation of the CSF-1 receptor does not result in full fibroblast transformation. The interaction between the CSF-1 receptor and PI 3'-kinase may contribute to c-fms fibroblast transformation and play a role in CSF-1-stimulated macrophages. Images PMID:2172781

  16. Rice phytochrome-interacting factor protein OsPIFff14 represses OsDREB1B gene expression through an extended N-box and interacts preferentially with the active form of phytochrome B

    USDA-ARS?s Scientific Manuscript database

    DREB1/CBF genes, known as major regulators of plant stress responses, are rapidly and transiently induced by low temperatures. Using a Yeast one Hybrid screening, we identified a putative Phytochrome-Interacting bHLH Factor (OsPIF14), as binding to the OsDREB1B promoter. bHLH proteins are able to bi...

  17. Free energy decomposition of protein-protein interactions.

    PubMed

    Noskov, S Y; Lim, C

    2001-08-01

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

  18. Protein interactions in concentrated ribonuclease solutions

    NASA Astrophysics Data System (ADS)

    Boyer, Mireille; Roy, Marie-Odile; Jullien, Magali; Bonneté, Françoise; Tardieu, Annette

    1999-01-01

    To investigate the protein interactions involved in the crystallization process of ribonuclease A, dynamic light scattering (DLS) and small angle X-ray scattering experiments (SAXS) were performed on concentrated solutions. Whereas the translational diffusion coefficient obtained from DLS is sensitive to thermodynamic and hydrodynamic interactions and permits to calculate an interaction parameter, the shape of the SAXS curves is related to the type of interaction (attractive or repulsive). We compared the effect of pH on protein interactions in the case of two types of crystallizing agents: a mixture of salts (3 M sodium chloride plus 0.2 M ammonium sulfate) and an organic solvent (ethanol). The results show that in the presence of ethanol, as in low salt, protein interactions become more attractive as the pH increases from 4 to 8 and approaches the isoelectric point. In contrast, a reverse effect is observed in high salt conditions: the strength of attractive interactions decreases as the pH increases. The range of the pH effect can be related to ionization of histidine residues, particularly those located in the active site of the protein. The present observations point out the important role played by localized charges in crystallization conditions, whatever the precipitating agent.

  19. 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.

  20. 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. Copyright © 2012 Wiley Periodicals, Inc.

  1. Pestivirus Npro Directly Interacts with Interferon Regulatory Factor 3 Monomer and Dimer

    PubMed Central

    Holthauzen, Luis Marcelo F.; Ruggli, Nicolas

    2016-01-01

    ABSTRACT Interferon regulatory factor 3 (IRF3) is a transcription factor involved in the activation of type I alpha/beta interferon (IFN-α/β) in response to viral infection. Upon viral infection, the IRF3 monomer is activated into a phosphorylated dimer, which induces the transcription of interferon genes in the nucleus. Viruses have evolved several ways to target IRF3 in order to subvert the innate immune response. Pestiviruses, such as classical swine fever virus (CSFV), target IRF3 for ubiquitination and subsequent proteasomal degradation. This is mediated by the viral protein Npro that interacts with IRF3, but the molecular details for this interaction are largely unknown. We used recombinant Npro and IRF3 proteins and show that Npro interacts with IRF3 directly without additional proteins and forms a soluble 1:1 complex. The full-length IRF3 but not merely either of the individual domains is required for this interaction. The interaction between Npro and IRF3 is not dependent on the activation state of IRF3, since Npro binds to a constitutively active form of IRF3 in the presence of its transcriptional coactivator, CREB-binding protein (CBP). The results indicate that the Npro-binding site on IRF3 encompasses a region that is unperturbed by the phosphorylation and subsequent activation of IRF3 and thus excludes the dimer interface and CBP-binding site. IMPORTANCE The pestivirus N-terminal protease, Npro, is essential for evading the host's immune system by facilitating the degradation of interferon regulatory factor 3 (IRF3). However, the nature of the Npro interaction with IRF3, including the IRF3 species (inactive monomer versus activated dimer) that Npro targets for degradation, is largely unknown. We show that classical swine fever virus Npro and porcine IRF3 directly interact in solution and that full-length IRF3 is required for interaction with Npro. Additionally, Npro interacts with a constitutively active form of IRF3 bound to its transcriptional

  2. A new protein-protein interaction sensor based on tripartite split-GFP association.

    PubMed

    Cabantous, Stéphanie; Nguyen, Hau B; Pedelacq, Jean-Denis; Koraïchi, Faten; Chaudhary, Anu; Ganguly, Kumkum; Lockard, Meghan A; Favre, Gilles; Terwilliger, Thomas C; Waldo, Geoffrey S

    2013-10-04

    Monitoring protein-protein interactions in living cells is key to unraveling their roles in numerous cellular processes and various diseases. Previously described split-GFP based sensors suffer from poor folding and/or self-assembly background fluorescence. Here, we have engineered a micro-tagging system to monitor protein-protein interactions in vivo and in vitro. The assay is based on tripartite association between two twenty amino-acids long GFP tags, GFP10 and GFP11, fused to interacting protein partners, and the complementary GFP1-9 detector. When proteins interact, GFP10 and GFP11 self-associate with GFP1-9 to reconstitute a functional GFP. Using coiled-coils and FRB/FKBP12 model systems we characterize the sensor in vitro and in Escherichia coli. We extend the studies to mammalian cells and examine the FK-506 inhibition of the rapamycin-induced association of FRB/FKBP12. The small size of these tags and their minimal effect on fusion protein behavior and solubility should enable new experiments for monitoring protein-protein association by fluorescence.

  3. A New Protein-Protein Interaction Sensor Based on Tripartite Split-GFP Association

    PubMed Central

    Cabantous, Stéphanie; Nguyen, Hau B.; Pedelacq, Jean-Denis; Koraïchi, Faten; Chaudhary, Anu; Ganguly, Kumkum; Lockard, Meghan A.; Favre, Gilles; Terwilliger, Thomas C.; Waldo, Geoffrey S.

    2013-01-01

    Monitoring protein-protein interactions in living cells is key to unraveling their roles in numerous cellular processes and various diseases. Previously described split-GFP based sensors suffer from poor folding and/or self-assembly background fluorescence. Here, we have engineered a micro-tagging system to monitor protein-protein interactions in vivo and in vitro. The assay is based on tripartite association between two twenty amino-acids long GFP tags, GFP10 and GFP11, fused to interacting protein partners, and the complementary GFP1-9 detector. When proteins interact, GFP10 and GFP11 self-associate with GFP1-9 to reconstitute a functional GFP. Using coiled-coils and FRB/FKBP12 model systems we characterize the sensor in vitro and in Escherichia coli. We extend the studies to mammalian cells and examine the FK-506 inhibition of the rapamycin-induced association of FRB/FKBP12. The small size of these tags and their minimal effect on fusion protein behavior and solubility should enable new experiments for monitoring protein-protein association by fluorescence. PMID:24092409

  4. Histone and RNA-binding protein interaction creates crosstalk network for regulation of alternative splicing.

    PubMed

    Kim, Yong-Eun; Park, Chungoo; Kim, Kyoon Eon; Kim, Kee K

    2018-04-30

    Alternative splicing is an essential process in eukaryotes, as it increases the complexity of gene expression by generating multiple proteins from a single pre-mRNA. However, information on the regulatory mechanisms for alternative splicing is lacking, because splicing occurs over a short period via the transient interactions of proteins within functional complexes of the spliceosome. Here, we investigated in detail the molecular mechanisms connecting alternative splicing with epigenetic mechanisms. We identified interactions between histone proteins and splicing factors such as Rbfox2, Rbfox3, and splicing factor proline and glutamine rich protein (SFPQ) by in vivo crosslinking and immunoprecipitation. Furthermore, we confirmed that splicing factors were bound to specific modified residues of histone proteins. Additionally, changes in histone methylation due to histone methyltransferase inhibitor treatment notably affected alternative splicing in selected genes. Therefore, we suggested that there may be crosstalk mechanisms connecting histone modifications and RNA-binding proteins that increase the local concentration of RNA-binding proteins in alternative exon loci of nucleosomes by binding specific modified histone proteins, leading to alternative splicing. This crosstalk mechanism may play a major role in epigenetic processes such as histone modification and the regulation of alternative splicing. Copyright © 2018 Elsevier Inc. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

    Zhang, Zhe; Witham, Shawn; Alexov, Emil

    2011-06-01

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

  6. Quantitative assessment of RNA-protein interactions with high-throughput sequencing-RNA affinity profiling.

    PubMed

    Ozer, Abdullah; Tome, Jacob M; Friedman, Robin C; Gheba, Dan; Schroth, Gary P; Lis, John T

    2015-08-01

    Because RNA-protein interactions have a central role in a wide array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay that couples sequencing on an Illumina GAIIx genome analyzer with the quantitative assessment of protein-RNA interactions. This assay is able to analyze interactions between one or possibly several proteins with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of the EGFP and negative elongation factor subunit E (NELF-E) proteins with their corresponding canonical and mutant RNA aptamers. Here we provide a detailed protocol for HiTS-RAP that can be completed in about a month (8 d hands-on time). This includes the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, HiTS and protein binding with a GAIIx instrument, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, quantitative analysis of RNA on a massively parallel array (RNA-MaP) and RNA Bind-n-Seq (RBNS), for quantitative analysis of RNA-protein interactions.

  7. Combining random gene fission and rational gene fusion to discover near-infrared fluorescent protein fragments that report on protein-protein interactions.

    PubMed

    Pandey, Naresh; Nobles, Christopher L; Zechiedrich, Lynn; Maresso, Anthony W; Silberg, Jonathan J

    2015-05-15

    Gene fission can convert monomeric proteins into two-piece catalysts, reporters, and transcription factors for systems and synthetic biology. However, some proteins can be challenging to fragment without disrupting function, such as near-infrared fluorescent protein (IFP). We describe a directed evolution strategy that can overcome this challenge by randomly fragmenting proteins and concomitantly fusing the protein fragments to pairs of proteins or peptides that associate. We used this method to create libraries that express fragmented IFP as fusions to a pair of associating peptides (IAAL-E3 and IAAL-K3) and proteins (CheA and CheY) and screened for fragmented IFP with detectable near-infrared fluorescence. Thirteen novel fragmented IFPs were identified, all of which arose from backbone fission proximal to the interdomain linker. Either the IAAL-E3 and IAAL-K3 peptides or CheA and CheY proteins could assist with IFP fragment complementation, although the IAAL-E3 and IAAL-K3 peptides consistently yielded higher fluorescence. These results demonstrate how random gene fission can be coupled to rational gene fusion to create libraries enriched in fragmented proteins with AND gate logic that is dependent upon a protein-protein interaction, and they suggest that these near-infrared fluorescent protein fragments will be suitable as reporters for pairs of promoters and protein-protein interactions within whole animals.

  8. Interaction of the Tumor Suppressor p53 with Replication Protein A.

    DTIC Science & Technology

    1996-08-01

    The DNA replication factor RPA physically associates with the tumor suppressor protein p53, an interaction that could be important for the function...binding single-stranded DNA, this mutant of RPA fails to support DNA replication . Therefore the region of RPA which interacts with p53 is essential for...of p53, p21/WAFl/CIPl, inhibits the cell-cycle by associating with cyclin-cdk kinases. It also inhibits DNA replication by interacting with a

  9. Ménage à trois: the complex relationships between mitogen-activated protein kinases, WRKY transcription factors, and VQ-motif-containing proteins.

    PubMed

    Weyhe, Martin; Eschen-Lippold, Lennart; Pecher, Pascal; Scheel, Dierk; Lee, Justin

    2014-01-01

    Out of the 34 members of the VQ-motif-containing protein (VQP) family, 10 are phosphorylated by the mitogen-activated protein kinases (MAPKs), MPK3 and MPK6. Most of these MPK3/6-targeted VQPs (MVQs) interacted with specific sub-groups of WRKY transcription factors in a VQ-motif-dependent manner. In some cases, the MAPK appears to phosphorylate either the MVQ or the WRKY, while in other cases, both proteins have been reported to act as MAPK substrates. We propose a network of dynamic interactions between members from the MAPK, MVQ and WRKY families - either as binary or as tripartite interactions. The compositions of the WRKY-MVQ transcriptional protein complexes may change - for instance, through MPK3/6-mediated modulation of protein stability - and therefore control defense gene transcription.

  10. RAIN: RNA–protein Association and Interaction Networks

    PubMed Central

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

    2017-01-01

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

  11. Evidence for dynamically organized modularity in the yeast protein-protein interaction network

    NASA Astrophysics Data System (ADS)

    Han, Jing-Dong J.; Bertin, Nicolas; Hao, Tong; Goldberg, Debra S.; Berriz, Gabriel F.; Zhang, Lan V.; Dupuy, Denis; Walhout, Albertha J. M.; Cusick, Michael E.; Roth, Frederick P.; Vidal, Marc

    2004-07-01

    In apparently scale-free protein-protein interaction networks, or `interactome' networks, most proteins interact with few partners, whereas a small but significant proportion of proteins, the `hubs', interact with many partners. Both biological and non-biological scale-free networks are particularly resistant to random node removal but are extremely sensitive to the targeted removal of hubs. A link between the potential scale-free topology of interactome networks and genetic robustness seems to exist, because knockouts of yeast genes encoding hubs are approximately threefold more likely to confer lethality than those of non-hubs. Here we investigate how hubs might contribute to robustness and other cellular properties for protein-protein interactions dynamically regulated both in time and in space. We uncovered two types of hub: `party' hubs, which interact with most of their partners simultaneously, and `date' hubs, which bind their different partners at different times or locations. Both in silico studies of network connectivity and genetic interactions described in vivo support a model of organized modularity in which date hubs organize the proteome, connecting biological processes-or modules -to each other, whereas party hubs function inside modules.

  12. Linker histone H1.0 interacts with an extensive network of proteins found in the nucleolus

    PubMed Central

    Kalashnikova, Anna A.; Winkler, Duane D.; McBryant, Steven J.; Henderson, Ryan K.; Herman, Jacob A.; DeLuca, Jennifer G.; Luger, Karolin; Prenni, Jessica E.; Hansen, Jeffrey C.

    2013-01-01

    The H1 linker histones are abundant chromatin-associated DNA-binding proteins. Recent evidence suggests that linker histones also may function through protein–protein interactions. To gain a better understanding of the scope of linker histone involvement in protein–protein interactions, we used a proteomics approach to identify H1-binding proteins in human nuclear extracts. Full-length H1.0 and H1.0 lacking its C-terminal domain (CTD) were used for protein pull-downs. A total of 107 candidate H1.0 binding proteins were identified by LC-MS/MS. About one-third of the H1.0-dependent interactions were mediated by the CTD, and two-thirds by the N-terminal domain-globular domain fragment. Many of the proteins pulled down by H1.0 were core splicing factors. Another group of H1-binding proteins functions in rRNA biogenesis. H1.0 also pulled down numerous ribosomal proteins and proteins involved in cellular transport. Strikingly, nearly all of the H1.0-binding proteins are found in the nucleolus. Quantitative biophysical studies with recombinant proteins confirmed that H1.0 directly binds to FACT and the splicing factors SF2/ASF and U2AF65. Our results demonstrate that H1.0 interacts with an extensive network of proteins that function in RNA metabolism in the nucleolus, and suggest that a new paradigm for linker histone action is in order. PMID:23435226

  13. 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

  14. PCPPI: a comprehensive database for the prediction of Penicillium-crop protein-protein interactions.

    PubMed

    Yue, Junyang; Zhang, Danfeng; Ban, Rongjun; Ma, Xiaojing; Chen, Danyang; Li, Guangwei; Liu, Jia; Wisniewski, Michael; Droby, Samir; Liu, Yongsheng

    2017-01-01

    Penicillium expansum , the causal agent of blue mold, is one of the most prevalent post-harvest pathogens, infecting a wide range of crops after harvest. In response, crops have evolved various defense systems to protect themselves against this and other pathogens. Penicillium -crop interaction is a multifaceted process and mediated by pathogen- and host-derived proteins. Identification and characterization of the inter-species protein-protein interactions (PPIs) are fundamental to elucidating the molecular mechanisms underlying infection processes between P. expansum and plant crops. Here, we have developed PCPPI, the Penicillium -Crop Protein-Protein Interactions database, which is constructed based on the experimentally determined orthologous interactions in pathogen-plant systems and available domain-domain interactions (DDIs) in each PPI. Thus far, it stores information on 9911 proteins, 439 904 interactions and seven host species, including apple, kiwifruit, maize, pear, rice, strawberry and tomato. Further analysis through the gene ontology (GO) annotation indicated that proteins with more interacting partners tend to execute the essential function. Significantly, semantic statistics of the GO terms also provided strong support for the accuracy of our predicted interactions in PCPPI. We believe that all the PCPPI datasets are helpful to facilitate the study of pathogen-crop interactions and freely available to the research community. : http://bdg.hfut.edu.cn/pcppi/index.html. © The Author(s) 2017. Published by Oxford University Press.

  15. Hexahistidine (6xHis) fusion-based assays for protein-protein interactions.

    PubMed

    Puckett, Mary C

    2015-01-01

    Fusion-protein tags provide a useful method to study protein-protein interactions. One widely used fusion tag is hexahistidine (6xHis). This tag has unique advantages over others due to its small size and the relatively low abundance of naturally occurring consecutive histidine repeats. 6xHis tags can interact with immobilized metal cations to provide for the capture of proteins and protein complexes of interest. In this chapter, a description of the benefits and uses of 6xHis-fusion proteins as well as a detailed method for performing a 6xHis-pulldown assay are described.

  16. An attempt to understand glioma stem cell biology through centrality analysis of a protein interaction network.

    PubMed

    Mallik, Mrinmay Kumar

    2018-02-07

    Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that

  17. PLIP: fully automated protein-ligand interaction profiler.

    PubMed

    Salentin, Sebastian; Schreiber, Sven; Haupt, V Joachim; Adasme, Melissa F; Schroeder, Michael

    2015-07-01

    The characterization of interactions in protein-ligand complexes is essential for research in structural bioinformatics, drug discovery and biology. However, comprehensive tools are not freely available to the research community. Here, we present the protein-ligand interaction profiler (PLIP), a novel web service for fully automated detection and visualization of relevant non-covalent protein-ligand contacts in 3D structures, freely available at projects.biotec.tu-dresden.de/plip-web. The input is either a Protein Data Bank structure, a protein or ligand name, or a custom protein-ligand complex (e.g. from docking). In contrast to other tools, the rule-based PLIP algorithm does not require any structure preparation. It returns a list of detected interactions on single atom level, covering seven interaction types (hydrogen bonds, hydrophobic contacts, pi-stacking, pi-cation interactions, salt bridges, water bridges and halogen bonds). PLIP stands out by offering publication-ready images, PyMOL session files to generate custom images and parsable result files to facilitate successive data processing. The full python source code is available for download on the website. PLIP's command-line mode allows for high-throughput interaction profiling. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  18. Regulation of PXR and CAR by protein-protein interaction and signaling crosstalk

    PubMed Central

    Oladimeji, Peter; Cui, Hongmei; Zhang, Chen; Chen, Taosheng

    2016-01-01

    Introduction Protein-protein interaction and signaling crosstalk contribute to the regulation of pregnane X receptor (PXR) and constitutive androstane receptor (CAR) and broaden their cellular function. Area covered This review covers key historic discoveries and recent advances in our understanding of the broad function of PXR and CAR and their regulation by protein-protein interaction and signaling crosstalk. Expert opinion PXR and CAR were first discovered as xenobiotic receptors. However, it is clear that PXR and CAR perform a much broader range of cellular functions through protein-protein interaction and signaling crosstalk, which typically mutually affect the function of all the partners involved. Future research on PXR and CAR should, therefore, look beyond their xenobiotic function. PMID:27295009

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

    PubMed Central

    Zhang, Zhe; Witham, Shawn; Alexov, Emil

    2011-01-01

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

  20. Inhibition of Interferon Regulatory Factor 3 Activation by Paramyxovirus V Protein

    PubMed Central

    Irie, Takashi; Kiyotani, Katsuhiro; Igarashi, Tomoki; Yoshida, Asuka

    2012-01-01

    The V protein of Sendai virus (SeV) suppresses innate immunity, resulting in enhancement of viral growth in mouse lungs and viral pathogenicity. The innate immunity restricted by the V protein is induced through activation of interferon regulatory factor 3 (IRF3). The V protein has been shown to interact with melanoma differentiation-associated gene 5 (MDA5) and to inhibit beta interferon production. In the present study, we infected MDA5-knockout mice with V-deficient SeV and found that MDA5 was largely unrelated to the innate immunity that the V protein suppresses in vivo. We therefore investigated the target of the SeV V protein. We previously reported interaction of the V protein with IRF3. Here we extended the observation and showed that the V protein appeared to inhibit translocation of IRF3 into the nucleus. We also found that the V protein inhibited IRF3 activation when induced by a constitutive active form of IRF3. The V proteins of measles virus and Newcastle disease virus inhibited IRF3 transcriptional activation, as did the V protein of SeV, while the V proteins of mumps virus and Nipah virus did not, and inhibition by these proteins correlated with interaction of each V protein with IRF3. These results indicate that IRF3 is important as an alternative target of paramyxovirus V proteins. PMID:22532687

  1. SynechoNET: integrated protein-protein interaction database of a model cyanobacterium Synechocystis sp. PCC 6803.

    PubMed

    Kim, Woo-Yeon; Kang, Sungsoo; Kim, Byoung-Chul; Oh, Jeehyun; Cho, Seongwoong; Bhak, Jong; Choi, Jong-Soon

    2008-01-01

    Cyanobacteria are model organisms for studying photosynthesis, carbon and nitrogen assimilation, evolution of plant plastids, and adaptability to environmental stresses. Despite many studies on cyanobacteria, there is no web-based database of their regulatory and signaling protein-protein interaction networks to date. We report a database and website SynechoNET that provides predicted protein-protein interactions. SynechoNET shows cyanobacterial domain-domain interactions as well as their protein-level interactions using the model cyanobacterium, Synechocystis sp. PCC 6803. It predicts the protein-protein interactions using public interaction databases that contain mutually complementary and redundant data. Furthermore, SynechoNET provides information on transmembrane topology, signal peptide, and domain structure in order to support the analysis of regulatory membrane proteins. Such biological information can be queried and visualized in user-friendly web interfaces that include the interactive network viewer and search pages by keyword and functional category. SynechoNET is an integrated protein-protein interaction database designed to analyze regulatory membrane proteins in cyanobacteria. It provides a platform for biologists to extend the genomic data of cyanobacteria by predicting interaction partners, membrane association, and membrane topology of Synechocystis proteins. SynechoNET is freely available at http://synechocystis.org/ or directly at http://bioportal.kobic.kr/SynechoNET/.

  2. In vitro fluorescence studies of transcription factor IIB-DNA interaction.

    PubMed

    Górecki, Andrzej; Figiel, Małgorzata; Dziedzicka-Wasylewska, Marta

    2015-01-01

    General transcription factor TFIIB is one of the basal constituents of the preinitiation complex of eukaryotic RNA polymerase II, acting as a bridge between the preinitiation complex and the polymerase, and binding promoter DNA in an asymmetric manner, thereby defining the direction of the transcription. Methods of fluorescence spectroscopy together with circular dichroism spectroscopy were used to observe conformational changes in the structure of recombinant human TFIIB after binding to specific DNA sequence. To facilitate the exploration of the structural changes, several site-directed mutations have been introduced altering the fluorescence properties of the protein. Our observations showed that binding of specific DNA sequences changed the protein structure and dynamics, and TFIIB may exist in two conformational states, which can be described by a different microenvironment of W52. Fluorescence studies using both intrinsic and exogenous fluorophores showed that these changes significantly depended on the recognition sequence and concerned various regions of the protein, including those interacting with other transcription factors and RNA polymerase II. DNA binding can cause rearrangements in regions of proteins interacting with the polymerase in a manner dependent on the recognized sequences, and therefore, influence the gene expression.

  3. 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…

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

    PubMed

    Sultana, Azmiri; Lee, Jeffrey E

    2015-02-02

    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. Copyright © 2015 John Wiley & Sons, Inc.

  5. Interaction specificity and coexpression of rice NPR1 homologs 1 and 3 (NH1 and NH3), TGA transcription factors and Negative Regulator of Resistance (NRR) proteins.

    PubMed

    Chern, Mawsheng; Bai, Wei; Ruan, Deling; Oh, Taeyun; Chen, Xuewei; Ronald, Pamela C

    2014-06-11

    The nonexpressor of pathogenesis-related genes 1, NPR1 (also known as NIM1 and SAI1), is a key regulator of SA-mediated systemic acquired resistance (SAR) in Arabidopsis. In rice, the NPR1 homolog 1 (NH1) interacts with TGA transcriptional regulators and the Negative Regulator of Resistance (NRR) protein to modulate the SAR response. Though five NPR1 homologs (NHs) have been identified in rice, only NH1 and NH3 enhance immunity when overexpressed. To understand why NH1 and NH3, but not NH2, NH4, or NH5, contribute to the rice immune response, we screened TGA transcription factors and NRR-like proteins for interactions specific to NH1 and NH3. We also examined their co-expression patterns using publicly available microarray data. We tested five NHs, four NRR homologs (RHs), and 13 rice TGA proteins for pair-wise protein interactions using yeast two-hybrid (Y2H) and split YFP assays. A survey of 331 inter-family interactions revealed a broad, complex protein interaction network. To investigate preferred interaction partners when all three families of proteins were present, we performed a bridged split YFP assay employing YFPN-fused TGA, YFPC-fused RH, and NH proteins without YFP fusions. We found 64 tertiary interactions mediated by NH family members among the 120 sets we examined. In the yeast two-hybrid assay, each NH protein was capable of interacting with most TGA and RH proteins. In the split YFP assay, NH1 was the most prevalent interactor of TGA and RH proteins, NH3 ranked the second, and NH4 ranked the third. Based on their interaction with TGA proteins, NH proteins can be divided into two subfamilies: NH1, NH2, and NH3 in one family and NH4 and NH5 in the other.In addition to evidence of overlap in interaction partners, co-expression analyses of microarray data suggest a correlation between NH1 and NH3 expression patterns, supporting their common role in rice immunity. However, NH3 is very tightly co-expressed with RH1 and RH2, while NH1 is strongly

  6. 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.

  7. Prediction of Heterodimeric Protein Complexes from Weighted Protein-Protein Interaction Networks Using Novel Features and Kernel Functions

    PubMed Central

    Ruan, Peiying; Hayashida, Morihiro; Maruyama, Osamu; Akutsu, Tatsuya

    2013-01-01

    Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been developed such as MCL, MCODE, RNSC, PCP, RRW, and NWE. These methods have dealt with only complexes with size of more than three because the methods often are based on some density of subgraphs. However, heterodimeric protein complexes that consist of two distinct proteins occupy a large part according to several comprehensive databases of known complexes. In this paper, we propose several feature space mappings from protein-protein interaction data, in which each interaction is weighted based on reliability. Furthermore, we make use of prior knowledge on protein domains to develop feature space mappings, domain composition kernel and its combination kernel with our proposed features. We perform ten-fold cross-validation computational experiments. These results suggest that our proposed kernel considerably outperforms the naive Bayes-based method, which is the best existing method for predicting heterodimeric protein complexes. PMID:23776458

  8. 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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Parallel force assay for protein-protein interactions.

    PubMed

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

    2014-01-01

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

  10. Physical interaction of the activator protein-1 factors c-Fos and c-Jun with Cbfa1 for collagenase-3 promoter activation

    NASA Technical Reports Server (NTRS)

    D'Alonzo, Richard C.; Selvamurugan, Nagarajan; Karsenty, Gerard; Partridge, Nicola C.

    2002-01-01

    Previously, we determined that the activator protein-1 (AP-1)-binding site and the runt domain (RD)-binding site and their binding proteins, c-Fos.c-Jun and Cbfa, regulate the collagenase-3 promoter in parathyroid hormone-treated and differentiating osteoblasts. Here we show that Cbfa1 and c-Fos.c-Jun appear to cooperatively bind the RD- and AP-1-binding sites and form ternary structures in vitro. Both in vitro and in vivo co-immunoprecipitation and yeast two-hybrid studies further demonstrate interaction between Cbfa1 with c-Fos and c-Jun in the absence of phosphorylation and without binding to DNA. Additionally, only the runt domain of Cbfa1 was required for interaction with c-Jun and c-Fos. In mammalian cells, overexpression of Cbfa1 enhanced c-Jun activation of AP-1-binding site promoter activity, demonstrating functional interaction. Finally, insertion of base pairs that disrupted the helical phasing between the AP-1- and RD-binding sites also inhibited collagenase-3 promoter activation. Thus, we provide direct evidence that Cbfa1 and c-Fos.c-Jun physically interact and cooperatively bind the AP-1- and RD-binding sites in the collagenase-3 promoter. Moreover, the AP-1- and RD-binding sites appear to be organized in a specific required helical arrangement that facilitates transcription factor interaction and enables promoter activation.

  11. 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

  12. Toward a molecular understanding of nanoparticle-protein interactions.

    PubMed

    Treuel, Lennart; Nienhaus, Gerd Ulrich

    2012-06-01

    Wherever nanoparticles (NPs) come in contact with a living organism, physical and chemical interactions take place between the surfaces of the NPs and biomatter, in particular proteins. When NP are exposed to biological fluids, an adsorption layer of proteins, a "protein corona" forms around the NPs. Consequently, living systems interact with the protein-coated NP rather than with a bare NP. To anticipate biological responses to NPs, we thus require comprehensive knowledge of the interactions at the bio-nano interface. In recent years, a wide variety of biophysical techniques have been employed to elucidate mechanistic aspects of NP-protein interactions. In this brief review, we present the latest findings regarding the composition of the protein corona as it forms on NPs in the blood stream. We also discuss molecular aspects of this adsorption layer and its time evolution. The current state of knowledge is summarized, and issues that still need to be addressed to further advance our understanding of NP-protein interactions are identified.

  13. Membrane receptor location defines receptor interaction with signaling proteins in a polarized epithelium.

    PubMed

    Amsler, K; Kuwada, S K

    1999-01-01

    Signal transduction from receptors is mediated by the interaction of activated receptors with proximate downstream signaling proteins. In polarized epithelial cells, the membrane is divided into subdomains: the apical and basolateral membranes. Membrane receptors may be present in one or both subdomains. Using a combination of immunoprecipitation and Western blot analyses, we tested the hypothesis that a tyrosine kinase growth factor receptor, epidermal growth factor receptor (EGFR), interacts with distinct signaling proteins when present at the apical vs. basolateral membrane of a polarized renal epithelial cell. We report here that tyrosine phosphorylation of phospholipase C-gamma (PLC-gamma) was induced only when basolateral EGFR was activated. In contrast, tyrosine phosphorylation of several other signaling proteins was increased by activation of receptor at either surface. All signaling proteins were distributed diffusely throughout the cytoplasm; however, PLC-gamma protein also displayed a concentration at lateral cell borders. These results demonstrate that in polarized epithelial cells the array of signaling pathways initiated by activation of a membrane receptor is defined, at least in part, by the membrane location of the receptor.

  14. Real-Time Analysis of Specific Protein-DNA Interactions with Surface Plasmon Resonance

    PubMed Central

    Ritzefeld, Markus; Sewald, Norbert

    2012-01-01

    Several proteins, like transcription factors, bind to certain DNA sequences, thereby regulating biochemical pathways that determine the fate of the corresponding cell. Due to these key positions, it is indispensable to analyze protein-DNA interactions and to identify their mode of action. Surface plasmon resonance is a label-free method that facilitates the elucidation of real-time kinetics of biomolecular interactions. In this article, we focus on this biosensor-based method and provide a detailed guide how SPR can be utilized to study binding of proteins to oligonucleotides. After a description of the physical phenomenon and the instrumental realization including fiber-optic-based SPR and SPR imaging, we will continue with a survey of immobilization methods. Subsequently, we will focus on the optimization of the experiment, expose pitfalls, and introduce how data should be analyzed and published. Finally, we summarize several interesting publications of the last decades dealing with protein-DNA and RNA interaction analysis by SPR. PMID:22500214

  15. SPRINT: ultrafast protein-protein interaction prediction of the entire human interactome.

    PubMed

    Li, Yiwei; Ilie, Lucian

    2017-11-15

    Proteins perform their functions usually by interacting with other proteins. Predicting which proteins interact is a fundamental problem. Experimental methods are slow, expensive, and have a high rate of error. Many computational methods have been proposed among which sequence-based ones are very promising. However, so far no such method is able to predict effectively the entire human interactome: they require too much time or memory. We present SPRINT (Scoring PRotein INTeractions), a new sequence-based algorithm and tool for predicting protein-protein interactions. We comprehensively compare SPRINT with state-of-the-art programs on seven most reliable human PPI datasets and show that it is more accurate while running orders of magnitude faster and using very little memory. SPRINT is the only sequence-based program that can effectively predict the entire human interactome: it requires between 15 and 100 min, depending on the dataset. Our goal is to transform the very challenging problem of predicting the entire human interactome into a routine task. The source code of SPRINT is freely available from https://github.com/lucian-ilie/SPRINT/ and the datasets and predicted PPIs from www.csd.uwo.ca/faculty/ilie/SPRINT/ .

  16. 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. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Kinome signaling through regulated protein-protein interactions in normal and cancer cells.

    PubMed

    Pawson, Tony; Kofler, Michael

    2009-04-01

    The flow of molecular information through normal and oncogenic signaling pathways frequently depends on protein phosphorylation, mediated by specific kinases, and the selective binding of the resulting phosphorylation sites to interaction domains present on downstream targets. This physical and functional interplay of catalytic and interaction domains can be clearly seen in cytoplasmic tyrosine kinases such as Src, Abl, Fes, and ZAP-70. Although the kinase and SH2 domains of these proteins possess similar intrinsic properties of phosphorylating tyrosine residues or binding phosphotyrosine sites, they also undergo intramolecular interactions when linked together, in a fashion that varies from protein to protein. These cooperative interactions can have diverse effects on substrate recognition and kinase activity, and provide a variety of mechanisms to link the stimulation of catalytic activity to substrate recognition. Taken together, these data have suggested how protein kinases, and the signaling pathways in which they are embedded, can evolve complex properties through the stepwise linkage of domains within single polypeptides or multi-protein assemblies.

  18. Enhancing the Functional Content of Eukaryotic Protein Interaction Networks

    PubMed Central

    Pandey, Gaurav; Arora, Sonali; Manocha, Sahil; Whalen, Sean

    2014-01-01

    Protein interaction networks are a promising type of data for studying complex biological systems. However, despite the rich information embedded in these networks, these networks face important data quality challenges of noise and incompleteness that adversely affect the results obtained from their analysis. Here, we apply a robust measure of local network structure called common neighborhood similarity (CNS) to address these challenges. Although several CNS measures have been proposed in the literature, an understanding of their relative efficacies for the analysis of interaction networks has been lacking. We follow the framework of graph transformation to convert the given interaction network into a transformed network corresponding to a variety of CNS measures evaluated. The effectiveness of each measure is then estimated by comparing the quality of protein function predictions obtained from its corresponding transformed network with those from the original network. Using a large set of human and fly protein interactions, and a set of over GO terms for both, we find that several of the transformed networks produce more accurate predictions than those obtained from the original network. In particular, the measure and other continuous CNS measures perform well this task, especially for large networks. Further investigation reveals that the two major factors contributing to this improvement are the abilities of CNS measures to prune out noisy edges and enhance functional coherence in the transformed networks. PMID:25275489

  19. The food colorant erythrosine is a promiscuous protein-protein interaction inhibitor.

    PubMed

    Ganesan, Lakshmi; Margolles-Clark, Emilio; Song, Yun; Buchwald, Peter

    2011-03-15

    Following our observation that erythrosine B (FD&C Red No. 3) is a relatively potent inhibitor of the TNF-R-TNFα and CD40-CD154 protein-protein interactions, we investigated whether this inhibitory activity extends to any other protein-protein interactions (PPI) as well as whether any other approved food colors possess such inhibitory activity. We found erythrosine, a poly-iodinated xanthene dye, to be a non-specific promiscuous inhibitor of a number of PPIs within the tumor necrosis factor superfamily (TNF-R-TNFα, CD40-CD154, BAFF-R-BAFF, RANK-RANKL, OX40-OX40L, 4-1BB-4-1BBL) as well as outside of it (EGF-R-EGF) with a remarkably consistent median inhibitory concentration (IC(50)) in the 2-20 μM (approximately 2-20mg/L) range. In agreement with this, erythrosine also showed cellular effects including clear cytotoxic effects around this concentration range (IC₅₀≈50 μM). Among the seven FDA-approved food colorants, only erythrosine showed consistent PPI inhibitory activity in the sub-100 μM range, which might also explain (at least partially) why it also has the lowest approved acceptable daily intake (ADI) (0.1 mg/kg body weight/day). Among a number of xanthene structural analogs of erythrosine tested for activity, rose Bengal, a food colorant approved in Japan, showed similar, maybe even more pronounced, promiscuous inhibitory activity, whereas fluorescein was inactive and gallein, phloxine, and eosin were somewhat active in some of the assays. Copyright © 2011 Elsevier Inc. All rights reserved.

  20. Contribution of Hydrophobic Interactions to Protein Stability

    PubMed Central

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

    2011-01-01

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

  1. Prediction of protein-protein interaction sites using electrostatic desolvation profiles.

    PubMed

    Fiorucci, Sébastien; Zacharias, Martin

    2010-05-19

    Protein-protein complex formation involves removal of water from the interface region. Surface regions with a small free energy penalty for water removal or desolvation may correspond to preferred interaction sites. A method to calculate the electrostatic free energy of placing a neutral low-dielectric probe at various protein surface positions has been designed and applied to characterize putative interaction sites. Based on solutions of the finite-difference Poisson equation, this method also includes long-range electrostatic contributions and the protein solvent boundary shape in contrast to accessible-surface-area-based solvation energies. Calculations on a large set of proteins indicate that in many cases (>90%), the known binding site overlaps with one of the six regions of lowest electrostatic desolvation penalty (overlap with the lowest desolvation region for 48% of proteins). Since the onset of electrostatic desolvation occurs even before direct protein-protein contact formation, it may help guide proteins toward the binding region in the final stage of complex formation. It is interesting that the probe desolvation properties associated with residue types were found to depend to some degree on whether the residue was outside of or part of a binding site. The probe desolvation penalty was on average smaller if the residue was part of a binding site compared to other surface locations. Applications to several antigen-antibody complexes demonstrated that the approach might be useful not only to predict protein interaction sites in general but to map potential antigenic epitopes on protein surfaces. Copyright (c) 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  2. Prediction of Protein-Protein Interaction Sites Using Electrostatic Desolvation Profiles

    PubMed Central

    Fiorucci, Sébastien; Zacharias, Martin

    2010-01-01

    Abstract Protein-protein complex formation involves removal of water from the interface region. Surface regions with a small free energy penalty for water removal or desolvation may correspond to preferred interaction sites. A method to calculate the electrostatic free energy of placing a neutral low-dielectric probe at various protein surface positions has been designed and applied to characterize putative interaction sites. Based on solutions of the finite-difference Poisson equation, this method also includes long-range electrostatic contributions and the protein solvent boundary shape in contrast to accessible-surface-area-based solvation energies. Calculations on a large set of proteins indicate that in many cases (>90%), the known binding site overlaps with one of the six regions of lowest electrostatic desolvation penalty (overlap with the lowest desolvation region for 48% of proteins). Since the onset of electrostatic desolvation occurs even before direct protein-protein contact formation, it may help guide proteins toward the binding region in the final stage of complex formation. It is interesting that the probe desolvation properties associated with residue types were found to depend to some degree on whether the residue was outside of or part of a binding site. The probe desolvation penalty was on average smaller if the residue was part of a binding site compared to other surface locations. Applications to several antigen-antibody complexes demonstrated that the approach might be useful not only to predict protein interaction sites in general but to map potential antigenic epitopes on protein surfaces. PMID:20441756

  3. Identification of host cellular proteins that interact with the M protein of a highly pathogenic porcine reproductive and respiratory syndrome virus vaccine strain.

    PubMed

    Wang, Qian; Li, Yanwei; Dong, Hong; Wang, Li; Peng, Jinmei; An, Tongqing; Yang, Xufu; Tian, Zhijun; Cai, Xuehui

    2017-02-22

    The highly pathogenic porcine reproductive and respiratory syndrome virus (HP-PRRSV) continues to pose one of the greatest threats to the swine industry. M protein is the most conserved and important structural protein of PRRSV. However, information about the host cellular proteins that interact with M protein remains limited. Host cellular proteins that interact with the M protein of HP-PRRSV were immunoprecipitated from MARC-145 cells infected with PRRSV HuN4-F112 using the M monoclonal antibody (mAb). The differentially expressed proteins were identified by LC-MS/MS. The screened proteins were used for bioinformatics analysis including Gene Ontology, the interaction network, and the enriched KEGG pathways. Some interested cellular proteins were validated to interact with M protein by CO-IP. The PRRSV HuN4-F112 infection group had 10 bands compared with the control group. The bands included 219 non-redundant cellular proteins that interact with M protein, which were identified by LC-MS/MS with high confidence. The gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) pathway bioinformatic analyses indicated that the identified proteins could be assigned to several different subcellular locations and functional classes. Functional analysis of the interactome profile highlighted cellular pathways associated with protein translation, infectious disease, and signal transduction. Two interested cellular proteins-nuclear factor of activated T cells 45 kDa (NF45) and proliferating cell nuclear antigen (PCNA)-that could interact with M protein were validated by Co-IP and confocal analyses. The interactome data between PRRSV M protein and cellular proteins were identified and contribute to the understanding of the roles of M protein in the replication and pathogenesis of PRRSV. The interactome of M protein will aid studies of virus/host interactions and provide means to decrease the threat of PRRSV to the swine industry in the future.

  4. Reconstituting protein interaction networks using parameter-dependent domain-domain interactions

    PubMed Central

    2013-01-01

    Background We can describe protein-protein interactions (PPIs) as sets of distinct domain-domain interactions (DDIs) that mediate the physical interactions between proteins. Experimental data confirm that DDIs are more consistent than their corresponding PPIs, lending support to the notion that analyses of DDIs may improve our understanding of PPIs and lead to further insights into cellular function, disease, and evolution. However, currently available experimental DDI data cover only a small fraction of all existing PPIs and, in the absence of structural data, determining which particular DDI mediates any given PPI is a challenge. Results We present two contributions to the field of domain interaction analysis. First, we introduce a novel computational strategy to merge domain annotation data from multiple databases. We show that when we merged yeast domain annotations from six annotation databases we increased the average number of domains per protein from 1.05 to 2.44, bringing it closer to the estimated average value of 3. Second, we introduce a novel computational method, parameter-dependent DDI selection (PADDS), which, given a set of PPIs, extracts a small set of domain pairs that can reconstruct the original set of protein interactions, while attempting to minimize false positives. Based on a set of PPIs from multiple organisms, our method extracted 27% more experimentally detected DDIs than existing computational approaches. Conclusions We have provided a method to merge domain annotation data from multiple sources, ensuring large and consistent domain annotation for any given organism. Moreover, we provided a method to extract a small set of DDIs from the underlying set of PPIs and we showed that, in contrast to existing approaches, our method was not biased towards DDIs with low or high occurrence counts. Finally, we used these two methods to highlight the influence of the underlying annotation density on the characteristics of extracted DDIs. Although

  5. Structural insights into pharmacophore-assisted in silico identification of protein-protein interaction inhibitors for inhibition of human toll-like receptor 4 - myeloid differentiation factor-2 (hTLR4-MD-2) complex.

    PubMed

    Mishra, Vinita; Pathak, Chandramani

    2018-05-29

    Toll-like receptor 4 (TLR4) is a member of Toll-Like Receptors (TLRs) family that serves as a receptor for bacterial lipopolysaccharide (LPS). TLR4 alone cannot recognize LPS without aid of co-receptor myeloid differentiation factor-2 (MD-2). Binding of LPS with TLR4 forms a LPS-TLR4-MD-2 complex and directs downstream signaling for activation of immune response, inflammation and NF-κB activation. Activation of TLR4 signaling is associated with various pathophysiological consequences. Therefore, targeting protein-protein interaction (PPI) in TLR4-MD-2 complex formation could be an attractive therapeutic approach for targeting inflammatory disorders. The aim of present study was directed to identify small molecule PPI inhibitors (SMPPIIs) using pharmacophore mapping-based approach of computational drug discovery. Here, we had retrieved the information about the hot spot residues and their pharmacophoric features at both primary (TLR4-MD-2) and dimerization (MD-2-TLR4*) protein-protein interaction interfaces in TLR4-MD-2 homo-dimer complex using in silico methods. Promising candidates were identified after virtual screening, which may restrict TLR4-MD-2 protein-protein interaction. In silico off-target profiling over the virtually screened compounds revealed other possible molecular targets. Two of the virtually screened compounds (C11 and C15) were predicted to have an inhibitory concentration in μM range after HYDE assessment. Molecular dynamics simulation study performed for these two compounds in complex with target protein confirms the stability of the complex. After virtual high throughput screening we found selective hTLR4-MD-2 inhibitors, which may have therapeutic potential to target chronic inflammatory diseases.

  6. Huntingtin-interacting protein 1: a Merkel cell carcinoma marker that interacts with c-Kit.

    PubMed

    Ames, Heather M; Bichakjian, Christopher K; Liu, Grace Y; Oravecz-Wilson, Katherine I; Fullen, Douglas R; Verhaegen, Monique E; Johnson, Timothy M; Dlugosz, Andrzej A; Ross, Theodora S

    2011-10-01

    Merkel cell carcinoma (MCC) is a neoplasm thought to originate from the neuroendocrine Merkel cells of the skin. Although the prevalence of MCC has been increasing, treatments for this disease remain limited because of a paucity of information regarding MCC biology. We have found that the endocytic oncoprotein Huntingtin-interacting protein 1 (HIP1) is expressed at high levels in ∼90% of MCC tumors and serves as a more reliable histological cytoplasmic stain than the gold standard, cytokeratin 20. Furthermore, high anti-HIP1 antibody reactivity in the sera of a cohort of MCC patients predicts the presence of metastases. Another protein that is frequently expressed at high levels in MCC tumors is the stem cell factor (SCF) receptor tyrosine kinase, c-Kit. In working toward an understanding of how HIP1 might contribute to MCC tumorigenesis, we have discovered that HIP1 interacts with SCF-activated c-Kit. These data not only identify HIP1 as a molecular marker for management of MCC patients but also show that HIP1 interacts with and slows the degradation of c-Kit.

  7. Structural Interface Parameters Are Discriminatory in Recognising Near-Native Poses of Protein-Protein Interactions

    PubMed Central

    Malhotra, Sony; Sankar, Kannan; Sowdhamini, Ramanathan

    2014-01-01

    Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native) structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets. PMID:24498255

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

    PubMed

    Malhotra, Sony; Sankar, Kannan; Sowdhamini, Ramanathan

    2014-01-01

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

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

    PubMed

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

    2012-01-01

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

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

    PubMed Central

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

    2012-01-01

    Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP) and thioesterase (TE) govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr) as a model, a structural simulation of docking CrACP to CrTE identifies a protein-protein recognition surface between the two domains. A virtual screen reveals plant TEs with similar in silico binding to CrACP. Employing an activity-based crosslinking probe designed to selectively trap transient protein-protein interactions between the TE and ACP, we demonstrate in vitro that CrTE must functionally interact with CrACP to release fatty acids, while TEs of vascular plants show no mechanistic crosslinking to CrACP. This is recapitulated in vivo, where overproduction of the endogenous CrTE increased levels of short-chain fatty acids and engineering plant TEs into the C. reinhardtii chloroplast did not alter the fatty acid profile. These findings highlight the critical role of protein-protein interactions in manipulating fatty acid biosynthesis for algae biofuel engineering as illuminated by activity-based probes. PMID:23028438

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

    Cancer.gov

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

  12. A Brief Review of RNA–Protein Interaction Database Resources

    PubMed Central

    Yi, Ying; Zhao, Yue; Huang, Yan; Wang, Dong

    2017-01-01

    RNA–Protein interactions play critical roles in various biological processes. By collecting and analyzing the RNA–Protein interactions and binding sites from experiments and predictions, RNA–Protein interaction databases have become an essential resource for the exploration of the transcriptional and post-transcriptional regulatory network. Here, we briefly review several widely used RNA–Protein interaction database resources developed in recent years to provide a guide of these databases. The content and major functions in databases are presented. The brief description of database helps users to quickly choose the database containing information they interested. In short, these RNA–Protein interaction database resources are continually updated, but the current state shows the efforts to identify and analyze the large amount of RNA–Protein interactions. PMID:29657278

  13. Development of Cell-Permeable, Non-Helical Constrained Peptides to Target a Key Protein-Protein Interaction in Ovarian Cancer.

    PubMed

    Wiedmann, Mareike M; Tan, Yaw Sing; Wu, Yuteng; Aibara, Shintaro; Xu, Wenshu; Sore, Hannah F; Verma, Chandra S; Itzhaki, Laura; Stewart, Murray; Brenton, James D; Spring, David R

    2017-01-09

    There is a lack of current treatment options for ovarian clear cell carcinoma (CCC) and the cancer is often resistant to platinum-based chemotherapy. Hence there is an urgent need for novel therapeutics. The transcription factor hepatocyte nuclear factor 1β (HNF1β) is ubiquitously overexpressed in CCC and is seen as an attractive therapeutic target. This was validated through shRNA-mediated knockdown of the target protein, HNF1β, in five high- and low-HNF1β-expressing CCC lines. To inhibit the protein function, cell-permeable, non-helical constrained proteomimetics to target the HNF1β-importin α protein-protein interaction were designed, guided by X-ray crystallographic data and molecular dynamics simulations. In this way, we developed the first reported series of constrained peptide nuclear import inhibitors. Importantly, this general approach may be extended to other transcription factors. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Protein-protein interaction networks: unraveling the wiring of molecular machines within the cell.

    PubMed

    De Las Rivas, Javier; Fontanillo, Celia

    2012-11-01

    Mapping and understanding of the protein interaction networks with their key modules and hubs can provide deeper insights into the molecular machinery underlying complex phenotypes. In this article, we present the basic characteristics and definitions of protein networks, starting with a distinction of the different types of associations between proteins. We focus the review on protein-protein interactions (PPIs), a subset of associations defined as physical contacts between proteins that occur by selective molecular docking in a particular biological context. We present such definition as opposed to other types of protein associations derived from regulatory, genetic, structural or functional relations. To determine PPIs, a variety of binary and co-complex methods exist; however, not all the technologies provide the same information and data quality. A way of increasing confidence in a given protein interaction is to integrate orthogonal experimental evidences. The use of several complementary methods testing each single interaction assesses the accuracy of PPI data and tries to minimize the occurrence of false interactions. Following this approach there have been important efforts to unify primary databases of experimentally proven PPIs into integrated databases. These meta-databases provide a measure of the confidence of interactions based on the number of experimental proofs that report them. As a conclusion, we can state that integrated information allows the building of more reliable interaction networks. Identification of communities, cliques, modules and hubs by analysing the topological parameters and graph properties of the protein networks allows the discovery of central/critical nodes, which are candidates to regulate cellular flux and dynamics.

  15. Nuclear actions of insulin-like growth factor binding protein-3.

    PubMed

    Baxter, Robert C

    2015-09-10

    In addition to its actions outside the cell, cellular uptake and nuclear import of insulin-like growth factor binding protein-3 (IGFBP-3) has been recognized for almost two decades, but knowledge of its nuclear actions has been slow to emerge. IGFBP-3 has a functional nuclear localization signal and interacts with the nuclear transport protein importin-β. Within the nucleus IGFBP-3 appears to have a role in transcriptional regulation. It can bind to the nuclear receptor, retinoid X receptor-α and several of its dimerization partners, including retinoic acid receptor, vitamin D receptor (VDR), and peroxisome proliferator-activated receptor-γ (PPARγ). These interactions modulate the functions of these receptors, for example inhibiting VDR-dependent transcription in osteoblasts and PPARγ-dependent transcription in adipocytes. Nuclear IGFBP-3 can be detected by immunohistochemistry in cancer and other tissues, and its presence in the nucleus has been shown in many cell culture studies to be necessary for its pro-apoptotic effect, which may also involve interaction with the nuclear receptor Nur77, and export from the nucleus. IGFBP-3 is p53-inducible and in response to DNA damage, forms a complex with the epidermal growth factor receptor (EGFR), translocating to the nucleus to interact with DNA-dependent protein kinase. Inhibition of EGFR kinase activity or downregulation of IGFBP-3 can inhibit DNA double strand-break repair by nonhomologous end joining. IGFBP-3 thus has the ability to influence many cell functions through its interactions with intranuclear pathways, but the importance of these interactions in vivo, and their potential to be targeted for therapeutic benefit, require further investigation. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. CIP, a cardiac Isl1-interacting protein, represses cardiomyocyte hypertrophy

    PubMed Central

    Huang, Zhan-Peng; Seok, Hee Young; Zhou, Bin; Chen, Jinghai; Chen, Jian-Fu; Tao, Yazhong; Pu, William T.; Wang, Da-Zhi

    2012-01-01

    Rationale Mammalian heart has minimal regenerative capacity. In response to mechanical or pathological stress, the heart undergoes cardiac remodeling. Pressure and volume overload in the heart cause increased size (hypertrophic growth) of cardiomyocytes. Whereas the regulatory pathways that activate cardiac hypertrophy have been well established, the molecular events that inhibit or repress cardiac hypertrophy are less known. Objective To identify and investigate novel regulators that modulate cardiac hypertrophy. Methods and Results Here, we report the identification, characterization and functional examination of CIP, a novel cardiac Isl1-interacting protein. CIP was identified from a bioinformatic search for novel cardiac-expressed genes in mouse embryonic hearts. CIP encodes a nuclear protein without recognizable motifs. Northern blotting, in situ hybridization and reporter gene tracing demonstrated that CIP is highly expressed in cardiomyocytes of developing and adult hearts. Yeast-two-hybrid screening identified Isl1, a LIM/homeodomain transcription factor essential for the specification of cardiac progenitor cells in the second heart field, as a co-factor of CIP. CIP directly interacted with Isl1 and we mapped the domains of these two proteins which mediate their interaction. We show that CIP represses the transcriptional activity of Isl1 in the activation of the MEF2C enhancer. The expression of CIP was dramatically reduced in hypertrophic cardiomyocytes. Most importantly, overexpression of CIP repressed agonist-induced cardiomyocyte hypertrophy. Conclusions Our studies therefore identify CIP a novel regulator of cardiac hypertrophy. PMID:22343712

  17. CIP, a cardiac Isl1-interacting protein, represses cardiomyocyte hypertrophy.

    PubMed

    Huang, Zhan-Peng; Young Seok, Hee; Zhou, Bin; Chen, Jinghai; Chen, Jian-Fu; Tao, Yazhong; Pu, William T; Wang, Da-Zhi

    2012-03-16

    Mammalian heart has minimal regenerative capacity. In response to mechanical or pathological stress, the heart undergoes cardiac remodeling. Pressure and volume overload in the heart cause increased size (hypertrophic growth) of cardiomyocytes. Whereas the regulatory pathways that activate cardiac hypertrophy have been well-established, the molecular events that inhibit or repress cardiac hypertrophy are less known. To identify and investigate novel regulators that modulate cardiac hypertrophy. Here, we report the identification, characterization, and functional examination of a novel cardiac Isl1-interacting protein (CIP). CIP was identified from a bioinformatic search for novel cardiac-expressed genes in mouse embryonic hearts. CIP encodes a nuclear protein without recognizable motifs. Northern blotting, in situ hybridization, and reporter gene tracing demonstrated that CIP is highly expressed in cardiomyocytes of developing and adult hearts. Yeast two-hybrid screening identified Isl1, a LIM/homeodomain transcription factor essential for the specification of cardiac progenitor cells in the second heart field, as a cofactor of CIP. CIP directly interacted with Isl1, and we mapped the domains of these two proteins, which mediate their interaction. We show that CIP represses the transcriptional activity of Isl1 in the activation of the myocyte enhancer factor 2C. The expression of CIP was dramatically reduced in hypertrophic cardiomyocytes. Most importantly, overexpression of CIP repressed agonist-induced cardiomyocyte hypertrophy. Our studies therefore identify CIP as a novel regulator of cardiac hypertrophy.

  18. Establishment of a robust dengue virus NS3-NS5 binding assay for identification of protein-protein interaction inhibitors.

    PubMed

    Takahashi, Hirotaka; Takahashi, Chikako; Moreland, Nicole J; Chang, Young-Tae; Sawasaki, Tatsuya; Ryo, Akihide; Vasudevan, Subhash G; Suzuki, Youichi; Yamamoto, Naoki

    2012-12-01

    Whereas the dengue virus (DENV) non-structural (NS) proteins NS3 and NS5 have been shown to interact in vitro and in vivo, the biological relevance of this interaction in viral replication has not been fully clarified. Here, we first applied a simple and robust in vitro assay based on AlphaScreen technology in combination with the wheat-germ cell-free protein production system to detect the DENV-2 NS3-NS5 interaction in a 384-well plate. The cell-free-synthesized NS3 and NS5 recombinant proteins were soluble and in possession of their respective enzymatic activities in vitro. In addition, AlphaScreen assays using the recombinant proteins detected a specific interaction between NS3 and NS5 with a robust Z' factor of 0.71. By employing the AlphaScreen assay, we found that both the N-terminal protease and C-terminal helicase domains of NS3 are required for its association with NS5. Furthermore, a competition assay revealed that the binding of full-length NS3 to NS5 was significantly inhibited by the addition of an excess of NS3 protease or helicase domains. Our results demonstrate that the AlphaScreen assay can be used to discover novel antiviral agents targeting the interactions between DENV NS proteins. Copyright © 2012 Elsevier B.V. All rights reserved.

  19. 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. © 2016 Schütze et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  20. 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

  1. A simple and efficient method for predicting protein-protein interaction sites.

    PubMed

    Higa, R H; Tozzi, C L

    2008-09-23

    Computational methods for predicting protein-protein interaction sites based on structural data are characterized by an accuracy between 70 and 80%. Some experimental studies indicate that only a fraction of the residues, forming clusters in the center of the interaction site, are energetically important for binding. In addition, the analysis of amino acid composition has shown that residues located in the center of the interaction site can be better discriminated from the residues in other parts of the protein surface. In the present study, we implement a simple method to predict interaction site residues exploiting this fact and show that it achieves a very competitive performance compared to other methods using the same dataset and criteria for performance evaluation (success rate of 82.1%).

  2. Single Molecule Study of Metalloregulatory Protein-DNA Interactions

    NASA Astrophysics Data System (ADS)

    Sarkar, Susanta; Benitez, Jaime; Huang, Zhengxi; Wang, Qi; Chen, Peng

    2007-03-01

    Control of metal concentrations is essential for living body. Metalloregulatory proteins respond to metal concentrations by regulating transcriptions of metal resistance genes via protein-DNA interactions. It is thus necessary to understand interactions of metalloregulatory proteins with DNA. Ensemble measurements provide average behavior of a vast number of biomolecules. In contrast, single molecule spectroscopy can track single molecules individually and elucidate dynamics of processes of short time scales and intermediate structures not revealed by ensemble measurements. Here we present single molecule study of interactions between PbrR691, a MerR-family metalloregulatory protein and DNA. We presume that the dynamics of protein/DNA conformational changes and interactions are important for the transcription regulation and kinetics of these dynamic processes can provide useful information about the mechanisms of these metalloregulatory proteins.

  3. Protein-Protein Interactions of Azurin Complex by Coarse-Grained Simulations with a Gō-Like Model

    NASA Astrophysics Data System (ADS)

    Rusmerryani, Micke; Takasu, Masako; Kawaguchi, Kazutomo; Saito, Hiroaki; Nagao, Hidemi

    Proteins usually perform their biological functions by forming a complex with other proteins. It is very important to study the protein-protein interactions since these interactions are crucial in many processes of a living organism. In this study, we develop a coarse grained model to simulate protein complex in liquid system. We carry out molecular dynamics simulations with topology-based potential interactions to simulate dynamical properties of Pseudomonas Aeruginosa azurin complex systems. Azurin is known to play an essential role as an anticancer agent and bind many important intracellular molecules. Some physical properties are monitored during simulation time to get a better understanding of the influence of protein-protein interactions to the azurin complex dynamics. These studies will provide valuable insights for further investigation on protein-protein interactions in more realistic system.

  4. Factor H-related proteins.

    PubMed

    Józsi, Mihály; Meri, Seppo

    2014-01-01

    Factor H-related proteins (CFHRs) are plasma glycoproteins related in structure and antigenicity to each other and to the complement inhibitory protein factor H. Such proteins are found in most mammals but their number and domain composition vary. This chapter summarizes our current knowledge on the human factor H-related proteins. In contrast to factor H, they have no strong complement inhibitory activity, although for some of them regulatory or complement modulatory activity has been reported. A common feature of CFHRs is that they bind to the C3b component of complement. Novel links between CFHRs and various diseases (C3 glomerulopathies, atypical hemolytic uremic syndrome and age-related macular degeneration) have been revealed in recent years, but we are still far from understanding their biological function.

  5. Interaction of plant chimeric calcium/calmodulin-dependent protein kinase with a homolog of eukaryotic elongation factor-1alpha

    NASA Technical Reports Server (NTRS)

    Wang, W.; Poovaiah, B. W.

    1999-01-01

    A chimeric Ca2+/calmodulin-dependent protein kinase (CCaMK) was previously cloned and characterized in this laboratory. To investigate the biological functions of CCaMK, the yeast two-hybrid system was used to isolate genes encoding proteins that interact with CCaMK. One of the cDNA clones obtained from the screening (LlEF-1alpha1) has high similarity with the eukaryotic elongation factor-1alpha (EF-1alpha). CCaMK phosphorylated LlEF-1alpha1 in a Ca2+/calmodulin-dependent manner. The phosphorylation site for CCaMK (Thr-257) was identified by site-directed mutagenesis. Interestingly, Thr-257 is located in the putative tRNA-binding region of LlEF-1alpha1. An isoform of Ca2+-dependent protein kinase (CDPK) phosphorylated multiple sites of LlEF-1alpha1 in a Ca2+-dependent but calmodulin-independent manner. Unlike CDPK, CCaMK phosphorylated only one site, and this site is different from CDPK phosphorylation sites. This suggests that the phosphorylation of EF-1alpha by these two kinases may have different functional significance. Although the phosphorylation of LlEF-1alpha1 by CCaMK is Ca2+/calmodulin-dependent, in vitro binding assays revealed that CCaMK binds to LlEF-1alpha1 in a Ca2+-independent manner. This was further substantiated by coimmunoprecipitation of CCaMK and EF-1alpha using the protein extract from lily anthers. Dissociation of CCaMK from EF-1alpha by Ca2+ and phosphorylation of EF-1alpha by CCaMK in a Ca2+/calmodulin-dependent manner suggests that these interactions may play a role in regulating the biological functions of EF-1alpha.

  6. Prediction and Dissection of Protein-RNA Interactions by Molecular Descriptors.

    PubMed

    Liu, Zhi-Ping; Chen, Luonan

    2016-01-01

    Protein-RNA interactions play crucial roles in numerous biological processes. However, detecting the interactions and binding sites between protein and RNA by traditional experiments is still time consuming and labor costing. Thus, it is of importance to develop bioinformatics methods for predicting protein-RNA interactions and binding sites. Accurate prediction of protein-RNA interactions and recognitions will highly benefit to decipher the interaction mechanisms between protein and RNA, as well as to improve the RNA-related protein engineering and drug design. In this work, we summarize the current bioinformatics strategies of predicting protein-RNA interactions and dissecting protein-RNA interaction mechanisms from local structure binding motifs. In particular, we focus on the feature-based machine learning methods, in which the molecular descriptors of protein and RNA are extracted and integrated as feature vectors of representing the interaction events and recognition residues. In addition, the available methods are classified and compared comprehensively. The molecular descriptors are expected to elucidate the binding mechanisms of protein-RNA interaction and reveal the functional implications from structural complementary perspective.

  7. Direct Protein Interactions Are Responsible for Ikaros-GATA and Ikaros-Cdk9 Cooperativeness in Hematopoietic Cells

    PubMed Central

    Bottardi, Stefania; Mavoungou, Lionel; Bourgoin, Vincent; Mashtalir, Nazar; Affar, El Bachir

    2013-01-01

    Ikaros (Ik) is a critical regulator of hematopoietic gene expression. Here, we established that the Ik interactions with GATA transcription factors and cyclin-dependent kinase 9 (Cdk9), a component of the positive transcription elongation factor b (P-TEFb), are required for transcriptional activation of Ik target genes. A detailed dissection of Ik-GATA and Ik-Cdk9 protein interactions indicated that the C-terminal zinc finger domain of Ik interacts directly with the C-terminal zinc fingers of GATA1, GATA2, and GATA3, whereas the N-terminal zinc finger domain of Ik is required for interaction with the kinase and T-loop domains of Cdk9. The relevance of these interactions was demonstrated in vivo in COS-7 and primary hematopoietic cells, in which Ik facilitated Cdk9 and GATA protein recruitment to gene promoters and transcriptional activation. Moreover, the oncogenic isoform Ik6 did not efficiently interact with Cdk9 or GATA proteins in vivo and perturbed Cdk9/P-TEFb recruitment to Ik target genes, thereby affecting transcription elongation. Finally, characterization of a novel nuclear Ik isoform revealed that Ik exon 6 is dispensable for interactions with Mi2 and GATA proteins but is essential for the Cdk9 interaction. Thus, Ik is central to the Ik-GATA-Cdk9 regulatory network, which is broadly utilized for gene regulation in hematopoietic cells. PMID:23732910

  8. Direct protein interactions are responsible for Ikaros-GATA and Ikaros-Cdk9 cooperativeness in hematopoietic cells.

    PubMed

    Bottardi, Stefania; Mavoungou, Lionel; Bourgoin, Vincent; Mashtalir, Nazar; Affar, El Bachir; Milot, Eric

    2013-08-01

    Ikaros (Ik) is a critical regulator of hematopoietic gene expression. Here, we established that the Ik interactions with GATA transcription factors and cyclin-dependent kinase 9 (Cdk9), a component of the positive transcription elongation factor b (P-TEFb), are required for transcriptional activation of Ik target genes. A detailed dissection of Ik-GATA and Ik-Cdk9 protein interactions indicated that the C-terminal zinc finger domain of Ik interacts directly with the C-terminal zinc fingers of GATA1, GATA2, and GATA3, whereas the N-terminal zinc finger domain of Ik is required for interaction with the kinase and T-loop domains of Cdk9. The relevance of these interactions was demonstrated in vivo in COS-7 and primary hematopoietic cells, in which Ik facilitated Cdk9 and GATA protein recruitment to gene promoters and transcriptional activation. Moreover, the oncogenic isoform Ik6 did not efficiently interact with Cdk9 or GATA proteins in vivo and perturbed Cdk9/P-TEFb recruitment to Ik target genes, thereby affecting transcription elongation. Finally, characterization of a novel nuclear Ik isoform revealed that Ik exon 6 is dispensable for interactions with Mi2 and GATA proteins but is essential for the Cdk9 interaction. Thus, Ik is central to the Ik-GATA-Cdk9 regulatory network, which is broadly utilized for gene regulation in hematopoietic cells.

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

    PubMed

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

    2018-01-15

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

  10. A Method for Predicting Protein Complexes from Dynamic Weighted Protein-Protein Interaction Networks.

    PubMed

    Liu, Lizhen; Sun, Xiaowu; Song, Wei; Du, Chao

    2018-06-01

    Predicting protein complexes from protein-protein interaction (PPI) network is of great significance to recognize the structure and function of cells. A protein may interact with different proteins under different time or conditions. Existing approaches only utilize static PPI network data that may lose much temporal biological information. First, this article proposed a novel method that combines gene expression data at different time points with traditional static PPI network to construct different dynamic subnetworks. Second, to further filter out the data noise, the semantic similarity based on gene ontology is regarded as the network weight together with the principal component analysis, which is introduced to deal with the weight computing by three traditional methods. Third, after building a dynamic PPI network, a predicting protein complexes algorithm based on "core-attachment" structural feature is applied to detect complexes from each dynamic subnetworks. Finally, it is revealed from the experimental results that our method proposed in this article performs well on detecting protein complexes from dynamic weighted PPI networks.

  11. Computational prediction of virus-human protein-protein interactions using embedding kernelized heterogeneous data.

    PubMed

    Nourani, Esmaeil; Khunjush, Farshad; Durmuş, Saliha

    2016-05-24

    Pathogenic microorganisms exploit host cellular mechanisms and evade host defense mechanisms through molecular pathogen-host interactions (PHIs). Therefore, comprehensive analysis of these PHI networks should be an initial step for developing effective therapeutics against infectious diseases. Computational prediction of PHI data is gaining increasing demand because of scarcity of experimental data. Prediction of protein-protein interactions (PPIs) within PHI systems can be formulated as a classification problem, which requires the knowledge of non-interacting protein pairs. This is a restricting requirement since we lack datasets that report non-interacting protein pairs. In this study, we formulated the "computational prediction of PHI data" problem using kernel embedding of heterogeneous data. This eliminates the abovementioned requirement and enables us to predict new interactions without randomly labeling protein pairs as non-interacting. Domain-domain associations are used to filter the predicted results leading to 175 novel PHIs between 170 human proteins and 105 viral proteins. To compare our results with the state-of-the-art studies that use a binary classification formulation, we modified our settings to consider the same formulation. Detailed evaluations are conducted and our results provide more than 10 percent improvements for accuracy and AUC (area under the receiving operating curve) results in comparison with state-of-the-art methods.

  12. 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

  13. Combining multiple positive training sets to generate confidence scores for protein-protein interactions.

    PubMed

    Yu, Jingkai; Finley, Russell L

    2009-01-01

    High-throughput experimental and computational methods are generating a wealth of protein-protein interaction data for a variety of organisms. However, data produced by current state-of-the-art methods include many false positives, which can hinder the analyses needed to derive biological insights. One way to address this problem is to assign confidence scores that reflect the reliability and biological significance of each interaction. Most previously described scoring methods use a set of likely true positives to train a model to score all interactions in a dataset. A single positive training set, however, may be biased and not representative of true interaction space. We demonstrate a method to score protein interactions by utilizing multiple independent sets of training positives to reduce the potential bias inherent in using a single training set. We used a set of benchmark yeast protein interactions to show that our approach outperforms other scoring methods. Our approach can also score interactions across data types, which makes it more widely applicable than many previously proposed methods. We applied the method to protein interaction data from both Drosophila melanogaster and Homo sapiens. Independent evaluations show that the resulting confidence scores accurately reflect the biological significance of the interactions.

  14. Evolutionary plasticity of plasma membrane interaction in DREPP family proteins.

    PubMed

    Vosolsobě, Stanislav; Petrášek, Jan; Schwarzerová, Kateřina

    2017-05-01

    The plant-specific DREPP protein family comprises proteins that were shown to regulate the actin and microtubular cytoskeleton in a calcium-dependent manner. Our phylogenetic analysis showed that DREPPs first appeared in ferns and that DREPPs have a rapid and plastic evolutionary history in plants. Arabidopsis DREPP paralogues called AtMDP25/PCaP1 and AtMAP18/PCaP2 are N-myristoylated, which has been reported as a key factor in plasma membrane localization. Here we show that N-myristoylation is neither conserved nor ancestral for the DREPP family. Instead, by using confocal microscopy and a new method for quantitative evaluation of protein membrane localization, we show that DREPPs rely on two mechanisms ensuring their plasma membrane localization. These include N-myristoylation and electrostatic interaction of a polybasic amino acid cluster. We propose that various plasma membrane association mechanisms resulting from the evolutionary plasticity of DREPPs are important for refining plasma membrane interaction of these signalling proteins under various conditions and in various cells. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Identification of Karyopherin α1 and α7 Interacting Proteins in Porcine Tissue

    PubMed Central

    Park, Ki-Eun; Inerowicz, H. Dorota; Wang, Xin; Li, Yanfang; Koser, Stephanie; Cabot, Ryan A.

    2012-01-01

    Specialized trafficking systems in eukaryotic cells serve a critical role in partitioning intracellular proteins between the nucleus and cytoplasm. Cytoplasmic proteins (including chromatin remodeling enzymes and transcription factors) must gain access to the nucleus to exert their functions to properly program fundamental cellular events ranging from cell cycle progression to gene transcription. Knowing that nuclear import mediated by members of the karyopherin α family of transport receptors plays a critical role in regulating development and differentiation, we wanted to determine the identity of proteins that are trafficked by this karyopherin α pathway. To this end, we performed a GST pull-down assay using porcine orthologs of karyopherin α1 (KPNA1) and karyopherin α7 (KPNA7) and prey protein derived from porcine fibroblast cells and used a liquid chromatography and tandem mass spectrometry (LC-MS/MS) approach to determine the identity of KPNA1 and KPNA7 interacting proteins. Our screen revealed that the proteins that interact with KPNA1 and KPNA7 are generally nuclear proteins that possess nuclear localization signals. We further validated two candidate proteins from this screen and showed that they are able to be imported into the nucleus in vivo and also interact with members of the karyopherin α family of proteins in vitro. Our results also reveal the utility of using a GST pull-down approach coupled with LC-MS/MS to screen for protein interaction partners in a non-traditional model system. PMID:22720010

  16. Force spectroscopy studies on protein-ligand interactions: a single protein mechanics perspective.

    PubMed

    Hu, Xiaotang; Li, Hongbin

    2014-10-01

    Protein-ligand interactions are ubiquitous and play important roles in almost every biological process. The direct elucidation of the thermodynamic, structural and functional consequences of protein-ligand interactions is thus of critical importance to decipher the mechanism underlying these biological processes. A toolbox containing a variety of powerful techniques has been developed to quantitatively study protein-ligand interactions in vitro as well as in living systems. The development of atomic force microscopy-based single molecule force spectroscopy techniques has expanded this toolbox and made it possible to directly probe the mechanical consequence of ligand binding on proteins. Many recent experiments have revealed how ligand binding affects the mechanical stability and mechanical unfolding dynamics of proteins, and provided mechanistic understanding on these effects. The enhancement effect of mechanical stability by ligand binding has been used to help tune the mechanical stability of proteins in a rational manner and develop novel functional binding assays for protein-ligand interactions. Single molecule force spectroscopy studies have started to shed new lights on the structural and functional consequence of ligand binding on proteins that bear force under their biological settings. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  17. Multiple Interacting Risk Factors: On Methods for Allocating Risk Factor Interactions.

    PubMed

    Price, Bertram; MacNicoll, Michael

    2015-05-01

    A persistent problem in health risk analysis where it is known that a disease may occur as a consequence of multiple risk factors with interactions is allocating the total risk of the disease among the individual risk factors. This problem, referred to here as risk apportionment, arises in various venues, including: (i) public health management, (ii) government programs for compensating injured individuals, and (iii) litigation. Two methods have been described in the risk analysis and epidemiology literature for allocating total risk among individual risk factors. One method uses weights to allocate interactions among the individual risk factors. The other method is based on risk accounting axioms and finding an optimal and unique allocation that satisfies the axioms using a procedure borrowed from game theory. Where relative risk or attributable risk is the risk measure, we find that the game-theory-determined allocation is the same as the allocation where risk factor interactions are apportioned to individual risk factors using equal weights. Therefore, the apportionment problem becomes one of selecting a meaningful set of weights for allocating interactions among the individual risk factors. Equal weights and weights proportional to the risks of the individual risk factors are discussed. © 2015 Society for Risk Analysis.

  18. Protein Interactions in T7 DNA Replisome Facilitate DNA Damage Bypass.

    PubMed

    Zou, Zhenyu; Chen, Ze; Xue, Qizhen; Xu, Ying; Xiong, Jingyuan; Yang, Ping; Le, Shuai; Zhang, Huidong

    2018-06-14

    DNA replisome inevitably encounters DNA damage during DNA replication. T7 DNA replisome contains DNA polymerase (gp5), the processivity factor thioredoxin (trx), helicase-primase (gp4), and ssDNA binding protein (gp2.5). T7 protein interactions mediate this DNA replication. However, whether the protein interactions could promote DNA damage bypass is still little addressed. In this study, we investigated the strand-displacement DNA synthesis past 8-oxoG or O6-MeG at the synthetic DNA fork by T7 DNA replisome. DNA damage does not obviously affect the binding affinities among helicase, polymerase, and DNA fork. Relative to unmodified G, both 8-oxoG and O6-MeG, as well as GC-rich template sequence clusters, inhibit the strand-displacement DNA synthesis and produce partial extension products. Relative to gp4 ΔC-tail, gp4 promotes the DNA damage bypass. The presence of gp2.5 further promotes this bypass. Thus, the interactions of polymerase with helicase and ssDNA binidng protein faciliate the DNA damage bypass. Similarly, accessory proteins in other complicated DNA replisomes also facilitate the DNA damage bypass. This work provides the novel mechanism information of DNA damage bypass by DNA replisome. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Parallel Force Assay for Protein-Protein Interactions

    PubMed Central

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

    2014-01-01

    Quantitative proteome research is greatly promoted by high-resolution parallel format assays. A characterization of protein complexes based on binding forces offers an unparalleled dynamic range and allows for the effective discrimination of non-specific interactions. Here we present a DNA-based Molecular Force Assay to quantify protein-protein interactions, namely the bond between different variants of GFP and GFP-binding nanobodies. We present different strategies to adjust the maximum sensitivity window of the assay by influencing the binding strength of the DNA reference duplexes. The binding of the nanobody Enhancer to the different GFP constructs is compared at high sensitivity of the assay. Whereas the binding strength to wild type and enhanced GFP are equal within experimental error, stronger binding to superfolder GFP is observed. This difference in binding strength is attributed to alterations in the amino acids that form contacts according to the crystal structure of the initial wild type GFP-Enhancer complex. Moreover, we outline the potential for large-scale parallelization of the assay. PMID:25546146

  20. Protein Surface Mimetics: Understanding How Ruthenium Tris(Bipyridines) Interact with Proteins.

    PubMed

    Hewitt, Sarah H; Filby, Maria H; Hayes, Ed; Kuhn, Lars T; Kalverda, Arnout P; Webb, Michael E; Wilson, Andrew J

    2017-01-17

    Protein surface mimetics achieve high-affinity binding by exploiting a scaffold to project binding groups over a large area of solvent-exposed protein surface to make multiple cooperative noncovalent interactions. Such recognition is a prerequisite for competitive/orthosteric inhibition of protein-protein interactions (PPIs). This paper describes biophysical and structural studies on ruthenium(II) tris(bipyridine) surface mimetics that recognize cytochrome (cyt) c and inhibit the cyt c/cyt c peroxidase (CCP) PPI. Binding is electrostatically driven, with enhanced affinity achieved through enthalpic contributions thought to arise from the ability of the surface mimetics to make a greater number of noncovalent interactions than CCP with surface-exposed basic residues on cyt c. High-field natural abundance 1 H, 15 N HSQC NMR experiments are consistent with surface mimetics binding to cyt c in similar manner to CCP. This provides a framework for understanding recognition of proteins by supramolecular receptors and informing the design of ligands superior to the protein partners upon which they are inspired. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. 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

  2. Mining Host-Pathogen Protein Interactions to Characterize Burkholderia mallei Infectivity Mechanisms

    DTIC Science & Technology

    2015-03-04

    were shown to attenuate disease progression in an aerosol infection animal model using the virulent Burkholderia mallei ATCC 23344 strain. Here, we...performed an extended analysis of primarily nine B. mallei virulence factors and their interactions with human proteins to map out how the bacteria can...virulent Burkholderia mallei ATCC 23344 strain. Here, we performed an extended analysis of primarily nine B. mallei virulence factors and their

  3. Protein interactions and ligand binding: from protein subfamilies to functional specificity.

    PubMed

    Rausell, Antonio; Juan, David; Pazos, Florencio; Valencia, Alfonso

    2010-02-02

    The divergence accumulated during the evolution of protein families translates into their internal organization as subfamilies, and it is directly reflected in the characteristic patterns of differentially conserved residues. These specifically conserved positions in protein subfamilies are known as "specificity determining positions" (SDPs). Previous studies have limited their analysis to the study of the relationship between these positions and ligand-binding specificity, demonstrating significant yet limited predictive capacity. We have systematically extended this observation to include the role of differential protein interactions in the segregation of protein subfamilies and explored in detail the structural distribution of SDPs at protein interfaces. Our results show the extensive influence of protein interactions in the evolution of protein families and the widespread association of SDPs with protein interfaces. The combined analysis of SDPs in interfaces and ligand-binding sites provides a more complete picture of the organization of protein families, constituting the necessary framework for a large scale analysis of the evolution of protein function.

  4. Protein-surface interactions on stimuli-responsive polymeric biomaterials.

    PubMed

    Cross, Michael C; Toomey, Ryan G; Gallant, Nathan D

    2016-03-04

    Responsive surfaces: a review of the dependence of protein adsorption on the reversible volume phase transition in stimuli-responsive polymers. Specifically addressed are a widely studied subset: thermoresponsive polymers. Findings are also generalizable to other materials which undergo a similarly reversible volume phase transition. As of 2015, over 100,000 articles have been published on stimuli-responsive polymers and many more on protein-biomaterial interactions. Significantly, fewer than 100 of these have focused specifically on protein interactions with stimuli-responsive polymers. These report a clear trend of increased protein adsorption in the collapsed state compared to the swollen state. This control over protein interactions makes stimuli-responsive polymers highly useful in biomedical applications such as wound repair scaffolds, on-demand drug delivery, and antifouling surfaces. Outstanding questions are whether the protein adsorption is reversible with the volume phase transition and whether there is a time-dependence. A clear understanding of protein interactions with stimuli-responsive polymers will advance theoretical models, experimental results, and biomedical applications.

  5. Protein Interaction Profile Sequencing (PIP-seq).

    PubMed

    Foley, Shawn W; Gregory, Brian D

    2016-10-10

    Every eukaryotic RNA transcript undergoes extensive post-transcriptional processing from the moment of transcription up through degradation. This regulation is performed by a distinct cohort of RNA-binding proteins which recognize their target transcript by both its primary sequence and secondary structure. Here, we describe protein interaction profile sequencing (PIP-seq), a technique that uses ribonuclease-based footprinting followed by high-throughput sequencing to globally assess both protein-bound RNA sequences and RNA secondary structure. PIP-seq utilizes single- and double-stranded RNA-specific nucleases in the absence of proteins to infer RNA secondary structure. These libraries are also compared to samples that undergo nuclease digestion in the presence of proteins in order to find enriched protein-bound sequences. Combined, these four libraries provide a comprehensive, transcriptome-wide view of RNA secondary structure and RNA protein interaction sites from a single experimental technique. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

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

    PubMed

    Folador, Edson Luiz; de Carvalho, Paulo Vinícius Sanches Daltro; Silva, Wanderson Marques; Ferreira, Rafaela Salgado; Silva, Artur; Gromiha, Michael; Ghosh, Preetam; Barh, Debmalya; Azevedo, Vasco; Röttger, Richard

    2016-11-04

    Corynebacterium pseudotuberculosis (Cp) is a gram-positive bacterium that is classified into equi and ovis serovars. The serovar ovis is the etiological agent of caseous lymphadenitis, a chronic infection affecting sheep and goats, causing economic losses due to carcass condemnation and decreased production of meat, wool, and milk. Current diagnosis or treatment protocols are not fully effective and, thus, require further research of Cp pathogenesis. Here, we mapped known protein-protein interactions (PPI) from various species to nine Cp strains to reconstruct parts of the potential Cp interactome and to identify potentially essential proteins serving as putative drug targets. On average, we predict 16,669 interactions for each of the nine strains (with 15,495 interactions shared among all strains). An in silico sanity check suggests that the potential networks were not formed by spurious interactions but have a strong biological bias. With the inferred Cp networks we identify 181 essential proteins, among which 41 are non-host homologous. The list of candidate interactions of the Cp strains lay the basis for developing novel hypotheses and designing according wet-lab studies. The non-host homologous essential proteins are attractive targets for therapeutic and diagnostic proposes. They allow for searching of small molecule inhibitors of binding interactions enabling modern drug discovery. Overall, the predicted Cp PPI networks form a valuable and versatile tool for researchers interested in Corynebacterium pseudotuberculosis.

  7. Aberrant Huntingtin interacting protein 1 in lymphoid malignancies.

    PubMed

    Bradley, Sarah V; Smith, Mitchell R; Hyun, Teresa S; Lucas, Peter C; Li, Lina; Antonuk, Danielle; Joshi, Indira; Jin, Fang; Ross, Theodora S

    2007-09-15

    Huntingtin interacting protein 1 (HIP1) is an inositol lipid, clathrin, and actin binding protein that is overexpressed in a variety of epithelial malignancies. Here, we report for the first time that HIP1 is elevated in non-Hodgkin's and Hodgkin's lymphomas and that patients with lymphoid malignancies frequently had anti-HIP1 antibodies in their serum. Moreover, p53-deficient mice with B-cell lymphomas were 13 times more likely to have anti-HIP1 antibodies in their serum than control mice. Furthermore, transgenic overexpression of HIP1 was associated with the development of lymphoid neoplasms. The HIP1 protein was induced by activation of the nuclear factor-kappaB pathway, which is frequently activated in lymphoid malignancies. These data identify HIP1 as a new marker of lymphoid malignancies that contributes to the transformation of lymphoid cells in vivo.

  8. Role for protein–protein interaction databases in human genetics

    PubMed Central

    Pattin, Kristine A; Moore, Jason H

    2010-01-01

    Proteomics and the study of protein–protein interactions are becoming increasingly important in our effort to understand human diseases on a system-wide level. Thanks to the development and curation of protein-interaction databases, up-to-date information on these interaction networks is accessible and publicly available to the scientific community. As our knowledge of protein–protein interactions increases, it is important to give thought to the different ways that these resources can impact biomedical research. In this article, we highlight the importance of protein–protein interactions in human genetics and genetic epidemiology. Since protein–protein interactions demonstrate one of the strongest functional relationships between genes, combining genomic data with available proteomic data may provide us with a more in-depth understanding of common human diseases. In this review, we will discuss some of the fundamentals of protein interactions, the databases that are publicly available and how information from these databases can be used to facilitate genome-wide genetic studies. PMID:19929610

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

    Cancer.gov

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

  10. High-Sensitivity Real-Time Imaging of Dual Protein-Protein Interactions in Living Subjects Using Multicolor Luciferases

    PubMed Central

    Hida, Naoki; Awais, Muhammad; Takeuchi, Masaki; Ueno, Naoto; Tashiro, Mayuri; Takagi, Chiyo; Singh, Tanuja; Hayashi, Makoto; Ohmiya, Yoshihiro; Ozawa, Takeaki

    2009-01-01

    Networks of protein-protein interactions play key roles in numerous important biological processes in living subjects. An effective methodology to assess protein-protein interactions in living cells of interest is protein-fragment complement assay (PCA). Particularly the assays using fluorescent proteins are powerful techniques, but they do not directly track interactions because of its irreversibility or the time for chromophore formation. By contrast, PCAs using bioluminescent proteins can overcome these drawbacks. We herein describe an imaging method for real-time analysis of protein-protein interactions using multicolor luciferases with different spectral characteristics. The sensitivity and signal-to-background ratio were improved considerably by developing a carboxy-terminal fragment engineered from a click beetle luciferase. We demonstrate its utility in spatiotemporal characterization of Smad1–Smad4 and Smad2–Smad4 interactions in early developing stages of a single living Xenopus laevis embryo. We also describe the value of this method by application of specific protein-protein interactions in cell cultures and living mice. This technique supports quantitative analyses and imaging of versatile protein-protein interactions with a selective luminescence wavelength in opaque or strongly auto-fluorescent living subjects. PMID:19536355

  11. Affinity purification combined with mass spectrometry to identify herpes simplex virus protein-protein interactions.

    PubMed

    Meckes, David G

    2014-01-01

    The identification and characterization of herpes simplex virus protein interaction complexes are fundamental to understanding the molecular mechanisms governing the replication and pathogenesis of the virus. Recent advances in affinity-based methods, mass spectrometry configurations, and bioinformatics tools have greatly increased the quantity and quality of protein-protein interaction datasets. In this chapter, detailed and reliable methods that can easily be implemented are presented for the identification of protein-protein interactions using cryogenic cell lysis, affinity purification, trypsin digestion, and mass spectrometry.

  12. Identification of FBXO25-interacting Proteins Using an Integrated Proteomics Approach

    PubMed Central

    Teixeira, Felipe R.; Yokoo, Sami; Gartner, Carlos G.; Manfiolli, Adriana O.; Baqui, Munira M. A.; Assmann, Eliana M.; Maragno, Ana Leticia G. C.; Yu, Huijun; de Lanerolle, Primal; Kobarg, Jörg; Gygi, Steven P.; Gomes, Marcelo D.

    2011-01-01

    FBXO25 is one of 68 human F-box proteins that serve as specificity factors for a family of ubiquitin ligases composed of Skp1, Rbx1, Cullin1 and F-box protein (SCF1) that are involved in targeting proteins for destruction across the ubiquitin proteasome system. We recently reported that the FBXO25 protein accumulates in novel subnuclear structures named FBXO25-associated nuclear domains (FANDs). Combining two-step affinity purification followed by mass spectrometry with a classical two-hybrid screen, we identified 132 novel potential FBXO25 interacting partners. One of the identified proteins, β-actin, physically interacts through its N-terminus with FBXO25 and is enriched in the FBXO25 nuclear compartments. Inhibitors of actin polymerization promote a significant disruption of FANDs, indicating that they are compartments influenced by the organizational state of actin in the nucleus. Furthermore, FBXO25 antibodies interfered with RNA polymerase II transcription in vitro. Our results open new perspectives for the understanding of this novel compartment and its nuclear functions. PMID:20473970

  13. New partner proteins containing novel internal recognition motif for human Glutaminase Interacting Protein (hGIP)

    PubMed Central

    Zencir, Sevil; Banerjee, Monimoy; Dobson, Melanie J.; Ayaydin, Ferhan; Fodor, Elfrieda Ayaydin; Topcu, Zeki; Mohanty, Smita

    2013-01-01

    Regulation of gene expression in cells is mediated by protein-protein, DNA-protein and receptor-ligand interactions. PDZ (PSD-95/Discs-large/ZO-1) domains are protein–protein interaction modules. PDZ-containing proteins function in the organization of multi-protein complexes controlling spatial and temporal fidelity of intracellular signaling pathways. In general, PDZ proteins possess multiple domains facilitating distinct interactions. The human Glutaminase Interacting Protein (hGIP) is an unusual PDZ protein comprising entirely of a single PDZ domain and plays pivotal roles in many cellular processes through its interaction with the C-terminus of partner proteins. Here, we report the identification by yeast two-hybrid screening of two new hGIP-interacting partners, DTX1 and STAU1. Both proteins lack the typical C-terminal PDZ recognition motif but contain a novel internal hGIP recognition motif recently identified in a phage display library screen. Fluorescence resonance energy transfer and confocal microscopy analysis confirmed the in vivo association of hGIP with DTX1 and STAU1 in mammalian cells validating the previous discovery of S/T-X-V/L-D as a consensus internal motif for hGIP recognition. Similar to hGIP, DTX1 and STAU1 have been implicated in neuronal function. Identification of these new interacting partners furthers our understanding of GIP-regulated signaling cascades and these interactions may represent potential new drug targets in humans. PMID:23395680

  14. The interactive association between heat shock factor 1 and heat shock proteins in primary myocardial cells subjected to heat stress.

    PubMed

    Tang, Shu; Chen, Hongbo; Cheng, Yanfen; Nasir, Mohammad Abdel; Kemper, Nicole; Bao, Endong

    2016-01-01

    Heat shock factor 1 (HSF1) is a heat shock transcription factor that rapidly induces heat shock gene transcription following thermal stress. In this study, we subjected primary neonatal rat myocardial cells to heat stress in vitro to create a model system for investigating the trends in expression and association between various heat shock proteins (HSPs) and HSF1 under adverse environmental conditions. After the cells were subjected to heat stress at 42˚C for different periods of time, HSP and HSF1 mRNA and protein levels were detected by qPCR and western blot analysis in the heat-stressed cells. The HSF1 expression levels significantly increased in the cells following 120 min of exposure to heat stess compared to the levels observed at the beginning of heat stress exposure. HSP90 followed a similar trend in expression to HSF1, whereas HSP70 followed an opposite trend. However, no significant changes were observed in the crystallin, alpha B (CRYAB, also known as HSP beta-5) expression levels during the 480‑min period of exposure to heat stress. The interaction between the HSPs and HSF1 was analyzed by STRING 9.1, and it was found that HSF1 interacted with HSP90 and HSP70, and that it did not play a role in regulating CRYAB expression. Based on our findings, HSP70 may suppress HSF1 in rat myocardial cells under conditions of heat stress. Furthermore, our data demonstrate that HSF1 is not the key factor for all HSPs, and this was particularly the case for CRYAB.

  15. The interactive association between heat shock factor 1 and heat shock proteins in primary myocardial cells subjected to heat stress

    PubMed Central

    TANG, SHU; CHEN, HONGBO; CHENG, YANFEN; NASIR, MOHAMMAD ABDEL; KEMPER, NICOLE; BAO, ENDONG

    2016-01-01

    Heat shock factor 1 (HSF1) is a heat shock transcription factor that rapidly induces heat shock gene transcription following thermal stress. In this study, we subjected primary neonatal rat myocardial cells to heat stress in vitro to create a model system for investigating the trends in expression and association between various heat shock proteins (HSPs) and HSF1 under adverse environmental conditions. After the cells were subjected to heat stress at 42°C for different periods of time, HSP and HSF1 mRNA and protein levels were detected by qPCR and western blot analysis in the heat-stressed cells. The HSF1 expression levels significantly increased in the cells following 120 min of exposure to heat stess compared to the levels observed at the beginning of heat stress exposure. HSP90 followed a similar trend in expression to HSF1, whereas HSP70 followed an opposite trend. However, no significant changes were observed in the crystallin, alpha B (CRYAB, also known as HSP beta-5) expression levels during the 480-min period of exposure to heat stress. The interaction between the HSPs and HSF1 was analyzed by STRING 9.1, and it was found that HSF1 interacted with HSP90 and HSP70, and that it did not play a role in regulating CRYAB expression. Based on our findings, HSP70 may suppress HSF1 in rat myocardial cells under conditions of heat stress. Furthermore, our data demonstrate that HSF1 is not the key factor for all HSPs, and this was particularly the case for CRYAB. PMID:26719858

  16. Stapled Voltage-Gated Calcium Channel (CaV) α-Interaction Domain (AID) Peptides Act As Selective Protein-Protein Interaction Inhibitors of CaV Function.

    PubMed

    Findeisen, Felix; Campiglio, Marta; Jo, Hyunil; Abderemane-Ali, Fayal; Rumpf, Christine H; Pope, Lianne; Rossen, Nathan D; Flucher, Bernhard E; DeGrado, William F; Minor, Daniel L

    2017-06-21

    For many voltage-gated ion channels (VGICs), creation of a properly functioning ion channel requires the formation of specific protein-protein interactions between the transmembrane pore-forming subunits and cystoplasmic accessory subunits. Despite the importance of such protein-protein interactions in VGIC function and assembly, their potential as sites for VGIC modulator development has been largely overlooked. Here, we develop meta-xylyl (m-xylyl) stapled peptides that target a prototypic VGIC high affinity protein-protein interaction, the interaction between the voltage-gated calcium channel (Ca V ) pore-forming subunit α-interaction domain (AID) and cytoplasmic β-subunit (Ca V β). We show using circular dichroism spectroscopy, X-ray crystallography, and isothermal titration calorimetry that the m-xylyl staples enhance AID helix formation are structurally compatible with native-like AID:Ca V β interactions and reduce the entropic penalty associated with AID binding to Ca V β. Importantly, electrophysiological studies reveal that stapled AID peptides act as effective inhibitors of the Ca V α 1 :Ca V β interaction that modulate Ca V function in an Ca V β isoform-selective manner. Together, our studies provide a proof-of-concept demonstration of the use of protein-protein interaction inhibitors to control VGIC function and point to strategies for improved AID-based Ca V modulator design.

  17. In silico modeling of the yeast protein and protein family interaction network

    NASA Astrophysics Data System (ADS)

    Goh, K.-I.; Kahng, B.; Kim, D.

    2004-03-01

    Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

  18. Dynamic interactions of proteins in complex networks

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    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 withmore » 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

  19. A Computational Investigation of Small-Molecule Engagement of Hot Spots at Protein-Protein Interaction Interfaces.

    PubMed

    Xu, David; Si, Yubing; Meroueh, Samy O

    2017-09-25

    The binding affinity of a protein-protein interaction is concentrated at amino acids known as hot spots. It has been suggested that small molecules disrupt protein-protein interactions by either (i) engaging receptor protein hot spots or (ii) mimicking hot spots of the protein ligand. Yet, no systematic studies have been done to explore how effectively existing small-molecule protein-protein interaction inhibitors mimic or engage hot spots at protein interfaces. Here, we employ explicit-solvent molecular dynamics simulations and end-point MM-GBSA free energy calculations to explore this question. We select 36 compounds for which high-quality binding affinity and cocrystal structures are available. Five complexes that belong to three classes of protein-protein interactions (primary, secondary, and tertiary) were considered, namely, BRD4•H4, XIAP•Smac, MDM2•p53, Bcl-xL•Bak, and IL-2•IL-2Rα. Computational alanine scanning using MM-GBSA identified hot-spot residues at the interface of these protein interactions. Decomposition energies compared the interaction of small molecules with individual receptor hot spots to those of the native protein ligand. Pharmacophore analysis was used to investigate how effectively small molecules mimic the position of hot spots of the protein ligand. Finally, we study whether small molecules mimic the effects of the native protein ligand on the receptor dynamics. Our results show that, in general, existing small-molecule inhibitors of protein-protein interactions do not optimally mimic protein-ligand hot spots, nor do they effectively engage protein receptor hot spots. The more effective use of hot spots in future drug design efforts may result in smaller compounds with higher ligand efficiencies that may lead to greater success in clinical trials.

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

    PubMed

    Cantu, Dario; Yang, Baoju; Ruan, Randy; Li, Kun; Menzo, Virginia; Fu, Daolin; Chern, Mawsheng; Ronald, Pamela C; Dubcovsky, Jorge

    2013-03-12

    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). 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. The observed high conservation of interactions between proteins that

  1. Rapid and sensitive MRM-based mass spectrometry approach for systematically exploring ganglioside-protein interactions.

    PubMed

    Tian, Ruijun; Jin, Jing; Taylor, Lorne; Larsen, Brett; Quaggin, Susan E; Pawson, Tony

    2013-04-01

    Gangliosides are ubiquitous components of cell membranes. Their interactions with bacterial toxins and membrane-associated proteins (e.g. receptor tyrosine kinases) have important roles in the regulation of multiple cellular functions. Currently, an effective approach for measuring ganglioside-protein interactions especially in a large-scale fashion is largely missing. To this end, we report a facile MS-based approach to explore gangliosides extracted from cells and measure their interactions with protein of interest globally. We optimized a two-step protocol for extracting total gangliosides from cells within 2 h. Easy-to-use magnetic beads conjugated with a protein of interest were used to capture interacting gangliosides. To measure ganglioside-protein interaction on a global scale, we applied a high-sensitive LC-MS system, containing hydrophilic interaction LC separation and multiple reaction monitoring-based MS for ganglioside detection. Sensitivity for ganglioside GM1 is below 100 pg, and the whole analysis can be done in 20 min with isocratic elution. To measure ganglioside interactions with soluble vascular endothelial growth factor receptor 1 (sFlt1), we extracted and readily detected 36 species of gangliosides from perivascular retinal pigment epithelium cells across eight different classes. Twenty-three ganglioside species have significant interactions with sFlt1 as compared with IgG control based on p value cutoff <0.05. These results show that the described method provides a rapid and high-sensitive approach for systematically measuring ganglioside-protein interactions. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Factor VIII Interacts with the Endocytic Receptor Low-density Lipoprotein Receptor-related Protein 1 via an Extended Surface Comprising "Hot-Spot" Lysine Residues.

    PubMed

    van den Biggelaar, Maartje; Madsen, Jesper J; Faber, Johan H; Zuurveld, Marleen G; van der Zwaan, Carmen; Olsen, Ole H; Stennicke, Henning R; Mertens, Koen; Meijer, Alexander B

    2015-07-03

    Lysine residues are implicated in driving the ligand binding to the LDL receptor family. However, it has remained unclear how specificity is regulated. Using coagulation factor VIII as a model ligand, we now study the contribution of individual lysine residues in the interaction with the largest member of the LDL receptor family, low-density lipoprotein receptor-related protein (LRP1). Using hydrogen-deuterium exchange mass spectrometry (HDX-MS) and SPR interaction analysis on a library of lysine replacement variants as two independent approaches, we demonstrate that the interaction between factor VIII (FVIII) and LRP1 occurs over an extended surface containing multiple lysine residues. None of the individual lysine residues account completely for LRP1 binding, suggesting an additive binding model. Together with structural docking studies, our data suggest that FVIII interacts with LRP1 via an extended surface of multiple lysine residues that starts at the bottom of the C1 domain and winds around the FVIII molecule. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  3. Interaction of CSFV E2 Protein with Swine Host Factors as Detected by Yeast Two-Hybrid System

    PubMed Central

    Gladue, Douglas P.; Baker-Bransetter, Ryan; Holinka, Lauren G.; Fernandez-Sainz, Ignacio J.; O’Donnell, Vivian; Fletcher, Paige; Lu, Zhiqiang; Borca, Manuel V.

    2014-01-01

    E2 is one of the envelope glycoproteins of pestiviruses, including classical swine fever virus (CSFV) and bovine viral diarrhea virus (BVDV). E2 is involved in several critical functions, including virus entry into target cells, induction of a protective immune response and virulence in swine. However, there is no information regarding any host binding partners for the E2 proteins. Here, we utilized the yeast two-hybrid system and identified fifty-seven host proteins as positive binding partners which bound E2 from both CSFV and BVDV with the exception of two proteins that were found to be positive for binding only to CSFV E2. Alanine scanning of CSFV E2 demonstrated that the binding sites for these cellular proteins on E2 are likely non-linear binding sites. The possible roles of the identified host proteins are discussed as the results presented here will be important for future studies to elucidate mechanisms of host protein-virus interactions during pestivirus infection. However, due to the limitations of the yeast two hybrid system, the proteins identified is not exhaustive and each interaction identified needs to be confirmed by independent experimental approaches in the context of virus-infected cells before any definitive conclusion can be drawn on relevance for the virus life cycle. PMID:24416391

  4. The HUPO PSI's molecular interaction format--a community standard for the representation of protein interaction data.

    PubMed

    Hermjakob, Henning; Montecchi-Palazzi, Luisa; Bader, Gary; Wojcik, Jérôme; Salwinski, Lukasz; Ceol, Arnaud; Moore, Susan; Orchard, Sandra; Sarkans, Ugis; von Mering, Christian; Roechert, Bernd; Poux, Sylvain; Jung, Eva; Mersch, Henning; Kersey, Paul; Lappe, Michael; Li, Yixue; Zeng, Rong; Rana, Debashis; Nikolski, Macha; Husi, Holger; Brun, Christine; Shanker, K; Grant, Seth G N; Sander, Chris; Bork, Peer; Zhu, Weimin; Pandey, Akhilesh; Brazma, Alvis; Jacq, Bernard; Vidal, Marc; Sherman, David; Legrain, Pierre; Cesareni, Gianni; Xenarios, Ioannis; Eisenberg, David; Steipe, Boris; Hogue, Chris; Apweiler, Rolf

    2004-02-01

    A major goal of proteomics is the complete description of the protein interaction network underlying cell physiology. A large number of small scale and, more recently, large-scale experiments have contributed to expanding our understanding of the nature of the interaction network. However, the necessary data integration across experiments is currently hampered by the fragmentation of publicly available protein interaction data, which exists in different formats in databases, on authors' websites or sometimes only in print publications. Here, we propose a community standard data model for the representation and exchange of protein interaction data. This data model has been jointly developed by members of the Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organization (HUPO), and is supported by major protein interaction data providers, in particular the Biomolecular Interaction Network Database (BIND), Cellzome (Heidelberg, Germany), the Database of Interacting Proteins (DIP), Dana Farber Cancer Institute (Boston, MA, USA), the Human Protein Reference Database (HPRD), Hybrigenics (Paris, France), the European Bioinformatics Institute's (EMBL-EBI, Hinxton, UK) IntAct, the Molecular Interactions (MINT, Rome, Italy) database, the Protein-Protein Interaction Database (PPID, Edinburgh, UK) and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING, EMBL, Heidelberg, Germany).

  5. Single-well monitoring of protein-protein interaction and phosphorylation-dephosphorylation events.

    PubMed

    Arcand, Mathieu; Roby, Philippe; Bossé, Roger; Lipari, Francesco; Padrós, Jaime; Beaudet, Lucille; Marcil, Alexandre; Dahan, Sophie

    2010-04-20

    We combined oxygen channeling assays with two distinct chemiluminescent beads to detect simultaneously protein phosphorylation and interaction events that are usually monitored separately. This novel method was tested in the ERK1/2 MAP kinase pathway. It was first used to directly monitor dissociation of MAP kinase ERK2 from MEK1 upon phosphorylation and to evaluate MAP kinase phosphatase (MKP) selectivity and mechanism of action. In addition, MEK1 and ERK2 were probed with an ATP competitor and an allosteric MEK1 inhibitor, which generated distinct phosphorylation-interaction patterns. Simultaneous monitoring of protein-protein interactions and substrate phosphorylation can provide significant mechanistic insight into enzyme activity and small molecule action.

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

    PubMed Central

    Pelassa, Ilaria; Fiumara, Ferdinando

    2015-01-01

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

  7. 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

  8. Trimeric Transmembrane Domain Interactions in Paramyxovirus Fusion Proteins

    PubMed Central

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

    2013-01-01

    Paramyxovirus fusion (F) proteins promote membrane fusion between the viral envelope and host cell membranes, a critical early step in viral infection. Although mutational analyses have indicated that transmembrane (TM) domain residues can affect folding or function of viral fusion proteins, direct analysis of TM-TM interactions has proved challenging. To directly assess TM interactions, the oligomeric state of purified chimeric proteins containing the Staphylococcal nuclease (SN) protein linked to the TM segments from three paramyxovirus F proteins was analyzed by sedimentation equilibrium analysis in detergent and buffer conditions that allowed density matching. A monomer-trimer equilibrium best fit was found for all three SN-TM constructs tested, and similar fits were obtained with peptides corresponding to just the TM region of two different paramyxovirus F proteins. These findings demonstrate for the first time that class I viral fusion protein TM domains can self-associate as trimeric complexes in the absence of the rest of the protein. Glycine residues have been implicated in TM helix interactions, so the effect of mutations at Hendra F Gly-508 was assessed in the context of the whole F protein. Mutations G508I or G508L resulted in decreased cell surface expression of the fusogenic form, consistent with decreased stability of the prefusion form of the protein. Sedimentation equilibrium analysis of TM domains containing these mutations gave higher relative association constants, suggesting altered TM-TM interactions. Overall, these results suggest that trimeric TM interactions are important driving forces for protein folding, stability and membrane fusion promotion. PMID:24178297

  9. Interaction of AIP with protein kinase A (cAMP-dependent protein kinase).

    PubMed

    Schernthaner-Reiter, Marie Helene; Trivellin, Giampaolo; Stratakis, Constantine A

    2018-05-02

    Germline mutations in the aryl hydrocarbon receptor-interacting protein (AIP) gene cause mostly somatotropinomas and/or prolactinomas in a subset of familial isolated pituitary adenomas (FIPA). AIP has been shown to interact with phosphodiesterases (PDEs) and G proteins, suggesting a link to the cyclic AMP (cAMP)-dependent protein kinase (PKA) pathway. Upregulation of PKA is seen in sporadic somatotropinomas that carry GNAS1 mutations, and those in Carney complex that are due to PRKAR1A mutations. To elucidate the mechanism of AIP-dependent pituitary tumorigenesis, we studied potential functional and physical interactions of AIP with PKA's main subunits PRKAR1A (R1α) and PRKACA (Cα). We found that AIP physically interacts with both R1α and Cα; this interaction is enhanced when all three components are present, but maintained during Cα-R1α dissociation by PKA pathway activation, indicating that AIP binds Cα/R1α both in complex and separately. The interaction between AIP and R1α/Cα is reduced when the frequent AIP pathogenic mutation p.R304* is present. AIP protein levels are regulated both by translation and the ubiquitin/proteasome pathway and Cα stabilizes both AIP and R1α protein levels. AIP reduction by siRNA leads to an increase of PKA pathway activity, which is disproportionately enhanced during PDE4-inhibition. We show that AIP interacts with the PKA pathway on multiple levels, including a physical interaction with both the main regulatory (R1α) and catalytic (Cα) PKA subunits and a functional interaction with PDE4-dependent PKA activation. These findings provide novel insights on the mechanisms of AIP-dependent pituitary tumorigenesis.

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

    PubMed Central

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

    2013-01-01

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

  11. Role of electrostatic interaction on surfactant induced protein unfolding

    NASA Astrophysics Data System (ADS)

    Sumit, Kumar, Sugam; Aswal, V. K.

    2013-02-01

    Small Angle Neutron Scattering has been used to examine the effect of electrostatic interaction on surfactant induced protein unfolding. Measurements are carried out from 1 wt% Bovine Serum Albumin (BSA) protein with 1 wt% Sodium Dodecyl Sulphate (SDS) surfactant at pH 7 in presence of varying concentration of NaCl. It is found that both the components (protein and surfactant micelle which are likely charged) exist individually without any interaction in absence of salt, whereas their interaction and protein unfolding is enhanced with the increase in salt concentration. The structure of protein-surfactant interaction is characterized by fractal bead-necklace model.

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

    PubMed

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

    2015-01-16

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

  13. Structural study of surfactant-dependent interaction with protein

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mehan, Sumit; Aswal, Vinod K., E-mail: vkaswal@barc.gov.in; 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.

  14. 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.

  15. Inhibition of nuclear factor kappaB proteins-platinated DNA interactions correlates with cytotoxic effectiveness of the platinum complexes

    PubMed Central

    Brabec, Viktor; Kasparkova, Jana; Kostrhunova, Hana; Farrell, Nicholas P.

    2016-01-01

    Nuclear DNA is the target responsible for anticancer activity of platinum anticancer drugs. Their activity is mediated by altered signals related to programmed cell death and the activation of various signaling pathways. An example is activation of nuclear factor kappaB (NF-κB). Binding of NF-κB proteins to their consensus sequences in DNA (κB sites) is the key biochemical activity responsible for the biological functions of NF-κB. Using gel-mobility-shift assays and surface plasmon resonance spectroscopy we examined the interactions of NF-κB proteins with oligodeoxyribonucleotide duplexes containing κB site damaged by DNA adducts of three platinum complexes. These complexes markedly differed in their toxic effects in tumor cells and comprised highly cytotoxic trinuclear platinum(II) complex BBR3464, less cytotoxic conventional cisplatin and ineffective transplatin. The results indicate that structurally different DNA adducts of these platinum complexes exhibit a different efficiency to affect the affinity of the platinated DNA (κB sites) to NF-κB proteins. Our results support the hypothesis that structural perturbations induced in DNA by platinum(II) complexes correlate with their higher efficiency to inhibit binding of NF-κB proteins to their κB sites and cytotoxicity as well. However, the full generalization of this hypothesis will require to evaluate a larger series of platinum(II) complexes. PMID:27574114

  16. Inhibition of nuclear factor kappaB proteins-platinated DNA interactions correlates with cytotoxic effectiveness of the platinum complexes.

    PubMed

    Brabec, Viktor; Kasparkova, Jana; Kostrhunova, Hana; Farrell, Nicholas P

    2016-08-30

    Nuclear DNA is the target responsible for anticancer activity of platinum anticancer drugs. Their activity is mediated by altered signals related to programmed cell death and the activation of various signaling pathways. An example is activation of nuclear factor kappaB (NF-κB). Binding of NF-κB proteins to their consensus sequences in DNA (κB sites) is the key biochemical activity responsible for the biological functions of NF-κB. Using gel-mobility-shift assays and surface plasmon resonance spectroscopy we examined the interactions of NF-κB proteins with oligodeoxyribonucleotide duplexes containing κB site damaged by DNA adducts of three platinum complexes. These complexes markedly differed in their toxic effects in tumor cells and comprised highly cytotoxic trinuclear platinum(II) complex BBR3464, less cytotoxic conventional cisplatin and ineffective transplatin. The results indicate that structurally different DNA adducts of these platinum complexes exhibit a different efficiency to affect the affinity of the platinated DNA (κB sites) to NF-κB proteins. Our results support the hypothesis that structural perturbations induced in DNA by platinum(II) complexes correlate with their higher efficiency to inhibit binding of NF-κB proteins to their κB sites and cytotoxicity as well. However, the full generalization of this hypothesis will require to evaluate a larger series of platinum(II) complexes.

  17. Gene essentiality and the topology of protein interaction networks

    PubMed Central

    Coulomb, Stéphane; Bauer, Michel; Bernard, Denis; Marsolier-Kergoat, Marie-Claude

    2005-01-01

    The mechanistic bases for gene essentiality and for cell mutational resistance have long been disputed. The recent availability of large protein interaction databases has fuelled the analysis of protein interaction networks and several authors have proposed that gene dispensability could be strongly related to some topological parameters of these networks. However, many results were based on protein interaction data whose biases were not taken into account. In this article, we show that the essentiality of a gene in yeast is poorly related to the number of interactants (or degree) of the corresponding protein and that the physiological consequences of gene deletions are unrelated to several other properties of proteins in the interaction networks, such as the average degrees of their nearest neighbours, their clustering coefficients or their relative distances. We also found that yeast protein interaction networks lack degree correlation, i.e. a propensity for their vertices to associate according to their degrees. Gene essentiality and more generally cell resistance against mutations thus seem largely unrelated to many parameters of protein network topology. PMID:16087428

  18. The effects of non-synonymous single nucleotide polymorphisms (nsSNPs) on protein-protein interactions.

    PubMed

    Yates, Christopher M; Sternberg, Michael J E

    2013-11-01

    Non-synonymous single nucleotide polymorphisms (nsSNPs) are single base changes leading to a change to the amino acid sequence of the encoded protein. Many of these variants are associated with disease, so nsSNPs have been well studied, with studies looking at the effects of nsSNPs on individual proteins, for example, on stability and enzyme active sites. In recent years, the impact of nsSNPs upon protein-protein interactions has also been investigated, giving a greater insight into the mechanisms by which nsSNPs can lead to disease. In this review, we summarize these studies, looking at the various mechanisms by which nsSNPs can affect protein-protein interactions. We focus on structural changes that can impair interaction, changes to disorder, gain of interaction, and post-translational modifications before looking at some examples of nsSNPs at human-pathogen protein-protein interfaces and the analysis of nsSNPs from a network perspective. © 2013.

  19. Protein-protein interaction site predictions with minimum covariance determinant and Mahalanobis distance.

    PubMed

    Qiu, Zhijun; Zhou, Bo; Yuan, Jiangfeng

    2017-11-21

    Protein-protein interaction site (PPIS) prediction must deal with the diversity of interaction sites that limits their prediction accuracy. Use of proteins with unknown or unidentified interactions can also lead to missing interfaces. Such data errors are often brought into the training dataset. In response to these two problems, we used the minimum covariance determinant (MCD) method to refine the training data to build a predictor with better performance, utilizing its ability of removing outliers. In order to predict test data in practice, a method based on Mahalanobis distance was devised to select proper test data as input for the predictor. With leave-one-validation and independent test, after the Mahalanobis distance screening, our method achieved higher performance according to Matthews correlation coefficient (MCC), although only a part of test data could be predicted. These results indicate that data refinement is an efficient approach to improve protein-protein interaction site prediction. By further optimizing our method, it is hopeful to develop predictors of better performance and wide range of application. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. 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

  1. Huntingtin Interacting Protein 1: a Merkel Cell Carcinoma Marker That Interacts with c-Kit

    PubMed Central

    Ames, Heather M.; Bichakjian, Christopher K.; Liu, Grace Y.; Oravecz-Wilson, Katherine I.; Fullen, Douglas R.; Verhaegen, Monique; Johnson, Timothy M.; Dlugosz, Andrzej A.; Ross, Theodora S.

    2011-01-01

    Merkel Cell Carcinoma (MCC) is a neoplasm thought to originate from the neuroendocrine Merkel cells of the skin. While the prevalence of MCC has been increasing, treatments for this disease remain limited due to a paucity of information regarding MCC biology. We have found that the endocytic oncoprotein Huntingtin interacting protein 1 (HIP1) is expressed at high levels in close to 90% of MCC tumors and serves as a more reliable histological cytoplasmic stain than the gold standard, cytokeratin 20 (CK20). Furthermore, high anti-HIP1 antibody reactivity in the sera of a cohort of MCC patients predicts the presence of metastases. Another protein that is frequently expressed at high levels in MCC tumors is the stem cell factor (SCF) receptor tyrosine kinase, c-Kit. In working towards an understanding of how HIP1 might contribute to MCC tumorigenesis, we have discovered that HIP1 interacts with SCF activated c-Kit. These data not only identify HIP1 as a molecular marker for management of MCC patients but also show that HIP1 interacts with and slows the degradation of c-Kit. PMID:21697888

  2. Growth factor transgenes interactively regulate articular chondrocytes.

    PubMed

    Shi, Shuiliang; Mercer, Scott; Eckert, George J; Trippel, Stephen B

    2013-04-01

    Adult articular chondrocytes lack an effective repair response to correct damage from injury or osteoarthritis. Polypeptide growth factors that stimulate articular chondrocyte proliferation and cartilage matrix synthesis may augment this response. Gene transfer is a promising approach to delivering such factors. Multiple growth factor genes regulate these cell functions, but multiple growth factor gene transfer remains unexplored. We tested the hypothesis that multiple growth factor gene transfer selectively modulates articular chondrocyte proliferation and matrix synthesis. We tested the hypothesis by delivering combinations of the transgenes encoding insulin-like growth factor I (IGF-I), fibroblast growth factor-2 (FGF-2), transforming growth factor beta1 (TGF-β1), bone morphogenetic protein-2 (BMP-2), and bone morphogenetic protien-7 (BMP-7) to articular chondrocytes and measured changes in the production of DNA, glycosaminoglycan, and collagen. The transgenes differentially regulated all these chondrocyte activities. In concert, the transgenes interacted to generate widely divergent responses from the cells. These interactions ranged from inhibitory to synergistic. The transgene pair encoding IGF-I and FGF-2 maximized cell proliferation. The three-transgene group encoding IGF-I, BMP-2, and BMP-7 maximized matrix production and also optimized the balance between cell proliferation and matrix production. These data demonstrate an approach to articular chondrocyte regulation that may be tailored to stimulate specific cell functions, and suggest that certain growth factor gene combinations have potential value for cell-based articular cartilage repair. Copyright © 2012 Wiley Periodicals, Inc.

  3. Structure-Templated Predictions of Novel Protein Interactions from Sequence Information

    PubMed Central

    Betel, Doron; Breitkreuz, Kevin E; Isserlin, Ruth; Dewar-Darch, Danielle; Tyers, Mike; Hogue, Christopher W. V

    2007-01-01

    The multitude of functions performed in the cell are largely controlled by a set of carefully orchestrated protein interactions often facilitated by specific binding of conserved domains in the interacting proteins. Interacting domains commonly exhibit distinct binding specificity to short and conserved recognition peptides called binding profiles. Although many conserved domains are known in nature, only a few have well-characterized binding profiles. Here, we describe a novel predictive method known as domain–motif interactions from structural topology (D-MIST) for elucidating the binding profiles of interacting domains. A set of domains and their corresponding binding profiles were derived from extant protein structures and protein interaction data and then used to predict novel protein interactions in yeast. A number of the predicted interactions were verified experimentally, including new interactions of the mitotic exit network, RNA polymerases, nucleotide metabolism enzymes, and the chaperone complex. These results demonstrate that new protein interactions can be predicted exclusively from sequence information. PMID:17892321

  4. Genome wide approaches to identify protein-DNA interactions.

    PubMed

    Ma, Tao; Ye, Zhenqing; Wang, Liguo

    2018-05-29

    Transcription factors are DNA-binding proteins that play key roles in many fundamental biological processes. Unraveling their interactions with DNA is essential to identify their target genes and understand the regulatory network. Genome-wide identification of their binding sites became feasible thanks to recent progress in experimental and computational approaches. ChIP-chip, ChIP-seq, and ChIP-exo are three widely used techniques to demarcate genome-wide transcription factor binding sites. This review aims to provide an overview of these three techniques including their experiment procedures, computational approaches, and popular analytic tools. ChIP-chip, ChIP-seq, and ChIP-exo have been the major techniques to study genome-wide in vivo protein-DNA interaction. Due to the rapid development of next-generation sequencing technology, array-based ChIP-chip is deprecated and ChIP-seq has become the most widely used technique to identify transcription factor binding sites in genome-wide. The newly developed ChIP-exo further improves the spatial resolution to single nucleotide. Numerous tools have been developed to analyze ChIP-chip, ChIP-seq and ChIP-exo data. However, different programs may employ different mechanisms or underlying algorithms thus each will inherently include its own set of statistical assumption and bias. So choosing the most appropriate analytic program for a given experiment needs careful considerations. Moreover, most programs only have command line interface so their installation and usage will require basic computation expertise in Unix/Linux. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  5. An exploration of alternative visualisations of the basic helix-loop-helix protein interaction network

    PubMed Central

    Holden, Brian J; Pinney, John W; Lovell, Simon C; Amoutzias, Grigoris D; Robertson, David L

    2007-01-01

    Background Alternative representations of biochemical networks emphasise different aspects of the data and contribute to the understanding of complex biological systems. In this study we present a variety of automated methods for visualisation of a protein-protein interaction network, using the basic helix-loop-helix (bHLH) family of transcription factors as an example. Results Network representations that arrange nodes (proteins) according to either continuous or discrete information are investigated, revealing the existence of protein sub-families and the retention of interactions following gene duplication events. Methods of network visualisation in conjunction with a phylogenetic tree are presented, highlighting the evolutionary relationships between proteins, and clarifying the context of network hubs and interaction clusters. Finally, an optimisation technique is used to create a three-dimensional layout of the phylogenetic tree upon which the protein-protein interactions may be projected. Conclusion We show that by incorporating secondary genomic, functional or phylogenetic information into network visualisation, it is possible to move beyond simple layout algorithms based on network topology towards more biologically meaningful representations. These new visualisations can give structure to complex networks and will greatly help in interpreting their evolutionary origins and functional implications. Three open source software packages (InterView, TVi and OptiMage) implementing our methods are available. PMID:17683601

  6. Predicting Human Protein Subcellular Locations by the Ensemble of Multiple Predictors via Protein-Protein Interaction Network with Edge Clustering Coefficients

    PubMed Central

    Du, Pufeng; Wang, Lusheng

    2014-01-01

    One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods. PMID:24466278

  7. A protein interaction map for cell polarity development

    PubMed Central

    Drees, Becky L.; Sundin, Bryan; Brazeau, Elizabeth; Caviston, Juliane P.; Chen, Guang-Chao; Guo, Wei; Kozminski, Keith G.; Lau, Michelle W.; Moskow, John J.; Tong, Amy; Schenkman, Laura R.; McKenzie, Amos; Brennwald, Patrick; Longtine, Mark; Bi, Erfei; Chan, Clarence; Novick, Peter; Boone, Charles; Pringle, John R.; Davis, Trisha N.; Fields, Stanley; Drubin, David G.

    2001-01-01

    Many genes required for cell polarity development in budding yeast have been identified and arranged into a functional hierarchy. Core elements of the hierarchy are widely conserved, underlying cell polarity development in diverse eukaryotes. To enumerate more fully the protein–protein interactions that mediate cell polarity development, and to uncover novel mechanisms that coordinate the numerous events involved, we carried out a large-scale two-hybrid experiment. 68 Gal4 DNA binding domain fusions of yeast proteins associated with the actin cytoskeleton, septins, the secretory apparatus, and Rho-type GTPases were used to screen an array of yeast transformants that express ∼90% of the predicted Saccharomyces cerevisiae open reading frames as Gal4 activation domain fusions. 191 protein–protein interactions were detected, of which 128 had not been described previously. 44 interactions implicated 20 previously uncharacterized proteins in cell polarity development. Further insights into possible roles of 13 of these proteins were revealed by their multiple two-hybrid interactions and by subcellular localization. Included in the interaction network were associations of Cdc42 and Rho1 pathways with proteins involved in exocytosis, septin organization, actin assembly, microtubule organization, autophagy, cytokinesis, and cell wall synthesis. Other interactions suggested direct connections between Rho1- and Cdc42-regulated pathways; the secretory apparatus and regulators of polarity establishment; actin assembly and the morphogenesis checkpoint; and the exocytic and endocytic machinery. In total, a network of interactions that provide an integrated response of signaling proteins, the cytoskeleton, and organelles to the spatial cues that direct polarity development was revealed. PMID:11489916

  8. 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. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  9. 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

  10. Bifunctional fusion proteins of calmodulin and protein A as affinity ligands in protein purification and in the study of protein-protein interactions.

    PubMed

    Hentz, N G; Daunert, S

    1996-11-15

    An affinity chromatography system is described that incorporates a genetically designed bifunctional affinity ligand. The utility of the system in protein purification and in the study of protein-protein interactions is demonstrated by using the interaction between protein A and the heat shock protein DnaK as a model system. The bifunctional affinity ligand was developed by genetically fusing calmodulin (CaM) to protein A (ProtA). The dual functionality of protein A-calmodulin (ProtA-CaM) stems from the molecular recognition properties of the two components of the fusion protein. In particular, CaM serves as the anchoring component by virtue of its binding properties toward phenothiazine. Thus, the ProtA-CaM can be immobilized on a solid support containing phenothiazine from the C-terminal domain of the fusion protein. Protein A is at the N-terminal domain of the fusion protein and serves as the affinity site for DnaK. While DnaK binds specifically to the protein A domain of the bifunctional ligand, it is released upon addition of ATP and under very mild conditions (pH 7.0). In addition to obtaining highly purified DnaK, this system is very rugged in terms of its performance. The proteinaceous bifunctional affinity ligand can be easily removed by addition of EGTA, and fresh ProtA-CaM can be easily reloaded onto the column. This allows for a facile regeneration of the affinity column because the phenothiazine-silica support matrix is stable for long periods of time under a variety of conditions. This study also demonstrates that calmodulin fusions can provide a new approach to study protein-protein interactions. Indeed, the ProtA-CaM fusion protein identified DnaK as a cellular component that interacts with protein A from among the thousands of proteins present in Escherichia coli.

  11. "Features of two proteins of Leptospira interrogans with potential role in host-pathogen interactions"

    PubMed Central

    2012-01-01

    Background Leptospirosis is considered a re-emerging infectious disease caused by pathogenic spirochaetes of the genus Leptospira. Pathogenic leptospires have the ability to survive and disseminate to multiple organs after penetrating the host. Leptospires were shown to express surface proteins that interact with the extracellular matrix (ECM) and to plasminogen (PLG). This study examined the interaction of two putative leptospiral proteins with laminin, collagen Type I, collagen Type IV, cellular fibronectin, plasma fibronectin, PLG, factor H and C4bp. Results We show that two leptospiral proteins encoded by LIC11834 and LIC12253 genes interact with laminin in a dose - dependent and saturable mode, with dissociation equilibrium constants (KD) of 367.5 and 415.4 nM, respectively. These proteins were named Lsa33 and Lsa25 (Leptospiral surface adhesin) for LIC11834 and LIC12253, respectively. Metaperiodate - treated laminin reduced Lsa25 - laminin interaction, suggesting that sugar moieties of this ligand participate in this interaction. The Lsa33 is also PLG - binding receptor, with a KD of 23.53 nM, capable of generating plasmin in the presence of an activator. Although in a weak manner, both proteins interact with C4bp, a regulator of complement classical route. In silico analysis together with proteinase K and immunoflorescence data suggest that these proteins might be surface exposed. Moreover, the recombinant proteins partially inhibited leptospiral adherence to immobilized laminin and PLG. Conclusions We believe that these multifunctional proteins have the potential to participate in the interaction of leptospires to hosts by mediating adhesion and by helping the bacteria to escape the immune system and to overcome tissue barriers. To our knowledge, Lsa33 is the first leptospiral protein described to date with the capability of binding laminin, PLG and C4bp in vitro. PMID:22463075

  12. Kinase Pathway Database: An Integrated Protein-Kinase and NLP-Based Protein-Interaction Resource

    PubMed Central

    Koike, Asako; Kobayashi, Yoshiyuki; Takagi, Toshihisa

    2003-01-01

    Protein kinases play a crucial role in the regulation of cellular functions. Various kinds of information about these molecules are important for understanding signaling pathways and organism characteristics. We have developed the Kinase Pathway Database, an integrated database involving major completely sequenced eukaryotes. It contains the classification of protein kinases and their functional conservation, ortholog tables among species, protein–protein, protein–gene, and protein–compound interaction data, domain information, and structural information. It also provides an automatic pathway graphic image interface. The protein, gene, and compound interactions are automatically extracted from abstracts for all genes and proteins by natural-language processing (NLP).The method of automatic extraction uses phrase patterns and the GENA protein, gene, and compound name dictionary, which was developed by our group. With this database, pathways are easily compared among species using data with more than 47,000 protein interactions and protein kinase ortholog tables. The database is available for querying and browsing at http://kinasedb.ontology.ims.u-tokyo.ac.jp/. PMID:12799355

  13. Protein annotation from protein interaction networks and Gene Ontology.

    PubMed

    Nguyen, Cao D; Gardiner, Katheleen J; Cios, Krzysztof J

    2011-10-01

    We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

  14. 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.

  15. [Identification of C(2)M interacting proteins by yeast two-hybrid screening].

    PubMed

    Yue, Shan-shan; Xia, Lai-xin

    2015-11-01

    The synaptonemal complex (SC) is a huge structure which assembles between the homologous chromosomes during meiotic prophase I. Drosophila germ cell-specific nucleoprotein C(2)M clustering at chromosomes can induce SC formation. To further study the molecular function and mechanism of C(2)M in meiosis, we constructed a bait vector for C(2)M and used the yeast two-hybrid system to identify C(2)M interacting proteins. Forty interacting proteins were obtained, including many DNA and histone binding proteins, ATP synthases and transcription factors. Gene silencing assays in Drosophila showed that two genes, wech and Psf1, may delay the disappearance of SC. These results indicate that Wech and Psf1 may form a complex with C(2)M to participate in the formation or stabilization of the SC complex.

  16. 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

  17. Plasma membrane lipid–protein interactions affect signaling processes in sterol-biosynthesis mutants in Arabidopsis thaliana

    PubMed Central

    Zauber, Henrik; Burgos, Asdrubal; Garapati, Prashanth; Schulze, Waltraud X.

    2014-01-01

    The plasma membrane is an important organelle providing structure, signaling and transport as major biological functions. Being composed of lipids and proteins with different physicochemical properties, the biological functions of membranes depend on specific protein–protein and protein–lipid interactions. Interactions of proteins with their specific sterol and lipid environment were shown to be important factors for protein recruitment into sub-compartmental structures of the plasma membrane. System-wide implications of altered endogenous sterol levels for membrane functions in living cells were not studied in higher plant cells. In particular, little is known how alterations in membrane sterol composition affect protein and lipid organization and interaction within membranes. Here, we conducted a comparative analysis of the plasma membrane protein and lipid composition in Arabidopsis sterol-biosynthesis mutants smt1 and ugt80A2;B1. smt1 shows general alterations in sterol composition while ugt80A2;B1 is significantly impaired in sterol glycosylation. By systematically analyzing different cellular fractions and combining proteomic with lipidomic data we were able to reveal contrasting alterations in lipid–protein interactions in both mutants, with resulting differential changes in plasma membrane signaling status. PMID:24672530

  18. Factor VII and protein C are phosphatidic acid-binding proteins.

    PubMed

    Tavoosi, Narjes; Smith, Stephanie A; Davis-Harrison, Rebecca L; Morrissey, James H

    2013-08-20

    Seven proteins in the human blood clotting cascade bind, via their GLA (γ-carboxyglutamate-rich) domains, to membranes containing exposed phosphatidylserine (PS), although with membrane binding affinities that vary by 3 orders of magnitude. Here we employed nanodiscs of defined phospholipid composition to quantify the phospholipid binding specificities of these seven clotting proteins. All bound preferentially to nanobilayers in which PS headgroups contained l-serine versus d-serine. Surprisingly, however, nanobilayers containing phosphatidic acid (PA) bound substantially more of two of these proteins, factor VIIa and activated protein C, than did equivalent bilayers containing PS. Consistent with this finding, liposomes containing PA supported higher proteolytic activity by factor VIIa and activated protein C toward their natural substrates (factors X and Va, respectively) than did PS-containing liposomes. Moreover, treating activated human platelets with phospholipase D enhanced the rates of factor X activation by factor VIIa in the presence of soluble tissue factor. We hypothesize that factor VII and protein C bind preferentially to the monoester phosphate of PA because of its accessibility and higher negative charge compared with the diester phosphates of most other phospholipids. We further found that phosphatidylinositol 4-phosphate, which contains a monoester phosphate attached to its myo-inositol headgroup, also supported enhanced enzymatic activity of factor VIIa and activated protein C. We conclude that factor VII and protein C bind preferentially to monoester phosphates, which may have implications for the function of these proteases in vivo.

  19. 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…

  20. Proteome-wide Prediction of Self-interacting Proteins Based on Multiple Properties*

    PubMed Central

    Liu, Zhongyang; Guo, Feifei; Zhang, Jiyang; Wang, Jian; Lu, Liang; Li, Dong; He, Fuchu

    2013-01-01

    Self-interacting proteins, whose two or more copies can interact with each other, play important roles in cellular functions and the evolution of protein interaction networks (PINs). Knowing whether a protein can self-interact can contribute to and sometimes is crucial for the elucidation of its functions. Previous related research has mainly focused on the structures and functions of specific self-interacting proteins, whereas knowledge on their overall properties is limited. Meanwhile, the two current most common high throughput protein interaction assays have limited ability to detect self-interactions because of biological artifacts and design limitations, whereas the bioinformatic prediction method of self-interacting proteins is lacking. This study aims to systematically study and predict self-interacting proteins from an overall perspective. We find that compared with other proteins the self-interacting proteins in the structural aspect contain more domains; in the evolutionary aspect they tend to be conserved and ancient; in the functional aspect they are significantly enriched with enzyme genes, housekeeping genes, and drug targets, and in the topological aspect tend to occupy important positions in PINs. Furthermore, based on these features, after feature selection, we use logistic regression to integrate six representative features, including Gene Ontology term, domain, paralogous interactor, enzyme, model organism self-interacting protein, and betweenness centrality in the PIN, to develop a proteome-wide prediction model of self-interacting proteins. Using 5-fold cross-validation and an independent test, this model shows good performance. Finally, the prediction model is developed into a user-friendly web service SLIPPER (SeLf-Interacting Protein PrEdictoR). Users may submit a list of proteins, and then SLIPPER will return the probability_scores measuring their possibility to be self-interacting proteins and various related annotation information. This

  1. Protein profile and protein interaction network of Moniliophthora perniciosa basidiospores.

    PubMed

    Mares, Joise Hander; Gramacho, Karina Peres; Dos Santos, Everton Cruz; Santiago, André da Silva; Silva, Edson Mário de Andrade; Alvim, Fátima Cerqueira; Pirovani, Carlos Priminho

    2016-06-24

    Witches' broom, a disease caused by the basidiomycete Moniliophthora perniciosa, is considered to be the most important disease of the cocoa crop in Bahia, an area in the Brazilian Amazon, and also in the other countries where it is found. M. perniciosa germ tubes may penetrate into the host through intact or natural openings in the cuticle surface, in epidermis cell junctions, at the base of trichomes, or through the stomata. Despite its relevance to the fungal life cycle, basidiospore biology has not been extensively investigated. In this study, our goal was to optimize techniques for producing basidiospores for protein extraction, and to produce the first proteomics analysis map of ungerminated basidiospores. We then presented a protein interaction network by using Ustilago maydis as a model. The average pileus area ranged from 17.35 to 211.24 mm(2). The minimum and maximum productivity were 23,200 and 6,666,667 basidiospores per basidiome, respectively. The protein yield in micrograms per million basidiospores were approximately 0.161; 2.307, and 3.582 for germination times of 0, 2, and 4 h after germination, respectively. A total of 178 proteins were identified through mass spectrometry. These proteins were classified according to their molecular function and their involvement in biological processes such as cellular energy production, oxidative metabolism, stress, protein synthesis, and protein folding. Furthermore, to better understand the expression pattern, signaling, and interaction events of spore proteins, we presented an interaction network using orthologous proteins from Ustilago maydis as a model. Most of the orthologous proteins that were identified in this study were not clustered in the network, but several of them play a very important role in hypha development and branching. The quantities of basidiospores 7 × 10(9); 5.2 × 10(8), and 6.7 × 10(8) were sufficient to obtain enough protein mass for the three 2D-PAGE replicates, for

  2. The calcium-sensing receptor and its interacting proteins

    PubMed Central

    Huang, Chunfa; Miller, R Tyler

    2007-01-01

    Abstract Seven membrane-spanning, or G protein-coupled receptors were originally thought to act through het-erotrimeric G proteins that in turn activate intracellular enzymes or ion channels, creating relatively simple, linear signalling pathways. Although this basic model remains true in that this family does act via a relatively small number of G proteins, these signalling systems are considerably more complex because the receptors interact with or are located near additional proteins that are often unique to a receptor or subset of receptors. These additional proteins give receptors their unique signalling ‘personalities’. The extracellular Ca-sensing receptor (CaR) signals via Gαi, Gαq and Gα12/13, but its effects in vivo demonstrate that the signalling pathways controlled by these subunits are not sufficient to explain all its biologic effects. Additional structural or signalling proteins that interact with the CaR may explain its behaviour more fully. Although the CaR is less well studied in this respect than other receptors, several CaR-interacting proteins such as filamin, a potential scaffolding protein, receptor activity modifying proteins (RAMPs) and potassium channels may contribute to the unique characteristics of the CaR. The CaR also appears to interact with additional proteins common to other G protein-coupled receptors such as arrestins, G protein receptor kinases, protein kinase C, caveolin and proteins in the ubiquitination pathway. These proteins probably represent a few initial members of CaR-based signalling complex. These and other proteins may not all be associated with the CaR in all tissues, but they form the basis for understanding the complete nature of CaR signalling. PMID:17979874

  3. Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations.

    PubMed

    Suratanee, Apichat; Plaimas, Kitiporn

    2017-01-01

    The associations between proteins and diseases are crucial information for investigating pathological mechanisms. However, the number of known and reliable protein-disease associations is quite small. In this study, an analysis framework to infer associations between proteins and diseases was developed based on a large data set of a human protein-protein interaction network integrating an effective network search, namely, the reverse k -nearest neighbor (R k NN) search. The R k NN search was used to identify an impact of a protein on other proteins. Then, associations between proteins and diseases were inferred statistically. The method using the R k NN search yielded a much higher precision than a random selection, standard nearest neighbor search, or when applying the method to a random protein-protein interaction network. All protein-disease pair candidates were verified by a literature search. Supporting evidence for 596 pairs was identified. In addition, cluster analysis of these candidates revealed 10 promising groups of diseases to be further investigated experimentally. This method can be used to identify novel associations to better understand complex relationships between proteins and diseases.

  4. Using neighborhood cohesiveness to infer interactions between protein domains.

    PubMed

    Segura, Joan; Sorzano, C O S; Cuenca-Alba, Jesus; Aloy, Patrick; Carazo, J M

    2015-08-01

    In recent years, large-scale studies have been undertaken to describe, at least partially, protein-protein interaction maps, or interactomes, for a number of relevant organisms, including human. However, current interactomes provide a somehow limited picture of the molecular details involving protein interactions, mostly because essential experimental information, especially structural data, is lacking. Indeed, the gap between structural and interactomics information is enlarging and thus, for most interactions, key experimental information is missing. We elaborate on the observation that many interactions between proteins involve a pair of their constituent domains and, thus, the knowledge of how protein domains interact adds very significant information to any interactomic analysis. In this work, we describe a novel use of the neighborhood cohesiveness property to infer interactions between protein domains given a protein interaction network. We have shown that some clustering coefficients can be extended to measure a degree of cohesiveness between two sets of nodes within a network. Specifically, we used the meet/min coefficient to measure the proportion of interacting nodes between two sets of nodes and the fraction of common neighbors. This approach extends previous works where homolog coefficients were first defined around network nodes and later around edges. The proposed approach substantially increases both the number of predicted domain-domain interactions as well as its accuracy as compared with current methods. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  5. Energy Landscape of All-Atom Protein-Protein Interactions Revealed by Multiscale Enhanced Sampling

    PubMed Central

    Moritsugu, Kei; Terada, Tohru; Kidera, Akinori

    2014-01-01

    Protein-protein interactions are regulated by a subtle balance of complicated atomic interactions and solvation at the interface. To understand such an elusive phenomenon, it is necessary to thoroughly survey the large configurational space from the stable complex structure to the dissociated states using the all-atom model in explicit solvent and to delineate the energy landscape of protein-protein interactions. In this study, we carried out a multiscale enhanced sampling (MSES) simulation of the formation of a barnase-barstar complex, which is a protein complex characterized by an extraordinary tight and fast binding, to determine the energy landscape of atomistic protein-protein interactions. The MSES adopts a multicopy and multiscale scheme to enable for the enhanced sampling of the all-atom model of large proteins including explicit solvent. During the 100-ns MSES simulation of the barnase-barstar system, we observed the association-dissociation processes of the atomistic protein complex in solution several times, which contained not only the native complex structure but also fully non-native configurations. The sampled distributions suggest that a large variety of non-native states went downhill to the stable complex structure, like a fast folding on a funnel-like potential. This funnel landscape is attributed to dominant configurations in the early stage of the association process characterized by near-native orientations, which will accelerate the native inter-molecular interactions. These configurations are guided mostly by the shape complementarity between barnase and barstar, and lead to the fast formation of the final complex structure along the downhill energy landscape. PMID:25340714

  6. 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.

  7. Protein–protein interactions and selection: yeast-based approaches that exploit guanine nucleotide-binding protein signaling.

    PubMed

    Ishii, Jun; Fukuda, Nobuo; Tanaka, Tsutomu; Ogino, Chiaki; Kondo, Akihiko

    2010-05-01

    For elucidating protein–protein interactions, many methodologies have been developed during the past two decades. For investigation of interactions inside cells under physiological conditions, yeast is an attractive organism with which to quickly screen for hopeful candidates using versatile genetic technologies, and various types of approaches are now available.Among them, a variety of unique systems using the guanine nucleotide-binding protein (G-protein) signaling pathway in yeast have been established to investigate the interactions of proteins for biological study and pharmaceutical research. G-proteins involved in various cellular processes are mainly divided into two groups: small monomeric G-proteins,and heterotrimeric G-proteins. In this minireview, we summarize the basic principles and applications of yeast-based screening systems, using these two types of G-protein, which are typically used for elucidating biological protein interactions but are differentiated from traditional yeast two-hybrid systems.

  8. Local Geometry and Evolutionary Conservation of Protein Surfaces Reveal the Multiple Recognition Patches in Protein-Protein Interactions

    PubMed Central

    Laine, Elodie; Carbone, Alessandra

    2015-01-01

    Protein-protein interactions (PPIs) are essential to all biological processes and they represent increasingly important therapeutic targets. Here, we present a new method for accurately predicting protein-protein interfaces, understanding their properties, origins and binding to multiple partners. Contrary to machine learning approaches, our method combines in a rational and very straightforward way three sequence- and structure-based descriptors of protein residues: evolutionary conservation, physico-chemical properties and local geometry. The implemented strategy yields very precise predictions for a wide range of protein-protein interfaces and discriminates them from small-molecule binding sites. Beyond its predictive power, the approach permits to dissect interaction surfaces and unravel their complexity. We show how the analysis of the predicted patches can foster new strategies for PPIs modulation and interaction surface redesign. The approach is implemented in JET2, an automated tool based on the Joint Evolutionary Trees (JET) method for sequence-based protein interface prediction. JET2 is freely available at www.lcqb.upmc.fr/JET2. PMID:26690684

  9. A lanthipeptide library used to identify a protein-protein interaction inhibitor.

    PubMed

    Yang, Xiao; Lennard, Katherine R; He, Chang; Walker, Mark C; Ball, Andrew T; Doigneaux, Cyrielle; Tavassoli, Ali; van der Donk, Wilfred A

    2018-04-01

    In this article we describe the production and screening of a genetically encoded library of 10 6 lanthipeptides in Escherichia coli using the substrate-tolerant lanthipeptide synthetase ProcM. This plasmid-encoded library was combined with a bacterial reverse two-hybrid system for the interaction of the HIV p6 protein with the UEV domain of the human TSG101 protein, which is a critical protein-protein interaction for HIV budding from infected cells. Using this approach, we identified an inhibitor of this interaction from the lanthipeptide library, whose activity was verified in vitro and in cell-based virus-like particle-budding assays. Given the variety of lanthipeptide backbone scaffolds that may be produced with ProcM, this method may be used for the generation of genetically encoded libraries of natural product-like lanthipeptides containing substantial structural diversity. Such libraries may be combined with any cell-based assay to identify lanthipeptides with new biological activities.

  10. Herpes simplex virus 1 regulatory protein ICP22 interacts with a new cell cycle-regulated factor and accumulates in a cell cycle-dependent fashion in infected cells.

    PubMed

    Bruni, R; Roizman, B

    1998-11-01

    The herpes simplex virus 1 infected cell protein 22 (ICP22), the product of the alpha22 gene, is a nucleotidylylated and phosphorylated nuclear protein with properties of a transcriptional factor required for the expression of a subset of viral genes. Here, we report the following. (i) ICP22 interacts with a previously unknown cellular factor designated p78 in the yeast two-hybrid system. The p78 cDNA encodes a polypeptide with a distribution of leucines reminiscent of a leucine zipper. (ii) In uninfected and infected cells, antibody to p78 reacts with two major bands with an apparent Mr of 78,000 and two minor bands with apparent Mrs of 62, 000 and 55,000. (ii) p78 also interacts with ICP22 in vitro. (iii) In uninfected cells, p78 was dispersed largely in the nucleoplasm in HeLa cells and in the nucleoplasm and cytoplasm in HEp-2 cells. After infection, p78 formed large dense bodies which did not colocalize with the viral regulatory protein ICP0. (iv) Accumulation of p78 was cell cycle dependent, being highest very early in S phase. (v) The accumulation of ICP22 in synchronized cells was highest in early S phase, in contrast to the accumulation of another protein, ICP27, which was relatively independent of the cell cycle. (vi) In the course of the cell cycle, ICP22 was transiently modified in an aberrant fashion, and this modification coincided with expression of p78. The results suggest that ICP22 interacts with and may be stabilized by cell cycle-dependent proteins.

  11. Feature generation and representations for protein-protein interaction classification.

    PubMed

    Lan, Man; Tan, Chew Lim; Su, Jian

    2009-10-01

    Automatic detecting protein-protein interaction (PPI) relevant articles is a crucial step for large-scale biological database curation. The previous work adopted POS tagging, shallow parsing and sentence splitting techniques, but they achieved worse performance than the simple bag-of-words representation. In this paper, we generated and investigated multiple types of feature representations in order to further improve the performance of PPI text classification task. Besides the traditional domain-independent bag-of-words approach and the term weighting methods, we also explored other domain-dependent features, i.e. protein-protein interaction trigger keywords, protein named entities and the advanced ways of incorporating Natural Language Processing (NLP) output. The integration of these multiple features has been evaluated on the BioCreAtIvE II corpus. The experimental results showed that both the advanced way of using NLP output and the integration of bag-of-words and NLP output improved the performance of text classification. Specifically, in comparison with the best performance achieved in the BioCreAtIvE II IAS, the feature-level and classifier-level integration of multiple features improved the performance of classification 2.71% and 3.95%, respectively.

  12. BRCA1 interacts directly with the Fanconi anemia protein FANCA.

    PubMed

    Folias, Alexandra; Matkovic, Mara; Bruun, Donald; Reid, Sonja; Hejna, James; Grompe, Markus; D'Andrea, Alan; Moses, Robb

    2002-10-01

    Fanconi anemia (FA) is a rare autosomal recessive disease characterized by skeletal defects, anemia, chromosomal instability and increased risk of leukemia. At the cellular level FA is characterized by increased sensitivity to agents forming interstrand crosslinks (ICL) in DNA. Six FA genes have been cloned and interactions among individual FANC proteins have been found. The FANCD2 protein co-localizes in nuclear foci with the BRCA1 protein following DNA damage and during S-phase, requiring the FANCA, C, E and G proteins to do so. This finding may reflect a direct role for the BRCA1 protein in double strand break (DSB) repair and interaction with the FANC proteins. Therefore interactions between BRCA1 and the FANC proteins were investigated. Among the known FANC proteins, we find evidence for direct interaction only between the FANCA protein and BRCA1. The evidence rests on three different tests: yeast two-hybrid analysis, coimmunoprecipitation from in vitro synthesis, and coimmunoprecipitation from cell extracts. The amino terminal portion of FANCA and the central part (aa 740-1083) of BRCA1 contain the sites of interaction. The interaction does not depend on DNA damage, thus FANCA and BRCA1 are constitutively interacting. The demonstrated interaction directly connects BRCA1 to the FA pathway of DNA repair.

  13. MdHIR proteins repress anthocyanin accumulation by interacting with the MdJAZ2 protein to inhibit its degradation in apples

    PubMed Central

    Chen, Ke-Qin; Zhao, Xian-Yan; An, Xiu-Hong; Tian, Yi; Liu, Dan-Dan; You, Chun-Xiang; Hao, Yu-Jin

    2017-01-01

    In higher plants, jasmonate ZIM-domain (JAZ) proteins negatively regulate the biosynthesis of anthocyanins by interacting with bHLH transcription factors. However, it is largely unknown if and how other regulators are involved in this process. In this study, the apple MdJAZ2 protein was characterized in regards to its function in the negative regulation of anthocyanin accumulation and peel coloration. MdJAZ2 was used as a bait to screen a cDNA library using the yeast two-hybrid method. The hypersensitive induced reaction (HIR) proteins, MdHIR2 and MdHIR4, were obtained from this yeast two-hybrid. The ZIM domain of MdJAZ2 and the PHB domain of the MdHIR proteins are necessary for their interactions. The interactions were further verified using an in vitro pull-down assay. Subsequently, immunoblotting assays demonstrated that MdHIR4 enhanced the stability of the MdJAZ2-GUS protein. Finally, a viral vector-based transformation method showed that MdHIR4 inhibited anthocyanin accumulation and fruit coloration in apple by modulating the expression of genes associated with anthocyanin biosynthesis. PMID:28317851

  14. Nanoparticle-Protein Interaction: The Significance and Role of Protein Corona.

    PubMed

    Ahsan, Saad Mohammad; Rao, Chintalagiri Mohan; Ahmad, Md Faiz

    2018-01-01

    The physico-chemical properties of nanoparticles, as characterized under idealized laboratory conditions, have been suggested to differ significantly when studied under complex physiological environments. A major reason for this variation has been the adsorption of biomolecules (mainly proteins) on the nanoparticle surface, constituting the so-called "biomolecular corona". The formation of biomolecular corona on the nanoparticle surface has been reported to influence various nanoparticle properties viz. cellular targeting, cellular interaction, in vivo clearance, toxicity, etc. Understanding the interaction of nanoparticles with proteins upon administration in vivo thus becomes important for the development of effective nanotechnology-based platforms for biomedical applications. In this chapter, we describe the formation of protein corona on nanoparticles and the differences arising in its composition due to variations in nanoparticle properties. Also discussed is the influence of protein corona on various nanoparticle activities.

  15. Pin1 down-regulates transforming growth factor-beta (TGF-beta) signaling by inducing degradation of Smad proteins.

    PubMed

    Nakano, Ayako; Koinuma, Daizo; Miyazawa, Keiji; Uchida, Takafumi; Saitoh, Masao; Kawabata, Masahiro; Hanai, Jun-ichi; Akiyama, Hirotada; Abe, Masahiro; Miyazono, Kohei; Matsumoto, Toshio; Imamura, Takeshi

    2009-03-06

    Transforming growth factor-beta (TGF-beta) is crucial in numerous cellular processes, such as proliferation, differentiation, migration, and apoptosis. TGF-beta signaling is transduced by intracellular Smad proteins that are regulated by the ubiquitin-proteasome system. Smad ubiquitin regulatory factor 2 (Smurf2) prevents TGF-beta and bone morphogenetic protein signaling by interacting with Smads and inducing their ubiquitin-mediated degradation. Here we identified Pin1, a peptidylprolyl cis-trans isomerase, as a novel protein binding Smads. Pin1 interacted with Smad2 and Smad3 but not Smad4; this interaction was enhanced by the phosphorylation of (S/T)P motifs in the Smad linker region. (S/T)P motif phosphorylation also enhanced the interaction of Smad2/3 with Smurf2. Pin1 reduced Smad2/3 protein levels in a manner dependent on its peptidyl-prolyl cis-trans isomerase activity. Knockdown of Pin1 increased the protein levels of endogenous Smad2/3. In addition, Pin1 both enhanced the interaction of Smurf2 with Smads and enhanced Smad ubiquitination. Pin1 inhibited TGF-beta-induced transcription and gene expression, suggesting that Pin1 negatively regulates TGF-beta signaling by down-regulating Smad2/3 protein levels via induction of Smurf2-mediated ubiquitin-proteasomal degradation.

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

    PubMed Central

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

    2016-01-01

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

  17. Filtering Gene Ontology semantic similarity for identifying protein complexes in large protein interaction networks.

    PubMed

    Wang, Jian; Xie, Dong; Lin, Hongfei; Yang, Zhihao; Zhang, Yijia

    2012-06-21

    Many biological processes recognize in particular the importance of protein complexes, and various computational approaches have been developed to identify complexes from protein-protein interaction (PPI) networks. However, high false-positive rate of PPIs leads to challenging identification. A protein semantic similarity measure is proposed in this study, based on the ontology structure of Gene Ontology (GO) terms and GO annotations to estimate the reliability of interactions in PPI networks. Interaction pairs with low GO semantic similarity are removed from the network as unreliable interactions. Then, a cluster-expanding algorithm is used to detect complexes with core-attachment structure on filtered network. Our method is applied to three different yeast PPI networks. The effectiveness of our method is examined on two benchmark complex datasets. Experimental results show that our method performed better than other state-of-the-art approaches in most evaluation metrics. The method detects protein complexes from large scale PPI networks by filtering GO semantic similarity. Removing interactions with low GO similarity significantly improves the performance of complex identification. The expanding strategy is also effective to identify attachment proteins of complexes.

  18. Hydrophobic interactions of sucralose with protein structures.

    PubMed

    Shukla, Nimesh; Pomarico, Enrico; Hecht, Cody J S; Taylor, Erika A; Chergui, Majed; Othon, Christina M

    2018-02-01

    Sucralose is a commonly employed artificial sweetener that appears to destabilize protein native structures. This is in direct contrast to the bio-preservative nature of its natural counterpart, sucrose, which enhances the stability of biomolecules against environmental stress. We have further explored the molecular interactions of sucralose as compared to sucrose to illuminate the origin of the differences in their bio-preservative efficacy. We show that the mode of interactions of sucralose and sucrose in bulk solution differ subtly through the use of hydration dynamics measurement and computational simulation. Sucralose does not appear to disturb the native state of proteins for moderate concentrations (<0.2 M) at room temperature. However, as the concentration increases, or in the thermally stressed state, sucralose appears to differ in its interactions with protein leading to the reduction of native state stability. This difference in interaction appears weak. We explored the difference in the preferential exclusion model using time-resolved spectroscopic techniques and observed that both molecules appear to be effective reducers of bulk hydration dynamics. However, the chlorination of sucralose appears to slightly enhance the hydrophobicity of the molecule, which reduces the preferential exclusion of sucralose from the protein-water interface. The weak interaction of sucralose with hydrophobic pockets on the protein surface differs from the behavior of sucrose. We experimentally followed up upon the extent of this weak interaction using isothermal titration calorimetry (ITC) measurements. We propose this as a possible origin for the difference in their bio-preservative properties. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Self diffusion of interacting membrane proteins.

    PubMed Central

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

    1989-01-01

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

  20. Interaction between mating-type proteins from the homothallic fungus Sordaria macrospora.

    PubMed

    Jacobsen, Sabine; Wittig, Michael; Pöggeler, Stefanie

    2002-06-01

    Mating-type genes control sexual development in ascomycetes. Little is known about their function in homothallic species, which are self-fertile and do not require a mating partner for sexual reproduction. The function of mating-type genes in the homothallic fungus Sordaria macrospora was assayed using a yeast system in order to find properties typical of eukaryotic transcription factors. We were able to demonstrate that the mating-type proteins SMTA-1 and SMTa-1 have domains capable of activating transcription of yeast reporter genes. Two-hybrid analysis for heterodimerization and homodimerization revealed the ability of SMTA-1 to interact with SMTa-1 and vice versa. These two proteins are encoded by different mating types in the related heterothallic species Neurospora crassa. The interaction between SMTA-1 and SMTa-1 was defined by experiments with truncated versions of SMTA-1 and in vitro by means of protein cross-linking. Moreover, we gained evidence for homodimerization of SMTA-1. Possible functions of mating-type proteins in the homothallic ascomycete S. macrospora are discussed.

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

    PubMed

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

    2017-04-01

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

  2. [Design of new anti-tumor agents interrupting deregulated signaling pathways induced by tyrosine kinase proteins. Inhibition of protein-protein interaction involving Grb2].

    PubMed

    Vidal, Michel; Liu, Wang Qing; Gril, Brunile; Assayag, Franck; Poupon, Marie-France; Garbay, Christiane

    2004-01-01

    Cellular signaling pathways induced by growth-factor receptors are frequently deregulated in cancer. Anti-tumor agents that inhibit their enzymatic tyrosine kinase activity have been designed and are now used in human chemotherapy. We propose here an alternative way to interrupt over-expressed signaling by inhibiting protein-protein interactions that involve either the over-expressed proteins or proteins located downstream. The adaptor protein Grb2 over-expressed in connection with HER2/ErbB2/neu in Ras signaling pathway was chosen as a target. Peptides with very high affinity for Grb2 were rationally designed from structural data. Their capacity to interrupt the signaling pathway, their anti-proliferative activity as well as their potential anti-tumor properties are described.

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

    PubMed

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

    2016-11-01

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

  4. Anomalous Protein-Protein Interactions in Multivalent Salt Solution.

    PubMed

    Pasquier, Coralie; Vazdar, Mario; Forsman, Jan; Jungwirth, Pavel; Lund, Mikael

    2017-04-13

    The stability of aqueous protein solutions is strongly affected by multivalent ions, which induce ion-ion correlations beyond the scope of classical mean-field theory. Using all-atom molecular dynamics (MD) and coarse grained Monte Carlo (MC) simulations, we investigate the interaction between a pair of protein molecules in 3:1 electrolyte solution. In agreement with available experimental findings of "reentrant protein condensation", we observe an anomalous trend in the protein-protein potential of mean force with increasing electrolyte concentration in the order: (i) double-layer repulsion, (ii) ion-ion correlation attraction, (iii) overcharge repulsion, and in excess of 1:1 salt, (iv) non Coulombic attraction. To efficiently sample configurational space we explore hybrid continuum solvent models, applicable to many-protein systems, where weakly coupled ions are treated implicitly, while strongly coupled ones are treated explicitly. Good agreement is found with the primitive model of electrolytes, as well as with atomic models of protein and solvent.

  5. Computational Methods to Predict Protein Interaction Partners

    NASA Astrophysics Data System (ADS)

    Valencia, Alfonso; Pazos, Florencio

    In the new paradigm for studying biological phenomena represented by Systems Biology, cellular components are not considered in isolation but as forming complex networks of relationships. Protein interaction networks are among the first objects studied from this new point of view. Deciphering the interactome (the whole network of interactions for a given proteome) has been shown to be a very complex task. Computational techniques for detecting protein interactions have become standard tools for dealing with this problem, helping and complementing their experimental counterparts. Most of these techniques use genomic or sequence features intuitively related with protein interactions and are based on "first principles" in the sense that they do not involve training with examples. There are also other computational techniques that use other sources of information (i.e. structural information or even experimental data) or are based on training with examples.

  6. Dynamic imaging of interaction between protein 14-3-3 and Bid in living cells

    NASA Astrophysics Data System (ADS)

    Chen, Tongsheng; Xing, Da; Wang, Jinjun

    2006-02-01

    The 14-3-3 proteins are known to sequester certain pro-apoptotic members of this family. BH3- interacting domain death agonist (Bid) may contribute to tumor necrosis factor α(TNF-α)-induced neuronal death, although regulation by 14-3-3 has not been reported. In this study we examined whether 14-3-3 proteins interact with Bid/tBid during TNF-α-induced cell death. The TNF-αtriggered Bid cleavage and tBid translocated to mitochondria. Human lung adenocarcinoma cells were co-transfected with both CFP-Bid and 14-3-3-YFP plasmids, and the dynamical interaction between the Bid/tBid and 14-3-3 were performed on laser confocal fluorescence microscope in single living cell during TNF-α-induced cell apoptosis. The Bid distribute equally only in the cytoplasm of healthy cells, and the 14-3-3 protein distribute not only in the cytoplasm but also in the nucleus of healthy cells. Our data showed that the tBid aggregate, but the 14-3-3 protein does not aggregate as the tBid, and the 14-3-3 protein separate from the aggregated tBid, implying that the 14-3-3 proteins do not interact with the aggregated tBid after TNF-αtreatment.

  7. Improving compound-protein interaction prediction by building up highly credible negative samples.

    PubMed

    Liu, Hui; Sun, Jianjiang; Guan, Jihong; Zheng, Jie; Zhou, Shuigeng

    2015-06-15

    Computational prediction of compound-protein interactions (CPIs) is of great importance for drug design and development, as genome-scale experimental validation of CPIs is not only time-consuming but also prohibitively expensive. With the availability of an increasing number of validated interactions, the performance of computational prediction approaches is severely impended by the lack of reliable negative CPI samples. A systematic method of screening reliable negative sample becomes critical to improving the performance of in silico prediction methods. This article aims at building up a set of highly credible negative samples of CPIs via an in silico screening method. As most existing computational models assume that similar compounds are likely to interact with similar target proteins and achieve remarkable performance, it is rational to identify potential negative samples based on the converse negative proposition that the proteins dissimilar to every known/predicted target of a compound are not much likely to be targeted by the compound and vice versa. We integrated various resources, including chemical structures, chemical expression profiles and side effects of compounds, amino acid sequences, protein-protein interaction network and functional annotations of proteins, into a systematic screening framework. We first tested the screened negative samples on six classical classifiers, and all these classifiers achieved remarkably higher performance on our negative samples than on randomly generated negative samples for both human and Caenorhabditis elegans. We then verified the negative samples on three existing prediction models, including bipartite local model, Gaussian kernel profile and Bayesian matrix factorization, and found that the performances of these models are also significantly improved on the screened negative samples. Moreover, we validated the screened negative samples on a drug bioactivity dataset. Finally, we derived two sets of new

  8. Coarse-Grained Model for Colloidal Protein Interactions, B22, and Protein Cluster Formation

    PubMed Central

    Blanco, Marco A.; Sahin, Eric; Robinson, Anne S.; Roberts, Christopher J.

    2014-01-01

    Reversible protein cluster formation is an important initial step in the processes of native and non-native protein aggregation, but involves relatively long time and length scales for detailed atomistic simulations and extensive mapping of free energy landscapes. A coarse-grained (CG) model is presented to semi-quantitatively characterize the thermodynamics and key configurations involved in the landscape for protein oligomerization, as well as experimental measures of interactions such as the osmotic second virial coefficient (B22). Based on earlier work, this CG model treats proteins as rigid bodies composed of one bead per amino acid, with each amino acid having specific parameters for its size, hydrophobicity, and charge. The net interactions are a combination of steric repulsions, short-range attractions, and screened long-range charge-charge interactions. Model parametrization was done by fitting simulation results against experimental values of the B22 as a function of solution ionic strength for α-chymotrypsinogen A and γD-crystallin (gD-Crys). The CG model is applied to characterize the pairwise interactions and dimerization of gD-Crys and the dependance on temperature, protein concentration, and ionic strength. The results illustrate that at experimentally relevant conditions where stable dimers do not form, the entropic contributions are predominant in the free-energy of protein cluster formation and colloidal protein interactions, arguing against interpretations that treat B22 primarily from energetic considerations alone. Additionally, the results suggest that electrostatic interactions help to modulate the population of the different stable configurations for protein nearest-neighbor pairs, while short-range attractions determine the relative orientations of proteins within these configurations. Finally, simulation results are combined with Principal Component Analysis to identify those amino-acids / surface patches that form inter-protein contacts

  9. Phosphorylation of human tristetraprolin in response to its interaction with the Cbl interacting protein CIN85.

    PubMed

    Kedar, Vishram P; Darby, Martyn K; Williams, Jason G; Blackshear, Perry J

    2010-03-08

    Tristetraprolin (TTP) is the prototype member of a family of CCCH tandem zinc finger proteins and is considered to be an anti-inflammatory protein in mammals. TTP plays a critical role in the decay of tumor necrosis factor alpha (TNF) mRNA, among others, by binding AU-rich RNA elements in the 3'-untranslated regions of this transcript and promoting its deadenylation and degradation. We used yeast two-hybrid analysis to identify potential protein binding partners for human TTP (hTTP). Various regions of hTTP recovered 31 proteins that fell into 12 categories based on sequence similarities. Among these, the interactions between hTTP and CIN85, cytoplasmic poly (A) binding protein (PABP), nucleolin and heat shock protein 70 were confirmed by co-immunoprecipitation experiments. CIN85 and hTTP co-localized in the cytoplasm of cells as determined by confocal microscopy. CIN85 contains three SH3 domains that specifically bind a unique proline-arginine motif (PXXXPR) found in several CIN85 effectors. We found that the SH3 domains of CIN85 bound to a PXXXPR motif located near the C-terminus of hTTP. Co-expression of CIN85 with hTTP resulted in the increased phosphorylation of hTTP at serine residues in positions 66 and 93, possibly due in part to the demonstrated association of mitogen-activated protein kinase kinase kinase 4 (MEKK4) to both proteins. The presence of CIN85 did not appear to alter hTTP's binding to RNA probes or its stimulated breakdown of TNF mRNA. These studies describe interactions between hTTP and nucleolin, cytoplasmic PABP, heat shock protein 70 and CIN85; these interactions were initially discovered by two-hybrid analysis, and confirmed by co-immunoprecipitation. We found that CIN85 binding to a C-terminal motif within hTTP led to the increased phosphorylation of hTTP, possibly through enhanced association with MEKK4. The functional consequences to each of the members of this putative complex remain to be determined.

  10. Tuning of protein-surfactant interaction to modify the resultant structure.

    PubMed

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

    2015-09-01

    Small-angle neutron scattering and dynamic light scattering studies have been carried out to examine the interaction of bovine serum albumin (BSA) protein with different surfactants under varying solution conditions. We show that the interaction of anionic BSA protein (pH7) with surfactant and the resultant structure are strongly modified by the charge head group of the surfactant, ionic strength of the solution, and mixed surfactants. The protein-surfactant interaction is maximum when two components are oppositely charged, followed by components being similarly charged through the site-specific binding, and no interaction in the case of a nonionic surfactant. This interaction of protein with ionic surfactants is characterized by the fractal structure representing a bead-necklace structure of micellelike clusters adsorbed along the unfolded protein chain. The interaction is enhanced with ionic strength only in the case of site-specific binding of an anionic surfactant with an anionic protein, whereas it is almost unchanged for other complexes of cationic and nonionic surfactants with anionic proteins. Interestingly, the interaction of BSA protein with ionic surfactants is significantly suppressed in the presence of nonionic surfactant. These results with mixed surfactants thus can be used to fold back the unfolded protein as well as to prevent surfactant-induced protein unfolding. For different solution conditions, the results are interpreted in terms of a change in fractal dimension, the overall size of the protein-surfactant complex, and the number of micelles attached to the protein. The interplay of electrostatic and hydrophobic interactions is found to govern the resultant structure of complexes.

  11. Tuning of protein-surfactant interaction to modify the resultant structure

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

    Small-angle neutron scattering and dynamic light scattering studies have been carried out to examine the interaction of bovine serum albumin (BSA) protein with different surfactants under varying solution conditions. We show that the interaction of anionic BSA protein (p H 7 ) with surfactant and the resultant structure are strongly modified by the charge head group of the surfactant, ionic strength of the solution, and mixed surfactants. The protein-surfactant interaction is maximum when two components are oppositely charged, followed by components being similarly charged through the site-specific binding, and no interaction in the case of a nonionic surfactant. This interaction of protein with ionic surfactants is characterized by the fractal structure representing a bead-necklace structure of micellelike clusters adsorbed along the unfolded protein chain. The interaction is enhanced with ionic strength only in the case of site-specific binding of an anionic surfactant with an anionic protein, whereas it is almost unchanged for other complexes of cationic and nonionic surfactants with anionic proteins. Interestingly, the interaction of BSA protein with ionic surfactants is significantly suppressed in the presence of nonionic surfactant. These results with mixed surfactants thus can be used to fold back the unfolded protein as well as to prevent surfactant-induced protein unfolding. For different solution conditions, the results are interpreted in terms of a change in fractal dimension, the overall size of the protein-surfactant complex, and the number of micelles attached to the protein. The interplay of electrostatic and hydrophobic interactions is found to govern the resultant structure of complexes.

  12. Fluorescent proteins for FRET microscopy: monitoring protein interactions in living cells.

    PubMed

    Day, Richard N; Davidson, Michael W

    2012-05-01

    The discovery and engineering of novel fluorescent proteins (FPs) from diverse organisms is yielding fluorophores with exceptional characteristics for live-cell imaging. In particular, the development of FPs for fluorescence (or Förster) resonance energy transfer (FRET) microscopy is providing important tools for monitoring dynamic protein interactions inside living cells. The increased interest in FRET microscopy has driven the development of many different methods to measure FRET. However, the interpretation of FRET measurements is complicated by several factors including the high fluorescence background, the potential for photoconversion artifacts and the relatively low dynamic range afforded by this technique. Here, we describe the advantages and disadvantages of four methods commonly used in FRET microscopy. We then discuss the selection of FPs for the different FRET methods, identifying the most useful FP candidates for FRET microscopy. The recent success in expanding the FP color palette offers the opportunity to explore new FRET pairs. Copyright © 2012 WILEY Periodicals, Inc.

  13. Identification of proteins that may directly interact with human RPA.

    PubMed

    Nakaya, Ryou; Takaya, Junichiro; Onuki, Takeshi; Moritani, Mariko; Nozaki, Naohito; Ishimi, Yukio

    2010-11-01

    RPA, which consisted of three subunits (RPA1, 2 and 3), plays essential roles in DNA transactions. At the DNA replication forks, RPA binds to single-stranded DNA region to stabilize the structure and to assemble other replication proteins. Interactions between RPA and several replication proteins have been reported but the analysis is not comprehensive. We systematically performed the qualitative analysis to identify RPA interaction partners to understand the protein-protein interaction at the replication forks. We expressed in insect cells the three subunits of human RPA, together with one replication protein, which is present at the forks under normal conditions and/or under the replication stress conditions, to examine the interaction. Among 30 proteins examined in total, it was found that at least 14 proteins interacted with RPA. RPA interacted with MCM3-7, MCM-BP and CDC45 proteins among the proteins that play roles in the initiation and the elongation of the DNA replication. RPA bound with TIPIN, CLASPIN and RAD17, which are involved in the DNA replication checkpoint functions. RPA also bound with cyclin-dependent kinases and an amino-terminal fragment of Rb protein that negatively regulates DNA replication. These results suggest that RPA interacts with the specific proteins among those that play roles in the regulation of the replication fork progression.

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

    Cancer.gov

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

  15. Use of a tandem affinity purification assay to detect interactions between West Nile and dengue viral proteins and proteins of the mosquito vector

    PubMed Central

    Colpitts, Tonya M.; Cox, Jonathan; Nguyen, Annie; Feitosa, Fabiana; Krishnan, Manoj N.; Fikrig, Erol

    2011-01-01

    West Nile and dengue viruses are (re)emerging mosquito-borne flaviviruses that cause significant morbidity and mortality in man. The identification of mosquito proteins that associate with flaviviruses may provide novel targets to inhibit infection of the vector or block transmission to humans. Here, a tandem affinity purification (TAP) assay was used to identify 18 mosquito proteins that interact with dengue and West Nile capsid, envelope, NS2A or NS2B proteins. We further analyzed the interaction of mosquito cadherin with dengue and West Nile virus envelope protein using co-immunoprecipitation and immunofluorescence. Blocking the function of select mosquito factors, including actin, myosin, PI3-kinase and myosin light chain kinase, reduced both dengue and West Nile virus infection in mosquito cells. We show that the TAP method may be used in insect cells to accurately identify flaviviral-host protein interactions. Our data also provides several targets for interrupting flavivirus infection in mosquito vectors. PMID:21700306

  16. Noninvasive imaging of protein-protein interactions in living organisms.

    PubMed

    Haberkorn, Uwe; Altmann, Annette

    2003-06-01

    Genomic research is expected to generate new types of complex observational data, changing the types of experiments as well as our understanding of biological processes. The investigation and definition of relationships among proteins is essential for understanding the function of each gene and the mechanisms of biological processes that specific genes are involved in. Recently, a study by Paulmurugan et al. demonstrated a tool for in vivo noninvasive imaging of protein-protein interactions and intracellular networks.

  17. Interaction of MYC with host cell factor-1 is mediated by the evolutionarily conserved Myc box IV motif.

    PubMed

    Thomas, L R; Foshage, A M; Weissmiller, A M; Popay, T M; Grieb, B C; Qualls, S J; Ng, V; Carboneau, B; Lorey, S; Eischen, C M; Tansey, W P

    2016-07-07

    The MYC family of oncogenes encodes a set of three related transcription factors that are overexpressed in many human tumors and contribute to the cancer-related deaths of more than 70,000 Americans every year. MYC proteins drive tumorigenesis by interacting with co-factors that enable them to regulate the expression of thousands of genes linked to cell growth, proliferation, metabolism and genome stability. One effective way to identify critical co-factors required for MYC function has been to focus on sequence motifs within MYC that are conserved throughout evolution, on the assumption that their conservation is driven by protein-protein interactions that are vital for MYC activity. In addition to their DNA-binding domains, MYC proteins carry five regions of high sequence conservation known as Myc boxes (Mb). To date, four of the Mb motifs (MbI, MbII, MbIIIa and MbIIIb) have had a molecular function assigned to them, but the precise role of the remaining Mb, MbIV, and the reason for its preservation in vertebrate Myc proteins, is unknown. Here, we show that MbIV is required for the association of MYC with the abundant transcriptional coregulator host cell factor-1 (HCF-1). We show that the invariant core of MbIV resembles the tetrapeptide HCF-binding motif (HBM) found in many HCF-interaction partners, and demonstrate that MYC interacts with HCF-1 in a manner indistinguishable from the prototypical HBM-containing protein VP16. Finally, we show that rationalized point mutations in MYC that disrupt interaction with HCF-1 attenuate the ability of MYC to drive tumorigenesis in mice. Together, these data expose a molecular function for MbIV and indicate that HCF-1 is an important co-factor for MYC.

  18. Novel insights into the architecture and protein interaction network of yeast eIF3.

    PubMed

    Khoshnevis, Sohail; Hauer, Florian; Milón, Pohl; Stark, Holger; Ficner, Ralf

    2012-12-01

    Translation initiation in eukaryotes is a multistep process requiring the orchestrated interaction of several eukaryotic initiation factors (eIFs). The largest of these factors, eIF3, forms the scaffold for other initiation factors, promoting their binding to the 40S ribosomal subunit. Biochemical and structural studies on eIF3 need highly pure eIF3. However, natively purified eIF3 comprise complexes containing other proteins such as eIF5. Therefore we have established in vitro reconstitution protocols for Saccharomyces cerevisiae eIF3 using its five recombinantly expressed and purified subunits. This reconstituted eIF3 complex (eIF3(rec)) exhibits the same size and activity as the natively purified eIF3 (eIF3(nat)). The homogeneity and stoichiometry of eIF3(rec) and eIF3(nat) were confirmed by analytical size exclusion chromatography, mass spectrometry, and multi-angle light scattering, demonstrating the presence of one copy of each subunit in the eIF3 complex. The reconstituted and native eIF3 complexes were compared by single-particle electron microscopy showing a high degree of structural conservation. The interaction network between eIF3 proteins was studied by means of limited proteolysis, analytical size exclusion chromatography, in vitro binding assays, and isothermal titration calorimetry, unveiling distinct protein domains and subcomplexes that are critical for the integrity of the protein network in yeast eIF3. Taken together, the data presented here provide a novel procedure to obtain highly pure yeast eIF3, suitable for biochemical and structural analysis, in addition to a detailed picture of the network of protein interactions within this complex.

  19. Novel Burkholderia mallei Virulence Factors Linked to Specific Host-Pathogen Protein Interactions

    DTIC Science & Technology

    2013-06-23

    Wallqvist‡ Burkholderia mallei is an infectious intracellular pathogen whose virulence and resistance to antibiotics makes it a potential bioterrorism agent ...experimental Burkholderia data to ini- tially select a small number of proteins as putative viru- lence factors. We then used yeast two-hybrid assays...causative agent of glan- ders, a disease primarily affecting horses but transmittable to humans; and Burkholderia pseudomallei, which is responsible for

  20. Analysis of protein targets in pathogen-host interaction in infectious diseases: a case study on Plasmodium falciparum and Homo sapiens interaction network.

    PubMed

    Saha, Sovan; Sengupta, Kaustav; Chatterjee, Piyali; Basu, Subhadip; Nasipuri, Mita

    2017-09-23

    Infection and disease progression is the outcome of protein interactions between pathogen and host. Pathogen, the role player of Infection, is becoming a severe threat to life as because of its adaptability toward drugs and evolutionary dynamism in nature. Identifying protein targets by analyzing protein interactions between host and pathogen is the key point. Proteins with higher degree and possessing some topologically significant graph theoretical measures are found to be drug targets. On the other hand, exceptional nodes may be involved in infection mechanism because of some pathway process and biologically unknown factors. In this article, we attempt to investigate characteristics of host-pathogen protein interactions by presenting a comprehensive review of computational approaches applied on different infectious diseases. As an illustration, we have analyzed a case study on infectious disease malaria, with its causative agent Plasmodium falciparum acting as 'Bait' and host, Homo sapiens/human acting as 'Prey'. In this pathogen-host interaction network based on some interconnectivity and centrality properties, proteins are viewed as central, peripheral, hub and non-hub nodes and their significance on infection process. Besides, it is observed that because of sparseness of the pathogen and host interaction network, there may be some topologically unimportant but biologically significant proteins, which can also act as Bait/Prey. So, functional similarity or gene ontology mapping can help us in this case to identify these proteins. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  1. Identification of host proteins, Spata3 and Dkk2, interacting with Toxoplasma gondii micronemal protein MIC3.

    PubMed

    Wang, Yifan; Fang, Rui; Yuan, Yuan; Pan, Ming; Hu, Min; Zhou, Yanqin; Shen, Bang; Zhao, Junlong

    2016-07-01

    As an obligate intracellular protozoan, Toxoplasma gondii is a successful pathogen infecting a variety of animals, including humans. As an adhesin involving in host invasion, the micronemal protein MIC3 plays important roles in host cell attachment, as well as modulation of host EGFR signaling cascade. However, the specific host proteins that interact with MIC3 are unknown and the identification of such proteins will increase our understanding of how MIC3 exerts its functions. This study was designed to identify host proteins interacting with MIC3 by yeast two-hybrid screens. Using MIC3 as bait, a library expressing mouse proteins was screened, uncovering eight mouse proteins that showed positive interactions with MIC3. Two of which, spermatogenesis-associated protein 3 (Spata3) and dickkopf-related protein 2 (Dkk2), were further confirmed to interact with MIC3 by additional protein-protein interaction tests. The results also revealed that the tandem repeat EGF domains of MIC3 were critical in mediating the interactions with the identified host proteins. This is the first study to show that MIC3 interacts with host proteins that are involved in reproduction, growth, and development. The results will provide a clearer understanding of the functions of adhesion-associated micronemal proteins in T. gondii.

  2. Interaction of Erp Protein of Mycobacterium tuberculosis with Rv2212 Enhances Intracellular Survival of Mycobacterium smegmatis.

    PubMed

    Ganaie, Arsheed Ahmad; Trivedi, Garima; Kaur, Amanpreet; Jha, Sidharth Shankar; Anand, Shashi; Rana, Vibhuti; Singh, Amit; Kumar, Shekhar; Sharma, Charu

    2016-10-15

    The Mycobacterium tuberculosis exported repetitive protein (RvErp) is a crucial virulence-associated factor as determined by its role in the survival and multiplication of mycobacteria in cultured macrophages and in vivo Although attempts have been made to understand the function of Erp protein, its exact role in Mycobacterium pathogenesis is still elusive. One way to determine this is by searching for novel interactions of RvErp. Using a yeast two-hybrid assay, an adenylyl cyclase (AC), Rv2212, was found to interact with RvErp. The interaction between RvErp and Rv2212 is direct and occurs at the endogenous level. The Erp protein of Mycobacterium smegmatis (MSMEG_6405, or MsErp) interacts neither with Rv2212 nor with Ms_4279, the M. smegmatis homologue of Rv2212. Deletion mutants of Rv2212 revealed its adenylyl cyclase domain to be responsible for the interaction. RvErp enhances Rv2212-mediated cyclic AMP (cAMP) production. Also, the biological significance of the interaction between RvErp and Rv2212 was demonstrated by the enhanced survival of M. smegmatis within THP-1 macrophages. Taken together, these studies address a novel mechanism by which Erp executes its function. RvErp is one of the important virulence factors of M. tuberculosis This study describes a novel function of RvErp protein of M. tuberculosis by identifying Rv2212 as its interacting protein. Rv2212 is an adenylyl cyclase (AC) and produces cAMP, one of the prime second messengers that regulate the intracellular survival of mycobacteria. Therefore, the significance of investigating novel interactions of RvErp is paramount in unraveling the mechanisms governing the intracellular survival of mycobacteria. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

  3. 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.

  4. Target identification in Fusobacterium nucleatum by subtractive genomics approach and enrichment analysis of host-pathogen protein-protein interactions.

    PubMed

    Kumar, Amit; Thotakura, Pragna Lakshmi; Tiwary, Basant Kumar; Krishna, Ramadas

    2016-05-12

    Fusobacterium nucleatum, a well studied bacterium in periodontal diseases, appendicitis, gingivitis, osteomyelitis and pregnancy complications has recently gained attention due to its association with colorectal cancer (CRC) progression. Treatment with berberine was shown to reverse F. nucleatum-induced CRC progression in mice by balancing the growth of opportunistic pathogens in tumor microenvironment. Intestinal microbiota imbalance and the infections caused by F. nucleatum might be regulated by therapeutic intervention. Hence, we aimed to predict drug target proteins in F. nucleatum, through subtractive genomics approach and host-pathogen protein-protein interactions (HP-PPIs). We also carried out enrichment analysis of host interacting partners to hypothesize the possible mechanisms involved in CRC progression due to F. nucleatum. In subtractive genomics approach, the essential, virulence and resistance related proteins were retrieved from RefSeq proteome of F. nucleatum by searching against Database of Essential Genes (DEG), Virulence Factor Database (VFDB) and Antibiotic Resistance Gene-ANNOTation (ARG-ANNOT) tool respectively. A subsequent hierarchical screening to identify non-human homologous, metabolic pathway-independent/pathway-specific and druggable proteins resulted in eight pathway-independent and 27 pathway-specific druggable targets. Co-aggregation of F. nucleatum with host induces proinflammatory gene expression thereby potentiates tumorigenesis. Hence, proteins from IBDsite, a database for inflammatory bowel disease (IBD) research and those involved in colorectal adenocarcinoma as interpreted from The Cancer Genome Atlas (TCGA) were retrieved to predict drug targets based on HP-PPIs with F. nucleatum proteome. Prediction of HP-PPIs exhibited 186 interactions contributed by 103 host and 76 bacterial proteins. Bacterial interacting partners were accounted as putative targets. And enrichment analysis of host interacting partners showed statistically

  5. Protein Interactions during the Flavivirus and Hepacivirus Life Cycle*

    PubMed Central

    Bruening, Janina; Weigel, Bettina; Pietschmann, Thomas

    2017-01-01

    Protein–protein interactions govern biological functions in cells, in the extracellular milieu, and at the border between cells and extracellular space. Viruses are small intracellular parasites and thus rely on protein interactions to produce progeny inside host cells and to spread from cell to cell. Usage of host proteins by viruses can have severe consequences e.g. apoptosis, metabolic disequilibria, or altered cell proliferation and mobility. Understanding protein interactions during virus infection can thus educate us on viral infection and pathogenesis mechanisms. Moreover, it has led to important clinical translations, including the development of new therapeutic and vaccination strategies. Here, we will discuss protein interactions of members of the Flaviviridae family, which are small enveloped RNA viruses. Dengue virus, Zika virus and hepatitis C virus belong to the most prominent human pathogenic Flaviviridae. With a genome of roughly ten kilobases encoding only ten viral proteins, Flaviviridae display intricate mechanisms to engage the host cell machinery for their purpose. In this review, we will highlight how dengue virus, hepatitis C virus, Japanese encephalitis virus, tick-borne encephalitis virus, West Nile virus, yellow fever virus, and Zika virus proteins engage host proteins and how this knowledge helps elucidate Flaviviridae infection. We will specifically address the protein composition of the virus particle as well as the protein interactions during virus entry, replication, particle assembly, and release from the host cell. Finally, we will give a perspective on future challenges in Flaviviridae interaction proteomics and why we believe these challenges should be met. PMID:28077444

  6. Affinity purification–mass spectrometry and network analysis to understand protein-protein interactions

    PubMed Central

    Morris, John H; Knudsen, Giselle M; Verschueren, Erik; Johnson, Jeffrey R; Cimermancic, Peter; Greninger, Alexander L; Pico, Alexander R

    2015-01-01

    By determining protein-protein interactions in normal, diseased and infected cells, we can improve our understanding of cellular systems and their reaction to various perturbations. In this protocol, we discuss how to use data obtained in affinity purification–mass spectrometry (AP-MS) experiments to generate meaningful interaction networks and effective figures. We begin with an overview of common epitope tagging, expression and AP practices, followed by liquid chromatography–MS (LC-MS) data collection. We then provide a detailed procedure covering a pipeline approach to (i) pre-processing the data by filtering against contaminant lists such as the Contaminant Repository for Affinity Purification (CRAPome) and normalization using the spectral index (SIN) or normalized spectral abundance factor (NSAF); (ii) scoring via methods such as MiST, SAInt and CompPASS; and (iii) testing the resulting scores. Data formats familiar to MS practitioners are then transformed to those most useful for network-based analyses. The protocol also explores methods available in Cytoscape to visualize and analyze these types of interaction data. The scoring pipeline can take anywhere from 1 d to 1 week, depending on one’s familiarity with the tools and data peculiarities. Similarly, the network analysis and visualization protocol in Cytoscape takes 2–4 h to complete with the provided sample data, but we recommend taking days or even weeks to explore one’s data and find the right questions. PMID:25275790

  7. Rice phytochrome-interacting factor protein OsPIF14 represses OsDREB1B gene expression through an extended N-box and interacts preferentially with the active form of Phytochrome B

    PubMed Central

    Cordeiro, André M.; Figueiredo, Duarte D.; Tepperman, James; Borba, Ana Rita; Lourenço, Tiago; Abreu, Isabel A.; Ouwerkerk, Pieter B.F.; Quail, Peter H.; Oliveira, M. Margarida; Saibo, Nelson J. M.

    2016-01-01

    DREB1/CBF genes, known as major regulators of plant stress responses, are rapidly and transiently induced by low temperatures. Using a Yeast one Hybrid screening, we identified a putative Phytochrome-Interacting bHLH Factor (OsPIF14), as binding to the OsDREB1B promoter. bHLH proteins are able to bind to hexameric E-box (CANNTG) or N-box (CACG(A/C)G) motifs, depending on transcriptional activity. We have shown that OsPIF14 binds to the OsDREB1B promoter through two N-boxes and that the flanking regions of the hexameric core are essential for protein-DNA interaction and stability. We also showed that OsPIF14 down-regulates OsDREB1B gene expression in rice protoplasts, corroborating the OsPIF14 repressor activity observed in the transactivation assays using Arabidopsis protoplasts. In addition, we showed that OsPIF14 is indeed a Phytochrome Interacting Factor, which preferentially binds to the active form (Pfr) of rice phytochrome B. This raises the possibility that OsPIF14 activity might be modulated by light. However, we did not observe any regulation of the OsDREB1B gene expression by light under control conditions. Moreover, OsPIF14 gene expression was shown to be modulated by different treatments, such as drought, salt, cold and ABA. Interestingly, OsPIF14 showed also a specific cold-induced alternative splicing. All together, these results suggest the possibility that OsPIF14 is involved in cross-talk between light and stress signaling through interaction with the OsDREB1B promoter. Although in the absence of stress, OsDREB1B gene expression was not regulated by light, given previous reports, it remains possible that OsPIF14 has a role in light modulation of stress responses. PMID:26732823

  8. A quantitative chaperone interaction network reveals the architecture of cellular protein homeostasis pathways

    PubMed Central

    Taipale, Mikko; Tucker, George; Peng, Jian; Krykbaeva, Irina; Lin, Zhen-Yuan; Larsen, Brett; Choi, Hyungwon; Berger, Bonnie; Gingras, Anne-Claude; Lindquist, Susan

    2014-01-01

    Chaperones are abundant cellular proteins that promote the folding and function of their substrate proteins (clients). In vivo, chaperones also associate with a large and diverse set of co-factors (co-chaperones) that regulate their specificity and function. However, how these co-chaperones regulate protein folding and whether they have chaperone-independent biological functions is largely unknown. We have combined mass spectrometry and quantitative high-throughput LUMIER assays to systematically characterize the chaperone/co-chaperone/client interaction network in human cells. We uncover hundreds of novel chaperone clients, delineate their participation in specific co-chaperone complexes, and establish a surprisingly distinct network of protein/protein interactions for co-chaperones. As a salient example of the power of such analysis, we establish that NUDC family co-chaperones specifically associate with structurally related but evolutionarily distinct β-propeller folds. We provide a framework for deciphering the proteostasis network, its regulation in development and disease, and expand the use of chaperones as sensors for drug/target engagement. PMID:25036637

  9. Dynamic interactions between 14-3-3 proteins and phosphoproteins regulate diverse cellular processes

    PubMed Central

    2004-01-01

    14-3-3 proteins exert an extraordinarily widespread influence on cellular processes in all eukaryotes. They operate by binding to specific phosphorylated sites on diverse target proteins, thereby forcing conformational changes or influencing interactions between their targets and other molecules. In these ways, 14-3-3s ‘finish the job’ when phosphorylation alone lacks the power to drive changes in the activities of intracellular proteins. By interacting dynamically with phosphorylated proteins, 14-3-3s often trigger events that promote cell survival – in situations from preventing metabolic imbalances caused by sudden darkness in leaves to mammalian cell-survival responses to growth factors. Recent work linking specific 14-3-3 isoforms to genetic disorders and cancers, and the cellular effects of 14-3-3 agonists and antagonists, indicate that the cellular complement of 14-3-3 proteins may integrate the specificity and strength of signalling through to different cellular responses. PMID:15167810

  10. Patterns of protein–protein interactions in salt solutions and implications for protein crystallization

    PubMed Central

    Dumetz, André C.; Snellinger-O'Brien, Ann M.; Kaler, Eric W.; Lenhoff, Abraham M.

    2007-01-01

    The second osmotic virial coefficients of seven proteins—ovalbumin, ribonuclease A, bovine serum albumin, α-lactalbumin, myoglobin, cytochrome c, and catalase—were measured in salt solutions. Comparison of the interaction trends in terms of the dimensionless second virial coefficient b2 shows that, at low salt concentrations, protein–protein interactions can be either attractive or repulsive, possibly due to the anisotropy of the protein charge distribution. At high salt concentrations, the behavior depends on the salt: In sodium chloride, protein interactions generally show little salt dependence up to very high salt concentrations, whereas in ammonium sulfate, proteins show a sharp drop in b2 with increasing salt concentration beyond a particular threshold. The experimental phase behavior of the proteins corroborates these observations in that precipitation always follows the drop in b2. When the proteins crystallize, they do so at slightly lower salt concentrations than seen for precipitation. The b2 measurements were extended to other salts for ovalbumin and catalase. The trends follow the Hofmeister series, and the effect of the salt can be interpreted as a water-mediated effect between the protein and salt molecules. The b2 trends quantify protein–protein interactions and provide some understanding of the corresponding phase behavior. The results explain both why ammonium sulfate is among the best crystallization agents, as well as some of the difficulties that can be encountered in protein crystallization. PMID:17766383

  11. Small Molecules Engage Hot Spots through Cooperative Binding To Inhibit a Tight Protein-Protein Interaction.

    PubMed

    Liu, Degang; Xu, David; Liu, Min; Knabe, William Eric; Yuan, Cai; Zhou, Donghui; Huang, Mingdong; Meroueh, Samy O

    2017-03-28

    Protein-protein interactions drive every aspect of cell signaling, yet only a few small-molecule inhibitors of these interactions exist. Despite our ability to identify critical residues known as hot spots, little is known about how to effectively engage them to disrupt protein-protein interactions. Here, we take advantage of the ease of preparation and stability of pyrrolinone 1, a small-molecule inhibitor of the tight interaction between the urokinase receptor (uPAR) and its binding partner, the urokinase-type plasminogen activator uPA, to synthesize more than 40 derivatives and explore their effect on the protein-protein interaction. We report the crystal structure of uPAR bound to previously discovered pyrazole 3 and to pyrrolinone 12. While both 3 and 12 bind to uPAR and compete with a fluorescently labeled peptide probe, only 12 and its derivatives inhibit the full uPAR·uPA interaction. Compounds 3 and 12 mimic and engage different hot-spot residues on uPA and uPAR, respectively. Interestingly, 12 is involved in a π-cation interaction with Arg-53, which is not considered a hot spot. Explicit-solvent molecular dynamics simulations reveal that 3 and 12 exhibit dramatically different correlations of motion with residues on uPAR. Free energy calculations for the wild-type and mutant uPAR bound to uPA or 12 show that Arg-53 interacts with uPA or with 12 in a highly cooperative manner, thereby altering the contributions of hot spots to uPAR binding. The direct engagement of peripheral residues not considered hot spots through π-cation or salt-bridge interactions could provide new opportunities for enhanced small-molecule engagement of hot spots to disrupt challenging protein-protein interactions.

  12. Rapid discovery of protein interactions by cell-free protein technologies.

    PubMed

    He, M; Taussig, M J

    2007-11-01

    Cell-free transcription and translation provides an open, controllable environment for production of correctly folded, soluble proteins and allows the rapid generation of proteins from DNA without the need for cloning. Thus it is becoming an increasingly attractive alternative to conventional in vivo expression systems, especially when parallel expression of multiple proteins is required. Through novel design and exploitation, powerful cell-free technologies of ribosome display and protein in situ arrays have been developed for in vitro production and isolation of protein-binding molecules from large libraries. These technologies can be combined for rapid detection of protein interactions.

  13. Super-resolution imaging and tracking of protein-protein interactions in sub-diffraction cellular space

    NASA Astrophysics Data System (ADS)

    Liu, Zhen; Xing, Dong; Su, Qian Peter; Zhu, Yun; Zhang, Jiamei; Kong, Xinyu; Xue, Boxin; Wang, Sheng; Sun, Hao; Tao, Yile; Sun, Yujie

    2014-07-01

    Imaging the location and dynamics of individual interacting protein pairs is essential but often difficult because of the fluorescent background from other paired and non-paired molecules, particularly in the sub-diffraction cellular space. Here we develop a new method combining bimolecular fluorescence complementation and photoactivated localization microscopy for super-resolution imaging and single-molecule tracking of specific protein-protein interactions. The method is used to study the interaction of two abundant proteins, MreB and EF-Tu, in Escherichia coli cells. The super-resolution imaging shows interesting distribution and domain sizes of interacting MreB-EF-Tu pairs as a subpopulation of total EF-Tu. The single-molecule tracking of MreB, EF-Tu and MreB-EF-Tu pairs reveals intriguing localization-dependent heterogonous dynamics and provides valuable insights to understanding the roles of MreB-EF-Tu interactions.

  14. Mpp10 represents a platform for the interaction of multiple factors within the 90S pre-ribosome

    PubMed Central

    Kharde, Satyavati; Ahmed, Yasar Luqman; Stier, Gunter; Kunze, Ruth; Sinning, Irmgard

    2017-01-01

    In eukaryotes, ribosome assembly is a highly complex process that involves more than 200 assembly factors that ensure the folding, modification and processing of the different rRNA species as well as the timely association of ribosomal proteins. One of these factors, Mpp10 associates with Imp3 and Imp4 to form a complex that is essential for the normal production of the 18S rRNA. Here we report the crystal structure of a complex between Imp4 and a short helical element of Mpp10 to a resolution of 1.88 Å. Furthermore, we extend the interaction network of Mpp10 and characterize two novel interactions. Mpp10 is able to bind the ribosome biogenesis factor Utp3/Sas10 through two conserved motifs in its N-terminal region. In addition, Mpp10 interacts with the ribosomal protein S5/uS7 using a short stretch within an acidic loop region. Thus, our findings reveal that Mpp10 provides a platform for the simultaneous interaction with multiple proteins in the 90S pre-ribosome. PMID:28813493

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

    PubMed Central

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

    2017-01-01

    DNA repair is essential for life, yet its efficiency declines with age for reasons that are unclear. Numerous proteins possess Nudix homology domains (NHDs) that have no known function. We show that NHDs are NAD+ (oxidized form of nicotinamide adenine dinucleotide) binding domains that regulate protein-protein interactions. The binding of NAD+ to the NHD domain of DBC1 (deleted in breast cancer 1) prevents it from inhibiting PARP1 [poly(adenosine diphosphate–ribose) polymerase], a critical DNA repair protein. As mice age and NAD+ concentrations decline, DBC1 is increasingly bound to PARP1, causing DNA damage to accumulate, a process rapidly reversed by restoring the abundance of NAD+. Thus, NAD+ directly regulates protein-protein interactions, the modulation of which may protect against cancer, radiation, and aging. PMID:28336669

  16. The coat protein of Alfalfa mosaic virus interacts and interferes with the transcriptional activity of the bHLH transcription factor ILR3 promoting salicylic acid-dependent defence signalling response.

    PubMed

    Aparicio, Frederic; Pallás, Vicente

    2017-02-01

    During virus infection, specific viral component-host factor interaction elicits the transcriptional reprogramming of diverse cellular pathways. Alfalfa mosaic virus (AMV) can establish a compatible interaction in tobacco and Arabidopsis hosts. We show that the coat protein (CP) of AMV interacts directly with transcription factor (TF) ILR3 of both species. ILR3 is a basic helix-loop-helix (bHLH) family member of TFs, previously proposed to participate in diverse metabolic pathways. ILR3 has been shown to regulate NEET in Arabidopsis, a critical protein in plant development, senescence, iron metabolism and reactive oxygen species (ROS) homeostasis. We show that the AMV CP-ILR3 interaction causes a fraction of this TF to relocate from the nucleus to the nucleolus. ROS, pathogenesis-related protein 1 (PR1) mRNAs, salicylic acid (SA) and jasmonic acid (JA) contents are increased in healthy Arabidopsis loss-of-function ILR3 mutant (ilr3.2) plants, which implicates ILR3 in the regulation of plant defence responses. In AMV-infected wild-type (wt) plants, NEET expression is reduced slightly, but is induced significantly in ilr3.2 mutant plants. Furthermore, the accumulation of SA and JA is induced in Arabidopsis wt-infected plants. AMV infection in ilr3.2 plants increases JA by over 10-fold, and SA is reduced significantly, indicating an antagonist crosstalk effect. The accumulation levels of viral RNAs are decreased significantly in ilr3.2 mutants, but the virus can still systemically invade the plant. The AMV CP-ILR3 interaction may down-regulate a host factor, NEET, leading to the activation of plant hormone responses to obtain a hormonal equilibrium state, where infection remains at a level that does not affect plant viability. © 2016 BSPP AND JOHN WILEY & SONS LTD.

  17. Altered receptor trafficking in Huntingtin Interacting Protein 1-transformed cells.

    PubMed

    Rao, Dinesh S; Bradley, Sarah V; Kumar, Priti D; Hyun, Teresa S; Saint-Dic, Djenann; Oravecz-Wilson, Katherine; Kleer, Celina G; Ross, Theodora S

    2003-05-01

    The clathrin-associated protein, Huntingtin Interacting Protein 1 (HIP1), is overexpressed in multiple human epithelial tumors. Here, we report that HIP1 is a novel oncoprotein that transforms cells. HIP1-transformed cells, in contrast to RasV12-transformed cells, have dysregulation of multiple receptors involved in clathrin trafficking. Examples include upregulation of the epidermal growth factor receptor (EGFR) and the transferrin receptor. Furthermore, accumulation of transferrin and EGF in the HIP1-transformed cells was increased, and breast tumors that had EGFR expressed also had HIP1 upregulated. Thus, HIP1 overexpression promotes tumor formation and is associated with a general alteration in receptor trafficking. HIP1 is the first endocytic protein to be directly implicated in tumor formation.

  18. Coarse-grained model for colloidal protein interactions, B(22), and protein cluster formation.

    PubMed

    Blanco, Marco A; Sahin, Erinc; Robinson, Anne S; Roberts, Christopher J

    2013-12-19

    Reversible protein cluster formation is an important initial step in the processes of native and non-native protein aggregation, but involves relatively long time and length scales for detailed atomistic simulations and extensive mapping of free energy landscapes. A coarse-grained (CG) model is presented to semiquantitatively characterize the thermodynamics and key configurations involved in the landscape for protein oligomerization, as well as experimental measures of interactions such as the osmotic second virial coefficient (B22). Based on earlier work (Grüenberger et al., J. Phys. Chem. B 2013, 117, 763), this CG model treats proteins as rigid bodies composed of one bead per amino acid, with each amino acid having specific parameters for its size, hydrophobicity, and charge. The net interactions are a combination of steric repulsions, short-range attractions, and screened long-range charge-charge interactions. Model parametrization was done by fitting simulation results against experimental value of B22 as a function of solution ionic strength for α-chymotrypsinogen A and γD-Crystallin (gD-Crys). The CG model is applied to characterize the pairwise interactions and dimerization of gD-Crys and the dependence on temperature, protein concentration, and ionic strength. The results illustrate that at experimentally relevant conditions where stable dimers do not form, the entropic contributions are predominant in the free-energy of protein cluster formation and colloidal protein interactions, arguing against interpretations that treat B22 primarily from energetic considerations alone. Additionally, the results suggest that electrostatic interactions help to modulate the population of the different stable configurations for protein nearest-neighbor pairs, while short-range attractions determine the relative orientations of proteins within these configurations. Finally, simulation results are combined with Principal Component Analysis to identify those amino

  19. Competition between Ski and CREB-binding protein for binding to Smad proteins in transforming growth factor-beta signaling.

    PubMed

    Chen, Weijun; Lam, Suvana S; Srinath, Hema; Schiffer, Celia A; Royer, William E; Lin, Kai

    2007-04-13

    The family of Smad proteins mediates transforming growth factor-beta (TGF-beta) signaling in cell growth and differentiation. Smads repress or activate TGF-beta signaling by interacting with corepressors (e.g. Ski) or coactivators (e.g. CREB-binding protein (CBP)), respectively. Specifically, Ski has been shown to interfere with the interaction between Smad3 and CBP. However, it is unclear whether Ski competes with CBP for binding to Smads and whether they can interact with Smad3 at the same binding surface on Smad3. We investigated the interactions among purified constructs of Smad, Ski, and CBP in vitro by size-exclusion chromatography, isothermal titration calorimetry, and mutational studies. Here, we show that Ski-(16-192) interacted directly with a homotrimer of receptor-regulated Smad protein (R-Smad), e.g. Smad2 or Smad3, to form a hexamer; Ski-(16-192) interacted with an R-Smad.Smad4 heterotrimer to form a pentamer. CBP-(1941-1992) was also found to interact directly with an R-Smad homotrimer to form a hexamer and with an R-Smad.Smad4 heterotrimer to form a pentamer. Moreover, these domains of Ski and CBP competed with each other for binding to Smad3. Our mutational studies revealed that domains of Ski and CBP interacted with Smad3 at a portion of the binding surface of the Smad anchor for receptor activation. Our results suggest that Ski negatively regulates TGF-beta signaling by replacing CBP in R-Smad complexes. Our working model suggests that Smad protein activity is delicately balanced by Ski and CBP in the TGF-beta pathway.

  20. CHEMOSENSITIZATION BY A NON-APOPTOGENIC HEAT SHOCK PROTEIN 70-BINDING APOPTOSIS INDUCING FACTOR MUTANT

    EPA Science Inventory

    Chemosensitization by a non-apoptogenic heat shock protein 70-binding apoptosis inducing factor mutant

    Abstract
    HSP70 inhibits apoptosis by neutralizing the caspase activator Apaf-1 and by interacting with apoptosis inducing factor (AIF), a mitochondrial flavoprotein wh...