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Sample records for adaptor proteins networks

  1. The fifth adaptor protein complex.

    Jennifer Hirst; Barlow, Lael D.; Gabriel Casey Francisco; Sahlender, Daniela A.; Seaman, Matthew N.J.; Dacks, Joel B.; Robinson, Margaret S.

    2011-01-01

    Adaptor protein (AP) complexes sort cargo into vesicles for transport from one membrane compartment of the cell to another. Four distinct AP complexes have been identified, which are present in most eukaryotes. We report the existence of a fifth AP complex, AP-5. Tagged AP-5 localises to a late endosomal compartment in HeLa cells. AP-5 does not associate with clathrin and is insensitive to brefeldin A. Knocking down AP-5 subunits interferes with the trafficking of the cation-independent manno...

  2. The Fifth Adaptor Protein Complex

    Hirst, Jennifer; D. Barlow, Lael; Francisco, Gabriel Casey; Sahlender, Daniela A.; Seaman, Matthew N.J.; Dacks, Joel B.; Robinson, Margaret S.

    2011-01-01

    Adaptor protein (AP) complexes sort cargo into vesicles for transport from one membrane compartment of the cell to another. Four distinct AP complexes have been identified, which are present in most eukaryotes. We report the existence of a fifth AP complex, AP-5. Tagged AP-5 localises to a late endosomal compartment in HeLa cells. AP-5 does not associate with clathrin and is insensitive to brefeldin A. Knocking down AP-5 subunits interferes with the trafficking of the cation-independent manno...

  3. The fifth adaptor protein complex.

    Jennifer Hirst

    2011-10-01

    Full Text Available Adaptor protein (AP complexes sort cargo into vesicles for transport from one membrane compartment of the cell to another. Four distinct AP complexes have been identified, which are present in most eukaryotes. We report the existence of a fifth AP complex, AP-5. Tagged AP-5 localises to a late endosomal compartment in HeLa cells. AP-5 does not associate with clathrin and is insensitive to brefeldin A. Knocking down AP-5 subunits interferes with the trafficking of the cation-independent mannose 6-phosphate receptor and causes the cell to form swollen endosomal structures with emanating tubules. AP-5 subunits can be found in all five eukaryotic supergroups, but they have been co-ordinately lost in many organisms. Concatenated phylogenetic analysis provides robust resolution, for the first time, into the evolutionary order of emergence of the adaptor subunit families, showing AP-3 as the basal complex, followed by AP-5, AP-4, and AP-1 and AP-2. Thus, AP-5 is an evolutionarily ancient complex, which is involved in endosomal sorting, and which has links with hereditary spastic paraplegia.

  4. PAG - a multipurpose transmembrane adaptor protein

    Hrdinka, Matouš; Hořejší, Václav

    2014-01-01

    Roč. 33, č. 41 (2014), s. 4881-4892. ISSN 0950-9232 R&D Projects: GA ČR(CZ) GBP302/12/G101 Institutional support: RVO:68378050 Keywords : PAG * adaptor protein * membrane raft Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 8.459, year: 2014

  5. Adaptor protein complexes and intracellular transport

    2014-01-01

    The AP (adaptor protein) complexes are heterotetrameric protein complexes that mediate intracellular membrane trafficking along endocytic and secretory transport pathways. There are five different AP complexes: AP-1, AP-2 and AP-3 are clathrin-associated complexes; whereas AP-4 and AP-5 are not. These five AP complexes localize to different intracellular compartments and mediate membrane trafficking in distinct pathways. They recognize and concentrate cargo proteins into vesicular carriers th...

  6. Role of adaptor proteins in secretory granule biogenesis and maturation

    RichardEMains

    2013-08-01

    Full Text Available In the regulated secretory pathway, secretory granules (SGs store peptide hormones that are released on demand. SGs are formed at the trans-Golgi network (TGN and must undergo a maturation process to become responsive to secretagogues. The production of mature SGs requires concentrating newly synthesized soluble content proteins in granules whose membranes contain the appropriate integral membrane proteins. The mechanisms underlying the sorting of soluble and integral membrane proteins destined for SGs from other proteins are not yet well understood. For soluble proteins, luminal pH and divalent metals can affect aggregation and interaction with surrounding membranes. The trafficking of granule membrane proteins can be controlled by both luminal and cytosolic factors. Cytosolic adaptor proteins, which recognize the cytosolic domains of proteins that span the SG membrane, have been shown to play essential roles in the assembly of functional SGs. Adaptor protein 1A (AP-1A is known to interact with specific motifs in its cargo proteins and with the clathrin heavy chain, contributing to the formation of a clathrin coat. AP-1A is present in patches on immature SG membranes, where it removes cargo and facilitates SG maturation. AP-1A recruitment to membranes can be modulated by PACS-1 (Phosphofurin Acidic Cluster Sorting protein 1, a cytosolic protein which interacts with both AP-1A and cargo that has been phosphorylated by casein kinase II. A cargo/PACS-1/AP-1A complex is necessary to drive the appropriate transport of several cargo proteins within the regulated secretory pathway. The GGA (Golgi-localized, -ear containing, ADP-ribosylation factor binding family of adaptor proteins serve a similar role. We review the functions of AP-1A, PACS-1 and GGAs in facilitating the retrieval of proteins from immature SGs and review examples of cargo proteins whose trafficking within the regulated secretory pathway is governed by adaptor proteins.

  7. The Transmembrane Adaptor Protein SIT Inhibits TCR-Mediated Signaling

    Arndt, Börge; Krieger, Tina; Kalinski, Thomas; Thielitz, Anja; Reinhold, Dirk; Roessner, Albert; Schraven, Burkhart; Simeoni, Luca

    2011-01-01

    Transmembrane adaptor proteins (TRAPs) organize signaling complexes at the plasma membrane, and thus function as critical linkers and integrators of signaling cascades downstream of antigen receptors. We have previously shown that the transmembrane adaptor protein SIT regulates the threshold for thymocyte selection. Moreover, T cells from SIT-deficient mice are hyperresponsive to CD3 stimulation and undergo enhanced lymphopenia-induced homeostatic proliferation, thus indicating that SIT inhib...

  8. Palmitoylated transmembrane adaptor proteins in leukocyte signaling

    Štěpánek, Ondřej; Dráber, Peter; Hořejší, Václav

    2014-01-01

    Roč. 26, č. 5 (2014), s. 895-902. ISSN 0898-6568 R&D Projects: GA ČR(CZ) GBP302/12/G101 Institutional support: RVO:68378050 Keywords : Leukocyte * Adaptor * Palmitoylation Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.315, year: 2014

  9. Yeast Golgi-localized, γ-Ear–containing, ADP-Ribosylation Factor-binding Proteins Are but Adaptor Protein-1 Is Not Required for Cell-free Transport of Membrane Proteins from the Trans-Golgi Network to the Prevacuolar Compartment

    Abazeed, Mohamed E.; Fuller, Robert S.

    2008-01-01

    Golgi-localized, γ-Ear–containing, ADP-ribosylation factor-binding proteins (GGAs) and adaptor protein-1 (AP-1) mediate clathrin-dependent trafficking of transmembrane proteins between the trans-Golgi network (TGN) and endosomes. In yeast, the vacuolar sorting receptor Vps10p follows a direct pathway from the TGN to the late endosome/prevacuolar compartment (PVC), whereas, the processing protease Kex2p partitions between the direct pathway and an indirect pathway through the early endosome. T...

  10. The Src homology and collagen A (ShcA) adaptor protein is required for the spatial organization of the costamere/Z-disk network during heart development.

    Mlih, Mohamed; Host, Lionel; Martin, Sophie; Niederhoffer, Nathalie; Monassier, Laurent; Terrand, Jérôme; Messaddeq, Nadia; Radke, Michael; Gotthardt, Michael; Bruban, Véronique; Kober, Frank; Bernard, Monique; Canet-Soulas, Emmanuelle; Abt-Jijon, Francisco; Boucher, Philippe; Matz, Rachel L

    2015-01-23

    Src homology and collagen A (ShcA) is an adaptor protein that binds to tyrosine kinase receptors. Its germ line deletion is embryonic lethal with abnormal cardiovascular system formation, and its role in cardiovascular development is unknown. To investigate its functional role in cardiovascular development in mice, ShcA was deleted in cardiomyocytes and vascular smooth muscle cells by crossing ShcA flox mice with SM22a-Cre transgenic mice. Conditional mutant mice developed signs of severe dilated cardiomyopathy, myocardial infarctions, and premature death. No evidence of a vascular contribution to the phenotype was observed. Histological analysis of the heart revealed aberrant sarcomeric Z-disk and M-band structures, and misalignments of T-tubules with Z-disks. We find that not only the ErbB3/Neuregulin signaling pathway but also the baroreceptor reflex response, which have been functionally associated, are altered in the mutant mice. We further demonstrate that ShcA interacts with Caveolin-1 and the costameric protein plasma membrane Ca(2+)/calmodulin-dependent ATPase (PMCA), and that its deletion leads to abnormal dystrophin signaling. Collectively, these results demonstrate that ShcA interacts with crucial proteins and pathways that link Z-disk and costamere. PMID:25488665

  11. The Src Homology and Collagen A (ShcA) Adaptor Protein Is Required for the Spatial Organization of the Costamere/Z-disk Network during Heart Development*

    Mlih, Mohamed; Host, Lionel; Martin, Sophie; Niederhoffer, Nathalie; Monassier, Laurent; Terrand, Jérôme; Messaddeq, Nadia; Radke, Michael; Gotthardt, Michael; Bruban, Véronique; Kober, Frank; Bernard, Monique; Canet-Soulas, Emmanuelle; Abt-Jijon, Francisco; Boucher, Philippe; Matz, Rachel L.

    2015-01-01

    Src homology and collagen A (ShcA) is an adaptor protein that binds to tyrosine kinase receptors. Its germ line deletion is embryonic lethal with abnormal cardiovascular system formation, and its role in cardiovascular development is unknown. To investigate its functional role in cardiovascular development in mice, ShcA was deleted in cardiomyocytes and vascular smooth muscle cells by crossing ShcA flox mice with SM22a-Cre transgenic mice. Conditional mutant mice developed signs of severe dilated cardiomyopathy, myocardial infarctions, and premature death. No evidence of a vascular contribution to the phenotype was observed. Histological analysis of the heart revealed aberrant sarcomeric Z-disk and M-band structures, and misalignments of T-tubules with Z-disks. We find that not only the ErbB3/Neuregulin signaling pathway but also the baroreceptor reflex response, which have been functionally associated, are altered in the mutant mice. We further demonstrate that ShcA interacts with Caveolin-1 and the costameric protein plasma membrane Ca2+/calmodulin-dependent ATPase (PMCA), and that its deletion leads to abnormal dystrophin signaling. Collectively, these results demonstrate that ShcA interacts with crucial proteins and pathways that link Z-disk and costamere. PMID:25488665

  12. Structure of the periplasmic adaptor protein from a major facilitator superfamily (MFS) multidrug efflux pump.

    Hinchliffe, Philip; Greene, Nicholas P; Paterson, Neil G; Crow, Allister; Hughes, Colin; Koronakis, Vassilis

    2014-08-25

    Periplasmic adaptor proteins are key components of bacterial tripartite efflux pumps. The 2.85 Å resolution structure of an MFS (major facilitator superfamily) pump adaptor, Aquifex aeolicus EmrA, shows linearly arranged α-helical coiled-coil, lipoyl, and β-barrel domains, but lacks the fourth membrane-proximal domain shown in other pumps to interact with the inner membrane transporter. The adaptor α-hairpin, which binds outer membrane TolC, is exceptionally long at 127 Å, and the β-barrel contains a conserved disordered loop. The structure extends the view of adaptors as flexible, modular components that mediate diverse pump assembly, and suggests that in MFS tripartite pumps a hexamer of adaptors could provide a periplasmic seal. PMID:24996185

  13. Structure of the periplasmic adaptor protein from a major facilitator superfamily (MFS) multidrug efflux pump

    Hinchliffe, Philip; Greene, Nicholas P.; Paterson, Neil G.; Crow, Allister; Hughes, Colin; Koronakis, Vassilis

    2014-01-01

    Periplasmic adaptor proteins are key components of bacterial tripartite efflux pumps. The 2.85 Å resolution structure of an MFS (major facilitator superfamily) pump adaptor, Aquifex aeolicus EmrA, shows linearly arranged α-helical coiled-coil, lipoyl, and β-barrel domains, but lacks the fourth membrane-proximal domain shown in other pumps to interact with the inner membrane transporter. The adaptor α-hairpin, which binds outer membrane TolC, is exceptionally long at 127 Å, and the β-barrel co...

  14. Autoinhibition of Mint1 adaptor protein regulates amyloid precursor protein binding and processing

    Matos, Maria F.; Xu, Yibin; Dulubova, Irina; Otwinowski, Zbyszek; Richardson, John M.; Tomchick, Diana R.; Rizo, Josep; Ho, Angela

    2012-01-01

    Mint adaptor proteins bind to the amyloid precursor protein (APP) and regulate APP processing associated with Alzheimer’s disease; however, the molecular mechanisms underlying Mint regulation in APP binding and processing remain unclear. Biochemical, biophysical, and cellular experiments now show that the Mint1 phosphotyrosine binding (PTB) domain that binds to APP is intramolecularly inhibited by the adjacent C-terminal linker region. The crystal structure of a C-terminally extended Mint1 PT...

  15. Molecular protein adaptor with genetically encoded interaction sites guiding the hierarchical assembly of plasmonically active nanoparticle architectures

    Schreiber, Andreas; Huber, Matthias C.; Cölfen, Helmut; Schiller, Stefan M.

    2015-03-01

    The control over the defined assembly of nano-objects with nm-precision is important to create systems and materials with enhanced properties, for example, metamaterials. In nature, the precise assembly of inorganic nano-objects with unique features, for example, magnetosomes, is accomplished by efficient and reliable recognition schemes involving protein effectors. Here we present a molecular approach using protein-based ‘adaptors/connectors’ with genetically encoded interaction sites to guide the assembly and functionality of different plasmonically active gold nanoparticle architectures (AuNP). The interaction of the defined geometricaly shaped protein adaptors with the AuNP induces the self-assembly of nanoarchitectures ranging from AuNP encapsulation to one-dimensional chain-like structures, complex networks and stars. Synthetic biology and bionanotechnology are applied to co-translationally encode unnatural amino acids as additional site-specific modification sites to generate functionalized biohybrid nanoarchitectures. This protein adaptor-based nano-object assembly approach might be expanded to other inorganic nano-objects creating biohybrid materials with unique electronic, photonic, plasmonic and magnetic properties.

  16. Biochemical and Structural Studies on the Adaptor Protein p130Cas

    Nasertorabi, Fariborz

    2005-01-01

    Crk associated substrate (Cas) is an adaptor protein that becomes phosphorylated upon integrin signaling and influences regulation of cell processes such as migration, proliferation and survival. It consists of multiple domains and regions that can interact with several signaling proteins involved in different signaling pathways. Cas was first discovered as a highly phosphorylated protein in v-Src and v-Crk transformed cells, showing involvement of this protein in cell transformation High lev...

  17. SR proteins are NXF1 adaptors that link alternative RNA processing to mRNA export.

    Müller-McNicoll, Michaela; Botti, Valentina; de Jesus Domingues, Antonio M; Brandl, Holger; Schwich, Oliver D; Steiner, Michaela C; Curk, Tomaz; Poser, Ina; Zarnack, Kathi; Neugebauer, Karla M

    2016-03-01

    Nuclear export factor 1 (NXF1) exports mRNA to the cytoplasm after recruitment to mRNA by specific adaptor proteins. How and why cells use numerous different export adaptors is poorly understood. Here we critically evaluate members of the SR protein family (SRSF1-7) for their potential to act as NXF1 adaptors that couple pre-mRNA processing to mRNA export. Consistent with this proposal, >1000 endogenous mRNAs required individual SR proteins for nuclear export in vivo. To address the mechanism, transcriptome-wide RNA-binding profiles of NXF1 and SRSF1-7 were determined in parallel by individual-nucleotide-resolution UV cross-linking and immunoprecipitation (iCLIP). Quantitative comparisons of RNA-binding sites showed that NXF1 and SR proteins bind mRNA targets at adjacent sites, indicative of cobinding. SRSF3 emerged as the most potent NXF1 adaptor, conferring sequence specificity to RNA binding by NXF1 in last exons. Interestingly, SRSF3 and SRSF7 were shown to bind different sites in last exons and regulate 3' untranslated region length in an opposing manner. Both SRSF3 and SRSF7 promoted NXF1 recruitment to mRNA. Thus, SRSF3 and SRSF7 couple alternative splicing and polyadenylation to NXF1-mediated mRNA export, thereby controlling the cytoplasmic abundance of transcripts with alternative 3' ends. PMID:26944680

  18. Yeast Golgi-localized, gamma-Ear-containing, ADP-ribosylation factor-binding proteins are but adaptor protein-1 is not required for cell-free transport of membrane proteins from the trans-Golgi network to the prevacuolar compartment.

    Abazeed, Mohamed E; Fuller, Robert S

    2008-11-01

    Golgi-localized, gamma-Ear-containing, ADP-ribosylation factor-binding proteins (GGAs) and adaptor protein-1 (AP-1) mediate clathrin-dependent trafficking of transmembrane proteins between the trans-Golgi network (TGN) and endosomes. In yeast, the vacuolar sorting receptor Vps10p follows a direct pathway from the TGN to the late endosome/prevacuolar compartment (PVC), whereas, the processing protease Kex2p partitions between the direct pathway and an indirect pathway through the early endosome. To examine the roles of the Ggas and AP-1 in TGN-PVC transport, we used a cell-free assay that measures delivery to the PVC of either Kex2p or a chimeric protein (K-V), in which the Vps10p cytosolic tail replaces the Kex2p tail. Either antibody inhibition or dominant-negative Gga2p completely blocked K-V transport but only partially blocked Kex2p transport. Deletion of APL2, encoding the beta subunit of AP-1, did not affect K-V transport but partially blocked Kex2p transport. Residual Kex2p transport seen with apl2Delta membranes was insensitive to dominant-negative Gga2p, suggesting that the apl2Delta mutation causes Kex2p to localize to a compartment that precludes Gga-dependent trafficking. These results suggest that yeast Ggas facilitate the specific and direct delivery of Vps10p and Kex2p from the TGN to the PVC and that AP-1 modulates Kex2p trafficking through a distinct pathway, presumably involving the early endosome. PMID:18784256

  19. Yeast Golgi-localized, γ-Ear–containing, ADP-Ribosylation Factor-binding Proteins Are but Adaptor Protein-1 Is Not Required for Cell-free Transport of Membrane Proteins from the Trans-Golgi Network to the Prevacuolar Compartment

    Abazeed, Mohamed E.

    2008-01-01

    Golgi-localized, γ-Ear–containing, ADP-ribosylation factor-binding proteins (GGAs) and adaptor protein-1 (AP-1) mediate clathrin-dependent trafficking of transmembrane proteins between the trans-Golgi network (TGN) and endosomes. In yeast, the vacuolar sorting receptor Vps10p follows a direct pathway from the TGN to the late endosome/prevacuolar compartment (PVC), whereas, the processing protease Kex2p partitions between the direct pathway and an indirect pathway through the early endosome. To examine the roles of the Ggas and AP-1 in TGN–PVC transport, we used a cell-free assay that measures delivery to the PVC of either Kex2p or a chimeric protein (K-V), in which the Vps10p cytosolic tail replaces the Kex2p tail. Either antibody inhibition or dominant-negative Gga2p completely blocked K-V transport but only partially blocked Kex2p transport. Deletion of APL2, encoding the β subunit of AP-1, did not affect K-V transport but partially blocked Kex2p transport. Residual Kex2p transport seen with apl2Δ membranes was insensitive to dominant-negative Gga2p, suggesting that the apl2Δ mutation causes Kex2p to localize to a compartment that precludes Gga-dependent trafficking. These results suggest that yeast Ggas facilitate the specific and direct delivery of Vps10p and Kex2p from the TGN to the PVC and that AP-1 modulates Kex2p trafficking through a distinct pathway, presumably involving the early endosome. PMID:18784256

  20. DMPD: Structure, function and regulation of the Toll/IL-1 receptor adaptor proteins. [Dynamic Macrophage Pathway CSML Database

    Full Text Available 17667936 Structure, function and regulation of the Toll/IL-1 receptor adaptor prote... (.svg) (.html) (.csml) Show Structure, function and regulation of the Toll/IL-1 receptor adaptor proteins. ...PubmedID 17667936 Title Structure, function and regulation of the Toll/IL-1 recep

  1. Insulin Receptor Substrate Adaptor Proteins Mediate Prognostic Gene Expression Profiles in Breast Cancer

    Becker, Marc A.; Ibrahim, Yasir H.; Oh, Annabell S.; Fagan, Dedra H.; Byron, Sara A.; Sarver, Aaron L.; Lee, Adrian V.; Shaw, Leslie M.; Fan, Cheng; Perou, Charles M.; Yee, Douglas

    2016-01-01

    Therapies targeting the type I insulin-like growth factor receptor (IGF-1R) have not been developed with predictive biomarkers to identify tumors with receptor activation. We have previously shown that the insulin receptor substrate (IRS) adaptor proteins are necessary for linking IGF1R to downstream signaling pathways and the malignant phenotype in breast cancer cells. The purpose of this study was to identify gene expression profiles downstream of IGF1R and its two adaptor proteins. IRS-null breast cancer cells (T47D-YA) were engineered to express IRS-1 or IRS-2 alone and their ability to mediate IGF ligand-induced proliferation, motility, and gene expression determined. Global gene expression signatures reflecting IRS adaptor specific and primary vs. secondary ligand response were derived (Early IRS-1, Late IRS-1, Early IRS-2 and Late IRS-2) and functional pathway analysis examined. IRS isoforms mediated distinct gene expression profiles, functional pathways, and breast cancer subtype association. For example, IRS-1/2-induced TGFb2 expression and blockade of TGFb2 abrogated IGF-induced cell migration. In addition, the prognostic value of IRS proteins was significant in the luminal B breast tumor subtype. Univariate and multivariate analyses confirmed that IRS adaptor signatures correlated with poor outcome as measured by recurrence-free and overall survival. Thus, IRS adaptor protein expression is required for IGF ligand responses in breast cancer cells. IRS-specific gene signatures represent accurate surrogates of IGF activity and could predict response to anti-IGF therapy in breast cancer. PMID:26991655

  2. The interaction between the adaptor protein APS and Enigma is involved in actin organisation

    Barres, Romain; Gonzalez, Teresa; Le Marchand-Brustel, Yannick; Tanti, Jean-François

    2005-01-01

    APS (adaptor protein with PH and SH2 domains) is an adaptor protein phosphorylated by several tyrosine kinase receptors including the insulin receptor. To identify novel binding partners of APS, we performed yeast two-hybrid screening. We identified Enigma, a PDZ and LIM domain-containing protein...... that was previously shown to be associated with the actin cytoskeleton. In HEK 293 cells, Enigma interacted specifically with APS, but not with the APS-related protein SH2-B. This interaction required the NPTY motif of APS and the LIM domains of Enigma. In NIH-3T3 cells that express the insulin...... receptor, Enigma and APS were partially co-localised with F-actin in small ruffling structures. Insulin increased the complex formation between APS and Enigma and their co-localisation in large F-actin containing ruffles. While in NIH-3T3 and HeLa cells the co-expression of both Enigma and APS did not...

  3. PIP2: choreographer of actin-adaptor proteins in the HIV-1 dance

    Rocha-Perugini, Vera; Gordon-Alonso, Mónica; Sánchez-Madrid, Francisco

    2014-01-01

    The actin cytoskeleton plays a key role during the replication cycle of human immunodeficiency virus-1 (HIV-1). HIV-1 infection is affected by cellular proteins that influence the clustering of viral receptors or the subcortical actin cytoskeleton. Several of these actin-adaptor proteins are controlled by the second messenger phosphatidylinositol 4,5-biphosphate (PIP2), an important regulator of actin organization. PIP2 production is induced by HIV-1 attachment and facilitates viral infection. However, the importance of PIP2 in regulating cytoskeletal proteins and thus HIV-1 infection has been overlooked. This review examines recent reports describing the roles played by actin-adaptor proteins during HIV-1 infection of CD4+ T cells, highlighting the influence of the signaling lipid PIP2 in this process. PMID:24768560

  4. Chromatin Adaptor Brd4 Modulates E2 Transcription Activity and Protein Stability*

    Lee, A-Young; Chiang, Cheng-Ming

    2009-01-01

    Brd4 is a chromatin adaptor containing tandem bromodomains binding to acetylated histone H3 and H4. Although Brd4 has been implicated in the transcriptional control of papillomavirus-encoded E2 protein, it is unclear how Brd4 regulates E2 function and whether the involvement of Brd4 in transactivation and transrepression is common to different types of E2 proteins. Using DNase I footprinting performed with in vitro reconstituted human papillomavirus (HPV) chromatin and...

  5. Nuclear Translocation of Crk Adaptor Proteins by the Influenza A Virus NS1 Protein.

    Ylösmäki, Leena; Fagerlund, Riku; Kuisma, Inka; Julkunen, Ilkka; Saksela, Kalle

    2016-01-01

    The non-structural protein-1 (NS1) of many influenza A strains, especially those of avian origin, contains an SH3 ligand motif, which binds tightly to the cellular adaptor proteins Crk (Chicken tumor virus number 10 (CT10) regulator of kinase) and Crk-like adapter protein (CrkL). This interaction has been shown to potentiate NS1-induced activation of the phosphatidylinositol 3-kinase (PI3K), but additional effects on the host cell physiology may exist. Here we show that NS1 can induce an efficient translocation of Crk proteins from the cytoplasm into the nucleus, which results in an altered pattern of nuclear protein tyrosine phosphorylation. This was not observed using NS1 proteins deficient in SH3 binding or engineered to be exclusively cytoplasmic, indicating a physical role for NS1 as a carrier in the nuclear translocation of Crk. These data further emphasize the role of Crk proteins as host cell interaction partners of NS1, and highlight the potential for host cell manipulation gained by a viral protein simply via acquiring a short SH3 binding motif. PMID:27092521

  6. Nuclear Translocation of Crk Adaptor Proteins by the Influenza A Virus NS1 Protein

    Leena Ylösmäki

    2016-04-01

    Full Text Available The non-structural protein-1 (NS1 of many influenza A strains, especially those of avian origin, contains an SH3 ligand motif, which binds tightly to the cellular adaptor proteins Crk (Chicken tumor virus number 10 (CT10 regulator of kinase and Crk-like adapter protein (CrkL. This interaction has been shown to potentiate NS1-induced activation of the phosphatidylinositol 3-kinase (PI3K, but additional effects on the host cell physiology may exist. Here we show that NS1 can induce an efficient translocation of Crk proteins from the cytoplasm into the nucleus, which results in an altered pattern of nuclear protein tyrosine phosphorylation. This was not observed using NS1 proteins deficient in SH3 binding or engineered to be exclusively cytoplasmic, indicating a physical role for NS1 as a carrier in the nuclear translocation of Crk. These data further emphasize the role of Crk proteins as host cell interaction partners of NS1, and highlight the potential for host cell manipulation gained by a viral protein simply via acquiring a short SH3 binding motif.

  7. Nuclear Translocation of Crk Adaptor Proteins by the Influenza A Virus NS1 Protein

    Ylösmäki, Leena; Fagerlund, Riku; Kuisma, Inka; Julkunen, Ilkka; Saksela, Kalle

    2016-01-01

    The non-structural protein-1 (NS1) of many influenza A strains, especially those of avian origin, contains an SH3 ligand motif, which binds tightly to the cellular adaptor proteins Crk (Chicken tumor virus number 10 (CT10) regulator of kinase) and Crk-like adapter protein (CrkL). This interaction has been shown to potentiate NS1-induced activation of the phosphatidylinositol 3-kinase (PI3K), but additional effects on the host cell physiology may exist. Here we show that NS1 can induce an efficient translocation of Crk proteins from the cytoplasm into the nucleus, which results in an altered pattern of nuclear protein tyrosine phosphorylation. This was not observed using NS1 proteins deficient in SH3 binding or engineered to be exclusively cytoplasmic, indicating a physical role for NS1 as a carrier in the nuclear translocation of Crk. These data further emphasize the role of Crk proteins as host cell interaction partners of NS1, and highlight the potential for host cell manipulation gained by a viral protein simply via acquiring a short SH3 binding motif. PMID:27092521

  8. New Insights to Clathrin and Adaptor Protein 2 for the Design and Development of Therapeutic Strategies

    Ebbe Toftgaard Poulsen

    2015-12-01

    Full Text Available The Amyloid Precursor Protein (APP has been extensively studied for its role as the precursor of the β-amyloid protein (Aβ in Alzheimer’s disease (AD. However, our understanding of the normal function of APP is still patchy. Emerging evidence indicates that a dysfunction in APP trafficking and degradation can be responsible for neuronal deficits and progressive degeneration in humans. We recently reported that the Y682 mutation in the 682YENPTY687 domain of APP affects its binding to specific adaptor proteins and leads to its anomalous trafficking, to defects in the autophagy machinery and to neuronal degeneration. In order to identify adaptors that influence APP function, we performed pull-down experiments followed by quantitative mass spectrometry (MS on hippocampal tissue extracts of three month-old mice incubated with either the 682YENPTY687 peptide, its mutated form, 682GENPTY687 or its phosphorylated form, 682pYENPTY687. Our experiments resulted in the identification of two proteins involved in APP internalization and trafficking: Clathrin heavy chain (hc and its Adaptor Protein 2 (AP-2. Overall our results consolidate and refine the importance of Y682 in APP normal functions from an animal model of premature aging and dementia. Additionally, they open the perspective to consider Clathrin hc and AP-2 as potential targets for the design and development of new therapeutic strategies.

  9. Science Signaling Podcast for 12 July 2016: Adaptor proteins limit signaling.

    Wiley, H Steven; VanHook, Annalisa M

    2016-01-01

    This Podcast features an interview with Steven Wiley, senior author of a Research Article that appears in the 12 July 2016 issue of Science Signaling, about how the abundance of adaptor proteins and feedback regulators affect the flow of information downstream of the epidermal growth factor receptor (EGFR). Information flows through a signaling pathway by sequential interactions between core components of the pathway, many of which have enzymatic activity. Adaptor proteins do not directly participate in relaying the signal and do not have enzymatic activity, but are important for signaling because they facilitate interactions between the core components. Using quantitative methods, Shi et al demonstrated that core components of the EGFR pathway were highly abundant in both normal cells and cancer cells. However, adaptor proteins were present in much lower abundance in both cell types, indicating that it is the abundance of these proteins that limit signaling downstream of EGFR. The authors also found that differences in EGFR signaling between different cell types likely resulted from the variable abundance of feedback regulators.Listen to Podcast. PMID:27405978

  10. Selective autophagy of non-ubiquitylated targets in plants: looking for cognate receptor/adaptor proteins

    Vasko eVeljanovski

    2014-06-01

    Full Text Available Cellular homeostasis is essential for the physiology of eukaryotic cells. Eukaryotic cells, including plant cells, utilize two main pathways to adjust the level of cytoplasmic components, namely the proteasomal and the lysosomal/vacuolar pathways. Macroautophagy is a lysosomal/vacuolar pathway which, until recently, was thought to be non-specific and a bulk degradation process. However, selective autophagy which can be activated in the cell under various physiological conditions, involves the specific degradation of defined macromolecules or organelles by a conserved molecular mechanism. For this process to be efficient, the mechanisms underlying the recognition and selection of the cargo to be engulfed by the double-membrane autophagosome are critical, and not yet well understood. Ubiquitin (poly-ubiquitin conjugation to the target appears to be a conserved ligand mechanism in many types of selective autophagy, and defined receptors/adaptors recognizing and regulating the autophagosomal capture of the ubiquitylated target have been characterized. However, non-proteinaceous and non-ubiquitylated cargoes are also selectively degraded by this pathway. This ubiquitin-independent selective autophagic pathway also involves receptor and/or adaptor proteins linking the cargo to the autophagic machinery. Some of these receptor/adaptor proteins including accessory autophagy-related (Atg and non-Atg proteins have been described in yeast and animal cells but not yet in plants. In this review we discuss the ubiquitin-independent cargo selection mechanisms in selective autophagy degradation of organelles and macromolecules and speculate on potential plant receptor/adaptor proteins.

  11. Molecular physiology of the tensin brotherhood of integrin adaptor proteins.

    Haynie, Donald T

    2014-07-01

    Numerous proteins have been identified as constituents of the adhesome, the totality of molecular components in the supramolecular assemblies known as focal adhesions, fibrillar adhesions and other kinds of adhesive contact. The transmembrane receptor proteins called integrins are pivotal adhesome members, providing a physical link between the extracellular matrix (ECM) and the actin cytoskeleton. Tensins are ever more widely investigated intracellular adhesome constituents. Involved in cell attachment and migration, cytoskeleton reorganization, signal transduction and other processes relevant to cancer research, tensins have recently been linked to functional properties of deleted in liver cancer 1 (DLC1) and a mitogen-activated protein kinases (MAPK), to cell migration in breast cancer, and to metastasis suppression in the kidney. Tensins are close relatives of phosphatase homolog/tensin homolog (PTEN), an extensively studied tumor suppressor. Such findings are recasting the earlier vision of tensin (TNS) as an actin-filament (F-actin) capping protein in a different light. This critical review aims to summarize current knowledge on tensins and thus to highlight key points concerning the expression, structure, function, and evolution of the various members of the TNS brotherhood. Insight is sought by comparisons with homologous proteins. Some historical points are added for perspective. PMID:24634006

  12. Surfactant Protein A Enhances Constitutive Immune Functions of Clathrin Heavy Chain and Clathrin Adaptor Protein 2.

    Moulakakis, Christina; Steinhäuser, Christine; Biedziak, Dominika; Freundt, Katja; Reiling, Norbert; Stamme, Cordula

    2016-07-01

    NF-κB transcription factors are key regulators of pulmonary inflammatory disorders and repair. Constitutive lung cell type- and microenvironment-specific NF-κB/inhibitor κBα (IκB-α) regulation, however, is poorly understood. Surfactant protein (SP)-A provides both a critical homeostatic and lung defense control, in part by immune instruction of alveolar macrophages (AMs) via clathrin-mediated endocytosis. The central endocytic proteins, clathrin heavy chain (CHC) and the clathrin adaptor protein (AP) complex AP2, have pivotal alternative roles in cellular homeostasis that are endocytosis independent. Here, we dissect endocytic from alternative functions of CHC, the α-subunit of AP2, and dynamin in basal and SP-A-modified LPS signaling of macrophages. As revealed by pharmacological inhibition and RNA interference in primary AMs and RAW264.7 macrophages, respectively, CHC and α-adaptin, but not dynamin, prevent IκB-α degradation and TNF-α release, independent of their canonical role in membrane trafficking. Kinetics studies employing confocal microscopy, Western analysis, and immunomagnetic sorting revealed that SP-A transiently enhances the basal protein expression of CHC and α-adaptin, depending on early activation of protein kinase CK2 (former casein kinase II) and Akt1 in primary AMs from rats, SP-A(+/+), and SP-A(-/-) mice, as well as in vivo when intratracheally administered to SP-A(+/+) mice. Constitutive immunomodulation by SP-A, but not SP-A-mediated inhibition of LPS-induced NF-κB activity and TNF-α release, requires CHC, α-adaptin, and dynamin. Our data demonstrate that endocytic proteins constitutively restrict NF-κB activity in macrophages and provide evidence that SP-A enhances the immune regulatory capacity of these proteins, revealing a previously unknown pathway of microenvironment-specific NF-κB regulation in the lung. PMID:26771574

  13. Regulation and function of the CD3¿ DxxxLL motif: a binding site for adaptor protein-1 and adaptor protein-2 in vitro

    Dietrich, J; Kastrup, J; Nielsen, B L;

    1997-01-01

    /CD3gamma chimeras; and in vitro by binding CD3gamma peptides to clathrin-coated vesicle adaptor proteins (APs). We find that the CD3gamma D127xxxLL131/132 sequence represents one united motif for binding of both AP-1 and AP-2, and that this motif functions as an active sorting motif in monomeric CD4...... and for AP binding in vitro. Furthermore, we provide evidence indicating that phosphorylation of CD3gamma S126 in the context of the complete TCR induces a conformational change that exposes the DxxxLL sequence for AP binding. Exposure of the DxxxLL motif causes an increase in the TCR internalization...

  14. The role of small adaptor proteins in the control of oncogenic signaling driven by tyrosine kinases in human cancer

    Naudin, Cécile; Chevalier, Clément; Roche, Serge

    2016-01-01

    Protein phosphorylation on tyrosine (Tyr) residues has evolved as an important mechanism to coordinate cell communication in multicellular organisms. The importance of this process has been revealed by the discovery of the prominent oncogenic properties of tyrosine kinases (TK) upon deregulation of their physiological activities, often due to protein overexpression and/or somatic mutation. Recent reports suggest that TK oncogenic signaling is also under the control of small adaptor proteins. These cytosolic proteins lack intrinsic catalytic activity and signal by linking two functional members of a catalytic pathway. While most adaptors display positive regulatory functions, a small group of this family exerts negative regulatory functions by targeting several components of the TK signaling cascade. Here, we review how these less studied adaptor proteins negatively control TK activities and how their loss of function induces abnormal TK signaling, promoting tumor formation. We also discuss the therapeutic consequences of this novel regulatory mechanism in human oncology. PMID:26788993

  15. The Cytoplasmic Adaptor Protein Dok7 Activates the Receptor Tyrosine Kinase MuSK via Dimerization

    Bergamin, E.; Hallock, P; Burden, S; Hubbard, S

    2010-01-01

    Formation of the vertebrate neuromuscular junction requires, among others proteins, Agrin, a neuronally derived ligand, and the following muscle proteins: LRP4, the receptor for Agrin; MuSK, a receptor tyrosine kinase (RTK); and Dok7 (or Dok-7), a cytoplasmic adaptor protein. Dok7 comprises a pleckstrin-homology (PH) domain, a phosphotyrosine-binding (PTB) domain, and C-terminal sites of tyrosine phosphorylation. Unique among adaptor proteins recruited to RTKs, Dok7 is not only a substrate of MuSK, but also an activator of MuSK's kinase activity. Here, we present the crystal structure of the Dok7 PH-PTB domains in complex with a phosphopeptide representing the Dok7-binding site on MuSK. The structure and biochemical data reveal a dimeric arrangement of Dok7 PH-PTB that facilitates trans-autophosphorylation of the kinase activation loop. The structure provides the molecular basis for MuSK activation by Dok7 and for rationalizing several Dok7 loss-of-function mutations found in patients with congenital myasthenic syndromes.

  16. Nrf2 reduces levels of phosphorylated tau protein by inducing autophagy adaptor protein NDP52

    Jo, Chulman; Gundemir, Soner; Pritchard, Susanne; Jin, Youngnam N.; Rahman, Irfan; Johnson, Gail V. W.

    2014-03-01

    Nuclear factor erythroid 2-related factor 2 (Nrf2) is a pivotal transcription factor in the defence against oxidative stress. Here we provide evidence that activation of the Nrf2 pathway reduces the levels of phosphorylated tau by induction of an autophagy adaptor protein NDP52 (also known as CALCOCO2) in neurons. The expression of NDP52, which we show has three antioxidant response elements (AREs) in its promoter region, is strongly induced by Nrf2, and its overexpression facilitates clearance of phosphorylated tau in the presence of an autophagy stimulator. In Nrf2-knockout mice, phosphorylated and sarkosyl-insoluble tau accumulates in the brains concurrent with decreased levels of NDP52. Moreover, NDP52 associates with phosphorylated tau from brain cortical samples of Alzheimer disease cases, and the amount of phosphorylated tau in sarkosyl-insoluble fractions is inversely proportional to that of NDP52. These results suggest that NDP52 plays a key role in autophagy-mediated degradation of phosphorylated tau in vivo.

  17. Transmembrane adaptor proteins in the high-affinity IgE receptor signaling

    Dráber, Petr; Hálová, Ivana; Levi-Schaffer, F.; Dráberová, Lubica

    2012-01-01

    Roč. 2, 11.1. (2012), s. 95. ISSN 1664-3224 R&D Projects: GA MŠk 1M0506; GA ČR GA301/09/1826; GA ČR GAP302/10/1759; GA AV ČR KAN200520701 Grant ostatní: AV ČR(CZ) M200520901 Institutional research plan: CEZ:AV0Z50520514 Institutional support: RVO:68378050 Keywords : IgE receptor * LAT/LAT1 * LAX * NTAL/Lab/LAT2 * PAG/Cbp * mast cells * plasma membrane * transmembrane adaptor proteins Subject RIV: EB - Genetics ; Molecular Biology

  18. The Influences of Connectors and Adaptors to Fiber-To-The-Home Network Performance

    Mohammad S. Ab-Rahman

    2012-01-01

    Full Text Available Problem statement: The reliability of the entire communications network was dependent on the reliability of each single element. Connector was important devices that can affect the performance of the fiber communication. There were a large number of issues that affect the performance of fiber optic connectors in todays networks. These factors were increasingly as data rates, the number of wavelengths and transmission distances continue to escalate. Approach: Therefore this study was carried out to test on the influence of connectors and adapters to the performance of the optical network. Initially the actual attenuation of connector and adaptor were tested by using multifunction loss tester. The first two 1 m corning optical fibers with a connector at each end are measured. Then, both the 1 m corning optical fibers were joined together by an adaptor and connected to the Multifunction loss tester. Three types of wavelength are used as the source to test the attenuation of the fiber which is 1310, 1490-1550 nm. In order to measure the Bit Error Rate (BER and the power loss in optical fiber communication, a simple simulation was carried out by using software opti sys. Results: The attenuation on the connector was caused mainly by existence of impurities in the connector, less perfect connection, scattering of beam and others. These causes the parameter such as power received, Q-factor, minimum BER and also the eye-height to change. Changes in these parameters also affect the performance at the user end. It was very critical that causes of attenuation to be eliminated. Conclusion/Recommendations: From the result it can be concluded that, the greater the attenuation, the greater the decrease in power received. It also affects the Q-factor of the system where as the attenuation increase, the maximum Q-factor decreases. As for the minimum BER, minimum BER changes as the attenuation increase initially, after a maximum value it decreases as the

  19. Phosphorylation-Dependent Regulation of the DNA Damage Response of Adaptor Protein KIBRA in Cancer Cells.

    Mavuluri, Jayadev; Beesetti, Swarnalatha; Surabhi, Rohan; Kremerskothen, Joachim; Venkatraman, Ganesh; Rayala, Suresh K

    2016-05-01

    Multifunctional adaptor proteins encompassing various protein-protein interaction domains play a central role in the DNA damage response pathway. In this report, we show that KIBRA is a physiologically interacting reversible substrate of ataxia telangiectasia mutated (ATM) kinase. We identified the site of phosphorylation in KIBRA as threonine 1006, which is embedded within the serine/threonine (S/T) Q consensus motif, by site-directed mutagenesis, and we further confirmed the same with a phospho-(S/T) Q motif-specific antibody. Results from DNA repair functional assays such as the γ-H2AX assay, pulsed-field gel electrophoresis (PFGE), Comet assay, terminal deoxynucleotidyltransferase-mediated dUTP-biotin nick end labeling (TUNEL) assay, and clonogenic cell survival assay using stable overexpression clones of wild-type (wt.) KIBRA and active (T1006E) and inactive (T1006A) KIBRA phosphorylation mutants showed that T1006 phosphorylation on KIBRA is essential for optimal DNA double-strand break repair in cancer cells. Further, results from stable retroviral short hairpin RNA-mediated knockdown (KD) clones of KIBRA and KIBRA knockout (KO) model cells generated by a clustered regularly interspaced short palindromic repeat (CRISPR)-Cas9 system showed that depleting KIBRA levels compromised the DNA repair functions in cancer cells upon inducing DNA damage. All these phenotypic events were reversed upon reconstitution of KIBRA into cells lacking KIBRA knock-in (KI) model cells. All these results point to the fact that phosphorylated KIBRA might be functioning as a scaffolding protein/adaptor protein facilitating the platform for further recruitment of other DNA damage response factors. In summary, these data demonstrate the imperative functional role of KIBRAper se(KIBRA phosphorylation at T1006 site as a molecular switch that regulates the DNA damage response, possibly via the nonhomologous end joining [NHEJ] pathway), suggesting that KIBRA could be a potential

  20. Proteins recruited by SH3 domains of Ruk/CIN85 adaptor identified by LC-MS/MS

    Havrylov Serhiy

    2009-06-01

    Full Text Available Abstract Background Ruk/CIN85 is a mammalian adaptor molecule with three SH3 domains. Using its SH3 domains Ruk/CIN85 can cluster multiple proteins and protein complexes, and, consequently, facilitates organisation of elaborate protein interaction networks with diverse regulatory roles. Previous research linked Ruk/CIN85 with the regulation of vesicle-mediated transport and cancer cell invasiveness. Despite the recent findings, precise molecular functions of Ruk/CIN85 in these processes remain largely elusive and further research is hampered by a lack of complete lists of its partner proteins. Results In the present study we employed a LC-MS/MS-based experimental pipeline to identify a considerable number (over 100 of proteins recruited by the SH3 domains of Ruk/CIN85 in vitro. Most of these identifications are novel Ruk/CIN85 interaction candidates. The identified proteins have diverse molecular architectures and can interact with other proteins, as well as with lipids and nucleic acids. Some of the identified proteins possess enzymatic activities. Functional profiling analyses and literature mining demonstrate that many of the proteins recruited by the SH3 domains of Ruk/CIN85 identified in this work were involved in the regulation of membranes and cytoskeletal structures necessary for vesicle-mediated transport and cancer cell invasiveness. Several groups of the proteins were also associated with few other cellular processes not previously related to Ruk/CIN85, most prominently with cell division. Conclusion Obtained data support the notion that Ruk/CIN85 regulates vesicle-mediated transport and cancer cell invasiveness through the assembly of multimeric protein complexes governing coordinated remodelling of membranes and underlying cytoskeletal structures, and imply its important roles in formation of coated vesicles and biogenesis of invadopodia. In addition, this study points to potential involvement of Ruk/CIN85 in other cellular

  1. The Adaptor Protein Rai/ShcC Promotes Astrocyte-Dependent Inflammation during Experimental Autoimmune Encephalomyelitis.

    Ulivieri, Cristina; Savino, Maria Teresa; Luccarini, Ilaria; Fanigliulo, Emanuela; Aldinucci, Alessandra; Bonechi, Elena; Benagiano, Marisa; Ortensi, Barbara; Pelicci, Giuliana; D'Elios, Mario Milco; Ballerini, Clara; Baldari, Cosima Tatiana

    2016-07-15

    Th17 cells have been casually associated to the pathogenesis of autoimmune disease. We have previously demonstrated that Rai/ShcC, a member of the Shc family of adaptor proteins, negatively regulates Th17 cell differentiation and lupus autoimmunity. In this study, we have investigated the pathogenic outcome of the Th17 bias associated with Rai deficiency on multiple sclerosis development, using the experimental autoimmune encephalomyelitis (EAE) mouse model. We found that, unexpectedly, EAE was less severe in Rai(-/-) mice compared with their wild-type counterparts despite an enhanced generation of myelin-specific Th17 cells that infiltrated into the CNS. Nevertheless, when adoptively transferred into immunodeficient Rai(+/+) mice, these cells promoted a more severe disease compared with wild-type encephalitogenic Th17 cells. This paradoxical phenotype was caused by a dampened inflammatory response of astrocytes, which were found to express Rai, to IL-17. The results provide evidence that Rai plays opposite roles in Th17 cell differentiation and astrocyte activation, with the latter dominant over the former in EAE, highlighting this adaptor as a potential novel target for the therapy of multiple sclerosis. PMID:27288534

  2. The role of palmitoylation and transmembrane domain in sorting of transmembrane adaptor proteins.

    Chum, Tomáš; Glatzová, Daniela; Kvíčalová, Zuzana; Malínský, Jan; Brdička, Tomáš; Cebecauer, Marek

    2016-01-01

    Plasma membrane proteins synthesised at the endoplasmic reticulum are delivered to the cell surface via sorting pathways. Hydrophobic mismatch theory based on the length of the transmembrane domain (TMD) dominates discussion about determinants required for protein sorting to the plasma membrane. Transmembrane adaptor proteins (TRAP) are involved in signalling events which take place at the plasma membrane. Members of this protein family have TMDs of varying length. We were interested in whether palmitoylation or other motifs contribute to the effective sorting of TRAP proteins. We found that palmitoylation is essential for some, but not all, TRAP proteins independent of their TMD length. We also provide evidence that palmitoylation and proximal sequences can modulate sorting of artificial proteins with TMDs of suboptimal length. Our observations point to a unique character of each TMD defined by its primary amino acid sequence and its impact on membrane protein localisation. We conclude that, in addition to the TMD length, secondary sorting determinants such as palmitoylation or flanking sequences have evolved for the localisation of membrane proteins. PMID:26585312

  3. Shc adaptor proteins are key transducers of mitogenic signaling mediated by the G protein-coupled thrombin receptor

    Chen, Y; Grall, D; Salcini, A E; Pelicci, P G; Pouysségur, J; Van Obberghen-Schilling, E

    1996-01-01

    The serine protease thrombin activates G protein signaling systems that lead to Ras activation and, in certain cells, proliferation. Whereas the steps leading to Ras activation by G protein-coupled receptors are not well defined, the mechanisms of Ras activation by receptor tyrosine kinases have...... kinase activation, gene induction and cell growth. From these data, we conclude that Shc represents a crucial point of convergence between signaling pathways activated by receptor tyrosine kinases and G protein-coupled receptors....... recently been elucidated biochemically and genetically. The present study was undertaken to determine whether common signaling components are used by these two distinct classes of receptors. Here we report that the adaptor protein Shc, is phosphorylated on tyrosine residues following stimulation of the...

  4. The Adaptor Protein-1 μ1B Subunit Expands the Repertoire of Basolateral Sorting Signal Recognition in Epithelial Cells

    Guo, Xiaoli; Mattera, Rafael; Ren, Xuefeng; Chen, Yu; Retamal, Claudio; González, Alfonso; Bonifacino, Juan S.

    2014-01-01

    SUMMARY An outstanding question in protein sorting is why polarized epithelial cells express two isoforms of the μ1 subunit of the AP-1 clathrin adaptor complex: the ubiquitous μ1A and the epithelial-specific μ1B. Previous studies led to the notion that μ1A and μ1B mediate basolateral sorting predominantly from the trans-Golgi network (TGN) and recycling endosomes, respectively. Using improved analytical tools, however, we find that μ1A and μ1B largely colocalize with each other. They also colocalize to similar extents with TGN and recycling endosome markers, as well as with basolateral cargoes transiting biosynthetic and endocytic-recycling routes. Instead, the two isoforms differ in their signal-recognition specificity. In particular, μ1B preferentially binds a subset of signals from cargoes that are sorted basolaterally in a μ1B-dependent manner. We conclude that expression of distinct μ1 isoforms in epithelial cells expands the repertoire of signals recognized by AP-1 for sorting of a broader range of cargoes to the basolateral surface. PMID:24229647

  5. Tetraspanins and Transmembrane Adaptor Proteins As Plasma Membrane Organizers—Mast Cell Case

    Halova, Ivana; Draber, Petr

    2016-01-01

    The plasma membrane contains diverse and specialized membrane domains, which include tetraspanin-enriched domains (TEMs) and transmembrane adaptor protein (TRAP)-enriched domains. Recent biophysical, microscopic, and functional studies indicated that TEMs and TRAP-enriched domains are involved in compartmentalization of physicochemical events of such important processes as immunoreceptor signal transduction and chemotaxis. Moreover, there is evidence of a cross-talk between TEMs and TRAP-enriched domains. In this review we discuss the presence and function of such domains and their crosstalk using mast cells as a model. The combined data based on analysis of selected mast cell-expressed tetraspanins [cluster of differentiation (CD)9, CD53, CD63, CD81, CD151)] or TRAPs [linker for activation of T cells (LAT), non-T cell activation linker (NTAL), and phosphoprotein associated with glycosphingolipid-enriched membrane microdomains (PAG)] using knockout mice or specific antibodies point to a diversity within these two families and bring evidence of the important roles of these molecules in signaling events. An example of this diversity is physical separation of two TRAPs, LAT and NTAL, which are in many aspects similar but show plasma membrane location in different microdomains in both non-activated and activated cells. Although our understanding of TEMs and TRAP-enriched domains is far from complete, pharmaceutical applications of the knowledge about these domains are under way.

  6. Cysteine-based regulation of the CUL3 adaptor protein Keap1

    Nrf2 (NF-E2-related factor 2) is a master transcription factor containing a powerful acidic transcriptional activation domain. Nrf2-dependent gene expression impacts cancer chemoprevention strategies, inflammatory responses, and progression of neurodegenerative diseases. Under basal conditions, association of Nrf2 with the CUL3 adaptor protein Keap1 results in the rapid Nrf2 ubiquitylation and proteasome-dependent degradation. Inhibition of Keap1 function blocks ubiquitylation of Nrf2, allowing newly synthesized Nrf2 to translocate into the nucleus, bind to ARE sites and direct target gene expression. Site-directed mutagenesis experiments coupled with proteomic analysis support a model in which Keap1 contains at least 2 distinct cysteine motifs. The first is located at Cys 151 in the BTB domain. The second is located in the intervening domain and centers around Cys 273 and 288. Adduction or oxidation at Cys151 has been shown to produce a conformational change in Keap1 that results in dissociation of Keap1 from CUL3, thereby inhibiting Nrf2 ubiquitylation. Thus, adduction captures specific chemical information and translates it into biochemical information via changes in structural conformation.

  7. Canine hepacivirus NS3 serine protease can cleave the human adaptor proteins MAVS and TRIF.

    Mariona Parera

    Full Text Available Canine hepacivirus (CHV was recently identified in domestic dogs and horses. The finding that CHV is genetically the virus most closely related to hepatitis C virus (HCV has raised the question of whether HCV might have evolved as the result of close contact between dogs and/or horses and humans. The aim of this study was to investigate whether the NS3/4A serine protease of CHV specifically cleaves human mitochondrial antiviral signaling protein (MAVS and Toll-IL-1 receptor domain-containing adaptor inducing interferon-beta (TRIF. The proteolytic activity of CHV NS3/4A was evaluated using a bacteriophage lambda genetic screen. Human MAVS- and TRIF-specific cleavage sites were engineered into the lambda cI repressor. Upon infection of Escherichia coli cells coexpressing these repressors and a CHV NS3/4A construct, lambda phage replicated up to 2000-fold more efficiently than in cells expressing a CHV protease variant carrying the inactivating substitution S139A. Comparable results were obtained when several HCV NS3/4A constructs of genotype 1b were assayed. This indicates that CHV can disrupt the human innate antiviral defense signaling pathway and suggests a possible evolutionary relationship between CHV and HCV.

  8. Adaptor protein LNK is a negative regulator of brain neural stem cell proliferation after stroke.

    Ahlenius, Henrik; Devaraju, Karthikeyan; Monni, Emanuela; Oki, Koichi; Wattananit, Somsak; Darsalia, Vladimer; Iosif, Robert E; Torper, Olof; Wood, James C; Braun, Sebastian; Jagemann, Lucas; Nuber, Ulrike A; Englund, Elisabet; Jacobsen, Sten-Eirik W; Lindvall, Olle; Kokaia, Zaal

    2012-04-11

    Ischemic stroke causes transient increase of neural stem and progenitor cell (NSPC) proliferation in the subventricular zone (SVZ), and migration of newly formed neuroblasts toward the damaged area where they mature to striatal neurons. The molecular mechanisms regulating this plastic response, probably involved in structural reorganization and functional recovery, are poorly understood. The adaptor protein LNK suppresses hematopoietic stem cell self-renewal, but its presence and role in the brain are poorly understood. Here we demonstrate that LNK is expressed in NSPCs in the adult mouse and human SVZ. Lnk(-/-) mice exhibited increased NSPC proliferation after stroke, but not in intact brain or following status epilepticus. Deletion of Lnk caused increased NSPC proliferation while overexpression decreased mitotic activity of these cells in vitro. We found that Lnk expression after stroke increased in SVZ through the transcription factors STAT1/3. LNK attenuated insulin-like growth factor 1 signaling by inhibition of AKT phosphorylation, resulting in reduced NSPC proliferation. Our findings identify LNK as a stroke-specific, endogenous negative regulator of NSPC proliferation, and suggest that LNK signaling is a novel mechanism influencing plastic responses in postischemic brain. PMID:22496561

  9. LIME: a new membrane raft-associated adaptor protein involved in CD4 and CD8 coreceptor signaling

    Brdičková, Naděžda; Brdička, Tomáš; Angelisová, Pavla; Horváth, Ondřej; Špička, Jiří; Hilgert, Ivan; Pačes, Jan; Simeoni, L.; Kliche, S.; Merten, C.; Schraven, B.; Hořejší, Václav

    2003-01-01

    Roč. 198, č. 10 (2003), s. 1453-1462. ISSN 0022-1007 R&D Projects: GA MŠk LN00A079; GA MŠk LN00A026 Grant ostatní: Wellcome Trust(GB) J1116W24Z Institutional research plan: CEZ:AV0Z5052915 Keywords : immunology * T-lymphocyte * adaptor protein Subject RIV: EC - Immunology Impact factor: 15.302, year: 2003

  10. Mint3/X11γ Is an ADP-Ribosylation Factor-dependent Adaptor that Regulates the Traffic of the Alzheimer's Precursor Protein from the Trans-Golgi Network

    Shrivastava-Ranjan, Punya; Faundez, Victor; Fang, Guofu; Rees, Howard; Lah, James J.; Allan I Levey; Kahn, Richard A.

    2008-01-01

    β-Amyloid peptides (Aβ) are the major component of plaques in brains of Alzheimer's patients, and are they derived from the proteolytic processing of the β-amyloid precursor protein (APP). The movement of APP between organelles is highly regulated, and it is tightly connected to its processing by secretases. We proposed previously that transport of APP within the cell is mediated in part through its sorting into Mint/X11-containing carriers. To test our hypothesis, we purified APP-containing ...

  11. Adaptor protein sorting nexin 17 regulates amyloid precursor protein trafficking and processing in the early endosomes

    Lee, Jiyeon; Retamal, Claudio; Cuitino, Loreto; Caruano-Yzermans, Amy; Shin, Jung-Eun; van Kerkhof, Peter; Marzolo, Maria-Paz; Bu, Guojun

    2008-01-01

    Accumulation of extracellular amyloid beta peptide (A beta), generated from amyloid precursor protein (APP) processing by beta- and gamma-secretases, is toxic to neurons and is central to the pathogenesis of Alzheimer disease. Production of A beta from APP is greatly affected by the subcellular loca

  12. Brain-derived neurotrophic factor modulation of Kv1.3 channel is disregulated by adaptor proteins Grb10 and nShc

    Marks David R

    2009-01-01

    Full Text Available Abstract Background Neurotrophins are important regulators of growth and regeneration, and acutely, they can modulate the activity of voltage-gated ion channels. Previously we have shown that acute brain-derived neurotrophic factor (BDNF activation of neurotrophin receptor tyrosine kinase B (TrkB suppresses the Shaker voltage-gated potassium channel (Kv1.3 via phosphorylation of multiple tyrosine residues in the N and C terminal aspects of the channel protein. It is not known how adaptor proteins, which lack catalytic activity, but interact with members of the neurotrophic signaling pathway, might scaffold with ion channels or modulate channel activity. Results We report the co-localization of two adaptor proteins, neuronal Src homology and collagen (nShc and growth factor receptor-binding protein 10 (Grb10, with Kv1.3 channel as demonstrated through immunocytochemical approaches in the olfactory bulb (OB neural lamina. To further explore the specificity and functional ramification of adaptor/channel co-localization, we performed immunoprecipitation and Western analysis of channel, kinase, and adaptor transfected human embryonic kidney 293 cells (HEK 293. nShc formed a direct protein-protein interaction with Kv1.3 that was independent of BDNF-induced phosphorylation of Kv1.3, whereas Grb10 did not complex with Kv1.3 in HEK 293 cells. Both adaptors, however, co-immunoprecipitated with Kv1.3 in native OB. Grb10 was interestingly able to decrease the total expression of Kv1.3, particularly at the membrane surface, and subsequently eliminated the BDNF-induced phosphorylation of Kv1.3. To examine the possibility that the Src homology 2 (SH2 domains of Grb10 were directly binding to basally phosphorylated tyrosines in Kv1.3, we utilized point mutations to substitute multiple tyrosine residues with phenylalanine. Removal of the tyrosines 111–113 and 449 prevented Grb10 from decreasing Kv1.3 expression. In the absence of either adaptor protein

  13. CD2v Interacts with Adaptor Protein AP-1 during African Swine Fever Infection.

    Daniel Pérez-Núñez

    Full Text Available African swine fever virus (ASFV CD2v protein is believed to be involved in virulence enhancement, viral hemadsorption, and pathogenesis, although the molecular mechanisms of the function of this viral protein are still not fully understood. Here we describe that CD2v localized around viral factories during ASFV infection, suggesting a role in the generation and/or dynamics of these viral structures and hence in disturbing cellular traffic. We show that CD2v targeted the regulatory trans-Golgi network (TGN protein complex AP-1, a key element in cellular traffic. This interaction was disrupted by brefeldin A even though the location of CD2v around the viral factory remained unchanged. CD2v-AP-1 binding was independent of CD2v glycosylation and occurred on the carboxy-terminal part of CD2v, where a canonical di-Leu motif previously reported to mediate AP-1 binding in eukaryotic cells, was identified. This motif was shown to be functionally interchangeable with the di-Leu motif present in HIV-Nef protein in an AP-1 binding assay. However, we demonstrated that it was not involved either in CD2v cellular distribution or in CD2v-AP-1 binding. Taken together, these findings shed light on CD2v function during ASFV infection by identifying AP-1 as a cellular factor targeted by CD2v and hence elucidate the cellular pathways used by the virus to enhance infectivity.

  14. Disruption of adaptor protein 2mu (AP-2mu) in cochlear hair cells impairs vesicle reloading of synaptic release sites and hearing

    Jung, S.; Maritzen, T.; Wichmann, C.; Jing, Z.; Neef, A.; Revelo, N.H.; Al-Moyed, H.; Meese, S.; Wojcik, S.M.; Panou, I.; Bulut, H.; Schu, P.; Ficner, R.; Reisinger, E.; Rizzoli, S.O.; Neef, J.; Strenzke, N.; Haucke, V.; Moser, T.

    2015-01-01

    Active zones (AZs) of inner hair cells (IHCs) indefatigably release hundreds of vesicles per second, requiring each release site to reload vesicles at tens per second. Here, we report that the endocytic adaptor protein 2mu (AP-2mu) is required for release site replenishment and hearing. We show that

  15. A dimer of the Toll-like receptor 4 cytoplasmic domain provides a specific scaffold for the recruitment of signalling adaptor proteins.

    Ricardo Núñez Miguel

    Full Text Available The Toll-like receptor 4 (TLR4 is a class I transmembrane receptor expressed on the surface of immune system cells. TLR4 is activated by exposure to lipopolysaccharides derived from the outer membrane of Gram negative bacteria and forms part of the innate immune response in mammals. Like other class 1 receptors, TLR4 is activated by ligand induced dimerization, and recent studies suggest that this causes concerted conformational changes in the receptor leading to self association of the cytoplasmic Toll/Interleukin 1 receptor (TIR signalling domain. This homodimerization event is proposed to provide a new scaffold that is able to bind downstream signalling adaptor proteins. TLR4 uses two different sets of adaptors; TRAM and TRIF, and Mal and MyD88. These adaptor pairs couple two distinct signalling pathways leading to the activation of interferon response factor 3 (IRF-3 and nuclear factor kappaB (NFkappaB respectively. In this paper we have generated a structural model of the TLR4 TIR dimer and used molecular docking to probe for potential sites of interaction between the receptor homodimer and the adaptor molecules. Remarkably, both the Mal and TRAM adaptors are strongly predicted to bind at two symmetry-related sites at the homodimer interface. This model of TLR4 activation is supported by extensive functional studies involving site directed mutagenesis, inhibition by cell permeable peptides and stable protein phosphorylation of receptor and adaptor TIR domains. Our results also suggest a molecular mechanism for two recent findings, the caspase 1 dependence of Mal signalling and the protective effects conferred by the Mal polymorphism Ser180Leu.

  16. Functional interaction of megalin with the megalinbinding protein (MegBP), a novel tetratrico peptide repeat-containing adaptor molecule.

    Petersen, Helle Heibroch; Hilpert, Jan; Militz, Daniel; Zandler, Valerie; Jacobsen, Christian; Roebroek, Anton J M; Willnow, Thomas E

    2003-02-01

    Megalin is a member of the LDL receptor gene family that plays an important role in forebrain development and in cellular vitamin D metabolism through endocytic uptake of vitamin D metabolites. Similar to other receptors in this gene family, megalin is believed to functionally interact with intracellular proteins through adaptors that bind to the receptor tail and regulate its endocytic and signal transducing activities. Using yeast two-hybrid screens, we identified a novel scaffold protein with tetratrico peptide repeats, the megalin-binding protein (MegBP) that associates with the receptor. The binding site of MegBP was mapped to an N-terminal region on the receptor tail harboring a proline-rich peptide element. MegBP binding did not block the endocytic activity of the receptor; however, overexpression resulted in cellular lethality. In further screens, we identified proteins that bound to MegBP and thus might be recruited to the megalin tail. MegBP-interacting partners included several transcriptional regulators such as the SKI-interacting protein (SKIP), a co-activator of the vitamin D receptor. These finding suggest a model whereby megalin directly participates in transcriptional regulation through controlled sequestration or release of transcription factors via MegBP. PMID:12508107

  17. Adaptor protein complexes AP-1 and AP-3 are required by the HHV-7 Immunoevasin U21 for rerouting of class I MHC molecules to the lysosomal compartment.

    Lisa A Kimpler

    Full Text Available The human herpesvirus-7 (HHV-7 U21 gene product binds to class I major histocompatibility complex (MHC molecules and reroutes them to a lysosomal compartment. Trafficking of integral membrane proteins to lysosomes is mediated through cytoplasmic sorting signals that recruit heterotetrameric clathrin adaptor protein (AP complexes, which in turn mediate protein sorting in post-Golgi vesicular transport. Since U21 can mediate rerouting of class I molecules to lysosomes even when lacking its cytoplasmic tail, we hypothesize the existence of a cellular protein that contains the lysosomal sorting information required to escort class I molecules to the lysosomal compartment. If such a protein exists, we expect that it might recruit clathrin adaptor protein complexes as a means of lysosomal sorting. Here we describe experiments demonstrating that the μ adaptins from AP-1 and AP-3 are involved in U21-mediated trafficking of class I molecules to lysosomes. These experiments support the idea that a cellular protein(s is necessary for U21-mediated lysosomal sorting of class I molecules. We also examine the impact of transient versus chronic knockdown of these adaptor protein complexes, and show that the few remaining μ subunits in the cells are eventually able to reroute class I molecules to lysosomes.

  18. Matrilin-2, an extracellular adaptor protein, is needed for the regeneration of muscle, nerve and other tissues

    va Korpos; Ferenc Dek; Ibolya Kiss

    2015-01-01

    The extracellular matrix (ECM) performs essential functions in the differentiation, maintenance and remodeling of tissues during development and regeneration, and it undergoes dynamic chang-es during remodeling concomitant to alterations in the cell-ECM interactions. Here we discuss recent data addressing the critical role of the widely expressed ECM protein, matrilin-2 (Matn2) in the timely onset of differentiation and regeneration processes in myogenic, neural and other tissues and in tumorigenesis. As a multiadhesion adaptor protein, it interacts with other ECM proteins and integrins. Matn2 promotes neurite outgrowth, Schwann cell migration, neuromuscular junc-tion formation, skeletal muscle and liver regeneration and skin wound healing. Matn2 deposition by myoblasts is crucial for the timely induction of the global switch toward terminal myogenic differentiation during muscle regeneration by affecting transforming growth factor beta/bone morphogenetic protein 7/Smad and other signal transduction pathways. Depending on the type of tissue and the pathomechanism, Matn2 can also promote or suppress tumor growth.

  19. A Cyclic di-GMP-binding Adaptor Protein Interacts with Histidine Kinase to Regulate Two-component Signaling.

    Xu, Linghui; Venkataramani, Prabhadevi; Ding, Yichen; Liu, Yang; Deng, Yinyue; Yong, Grace Lisi; Xin, Lingyi; Ye, Ruijuan; Zhang, Lianhui; Yang, Liang; Liang, Zhao-Xun

    2016-07-29

    The bacterial messenger cyclic di-GMP (c-di-GMP) binds to a diverse range of effectors to exert its biological effect. Despite the fact that free-standing PilZ proteins are by far the most prevalent c-di-GMP effectors known to date, their physiological function and mechanism of action remain largely unknown. Here we report that the free-standing PilZ protein PA2799 from the opportunistic pathogen Pseudomonas aeruginosa interacts directly with the hybrid histidine kinase SagS. We show that PA2799 (named as HapZ: histidine kinase associated PilZ) binds directly to the phosphoreceiver (REC) domain of SagS, and that the SagS-HapZ interaction is further enhanced at elevated c-di-GMP concentration. We demonstrate that binding of HapZ to SagS inhibits the phosphotransfer between SagS and the downstream protein HptB in a c-di-GMP-dependent manner. In accordance with the role of SagS as a motile-sessile switch and biofilm growth factor, we show that HapZ impacts surface attachment and biofilm formation most likely by regulating the expression of a large number of genes. The observations suggest a previously unknown mechanism whereby c-di-GMP mediates two-component signaling through a PilZ adaptor protein. PMID:27231351

  20. The cytoskeleton adaptor protein ankyrin-1 is upregulated by p53 following DNA damage and alters cell migration.

    Hall, A E; Lu, W-T; Godfrey, J D; Antonov, A V; Paicu, C; Moxon, S; Dalmay, T; Wilczynska, A; Muller, P A J; Bushell, M

    2016-01-01

    The integrity of the genome is maintained by a host of surveillance and repair mechanisms that are pivotal for cellular function. The tumour suppressor protein p53 is a major component of the DNA damage response pathway and plays a vital role in the maintenance of cell-cycle checkpoints. Here we show that a microRNA, miR-486, and its host gene ankyrin-1 (ANK1) are induced by p53 following DNA damage. Strikingly, the cytoskeleton adaptor protein ankyrin-1 was induced over 80-fold following DNA damage. ANK1 is upregulated in response to a variety of DNA damage agents in a range of cell types. We demonstrate that miR-486-5p is involved in controlling G1/S transition following DNA damage, whereas the induction of the ankyrin-1 protein alters the structure of the actin cytoskeleton and sustains limited cell migration during DNA damage. Importantly, we found that higher ANK1 expression correlates with decreased survival in cancer patients. Thus, these observations highlight ANK1 as an important effector downstream of the p53 pathway. PMID:27054339

  1. Syk Kinase-Coupled C-type Lectin Receptors Engage Protein Kinase C-δ to Elicit Card9 Adaptor-Mediated Innate Immunity

    Strasser, Dominikus; Neumann, Konstantin; Bergmann, Hanna; Marakalala, Mohlopheni J.; Guler, Reto; Rojowska, Anna; Hopfner, Karl-Peter; Brombacher, Frank; Urlaub, Henning; Baier, Gottfried; Brown, Gordon D.; Leitges, Michael; Ruland, Jürgen

    2012-01-01

    Summary C-type lectin receptors (CLRs) that couple with the kinase Syk are major pattern recognition receptors for the activation of innate immunity and host defense. CLRs recognize fungi and other forms of microbial or sterile danger, and they induce inflammatory responses through the adaptor protein Card9. The mechanisms relaying CLR proximal signals to the core Card9 module are unknown. Here we demonstrated that protein kinase C-δ (PKCδ) was activated upon Dectin-1-Syk signaling, mediated ...

  2. An Inducible System for Rapid Degradation of Specific Cellular Proteins Using Proteasome Adaptors

    Wilmington, Shameika R.; Matouschek, Andreas

    2016-01-01

    A common way to study protein function is to deplete the protein of interest from cells and observe the response. Traditional methods involve disrupting gene expression but these techniques are only effective against newly synthesized proteins and leave previously existing and stable proteins untouched. Here, we introduce a technique that induces the rapid degradation of specific proteins in mammalian cells by shuttling the proteins to the proteasome for degradation in a ubiquitin-independent manner. We present two implementations of the system in human culture cells that can be used individually to control protein concentration. Our study presents a simple, robust, and flexible technology platform for manipulating intracellular protein levels. PMID:27043013

  3. A transgenic Drosophila model demonstrates that the Helicobacter pylori CagA protein functions as a eukaryotic Gab adaptor.

    Crystal M Botham

    2008-05-01

    Full Text Available Infection with the human gastric pathogen Helicobacter pylori is associated with a spectrum of diseases including gastritis, peptic ulcers, gastric adenocarcinoma, and gastric mucosa-associated lymphoid tissue lymphoma. The cytotoxin-associated gene A (CagA protein of H. pylori, which is translocated into host cells via a type IV secretion system, is a major risk factor for disease development. Experiments in gastric tissue culture cells have shown that once translocated, CagA activates the phosphatase SHP-2, which is a component of receptor tyrosine kinase (RTK pathways whose over-activation is associated with cancer formation. Based on CagA's ability to activate SHP-2, it has been proposed that CagA functions as a prokaryotic mimic of the eukaryotic Grb2-associated binder (Gab adaptor protein, which normally activates SHP-2. We have developed a transgenic Drosophila model to test this hypothesis by investigating whether CagA can function in a well-characterized Gab-dependent process: the specification of photoreceptors cells in the Drosophila eye. We demonstrate that CagA expression is sufficient to rescue photoreceptor development in the absence of the Drosophila Gab homologue, Daughter of Sevenless (DOS. Furthermore, CagA's ability to promote photoreceptor development requires the SHP-2 phosphatase Corkscrew (CSW. These results provide the first demonstration that CagA functions as a Gab protein within the tissue of an organism and provide insight into CagA's oncogenic potential. Since many translocated bacterial proteins target highly conserved eukaryotic cellular processes, such as the RTK signaling pathway, the transgenic Drosophila model should be of general use for testing the in vivo function of bacterial effector proteins and for identifying the host genes through which they function.

  4. Early Loss of Telomerase Action in Yeast Creates a Dependence on the DNA Damage Response Adaptor Proteins.

    Jay, Kyle A; Smith, Dana L; Blackburn, Elizabeth H

    2016-07-15

    Telomeres cap the ends of chromosomes, protecting them from degradation and inappropriate DNA repair processes that can lead to genomic instability. A short telomere elicits increased telomerase action on itself that replenishes telomere length, thereby stabilizing the telomere. In the prolonged absence of telomerase activity in dividing cells, telomeres eventually become critically short, inducing a permanent cell cycle arrest (senescence). We recently showed that even early after telomerase inactivation (ETI), yeast cells have accelerated mother cell aging and mildly perturbed cell cycles. Here, we show that the complete disruption of DNA damage response (DDR) adaptor proteins in ETI cells causes severe growth defects. This synthetic-lethality phenotype was as pronounced as that caused by extensive DNA damage in wild-type cells but showed genetic dependencies distinct from such damage and was completely alleviated by SML1 deletion, which increases deoxynucleoside triphosphate (dNTP) pools. Our results indicated that these deleterious effects in ETI cells cannot be accounted for solely by the slow erosion of telomeres due to incomplete replication that leads to senescence. We propose that normally occurring telomeric DNA replication stress is resolved by telomerase activity and the DDR in two parallel pathways and that deletion of Sml1 prevents this stress. PMID:27161319

  5. PRR7 Is a transmembrane adaptor protein expressed in activated T cells involved in regulation of T cell receptor signaling and apoptosis

    Hrdinka, Matouš; Dráber, Peter; Štěpánek, Ondřej; Ormsby, Tereza; Otáhal, Pavel; Angelisová, Pavla; Brdička, Tomáš; Pačes, Jan; Hořejší, Václav; Drbal, Karel

    2011-01-01

    Roč. 286, č. 22 (2011), s. 19617-19629. ISSN 0021-9258 R&D Projects: GA MŠk 1M0506 Grant ostatní: GAČR(CZ) MEM/09/E011 Institutional research plan: CEZ:AV0Z50520514 Keywords : PRR7 * transmembrane adaptor protein * apoptosis Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.773, year: 2011

  6. Protein Interaction Profiling of the p97 Adaptor UBXD1 Points to a Role for the Complex in Modulating ERGIC-53 Trafficking*

    Haines, Dale S.; Lee, J. Eugene; Beauparlant, Stephen L.; Kyle, Dane B.; den Besten, Willem; Sweredoski, Michael J.; Graham, Robert L. J.; Hess, Sonja; Deshaies, Raymond J

    2012-01-01

    UBXD1 is a member of the poorly understood subfamily of p97 adaptors that do not harbor a ubiquitin association domain or bind ubiquitin-modified proteins. Of clinical importance, p97 mutants found in familial neurodegenerative conditions Inclusion Body Myopathy Paget's disease of the bone and/or Frontotemporal Dementia and Amyotrophic Lateral Sclerosis are defective at interacting with UBXD1, indicating that functions regulated by a p97-UBXD1 complex are altered in these diseases. We have pe...

  7. A combinatorial F box protein directed pathway controls TRAF adaptor stability to regulate inflammation

    Chen, Bill B; Coon, Tiffany A.; Glasser, Jennifer R; McVerry, Bryan J.; Zhao, Jing; Zhao, Yutong; Zou, Chunbin; Ellis, Bryon; Sciurba, Frank C.; Zhang, Yingze; Mallampalli, Rama K.

    2013-01-01

    Uncontrolled activation of tumor necrosis factor receptor-associated factor (TRAF) proteins may result in profound tissue injury by linking surface signals to cytokine release. Here we show that a ubiquitin E3 ligase component, Fbxo3, potently stimulates cytokine secretion from human inflammatory cells by destabilizing a sentinel TRAF inhibitor, Fbxl2. Fbxo3 and TRAF protein in circulation positively correlated with cytokine responses in septic subjects and we furthermore identified a hypofun...

  8. CD2v interacts with Adaptor Protein AP-1 during African swine fever infection

    Pérez-Núñez, Daniel; García-Urdiales, Eduardo; Martínez Bonet, Marta; Nogal París, María Luisa; Barroso, Susana; Revilla, Yolanda; Madrid, Ricardo

    2015-01-01

    African swine fever virus (ASFV) CD2v protein is believed to be involved in virulence enhancement, viral hemadsorption, and pathogenesis, although the molecular mechanisms of the function of this viral protein are still not fully understood. Here we describe that CD2v localized around viral factories during ASFV infection, suggesting a role in the generation and/or dynamics of these viral structures and hence in disturbing cellular traffic. We show that CD2v targeted the regulatory trans-Golg...

  9. Enigma interacts with adaptor protein with PH and SH2 domains to control insulin-induced actin cytoskeleton remodeling and glucose transporter 4 translocation

    Barres, Romain; Grémeaux, Thierry; Gual, Philippe;

    2006-01-01

    and Glut 4 translocation without alterations in proximal insulin signaling. This inhibitory effect was prevented with the deletion of the LIM domains of Enigma. Using time-lapse fluorescent microscopy of green fluorescent protein-actin, we demonstrated that the overexpression of Enigma altered insulin......APS (adaptor protein with PH and SH2 domains) initiates a phosphatidylinositol 3-kinase-independent pathway involved in insulin-stimulated glucose transport. We recently identified Enigma, a PDZ and LIM domain-containing protein, as a partner of APS and showed that APS-Enigma complex plays...

  10. A combinatorial F box protein directed pathway controls TRAF adaptor stability to regulate inflammation.

    Chen, Bill B; Coon, Tiffany A; Glasser, Jennifer R; McVerry, Bryan J; Zhao, Jing; Zhao, Yutong; Zou, Chunbin; Ellis, Bryon; Sciurba, Frank C; Zhang, Yingze; Mallampalli, Rama K

    2013-05-01

    Uncontrolled activation of tumor necrosis factor receptor-associated factor (TRAF) proteins may result in profound tissue injury by linking surface signals to cytokine release. Here we show that a ubiquitin E3 ligase component, Fbxo3, potently stimulates cytokine secretion from human inflammatory cells by destabilizing a sentinel TRAF inhibitor, Fbxl2. Fbxo3 and TRAF protein in circulation positively correlated with cytokine responses in subjects with sepsis, and we identified a polymorphism in human Fbxo3, with one variant being hypofunctional. A small-molecule inhibitor targeting Fbxo3 was sufficient to lessen severity of cytokine-driven inflammation in several mouse disease models. These studies identified a pathway of innate immunity that may be useful to detect subjects with altered immune responses during critical illness or provide a basis for therapeutic intervention targeting TRAF protein abundance. PMID:23542741

  11. Multiple upstream signals converge on the adaptor protein Mst50 in Magnaporthe grisea

    G. Park; Xue, C.; X. Zhao; Kim, Y.; Orbach, M.; Xu, J.R.

    2006-01-01

    Rice blast fungus ( Magnaporthe grisea) forms a highly specialized infection structure for plant penetration, the appressorium, the formation and growth of which are regulated by the Mst11- Mst7- Pmk1 mitogen- activated protein kinase cascade. We characterized the MST50 gene that directly interacts with both MST11 and MST7. Similar to the mst11 mutant, the mst50 mutant was defective in appressorium formation, sens...

  12. The adaptor protein alpha-syntrophin regulates adipocyte lipid droplet growth.

    Eisinger, Kristina; Rein-Fischboeck, Lisa; Pohl, Rebekka; Meier, Elisabeth M; Krautbauer, Sabrina; Buechler, Christa

    2016-07-01

    The scaffold protein alpha-syntrophin (SNTA) regulates lipolysis indicating a role in lipid homeostasis. Adipocytes are the main lipid storage cells in the body, and here, the function of SNTA has been analyzed in 3T3-L1 cells. SNTA is expressed in preadipocytes and is induced early during adipogenesis. Knock-down of SNTA in preadipocytes increases their proliferation. Proteins which are induced during adipogenesis like adiponectin and caveolin-1, and the inflammatory cytokine IL-6 are at normal levels in the mature cells differentiated from preadipocytes with low SNTA. This suggests that SNTA does neither affect differentiation nor inflammation. Expression of proteins with a role in cholesterol and triglyceride homeostasis is unchanged. Consequently, basal and epinephrine induced lipolysis as well as insulin stimulated phosphorylation of Akt and ERK1/2 are normal. Importantly, adipocytes with low SNTA form smaller lipid droplets and store less triglycerides. Stearoyl-CoA reductase and MnSOD are reduced upon SNTA knock-down but do not contribute to lower lipid levels. Oleate uptake is even increased in cells with SNTA knock-down. In summary, current data show that SNTA is involved in the expansion of lipid droplets independent of adipogenesis. Enhanced preadipocyte proliferation and capacity to store surplus fatty acids may protect adipocytes with low SNTA from lipotoxicity in obesity. PMID:27242274

  13. Mutations in the Gene Encoding the Sigma 2 Subunit of the Adaptor Protein 1 Complex, AP1S2, Cause X-Linked Mental Retardation

    Tarpey, Patrick S. ; Stevens, Claire ; Teague, Jon ; Edkins, Sarah ; O’Meara, Sarah ; Avis, Tim ; Barthorpe, Syd ; Buck, Gemma ; Butler, Adam ; Cole, Jennifer ; Dicks, Ed ; Gray, Kristian ; Halliday, Kelly ; Harrison, Rachel ; Hills, Katy 

    2006-01-01

    In a systematic sequencing screen of the coding exons of the X chromosome in 250 families with X-linked mental retardation (XLMR), we identified two nonsense mutations and one consensus splice-site mutation in the AP1S2 gene on Xp22 in three families. Affected individuals in these families showed mild-to-profound mental retardation. Other features included hypotonia early in life and delay in walking. AP1S2 encodes an adaptin protein that constitutes part of the adaptor protein complex found ...

  14. The adaptor protein DCAF7 mediates the interaction of the adenovirus E1A oncoprotein with the protein kinases DYRK1A and HIPK2.

    Glenewinkel, Florian; Cohen, Michael J; King, Cason R; Kaspar, Sophie; Bamberg-Lemper, Simone; Mymryk, Joe S; Becker, Walter

    2016-01-01

    DYRK1A is a constitutively active protein kinase that has a critical role in growth and development which functions by regulating cell proliferation, differentiation and survival. DCAF7 (also termed WDR68 or HAN11) is a cellular binding partner of DYRK1A and also regulates signalling by the protein kinase HIPK2. DCAF7 is an evolutionarily conserved protein with a single WD40 repeat domain and has no catalytic activity. We have defined a DCAF7 binding motif of 12 amino acids in the N-terminal domain of class 1 DYRKs that is functionally conserved in DYRK1 orthologs from Xenopus, Danio rerio and the slime mold Dictyostelium discoideum. A similar sequence was essential for DCAF7 binding to HIPK2, whereas the closely related HIPK1 family member did not bind DCAF7. Immunoprecipitation and pulldown experiments identified DCAF7 as an adaptor for the association of the adenovirus E1A protein with DYRK1A and HIPK2. Furthermore, DCAF7 was required for the hyperphosphorylation of E1A in DYRK1A or HIPK2 overexpressing cells. Our results characterize DCAF7 as a substrate recruiting subunit of DYRK1A and HIPK2 and suggest that it is required for the negative effect of DYRK1A on E1A-induced oncogenic transformation. PMID:27307198

  15. Adaptor protein containing PH domain, PTB domain and leucine zipper (APPL1) regulates the protein level of EGFR by modulating its trafficking

    Highlights: ► APPL1 regulates the protein level of EGFR in response to EGF stimulation. ► Depletion of APPL1 accelerates the movement of EGF/EGFR from the cell surface to the perinuclear region in response to EGF. ► Knockdown of APPL1 enhances the activity of Rab5. -- Abstract: The EGFR-mediated signaling pathway regulates multiple biological processes such as cell proliferation, survival and differentiation. Previously APPL1 (adaptor protein containing PH domain, PTB domain and leucine zipper 1) has been reported to function as a downstream effector of EGF-initiated signaling. Here we demonstrate that APPL1 regulates EGFR protein levels in response to EGF stimulation. Overexpression of APPL1 enhances EGFR stabilization while APPL1 depletion by siRNA reduces EGFR protein levels. APPL1 depletion accelerates EGFR internalization and movement of EGF/EGFR from cell surface to the perinuclear region in response to EGF treatment. Conversely, overexpression of APPL1 decelerates EGFR internalization and translocation of EGF/EGFR to the perinuclear region. Furthermore, APPL1 depletion enhances the activity of Rab5 which is involved in internalization and trafficking of EGFR and inhibition of Rab5 in APPL1-depleted cells restored EGFR levels. Consistently, APPL1 depletion reduced activation of Akt, the downstream signaling effector of EGFR and this is restored by inhibition of Rab5. These findings suggest that APPL1 is required for EGFR signaling by regulation of EGFR stabilities through inhibition of Rab5.

  16. Phosphorylation of APP-CTF-AICD domains and interaction with adaptor proteins: signal transduction and/or transcriptional role--relevance for Alzheimer pathology.

    Schettini, Gennaro; Govoni, Stefano; Racchi, Marco; Rodriguez, Guido

    2010-12-01

    In recent decades, the study of the amyloid precursor protein (APP) and of its proteolytic products carboxy terminal fragment (CTF), APP intracellular C-terminal domain (AICD) and amyloid beta has been mostly focussed on the role of APP as a producer of the toxic amyloid beta peptide. Here, we reconsider the role of APP suggesting, in a provocative way, the protein as a central player in a putative signalling pathway. We highlight the presence in the cytosolic tail of APP of the YENPTY motif which is typical of tyrosine kinase receptors, the phosphorylation of the tyrosine, serine and threonine residues, the kinases involved and the interaction with intracellular adaptor proteins. In particular, we examine the interaction with Shc and Grb2 regulators, which through the activation of Ras proteins elicit downstream signalling events such as the MAPK pathway. The review also addresses the interaction of APP, CTFs and AICD with other adaptor proteins and in particular with Fe65 for nuclear transcriptional activity and the importance of phosphorylation for sorting the secretases involved in the amyloidogenic or non-amyloidogenic pathways. We provide a novel perspective on Alzheimer's disease pathogenesis, focussing on the perturbation of the physiological activities of APP-CTFs and AICD as an alternative perspective from that which normally focuses on the accumulation of neurotoxic proteolytic fragments. PMID:21039524

  17. Mutations in the gene encoding the Sigma 2 subunit of the adaptor protein 1 complex, AP1S2, cause X-linked mental retardation.

    Tarpey, Patrick S; Stevens, Claire; Teague, Jon; Edkins, Sarah; O'Meara, Sarah; Avis, Tim; Barthorpe, Syd; Buck, Gemma; Butler, Adam; Cole, Jennifer; Dicks, Ed; Gray, Kristian; Halliday, Kelly; Harrison, Rachel; Hills, Katy; Hinton, Jonathon; Jones, David; Menzies, Andrew; Mironenko, Tatiana; Perry, Janet; Raine, Keiran; Richardson, David; Shepherd, Rebecca; Small, Alexandra; Tofts, Calli; Varian, Jennifer; West, Sofie; Widaa, Sara; Yates, Andy; Catford, Rachael; Butler, Julia; Mallya, Uma; Moon, Jenny; Luo, Ying; Dorkins, Huw; Thompson, Deborah; Easton, Douglas F; Wooster, Richard; Bobrow, Martin; Carpenter, Nancy; Simensen, Richard J; Schwartz, Charles E; Stevenson, Roger E; Turner, Gillian; Partington, Michael; Gecz, Jozef; Stratton, Michael R; Futreal, P Andrew; Raymond, F Lucy

    2006-12-01

    In a systematic sequencing screen of the coding exons of the X chromosome in 250 families with X-linked mental retardation (XLMR), we identified two nonsense mutations and one consensus splice-site mutation in the AP1S2 gene on Xp22 in three families. Affected individuals in these families showed mild-to-profound mental retardation. Other features included hypotonia early in life and delay in walking. AP1S2 encodes an adaptin protein that constitutes part of the adaptor protein complex found at the cytoplasmic face of coated vesicles located at the Golgi complex. The complex mediates the recruitment of clathrin to the vesicle membrane. Aberrant endocytic processing through disruption of adaptor protein complexes is likely to result from the AP1S2 mutations identified in the three XLMR-affected families, and such defects may plausibly cause abnormal synaptic development and function. AP1S2 is the first reported XLMR gene that encodes a protein directly involved in the assembly of endocytic vesicles. PMID:17186471

  18. Involvement of β3A Subunit of Adaptor Protein-3 in Intracellular Trafficking of Receptor-like Protein Tyrosine Phosphatase PCP-2

    Hui DONG; Hong YUAN; Weirong JIN; Yan SHEN; Xiaojing XU; Hongyang WANG

    2007-01-01

    PCP-2 is a human receptor-like protein tyrosine phosphatase and a member of the MAM domain family cloned in human pancreatic adenocarcinoma cells. Previous studies showed that PCP-2 directly interacted with β-catenin through the juxtamembrane domain, dephosphorylated β-catenin and played an important role in the regulation of cell adhesion. Recent study showed that PCP-2 was also involved in the repression of β-catenin-induced transcriptional activity. Here we describe the interactions of PCP-2 with the β3A subunit of adaptor protein (AP)-3 and sorting nexin (SNX) 3. These protein complexes were detected using the yeast two-hybrid assay with the juxtamembrane and membrane-proximal catalytic domain of PCP-2 as "bait". Both AP-3 and SNX3 are molecules involved in intracellular trafficking of membrane receptors. The association between the β3A subunit of AP-3 and PCP-2 was further confirmed in mammalian cells. Our results suggested a possible mechanism of intracellular trafficking of PCP-2 mediated by AP-3 and SNX3 which might participate in the regulation of PCP-2 functions.

  19. Impaired Lysosomal Integral Membrane Protein 2-dependent Peroxiredoxin 6 Delivery to Lamellar Bodies Accounts for Altered Alveolar Phospholipid Content in Adaptor Protein-3-deficient pearl Mice.

    Kook, Seunghyi; Wang, Ping; Young, Lisa R; Schwake, Michael; Saftig, Paul; Weng, Xialian; Meng, Ying; Neculai, Dante; Marks, Michael S; Gonzales, Linda; Beers, Michael F; Guttentag, Susan

    2016-04-15

    The Hermansky Pudlak syndromes (HPS) constitute a family of disorders characterized by oculocutaneous albinism and bleeding diathesis, often associated with lethal lung fibrosis. HPS results from mutations in genes of membrane trafficking complexes that facilitate delivery of cargo to lysosome-related organelles. Among the affected lysosome-related organelles are lamellar bodies (LB) within alveolar type 2 cells (AT2) in which surfactant components are assembled, modified, and stored. AT2 from HPS patients and mouse models of HPS exhibit enlarged LB with increased phospholipid content, but the mechanism underlying these defects is unknown. We now show that AT2 in the pearl mouse model of HPS type 2 lacking the adaptor protein 3 complex (AP-3) fails to accumulate the soluble enzyme peroxiredoxin 6 (PRDX6) in LB. This defect reflects impaired AP-3-dependent trafficking of PRDX6 to LB, because pearl mouse AT2 cells harbor a normal total PRDX6 content. AP-3-dependent targeting of PRDX6 to LB requires the transmembrane protein LIMP-2/SCARB2, a known AP-3-dependent cargo protein that functions as a carrier for lysosomal proteins in other cell types. Depletion of LB PRDX6 in AP-3- or LIMP-2/SCARB2-deficient mice correlates with phospholipid accumulation in lamellar bodies and with defective intraluminal degradation of LB disaturated phosphatidylcholine. Furthermore, AP-3-dependent LB targeting is facilitated by protein/protein interaction between LIMP-2/SCARB2 and PRDX6 in vitro and in vivo Our data provide the first evidence for an AP-3-dependent cargo protein required for the maturation of LB in AT2 and suggest that the loss of PRDX6 activity contributes to the pathogenic changes in LB phospholipid homeostasis found HPS2 patients. PMID:26907692

  20. Expression of the neuronal adaptor protein X11alpha protects against memory dysfunction in a transgenic mouse model of Alzheimer's disease.

    Mitchell, Jacqueline C

    2010-01-01

    X11alpha is a neuronal-specific adaptor protein that binds to the amyloid-beta protein precursor (AbetaPP). Overexpression of X11alpha reduces Abeta production but whether X11alpha also protects against Abeta-related memory dysfunction is not known. To test this possibility, we crossed X11alpha transgenic mice with AbetaPP-Tg2576 mice. AbetaPP-Tg2576 mice produce high levels of brain Abeta and develop age-related defects in memory function that correlate with increasing Abeta load. Overexpression of X11alpha alone had no detectable adverse effect upon behavior. However, X11alpha reduced brain Abeta levels and corrected spatial reference memory defects in aged X11alpha\\/AbetaPP double transgenics. Thus, X11alpha may be a therapeutic target for Alzheimer\\'s disease.

  1. A novel method for evaluating microglial activation using ionized calcium-binding adaptor protein-1 staining: cell body to cell size ratio

    Iris Bertha Hovens

    2014-09-01

    Full Text Available Aim: The aim was to validate a newly developed methodology of semi-automatic image analysis to analyze microglial morphology as marker for microglial activation in ionized calcium-binding adaptor protein-1 (IBA-1 stained brain sections. Methods: The novel method was compared to currently used analysis methods, visual characterization of activation stage and optical density measurement, in brain sections of young and aged rats that had undergone surgery or remained naοve. Results: The cell body to cell size ratio of microglia was strongly correlated to the visual characterization activation stage. In addition, we observed specific surgery and age-related changes in cell body size, size of the dendritic processes and cell body to cell size ratio. Conclusion: The novel analysis method provides a sensitive marker for microglial activation in the rat brain, which is quick and easy to perform and provides additional information about microglial morphology.

  2. Spectral affinity in protein networks

    Teng Shang-Hua; Voevodski Konstantin; Xia Yu

    2009-01-01

    Abstract Background Protein-protein interaction (PPI) networks enable us to better understand the functional organization of the proteome. We can learn a lot about a particular protein by querying its neighborhood in a PPI network to find proteins with similar function. A spectral approach that considers random walks between nodes of interest is particularly useful in evaluating closeness in PPI networks. Spectral measures of closeness are more robust to noise in the data and are more precise...

  3. Skb5, an SH3 adaptor protein, regulates Pmk1 MAPK signaling by controlling the intracellular localization of the MAPKKK Mkh1.

    Kanda, Yuki; Satoh, Ryosuke; Matsumoto, Saki; Ikeda, Chisato; Inutsuka, Natsumi; Hagihara, Kanako; Matzno, Sumio; Tsujimoto, Sho; Kita, Ayako; Sugiura, Reiko

    2016-08-15

    The mitogen-activated protein kinase (MAPK) cascade is a highly conserved signaling module composed of MAPK kinase kinases (MAPKKKs), MAPK kinases (MAPKK) and MAPKs. The MAPKKK Mkh1 is an initiating kinase in Pmk1 MAPK signaling, which regulates cell integrity in fission yeast (Schizosaccharomyces pombe). Our genetic screen for regulators of Pmk1 signaling identified Shk1 kinase binding protein 5 (Skb5), an SH3-domain-containing adaptor protein. Here, we show that Skb5 serves as an inhibitor of Pmk1 MAPK signaling activation by downregulating Mkh1 localization to cell tips through its interaction with the SH3 domain. Consistent with this, the Mkh1(3PA) mutant protein, with impaired Skb5 binding, remained in the cell tips, even when Skb5 was overproduced. Intriguingly, Skb5 needs Mkh1 to localize to the growing ends as Mkh1 deletion and disruption of Mkh1 binding impairs Skb5 localization. Deletion of Pck2, an upstream activator of Mkh1, impaired the cell tip localization of Mkh1 and Skb5 as well as the Mkh1-Skb5 interaction. Interestingly, both Pck2 and Mkh1 localized to the cell tips at the G1/S phase, which coincided with Pmk1 MAPK activation. Taken together, Mkh1 localization to cell tips is important for transmitting upstream signaling to Pmk1, and Skb5 spatially regulates this process. PMID:27451356

  4. Human kidney anion exchanger 1 interacts with adaptor-related protein complex 1 {mu}1A (AP-1 mu1A)

    Sawasdee, Nunghathai; Junking, Mutita [Division of Medical Molecular Biology and BIOTEC-Medical Biotechnology Unit, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Ngaojanlar, Piengpaga [Division of Medical Molecular Biology and BIOTEC-Medical Biotechnology Unit, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Department of Immunology and Graduate Program in Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Sukomon, Nattakan; Ungsupravate, Duangporn [Division of Medical Molecular Biology and BIOTEC-Medical Biotechnology Unit, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Limjindaporn, Thawornchai [Division of Medical Molecular Biology and BIOTEC-Medical Biotechnology Unit, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Department of Anatomy, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Akkarapatumwong, Varaporn [Institute of Molecular Biosciences, Mahidol University at Salaya Campus, Nakorn Pathom 73170 (Thailand); Noisakran, Sansanee [Division of Medical Molecular Biology and BIOTEC-Medical Biotechnology Unit, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Yenchitsomanus, Pa-thai, E-mail: grpye@mahidol.ac.th [Division of Medical Molecular Biology and BIOTEC-Medical Biotechnology Unit, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand)

    2010-10-08

    Research highlights: {yields} Trafficking defect of kAE1 is a cause of dRTA but trafficking pathway of kAE1 has not been clearly described. {yields} Adaptor-related protein complex 1 {mu}1A (AP-1 mu1A) was firstly reported to interact with kAE1. {yields} The interacting site for AP-1 mu1A on Ct-kAE1 was found to be Y904DEV907, a subset of YXXO motif. {yields} AP-1 mu1A knockdown showed a marked reduction of kAE1 on the cell membrane and its accumulation in endoplasmic reticulum. {yields} AP-1 mu1A has a critical role in kAE1 trafficking to the plasma membrane. -- Abstract: Kidney anion exchanger 1 (kAE1) mediates chloride (Cl{sup -}) and bicarbonate (HCO{sub 3}{sup -}) exchange at the basolateral membrane of kidney {alpha}-intercalated cells. Impaired trafficking of kAE1 leads to defect of the Cl{sup -}/HCO{sub 3}{sup -} exchange at the basolateral membrane and failure of proton (H{sup +}) secretion at the apical membrane, causing a kidney disease - distal renal tubular acidosis (dRTA). To gain a better insight into kAE1 trafficking, we searched for proteins physically interacting with the C-terminal region of kAE1 (Ct-kAE1), which contains motifs crucial for intracellular trafficking, by a yeast two-hybrid (Y2H) system. An adaptor-related protein complex 1 {mu}1A (AP-1 mu1A) subunit was found to interact with Ct-kAE1. The interaction between either Ct-kAE1 or full-length kAE1 and AP-1 mu1A were confirmed in human embryonic kidney (HEK) 293T by co-immunoprecipitation, affinity co-purification, co-localization, yellow fluorescent protein (YFP)-based protein fragment complementation assay (PCA) and GST pull-down assay. The interacting site for AP-1 mu1A on Ct-kAE1 was found to be Y904DEV907, a subset of YXXO motif. Interestingly, suppression of endogenous AP-1 mu1A in HEK 293T by small interfering RNA (siRNA) decreased membrane localization of kAE1 and increased its intracellular accumulation, suggesting for the first time that AP-1 mu1A is involved in the kAE1

  5. Human kidney anion exchanger 1 interacts with adaptor-related protein complex 1 μ1A (AP-1 mu1A)

    Research highlights: → Trafficking defect of kAE1 is a cause of dRTA but trafficking pathway of kAE1 has not been clearly described. → Adaptor-related protein complex 1 μ1A (AP-1 mu1A) was firstly reported to interact with kAE1. → The interacting site for AP-1 mu1A on Ct-kAE1 was found to be Y904DEV907, a subset of YXXO motif. → AP-1 mu1A knockdown showed a marked reduction of kAE1 on the cell membrane and its accumulation in endoplasmic reticulum. → AP-1 mu1A has a critical role in kAE1 trafficking to the plasma membrane. -- Abstract: Kidney anion exchanger 1 (kAE1) mediates chloride (Cl-) and bicarbonate (HCO3-) exchange at the basolateral membrane of kidney α-intercalated cells. Impaired trafficking of kAE1 leads to defect of the Cl-/HCO3- exchange at the basolateral membrane and failure of proton (H+) secretion at the apical membrane, causing a kidney disease - distal renal tubular acidosis (dRTA). To gain a better insight into kAE1 trafficking, we searched for proteins physically interacting with the C-terminal region of kAE1 (Ct-kAE1), which contains motifs crucial for intracellular trafficking, by a yeast two-hybrid (Y2H) system. An adaptor-related protein complex 1 μ1A (AP-1 mu1A) subunit was found to interact with Ct-kAE1. The interaction between either Ct-kAE1 or full-length kAE1 and AP-1 mu1A were confirmed in human embryonic kidney (HEK) 293T by co-immunoprecipitation, affinity co-purification, co-localization, yellow fluorescent protein (YFP)-based protein fragment complementation assay (PCA) and GST pull-down assay. The interacting site for AP-1 mu1A on Ct-kAE1 was found to be Y904DEV907, a subset of YXXO motif. Interestingly, suppression of endogenous AP-1 mu1A in HEK 293T by small interfering RNA (siRNA) decreased membrane localization of kAE1 and increased its intracellular accumulation, suggesting for the first time that AP-1 mu1A is involved in the kAE1 trafficking of kidney α-intercalated cells.

  6. Evidence against roles for phorbol binding protein Munc13-1, ADAM adaptor Eve-1, or vesicle trafficking phosphoproteins Munc18 or NSF as phospho-state-sensitive modulators of phorbol/PKC-activated Alzheimer APP ectodomain shedding

    Lovestone Simon

    2007-12-01

    Full Text Available Abstract Background Shedding of the Alzheimer amyloid precursor protein (APP ectodomain can be accelerated by phorbol esters, compounds that act via protein kinase C (PKC or through unconventional phorbol-binding proteins such as Munc13-1. We have previously demonstrated that application of phorbol esters or purified PKC potentiates budding of APP-bearing secretory vesicles at the trans-Golgi network (TGN and toward the plasma membrane where APP becomes a substrate for enzymes responsible for shedding, known collectively as α-secretase(s. However, molecular identification of the presumptive "phospho-state-sensitive modulators of ectodomain shedding" (PMES responsible for regulated shedding has been challenging. Here, we examined the effects on APP ectodomain shedding of four phorbol-sensitive proteins involved in regulation of vesicular membrane trafficking of APP: Munc13-1, Munc18, NSF, and Eve-1. Results Overexpression of either phorbol-sensitive wildtype Munc13-1 or phorbol-insensitive Munc13-1 H567K resulted in increased basal APP ectodomain shedding. However, in contrast to the report of Roßner et al (2004, phorbol ester-dependent APP ectodomain shedding from cells overexpressing APP and Munc13-1 wildtype was indistinguishable from that observed following application of phorbol to cells overexpressing APP and Munc13-1 H567K mutant. This pattern of similar effects on basal and stimulated APP shedding was also observed for Munc18 and NSF. Eve-1, an ADAM adaptor protein reported to be essential for PKC-regulated shedding of pro-EGF, was found to play no obvious role in regulated shedding of sAPPα. Conclusion Our results indicate that, in the HEK293 system, Munc13-1, Munc18, NSF, and EVE-1 fail to meet essential criteria for identity as PMES for APP.

  7. The Ras suppressor Rsu-1 binds to the LIM 5 domain of the adaptor protein PINCH1 and participates in adhesion-related functions

    Rsu-1 is a highly conserved leucine rich repeat (LRR) protein that is expressed ubiquitously in mammalian cells. Rsu-1 was identified based on its ability to inhibit transformation by Ras, and previous studies demonstrated that ectopic expression of Rsu-1 inhibited anchorage-independent growth of Ras-transformed cells and human tumor cell lines. Using GAL4-based yeast two-hybrid screening, the LIM domain protein, PINCH1, was identified as the binding partner of Rsu-1. PINCH1 is an adaptor protein that localizes to focal adhesions and it has been implicated in the regulation of adhesion functions. Subdomain mapping in yeast revealed that Rsu-1 binds to the LIM 5 domain of PINCH1, a region not previously identified as a specific binding domain for any other protein. Additional testing demonstrated that PINCH2, which is highly homologous to PINCH1, except in the LIM 5 domain, does not interact with Rsu-1. Glutathione transferase fusion protein binding studies determined that the LRR region of Rsu-1 interacts with PINCH1. Transient expression studies using epitope-tagged Rsu-1 and PINCH1 revealed that Rsu-1 co-immunoprecipitated with PINCH1 and colocalized with vinculin at sites of focal adhesions in mammalian cells. In addition, endogenous P33 Rsu-1 from 293T cells co-immunoprecipitated with transiently expressed myc-tagged PINCH1. Furthermore, RNAi-induced reduction in Rsu-1 RNA and protein inhibited cell attachment, and while previous studies demonstrated that ectopic expression of Rsu-1 inhibited Jun kinase activation, the depletion of Rsu-1 resulted in activation of Jun and p38 stress kinases. These studies demonstrate that Rsu-1 interacts with PINCH1 in mammalian cells and functions, in part, by altering cell adhesion

  8. Multiple molecular forms of adaptor protein Ruk/CIN85 specifically associate with different subcellular compartments in human breast adenocarcinoma MCF-7 cells.

    Vynnytska-Myronovska, B O; Bobak, Ya P; Pasichnyk, G V; Igumentseva, N I; Samoylenko, A A; Drobot, L B

    2014-01-01

    Ruk/CIN85 is a receptor-proximal 'signalling' adaptor that possesses three SH3 domains, Pro- and Ser-rich regions and C-terminal coiled-coil domain. It employs distinct domains and motifs to act as a transducer platform in intracellular signaling. Based on cDNA analysis, various isoforms of Ruk/CIN85 with different combination of protein-protein interaction domains as well as additional Ruk/CIN85 forms that are the products of post-translational modifications have been demonstrated. Nevertheless, there is no precise information regarding both the subcellular distribution and the role of Ruk/CIN85 multiple molecular forms in cellular responses. Using MCF-7 human breast adenocarcinoma cells and cell fractionation technique, specific association of Ruk/CIN85 molecular forms with different subcellular compartments was demonstrated. Induction of apoptosis of MCF-7 cells by doxorubicin treatment or by serum deprivation resulted in the system changes of Ruk/CIN85 molecular forms intracellular localization as well as their ratio. The data obtained provide a new insight into potential physiological significance of Ruk/CIN85 molecular forms in the regulation of various cellular functions. PMID:25816594

  9. Yeast Ste2 receptors as tools for study of mammalian protein kinases and adaptors involved in receptor trafficking

    2006-01-01

    Background Mammalian receptors that couple to effectors via heterotrimeric G proteins (e.g., beta 2-adrenergic receptors) and receptors with intrinsic tyrosine kinase activity (e.g., insulin and IGF-I receptors) constitute the proximal points of two dominant cell signaling pathways. Receptors coupled to G proteins can be substrates for tyrosine kinases, integrating signals from both pathways. Yeast cells, in contrast, display G protein-coupled receptors (e.g., alpha-factor pheromone receptor ...

  10. Increased abundance of the adaptor protein containing pleckstrin homology domain, phosphotyrosine binding domain and leucine zipper motif (APPL1) in patients with obesity and type 2 diabetes: evidence for altered adiponectin signalling

    Holmes, R.M.; Yi, Z; De Filippis, E.; Berria, R.; S. Shahani; P. Sathyanarayana; Sherman, V.; K. Fujiwara; Meyer, C.; Christ-Roberts, C.; Hwang, H; Finlayson, J.; Dong, L. Q.; Mandarino, L. J.; Bajaj, M.

    2011-01-01

    Aims/hypothesis The adiponectin signalling pathway is largely unknown, but recently the adaptor protein containing pleckstrin homology domain, phosphotyrosine binding domain and leucine zipper motif (APPL1), has been shown to interact directly with adiponectin receptor (ADIPOR)1. APPL1 is present in C2C12 myoblasts and mouse skeletal muscle, but its presence in human skeletal muscle has not been investigated. Methods Samples from type 2 diabetic, and lean and non-diabetic obese participants w...

  11. Spectral affinity in protein networks

    Teng Shang-Hua

    2009-11-01

    Full Text Available Abstract Background Protein-protein interaction (PPI networks enable us to better understand the functional organization of the proteome. We can learn a lot about a particular protein by querying its neighborhood in a PPI network to find proteins with similar function. A spectral approach that considers random walks between nodes of interest is particularly useful in evaluating closeness in PPI networks. Spectral measures of closeness are more robust to noise in the data and are more precise than simpler methods based on edge density and shortest path length. Results We develop a novel affinity measure for pairs of proteins in PPI networks, which uses personalized PageRank, a random walk based method used in context-sensitive search on the Web. Our measure of closeness, which we call PageRank Affinity, is proportional to the number of times the smaller-degree protein is visited in a random walk that restarts at the larger-degree protein. PageRank considers paths of all lengths in a network, therefore PageRank Affinity is a precise measure that is robust to noise in the data. PageRank Affinity is also provably related to cluster co-membership, making it a meaningful measure. In our experiments on protein networks we find that our measure is better at predicting co-complex membership and finding functionally related proteins than other commonly used measures of closeness. Moreover, our experiments indicate that PageRank Affinity is very resilient to noise in the network. In addition, based on our method we build a tool that quickly finds nodes closest to a queried protein in any protein network, and easily scales to much larger biological networks. Conclusion We define a meaningful way to assess the closeness of two proteins in a PPI network, and show that our closeness measure is more biologically significant than other commonly used methods. We also develop a tool, accessible at http://xialab.bu.edu/resources/pnns, that allows the user to

  12. Adaptor protein CRK induces epithelial–mesenchymal transition and metastasis of bladder cancer cells through HGF/c-Met feedback loop

    Matsumoto, Ryuji; Tsuda, Masumi; Wang, Lei; Maishi, Nako; Abe, Takashige; Kimura, Taichi; Tanino, Mishie; Nishihara, Hiroshi; Hida, Kyoko; Ohba, Yusuke; Shinohara, Nobuo; Nonomura, Katsuya; Tanaka, Shinya

    2015-01-01

    We have previously reported that an adaptor protein CRK, including CRK-I and CRK-II, plays essential roles in the malignant potential of various aggressive human cancers, suggesting the validity of targeting CRK in molecular targeted therapy of a wide range of cancers. Nevertheless, the role of CRK in human bladder cancer with marked invasion, characterized by distant metastasis and poor prognosis, remains obscure. In the present study, immunohistochemistry indicated a striking enhancement of CRK-I/-II, but not CRK-like, in human bladder cancer tissues compared to normal urothelium. We established CRK-knockdown bladder cancer cells using 5637 and UM-UC-3, which showed a significant decline in cell migration, invasion, and proliferation. It is noteworthy that an elimination of CRK conferred suppressed phosphorylation of c-Met and the downstream scaffold protein Gab1 in a hepatocyte growth factor-dependent and -independent manner. In epithelial–mesenchymal transition-related molecules, E-cadherin was upregulated by CRK elimination, whereas N-cadherin, vimentin, and Zeb1 were downregulated. A similar effect was observed following treatment with c-Met inhibitor SU11274. Depletion of CRK significantly decreased cell proliferation of 5637 and UM-UC-3, consistent with reduced activity of ERK. An orthotopic xenograft model with bioluminescent imaging revealed that CRK knockdown significantly attenuated not only tumor volume but also the number of circulating tumor cells, resulted in a complete abrogation of metastasis. Taken together, this evidence uncovered essential roles of CRK in invasive bladder cancer through the hepatocyte growth factor/c-Met/CRK feedback loop for epithelial–mesenchymal transition induction. Thus, CRK might be a potent molecular target in bladder cancer, particularly for preventing metastasis, leading to the resolution of clinically longstanding critical issues. PMID:25816892

  13. Distinct in vitro interaction pattern of dopamine receptor subtypes with adaptor proteins involved in post-endocytotic receptor targeting

    Heydorn, Arne; Søndergaard, Birgitte P; Hadrup, Niels;

    2004-01-01

    The mechanisms underlying targeted sorting of endocytosed receptors for recycling to the plasma membrane or degradation in lysosomes are poorly understood. In this report, the C-terminal tails of the five dopamine receptors (D1-D5) were expressed as glutathione S-transferase (GST) fusion proteins...

  14. Structural and functional insights into CARDs of zebrafish (Danio rerio) NOD1 and NOD2, and their interaction with adaptor protein RIP2.

    Maharana, Jitendra; Dehury, Budheswar; Sahoo, Jyoti Ranjan; Jena, Itishree; Bej, Aritra; Panda, Debashis; Sahoo, Bikash Ranjan; Patra, Mahesh Chandra; Pradhan, Sukanta Kumar

    2015-08-01

    Nucleotide-binding and oligomerization domain-containing protein 1 (NOD1) and NOD2 are cytosolic pattern-recognition receptors (PRRs) composed of an N-terminal caspase activation and recruitment domain (CARD), a central NACHT domain and C-terminal leucine-rich repeats (LRRs). They play a vital role in innate immune signaling by activating the NF-κB pathway via recognition of peptidoglycans by LRRs, and ATP-dependent self-oligomerization of NACHT followed by downstream signaling. After oligomerization, CARD/s play a crucial role in activating downstream signaling via the adaptor molecule, RIP2. Due to the inadequacy of experimental 3D structures of CARD/s of NOD2 and RIP2, and results from differential experimental setups, the RIP2-mediated CARD-CARD interaction has remained as a contradictory statement. We employed a combinatorial approach involving protein modeling, docking, molecular dynamics simulation, and binding free energy calculation to illuminate the molecular mechanism that shows the possible involvement of either the acidic or basic patch of zebrafish NOD1/2-CARD/a and RIP2-CARD in CARD-CARD interaction. Herein, we have hypothesized 'type-I' mode of CARD-CARD interaction in NOD1 and NOD2, where NOD1/2-CARD/a involve their acidic surfaces to interact with RIP2. Asp37 and Glu51 (of NOD1) and Arg477, Arg521 and Arg529 (of RIP2) were identified to be crucial for NOD1-RIP2 interaction. However, in NOD2-RIP2, Asp32 (of NOD2) and Arg477 and Arg521 (of RIP2) were anticipated to be significant for downstream signaling. Furthermore, we found that strong electrostatic contacts and salt bridges are crucial for protein-protein interactions. Altogether, our study has provided novel insights into the RIP2-mediated CARD-CARD interaction in zebrafish NOD1 and NOD2, which will be helpful to understand the molecular basis of the NOD1/2 signaling mechanism. PMID:26079944

  15. Interplays between Sumoylation, SUMO-Targeted Ubiquitin Ligases, and the Ubiquitin-Adaptor Protein Ufd1 in Fission Yeast

    Køhler, Julie Bonne

    and the specific molecular interactions and sequence of events linking sumoylation, ubiquitylation and substrate degradation, has been largely uncovered. Using the fission yeast model organism I here present evidence for a role of the Ufd1 (ubiquitinfusion degradation 1) protein, and by extension of the Cdc48-Ufd1...... other downstream fates. My work provides insight into how Cdc48-Ufd1-Npl4 also contributes to the processing of SUMO conjugates and suggests that at least some of these activities are coordinated with STUbL function. To gain insight into the sumoylated species regulated by Ufd1 and/or by STUbLs, I made......-Npl4 activities are coupled to dynamically regulate cellular processes....

  16. A Network Synthesis Model for Generating Protein Interaction Network Families

    Sayed Mohammad Ebrahim Sahraeian; Byung-Jun Yoon

    2012-01-01

    In this work, we introduce a novel network synthesis model that can generate families of evolutionarily related synthetic protein-protein interaction (PPI) networks. Given an ancestral network, the proposed model generates the network family according to a hypothetical phylogenetic tree, where the descendant networks are obtained through duplication and divergence of their ancestors, followed by network growth using network evolution models. We demonstrate that this network synthesis model ca...

  17. A combined LDL receptor/LDL receptor adaptor protein 1 mutation as the cause for severe familial hypercholesterolemia.

    Soufi, Muhidien; Rust, Stephan; Walter, Michael; Schaefer, Juergen R

    2013-05-25

    Familial hypercholesterolemia (FH) results from impaired catabolism of plasma low density lipoproteins (LDL), thus leading to high cholesterol, atherosclerosis, and a high risk of premature myocardial infarction. FH is commonly caused by defects of the LDL receptor or its main ligand apoB, together mediating cellular uptake and clearance of plasma LDL. In some cases FH is inherited by mutations in the genes of PCSK9 and LDLRAP1 (ARH) in a dominant or recessive trait. The encoded proteins are required for LDL receptor stability and internalization within the LDLR pathway. To detect the underlying genetic defect in a family of Turkish descent showing unregular inheritance of severe FH, we screened the four candidate genes by denaturing gradient gel electrophoresis (DGGE) mutation analysis. We identified different combinatory mixtures of LDLR- and LDLRAP1-gene defects as the cause for severe familial hypercholesterolemia in this family. We also show for the first time that a heterozygous LDLR mutation combined with a homozygous LDLRAP1 mutation produces a more severe hypercholesterolemia phenotype in the same family than a homozygous LDLR mutation alone. PMID:23510778

  18. Protein evolution on a human signaling network

    Purisima Enrico O; Cui Qinghua; Wang Edwin

    2009-01-01

    Abstract Background The architectural structure of cellular networks provides a framework for innovations as well as constraints for protein evolution. This issue has previously been studied extensively by analyzing protein interaction networks. However, it is unclear how signaling networks influence and constrain protein evolution and conversely, how protein evolution modifies and shapes the functional consequences of signaling networks. In this study, we constructed a human signaling networ...

  19. The Clathrin Adaptor AP-1A Mediates Basolateral Polarity

    Gravotta, Diego; Carvajal-Gonzalez, Jose Maria; Mattera, Rafael; Deborde, Sylvie; Banfelder, Jason R.; Bonifacino, Juan S.; Rodriguez-Boulan, Enrique

    2012-01-01

    Clathrin and the epithelial-specific clathrin adaptor AP-1B mediate basolateral trafficking in epithelia. However, several epithelia lack AP-1B and mice knocked-out for AP-1B are viable, suggesting the existence of additional mechanisms that control basolateral polarity. Here, we demonstrate a distinct role of the ubiquitous clathrin adaptor AP-1A in basolateral protein sorting. Knock-down of AP-1A causes missorting of basolateral proteins in MDCK cells but only after knock-down of AP-1B, sug...

  20. Structural analysis of intermolecular interactions in the kinesin adaptor complex fasciculation and elongation protein zeta 1/ short coiled-coil protein (FEZ1/SCOCO.

    Marcos Rodrigo Alborghetti

    Full Text Available Cytoskeleton and protein trafficking processes, including vesicle transport to synapses, are key processes in neuronal differentiation and axon outgrowth. The human protein FEZ1 (fasciculation and elongation protein zeta 1 / UNC-76, in C. elegans, SCOCO (short coiled-coil protein / UNC-69 and kinesins (e.g. kinesin heavy chain / UNC116 are involved in these processes. Exploiting the feature of FEZ1 protein as a bivalent adapter of transport mediated by kinesins and FEZ1 protein interaction with SCOCO (proteins involved in the same path of axonal growth, we investigated the structural aspects of intermolecular interactions involved in this complex formation by NMR (Nuclear Magnetic Resonance, cross-linking coupled with mass spectrometry (MS, SAXS (Small Angle X-ray Scattering and molecular modelling. The topology of homodimerization was accessed through NMR (Nuclear Magnetic Resonance studies of the region involved in this process, corresponding to FEZ1 (92-194. Through studies involving the protein in its monomeric configuration (reduced and dimeric state, we propose that homodimerization occurs with FEZ1 chains oriented in an anti-parallel topology. We demonstrate that the interaction interface of FEZ1 and SCOCO defined by MS and computational modelling is in accordance with that previously demonstrated for UNC-76 and UNC-69. SAXS and literature data support a heterotetrameric complex model. These data provide details about the interaction interfaces probably involved in the transport machinery assembly and open perspectives to understand and interfere in this assembly and its involvement in neuronal differentiation and axon outgrowth.

  1. Preferential attachment in the protein network evolution

    Eisenberg, Eli; Levanon, Erez Y.

    2003-01-01

    The Saccharomyces cerevisiae protein-protein interaction map, as well as many natural and man-made networks, shares the scale-free topology. The preferential attachment model was suggested as a generic network evolution model that yields this universal topology. However, it is not clear that the model assumptions hold for the protein interaction network. Using a cross genome comparison we show that (a) the older a protein, the better connected it is, and (b) The number of interactions a prote...

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

    Yang Zhihao; Lin Hongfei; Xu Bo

    2011-01-01

    Abstract Background Protein complexes can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of protein complexes detection algorithms. Methods We have developed novel semantic similarity metho...

  3. Yeast Interacting Proteins Database: YLR170C, YPR029C [Yeast Interacting Proteins Database

    Full Text Available YLR170C APS1 Small subunit of the clathrin-associated adaptor complex AP-1, which is involved in ... protein sorting at the trans-Golgi network ; homolog of the sigma subunit of the mammalian cla ... is involved in protein sorting at the trans-Golgi network ; homolog of the sigma subunit of the mammalian cla ...

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

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

    2009-01-01

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

  5. Hub Promiscuity in Protein-Protein Interaction Networks

    Haruki Nakamura; Kengo Kinoshita; Ashwini Patil

    2010-01-01

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

  6. Protein interaction networks from literature mining

    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.

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

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

    2015-01-01

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

  8. Systematic computational prediction of protein interaction networks

    Determining the network of physical protein associations is an important first step in developing mechanistic evidence for elucidating biological pathways. Despite rapid advances in the field of high throughput experiments to determine protein interactions, the majority of associations remain unknown. Here we describe computational methods for significantly expanding protein association networks. We describe methods for integrating multiple independent sources of evidence to obtain higher quality predictions and we compare the major publicly available resources available for experimentalists to use

  9. Systematic computational prediction of protein interaction networks.

    Lees, J G; Heriche, J K; Morilla, I; Ranea, J A; Orengo, C A

    2011-06-01

    Determining the network of physical protein associations is an important first step in developing mechanistic evidence for elucidating biological pathways. Despite rapid advances in the field of high throughput experiments to determine protein interactions, the majority of associations remain unknown. Here we describe computational methods for significantly expanding protein association networks. We describe methods for integrating multiple independent sources of evidence to obtain higher quality predictions and we compare the major publicly available resources available for experimentalists to use. PMID:21572181

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

    Luciani Davide

    2012-05-01

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

  11. NAPS: Network Analysis of Protein Structures.

    Chakrabarty, Broto; Parekh, Nita

    2016-07-01

    Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue-residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in Å) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein-protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/. PMID:27151201

  12. A novel interaction between the SH2 domain of signaling adaptor protein Nck-1 and the upstream regulator of the Rho family GTPase Rac1 engulfment and cell motility 1 (ELMO1) promotes Rac1 activation and cell motility.

    Zhang, Guo; Chen, Xia; Qiu, Fanghua; Zhu, Fengxin; Lei, Wenjing; Nie, Jing

    2014-08-15

    Nck family proteins function as adaptors to couple tyrosine phosphorylation signals to actin cytoskeleton reorganization. Several lines of evidence indicate that Nck family proteins involve in regulating the activity of Rho family GTPases. In the present study, we characterized a novel interaction between Nck-1 with engulfment and cell motility 1 (ELMO1). GST pull-down and co-immunoprecipitation assay demonstrated that the Nck-1-ELMO1 interaction is mediated by the SH2 domain of Nck-1 and the phosphotyrosine residues at position 18, 216, 395, and 511 of ELMO1. A R308K mutant of Nck-1 (in which the SH2 domain was inactive), or a 4YF mutant of ELMO1 lacking these four phosphotyrosine residues, diminished Nck-1-ELMO1 interaction. Conversely, tyrosine phosphatase inhibitor treatment and overexpression of Src family kinase Hck significantly enhanced Nck-1-ELMO1 interaction. Moreover, wild type Nck-1, but not R308K mutant, significantly augmented the interaction between ELMO1 and constitutively active RhoG (RhoG(V12A)), thus promoted Rac1 activation and cell motility. Taken together, the present study characterized a novel Nck-1-ELMO1 interaction and defined a new role for Nck-1 in regulating Rac1 activity. PMID:24928514

  13. Finding local communities in protein networks

    Teng Shang-Hua; Voevodski Konstantin; Xia Yu

    2009-01-01

    Abstract Background Protein-protein interactions (PPIs) play fundamental roles in nearly all biological processes, and provide major insights into the inner workings of cells. A vast amount of PPI data for various organisms is available from BioGRID and other sources. The identification of communities in PPI networks is of great interest because they often reveal previously unknown functional ties between proteins. A large number of global clustering algorithms have been applied to protein ne...

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

    Xiaomin Wang; Zhengzhi Wang; Jun Ye

    2011-01-01

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

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

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

    2014-01-01

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

  16. Characterization of Toll-like receptors in primary lung epithelial cells: strong impact of the TLR3 ligand poly(I:C on the regulation of Toll-like receptors, adaptor proteins and inflammatory response

    Weith Andreas

    2005-11-01

    Full Text Available Abstract Background Bacterial and viral exacerbations play a crucial role in a variety of lung diseases including COPD or asthma. Since the lung epithelium is a major source of various inflammatory mediators that affect the immune response, we analyzed the inflammatory reaction of primary lung epithelial cells to different microbial molecules that are recognized by Toll-like receptors (TLR. Methods The effects of TLR ligands on primary small airway epithelial cells were analyzed in detail with respect to cytokine, chemokine and matrix metalloproteinase secretion. In addition, the regulation of the expression of TLRs and their adaptor proteins in small airway epithelial cells was investigated. Results Our data demonstrate that poly(I:C, a synthetic analog of viral dsRNA, mediated the strongest proinflammatory effects among the tested ligands, including an increased secretion of IL-6, IL-8, TNF-α, GM-CSF, GRO-α, TARC, MCP-1, MIP-3α, RANTES, IFN-β, IP-10 and ITAC as well as an increased release of MMP-1, MMP-8, MMP-9, MMP-10 and MMP-13. Furthermore, our data show that poly(I:C as well as type-1 and type-2 cytokines have a pronounced effect on the expression of TLRs and molecules involved in TLR signaling in small airway epithelial cells. Poly(I:C induced an elevated expression of TLR1, TLR2 and TLR3 and increased the gene expression of the general TLR adaptor MyD88 and IRAK-2. Simultaneously, poly(I:C decreased the expression of TLR5, TLR6 and TOLLIP. Conclusion Poly(I:C, an analog of viral dsRNA and a TLR3 ligand, triggers a strong inflammatory response in small airway epithelial cells that is likely to contribute to viral exacerbations of pulmonary diseases like asthma or COPD. The pronounced effects of poly(I:C on the expression of Toll-like receptors and molecules involved in TLR signaling is assumed to influence the immune response of the lung epithelium to viral and bacterial infections. Likewise, the regulation of TLR expression by type

  17. Neural Networks for protein Structure Prediction

    Bohr, Henrik

    1998-01-01

    This is a review about neural network applications in bioinformatics. Especially the applications to protein structure prediction, e.g. prediction of secondary structures, prediction of surface structure, fold class recognition and prediction of the 3-dimensional structure of protein backbones, is...

  18. Multiplexed imaging of intracellular protein networks.

    Grecco, Hernán E; Imtiaz, Sarah; Zamir, Eli

    2016-08-01

    Cellular functions emerge from the collective action of a large number of different proteins. Understanding how these protein networks operate requires monitoring their components in intact cells. Due to intercellular and intracellular molecular variability, it is important to monitor simultaneously multiple components at high spatiotemporal resolution. However, inherent trade-offs narrow the boundaries of achievable multiplexed imaging. Pushing these boundaries is essential for a better understanding of cellular processes. Here the motivations, challenges and approaches for multiplexed imaging of intracellular protein networks are discussed. © 2016 International Society for Advancement of Cytometry. PMID:27183498

  19. Multifunctional proteins revealed by overlapping clustering in protein interaction network

    Becker, Emmanuelle; Robisson, Benoît; Chapple, Charles E.; Guénoche, Alain; Brun, Christine

    2011-01-01

    Motivation: Multifunctional proteins perform several functions. They are expected to interact specifically with distinct sets of partners, simultaneously or not, depending on the function performed. Current graph clustering methods usually allow a protein to belong to only one cluster, therefore impeding a realistic assignment of multifunctional proteins to clusters. Results: Here, we present Overlapping Cluster Generator (OCG), a novel clustering method which decomposes a network into overla...

  20. Network analysis of human protein location

    Ranganathan Shoba; Kumar Gaurav

    2010-01-01

    Abstract Background Understanding cellular systems requires the knowledge of a protein's subcellular localization (SCL). Although experimental and predicted data for protein SCL are archived in various databases, SCL prediction remains a non-trivial problem in genome annotation. Current SCL prediction tools use amino-acid sequence features and text mining approaches. A comprehensive analysis of protein SCL in human PPI and metabolic networks for various subcellular compartments is necessary f...

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

    Oleksii Kuchaiev

    2009-08-01

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

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

    Sun Zhirong; Liu Ke; Chen Hu; Zhang Song

    2009-01-01

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

  3. Association between receptor protein-tyrosine phosphatase RPTPalpha and the Grb2 adaptor. Dual Src homology (SH) 2/SH3 domain requirement and functional consequences

    Su, J; Yang, L T; Sap, J

    1996-01-01

    binding site in RPTPalpha was studied further by expression of wild type or mutant RPTPalpha proteins in PC12 cells. In these cells, wild type RPTPalpha interferes with acidic fibroblast growth factor-induced neurite outgrowth; this effect requires both the catalytic activity and the Grb2 binding Tyr798...

  4. VITAMIN E (E) SUPPLEMENTATION REVERSES THE AGE ASSOCIATED DECLINE IN PHOSPHORYLATION OF THE ADAPTOR PROTEIN LAT IN CD4+ T CELLS

    T cell proliferation and interleukin (IL-2) production declines with age. Engagement of the T cell receptor (TCR) by antigen, known as the immune synapse (IS), in coordination with phosphorylation of key signaling proteins, leads to increased IL-2 synthesis and T cell proliferation. Defects in effec...

  5. Vitamin E (E) supplementation reverses the age associated decline in phosphorylation of the adaptor protein LAT in CD4+ T cells of old mice

    T cell proliferation and interleukin (IL-2) production declines with age. Engagement of the T cell receptor (TCR) by antigen (Ag), known as the immune synapse (IS), in coordination with phosphorylation of key signaling proteins, leads to increased IL-2 synthesis and T cell proliferation. Defects in ...

  6. Data management of protein interaction networks

    Cannataro, Mario

    2012-01-01

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

  7. Finding local communities in protein networks

    Teng Shang-Hua

    2009-09-01

    Full Text Available Abstract Background Protein-protein interactions (PPIs play fundamental roles in nearly all biological processes, and provide major insights into the inner workings of cells. A vast amount of PPI data for various organisms is available from BioGRID and other sources. The identification of communities in PPI networks is of great interest because they often reveal previously unknown functional ties between proteins. A large number of global clustering algorithms have been applied to protein networks, where the entire network is partitioned into clusters. Here we take a different approach by looking for local communities in PPI networks. Results We develop a tool, named Local Protein Community Finder, which quickly finds a community close to a queried protein in any network available from BioGRID or specified by the user. Our tool uses two new local clustering algorithms Nibble and PageRank-Nibble, which look for a good cluster among the most popular destinations of a short random walk from the queried vertex. The quality of a cluster is determined by proportion of outgoing edges, known as conductance, which is a relative measure particularly useful in undersampled networks. We show that the two local clustering algorithms find communities that not only form excellent clusters, but are also likely to be biologically relevant functional components. We compare the performance of Nibble and PageRank-Nibble to other popular and effective graph partitioning algorithms, and show that they find better clusters in the graph. Moreover, Nibble and PageRank-Nibble find communities that are more functionally coherent. Conclusion The Local Protein Community Finder, accessible at http://xialab.bu.edu/resources/lpcf, allows the user to quickly find a high-quality community close to a queried protein in any network available from BioGRID or specified by the user. We show that the communities found by our tool form good clusters and are functionally coherent

  8. DETECTION OF TOPOLOGICAL PATTERNS IN PROTEIN NETWORKS.

    MASLOV,S.SNEPPEN,K.

    2003-11-17

    Complex networks appear in biology on many different levels: (1) All biochemical reactions taking place in a single cell constitute its metabolic network, where nodes are individual metabolites, and edges are metabolic reactions converting them to each other. (2) Virtually every one of these reactions is catalyzed by an enzyme and the specificity of this catalytic function is ensured by the key and lock principle of its physical interaction with the substrate. Often the functional enzyme is formed by several mutually interacting proteins. Thus the structure of the metabolic network is shaped by the network of physical interactions of cell's proteins with their substrates and each other. (3) The abundance and the level of activity of each of the proteins in the physical interaction network in turn is controlled by the regulatory network of the cell. Such regulatory network includes all of the multiple mechanisms in which proteins in the cell control each other including transcriptional and translational regulation, regulation of mRNA editing and its transport out of the nucleus, specific targeting of individual proteins for degradation, modification of their activity e.g. by phosphorylation/dephosphorylation or allosteric regulation, etc. To get some idea about the complexity and interconnectedness of protein-protein regulations in baker's yeast Saccharomyces Cerevisiae in Fig. 1 we show a part of the regulatory network corresponding to positive or negative regulations that regulatory proteins exert on each other. (4) On yet higher level individual cells of a multicellular organism exchange signals with each other. This gives rise to several new networks such as e.g. nervous, hormonal, and immune systems of animals. The intercellular signaling network stages the development of a multicellular organism from the fertilized egg. (5) Finally, on the grandest scale, the interactions between individual species in ecosystems determine their food webs. An

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

    Nepusz, Tamás; Yu, Haiyuan; Paccanaro, Alberto

    2012-01-01

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

  10. Differential Association of the Na+/H+ Exchanger Regulatory Factor (NHERF Family of Adaptor Proteins with the Raft- and the Non-Raft Brush Border Membrane Fractions of NHE3

    Ayesha Sultan

    2013-11-01

    Full Text Available Background/Aims: Trafficking, brush border membrane (BBM retention, and signal-specific regulation of the Na+/H+ exchanger NHE3 is regulated by the Na+/H+ Exchanger Regulatory Factor (NHERF family of PDZ-adaptor proteins, which enable the formation of multiprotein complexes. It is unclear, however, what determines signal specificity of these NHERFs. Thus, we studied the association of NHE3, NHERF1 (EBP50, NHERF2 (E3KARP, and NHERF3 (PDZK1 with lipid rafts in murine small intestinal BBM. Methods: Detergent resistant membranes (“lipid rafts” were isolated by floatation of Triton X-incubated small intestinal BBM from a variety of knockout mouse strains in an Optiprep step gradient. Acid-activated NHE3 activity was measured fluorometrically in BCECF-loaded microdissected villi, or by assessment of CO2/HCO3- mediated increase in fluid absorption in perfused jejunal loops of anethetized mice. Results: NHE3 was found to partially associate with lipid rafts in the native BBM, and NHE3 raft association had an impact on NHE3 transport activity and regulation in vivo. NHERF1, 2 and 3 were differentially distributed to rafts and non-rafts, with NHERF2 being most raft-associated and NHERF3 entirely non-raft associated. NHERF2 expression enhanced the localization of NHE3 to membrane rafts. The use of acid sphingomyelinase-deficient mice, which have altered membrane lipid as well as lipid raft composition, allowed us to test the validity of the lipid raft concept in vivo. Conclusions: The differential association of the NHERFs with the raft-associated and the non-raft fraction of NHE3 in the brush border membrane is one component of the differential and signal-specific NHE3 regulation by the different NHERFs.

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

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

    2008-01-01

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

  12. Analysis of protein folds using protein contact networks

    Pankaj Barah; Somdatta Sinha

    2008-08-01

    Proteins are important biomolecules, which perform diverse structural and functional roles in living systems. Starting from a linear chain of amino acids, proteins fold to different secondary structures, which then fold through short- and long-range interactions to give rise to the final three-dimensional shapes useful to carry out the biophysical and biochemical functions. Proteins are defined as having a common `fold' if they have major secondary structural elements with same topological connections. It is known that folding mechanisms are largely determined by a protein's topology rather than its interatomic interactions. The native state protein structures can, thus, be modelled, using a graph-theoretical approach, as coarse-grained networks of amino acid residues as `nodes' and the inter-residue interactions/contacts as `links'. Using the network representation of protein structures and their 2D contact maps, we have identified the conserved contact patterns (groups of contacts) representing two typical folds – the EF-hand and the ubiquitin-like folds. Our results suggest that this direct and computationally simple methodology can be used to infer about the presence of specific folds from the protein's contact map alone.

  13. Network-Based Protein Biomarker Discovery Platforms.

    Kim, Minhyung; Hwang, Daehee

    2016-03-01

    The advances in mass spectrometry-based proteomics technologies have enabled the generation of global proteome data from tissue or body fluid samples collected from a broad spectrum of human diseases. Comparative proteomic analysis of global proteome data identifies and prioritizes the proteins showing altered abundances, called differentially expressed proteins (DEPs), in disease samples, compared to control samples. Protein biomarker candidates that can serve as indicators of disease states are then selected as key molecules among these proteins. Recently, it has been addressed that cellular pathways can provide better indications of disease states than individual molecules and also network analysis of the DEPs enables effective identification of cellular pathways altered in disease conditions and key molecules representing the altered cellular pathways. Accordingly, a number of network-based approaches to identify disease-related pathways and representative molecules of such pathways have been developed. In this review, we summarize analytical platforms for network-based protein biomarker discovery and key components in the platforms. PMID:27103885

  14. Extracting protein regulatory networks with graphical models.

    Grzegorczyk, Marco

    2007-09-01

    During the last decade the development of high-throughput biotechnologies has resulted in the production of exponentially expanding quantities of biological data, such as genomic and proteomic expression data. One fundamental problem in systems biology is to learn the architecture of biochemical pathways and regulatory networks in an inferential way from such postgenomic data. Along with the increasing amount of available data, a lot of novel statistical methods have been developed and proposed in the literature. This article gives a non-mathematical overview of three widely used reverse engineering methods, namely relevance networks, graphical Gaussian models, and Bayesian networks, whereby the focus is on their relative merits and shortcomings. In addition the reverse engineering results of these graphical methods on cytometric protein data from the RAF-signalling network are cross-compared via AUROC scatter plots. PMID:17893851

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

    Best, Christoph; Zimmer, Ralf; Apostolakis, Joannis

    2005-01-01

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

  16. The E3 Ubiquitin Ligase Adaptor Protein Skp1 Is Glycosylated by an Evolutionarily Conserved Pathway That Regulates Protist Growth and Development.

    Rahman, Kazi; Zhao, Peng; Mandalasi, Msano; van der Wel, Hanke; Wells, Lance; Blader, Ira J; West, Christopher M

    2016-02-26

    Toxoplasma gondii is a protist parasite of warm-blooded animals that causes disease by proliferating intracellularly in muscle and the central nervous system. Previous studies showed that a prolyl 4-hydroxylase related to animal HIFα prolyl hydroxylases is required for optimal parasite proliferation, especially at low O2. We also observed that Pro-154 of Skp1, a subunit of the Skp1/Cullin-1/F-box protein (SCF)-class of E3-ubiquitin ligases, is a natural substrate of this enzyme. In an unrelated protist, Dictyostelium discoideum, Skp1 hydroxyproline is modified by five sugars via the action of three glycosyltransferases, Gnt1, PgtA, and AgtA, which are required for optimal O2-dependent development. We show here that TgSkp1 hydroxyproline is modified by a similar pentasaccharide, based on mass spectrometry, and that assembly of the first three sugars is dependent on Toxoplasma homologs of Gnt1 and PgtA. Reconstitution of the glycosyltransferase reactions in extracts with radioactive sugar nucleotide substrates and appropriate Skp1 glycoforms, followed by chromatographic analysis of acid hydrolysates of the reaction products, confirmed the predicted sugar identities as GlcNAc, Gal, and Fuc. Disruptions of gnt1 or pgtA resulted in decreased parasite growth. Off target effects were excluded based on restoration of the normal glycan chain and growth upon genetic complementation. By analogy to Dictyostelium Skp1, the mechanism may involve regulation of assembly of the SCF complex. Understanding the mechanism of Toxoplasma Skp1 glycosylation is expected to help develop it as a drug target for control of the pathogen, as the glycosyltransferases are absent from mammalian hosts. PMID:26719340

  17. Modularity detection in protein-protein interaction networks

    Narayanan Tejaswini

    2011-12-01

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

  18. The Effects of Network Neighbours on Protein Evolution

    Guang-Zhong Wang; Martin J Lercher

    2011-01-01

    Interacting proteins may often experience similar selection pressures. Thus, we may expect that neighbouring proteins in biological interaction networks evolve at similar rates. This has been previously shown for protein-protein interaction networks. Similarly, we find correlated rates of evolution of neighbours in networks based on co-expression, metabolism, and synthetic lethal genetic interactions. While the correlations are statistically significant, their magnitude is small, with network...

  19. CPL:Detecting Protein Complexes by Propagating Labels on Protein-Protein Interaction Network

    代启国; 郭茂祖; 刘晓燕; 滕志霞; 王春宇

    2014-01-01

    Proteins usually bind together to form complexes, which play an important role in cellular activities. Many graph clustering methods have been proposed to identify protein complexes by finding dense regions in protein-protein interaction networks. We present a novel framework (CPL) that detects protein complexes by propagating labels through interactions in a network, in which labels denote complex identifiers. With proper propagation in CPL, proteins in the same complex will be assigned with the same labels. CPL does not make any strong assumptions about the topological structures of the complexes, as in previous methods. The CPL algorithm is tested on several publicly available yeast protein-protein interaction networks and compared with several state-of-the-art methods. The results suggest that CPL performs better than the existing methods. An analysis of the functional homogeneity based on a gene ontology analysis shows that the detected complexes of CPL are highly biologically relevant.

  20. Transmembrane adaptor proteins: organizers of immunoreceptor signalling

    Hořejší, Václav; Zhang, W.; Schraven, B.

    2004-01-01

    Roč. 4, č. 8 (2004), s. 603-616. ISSN 1474-1733 R&D Projects: GA MŠk LN00A026 Institutional research plan: CEZ:AV0Z5052915 Keywords : immunoreceptor * signalling Subject RIV: EC - Immunology Impact factor: 32.695, year: 2004

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

    Jiang Jonathan Q; Wu Maoying

    2012-01-01

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

  2. CCM2-CCM3 interaction stabilizes their protein expression and permits endothelial network formation

    Draheim, Kyle M.; Li, Xiaofeng; Zhang, Rong; Fisher, Oriana S.; Villari, Giulia; Boggon, Titus J.; Calderwood, David A. [Yale

    2015-04-21

    Mutations in the essential adaptor proteins CCM2 or CCM3 lead to cerebral cavernous malformations (CCM), vascular lesions that most frequently occur in the brain and are strongly associated with hemorrhagic stroke, seizures, and other neurological disorders. CCM2 binds CCM3, but the molecular basis of this interaction, and its functional significance, have not been elucidated. Here, we used x-ray crystallography and structure-guided mutagenesis to show that an α-helical LD-like motif within CCM2 binds the highly conserved “HP1” pocket of the CCM3 focal adhesion targeting (FAT) homology domain. By knocking down CCM2 or CCM3 and rescuing with binding-deficient mutants, we establish that CCM2–CCM3 interactions protect CCM2 and CCM3 proteins from proteasomal degradation and show that both CCM2 and CCM3 are required for normal endothelial cell network formation. However, CCM3 expression in the absence of CCM2 is sufficient to support normal cell growth, revealing complex-independent roles for CCM3.

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

    Tan Kai

    2010-10-01

    Full Text Available Abstract Background Recent advances in proteomic technologies have enabled us to create detailed protein-protein interaction maps in multiple species and in both normal and diseased cells. As the size of the interaction dataset increases, powerful computational methods are required in order to effectively distil network models from large-scale interactome data. Results We present an algorithm, miPALM (Module Inference by Parametric Local Modularity, to infer protein complexes in a protein-protein interaction network. The algorithm uses a novel graph theoretic measure, parametric local modularity, to identify highly connected sub-networks as candidate protein complexes. Using gold standard sets of protein complexes and protein function and localization annotations, we show our algorithm achieved an overall improvement over previous algorithms in terms of precision, recall, and biological relevance of the predicted complexes. We applied our algorithm to predict and characterize a set of 138 novel protein complexes in S. cerevisiae. Conclusions miPALM is a novel algorithm for detecting protein complexes from large protein-protein interaction networks with improved accuracy than previous methods. The software is implemented in Matlab and is freely available at http://www.medicine.uiowa.edu/Labs/tan/software.html.

  4. Evolutionarily conserved herpesviral protein interaction networks.

    Even Fossum

    2009-09-01

    Full Text Available Herpesviruses constitute a family of large DNA viruses widely spread in vertebrates and causing a variety of different diseases. They possess dsDNA genomes ranging from 120 to 240 kbp encoding between 70 to 170 open reading frames. We previously reported the protein interaction networks of two herpesviruses, varicella-zoster virus (VZV and Kaposi's sarcoma-associated herpesvirus (KSHV. In this study, we systematically tested three additional herpesvirus species, herpes simplex virus 1 (HSV-1, murine cytomegalovirus and Epstein-Barr virus, for protein interactions in order to be able to perform a comparative analysis of all three herpesvirus subfamilies. We identified 735 interactions by genome-wide yeast-two-hybrid screens (Y2H, and, together with the interactomes of VZV and KSHV, included a total of 1,007 intraviral protein interactions in the analysis. Whereas a large number of interactions have not been reported previously, we were able to identify a core set of highly conserved protein interactions, like the interaction between HSV-1 UL33 with the nuclear egress proteins UL31/UL34. Interactions were conserved between orthologous proteins despite generally low sequence similarity, suggesting that function may be more conserved than sequence. By combining interactomes of different species we were able to systematically address the low coverage of the Y2H system and to extract biologically relevant interactions which were not evident from single species.

  5. Connecting the dots in Huntington's disease with protein interaction networks

    Giorgini, Flaviano; Muchowski, Paul J.

    2005-01-01

    Analysis of protein-protein interaction networks is becoming important for inferring the function of uncharacterized proteins. A recent study using this approach has identified new proteins and interactions that might be involved in the pathogenesis of the neurodegenerative disorder Huntington's disease, including a GTPase-activating protein that co-localizes with protein aggregates in Huntington's disease patients.

  6. Competitive and cooperative interactions mediate RNA transfer from herpesvirus saimiri ORF57 to the mammalian export adaptor ALYREF.

    Richard B Tunnicliffe

    2014-02-01

    Full Text Available The essential herpesvirus adaptor protein HVS ORF57, which has homologs in all other herpesviruses, promotes viral mRNA export by utilizing the cellular mRNA export machinery. ORF57 protein specifically recognizes viral mRNA transcripts, and binds to proteins of the cellular transcription-export (TREX complex, in particular ALYREF. This interaction introduces viral mRNA to the NXF1 pathway, subsequently directing it to the nuclear pore for export to the cytoplasm. Here we have used a range of techniques to reveal the sites for direct contact between RNA and ORF57 in the absence and presence of ALYREF. A binding site within ORF57 was characterized which recognizes specific viral mRNA motifs. When ALYREF is present, part of this ORF57 RNA binding site, composed of an α-helix, binds preferentially to ALYREF. This competitively displaces viral RNA from the α-helix, but contact with RNA is still maintained by a flanking region. At the same time, the flexible N-terminal domain of ALYREF comes into contact with the viral RNA, which becomes engaged in an extensive network of synergistic interactions with both ALYREF and ORF57. Transfer of RNA to ALYREF in the ternary complex, and involvement of individual ORF57 residues in RNA recognition, were confirmed by UV cross-linking and mutagenesis. The atomic-resolution structure of the ORF57-ALYREF interface was determined, which noticeably differed from the homologous ICP27-ALYREF structure. Together, the data provides the first site-specific description of how viral mRNA is locked by a herpes viral adaptor protein in complex with cellular ALYREF, giving herpesvirus access to the cellular mRNA export machinery. The NMR strategy used may be more generally applicable to the study of fuzzy protein-protein-RNA complexes which involve flexible polypeptide regions.

  7. Modularity in the evolution of yeast protein interaction network

    Ogishima, Soichi; Tanaka, Hiroshi; Nakaya, Jun

    2015-01-01

    Protein interaction networks are known to exhibit remarkable structures: scale-free and small-world and modular structures. To explain the evolutionary processes of protein interaction networks possessing scale-free and small-world structures, preferential attachment and duplication-divergence models have been proposed as mathematical models. Protein interaction networks are also known to exhibit another remarkable structural characteristic, modular structure. How the protein interaction netw...

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

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

    2016-01-01

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

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

    Tan Kai; Kim Jongkwang

    2010-01-01

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

  10. Protein interaction network related to Helicobacter pylori infection response

    Kyu Kwang Kim; Han Bok Kim

    2009-01-01

    AIM: To understand the complex reaction of gastric inflammation induced by Helicobacter pylori (H pylori ) in a systematic manner using a protein interaction network. METHODS: The expression of genes significantly changed on microarray during H pylori infection was scanned from the web literary database and translated into proteins. A network of protein interactions was constructed by searching the primary interactions of selected proteins. The constructed network was mathematically analyzed and its biological function was examined. In addition, the nodes on the network were checked to determine if they had any further functional importance or relation to other proteins by extending them.RESULTS: The scale-free network showing the relationship between inflammation and carcinogenesis was constructed. Mathematical analysis showed hub and bottleneck proteins, and these proteins were mostly related to immune response. The network contained pathways and proteins related to H pylori infection, such as the JAK-STAT pathway triggered by interleukins. Activation of nuclear factor (NF)-kB, TLR4, and other proteins known to function as core proteins of immune response were also found.These immune-related proteins interacted on the network with pathways and proteins related to the cell cycle, cell maintenance and proliferation, and transcription regulators such as BRCA1, FOS, REL, and zinc finger proteins. The extension of nodes showed interactions of the immune proteins with cancerrelated proteins. One extended network, the core network, a summarized form of the extended network, and cell pathway model were constructed. CONCLUSION: Immune-related proteins activated by H pylori infection interact with proto-oncogene proteins. The hub and bottleneck proteins are potential drug targets for gastric inflammation and cancer.

  11. The AP-3 adaptor complex is required for vacuolar function in Arabidopsis

    Zwiewka, M.; Feraru, E.; Moller, B.K.; Hwang, I.; Feraru, M.I.; Kleine-Vehn, J.; Weijers, D.; Friml, J.

    2011-01-01

    Subcellular trafficking is required for a multitude of functions in eukaryotic cells. It involves regulation of cargo sorting, vesicle formation, trafficking and fusion processes at multiple levels. Adaptor protein (AP) complexes are key regulators of cargo sorting into vesicles in yeast and mammals

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

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

    2014-01-01

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

  13. Identifying drug-target proteins based on network features

    2009-01-01

    Proteins rarely function in isolation inside and outside cells, but operate as part of a highly intercon- nected cellular network called the interaction network. Therefore, the analysis of the properties of drug-target proteins in the biological network is especially helpful for understanding the mechanism of drug action in terms of informatics. At present, no detailed characterization and description of the topological features of drug-target proteins have been available in the human protein-protein interac- tion network. In this work, by mapping the drug-targets in DrugBank onto the interaction network of human proteins, five topological indices of drug-targets were analyzed and compared with those of the whole protein interactome set and the non-drug-target set. The experimental results showed that drug-target proteins have higher connectivity and quicker communication with each other in the PPI network. Based on these features, all proteins in the interaction network were ranked. The results showed that, of the top 100 proteins, 48 are covered by DrugBank; of the remaining 52 proteins, 9 are drug-target proteins covered by the TTD, Matador and other databases, while others have been dem- onstrated to be drug-target proteins in the literature.

  14. Identifying drug-target proteins based on network features

    ZHU MingZhu; GAO Lei; LI Xia; LIU ZhiCheng

    2009-01-01

    Proteins rarely function in isolation Inside and outside cells, but operate as part of a highly Intercon-nected cellular network called the interaction network. Therefore, the analysis of the properties of drug-target proteins in the biological network is especially helpful for understanding the mechanism of drug action In terms of informatice. At present, no detailed characterization and description of the topological features of drug-target proteins have been available in the human protein-protein interac-tion network. In this work, by mapping the drug-targets in DrugBank onto the interaction network of human proteins, five topological indices of drug-targets were analyzed and compared with those of the whole protein interactome set and the non-drug-target set. The experimental results showed that drug-target proteins have higher connectivity and quicker communication with each other in the PPI network. Based on these features, all proteins In the interaction network were ranked. The results showed that, of the top 100 proteins, 48 are covered by DrugBank; of the remaining 52 proteins, 9 are drug-target proteins covered by the TTD, Matador and other databases, while others have been dem-onstrated to be drug-target proteins in the literature.

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

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

    2016-01-01

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

  16. Topological aspects of the human protein interaction network

    Wiebringhaus, Thomas

    2008-01-01

    It is currently widely accepted that the understanding of complex cell functions depends on an integrated network theoretical approach and not on an isolated view of the different molecular agents. Aim of this thesis was the examination of topological properties that mirror known biological aspects by depicting the human protein network with methods from graph- and network theory. The presented network is a partial human interactome of 9222 proteins and 36324 interactions, consisting of singl...

  17. Dynamical Analysis of Protein Regulatory Network in Budding Yeast Nucleus

    LI Fang-Ting; JIA Xun

    2006-01-01

    @@ Recent progresses in the protein regulatory network of budding yeast Saccharomyces cerevisiae have provided a global picture of its protein network for further dynamical research. We simplify and modularize the protein regulatory networks in yeast nucleus, and study the dynamical properties of the core 37-node network by a Boolean network model, especially the evolution steps and final fixed points. Our simulation results show that the number of fixed points N(k) for a given size of the attraction basin k obeys a power-law distribution N(k)∝k-2.024. The yeast network is more similar to a scale-free network than a random network in the above dynamical properties.

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

    Hao Wu

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

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

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

    2014-01-01

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

  20. The Role of the Clathrin Adaptor AP-1: Polarized Sorting and Beyond

    Fubito Nakatsu

    2014-11-01

    Full Text Available The selective transport of proteins or lipids by vesicular transport is a fundamental process supporting cellular physiology. The budding process involves cargo sorting and vesicle formation at the donor membrane and constitutes an important process in vesicular transport. This process is particularly important for the polarized sorting in epithelial cells, in which the cargo molecules need to be selectively sorted and transported to two distinct destinations, the apical or basolateral plasma membrane. Adaptor protein (AP-1, a member of the AP complex family, which includes the ubiquitously expressed AP-1A and the epithelium-specific AP-1B, regulates polarized sorting at the trans-Golgi network and/or at the recycling endosomes. A growing body of evidence, especially from studies using model organisms and animals, demonstrates that the AP-1-mediated polarized sorting supports the development and physiology of multi-cellular units as functional organs and tissues (e.g., cell fate determination, inflammation and gut immune homeostasis. Furthermore, a possible involvement of AP-1B in the pathogenesis of human diseases, such as Crohn’s disease and cancer, is now becoming evident. These data highlight the significant contribution of AP-1 complexes to the physiology of multicellular organisms, as master regulators of polarized sorting in epithelial cells.

  1. Construction of Ontology Augmented Networks for Protein Complex Prediction

    Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Jian WANG

    2013-01-01

    Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology a...

  2. Evaluation of clustering algorithms for protein-protein interaction networks

    van Helden Jacques

    2006-11-01

    Full Text Available Abstract Background Protein interactions are crucial components of all cellular processes. Recently, high-throughput methods have been developed to obtain a global description of the interactome (the whole network of protein interactions for a given organism. In 2002, the yeast interactome was estimated to contain up to 80,000 potential interactions. This estimate is based on the integration of data sets obtained by various methods (mass spectrometry, two-hybrid methods, genetic studies. High-throughput methods are known, however, to yield a non-negligible rate of false positives, and to miss a fraction of existing interactions. The interactome can be represented as a graph where nodes correspond with proteins and edges with pairwise interactions. In recent years clustering methods have been developed and applied in order to extract relevant modules from such graphs. These algorithms require the specification of parameters that may drastically affect the results. In this paper we present a comparative assessment of four algorithms: Markov Clustering (MCL, Restricted Neighborhood Search Clustering (RNSC, Super Paramagnetic Clustering (SPC, and Molecular Complex Detection (MCODE. Results A test graph was built on the basis of 220 complexes annotated in the MIPS database. To evaluate the robustness to false positives and false negatives, we derived 41 altered graphs by randomly removing edges from or adding edges to the test graph in various proportions. Each clustering algorithm was applied to these graphs with various parameter settings, and the clusters were compared with the annotated complexes. We analyzed the sensitivity of the algorithms to the parameters and determined their optimal parameter values. We also evaluated their robustness to alterations of the test graph. We then applied the four algorithms to six graphs obtained from high-throughput experiments and compared the resulting clusters with the annotated complexes. Conclusion This

  3. Protein Co-Expression Network Analysis (ProCoNA)

    Gibbs, David L.; Baratt, Arie; Baric, Ralph; Kawaoka, Yoshihiro; Smith, Richard D.; Orwoll, Eric S.; Katze, Michael G.; Mcweeney, Shannon K.

    2013-06-01

    Biological networks are important for elucidating disease etiology due to their ability to model complex high dimensional data and biological systems. Proteomics provides a critical data source for such models, but currently lacks robust de novo methods for network construction, which could bring important insights in systems biology. We have evaluated the construction of network models using methods derived from weighted gene co-expression network analysis (WGCNA). We show that approximately scale-free peptide networks, composed of statistically significant modules, are feasible and biologically meaningful using two mouse lung experiments and one human plasma experiment. Within each network, peptides derived from the same protein are shown to have a statistically higher topological overlap and concordance in abundance, which is potentially important for inferring protein abundance. The module representatives, called eigenpeptides, correlate significantly with biological phenotypes. Furthermore, within modules, we find significant enrichment for biological function and known interactions (gene ontology and protein-protein interactions). Biological networks are important tools in the analysis of complex systems. In this paper we evaluate the application of weighted co-expression network analysis to quantitative proteomics data. Protein co-expression networks allow novel approaches for biological interpretation, quality control, inference of protein abundance, a framework for potentially resolving degenerate peptide-protein mappings, and a biomarker signature discovery.

  4. Combining neural networks for protein secondary structure prediction

    Riis, Søren Kamaric

    1995-01-01

    In this paper structured neural networks are applied to the problem of predicting the secondary structure of proteins. A hierarchical approach is used where specialized neural networks are designed for each structural class and then combined using another neural network. The submodels are designe...... is better than most secondary structure prediction methods based on single sequences even though this model contains much fewer parameters...

  5. Visualizing and Clustering Protein Similarity Networks: Sequences, Structures, and Functions.

    Mai, Te-Lun; Hu, Geng-Ming; Chen, Chi-Ming

    2016-07-01

    Research in the recent decade has demonstrated the usefulness of protein network knowledge in furthering the study of molecular evolution of proteins, understanding the robustness of cells to perturbation, and annotating new protein functions. In this study, we aimed to provide a general clustering approach to visualize the sequence-structure-function relationship of protein networks, and investigate possible causes for inconsistency in the protein classifications based on sequences, structures, and functions. Such visualization of protein networks could facilitate our understanding of the overall relationship among proteins and help researchers comprehend various protein databases. As a demonstration, we clustered 1437 enzymes by their sequences and structures using the minimum span clustering (MSC) method. The general structure of this protein network was delineated at two clustering resolutions, and the second level MSC clustering was found to be highly similar to existing enzyme classifications. The clustering of these enzymes based on sequence, structure, and function information is consistent with each other. For proteases, the Jaccard's similarity coefficient is 0.86 between sequence and function classifications, 0.82 between sequence and structure classifications, and 0.78 between structure and function classifications. From our clustering results, we discussed possible examples of divergent evolution and convergent evolution of enzymes. Our clustering approach provides a panoramic view of the sequence-structure-function network of proteins, helps visualize the relation between related proteins intuitively, and is useful in predicting the structure and function of newly determined protein sequences. PMID:27267620

  6. Convolutional LSTM Networks for Subcellular Localization of Proteins

    Nielsen, Henrik; Sønderby, Søren Kaae; Sønderby, Casper Kaae; Winther, Ole

    2015-01-01

    Machine learning is widely used to analyze biological sequence data. Non-sequential models such as SVMs or feed-forward neural networks are often used although they have no natural way of handling sequences of varying length. Recurrent neural networks such as the long short term memory (LSTM) model on the other hand are designed to handle sequences. In this study we demonstrate that LSTM networks predict the subcellular location of proteins given only the protein sequence with high accuracy (...

  7. Towards a matrix mechanics framework for dynamic protein network

    Bhattacharya, Sanjoy K.

    2010-01-01

    Protein–protein interaction networks are currently visualized by software generated interaction webs based upon static experimental data. Current state is limited to static, mostly non-compartmental network and non time resolved protein interactions. A satisfactory mathematical foundation for particle interactions within a viscous liquid state (situation within the cytoplasm) does not exist nor do current computer programs enable building dynamic interaction networks for time resolved interac...

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

    Peng Liu; Lei Yang; Daming Shi; Xianglong Tang

    2015-01-01

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

  9. Connectivity of neutral networks and structural conservation in protein evolution

    Bastolla, Ugo; Porto, Markus; Roman, H. Eduardo; Vendruscolo, Michele

    2001-01-01

    Protein structures are much more conserved than sequences during evolution. Based on this observation, we investigate the consequences of structural conservation on protein evolution. We study seven of the most studied protein folds, finding out that an extended neutral network in sequence space is associated to each of them. Within our model, neutral evolution leads to a non-Poissonian substitution process, due to the broad distribution of connectivities in neutral networks. The observation ...

  10. Crystal structure of the mammalian Grb2 adaptor.

    Maignan, S; Guilloteau, J P; Fromage, N; Arnoux, B; Becquart, J; Ducruix, A

    1995-04-14

    The mammalian growth factor receptor-binding protein Grb2 is an adaptor that mediates activation of guanine nucleotide exchange on Ras. Grb2 binds to the receptor through its SH2 domain and to the carboxyl-terminal domain of Son of sevenless through its two SH3 domains. It is thus a key element in the signal transduction pathway. The crystal structure of Grb2 was determined to 3.1 angstrom resolution. The asymmetric unit is composed of an embedded dimer. The interlaced junctions between the SH2 and SH3 domains bring the two adjacent faces of the SH3 domains in van der Waals contact but leave room for the binding of proline-rich peptides. PMID:7716522

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

    Zhao Yiqiang; Mooney Sean D

    2012-01-01

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

  12. Profiling of Protein Interaction Networks of Protein Complexes Using Affinity Purification and Quantitative Mass Spectrometry*

    Kaake, Robyn M; Wang, Xiaorong; Huang, Lan

    2010-01-01

    Protein-protein interactions are important for nearly all biological processes, and it is known that aberrant protein-protein interactions can lead to human disease and cancer. Recent evidence has suggested that protein interaction interfaces describe a new class of attractive targets for drug development. Full characterization of protein interaction networks of protein complexes and their dynamics in response to various cellular cues will provide essential information for us to understand ho...

  13. Dissipative electro-elastic network model of protein electrostatics

    We propose a dissipative electro-elastic network model to describe the dynamics and statistics of electrostatic fluctuations at active sites of proteins. The model combines the harmonic network of residue beads with overdamped dynamics of the normal modes of the network characterized by two friction coefficients. The electrostatic component is introduced to the model through atomic charges of the protein force field. The overall effect of the electrostatic fluctuations of the network is recorded through the frequency-dependent response functions of the electrostatic potential and electric field at the protein active site. We also consider the dynamics of displacements of individual residues in the network and the dynamics of distances between pairs of residues. The model is tested against loss spectra of residue displacements and the electrostatic potential and electric field at the heme's iron from all-atom molecular dynamics simulations of three hydrated globular proteins. (paper)

  14. Identifying protein complexes in protein-protein interaction networks by using clique seeds and graph entropy.

    Chen, Bolin; Shi, Jinhong; Zhang, Shenggui; Wu, Fang-Xiang

    2013-01-01

    The identification of protein complexes plays a key role in understanding major cellular processes and biological functions. Various computational algorithms have been proposed to identify protein complexes from protein-protein interaction (PPI) networks. In this paper, we first introduce a new seed-selection strategy for seed-growth style algorithms. Cliques rather than individual vertices are employed as initial seeds. After that, a result-modification approach is proposed based on this seed-selection strategy. Predictions generated by higher order clique seeds are employed to modify results that are generated by lower order ones. The performance of this seed-selection strategy and the result-modification approach are tested by using the entropy-based algorithm, which is currently the best seed-growth style algorithm to detect protein complexes from PPI networks. In addition, we investigate four pairs of strategies for this algorithm in order to improve its accuracy. The numerical experiments are conducted on a Saccharomyces cerevisiae PPI network. The group of best predictions consists of 1711 clusters, with the average f-score at 0.68 after removing all similar and redundant clusters. We conclude that higher order clique seeds can generate predictions with higher accuracy and that our improved entropy-based algorithm outputs more reasonable predictions than the original one. PMID:23112006

  15. Evidence of probabilistic behaviour in protein interaction networks

    Reifman Jaques

    2008-01-01

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

  16. Multi-level integrative analysis of Protein Protein Interaction networks: connecting completeness, depth and robustness.

    Blayney, Jaine K; Zheng, Huiru; Wang, Haiying; Azuaje, Francisco

    2010-01-01

    A fully extended Protein Protein Interaction (PPI) network can consist of upwards of several thousand nodes and edges. To simplify analysis, smaller child samples are often used in substitution of the global network. In this study, the impact of different levels of sampling was evaluated on six PPI networks. Results from the case studies suggest that restricting analysis to the first network level, using metrics such as degree and BC, could lead to misrepresentative results, omitting potentially significant nodes. Fault-tolerance analysis also indicates that key nodes within the second network level, and above, contribute to the stability of the global network. PMID:20693609

  17. Crystal structure of Toll-like receptor adaptor MAL/TIRAP reveals the molecular basis for signal transduction and disease protection

    Valkov, Eugene; Stamp, Anna; DiMaio, Frank; Baker, David; Verstak, Brett; Roversi, Pietro; Kellie, Stuart; Sweet, Matthew J.; Mansell, Ashley; Gay, Nicholas J.; Jennifer L Martin; Kobe, Bostjan

    2011-01-01

    Initiation of the innate immune response requires agonist recognition by pathogen-recognition receptors such as the Toll-like receptors (TLRs). Toll/interleukin-1 receptor (TIR) domain-containing adaptors are critical in orchestrating the signal transduction pathways after TLR and interleukin-1 receptor activation. Myeloid differentiation primary response gene 88 (MyD88) adaptor-like (MAL)/TIR domain-containing adaptor protein (TIRAP) is involved in bridging MyD88 to TLR2 and TLR4 in response...

  18. 3DProIN: Protein-Protein Interaction Networks and Structure Visualization

    Hui LI; Liu, Chunmei

    2014-01-01

    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 interne...

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

    G Jack Peterson

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

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

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

    2012-01-01

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

  1. Protein interaction networks--more than mere modules.

    Stefan Pinkert

    2010-01-01

    Full Text Available It is widely believed that the modular organization of cellular function is reflected in a modular structure of molecular networks. A common view is that a "module" in a network is a cohesively linked group of nodes, densely connected internally and sparsely interacting with the rest of the network. Many algorithms try to identify functional modules in protein-interaction networks (PIN by searching for such cohesive groups of proteins. Here, we present an alternative approach independent of any prior definition of what actually constitutes a "module". In a self-consistent manner, proteins are grouped into "functional roles" if they interact in similar ways with other proteins according to their functional roles. Such grouping may well result in cohesive modules again, but only if the network structure actually supports this. We applied our method to the PIN from the Human Protein Reference Database (HPRD and found that a representation of the network in terms of cohesive modules, at least on a global scale, does not optimally represent the network's structure because it focuses on finding independent groups of proteins. In contrast, a decomposition into functional roles is able to depict the structure much better as it also takes into account the interdependencies between roles and even allows groupings based on the absence of interactions between proteins in the same functional role. This, for example, is the case for transmembrane proteins, which could never be recognized as a cohesive group of nodes in a PIN. When mapping experimental methods onto the groups, we identified profound differences in the coverage suggesting that our method is able to capture experimental bias in the data, too. For example yeast-two-hybrid data were highly overrepresented in one particular group. Thus, there is more structure in protein-interaction networks than cohesive modules alone and we believe this finding can significantly improve automated function

  2. Parallel SCF adaptor capture proteomics reveals a role for SCFFBXL17 in NRF2 activation via BACH1 repressor turnover.

    Tan, Meng-Kwang Marcus; Lim, Hui-Jun; Bennett, Eric J; Shi, Yang; Harper, J Wade

    2013-10-10

    Modular cullin-RING E3 ubiquitin ligases (CRLs) use substrate binding adaptor proteins to specify target ubiquitylation. Many of the ~200 human CRL adaptor proteins remain poorly studied due to a shortage of efficient methods to identify biologically relevant substrates. Here, we report the development of parallel adaptor capture (PAC) proteomics and its use to systematically identify candidate targets for the leucine-rich repeat family of F-box proteins (FBXLs) that function with SKP1-CUL1-F-box protein (SCF) E3s. In validation experiments, we identify the unstudied F-box protein FBXL17 as a regulator of the NFR2 oxidative stress pathway. We demonstrate that FBXL17 controls the transcription of the NRF2 target HMOX1 via turnover of the transcriptional repressor BACH1 in the absence or presence of extrinsic oxidative stress. This work identifies a role for SCF(FBXL17) in controlling the threshold for NRF2-dependent gene activation and provides a framework for elucidating the functions of CRL adaptor proteins. PMID:24035498

  3. Evolution of a protein domain interaction network

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

  4. CNNcon: improved protein contact maps prediction using cascaded neural networks.

    Wang Ding

    Full Text Available BACKGROUNDS: Despite continuing progress in X-ray crystallography and high-field NMR spectroscopy for determination of three-dimensional protein structures, the number of unsolved and newly discovered sequences grows much faster than that of determined structures. Protein modeling methods can possibly bridge this huge sequence-structure gap with the development of computational science. A grand challenging problem is to predict three-dimensional protein structure from its primary structure (residues sequence alone. However, predicting residue contact maps is a crucial and promising intermediate step towards final three-dimensional structure prediction. Better predictions of local and non-local contacts between residues can transform protein sequence alignment to structure alignment, which can finally improve template based three-dimensional protein structure predictors greatly. METHODS: CNNcon, an improved multiple neural networks based contact map predictor using six sub-networks and one final cascade-network, was developed in this paper. Both the sub-networks and the final cascade-network were trained and tested with their corresponding data sets. While for testing, the target protein was first coded and then input to its corresponding sub-networks for prediction. After that, the intermediate results were input to the cascade-network to finish the final prediction. RESULTS: The CNNcon can accurately predict 58.86% in average of contacts at a distance cutoff of 8 Å for proteins with lengths ranging from 51 to 450. The comparison results show that the present method performs better than the compared state-of-the-art predictors. Particularly, the prediction accuracy keeps steady with the increase of protein sequence length. It indicates that the CNNcon overcomes the thin density problem, with which other current predictors have trouble. This advantage makes the method valuable to the prediction of long length proteins. As a result, the effective

  5. Dissipative electro-elastic network model of protein electrostatics

    Martin, Daniel R; Matyushov, Dmitry V

    2011-01-01

    We propose a dissipative electro-elastic network model (DENM) to describe the dynamics and statistics of electrostatic fluctuations at active sites of proteins. The model combines the harmonic network of residue beads with overdamped dynamics of the normal modes of the network characterized by two friction coefficients. The electrostatic component is introduced to the model through atomic charges of the protein force field. The overall effect of the electrostatic fluctuations of the network is recorded through the frequency-dependent response functions of the electrostatic potential and electric field at the active site. We also consider the dynamics of displacements of individual residues in the network and the dynamics of distances between pairs of residues. The model is tested against loss spectra of residue displacements and the electrostatic potential and electric field at the heme's iron from all-atom molecular dynamics simulations of three hydrated globular proteins.

  6. PhIN: A Protein Pharmacology Interaction Network Database

    Wang, Z.; Li, J.; Dang, R; Liang, L; J. Lin

    2015-01-01

    Network pharmacology is a new and hot concept in drug discovery for its ability to investigate the complexity of polypharmacology, and becomes more and more important in drug development. Here we report a protein pharmacology interaction network database (PhIN), aiming to assist multitarget drug discovery by providing comprehensive and flexible network pharmacology analysis. Overall, PhIN contains 1,126,060 target–target interaction pairs in terms of shared compounds and 3,428,020 pairs in te...

  7. Nck adaptors are positive regulators of the size and sensitivity of the T-cell repertoire

    Roy, Edwige; Togbe, Dieudonnée; Holdorf, Amy D.; Trubetskoy, Dmitry; Nabti, Sabrina; Küblbeck, Günter; Klevenz, Alexandra; Kopp-Schneider, Annette; Leithäuser, Frank; Möller, Peter; Bladt, Friedhelm; Hämmerling, Günter; Arnold, Bernd; Pawson, Tony; Tafuri, Anna

    2010-01-01

    The size and sensitivity of the T-cell repertoire governs the effectiveness of immune responses against invading pathogens. Both are modulated by T-cell receptor (TCR) activity through molecular mechanisms, which remain unclear. Here, we provide genetic evidence that the SH2/SH3 domain containing proteins Nck lower the threshold of T-cell responsiveness. The hallmarks of Nck deletion were T-cell lymphopenia and hyporeactivity to TCR-mediated stimulation. In the absence of the Nck adaptors, pe...

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

    Gillis, Jesse; Ballouz, Sara; Pavlidis, Paul

    2014-01-01

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

  9. Accuracy improvement in protein complex prediction from protein interaction networks by refining cluster overlaps

    Chiam Tak; Cho Young-Rae

    2012-01-01

    Abstract Background Recent computational techniques have facilitated analyzing genome-wide protein-protein interaction data for several model organisms. Various graph-clustering algorithms have been applied to protein interaction networks on the genomic scale for predicting the entire set of potential protein complexes. In particular, the density-based clustering algorithms which are able to generate overlapping clusters, i.e. the clusters sharing a set of nodes, are well-suited to protein co...

  10. Predicting and validating protein interactions using network structure.

    Pao-Yang Chen

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

  11. Programming Molecular Association and Viscoelastic Behavior in Protein Networks.

    Dooling, Lawrence J; Buck, Maren E; Zhang, Wen-Bin; Tirrell, David A

    2016-06-01

    A set of recombinant artificial proteins that can be cross-linked, by either covalent bonds or association of helical domains or both, is described. The designed proteins can be used to construct molecular networks in which the mechanism of crosslinking determines the time-dependent responses to mechanical deformation. PMID:27061171

  12. Construction and analysis of protein-protein interaction networks based on proteomics data of prostate cancer.

    Chen, Chen; Shen, Hong; Zhang, Li-Guo; Liu, Jian; Cao, Xiao-Ge; Yao, An-Liang; Kang, Shao-San; Gao, Wei-Xing; Han, Hui; Cao, Feng-Hong; Li, Zhi-Guo

    2016-06-01

    Currently, using human prostate cancer (PCa) tissue samples to conduct proteomics research has generated a large amount of data; however, only a very small amount has been thoroughly investigated. In this study, we manually carried out the mining of the full text of proteomics literature that involved comparisons between PCa and normal or benign tissue and identified 41 differentially expressed proteins verified or reported more than 2 times from different research studies. We regarded these proteins as seed proteins to construct a protein-protein interaction (PPI) network. The extended network included one giant network, which consisted of 1,264 nodes connected via 1,744 edges, and 3 small separate components. The backbone network was then constructed, which was derived from key nodes and the subnetwork consisting of the shortest path between seed proteins. Topological analyses of these networks were conducted to identify proteins essential for the genesis of PCa. Solute carrier family 2 (facilitated glucose transporter), member 4 (SLC2A4) had the highest closeness centrality located in the center of each network, and the highest betweenness centrality and largest degree in the backbone network. Tubulin, beta 2C (TUBB2C) had the largest degree in the giant network and subnetwork. In addition, using module analysis of the whole PPI network, we obtained a densely connected region. Functional annotation indicated that the Ras protein signal transduction biological process, mitogen-activated protein kinase (MAPK), neurotrophin and the gonadotropin-releasing hormone (GnRH) signaling pathway may play an important role in the genesis and development of PCa. Further investigation of the SLC2A4, TUBB2C proteins, and these biological processes and pathways may therefore provide a potential target for the diagnosis and treatment of PCa. PMID:27121963

  13. Topological features of proteins from amino acid residue networks

    Alves, N A; Alves, Nelson Augusto; Martinez, Alexandre Souto

    2006-01-01

    Topological properties of native folds are obtained from statistical analysis of 160 low homology proteins covering the four structural classes. This is done analysing one, two and three-vertex joint distribution of quantities related to the corresponding network of amino acid residues. Emphasis on the amino acid residue hydrophobicity leads to the definition of their center of mass as vertices in this contact network model with interactions represented by edges. The network analysis helps us to interpret experimental results such as hydrophobic scales and fraction of buried accessible surface area in terms of the network connectivity. To explore the vertex type dependent correlations, we build a network of hydrophobic and polar vertices. This procedure presents the wiring diagram of the topological structure of globular proteins leading to the following attachment probabilities between hydrophobic-hydrophobic 0.424(5), hydrophobic-polar 0.419(2) and polar-polar 0.157(3) residues.

  14. Vps10p Transport from the trans-Golgi Network to the Endosome Is Mediated by Clathrin-coated Vesicles

    Deloche, Olivier; Yeung, Bonny G.; Payne, Gregory S.; Schekman, Randy

    2001-01-01

    A native immunoisolation procedure has been used to investigate the role of clathrin-coated vesicles (CCVs) in the transport of vacuolar proteins between the trans-Golgi network (TGN) and the prevacuolar/endosome compartments in the yeast Saccharomyces cerevisiae. We find that Apl2p, one large subunit of the adaptor protein-1 complex, and Vps10p, the carboxypeptidase Y vacuolar protein receptor, are associated with clathrin molecules. Vps10p packaging in CCVs is re...

  15. Construction of a chloroplast protein interaction network and functional mining of photosynthetic proteins in Arabidopsis thaliana

    Qing-Bo Yu; Yong-Lan Cui; Kang Chong; Yi-Xue Li; Yu-Hua Li; Zhongming Zhao; Tie-Liu Shi; Zhong-Nan Yang; Guang Li; Guan Wang; Jing-Chun Sun; Peng-Cheng Wang; Chen Wang; Hua-Ling Mi; Wei-Min Ma; Jian Cui

    2008-01-01

    Chloroplast is a typical plant cell organeUe where photosynthesis takes place.In this study,a total of 1 808 chloroplast core proteins in Arabidopsis thaliana were reliably identified by combining the results of previously published studies and our own predictions.We then constructed a chloroplast protein interaction network primarily based on these core protein interactions.The network had 22 925 protein interaction pairs which involved 2 214 proteins.A total of 160 previously uncharacterized proteins were annotated in this network.The subunits of the photosynthetic complexes were modularized,and the functional relationships among photosystem Ⅰ (PSI),photosystem Ⅱ (PSII),light harvesting complex of photosystem Ⅰ (LHC Ⅰ) and light harvesting complex of photosystem Ⅰ (LHC Ⅱ) could be deduced from the predicted protein interactions in this network.We further confirmed an interaction between an unknown protein AT1G52220 and a photosynthetic subunit PSI-D2 by yeast two-hybrid analysis.Our chloroplast protein interaction network should be useful for functional mining of photosynthetic proteins and investigation of chloroplast-related functions at the systems biology level in Arabidopsis.

  16. Reconstruction of Protein Networks Using Reverse-Phase Protein Array Data.

    von der Heyde, Silvia; Sonntag, Johanna; Kramer, Frank; Bender, Christian; Korf, Ulrike; Beißbarth, Tim

    2016-01-01

    In this chapter, we describe an approach to reconstruct cellular signaling networks based on measurements of protein activation after different stimulation experiments. As experimental platform reverse-phase protein arrays (RPPA) are used. RPPA allow the measurement of proteins and phosphoproteins across many samples in parallel with minimal sample consumption using a panel of highly target protein-specific antibodies. Functional interactions of proteins are modeled using a Boolean network. We describe the Boolean network reconstruction approach ddepn (dynamic deterministic effects propagation networks), which uses time course data to derive protein interactions based on perturbation experiments. We explain how the method works, give a practical application example, and describe how the results can be interpreted. Furthermore prior knowledge on signaling pathways is essential for network reconstruction. Here we describe the use of our software rBiopaxParser to integrate prior knowledge on protein signaling available in public databases. All applied methods are freely available as open-source R software packages. We describe the preparation of RPPA data as well as all relevant programming steps to format the RPPA data, to infer the prior knowledge, and to reconstruct and analyze the protein signaling networks. PMID:26519181

  17. Nck adaptors are positive regulators of the size and sensitivity of the T-cell repertoire.

    Roy, Edwige; Togbe, Dieudonnée; Holdorf, Amy D; Trubetskoy, Dmitry; Nabti, Sabrina; Küblbeck, Günter; Klevenz, Alexandra; Kopp-Schneider, Annette; Leithäuser, Frank; Möller, Peter; Bladt, Friedhelm; Hämmerling, Günter; Arnold, Bernd; Pawson, Tony; Tafuri, Anna

    2010-08-31

    The size and sensitivity of the T-cell repertoire governs the effectiveness of immune responses against invading pathogens. Both are modulated by T-cell receptor (TCR) activity through molecular mechanisms, which remain unclear. Here, we provide genetic evidence that the SH2/SH3 domain containing proteins Nck lower the threshold of T-cell responsiveness. The hallmarks of Nck deletion were T-cell lymphopenia and hyporeactivity to TCR-mediated stimulation. In the absence of the Nck adaptors, peripheral T cells expressing a TCR with low avidity for self-antigens were strongly reduced, whereas an overall impairment of T-cell activation by weak antigenic stimulation was observed. Mechanistically, Nck deletion resulted in a significant decrease in calcium mobilization and ERK phosphorylation upon TCR engagement. Taken together, our findings unveil a crucial role for the Nck adaptors in shaping the T-cell repertoire to ensure maximal antigenic coverage and optimal T cell excitability. PMID:20709959

  18. Creative elements: network-based predictions of active centres in proteins, cellular and social networks

    Csermely, Peter

    2008-01-01

    Active centres and hot spots of proteins have a paramount importance in enzyme action, protein complex formation and drug design. Recently a number of publications successfully applied the analysis of residue networks to predict active centres in proteins. Most real-world networks show a number of properties, such as small-worldness or scale-free degree distribution, which are rather general features of networks from molecules to the society. Based on extensive analogies I propose that the existing findings and methodology enable us to detect active centres in cells, social networks and ecosystems. Members of these active centres are creative elements of the respective networks, which may help them to survive unprecedented, novel challenges, and play a key role in the development, survival and evolvability of complex systems.

  19. Protein diffusion in photopolymerized poly(ethylene glycol) hydrogel networks

    Engberg, Kristin; Frank, Curtis W, E-mail: curt.frank@stanford.edu [Department of Chemical Engineering, Stanford University, 381 North-South Mall, Stauffer III, Stanford, CA 94305 (United States)

    2011-10-15

    In this study, protein diffusion through swollen hydrogel networks prepared from end-linked poly(ethylene glycol)-diacrylate (PEG-DA) was investigated. Hydrogels were prepared via photopolymerization from PEG-DA macromonomer solutions of two molecular weights, 4600 Da and 8000 Da, with three initial solid contents: 20, 33 and 50 wt/wt% PEG. Diffusion coefficients for myoglobin traveling across the hydrogel membrane were determined for all PEG network compositions. The diffusion coefficient depended on PEG molecular weight and initial solid content, with the slowest diffusion occurring through lower molecular weight, high-solid-content networks (D{sub gel} = 0.16 {+-} 0.02 x 10{sup -8} cm{sup 2} s{sup -1}) and the fastest diffusion occurring through higher molecular weight, low-solid-content networks (D{sub gel} = 11.05 {+-} 0.43 x 10{sup -8} cm{sup 2} s{sup -1}). Myoglobin diffusion coefficients increased linearly with the increase of water content within the hydrogels. The permeability of three larger model proteins (horseradish peroxidase, bovine serum albumin and immunoglobulin G) through PEG(8000) hydrogel membranes was also examined, with the observation that globular molecules as large as 10.7 nm in hydrodynamic diameter can diffuse through the PEG network. Protein diffusion coefficients within the PEG hydrogels ranged from one to two orders of magnitude lower than the diffusion coefficients in free water. Network defects were determined to be a significant contributing factor to the observed protein diffusion.

  20. Clustering proteins into families using artificial neural networks.

    Ferrán, E A; Ferrara, P

    1992-02-01

    An artificial neural network was used to cluster proteins into families. The network, composed of 7 x 7 neurons, was trained with the Kohonen unsupervised learning algorithm using, as inputs, matrix patterns derived from the bipeptide composition of 447 proteins, belonging to 13 different families. As a result of the training, and without any a priori indication of the number or composition of the expected families, the network self-organized the activation of its neurons into topologically ordered maps in which almost all the proteins (96.7%) were correctly clustered into the corresponding families. In a second computational experiment, a similar network was trained with one family of the previous learning set (76 cytochrome c sequences). The new neural map clustered these proteins into 25 different neurons (five in the first experiment), wherein phylogenetically related sequences were positioned close to each other. This result shows that the network can adapt the clustering resolution to the complexity of the learning set, a useful feature when working with an unknown number of clusters. Although the learning stage is time consuming, once the topological map is obtained, the classification of new proteins is very fast. Altogether, our results suggest that this novel approach may be a useful tool to organize the search for homologies in large macromolecular databases. PMID:1314686

  1. Neuron-Like Networks Between Ribosomal Proteins Within the Ribosome.

    Poirot, Olivier; Timsit, Youri

    2016-01-01

    From brain to the World Wide Web, information-processing networks share common scale invariant properties. Here, we reveal the existence of neural-like networks at a molecular scale within the ribosome. We show that with their extensions, ribosomal proteins form complex assortative interaction networks through which they communicate through tiny interfaces. The analysis of the crystal structures of 50S eubacterial particles reveals that most of these interfaces involve key phylogenetically conserved residues. The systematic observation of interactions between basic and aromatic amino acids at the interfaces and along the extension provides new structural insights that may contribute to decipher the molecular mechanisms of signal transmission within or between the ribosomal proteins. Similar to neurons interacting through "molecular synapses", ribosomal proteins form a network that suggest an analogy with a simple molecular brain in which the "sensory-proteins" innervate the functional ribosomal sites, while the "inter-proteins" interconnect them into circuits suitable to process the information flow that circulates during protein synthesis. It is likely that these circuits have evolved to coordinate both the complex macromolecular motions and the binding of the multiple factors during translation. This opens new perspectives on nanoscale information transfer and processing. PMID:27225526

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

    Pike Andrew D

    2010-06-01

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

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

    Sandip Chakraborty

    2016-01-01

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

  4. Robustness of indispensable nodes in controlling protein-protein interaction network

    Zhang, Xizhe; Yang, Yunyi

    2016-01-01

    Recently, the structural controllability theory has been introduced to analyze the Protein-Protein Interaction (PPI) network. The indispensable nodes, which their removal increase the number of driver nodes to control the network, are found essential in PPI network. However, the PPI network is far from complete and there may exist many false-positive or false-negative interactions, which promotes us to question: are these indispensable nodes robust to structural change? Here we systematically investigate the robustness of indispensable nodes of PPI network by removing and adding possible interactions. We found that the indispensable nodes are sensitive to the structural change and very few edges can change the type of many indispensable nodes. The finding may promote our understanding to the control principle of PPI network.

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

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

    2014-01-01

    Background One of the central interests of Virology is the identification of host factors that contribute to virus infection. Despite tremendous efforts, the list of factors identified remains limited. With omics techniques, the focus has changed from identifying and thoroughly characterizing individual host factors to the simultaneous analysis of thousands of interactions, framing them on the context of protein-protein interaction networks and of transcriptional regulatory networks. This new...

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

    Ru Shen; Xiaosheng Wang; Chittibabu Guda

    2015-01-01

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

  7. The adaptor molecule CARD9 is essential for tuberculosis control

    Dorhoi, Anca; Desel, Christiane; Yeremeev, Vladimir; Pradl, Lydia; Brinkmann, Volker; Mollenkopf, Hans J; Hanke, Karin; Gross, Olaf; Ruland, Jürgen; Stefan H. E. Kaufmann

    2010-01-01

    The cross talk between host and pathogen starts with recognition of bacterial signatures through pattern recognition receptors (PRRs), which mobilize downstream signaling cascades. We investigated the role of the cytosolic adaptor caspase recruitment domain family, member 9 (CARD9) in tuberculosis. This adaptor was critical for full activation of innate immunity by converging signals downstream of multiple PRRs. Card9(-/-) mice succumbed early after aerosol infection, with higher mycobacteria...

  8. Yeast Gga Coat Proteins Function with Clathrin in Golgi to Endosome Transport

    Costaguta, G; Stefan, C. J.; Bensen, E. S.; Emr, S D; Payne, G S

    2001-01-01

    Gga proteins represent a newly recognized, evolutionarily conserved protein family with homology to the “ear” domain of the clathrin adaptor AP-1 γ subunit. Yeast cells contain two Gga proteins, Gga1p and Gga2p, that have been proposed to act in transport between the trans-Golgi network and endosomes. Here we provide genetic and physical evidence that yeast Gga proteins function in trans-Golgi network clathrin coats. Deletion of Gga2p (gga2Δ), the major Gga protein...

  9. Lists2Networks: Integrated analysis of gene/protein lists

    Ma'ayan Avi

    2010-02-01

    Full Text Available Abstract Background Systems biologists are faced with the difficultly of analyzing results from large-scale studies that profile the activity of many genes, RNAs and proteins, applied in different experiments, under different conditions, and reported in different publications. To address this challenge it is desirable to compare the results from different related studies such as mRNA expression microarrays, genome-wide ChIP-X, RNAi screens, proteomics and phosphoproteomics experiments in a coherent global framework. In addition, linking high-content multilayered experimental results with prior biological knowledge can be useful for identifying functional themes and form novel hypotheses. Results We present Lists2Networks, a web-based system that allows users to upload lists of mammalian genes/proteins onto a server-based program for integrated analysis. The system includes web-based tools to manipulate lists with different set operations, to expand lists using existing mammalian networks of protein-protein interactions, co-expression correlation, or background knowledge co-annotation correlation, as well as to apply gene-list enrichment analyses against many gene-list libraries of prior biological knowledge such as pathways, gene ontology terms, kinase-substrate, microRNA-mRAN, and protein-protein interactions, metabolites, and protein domains. Such analyses can be applied to several lists at once against many prior knowledge libraries of gene-lists associated with specific annotations. The system also contains features that allow users to export networks and share lists with other users of the system. Conclusions Lists2Networks is a user friendly web-based software system expected to significantly ease the computational analysis process for experimental systems biologists employing high-throughput experiments at multiple layers of regulation. The system is freely available at http://www.lists2networks.org.

  10. Context-specific protein network miner - an online system for exploring context-specific protein interaction networks from the literature

    Chowdhary, Rajesh

    2012-04-06

    Background: Protein interaction networks (PINs) specific within a particular context contain crucial information regarding many cellular biological processes. For example, PINs may include information on the type and directionality of interaction (e.g. phosphorylation), location of interaction (i.e. tissues, cells), and related diseases. Currently, very few tools are capable of deriving context-specific PINs for conducting exploratory analysis. Results: We developed a literature-based online system, Context-specific Protein Network Miner (CPNM), which derives context-specific PINs in real-time from the PubMed database based on a set of user-input keywords and enhanced PubMed query system. CPNM reports enriched information on protein interactions (with type and directionality), their network topology with summary statistics (e.g. most densely connected proteins in the network; most densely connected protein-pairs; and proteins connected by most inbound/outbound links) that can be explored via a user-friendly interface. Some of the novel features of the CPNM system include PIN generation, ontology-based PubMed query enhancement, real-time, user-queried, up-to-date PubMed document processing, and prediction of PIN directionality. Conclusions: CPNM provides a tool for biologists to explore PINs. It is freely accessible at http://www.biotextminer.com/CPNM/. © 2012 Chowdhary et al.

  11. Topological Properties of Protein-Protein and Metabolic Interaction Networks of Drosophila melanogaster

    Thanigaimani Rajarathinam; Yen-Han Lin

    2006-01-01

    The underlying principle governing the natural phenomena of life is one of the critical issues receiving due importance in recent years. A key feature of the scale-free architecture is the vitality of the most connected nodes (hubs). The major objective of this article was to analyze the protein-protein and metabolic interaction networks of Drosophila melanogaster by considering the architectural patterns and the consequence of removal of hubs on the topological parameter of the two interaction systems. Analysis showed that both interaction networks follow a scale-free model, establishing the fact that most real world networks,from varied situations, conform to the small world pattern. The average path length showed a two-fold and a three-fold increase (changing from 9.42 to 20.93 and from 5.29 to 17.75, respectively) for the protein-protein and metabolic interaction networks, respectively, due to the deletion of hubs. On the contrary, the arbitrary elimination of nodes did not show any remarkable disparity in the topological parameter of the protein-protein and metabolic interaction networks (average path length: 9.42±0.02 and 5.27±0.01, respectively). This aberrant behavior for the two cases underscores the significance of the most linked nodes to the natural topology of the networks.

  12. Graph theory and stability analysis of protein complex interaction networks.

    Huang, Chien-Hung; Chen, Teng-Hung; Ng, Ka-Lok

    2016-04-01

    Protein complexes play an essential role in many biological processes. Complexes can interact with other complexes to form protein complex interaction network (PCIN) that involves in important cellular processes. There are relatively few studies on examining the interaction topology among protein complexes; and little is known about the stability of PCIN under perturbations. We employed graph theoretical approach to reveal hidden properties and features of four species PCINs. Two main issues are addressed, (i) the global and local network topological properties, and (ii) the stability of the networks under 12 types of perturbations. According to the topological parameter classification, we identified some critical protein complexes and validated that the topological analysis approach could provide meaningful biological interpretations of the protein complex systems. Through the Kolmogorov-Smimov test, we showed that local topological parameters are good indicators to characterise the structure of PCINs. We further demonstrated the effectiveness of the current approach by performing the scalability and data normalization tests. To measure the robustness of PCINs, we proposed to consider eight topological-based perturbations, which are specifically applicable in scenarios of targeted, sustained attacks. We found that the degree-based, betweenness-based and brokering-coefficient-based perturbations have the largest effect on network stability. PMID:26997661

  13. Reconstruction and Application of Protein–Protein Interaction Network

    Tong Hao

    2016-06-01

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

  14. The clathrin adaptor complexes as a paradigm for membrane-associated allostery

    Canagarajah, Bertram J.; Ren, Xuefeng; Bonifacino, Juan S.; Hurley, James H.

    2013-01-01

    The clathrin-associated adaptor protein (AP) complexes AP-1 and AP-2 are two members of a family of heterotetrameric assemblies that connect transmembrane protein cargo to vesicular coats. Cargo binding by AP-1 is activated by the small GTPase Arf1, while AP-2 is activated by the phosphoinositide PI(4,5)P2. The structures of both AP-1 and AP-2 have been determined in their locked and unlocked conformations. The structures show how different activators use different mechanisms to trigger simil...

  15. Network analysis and cross species comparison of protein-protein interaction networks of human, mouse and rat cytochrome P450 proteins that degrade xenobiotics.

    Karthikeyan, Bagavathy Shanmugam; Akbarsha, Mohammad Abdulkader; Parthasarathy, Subbiah

    2016-06-21

    Cytochrome P450 (CYP) enzymes that degrade xenobiotics play a critical role in the metabolism and biotransformation of drugs and xenobiotics in humans as well as experimental animal models such as mouse and rat. These proteins function as a network collectively as well as independently. Though there are several reports on the organization, regulation and functionality of various CYP enzymes at the molecular level, the understanding of organization and functionality of these proteins at the holistic level remain unclear. The objective of this study is to understand the organization and functionality of xenobiotic degrading CYP enzymes of human, mouse and rat using network theory approaches and to study species differences that exist among them at the holistic level. For our analysis, a protein-protein interaction (PPI) network for CYP enzymes of human, mouse and rat was constructed using the STRING database. Topology, centrality, modularity and robustness analyses were performed for our predicted CYP PPI networks that were then validated by comparison with randomly generated network models. Network centrality analyses of CYP PPI networks reveal the central/hub proteins in the network. Modular analysis of the CYP PPI networks of human, mouse and rat resulted in functional clusters. These clusters were subjected to ontology and pathway enrichment analysis. The analyses show that the cluster of the human CYP PPI network is enriched with pathways principally related to xenobiotic/drug metabolism. Endo-xenobiotic crosstalk dominated in mouse and rat CYP PPI networks, and they were highly enriched with endogenous metabolic and signaling pathways. Thus, cross-species comparisons and analyses of human, mouse and rat CYP PPI networks gave insights about species differences that existed at the holistic level. More investigations from both reductionist and holistic perspectives can help understand CYP metabolism and species extrapolation in a much better way. PMID:27194593

  16. The topology of the bacterial co-conserved protein network and its implications for predicting protein function

    Leach Sonia M

    2008-06-01

    Full Text Available Abstract Background Protein-protein interactions networks are most often generated from physical protein-protein interaction data. Co-conservation, also known as phylogenetic profiles, is an alternative source of information for generating protein interaction networks. Co-conservation methods generate interaction networks among proteins that are gained or lost together through evolution. Co-conservation is a particularly useful technique in the compact bacteria genomes. Prior studies in yeast suggest that the topology of protein-protein interaction networks generated from physical interaction assays can offer important insight into protein function. Here, we hypothesize that in bacteria, the topology of protein interaction networks derived via co-conservation information could similarly improve methods for predicting protein function. Since the topology of bacteria co-conservation protein-protein interaction networks has not previously been studied in depth, we first perform such an analysis for co-conservation networks in E. coli K12. Next, we demonstrate one way in which network connectivity measures and global and local function distribution can be exploited to predict protein function for previously uncharacterized proteins. Results Our results showed, like most biological networks, our bacteria co-conserved protein-protein interaction networks had scale-free topologies. Our results indicated that some properties of the physical yeast interaction network hold in our bacteria co-conservation networks, such as high connectivity for essential proteins. However, the high connectivity among protein complexes in the yeast physical network was not seen in the co-conservation network which uses all bacteria as the reference set. We found that the distribution of node connectivity varied by functional category and could be informative for function prediction. By integrating of functional information from different annotation sources and using the

  17. Decoding protein networks during virus entry by quantitative proteomics.

    Gerold, Gisa; Bruening, Janina; Pietschmann, Thomas

    2016-06-15

    Virus entry into host cells relies on interactions between viral and host structures including lipids, carbohydrates and proteins. Particularly, protein-protein interactions between viral surface proteins and host proteins as well as secondary host protein-protein interactions play a pivotal role in coordinating virus binding and uptake. These interactions are dynamic and frequently involve multiprotein complexes. In the past decade mass spectrometry based proteomics methods have reached sensitivities and high throughput compatibilities of genomics methods and now allow the reliable quantitation of proteins in complex samples from limited material. As proteomics provides essential information on the biologically active entity namely the protein, including its posttranslational modifications and its interactions with other proteins, it is an indispensable method in the virologist's toolbox. Here we review protein interactions during virus entry and compare classical biochemical methods to study entry with novel technically advanced quantitative proteomics techniques. We highlight the value of quantitative proteomics in mapping functional virus entry networks, discuss the benefits and limitations and illustrate how the methodology will help resolve unsettled questions in virus entry research in the future. PMID:26365680

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

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

    2015-01-01

    Developing suitable methods for the detection of protein complexes in protein interaction networks continues to be an intriguing area of research. The importance of this objective originates from the fact that protein complexes are key players in most cellular processes. The more complexes we identify, the better we can understand normal as well as abnormal molecular events. Up till now, various computational methods were designed for this purpose. However, despite their notable performance, questions arise regarding potential ways to improve them, in addition to ameliorative guidelines to introduce novel approaches. A close interpretation leads to the assent that the way in which protein interaction networks are initially viewed should be adjusted. These networks are dynamic in reality and it is necessary to consider this fact to enhance the detection of protein complexes. In this paper, we present "DyCluster", a framework to model the dynamic aspect of protein interaction networks by incorporating gene expression data, through biclustering techniques, prior to applying complex-detection algorithms. The experimental results show that DyCluster leads to higher numbers of correctly-detected complexes with better evaluation scores. The high accuracy achieved by DyCluster in detecting protein complexes is a valid argument in favor of the proposed method. DyCluster is also able to detect biologically meaningful protein groups. The code and datasets used in the study are downloadable from https://github.com/emhanna/DyCluster. PMID:26641660

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

    Eileen Marie Hanna

    Full Text Available Developing suitable methods for the detection of protein complexes in protein interaction networks continues to be an intriguing area of research. The importance of this objective originates from the fact that protein complexes are key players in most cellular processes. The more complexes we identify, the better we can understand normal as well as abnormal molecular events. Up till now, various computational methods were designed for this purpose. However, despite their notable performance, questions arise regarding potential ways to improve them, in addition to ameliorative guidelines to introduce novel approaches. A close interpretation leads to the assent that the way in which protein interaction networks are initially viewed should be adjusted. These networks are dynamic in reality and it is necessary to consider this fact to enhance the detection of protein complexes. In this paper, we present "DyCluster", a framework to model the dynamic aspect of protein interaction networks by incorporating gene expression data, through biclustering techniques, prior to applying complex-detection algorithms. The experimental results show that DyCluster leads to higher numbers of correctly-detected complexes with better evaluation scores. The high accuracy achieved by DyCluster in detecting protein complexes is a valid argument in favor of the proposed method. DyCluster is also able to detect biologically meaningful protein groups. The code and datasets used in the study are downloadable from https://github.com/emhanna/DyCluster.

  20. Graphics processing unit-based alignment of protein interaction networks.

    Xie, Jiang; Zhou, Zhonghua; Ma, Jin; Xiang, Chaojuan; Nie, Qing; Zhang, Wu

    2015-08-01

    Network alignment is an important bridge to understanding human protein-protein interactions (PPIs) and functions through model organisms. However, the underlying subgraph isomorphism problem complicates and increases the time required to align protein interaction networks (PINs). Parallel computing technology is an effective solution to the challenge of aligning large-scale networks via sequential computing. In this study, the typical Hungarian-Greedy Algorithm (HGA) is used as an example for PIN alignment. The authors propose a HGA with 2-nearest neighbours (HGA-2N) and implement its graphics processing unit (GPU) acceleration. Numerical experiments demonstrate that HGA-2N can find alignments that are close to those found by HGA while dramatically reducing computing time. The GPU implementation of HGA-2N optimises the parallel pattern, computing mode and storage mode and it improves the computing time ratio between the CPU and GPU compared with HGA when large-scale networks are considered. By using HGA-2N in GPUs, conserved PPIs can be observed, and potential PPIs can be predicted. Among the predictions based on 25 common Gene Ontology terms, 42.8% can be found in the Human Protein Reference Database. Furthermore, a new method of reconstructing phylogenetic trees is introduced, which shows the same relationships among five herpes viruses that are obtained using other methods. PMID:26243827

  1. Characterization of Protein Complexes and Protein Interaction Networks by Mass Spectrometry

    Shevchenko, Anna

    2004-01-01

    The major goal of this study was to develop an experimental proteomics approach for deciphering protein complexes and protein interaction networks in the budding and fission yeasts. Key steps of the employed analytical routine, including the purification of complexes and mass spectrometric identification of their subunits, were investigated in detail. Archiving, storage and handling of polyacylamide gels, visualization of protein bands and their effect on the efficiency of in-gel digestion an...

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

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

    2011-01-01

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

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

    Eileen Marie Hanna; Nazar Zaki; Amr Amin

    2015-01-01

    Developing suitable methods for the detection of protein complexes in protein interaction networks continues to be an intriguing area of research. The importance of this objective originates from the fact that protein complexes are key players in most cellular processes. The more complexes we identify, the better we can understand normal as well as abnormal molecular events. Up till now, various computational methods were designed for this purpose. However, despite their notable performance, ...

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

    Zohar Itzhaki

    2011-01-01

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

  5. Predicting the Secondary Structure of Proteins by Cascading Neural Networks

    Maryam Alirezaee

    2012-11-01

    Full Text Available Protein Secondary Structure Prediction (PSSP is considered as a challenging task in bioinformatics and so many approaches have been proposed in the literature to solve this problem via achieving more accurate prediction results. Accurate prediction of secondary structure is a critical role in deducing tertiary structure of proteins and their functions. Among the proposed approaches to tackle this problem, Artificial Neural Networks (ANNs are considered as one of the successful tools that are widely used in this field. Recently, many efforts have been devoted to modify, improve and combine this methodology with other machine learning methods in order to get better results. In this work, we have proposed a two-stage feed forward neural network for prediction of protein secondary structures. To evaluate our approach, it is applied on RS126 dataset and its results are compared with some other NN-based methods.

  6. AtPIN: Arabidopsis thaliana Protein Interaction Network

    Silva-Filho Marcio C

    2009-12-01

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

  7. Cooperative and independent roles of the Drp1 adaptors Mff, MiD49 and MiD51 in mitochondrial fission.

    Osellame, Laura D; Singh, Abeer P; Stroud, David A; Palmer, Catherine S; Stojanovski, Diana; Ramachandran, Rajesh; Ryan, Michael T

    2016-06-01

    Cytosolic dynamin-related protein 1 (Drp1, also known as DNM1L) is required for both mitochondrial and peroxisomal fission. Drp1-dependent division of these organelles is facilitated by a number of adaptor proteins at mitochondrial and peroxisomal surfaces. To investigate the interplay of these adaptor proteins, we used gene-editing technology to create a suite of cell lines lacking the adaptors MiD49 (also known as MIEF2), MiD51 (also known as MIEF1), Mff and Fis1. Increased mitochondrial connectivity was observed following loss of individual adaptors, and this was further enhanced following the combined loss of MiD51 and Mff. Moreover, loss of adaptors also conferred increased resistance of cells to intrinsic apoptotic stimuli, with MiD49 and MiD51 showing the more prominent role. Using a proximity-based biotin labeling approach, we found close associations between MiD51, Mff and Drp1, but not Fis1. Furthermore, we found that MiD51 can suppress Mff-dependent enhancement of Drp1 GTPase activity. Our data indicates that Mff and MiD51 regulate Drp1 in specific ways to promote mitochondrial fission. PMID:27076521

  8. Systematic discovery of new recognition peptides mediating protein interaction networks.

    2005-12-01

    Full Text Available Many aspects of cell signalling, trafficking, and targeting are governed by interactions between globular protein domains and short peptide segments. These domains often bind multiple peptides that share a common sequence pattern, or "linear motif" (e.g., SH3 binding to PxxP. Many domains are known, though comparatively few linear motifs have been discovered. Their short length (three to eight residues, and the fact that they often reside in disordered regions in proteins makes them difficult to detect through sequence comparison or experiment. Nevertheless, each new motif provides critical molecular details of how interaction networks are constructed, and can explain how one protein is able to bind to very different partners. Here we show that binding motifs can be detected using data from genome-scale interaction studies, and thus avoid the normally slow discovery process. Our approach based on motif over-representation in non-homologous sequences, rediscovers known motifs and predicts dozens of others. Direct binding experiments reveal that two predicted motifs are indeed protein-binding modules: a DxxDxxxD protein phosphatase 1 binding motif with a KD of 22 microM and a VxxxRxYS motif that binds Translin with a KD of 43 microM. We estimate that there are dozens or even hundreds of linear motifs yet to be discovered that will give molecular insight into protein networks and greatly illuminate cellular processes.

  9. Graphical Features of Functional Genes in Human Protein Interaction Network.

    Wang, Pei; Chen, Yao; Lu, Jinhu; Wang, Qingyun; Yu, Xinghuo

    2016-06-01

    With the completion of the human genome project, it is feasible to investigate large-scale human protein interaction network (HPIN) with complex networks theory. Proteins are encoded by genes. Essential, viable, disease, conserved, housekeeping (HK) and tissue-enriched (TE) genes are functional genes, which are organized and functioned via interaction networks. Based on up-to-date data from various databases or literature, two large-scale HPINs and six subnetworks are constructed. We illustrate that the HPINs and most of the subnetworks are sparse, small-world, scale-free, disassortative and with hierarchical modularity. Among the six subnetworks, essential, disease and HK subnetworks are more densely connected than the others. Statistical analysis on the topological structures of the HPIN reveals that the lethal, the conserved, the HK and the TE genes are with hallmark graphical features. Receiver operating characteristic (ROC) curves indicate that the essential genes can be distinguished from the viable ones with accuracy as high as almost 70%. Closeness, semi-local and eigenvector centralities can distinguish the HK genes from the TE ones with accuracy around 82%. Furthermore, the Venn diagram, cluster dendgrams and classifications of disease genes reveal that some classes of disease genes are with hallmark graphical features, especially for cancer genes, HK disease genes and TE disease genes. The findings facilitate the identification of some functional genes via topological structures. The investigations shed some light on the characteristics of the compete interactome, which have potential implications in networked medicine and biological network control. PMID:26841412

  10. ATP binding to p97/VCP D1 domain regulates selective recruitment of adaptors to its proximal N-domain.

    Wei Sheng Chia

    Full Text Available p97/Valosin-containing protein (VCP is a member of the AAA-ATPase family involved in many cellular processes including cell division, intracellular trafficking and extraction of misfolded proteins in endoplasmic reticulum-associated degradation (ERAD. It is a homohexamer with each subunit containing two tandem D1 and D2 ATPase domains and N- and C-terminal regions that function as adaptor protein binding domains. p97/VCP is directed to its many different functional pathways by associating with various adaptor proteins. The regulation of the recruitment of the adaptor proteins remains unclear. Two adaptor proteins, Ufd1/Npl4 and p47, which bind exclusively to the p97/VCP N-domain and direct p97/VCP to either ERAD-related processes or homotypic fusion of Golgi fragments, were studied here. Surface plasmon resonance biosensor-based assays allowed the study of binding kinetics in real time. In competition experiments, it was observed that in the presence of ATP, Ufd1/Npl4 was able to compete more effectively with p47 for binding to p97/VCP. By using non-hydrolysable ATP analogues and the hexameric truncated p97/N-D1 fragment, it was shown that binding rather than hydrolysis of ATP to the proximal D1 domain strengthened the Ufd1/Npl4 association with the N-domain, thus regulating the recruitment of either Ufd1/Npl4 or p47. This novel role of ATP and an assigned function to the D1 AAA-ATPase domain link the multiple functions of p97/VCP to the metabolic status of the cell.

  11. Integrated cellular network of transcription regulations and protein-protein interactions

    Chen Bor-Sen

    2010-03-01

    Full Text Available Abstract Background With the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway. Results In this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated. Conclusions We successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology.

  12. Protein thermal denaturation is modulated by central residues in the protein structure network.

    Souza, Valquiria P; Ikegami, Cecília M; Arantes, Guilherme M; Marana, Sandro R

    2016-03-01

    Network structural analysis, known as residue interaction networks or graphs (RIN or RIG, respectively) or protein structural networks or graphs (PSN or PSG, respectively), comprises a useful tool for detecting important residues for protein function, stability, folding and allostery. In RIN, the tertiary structure is represented by a network in which residues (nodes) are connected by interactions (edges). Such structural networks have consistently presented a few central residues that are important for shortening the pathways linking any two residues in a protein structure. To experimentally demonstrate that central residues effectively participate in protein properties, mutations were directed to seven central residues of the β-glucosidase Sfβgly (β-d-glucoside glucohydrolase; EC 3.2.1.21). These mutations reduced the thermal stability of the enzyme, as evaluated by changes in transition temperature (Tm ) and the denaturation rate at 45 °C. Moreover, mutations directed to the vicinity of a central residue also caused significant decreases in the Tm of Sfβgly and clearly increased the unfolding rate constant at 45 °C. However, mutations at noncentral residues or at surrounding residues did not affect the thermal stability of Sfβgly. Therefore, the data reported in the present study suggest that the perturbation of the central residues reduced the stability of the native structure of Sfβgly. These results are in agreement with previous findings showing that networks are robust, whereas attacks on central nodes cause network failure. Finally, the present study demonstrates that central residues underlie the functional properties of proteins. PMID:26785700

  13. Protein Kinase C Epsilon and Genetic Networks in Osteosarcoma Metastasis

    Goudarzi, Atta, E-mail: atta.goudarzi@utoronto.ca [Department of Molecular Genetics, University of Toronto, 1 King’s College Circle, Toronto, ON M5S 1A8 (Canada); Samuel Lunenfeld Research Institute, Mount Sinai Hospital, 600 University Ave., Toronto, ON M5G 1X5 (Canada); Gokgoz, Nalan; Gill, Mona; Pinnaduwage, Dushanthi [Samuel Lunenfeld Research Institute, Mount Sinai Hospital, 600 University Ave., Toronto, ON M5G 1X5 (Canada); Merico, Daniele [The Centre for Applied Genomics, The Hospital for Sick Children, MaRS Centre-East Tower, 101 College Street Rm.14-701, Toronto, ON M5G 1L7 (Canada); Wunder, Jay S. [Samuel Lunenfeld Research Institute, Mount Sinai Hospital, 600 University Ave., Toronto, ON M5G 1X5 (Canada); Andrulis, Irene L. [Department of Molecular Genetics, University of Toronto, 1 King’s College Circle, Toronto, ON M5S 1A8 (Canada); Samuel Lunenfeld Research Institute, Mount Sinai Hospital, 600 University Ave., Toronto, ON M5G 1X5 (Canada)

    2013-04-08

    Osteosarcoma (OS) is the most common primary malignant tumor of the bone, and pulmonary metastasis is the most frequent cause of OS mortality. The aim of this study was to discover and characterize genetic networks differentially expressed in metastatic OS. Expression profiling of OS tumors, and subsequent supervised network analysis, was performed to discover genetic networks differentially activated or organized in metastatic OS compared to localized OS. Broad trends among the profiles of metastatic tumors include aberrant activity of intracellular organization and translation networks, as well as disorganization of metabolic networks. The differentially activated PRKCε-RASGRP3-GNB2 network, which interacts with the disorganized DLG2 hub, was also found to be differentially expressed among OS cell lines with differing metastatic capacity in xenograft models. PRKCε transcript was more abundant in some metastatic OS tumors; however the difference was not significant overall. In functional studies, PRKCε was not found to be involved in migration of M132 OS cells, but its protein expression was induced in M112 OS cells following IGF-1 stimulation.

  14. Protein Kinase C Epsilon and Genetic Networks in Osteosarcoma Metastasis

    Osteosarcoma (OS) is the most common primary malignant tumor of the bone, and pulmonary metastasis is the most frequent cause of OS mortality. The aim of this study was to discover and characterize genetic networks differentially expressed in metastatic OS. Expression profiling of OS tumors, and subsequent supervised network analysis, was performed to discover genetic networks differentially activated or organized in metastatic OS compared to localized OS. Broad trends among the profiles of metastatic tumors include aberrant activity of intracellular organization and translation networks, as well as disorganization of metabolic networks. The differentially activated PRKCε-RASGRP3-GNB2 network, which interacts with the disorganized DLG2 hub, was also found to be differentially expressed among OS cell lines with differing metastatic capacity in xenograft models. PRKCε transcript was more abundant in some metastatic OS tumors; however the difference was not significant overall. In functional studies, PRKCε was not found to be involved in migration of M132 OS cells, but its protein expression was induced in M112 OS cells following IGF-1 stimulation

  15. Protein-protein interaction networks: unraveling the wiring of molecular machines within the cell.

    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. PMID:22908212

  16. Optimized Adaptor Polymerase Chain Reaction Method for Efficient Genomic Walking

    Peng XU; Rui-Ying HU; Xiao-Yan DING

    2006-01-01

    Genomic walking is one of the most useful approaches in genome-related research. Three kinds of PCR-based methods are available for this purpose. However, none of them has been generally applied because they are either insensitive or inefficient. Here we present an efficient PCR protocol, an optimized adaptor PCR method for genomic walking. Using a combination of a touchdown PCR program and a special adaptor, the optimized adaptor PCR protocol achieves high sensitivity with low background noise. By applying this protocol, the insertion sites of a gene trap mouse line and two gene promoters from the incompletely sequenced Xenopus laevis genome were successfully identified with high efficiency. The general application of this protocol in genomic walking was promising.

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

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

    2011-01-01

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

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

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

    2011-01-01

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

  19. Improving Protein Fold Recognition by Deep Learning Networks

    Jo, Taeho; Hou, Jie; Eickholt, Jesse; Cheng, Jianlin

    2015-12-01

    For accurate recognition of protein folds, a deep learning network method (DN-Fold) was developed to predict if a given query-template protein pair belongs to the same structural fold. The input used stemmed from the protein sequence and structural features extracted from the protein pair. We evaluated the performance of DN-Fold along with 18 different methods on Lindahl’s benchmark dataset and on a large benchmark set extracted from SCOP 1.75 consisting of about one million protein pairs, at three different levels of fold recognition (i.e., protein family, superfamily, and fold) depending on the evolutionary distance between protein sequences. The correct recognition rate of ensembled DN-Fold for Top 1 predictions is 84.5%, 61.5%, and 33.6% and for Top 5 is 91.2%, 76.5%, and 60.7% at family, superfamily, and fold levels, respectively. We also evaluated the performance of single DN-Fold (DN-FoldS), which showed the comparable results at the level of family and superfamily, compared to ensemble DN-Fold. Finally, we extended the binary classification problem of fold recognition to real-value regression task, which also show a promising performance. DN-Fold is freely available through a web server at http://iris.rnet.missouri.edu/dnfold.

  20. Sorting of the Alzheimer's Disease Amyloid Precursor Protein Mediated by the AP-4 Complex

    Burgos, Patricia V.; Mardones, Gonzalo A.; Rojas, Adriana L.; daSilva, Luis L.P.; Prabhu, Yogikala; Hurley, James H.; Bonifacino, Juan S. (NIH)

    2010-08-12

    Adaptor protein 4 (AP-4) is the most recently discovered and least well-characterized member of the family of heterotetrameric adaptor protein (AP) complexes that mediate sorting of transmembrane cargo in post-Golgi compartments. Herein, we report the interaction of an YKFFE sequence from the cytosolic tail of the Alzheimer's disease amyloid precursor protein (APP) with the {micro}4 subunit of AP-4. Biochemical and X-ray crystallographic analyses reveal that the properties of the APP sequence and the location of the binding site on 4 are distinct from those of other signal-adaptor interactions. Disruption of the APP-AP-4 interaction decreases localization of APP to endosomes and enhances {gamma}-secretase-catalyzed cleavage of APP to the pathogenic amyloid-{beta} peptide. These findings demonstrate that APP and AP-4 engage in a distinct type of signal-adaptor interaction that mediates transport of APP from the trans-Golgi network (TGN) to endosomes, thereby reducing amyloidogenic processing of the protein.

  1. Prediction and systematic study of protein-protein interaction networks of Leptospira interrogans

    SUN Jingchun; XU Jinlin; CAO Jianping; LIU Qi; GUO Xiaokui; SHI Tieliu; LI Yixue

    2006-01-01

    Leptospira interrogans serovar Lai is a pathogenic bacterium that causes a spirochetal zoonosis in humans and some animals. With its complete genome sequence available, it is possible to analyze protein-protein interactions from a whole- genome standpoint. Here we combine four recently developed computational approaches (gene fusion method, gene neighbor method, phylogenetic profiles method, and operon method) to predict protein-pro- tein interaction networks of Leptospira interrogans strain Lai. Through comprehensive analysis on in- teractions among proteins of motility and chemotaxis system, signal transduction, lipopolysaccaride bio- synthesis and a series of proteins related to adhesion and invasion, we provided information for further studying on its pathogenic mechanism. In addition, we also assigned 203 previously uncharacterized proteins with possible functions based on the known functions of its interacting partners. This work is helpful for further investigating L. interrogans strain Lai.

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

    Eric A Yen

    2014-05-01

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

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

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

    2014-05-01

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

  4. In vitro and in vivo Analysis of the Binding of the C Terminus of the HDL Receptor Scavenger Receptor Class B type I (SR-BI) to the PDZ1 Domain of its Cytoplasmic Adaptor Protein PDZK1

    O Kocher; G Birrane; K Tsukamoto; S Fenske; A Yesilaltay; R Pal; K Daniels; J Ladias; M Krieger

    2011-12-31

    The PDZ1 domain of the four PDZ domain-containing protein PDZK1 has been reported to bind the C terminus of the HDL receptor scavenger receptor class B, type I (SR-BI), and to control hepatic SR-BI expression and function. We generated wild-type (WT) and mutant murine PDZ1 domains, the mutants bearing single amino acid substitutions in their carboxylate binding loop (Lys(14)-Xaa(4)-Asn(19)-Tyr-Gly-Phe-Phe-Leu(24)), and measured their binding affinity for a 7-residue peptide corresponding to the C terminus of SR-BI ((503)VLQEAKL(509)). The Y20A and G21Y substitutions abrogated all binding activity. Surprisingly, binding affinities (K(d)) of the K14A and F22A mutants were 3.2 and 4.0 ?M, respectively, similar to 2.6 ?M measured for the WT PDZ1. To understand these findings, we determined the high resolution structure of WT PDZ1 bound to a 5-residue sequence from the C-terminal SR-BI ((505)QEAKL(509)) using x-ray crystallography. In addition, we incorporated the K14A and Y20A substitutions into full-length PDZK1 liver-specific transgenes and expressed them in WT and PDZK1 knock-out mice. In WT mice, the transgenes did not alter endogenous hepatic SR-BI protein expression (intracellular distribution or amount) or lipoprotein metabolism (total plasma cholesterol, lipoprotein size distribution). In PDZK1 knock-out mice, as expected, the K14A mutant behaved like wild-type PDZK1 and completely corrected their hepatic SR-BI and plasma lipoprotein abnormalities. Unexpectedly, the 10-20-fold overexpressed Y20A mutant also substantially, but not completely, corrected these abnormalities. The results suggest that there may be an additional site(s) within PDZK1 that bind(s) SR-BI and mediate(s) productive SR-BI-PDZK1 interaction previously attributed exclusively to the canonical binding of the C-terminal SR-BI to PDZ1.

  5. Cytosol- and clathrin-dependent stimulation of endocytosis in vitro by purified adaptors

    1992-01-01

    Using stage-specific assays for receptor-mediated endocytosis of transferrin (Tfn) into perforated A431 cells we show that purified adaptors stimulate coated pit assembly and ligand sequestration into deeply invaginated coated pits. Late events in endocytosis involving membrane fission and coated vesicle budding which lead to the internalization of Tfn are unaffected. AP2, plasma membrane adaptors, are active at physiological concentrations, whereas AP1, Golgi adaptors, are inactive. Adaptor-...

  6. Systematic discovery of new recognition peptides mediating protein interaction networks

    Neduva, Victor; Linding, Rune; Su-Angrand, Isabelle;

    2005-01-01

    Many aspects of cell signalling, trafficking, and targeting are governed by interactions between globular protein domains and short peptide segments. These domains often bind multiple peptides that share a common sequence pattern, or "linear motif" (e.g., SH3 binding to PxxP). Many domains are...... that binds Translin with a KD of 43 microM. We estimate that there are dozens or even hundreds of linear motifs yet to be discovered that will give molecular insight into protein networks and greatly illuminate cellular processes.Many aspects of cell signalling, trafficking, and targeting are governed...... known, though comparatively few linear motifs have been discovered. Their short length (three to eight residues), and the fact that they often reside in disordered regions in proteins makes them difficult to detect through sequence comparison or experiment. Nevertheless, each new motif provides critical...

  7. Information theory in systems biology. Part II: protein-protein interaction and signaling networks.

    Mousavian, Zaynab; Díaz, José; Masoudi-Nejad, Ali

    2016-03-01

    By the development of information theory in 1948 by Claude Shannon to address the problems in the field of data storage and data communication over (noisy) communication channel, it has been successfully applied in many other research areas such as bioinformatics and systems biology. In this manuscript, we attempt to review some of the existing literatures in systems biology, which are using the information theory measures in their calculations. As we have reviewed most of the existing information-theoretic methods in gene regulatory and metabolic networks in the first part of the review, so in the second part of our study, the application of information theory in other types of biological networks including protein-protein interaction and signaling networks will be surveyed. PMID:26691180

  8. A liquid crystal of ascorbyl palmitate, used as vaccine platform, provides sustained release of antigen and has intrinsic pro-inflammatory and adjuvant activities which are dependent on MyD88 adaptor protein.

    Sánchez Vallecillo, María F; Minguito de la Escalera, María M; Aguirre, María V; Ullio Gamboa, Gabriela V; Palma, Santiago D; González-Cintado, Leticia; Chiodetti, Ana L; Soldano, Germán; Morón, Gabriel; Allemandi, Daniel A; Ardavín, Carlos; Pistoresi-Palencia, María C; Maletto, Belkys A

    2015-09-28

    Modern subunit vaccines require the development of new adjuvant strategies. Recently, we showed that CpG-ODN formulated with a liquid crystal nanostructure formed by self-assembly of 6-O-ascorbyl palmitate (Coa-ASC16) is an attractive system for promoting an antigen-specific immune response to weak antigens. Here, we showed that after subcutaneous injection of mice with near-infrared fluorescent dye-labeled OVA antigen formulated with Coa-ASC16, the dye-OVA was retained at the injection site for a longer period than when soluble dye-OVA was administered. Coa-ASC16 alone elicited a local inflammation, but how this material triggers this response has not been described yet. Although it is known that some materials used as a platform are not immunologically inert, very few studies have directly focused on this topic. In this study, we explored the underlying mechanisms concerning the interaction between Coa-ASC16 and the immune system and we found that the whole inflammatory response elicited by Coa-ASC16 (leukocyte recruitment and IL-1β, IL-6 and IL-12 production) was dependent on the MyD88 protein. TLR2, TLR4, TLR7 and NLRP3-inflammasome signaling were not required for induction of this inflammatory response. Coa-ASC16 induced local release of self-DNA, and in TLR9-deficient mice IL-6 production was absent. In addition, Coa-ASC16 revealed an intrinsic adjuvant activity which was affected by MyD88 and IL-6 absence. Taken together these results indicate that Coa-ASC16 used as a vaccine platform is effective due to the combination of the controlled release of antigen and its intrinsic pro-inflammatory activity. Understanding how Coa-ASC16 works might have significant implications for rational vaccine design. PMID:26188153

  9. Phospho-tyrosine dependent protein–protein interaction network

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

    2015-01-01

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

  10. Validation of protein models by a neural network approach

    Fantucci Piercarlo

    2008-01-01

    Full Text Available Abstract Background The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure refinement, which has been recently identified as one of the bottlenecks limiting the quality and usefulness of protein structure prediction. Results In this contribution, we present a computational method (Artificial Intelligence Decoys Evaluator: AIDE which is able to consistently discriminate between correct and incorrect protein models. In particular, the method is based on neural networks that use as input 15 structural parameters, which include energy, solvent accessible surface, hydrophobic contacts and secondary structure content. The results obtained with AIDE on a set of decoy structures were evaluated using statistical indicators such as Pearson correlation coefficients, Znat, fraction enrichment, as well as ROC plots. It turned out that AIDE performances are comparable and often complementary to available state-of-the-art learning-based methods. Conclusion In light of the results obtained with AIDE, as well as its comparison with available learning-based methods, it can be concluded that AIDE can be successfully used to evaluate the quality of protein structures. The use of AIDE in combination with other evaluation tools is expected to further enhance protein refinement efforts.

  11. DMPD: The SAP family of adaptors in immune regulation. [Dynamic Macrophage Pathway CSML Database

    Full Text Available 15541655 The SAP family of adaptors in immune regulation. Latour S, Veillette A. Se...min Immunol. 2004 Dec;16(6):409-19. (.png) (.svg) (.html) (.csml) Show The SAP family of adaptors in immune ...regulation. PubmedID 15541655 Title The SAP family of adaptors in immune regulation. Authors Latour S, Veill

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

    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. PMID:25303791

  13. Development and implementation of an algorithm for detection of protein complexes in large interaction networks

    Kanaya Shigehiko

    2006-04-01

    Full Text Available Abstract Background After complete sequencing of a number of genomes the focus has now turned to proteomics. Advanced proteomics technologies such as two-hybrid assay, mass spectrometry etc. are producing huge data sets of protein-protein interactions which can be portrayed as networks, and one of the burning issues is to find protein complexes in such networks. The enormous size of protein-protein interaction (PPI networks warrants development of efficient computational methods for extraction of significant complexes. Results This paper presents an algorithm for detection of protein complexes in large interaction networks. In a PPI network, a node represents a protein and an edge represents an interaction. The input to the algorithm is the associated matrix of an interaction network and the outputs are protein complexes. The complexes are determined by way of finding clusters, i. e. the densely connected regions in the network. We also show and analyze some protein complexes generated by the proposed algorithm from typical PPI networks of Escherichia coli and Saccharomyces cerevisiae. A comparison between a PPI and a random network is also performed in the context of the proposed algorithm. Conclusion The proposed algorithm makes it possible to detect clusters of proteins in PPI networks which mostly represent molecular biological functional units. Therefore, protein complexes determined solely based on interaction data can help us to predict the functions of proteins, and they are also useful to understand and explain certain biological processes.

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

    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.

  15. Molecular Architecture of Spinal Cord Injury Protein Interaction Network.

    Ali Alawieh

    Full Text Available Spinal cord injury (SCI is associated with complex pathophysiological processes that follow the primary traumatic event and determine the extent of secondary damage and functional recovery. Numerous reports have used global and hypothesis-driven approaches to identify protein changes that contribute to the overall pathology of SCI in an effort to identify potential therapeutic interventions. In this study, we use a semi-automatic annotation approach to detect terms referring to genes or proteins dysregulated in the SCI literature and develop a curated SCI interactome. Network analysis of the SCI interactome revealed the presence of a rich-club organization corresponding to a "powerhouse" of highly interacting hub-proteins. Studying the modular organization of the network have shown that rich-club proteins cluster into modules that are specifically enriched for biological processes that fall under the categories of cell death, inflammation, injury recognition and systems development. Pathway analysis of the interactome and the rich-club revealed high similarity indicating the role of the rich-club proteins as hubs of the most prominent pathways in disease pathophysiology and illustrating the centrality of pro-and anti-survival signal competition in the pathology of SCI. In addition, evaluation of centrality measures of single nodes within the rich-club have revealed that neuronal growth factor (NGF, caspase 3, and H-Ras are the most central nodes and potentially an interesting targets for therapy. Our integrative approach uncovers the molecular architecture of SCI interactome, and provide an essential resource for evaluating significant therapeutic candidates.

  16. Category theoretic analysis of hierarchical protein materials and social networks

    Spivak, David I; Buehler, Markus J

    2011-01-01

    Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we review an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a "concept web" or "semantic network" except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other ologs. We consider a simple example of an alpha-helical and an amyloid-like protein filament subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog f...

  17. Convolutional neural network architectures for predicting DNA–protein binding

    Zeng, Haoyang; Edwards, Matthew D.; Liu, Ge; Gifford, David K.

    2016-01-01

    Motivation: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications. Results: We present a systematic exploration of CNN architectures for predicting DNA sequence binding using a large compendium of transcription factor datasets. We identify the best-performing architectures by varying CNN width, depth and pooling designs. We find that adding convolutional kernels to a network is important for motif-based tasks. We show the benefits of CNNs in learning rich higher-order sequence features, such as secondary motifs and local sequence context, by comparing network performance on multiple modeling tasks ranging in difficulty. We also demonstrate how careful construction of sequence benchmark datasets, using approaches that control potentially confounding effects like positional or motif strength bias, is critical in making fair comparisons between competing methods. We explore how to establish the sufficiency of training data for these learning tasks, and we have created a flexible cloud-based framework that permits the rapid exploration of alternative neural network architectures for problems in computational biology. Availability and Implementation: All the models analyzed are available at http://cnn.csail.mit.edu. Contact: gifford@mit.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307608

  18. Quantitation, network and function of protein phosphorylation in plant cell

    Lin eZHU

    2013-01-01

    Full Text Available Protein phosphorylation is one of the most important post-translational modifications (PTMs as it participates in regulating various cellular processes and biological functions. It is therefore crucial to identify phosphorylated proteins to construct a phosphor-relay network, and eventually to understand the underlying molecular regulatory mechanism in response to both internal and external stimuli. The changes in phosphorylation status at these novel phosphosites can be accurately measured using a 15N-stable isotopic labeling in Arabidopsis (SILIA quantitative proteomic approach in a high-throughput manner. One of the unique characteristics of the SILIA quantitative phosphoproteomic approach is the preservation of native PTM status on protein during the entire peptide preparation procedure. Evolved from SILIA is another quantitative PTM proteomic approach, AQUIP (absolute quantitation of isoforms of post-translationally modified proteins, which was developed by combining the advantages of targeted proteomics with SILIA. Bioinformatics-based phosphorylation site prediction coupled with an MS-based in vitro kinase assay is an additional way to extend the capability of phosphosite identification from the total cellular protein. The combined use of SILIA and AQUIP provides a novel strategy for molecular systems biological study and for investigation of in vivo biological functions of these phosphoprotein isoforms and combinatorial codes of PTMs.

  19. Gene, protein and network of male sterility in rice

    Wang eKun

    2013-04-01

    Full Text Available Rice is one of the most important model crop plants whose heterosis has been well exploited in commercial hybrid seed production via a variety of types of male sterile lines. Hybrid rice cultivation area is steadily expanding around the world, especially in Southern Asia. Characterization of genes and proteins related to male sterility aims to understand how and why the male sterility occurs, and which proteins are the key players for microspores abortion. Recently, a series of genes and proteins related to cytoplasmic male sterility, photoperiod sensitive male sterility, self-incompatibility and other types of microspores deterioration have been characterized through genetics or proteomics. Especially the latter, offers us a powerful and high throughput approach to discern the novel proteins involving in male-sterile pathways which may help us to breed artificial male-sterile system. This represents an alternative tool to meet the critical challenge of further development of hybrid rice. In this paper, we reviewed the recent developments in our understanding of male sterility in rice hybrid production across gene, protein and integrated network levels, and also, present a perspective on the engineering of male sterile lines for hybrid rice production.

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

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

    2011-01-01

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

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

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

    2009-01-01

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

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

    Nandy, Subir Kumar; Jouhten, Paula; Nielsen, Jens

    2010-01-01

    BACKGROUND: Several protein-protein interaction studies have been performed for the yeast Saccharomyces cerevisiae using different high-throughput experimental techniques. All these results are collected in the BioGRID database and the SGD database provide detailed annotation of the different...... proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives. RESULTS: Here we describe an annotated reconstruction of the protein-protein interactions around four key nutrient-sensing and...... metabolic regulatory signal transduction pathways (STP) operating in Saccharomyces cerevisiae. The reconstructed STP network includes a full protein-protein interaction network including the key nodes Snf1, Tor1, Hog1 and Pka1. The network includes a total of 623 structural open reading frames (ORFs) and...

  3. Spiral biasing adaptor for use in Si drift detectors and Si drift detector arrays

    Li, Zheng; Chen, Wei

    2016-07-05

    A drift detector array, preferably a silicon drift detector (SDD) array, that uses a low current biasing adaptor is disclosed. The biasing adaptor is customizable for any desired geometry of the drift detector single cell with minimum drift time of carriers. The biasing adaptor has spiral shaped ion-implants that generate the desired voltage profile. The biasing adaptor can be processed on the same wafer as the drift detector array and only one biasing adaptor chip/side is needed for one drift detector array to generate the voltage profiles on the front side and back side of the detector array.

  4. Competitive and Cooperative Interactions Mediate RNA Transfer from Herpesvirus Saimiri ORF57 to the Mammalian Export Adaptor ALYREF

    Tunnicliffe, Richard B.; Hautbergue, Guillaume M.; Wilson, Stuart A.; Priti Kalra; Golovanov, Alexander P.

    2014-01-01

    The essential herpesvirus adaptor protein HVS ORF57, which has homologs in all other herpesviruses, promotes viral mRNA export by utilizing the cellular mRNA export machinery. ORF57 protein specifically recognizes viral mRNA transcripts, and binds to proteins of the cellular transcription-export (TREX) complex, in particular ALYREF. This interaction introduces viral mRNA to the NXF1 pathway, subsequently directing it to the nuclear pore for export to the cytoplasm. Here we have used a range o...

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

    Nielsen Jens

    2010-05-01

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

  6. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-11-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

  7. Protein networks in induced sputum from smokers and COPD patients

    Baraniuk JN

    2015-09-01

    Full Text Available James N Baraniuk,1 Begona Casado,1 Lewis K Pannell,2 Peter B McGarvey,3 Piera Boschetto,4 Maurizio Luisetti,5,† Paolo Iadarola6 1Division of Rheumatology, Immunology and Allergy, Georgetown University, Washington, DC, 2Proteomics and Mass Spectrometry Laboratory, Mitchell Cancer Center, University of South Alabama, Mobile, AL, 3Innovation Center for Biomedical Informatics, Georgetown University, Washington, DC, USA; 4Department of Medical Sciences, University of Ferrara, Ferrara, 5SC Pneumologia, Dipartimento Medicina Molecolare, Fondazione IRCCS Policlinico San Matteo, 6Lazzaro Spallanzani Department of Biology and Biotechnology, University of Pavia, Pavia, Italy †Maurizio Luisetti passed away on October 20, 2014 Rationale: Subtypes of cigarette smoke-induced disease affect different lung structures and may have distinct pathophysiological mechanisms. Objective: To determine if proteomic classification of the cellular and vascular origins of sputum proteins can characterize these mechanisms and phenotypes. Subjects and methods: Individual sputum specimens from lifelong nonsmokers (n=7 and smokers with normal lung function (n=13, mucous hypersecretion with normal lung function (n=11, obstructed airflow without emphysema (n=15, and obstruction plus emphysema (n=10 were assessed with mass spectrometry. Data reduction, logarithmic transformation of spectral counts, and Cytoscape network-interaction analysis were performed. The original 203 proteins were reduced to the most informative 50. Sources were secretory dimeric IgA, submucosal gland serous and mucous cells, goblet and other epithelial cells, and vascular permeability. Results: Epithelial proteins discriminated nonsmokers from smokers. Mucin 5AC was elevated in healthy smokers and chronic bronchitis, suggesting a continuum with the severity of hypersecretion determined by mechanisms of goblet-cell hyperplasia. Obstructed airflow was correlated with glandular proteins and lower levels of

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

    Thomas Wallach

    2013-03-01

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

  9. The role of exon shuffling in shaping protein-protein interaction networks

    França Gustavo S

    2010-12-01

    Full Text Available Abstract Background Physical protein-protein interaction (PPI is a critical phenomenon for the function of most proteins in living organisms and a significant fraction of PPIs are the result of domain-domain interactions. Exon shuffling, intron-mediated recombination of exons from existing genes, is known to have been a major mechanism of domain shuffling in metazoans. Thus, we hypothesized that exon shuffling could have a significant influence in shaping the topology of PPI networks. Results We tested our hypothesis by compiling exon shuffling and PPI data from six eukaryotic species: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Cryptococcus neoformans and Arabidopsis thaliana. For all four metazoan species, genes enriched in exon shuffling events presented on average higher vertex degree (number of interacting partners in PPI networks. Furthermore, we verified that a set of protein domains that are simultaneously promiscuous (known to interact to multiple types of other domains, self-interacting (able to interact with another copy of themselves and abundant in the genomes presents a stronger signal for exon shuffling. Conclusions Exon shuffling appears to have been a recurrent mechanism for the emergence of new PPIs along metazoan evolution. In metazoan genomes, exon shuffling also promoted the expansion of some protein domains. We speculate that their promiscuous and self-interacting properties may have been decisive for that expansion.

  10. A membrane protein / signaling protein interaction network for Arabidopsis version AMPv2

    Sylvie Lalonde

    2010-09-01

    Full Text Available Interactions between membrane proteins and the soluble fraction are essential for signal transduction and for regulating nutrient transport. To gain insights into the membrane-based interactome, 3,852 open reading frames (ORFs out of a target list of 8,383 representing membrane and signaling proteins from Arabidopsis thaliana were cloned into a Gateway compatible vector. The mating-based split-ubiquitin system was used to screen for potential protein-protein interactions (pPPIs among 490 Arabidopsis ORFs. A binary robotic screen between 142 receptor-like kinases, 72 transporters, 57 soluble protein kinases and phosphatases, 40 glycosyltransferases, 95 proteins of various functions and 89 proteins with unknown function detected 387 out of 90,370 possible PPIs. A secondary screen confirmed 343 (of 387 pPPIs between 179 proteins, yielding a scale-free network (r2=0.863. Eighty of 142 transmembrane receptor-like kinases (RLK tested positive, identifying three homomers, 63 heteromers and 80 pPPIs with other proteins. Thirty-one out of 142 RLK interactors (including RLKs had previously been found to be phosphorylated; thus interactors may be substrates for respective RLKs. None of the pPPIs described here had been reported in the major interactome databases, including potential interactors of G protein-coupled receptors, phospholipase C, and AMT ammonium transporters. Two RLKs found as putative interactors of AMT1;1 were independently confirmed using a split luciferase assay in Arabidopsis protoplasts. These RLKs may be involved in ammonium-dependent phosphorylation of the C-terminus and regulation of ammonium uptake activity. The robotic screening method established here will enable a systematic analysis of membrane protein interactions in fungi, plants and metazoa.

  11. Visualization of protein interaction networks: problems and solutions

    Agapito Giuseppe

    2013-01-01

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

  12. Protein Interaction Network of Arabidopsis thaliana Female Gametophyte Development Identifies Novel Proteins and Relations

    Hosseinpour, Batool; HajiHoseini, Vahid; Kashfi, Rafieh; Ebrahimie, Esmaeil; Hemmatzadeh, Farhid

    2012-01-01

    Although the female gametophyte in angiosperms consists of just seven cells, it has a complex biological network. In this study, female gametophyte microarray data from Arabidopsis thaliana were integrated into the Arabidopsis interactome database to generate a putative interaction map of the female gametophyte development including proteome map based on biological processes and molecular functions of proteins. Biological and functional groups as well as topological characteristics of the net...

  13. Motors and Adaptors : Transport Regulation within Neurons

    van Spronsen, C.S.A.M.

    2012-01-01

    Human thoughts and behavior are the outcome of communication between neurons in our brains. There is an entire world inside each of these neurons where transactions are established and meeting points are set. By using molecular motors to transport proteins and organelles along cytoskeletal tracks, neurons create the internal order of the bustling community of macromolecules. Given the challenging geometry of the neuron, the mechanisms that deliver fuel and materials to sustain the distant syn...

  14. Limitations of Gene Duplication Models: Evolution of Modules in Protein Interaction Networks

    Frank Emmert-Streib

    2012-01-01

    It has been generally acknowledged that the module structure of protein interaction networks plays a crucial role with respect to the functional understanding of these networks. In this paper, we study evolutionary aspects of the module structure of protein interaction networks, which forms a mesoscopic level of description with respect to the architectural principles of networks. The purpose of this paper is to investigate limitations of well known gene duplication models by showing that the...

  15. Gene Prioritization by Integrated Analysis of Protein Structural and Network Topological Properties for the Protein-Protein Interaction Network of Neurological Disorders

    Yashna Paul

    2016-01-01

    Full Text Available Neurological disorders are known to show similar phenotypic manifestations like anxiety, depression, and cognitive impairment. There is a need to identify shared genetic markers and molecular pathways in these diseases, which lead to such comorbid conditions. Our study aims to prioritize novel genetic markers that might increase the susceptibility of patients affected with one neurological disorder to other diseases with similar manifestations. Identification of pathways involving common candidate markers will help in the development of improved diagnosis and treatments strategies for patients affected with neurological disorders. This systems biology study for the first time integratively uses 3D-structural protein interface descriptors and network topological properties that characterize proteins in a neurological protein interaction network, to aid the identification of genes that are previously not known to be shared between these diseases. Results of protein prioritization by machine learning have identified known as well as new genetic markers which might have direct or indirect involvement in several neurological disorders. Important gene hubs have also been identified that provide an evidence for shared molecular pathways in the neurological disease network.

  16. Illuminating spatial and temporal organization of protein interaction networks by mass spectrometry-based proteomics

    Jiwen eYang; Sebastian Alexander Wagner; Petra eBeli

    2015-01-01

    Protein-protein interactions are at the core of all cellular functions and dynamic alterations in protein interactions regulate cellular signaling. In the last decade, mass spectrometry-based proteomics has delivered unprecedented insights into human protein interaction networks. Affinity purification-mass spectrometry has been extensively employed for focused and high-throughput studies of steady state protein-protein interactions. Future challenges remain in mapping transient protein intera...

  17. Network analysis identifies protein clusters of functional importance in juvenile idiopathic arthritis

    Stevens, Adam; Meyer, Stefan; Hanson, Daniel; Clayton, Peter; Donn, Rachelle

    2014-01-01

    Introduction Our objective was to utilise network analysis to identify protein clusters of greatest potential functional relevance in the pathogenesis of oligoarticular and rheumatoid factor negative (RF-ve) polyarticular juvenile idiopathic arthritis (JIA). Methods JIA genetic association data were used to build an interactome network model in BioGRID 3.2.99. The top 10% of this protein:protein JIA Interactome was used to generate a minimal essential network (MEN). Reactome FI Cytoscape 2.83...

  18. A novel functional module detection algorithm for protein-protein interaction networks

    Zhang Aidong

    2006-12-01

    Full Text Available Abstract Background The sparse connectivity of protein-protein interaction data sets makes identification of functional modules challenging. The purpose of this study is to critically evaluate a novel clustering technique for clustering and detecting functional modules in protein-protein interaction networks, termed STM. Results STM selects representative proteins for each cluster and iteratively refines clusters based on a combination of the signal transduced and graph topology. STM is found to be effective at detecting clusters with a diverse range of interaction structures that are significant on measures of biological relevance. The STM approach is compared to six competing approaches including the maximum clique, quasi-clique, minimum cut, betweeness cut and Markov Clustering (MCL algorithms. The clusters obtained by each technique are compared for enrichment of biological function. STM generates larger clusters and the clusters identified have p-values that are approximately 125-fold better than the other methods on biological function. An important strength of STM is that the percentage of proteins that are discarded to create clusters is much lower than the other approaches. Conclusion STM outperforms competing approaches and is capable of effectively detecting both densely and sparsely connected, biologically relevant functional modules with fewer discards.

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

    Yuval Gilad

    2014-08-01

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

  20. Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer

    H Billur Engin; Emre Guney; Ozlem Keskin; Baldo Oliva; Attila Gursoy

    2013-01-01

    Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer H. Billur Engin1, Emre Guney2, Ozlem Keskin1, Baldo Oliva2, Attila Gursoy1* 1 Center for Computational Biology and Bioinformatics and College of Engineering, Koc University, Istanbul, Turkey, 2 Structural Bioinformatics Group (GRIB), Universitat Pompeu Fabra Abstract Blocking specific protein interactions can lead to human diseases. Accordingly, protein i...

  1. Integrating structure to protein-protein interaction networks that drive metastasis to brain and lung in breast cancer

    Engin, H Billur; G??ney, Emre, 1983-; Keskin, Ozlem; Oliva Miguel, Baldomero; Gursoy, Attila

    2013-01-01

    Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer H. Billur Engin1, Emre Guney2, Ozlem Keskin1, Baldo Oliva2, Attila Gursoy1* 1 Center for Computational Biology and Bioinformatics and College of Engineering, Koc University, Istanbul, Turkey, 2 Structural Bioinformatics Group (GRIB), Universitat Pompeu Fabra Abstract Blocking specific protein interactions can lead to human diseases. Accordingly, protein i...

  2. Protein Complex Discovery by Interaction Filtering from Protein Interaction Networks Using Mutual Rank Coexpression and Sequence Similarity

    Ali Kazemi-Pour

    2015-01-01

    Full Text Available The evaluation of the biological networks is considered the essential key to understanding the complex biological systems. Meanwhile, the graph clustering algorithms are mostly used in the protein-protein interaction (PPI network analysis. The complexes introduced by the clustering algorithms include noise proteins. The error rate of the noise proteins in the PPI network researches is about 40–90%. However, only 30–40% of the existing interactions in the PPI databases depend on the specific biological function. It is essential to eliminate the noise proteins and the interactions from the complexes created via clustering methods. We have introduced new methods of weighting interactions in protein clusters and the splicing of noise interactions and proteins-based interactions on their weights. The coexpression and the sequence similarity of each pair of proteins are considered the edge weight of the proteins in the network. The results showed that the edge filtering based on the amount of coexpression acts similar to the node filtering via graph-based characteristics. Regarding the removal of the noise edges, the edge filtering has a significant advantage over the graph-based method. The edge filtering based on the amount of sequence similarity has the ability to remove the noise proteins and the noise interactions.

  3. Assessment of protein domain fusions in human protein interaction networks prediction: application to the human kinetochore model.

    Morilla, Ian; Lees, Jon G; Reid, Adam J; Orengo, Christine; Ranea, Juan A G

    2010-12-31

    In order to understand how biological systems function it is necessary to determine the interactions and associations between proteins. Some proteins, involved in a common biological process and encoded by separate genes in one organism, can be found fused within a single protein chain in other organisms. By detecting these triplets, a functional relationship can be established between the unfused proteins. Here we use a domain fusion prediction method to predict these protein interactions for the human interactome. We observed that gene fusion events are more related to physical interaction between proteins than to other weaker functional relationships such as participation in a common biological pathway. These results suggest that domain fusion is an appropriate method for predicting protein complexes. The most reliable fused domain predictions were used to build protein-protein interaction (PPI) networks. These predicted PPI network models showed the same topological features as real biological networks and different features from random behaviour. We built the PPI domain fusion sub-network model of the human kinetochore and observed that the majority of the predicted interactions have not yet been experimentally characterised in the publicly available PPI repositories. The study of the human kinetochore domain fusion sub-network reveals undiscovered kinetochore proteins with presumably relevant functions, such as hubs with many connections in the kinetochore sub-network. These results suggest that experimentally hidden regions in the predicted PPI networks contain key functional elements, associated with important functional areas, still undiscovered in the human interactome. Until novel experiments shed light on these hidden regions; domain fusion predictions provide a valuable approach for exploring them. PMID:20851221

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

    Quan, Chanqin

    2016-01-01

    The state-of-the-art methods for protein-protein interaction (PPI) extraction are primarily based on kernel methods, and their performances strongly depend on the handcraft features. In this paper, we tackle PPI extraction by using convolutional neural networks (CNN) and propose a shortest dependency path based CNN (sdpCNN) model. The proposed method (1) only takes the sdp and word embedding as input and (2) could avoid bias from feature selection by using CNN. We performed experiments on standard Aimed and BioInfer datasets, and the experimental results demonstrated that our approach outperformed state-of-the-art kernel based methods. In particular, by tracking the sdpCNN model, we find that sdpCNN could extract key features automatically and it is verified that pretrained word embedding is crucial in PPI task. PMID:27493967

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

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

    2014-01-01

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

  6. Prediction of protein hydration sites from sequence by modular neural networks

    Ehrlich, L.; Reczko, M.; Bohr, Henrik; Wade, R.C.

    1998-01-01

    separate neural networks. These predictions are used as input together with protein sequences for networks predicting hydration of residues, backbone atoms and sidechains. These networks are teined with protein crystal structures. The prediction of hydration is improved by adding information on secondary......The hydration properties of a protein are important determinants of its structure and function. Here, modular neural networks are employed to predict ordered hydration sites using protein sequence information. First, secondary structure and solvent accessibility are predicted from sequence with two...... using the actual values. The inclusion of property information allows a smaller squence window to be used in the networks to predict hydration. It has a greater impact on the accuracy of hydration site prediction for backbone atoms than for sidechains and for non-polar than polar residues. The networks...

  7. Molecular Principles of Gene Fusion Mediated Rewiring of Protein Interaction Networks in Cancer.

    Latysheva, Natasha S; Oates, Matt E; Maddox, Louis; Flock, Tilman; Gough, Julian; Buljan, Marija; Weatheritt, Robert J; Babu, M Madan

    2016-08-18

    Gene fusions are common cancer-causing mutations, but the molecular principles by which fusion protein products affect interaction networks and cause disease are not well understood. Here, we perform an integrative analysis of the structural, interactomic, and regulatory properties of thousands of putative fusion proteins. We demonstrate that genes that form fusions (i.e., parent genes) tend to be highly connected hub genes, whose protein products are enriched in structured and disordered interaction-mediating features. Fusion often results in the loss of these parental features and the depletion of regulatory sites such as post-translational modifications. Fusion products disproportionately connect proteins that did not previously interact in the protein interaction network. In this manner, fusion products can escape cellular regulation and constitutively rewire protein interaction networks. We suggest that the deregulation of central, interaction-prone proteins may represent a widespread mechanism by which fusion proteins alter the topology of cellular signaling pathways and promote cancer. PMID:27540857

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

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

  9. Dynamic functional modules in co-expressed protein interaction networks of dilated cardiomyopathy

    Oyang Yen-Jen

    2010-10-01

    Full Text Available Abstract Background Molecular networks represent the backbone of molecular activity within cells and provide opportunities for understanding the mechanism of diseases. While protein-protein interaction data constitute static network maps, integration of condition-specific co-expression information provides clues to the dynamic features of these networks. Dilated cardiomyopathy is a leading cause of heart failure. Although previous studies have identified putative biomarkers or therapeutic targets for heart failure, the underlying molecular mechanism of dilated cardiomyopathy remains unclear. Results We developed a network-based comparative analysis approach that integrates protein-protein interactions with gene expression profiles and biological function annotations to reveal dynamic functional modules under different biological states. We found that hub proteins in condition-specific co-expressed protein interaction networks tended to be differentially expressed between biological states. Applying this method to a cohort of heart failure patients, we identified two functional modules that significantly emerged from the interaction networks. The dynamics of these modules between normal and disease states further suggest a potential molecular model of dilated cardiomyopathy. Conclusions We propose a novel framework to analyze the interaction networks in different biological states. It successfully reveals network modules closely related to heart failure; more importantly, these network dynamics provide new insights into the cause of dilated cardiomyopathy. The revealed molecular modules might be used as potential drug targets and provide new directions for heart failure therapy.

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

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

    2016-01-01

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

  11. Targeting the Human Cancer Pathway Protein Interaction Network by Structural Genomics*

    Huang, Yuanpeng Janet; Hang, Dehua; Lu, Long Jason; Tong, Liang; Gerstein, Mark B; Montelione, Gaetano T.

    2008-01-01

    Structural genomics provides an important approach for characterizing and understanding systems biology. As a step toward better integrating protein three-dimensional (3D) structural information in cancer systems biology, we have constructed a Human Cancer Pathway Protein Interaction Network (HCPIN) by analysis of several classical cancer-associated signaling pathways and their physical protein-protein interactions. Many well known cancer-associated proteins play central roles as “hubs” or “b...

  12. Illuminating Spatial and Temporal Organization of Protein Interaction Networks by Mass Spectrometry-Based Proteomics

    Yang, Jiwen; Wagner, Sebastian A; Beli, Petra

    2015-01-01

    Protein–protein interactions are at the core of all cellular functions and dynamic alterations in protein interactions regulate cellular signaling. In the last decade, mass spectrometry (MS)-based proteomics has delivered unprecedented insights into human protein interaction networks. Affinity purification-MS (AP-MS) has been extensively employed for focused and high-throughput studies of steady state protein–protein interactions. Future challenges remain in mapping transient protein interact...

  13. The AP-1A and AP-1B clathrin adaptor complexes define biochemically and functionally distinct membrane domains

    Fölsch, Heike; Pypaert, Marc; Maday, Sandra; Pelletier, Laurence; Mellman, Ira

    2003-01-01

    Most epithelial cells contain two AP-1 clathrin adaptor complexes. AP-1A is ubiquitously expressed and involved in transport between the TGN and endosomes. AP-1B is expressed only in epithelia and mediates the polarized targeting of membrane proteins to the basolateral surface. Both AP-1 complexes are heterotetramers and differ only in their 50-kD μ1A or μ1B subunits. Here, we show that AP-1A and AP-1B, together with their respective cargoes, define physically and functionally distinct membra...

  14. The integrated analysis of metabolic and protein interaction networks reveals novel molecular organizing principles

    Walther Dirk

    2008-11-01

    Full Text Available Abstract Background The study of biological interaction networks is a central theme of systems biology. Here, we investigate the relationships between two distinct types of interaction networks: the metabolic pathway map and the protein-protein interaction network (PIN. It has long been established that successive enzymatic steps are often catalyzed by physically interacting proteins forming permanent or transient multi-enzymes complexes. Inspecting high-throughput PIN data, it was shown recently that, indeed, enzymes involved in successive reactions are generally more likely to interact than other protein pairs. In our study, we expanded this line of research to include comparisons of the underlying respective network topologies as well as to investigate whether the spatial organization of enzyme interactions correlates with metabolic efficiency. Results Analyzing yeast data, we detected long-range correlations between shortest paths between proteins in both network types suggesting a mutual correspondence of both network architectures. We discovered that the organizing principles of physical interactions between metabolic enzymes differ from the general PIN of all proteins. While physical interactions between proteins are generally dissortative, enzyme interactions were observed to be assortative. Thus, enzymes frequently interact with other enzymes of similar rather than different degree. Enzymes carrying high flux loads are more likely to physically interact than enzymes with lower metabolic throughput. In particular, enzymes associated with catabolic pathways as well as enzymes involved in the biosynthesis of complex molecules were found to exhibit high degrees of physical clustering. Single proteins were identified that connect major components of the cellular metabolism and may thus be essential for the structural integrity of several biosynthetic systems. Conclusion Our results reveal topological equivalences between the protein

  15. Modeling the two-hybrid detector: experimental bias on protein interaction networks.

    Stibius, Karin B; Sneppen, Kim

    2007-10-01

    This work was done to investigate the two-hybrid experiment for finding protein-protein interactions to explain the asymmetry found in the experimental data, and to help screen the data for high confidence interactions. By looking at the bait-prey experimental setup the resulting protein interaction network can be examined as a directed network (bait --> prey). We have investigated two possible scenarios for the asymmetry in the directed network by developing a biochemical model for the protein-DNA and protein-protein bindings inside the living yeast. One scenario assumes a background activity of bait proteins acting even without the prey, the other scenario explores the asymmetry in the chemistry associated with the bait being automatically located in the right position on the DNA. We conclude that the latter model gives the best description of the observed asymmetry. PMID:17557786

  16. Identifying potential survival strategies of HIV-1 through virus-host protein interaction networks

    Boucher Charles AB

    2010-07-01

    Full Text Available Abstract Background The National Institute of Allergy and Infectious Diseases has launched the HIV-1 Human Protein Interaction Database in an effort to catalogue all published interactions between HIV-1 and human proteins. In order to systematically investigate these interactions functionally and dynamically, we have constructed an HIV-1 human protein interaction network. This network was analyzed for important proteins and processes that are specific for the HIV life-cycle. In order to expose viral strategies, network motif analysis was carried out showing reoccurring patterns in virus-host dynamics. Results Our analyses show that human proteins interacting with HIV form a densely connected and central sub-network within the total human protein interaction network. The evaluation of this sub-network for connectivity and centrality resulted in a set of proteins essential for the HIV life-cycle. Remarkably, we were able to associate proteins involved in RNA polymerase II transcription with hubs and proteasome formation with bottlenecks. Inferred network motifs show significant over-representation of positive and negative feedback patterns between virus and host. Strikingly, such patterns have never been reported in combined virus-host systems. Conclusions HIV infection results in a reprioritization of cellular processes reflected by an increase in the relative importance of transcriptional machinery and proteasome formation. We conclude that during the evolution of HIV, some patterns of interaction have been selected for resulting in a system where virus proteins preferably interact with central human proteins for direct control and with proteasomal proteins for indirect control over the cellular processes. Finally, the patterns described by network motifs illustrate how virus and host interact with one another.

  17. FunMod: A Cytoscape Plugin for Identifying Functional Modules in Undirected Protein–Protein Networks

    Massimo Natale

    2014-08-01

    Full Text Available The characterization of the interacting behaviors of complex biological systems is a primary objective in protein–protein network analysis and computational biology. In this paper we present FunMod, an innovative Cytoscape version 2.8 plugin that is able to mine undirected protein–protein networks and to infer sub-networks of interacting proteins intimately correlated with relevant biological pathways. This plugin may enable the discovery of new pathways involved in diseases. In order to describe the role of each protein within the relevant biological pathways, FunMod computes and scores three topological features of the identified sub-networks. By integrating the results from biological pathway clustering and topological network analysis, FunMod proved to be useful for the data interpretation and the generation of new hypotheses in two case studies.

  18. Similar pathogen targets in Arabidopsis thaliana and homo sapiens protein networks.

    Paulo Shakarian

    Full Text Available We study the behavior of pathogens on host protein networks for humans and Arabidopsis - noting striking similarities. Specifically, we preform [Formula: see text]-shell decomposition analysis on these networks - which groups the proteins into various "shells" based on network structure. We observe that shells with a higher average degree are more highly targeted (with a power-law relationship and that highly targeted nodes lie in shells closer to the inner-core of the network. Additionally, we also note that the inner core of the network is significantly under-targeted. We show that these core proteins may have a role in intra-cellular communication and hypothesize that they are less attacked to ensure survival of the host. This may explain why certain high-degree proteins are not significantly attacked.

  19. Protein co-expression network analysis (ProCoNA)

    Gibbs, David L.; Baratt, Arie; Baric, Ralph S.; Kawaoka, Yoshihiro; Smith, Richard D.; Orwoll, Eric S.; Michael G Katze; McWeeney, Shannon K.

    2013-01-01

    Background Biological networks are important for elucidating disease etiology due to their ability to model complex high dimensional data and biological systems. Proteomics provides a critical data source for such models, but currently lacks robust de novo methods for network construction, which could bring important insights in systems biology. Results We have evaluated the construction of network models using methods derived from weighted gene co-expression network analysis (WGCNA). We show...

  20. Exploring hierarchical and overlapping modular structure in the yeast protein interaction network

    Zhao Yi

    2010-12-01

    Full Text Available Abstract Background Developing effective strategies to reveal modular structures in protein interaction networks is crucial for better understanding of molecular mechanisms of underlying biological processes. In this paper, we propose a new density-based algorithm (ADHOC for clustering vertices of a protein interaction network using a novel subgraph density measurement. Results By statistically evaluating several independent criteria, we found that ADHOC could significantly improve the outcome as compared with five previously reported density-dependent methods. We further applied ADHOC to investigate the hierarchical and overlapping modular structure in the yeast PPI network. Our method could effectively detect both protein modules and the overlaps between them, and thus greatly promote the precise prediction of protein functions. Moreover, by further assaying the intermodule layer of the yeast PPI network, we classified hubs into two types, module hubs and inter-module hubs. Each type presents distinct characteristics both in network topology and biological functions, which could conduce to the better understanding of relationship between network architecture and biological implications. Conclusions Our proposed algorithm based on the novel subgraph density measurement makes it possible to more precisely detect hierarchical and overlapping modular structures in protein interaction networks. In addition, our method also shows a strong robustness against the noise in network, which is quite critical for analyzing such a high noise network.

  1. p42.3 gene expression in gastric cancer cell and its protein regulatory network analysis

    Zhang Jianhua

    2012-12-01

    Full Text Available Abstract Background To analyze the p42.3 gene expression in gastric cancer (GC cell, find the relationship between protein structure and function, establish the regulatory network of p42.3 protein molecule and then to obtain the optimal regulatory pathway. Methods The expression of p42.3 gene was analyzed by RT-PCR, Western Blot and other biotechnologies. The relationship between the spatial conformation of p42.3 protein molecule and its function was analyzed using bioinformatics, MATLAB and related knowledge about protein structure and function. Furthermore, based on similarity algorithm of spatial layered spherical coordinate, we compared p42.3 molecule with several similar structured proteins which are known for the function, screened the characteristic nodes related to tumorigenesis and development, and established the multi variable relational model between p42.3 protein expression, cell cycle regulation and biological characteristics in the level of molecular regulatory networks. Finally, the optimal regulatory network was found by using Bayesian network. Results (1 The expression amount of p42.3 in G1 and M phase was higher than that in S and G2 phase; (2 The space coordinate systems of different structural domains of p42.3 protein were established in Matlab7.0 software; (3 The optimal pathway of p42.3 gene in protein regulatory network in gastric cancer is Ras protein, Raf-1 protein, MEK, MAPK kinase, MAPK, tubulin, spindle protein, centromere protein and tumor. Conclusion It is of vital significance for mechanism research to find out the action pathway of p42.3 in protein regulatory network, since p42.3 protein plays an important role in the generation and development of GC.

  2. Multiple pathways for regulation of sigmaS (RpoS) stability in Escherichia coli via the action of multiple anti-adaptors.

    Bougdour, Alexandre; Cunning, Christofer; Baptiste, Patrick Jean; Elliott, Thomas; Gottesman, Susan

    2008-04-01

    SigmaS, the stationary phase sigma factor of Escherichia coli and Salmonella, is regulated at multiple levels. The sigmaS protein is unstable during exponential growth and is stabilized during stationary phase and after various stress treatments. Degradation requires both the ClpXP protease and the adaptor RssB. The small antiadaptor protein IraP is made in response to phosphate starvation and interacts with RssB, causing sigmaS stabilization under this stress condition. IraP is essential for sigmaS stabilization in some but not all starvation conditions, suggesting the existence of other anti-adaptor proteins. We report here the identification of new regulators of sigmaS stability, important under other stress conditions. IraM (inhibitor of RssB activity during Magnesium starvation) and IraD (inhibitor of RssB activity after DNA damage) inhibit sigmaS proteolysis both in vivo and in vitro. Our results reveal that multiple anti-adaptor proteins allow the regulation of sigmaS stability through the regulation of RssB activity under a variety of stress conditions. PMID:18383615

  3. Methods for the Analysis of Protein Phosphorylation–Mediated Cellular Signaling Networks

    White, Forest M.; Wolf-Yadlin, Alejandro

    2016-06-01

    Protein phosphorylation–mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

  4. Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks.

    White, Forest M; Wolf-Yadlin, Alejandro

    2016-06-12

    Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks. PMID:27049636

  5. A Big-Five Personality Profile of the Adaptor and Innovator.

    Kwang, Ng Aik; Rodrigues, Daphne

    2002-01-01

    A study explored the relationship between two creative types (adaptor and innovator) and the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience), in 164 teachers in Singapore. Adaptors were significantly more conscientious than innovators, while innovators were significantly more…

  6. A local average connectivity-based method for identifying essential proteins from the network level.

    Li, Min; Wang, Jianxin; Chen, Xiang; Wang, Huan; Pan, Yi

    2011-06-01

    Identifying essential proteins is very important for understanding the minimal requirements of cellular survival and development. Fast growth in the amount of available protein-protein interactions has produced unprecedented opportunities for detecting protein essentiality from the network level. Essential proteins have been found to be more abundant among those highly connected proteins. However, there exist a number of highly connected proteins which are not essential. By analyzing these proteins, we find that few of their neighbors interact with each other. Thus, we propose a new local method, named LAC, to determine a protein's essentiality by evaluating the relationship between a protein and its neighbors. The performance of LAC is validated based on the yeast protein interaction networks obtained from two different databases: DIP and BioGRID. The experimental results of the two networks show that the number of essential proteins predicted by LAC clearly exceeds that explored by Degree Centrality (DC). More over, LAC is also compared with other seven measures of protein centrality (Neighborhood Component (DMNC), Betweenness Centrality (BC), Closeness Centrality (CC), Bottle Neck (BN), Information Centrality (IC), Eigenvector Centrality (EC), and Subgraph Centrality (SC)) in identifying essential proteins. The comparison results based on the validations of sensitivity, specificity, F-measure, positive predictive value, negative predictive value, and accuracy consistently show that LAC outweighs these seven previous methods. PMID:21704260

  7. Automatic extraction of gene ontology annotation and its correlation with clusters in protein networks

    Mazo Ilya

    2007-07-01

    Full Text Available Abstract Background Uncovering cellular roles of a protein is a task of tremendous importance and complexity that requires dedicated experimental work as well as often sophisticated data mining and processing tools. Protein functions, often referred to as its annotations, are believed to manifest themselves through topology of the networks of inter-proteins interactions. In particular, there is a growing body of evidence that proteins performing the same function are more likely to interact with each other than with proteins with other functions. However, since functional annotation and protein network topology are often studied separately, the direct relationship between them has not been comprehensively demonstrated. In addition to having the general biological significance, such demonstration would further validate the data extraction and processing methods used to compose protein annotation and protein-protein interactions datasets. Results We developed a method for automatic extraction of protein functional annotation from scientific text based on the Natural Language Processing (NLP technology. For the protein annotation extracted from the entire PubMed, we evaluated the precision and recall rates, and compared the performance of the automatic extraction technology to that of manual curation used in public Gene Ontology (GO annotation. In the second part of our presentation, we reported a large-scale investigation into the correspondence between communities in the literature-based protein networks and GO annotation groups of functionally related proteins. We found a comprehensive two-way match: proteins within biological annotation groups form significantly denser linked network clusters than expected by chance and, conversely, densely linked network communities exhibit a pronounced non-random overlap with GO groups. We also expanded the publicly available GO biological process annotation using the relations extracted by our NLP technology

  8. Context-specific protein network miner--an online system for exploring context-specific protein interaction networks from the literature.

    Rajesh Chowdhary

    Full Text Available BACKGROUND: Protein interaction networks (PINs specific within a particular context contain crucial information regarding many cellular biological processes. For example, PINs may include information on the type and directionality of interaction (e.g. phosphorylation, location of interaction (i.e. tissues, cells, and related diseases. Currently, very few tools are capable of deriving context-specific PINs for conducting exploratory analysis. RESULTS: We developed a literature-based online system, Context-specific Protein Network Miner (CPNM, which derives context-specific PINs in real-time from the PubMed database based on a set of user-input keywords and enhanced PubMed query system. CPNM reports enriched information on protein interactions (with type and directionality, their network topology with summary statistics (e.g. most densely connected proteins in the network; most densely connected protein-pairs; and proteins connected by most inbound/outbound links that can be explored via a user-friendly interface. Some of the novel features of the CPNM system include PIN generation, ontology-based PubMed query enhancement, real-time, user-queried, up-to-date PubMed document processing, and prediction of PIN directionality. CONCLUSIONS: CPNM provides a tool for biologists to explore PINs. It is freely accessible at http://www.biotextminer.com/CPNM/.

  9. On the Variability of Neural Network Classification Measures in the Protein Secondary Structure Prediction Problem

    Eric Sakk

    2013-01-01

    Full Text Available We revisit the protein secondary structure prediction problem using linear and backpropagation neural network architectures commonly applied in the literature. In this context, neural network mappings are constructed between protein training set sequences and their assigned structure classes in order to analyze the class membership of test data and associated measures of significance. We present numerical results demonstrating that classifier performance measures can vary significantly depending upon the classifier architecture and the structure class encoding technique. Furthermore, an analytic formulation is introduced in order to substantiate the observed numerical data. Finally, we analyze and discuss the ability of the neural network to accurately model fundamental attributes of protein secondary structure.

  10. A Quantitative Approach to Analyzing Genome Reductive Evolution Using Protein-Protein Interaction Networks: A Case Study of Mycobacterium leprae.

    Akinola, Richard O; Mazandu, Gaston K; Mulder, Nicola J

    2016-01-01

    The advance in high-throughput sequencing technologies has yielded complete genome sequences of several organisms, including complete bacterial genomes. The growing number of these available sequenced genomes has enabled analyses of their dynamics, as well as the molecular and evolutionary processes which these organisms are under. Comparative genomics of different bacterial genomes have highlighted their genome size and gene content in association with lifestyles and adaptation to various environments and have contributed to enhancing our understanding of the mechanisms of their evolution. Protein-protein functional interactions mediate many essential processes for maintaining the stability of the biological systems under changing environmental conditions. Thus, these interactions play crucial roles in the evolutionary processes of different organisms, especially for obligate intracellular bacteria, proven to generally have reduced genome sizes compared to their nearest free-living relatives. In this study, we used the approach based on the Renormalization Group (RG) analysis technique and the Maximum-Excluded-Mass-Burning (MEMB) model to investigate the evolutionary process of genome reduction in relation to the organization of functional networks of two organisms. Using a Mycobacterium leprae (MLP) network in comparison with a Mycobacterium tuberculosis (MTB) network as a case study, we show that reductive evolution in MLP was as a result of removal of important proteins from neighbors of corresponding orthologous MTB proteins. While each orthologous MTB protein had an increase in number of interacting partners in most instances, the corresponding MLP protein had lost some of them. This work provides a quantitative model for mapping reductive evolution and protein-protein functional interaction network organization in terms of roles played by different proteins in the network structure. PMID:27066064

  11. Semantic integration to identify overlapping functional modules in protein interaction networks

    Ramanathan Murali

    2007-07-01

    Full Text Available Abstract Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.

  12. Eyes underground: regression of visual protein networks in subterranean mammals.

    Emerling, Christopher A; Springer, Mark S

    2014-09-01

    Regressive evolution involves the degeneration of formerly useful structures in a lineage over time, and may be accompanied by the molecular decay of phenotype-specific genes. The mammalian eye has repeatedly undergone degeneration in taxa that occupy dim-light environments including subterranean habitats. Here we assess whether a decrease in the amount of light that reaches the retina is associated with increased regression of retinal genes, whether the phototransduction and visual cycle pathways degrade in a predictable pattern, and if the timing of retinal gene loss is associated with the entrance of mammalian lineages into subterranean environments. Sequence data were obtained from the publically available genomes of the Cape golden mole (Chrysochloris asiatica), naked mole-rat (Heterocephalus glaber) and star-nosed mole (Condylura cristata) for 65 genes associated with phototransduction, the visual cycle, and other retinal functions. Gene sequences were inspected for inactivating mutations and, when present, pseudogene sequences were compared to sequences from subaerial outgroup species. To test whether retinal degeneration is correlated with historical entrances into subterranean environments, estimated dates of retinal gene inactivation were compared to the fossil record and phylogenetic inferences of ancestral fossoriality. Our results show that (1) lower levels of light available to the retina correspond with an increase in the number of retinal pseudogenes, (2) retinal protein networks generally degrade in a predictable manner, although the extensive loss of cone phototransduction genes in Heterocephalus raises further questions regarding SWS1-cone monochromacy versus functional rod monochromacy in this species, and (3) inactivation dates of retinal genes usually post-date inferred entrances into subterranean habitats. PMID:24859681

  13. Creating a specialist protein resource network: a meeting report for the protein bioinformatics and community resources retreat.

    Babbitt, Patricia C; Bagos, Pantelis G; Bairoch, Amos; Bateman, Alex; Chatonnet, Arnaud; Chen, Mark Jinan; Craik, David J; Finn, Robert D; Gloriam, David; Haft, Daniel H; Henrissat, Bernard; Holliday, Gemma L; Isberg, Vignir; Kaas, Quentin; Landsman, David; Lenfant, Nicolas; Manning, Gerard; Nagano, Nozomi; Srinivasan, Narayanaswamy; O'Donovan, Claire; Pruitt, Kim D; Sowdhamini, Ramanathan; Rawlings, Neil D; Saier, Milton H; Sharman, Joanna L; Spedding, Michael; Tsirigos, Konstantinos D; Vastermark, Ake; Vriend, Gerrit

    2015-01-01

    During 11-12 August 2014, a Protein Bioinformatics and Community Resources Retreat was held at the Wellcome Trust Genome Campus in Hinxton, UK. This meeting brought together the principal investigators of several specialized protein resources (such as CAZy, TCDB and MEROPS) as well as those from protein databases from the large Bioinformatics centres (including UniProt and RefSeq). The retreat was divided into five sessions: (1) key challenges, (2) the databases represented, (3) best practices for maintenance and curation, (4) information flow to and from large data centers and (5) communication and funding. An important outcome of this meeting was the creation of a Specialist Protein Resource Network that we believe will improve coordination of the activities of its member resources. We invite further protein database resources to join the network and continue the dialogue. PMID:26284514

  14. Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution

    Mannakee, Brian K.; Gutenkunst, Ryan N.

    2016-01-01

    The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein’s rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces. PMID:27380265

  15. Survey: Enhancing protein complex prediction in PPI networks with GO similarity weighting.

    Price, True; Peña, Francisco I; Cho, Young-Rae

    2013-09-01

    Predicting protein complexes from protein-protein interaction (PPI) networks has been the focus of many computational approaches over the last decade. These methods tend to vary in performance based on the structure of the network and the parameters provided to the algorithm. Here, we evaluate the merits of enhancing PPI networks with semantic similarity edge weights using Gene Ontology (GO) and its annotation data. We compare the cluster features and predictive efficacy of six well-known unweighted protein complex detection methods (Clique Percolation, MCODE, DPClus, IPCA, Graph Entropy, and CoAch) against updated weighted implementations. We conclude that incorporating semantic similarity edge weighting in PPI network analysis unequivocally increases the performance of these methods. PMID:24307411

  16. Defining the protein interaction network of human malaria parasite Plasmodium falciparum

    Ramaprasad, Abhinay

    2012-02-01

    Malaria, caused by the protozoan parasite Plasmodium falciparum, affects around 225. million people yearly and a huge international effort is directed towards combating this grave threat to world health and economic development. Considerable advances have been made in malaria research triggered by the sequencing of its genome in 2002, followed by several high-throughput studies defining the malaria transcriptome and proteome. A protein-protein interaction (PPI) network seeks to trace the dynamic interactions between proteins, thereby elucidating their local and global functional relationships. Experimentally derived PPI network from high-throughput methods such as yeast two hybrid (Y2H) screens are inherently noisy, but combining these independent datasets by computational methods tends to give a greater accuracy and coverage. This review aims to discuss the computational approaches used till date to construct a malaria protein interaction network and to catalog the functional predictions and biological inferences made from analysis of the PPI network. © 2011 Elsevier Inc.

  17. Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

    Ba, Qian [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Li, Junyang; Huang, Chao [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Li, Jingquan; Chu, Ruiai [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wu, Yongning, E-mail: wuyongning@cfsa.net.cn [Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wang, Hui, E-mail: huiwang@sibs.ac.cn [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); School of Life Science and Technology, ShanghaiTech University, Shanghai (China)

    2015-03-01

    Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong to the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified.

  18. Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

    Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong to the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified

  19. Convolutional LSTM Networks for Subcellular Localization of Proteins

    Sønderby, Søren Kaae; Sønderby, Casper Kaae; Nielsen, Henrik;

    2015-01-01

    Machine learning is widely used to analyze biological sequence data. Non-sequential models such as SVMs or feed-forward neural networks are often used although they have no natural way of handling sequences of varying length. Recurrent neural networks such as the long short term memory (LSTM) model...

  20. Convolutional LSTM Networks for Subcellular Localization of Proteins

    Nielsen, Henrik; Sønderby, Søren Kaae; Sønderby, Casper Kaae;

    Machine learning is widely used to analyze biological sequence data. Non-sequential models such as SVMs or feed-forward neural networks are often used although they have no natural way of handling sequences of varying length. Recurrent neural networks such as the long short term memory (LSTM) model...

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

    Wuchty Stefan

    2006-05-01

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

  2. Emergence of Complexity in Protein Functions and Metabolic Networks

    Pohorille, Andzej

    2009-01-01

    In modern organisms proteins perform a majority of cellular functions, such as chemical catalysis, energy transduction and transport of material across cell walls. Although great strides have been made towards understanding protein evolution, a meaningful extrapolation from contemporary proteins to their earliest ancestors is virtually impossible. In an alternative approach, the origin of water-soluble proteins was probed through the synthesis of very large libraries of random amino acid sequences and subsequently subjecting them to in vitro evolution. In combination with computer modeling and simulations, these experiments allow us to address a number of fundamental questions about the origins of proteins. Can functionality emerge from random sequences of proteins? How did the initial repertoire of functional proteins diversify to facilitate new functions? Did this diversification proceed primarily through drawing novel functionalities from random sequences or through evolution of already existing proto-enzymes? Did protein evolution start from a pool of proteins defined by a frozen accident and other collections of proteins could start a different evolutionary pathway? Although we do not have definitive answers to these questions, important clues have been uncovered. Considerable progress has been also achieved in understanding the origins of membrane proteins. We will address this issue in the example of ion channels - proteins that mediate transport of ions across cell walls. Remarkably, despite overall complexity of these proteins in contemporary cells, their structural motifs are quite simple, with -helices being most common. By combining results of experimental and computer simulation studies on synthetic models and simple, natural channels, I will show that, even though architectures of membrane proteins are not nearly as diverse as those of water-soluble proteins, they are sufficiently flexible to adapt readily to the functional demands arising during

  3. Revisiting topological properties and models of protein-protein interaction networks from the perspective of dataset evolution.

    Shao, Mingyu; Zhou, Shuigeng; Guan, Jihong

    2015-08-01

    Protein-protein interaction (PPI) networks are crucial for organisms. Many research efforts have thus been devoted to the study on the topological properties and models of PPI networks. However, existing studies did not always report consistent results on the topological properties of PPI networks. Although a number of PPI network models have been introduced, yet in the literature there is no convincing conclusion on which model is best for describing PPI networks. This situation is primarily caused by the incompleteness of current PPI datasets. To solve this problem, in this study, the authors propose to revisit the topological properties and models of PPI networks from the perspective of PPI dataset evolution. Concretely, they used 12 PPI datasets of Arabidopsis thaliana and 10 PPI datasets of Saccharomyces cerevisiae from different Biological General Repository for Interaction Datasets (BioGRID) database versions, and compared the topological properties of these datasets and the fitting capabilities of five typical PPI network models over these datasets. PMID:26243826

  4. Protein network signatures associated with exogenous biofuels treatments in cyanobacterium Synechocystis sp. PCC 6803

    Guangsheng ePei

    2014-11-01

    Full Text Available Although recognized as a promising microbial cell factory for producing biofuels, current productivity in cyanobacterial systems is low. To make the processes economically feasible, one of the hurdles which needs to be overcome is the low tolerance of hosts to toxic biofuels. Meanwhile, little information is available regarding the cellular responses to biofuels stress in cyanobacteria, which makes it challenging for tolerance engineering. Using large proteomic datasets of Synechocystis under various biofuels stress and environmental perturbation, a protein co-expression network was first constructed and then combined with the experimentally determined protein-protein interaction (PPI network. Proteins with statistically higher topological overlap in the integrated network were identified as common responsive proteins to both biofuels stress and environmental perturbations. In addition, a WGCNA network analysis was performed to distinguish unique responses to biofuels from those to environmental perturbations and to uncover metabolic modules and proteins uniquely associated with biofuels stress. The results showed that biofuel-specific proteins and modules were enriched in several functional categories, including photosynthesis, carbon fixation and amino acid metabolism, which may represent potential key signatures for biofuels stress responses in Synechocystis. Network-based analysis allowed determination of the responses specifically related to biofuels stress, and the results constituted an important knowledge foundation for tolerance engineering against biofuels in Synechocystis.

  5. Alpha-helical protein networks are self-protective and flaw-tolerant.

    Ackbarow, Theodor; Sen, Dipanjan; Thaulow, Christian; Buehler, Markus J

    2009-01-01

    Alpha-helix based protein networks as they appear in intermediate filaments in the cell's cytoskeleton and the nuclear membrane robustly withstand large deformation of up to several hundred percent strain, despite the presence of structural imperfections or flaws. This performance is not achieved by most synthetic materials, which typically fail at much smaller deformation and show a great sensitivity to the existence of structural flaws. Here we report a series of molecular dynamics simulations with a simple coarse-grained multi-scale model of alpha-helical protein domains, explaining the structural and mechanistic basis for this observed behavior. We find that the characteristic properties of alpha-helix based protein networks are due to the particular nanomechanical properties of their protein constituents, enabling the formation of large dissipative yield regions around structural flaws, effectively protecting the protein network against catastrophic failure. We show that the key for these self protecting properties is a geometric transformation of the crack shape that significantly reduces the stress concentration at corners. Specifically, our analysis demonstrates that the failure strain of alpha-helix based protein networks is insensitive to the presence of structural flaws in the protein network, only marginally affecting their overall strength. Our findings may help to explain the ability of cells to undergo large deformation without catastrophic failure while providing significant mechanical resistance. PMID:19547709

  6. Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding

    Cannistraci, Carlo

    2013-06-21

    Motivation: Most functions within the cell emerge thanks to protein-protein interactions (PPIs), yet experimental determination of PPIs is both expensive and time-consuming. PPI networks present significant levels of noise and incompleteness. Predicting interactions using only PPI-network topology (topological prediction) is difficult but essential when prior biological knowledge is absent or unreliable.Methods: Network embedding emphasizes the relations between network proteins embedded in a low-dimensional space, in which protein pairs that are closer to each other represent good candidate interactions. To achieve network denoising, which boosts prediction performance, we first applied minimum curvilinear embedding (MCE), and then adopted shortest path (SP) in the reduced space to assign likelihood scores to candidate interactions. Furthermore, we introduce (i) a new valid variation of MCE, named non-centred MCE (ncMCE); (ii) two automatic strategies for selecting the appropriate embedding dimension; and (iii) two new randomized procedures for evaluating predictions.Results: We compared our method against several unsupervised and supervisedly tuned embedding approaches and node neighbourhood techniques. Despite its computational simplicity, ncMCE-SP was the overall leader, outperforming the current methods in topological link prediction.Conclusion: Minimum curvilinearity is a valuable non-linear framework that we successfully applied to the embedding of protein networks for the unsupervised prediction of novel PPIs. The rationale for our approach is that biological and evolutionary information is imprinted in the non-linear patterns hidden behind the protein network topology, and can be exploited for predicting new protein links. The predicted PPIs represent good candidates for testing in high-throughput experiments or for exploitation in systems biology tools such as those used for network-based inference and prediction of disease-related functional modules. The

  7. Finding the "dark matter" in human and yeast protein network prediction and modelling.

    Ranea, Juan A G; Morilla, Ian; Lees, Jon G; Reid, Adam J; Yeats, Corin; Clegg, Andrew B; Sanchez-Jimenez, Francisca; Orengo, Christine

    2010-01-01

    Accurate modelling of biological systems requires a deeper and more complete knowledge about the molecular components and their functional associations than we currently have. Traditionally, new knowledge on protein associations generated by experiments has played a central role in systems modelling, in contrast to generally less trusted bio-computational predictions. However, we will not achieve realistic modelling of complex molecular systems if the current experimental designs lead to biased screenings of real protein networks and leave large, functionally important areas poorly characterised. To assess the likelihood of this, we have built comprehensive network models of the yeast and human proteomes by using a meta-statistical integration of diverse computationally predicted protein association datasets. We have compared these predicted networks against combined experimental datasets from seven biological resources at different level of statistical significance. These eukaryotic predicted networks resemble all the topological and noise features of the experimentally inferred networks in both species, and we also show that this observation is not due to random behaviour. In addition, the topology of the predicted networks contains information on true protein associations, beyond the constitutive first order binary predictions. We also observe that most of the reliable predicted protein associations are experimentally uncharacterised in our models, constituting the hidden or "dark matter" of networks by analogy to astronomical systems. Some of this dark matter shows enrichment of particular functions and contains key functional elements of protein networks, such as hubs associated with important functional areas like the regulation of Ras protein signal transduction in human cells. Thus, characterising this large and functionally important dark matter, elusive to established experimental designs, may be crucial for modelling biological systems. In any case

  8. The AP-3 adaptor complex is required for vacuolar function in Arabidopsis

    Maria Zwiewka; Elena Feraru; Barbara M(o)ller; Inhwan Hwang; Mugurel I Feraru; Jürgen Kleine-Vehn; Dolf Weijers; Ji(n) Friml

    2011-01-01

    Subcellular trafficking is required for a multitude of functions in eukaryotic cells.It involves regulation of cargo sorting,vesicle formation,trafficking and fusion processes at multiple levels.Adaptor protein (AP) complexes are key regulators of cargo sorting into vesicles in yeast and mammals but their existence and function in plants have not been demonstrated.Here we report the identification of the protein-affected trafficking 4 (pat4) mutant defective in the putative δ subunit of the AP-3 complex.pat4 and pat2,a mutant isolated from the same GFP imaging-based forward genetic screen that lacks a functional putative AP-3 β,as well as dominant negative AP-3 μ transgenic lines display undistinguishable phenotypes characterized by largely normal morphology and development,but strong intracellular accumulation of membrane proteins in aberrant vacuolar structures.All mutants are defective in morphology and function of lytic and protein storage vacuoles (PSVs) but show normal sorting of reserve proteins to PSVs.Immunoprecipitation experiments and genetic studies revealed tight functional and physical associations of putative AP-3 β and AP-3 δ subunits.Furthermore,both proteins are closely linked with putative AP-3 μ and σ subunits and several components of the clathrin and dynamin machineries.Taken together,these results demonstrate that AP complexes,similar to those in other eukaryotes,exist in plants,and that AP-3 plays a specific role in the regulation of biogenesis and function of vacuoles in plant cells.

  9. Scoring protein relationships in functional interaction networks predicted from sequence data.

    Gaston K Mazandu

    Full Text Available UNLABELLED: The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms. This requires computational methods in order to integrate and exploit these data effectively and elucidate local and genome wide functional connections between protein pairs, thus enabling functional inferences for uncharacterized proteins. These biological data are primarily in the form of sequences, which determine functions, although functional properties of a protein can often be predicted from just the domains it contains. Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts. In this work, we introduce information-theoretic based approaches to score protein-protein functional interaction pairs predicted from protein sequence similarity and conserved protein signature matches. The proposed schemes are effective for data-driven scoring of connections between protein pairs. We applied these schemes to the Mycobacterium tuberculosis proteome to produce a homology-based functional network of the organism with a high confidence and coverage. We use the network for predicting functions of uncharacterised proteins. AVAILABILITY: Protein pair-wise functional relationship scores for Mycobacterium tuberculosis strain CDC1551 sequence data and python scripts to compute these scores are available at http://web.cbio.uct.ac.za/~gmazandu/scoringschemes.

  10. Study on the isothermal forging process of MB26 magnesium alloy adaptor

    Xu Wenchen

    2015-01-01

    Full Text Available The isothermal forging process is an effective method to manufacture complex-shaped components of hard-to-work materials, such as magnesium alloys. This study investigates the isothermal forging process of an MB26 magnesium alloy adaptor with three branches. The results show that two-step forging process is appropriate to form the adaptor forging, which not only improves the filling quality but also reduces the forging load compared with one-step forging process. Moreover, the flow line is distributed along the contour of the complex-shaped adaptor forging.

  11. The function of communities in protein interaction networks at multiple scales

    Jones Nick S

    2010-07-01

    Full Text Available Abstract Background If biology is modular then clusters, or communities, of proteins derived using only protein interaction network structure should define protein modules with similar biological roles. We investigate the link between biological modules and network communities in yeast and its relationship to the scale at which we probe the network. Results Our results demonstrate that the functional homogeneity of communities depends on the scale selected, and that almost all proteins lie in a functionally homogeneous community at some scale. We judge functional homogeneity using a novel test and three independent characterizations of protein function, and find a high degree of overlap between these measures. We show that a high mean clustering coefficient of a community can be used to identify those that are functionally homogeneous. By tracing the community membership of a protein through multiple scales we demonstrate how our approach could be useful to biologists focusing on a particular protein. Conclusions We show that there is no one scale of interest in the community structure of the yeast protein interaction network, but we can identify the range of resolution parameters that yield the most functionally coherent communities, and predict which communities are most likely to be functionally homogeneous.

  12. Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

    Hjerrild, Majbrit; Stensballe, Allan; Rasmussen, Thomas E;

    2011-01-01

    Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein...

  13. Reuse of structural domain–domain interactions in protein networks

    Bateman Alex; Schuster-Böckler Benjamin

    2007-01-01

    Abstract Background Protein interactions are thought to be largely mediated by interactions between structural domains. Databases such as iPfam relate interactions in protein structures to known domain families. Here, we investigate how the domain interactions from the iPfam database are distributed in protein interactions taken from the HPRD, MPact, BioGRID, DIP and IntAct databases. Results We find that known structural domain interactions can only explain a subset of 4–19% of the available...

  14. Redundancies in Large-scale Protein Interaction Networks

    Samanta, M P; Samanta, Manoj Pratim; Liang, Shoudan

    2003-01-01

    Understanding functional associations among genes discovered in sequencing projects is a key issue in post-genomic biology. However, reliable interpretation of the protein interaction data has been difficult. In this work, we show 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 more than 2800 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.

  15. How does the antagonism between capping and anti-capping proteins affect actin network dynamics?

    Actin-based cell motility is essential to many biological processes. We built a simplified, three-dimensional computational model and subsequently performed stochastic simulations to study the growth dynamics of lamellipodia-like branched networks. In this work, we shed light on the antagonism between capping and anti-capping proteins in regulating actin dynamics in the filamentous network. We discuss detailed mechanisms by which capping and anti-capping proteins affect the protrusion speed of the actin network and the rate of nucleation of filaments. We computed a phase diagram showing the regimes of motility enhancement and inhibition by these proteins. Our work shows that the effects of capping and anti-capping proteins are mainly transmitted by modulation of the filamentous network density and local availability of monomeric actin. We discovered that the combination of the capping/anti-capping regulatory network with nucleation-promoting proteins introduces robustness and redundancy in cell motility machinery, allowing the cell to easily achieve maximal protrusion speeds under a broader set of conditions. Finally, we discuss distributions of filament lengths under various conditions and speculate on their potential implication for the emergence of filopodia from the lamellipodial network.

  16. How does the antagonism between capping and anti-capping proteins affect actin network dynamics?

    Hu, Longhua; Papoian, Garegin A.

    2011-09-01

    Actin-based cell motility is essential to many biological processes. We built a simplified, three-dimensional computational model and subsequently performed stochastic simulations to study the growth dynamics of lamellipodia-like branched networks. In this work, we shed light on the antagonism between capping and anti-capping proteins in regulating actin dynamics in the filamentous network. We discuss detailed mechanisms by which capping and anti-capping proteins affect the protrusion speed of the actin network and the rate of nucleation of filaments. We computed a phase diagram showing the regimes of motility enhancement and inhibition by these proteins. Our work shows that the effects of capping and anti-capping proteins are mainly transmitted by modulation of the filamentous network density and local availability of monomeric actin. We discovered that the combination of the capping/anti-capping regulatory network with nucleation-promoting proteins introduces robustness and redundancy in cell motility machinery, allowing the cell to easily achieve maximal protrusion speeds under a broader set of conditions. Finally, we discuss distributions of filament lengths under various conditions and speculate on their potential implication for the emergence of filopodia from the lamellipodial network.

  17. How does the antagonism between capping and anti-capping proteins affect actin network dynamics?

    Hu Longhua; Papoian, Garegin A, E-mail: gpapoian@umd.edu [Department of Chemistry and Biochemistry, University of Maryland, College Park, MD 20742 (United States)

    2011-09-21

    Actin-based cell motility is essential to many biological processes. We built a simplified, three-dimensional computational model and subsequently performed stochastic simulations to study the growth dynamics of lamellipodia-like branched networks. In this work, we shed light on the antagonism between capping and anti-capping proteins in regulating actin dynamics in the filamentous network. We discuss detailed mechanisms by which capping and anti-capping proteins affect the protrusion speed of the actin network and the rate of nucleation of filaments. We computed a phase diagram showing the regimes of motility enhancement and inhibition by these proteins. Our work shows that the effects of capping and anti-capping proteins are mainly transmitted by modulation of the filamentous network density and local availability of monomeric actin. We discovered that the combination of the capping/anti-capping regulatory network with nucleation-promoting proteins introduces robustness and redundancy in cell motility machinery, allowing the cell to easily achieve maximal protrusion speeds under a broader set of conditions. Finally, we discuss distributions of filament lengths under various conditions and speculate on their potential implication for the emergence of filopodia from the lamellipodial network.

  18. The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics.

    Yu, Haiyuan; Kim, Philip M; Sprecher, Emmett; Trifonov, Valery; Gerstein, Mark

    2007-04-20

    It has been a long-standing goal in systems biology to find relations between the topological properties and functional features of protein networks. However, most of the focus in network studies has been on highly connected proteins ("hubs"). As a complementary notion, it is possible to define bottlenecks as proteins with a high betweenness centrality (i.e., network nodes that have many "shortest paths" going through them, analogous to major bridges and tunnels on a highway map). Bottlenecks are, in fact, key connector proteins with surprising functional and dynamic properties. In particular, they are more likely to be essential proteins. In fact, in regulatory and other directed networks, betweenness (i.e., "bottleneck-ness") is a much more significant indicator of essentiality than degree (i.e., "hub-ness"). Furthermore, bottlenecks correspond to the dynamic components of the interaction network-they are significantly less well coexpressed with their neighbors than non-bottlenecks, implying that expression dynamics is wired into the network topology. PMID:17447836

  19. Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality.

    Elena Zotenko

    Full Text Available The centrality-lethality rule, which notes that high-degree nodes in a protein interaction network tend to correspond to proteins that are essential, suggests that the topological prominence of a protein in a protein interaction network may be a good predictor of its biological importance. Even though the correlation between degree and essentiality was confirmed by many independent studies, the reason for this correlation remains illusive. Several hypotheses about putative connections between essentiality of hubs and the topology of protein-protein interaction networks have been proposed, but as we demonstrate, these explanations are not supported by the properties of protein interaction networks. To identify the main topological determinant of essentiality and to provide a biological explanation for the connection between the network topology and essentiality, we performed a rigorous analysis of six variants of the genomewide protein interaction network for Saccharomyces cerevisiae obtained using different techniques. We demonstrated that the majority of hubs are essential due to their involvement in Essential Complex Biological Modules, a group of densely connected proteins with shared biological function that are enriched in essential proteins. Moreover, we rejected two previously proposed explanations for the centrality-lethality rule, one relating the essentiality of hubs to their role in the overall network connectivity and another relying on the recently published essential protein interactions model.

  20. Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

    Hjerrild, M.; Stensballe, A.; Rasmussen, T.E.; Kofoed, C.B.; Blom, Nikolaj; Sicheritz-Pontén, Thomas; Larsen, M.R.; Brunak, Søren; Jensen, O.N.; Gammeltoft, S.

    2004-01-01

    Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein...... kinase A (PKA) phosphorylation sites. The neural network was trained with a positive set of 258 experimentally verified PKA phosphorylation sites. The predictions by NetPhosK were! validated using four novel PKA substrates: Necdin, RFX5, En-2, and Wee 1. The four proteins were phosphorylated by PKA in...

  1. Reuse of structural domain–domain interactions in protein networks

    Bateman Alex

    2007-07-01

    Full Text Available Abstract Background Protein interactions are thought to be largely mediated by interactions between structural domains. Databases such as iPfam relate interactions in protein structures to known domain families. Here, we investigate how the domain interactions from the iPfam database are distributed in protein interactions taken from the HPRD, MPact, BioGRID, DIP and IntAct databases. Results We find that known structural domain interactions can only explain a subset of 4–19% of the available protein interactions, nevertheless this fraction is still significantly bigger than expected by chance. There is a correlation between the frequency of a domain interaction and the connectivity of the proteins it occurs in. Furthermore, a large proportion of protein interactions can be attributed to a small number of domain interactions. We conclude that many, but not all, domain interactions constitute reusable modules of molecular recognition. A substantial proportion of domain interactions are conserved between E. coli, S. cerevisiae and H. sapiens. These domains are related to essential cellular functions, suggesting that many domain interactions were already present in the last universal common ancestor. Conclusion Our results support the concept of domain interactions as reusable, conserved building blocks of protein interactions, but also highlight the limitations currently imposed by the small number of available protein structures.

  2. Mining protein interactomes to improve their reliability and support the advancement of network medicine

    Alanis-Lobato, Gregorio

    2015-09-23

    High-throughput detection of protein interactions has had a major impact in our understanding of the intricate molecular machinery underlying the living cell, and has permitted the construction of very large protein interactomes. The protein networks that are currently available are incomplete and a significant percentage of their interactions are false positives. Fortunately, the structural properties observed in good quality social or technological networks are also present in biological systems. This has encouraged the development of tools, to improve the reliability of protein networks and predict new interactions based merely on the topological characteristics of their components. Since diseases are rarely caused by the malfunction of a single protein, having a more complete and reliable interactome is crucial in order to identify groups of inter-related proteins involved in disease etiology. These system components can then be targeted with minimal collateral damage. In this article, an important number of network mining tools is reviewed, together with resources from which reliable protein interactomes can be constructed. In addition to the review, a few representative examples of how molecular and clinical data can be integrated to deepen our understanding of pathogenesis are discussed.

  3. Uncovering protein interaction in abstracts and text using a novel linear model and word proximity networks

    Abi-Haidar, Alaa; Maguitman, Ana G; Radivojac, Predrag; Retchsteiner, Andreas; Verspoor, Karin; Wang, Zhiping; Rocha, Luis M; 10.1186/gb-2008-9-s2-s11

    2008-01-01

    We participated in three of the protein-protein interaction subtasks of the Second BioCreative Challenge: classification of abstracts relevant for protein-protein interaction (IAS), discovery of protein pairs (IPS) and text passages characterizing protein interaction (ISS) in full text documents. We approached the abstract classification task with a novel, lightweight linear model inspired by spam-detection techniques, as well as an uncertainty-based integration scheme. We also used a Support Vector Machine and the Singular Value Decomposition on the same features for comparison purposes. Our approach to the full text subtasks (protein pair and passage identification) includes a feature expansion method based on word-proximity networks. Our approach to the abstract classification task (IAS) was among the top submissions for this task in terms of the measures of performance used in the challenge evaluation (accuracy, F-score and AUC). We also report on a web-tool we produced using our approach: the Protein Int...

  4. The architectural network for protein secondary structure prediction

    Anindya Sundar Panja

    2016-07-01

    Full Text Available Over the past 25 years, the accuracy of proteins secondary structure prediction has improved substantially. Recently evolutionary information taken from the deviation of proteins in some structural family have again enhance prediction accuracy for all these residues predicted correctly is in one of the three sates helix, strands and others . The new methods developed over the past few years may be interesting in context of improvements which is achieved through combination of the existing methods. Evolutionary divergences profile posses’ adequate information to improve protein secondary structure prediction accuracy. These profiles can also able to correctly predict long stretches of identical residues in other secondary structure. This sequence structure relationship may help to help to developed tool which can efficiently predict the protein secondary structure from its amino acid sequence

  5. Prediction of beta-turns in proteins using neural networks.

    McGregor, M J; Flores, T P; Sternberg, M J

    1989-05-01

    The use of neural networks to improve empirical secondary structure prediction is explored with regard to the identification of the position and conformational class of beta-turns, a four-residue chain reversal. Recently an algorithm was developed for beta-turn predictions based on the empirical approach of Chou and Fasman using different parameters for three classes (I, II and non-specific) of beta-turns. In this paper, using the same data, an alternative approach to derive an empirical prediction method is used based on neural networks which is a general learning algorithm extensively used in artificial intelligence. Thus the results of the two approaches can be compared. The most severe test of prediction accuracy is the percentage of turn predictions that are correct and the neural network gives an overall improvement from 20.6% to 26.0%. The proportion of correctly predicted residues is 71%, compared to a chance level of about 58%. Thus neural networks provide a method of obtaining more accurate predictions from empirical data than a simpler method of deriving propensities. PMID:2748568

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

    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 non-incorporated protein in concert with numerous insect and plant proteins to regulate virus movem...

  7. Gene, protein, and network of male sterility in rice

    WANG Kun; Peng, Xiaojue; Ji, Yanxiao; Yang, Pingfang; Zhu, Yingguo; LI, SHAOQING

    2013-01-01

    Rice is one of the most important model crop plants whose heterosis has been well-exploited in commercial hybrid seed production via a variety of types of male-sterile lines. Hybrid rice cultivation area is steadily expanding around the world, especially in Southern Asia. Characterization of genes and proteins related to male sterility aims to understand how and why the male sterility occurs, and which proteins are the key players for microspores abortion. Recently, a series of genes and prot...

  8. Study on the isothermal forging process of MB26 magnesium alloy adaptor

    Xu Wenchen; Yang Chuan; Shaninst Debin; Xu Fuchang; Wang Guan; Guo Bin

    2015-01-01

    The isothermal forging process is an effective method to manufacture complex-shaped components of hard-to-work materials, such as magnesium alloys. This study investigates the isothermal forging process of an MB26 magnesium alloy adaptor with three branches. The results show that two-step forging process is appropriate to form the adaptor forging, which not only improves the filling quality but also reduces the forging load compared with one-step forging process. Moreover, the flow line is di...

  9. A combinatorial approach to detect coevolved amino acid networks in protein families of variable divergence.

    Julie Baussand

    2009-09-01

    Full Text Available Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity, allosteric regulation and conformational change as residues directly contacting the substrate. The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues. Networks of interaction between coevolved residues can be reconstructed, and from the networks, one can possibly derive insights into functional mechanisms for the protein family. We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences, the associated distance tree and the combinatorics of its subtrees. The degree of coevolution of all pairs of coevolved residues is identified numerically, and networks are reconstructed with a dedicated clustering algorithm. The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed. We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence.

  10. Toward a rigorous network of protein-protein interactions of the model sulfate reducer Desulfovibrio vulgaris Hildenborough

    Chhabra, S.R.; Joachimiak, M.P.; Petzold, C.J.; Zane, G.M.; Price, M.N.; Gaucher, S.; Reveco, S.A.; Fok, V.; Johanson, A.R.; Batth, T.S.; Singer, M.; Chandonia, J.M.; Joyner, D.; Hazen, T.C.; Arkin, A.P.; Wall, J.D.; Singh, A.K.; Keasling, J.D.

    2011-05-01

    Protein–protein interactions offer an insight into cellular processes beyond what may be obtained by the quantitative functional genomics tools of proteomics and transcriptomics. The aforementioned tools have been extensively applied to study E. coli and other aerobes and more recently to study the stress response behavior of Desulfovibrio 5 vulgaris Hildenborough, a model anaerobe and sulfate reducer. In this paper we present the first attempt to identify protein-protein interactions in an obligate anaerobic bacterium. We used suicide vector-assisted chromosomal modification of 12 open reading frames encoded by this sulfate reducer to append an eight amino acid affinity tag to the carboxy-terminus of the chosen proteins. Three biological replicates of the 10 ‘pulled-down’ proteins were separated and analyzed using liquid chromatography-mass spectrometry. Replicate agreement ranged between 35% and 69%. An interaction network among 12 bait and 90 prey proteins was reconstructed based on 134 bait-prey interactions computationally identified to be of high confidence. We discuss the biological significance of several unique metabolic features of D. vulgaris revealed by this protein-protein interaction data 15 and protein modifications that were observed. These include the distinct role of the putative carbon monoxide-induced hydrogenase, unique electron transfer routes associated with different oxidoreductases, and the possible role of methylation in regulating sulfate reduction.

  11. Hepatitis C Virus Protein Interaction Network Analysis Based on Hepatocellular Carcinoma.

    Han, Yuewen; Niu, Jun; Wang, Dong; Li, Yuanyuan

    2016-01-01

    Epidemiological studies have validated the association between hepatitis C virus (HCV) infection and hepatocellular carcinoma (HCC). An increasing number of studies show that protein-protein interactions (PPIs) between HCV proteins and host proteins play a vital role in infection and mediate HCC progression. In this work, we collected all published interaction between HCV and human proteins, which include 455 unique human proteins participating in 524 HCV-human interactions. Then, we construct the HCV-human and HCV-HCC protein interaction networks, which display the biological knowledge regarding the mechanism of HCV pathogenesis, particularly with respect to pathogenesis of HCC. Through in-depth analysis of the HCV-HCC interaction network, we found that interactors are enriched in the JAK/STAT, p53, MAPK, TNF, Wnt, and cell cycle pathways. Using a random walk with restart algorithm, we predicted the importance of each protein in the HCV-HCC network and found that AKT1 may play a key role in the HCC progression. Moreover, we found that NS5A promotes HCC cells proliferation and metastasis by activating AKT/GSK3β/β-catenin pathway. This work provides a basis for a detailed map tracking new cellular interactions of HCV and identifying potential targets for HCV-related hepatocellular carcinoma treatment. PMID:27115606

  12. Dynamic changes in protein functional linkage networks revealed by integration with gene expression data.

    Shubhada R Hegde

    2008-11-01

    Full Text Available Response of cells to changing environmental conditions is governed by the dynamics of intricate biomolecular interactions. It may be reasonable to assume, proteins being the dominant macromolecules that carry out routine cellular functions, that understanding the dynamics of protein:protein interactions might yield useful insights into the cellular responses. The large-scale protein interaction data sets are, however, unable to capture the changes in the profile of protein:protein interactions. In order to understand how these interactions change dynamically, we have constructed conditional protein linkages for Escherichia coli by integrating functional linkages and gene expression information. As a case study, we have chosen to analyze UV exposure in wild-type and SOS deficient E. coli at 20 minutes post irradiation. The conditional networks exhibit similar topological properties. Although the global topological properties of the networks are similar, many subtle local changes are observed, which are suggestive of the cellular response to the perturbations. Some such changes correspond to differences in the path lengths among the nodes of carbohydrate metabolism correlating with its loss in efficiency in the UV treated cells. Similarly, expression of hubs under unique conditions reflects the importance of these genes. Various centrality measures applied to the networks indicate increased importance for replication, repair, and other stress proteins for the cells under UV treatment, as anticipated. We thus propose a novel approach for studying an organism at the systems level by integrating genome-wide functional linkages and the gene expression data.

  13. Hepatitis C Virus Protein Interaction Network Analysis Based on Hepatocellular Carcinoma.

    Yuewen Han

    Full Text Available Epidemiological studies have validated the association between hepatitis C virus (HCV infection and hepatocellular carcinoma (HCC. An increasing number of studies show that protein-protein interactions (PPIs between HCV proteins and host proteins play a vital role in infection and mediate HCC progression. In this work, we collected all published interaction between HCV and human proteins, which include 455 unique human proteins participating in 524 HCV-human interactions. Then, we construct the HCV-human and HCV-HCC protein interaction networks, which display the biological knowledge regarding the mechanism of HCV pathogenesis, particularly with respect to pathogenesis of HCC. Through in-depth analysis of the HCV-HCC interaction network, we found that interactors are enriched in the JAK/STAT, p53, MAPK, TNF, Wnt, and cell cycle pathways. Using a random walk with restart algorithm, we predicted the importance of each protein in the HCV-HCC network and found that AKT1 may play a key role in the HCC progression. Moreover, we found that NS5A promotes HCC cells proliferation and metastasis by activating AKT/GSK3β/β-catenin pathway. This work provides a basis for a detailed map tracking new cellular interactions of HCV and identifying potential targets for HCV-related hepatocellular carcinoma treatment.

  14. Predicting the binding patterns of hub proteins: a study using yeast protein interaction networks.

    Carson M Andorf

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

  15. Insights into biological information processing: structural and dynamical analysis of a human protein signalling network

    We present an investigation on the structural and dynamical properties of a 'human protein signalling network' (HPSN). This biological network is composed of nodes that correspond to proteins and directed edges that represent signal flows. In order to gain insight into the organization of cell information processing this network is analysed taking into account explicitly the edge directions. We explore the topological properties of the HPSN at the global and the local scale, further applying the generating function formalism to provide a suitable comparative model. The relationship between the node degrees and the distribution of signals through the network is characterized using degree correlation profiles. Finally, we analyse the dynamical properties of small sub-graphs showing high correlation between their occurrence and dynamic stability

  16. BioNetwork Bench: Database and Software for Storage, Query, and Analysis of Gene and Protein Networks

    Oksana Kohutyuk; Fadi Towfic; M. Heather West Greenlee; Vasant Honavar

    2012-01-01

    Gene and protein networks offer a powerful approach for integration of the disparate yet complimentary types of data that result from high-throughput analyses. Although many tools and databases are currently available for accessing such data, they are left unutilized by bench scientists as they generally lack features for effective analysis and integration of both public and private datasets and do not offer an intuitive interface for use by scientists with limited computational expertise. We...

  17. Transmembrane adaptor molecules: a new category of lymphoid-cell markers.

    Tedoldi, Sara; Paterson, Jennifer C; Hansmann, Martin-Leo; Natkunam, Yasodha; Rüdiger, Thomas; Angelisova, Pavla; Du, Ming Q; Roberton, Helen; Roncador, Giovanna; Sanchez, Lydia; Pozzobon, Michela; Masir, Noraidah; Barry, Richard; Pileri, Stefano; Mason, David Y; Marafioti, Teresa; Horejsí, Václav

    2006-01-01

    Transmembrane adaptor proteins (of which 7 have been identified so far) are involved in receptor signaling in immune cells. They have only a short extracellular region, with most of the molecule comprising a substantial intracytoplasmic region carrying multiple tyrosine residues that can be phosphorylated by Src- or Syk-family kinases. In this paper, we report an immunohistologic study of 6 of these molecules in normal and neoplastic human tissue sections and show that they are restricted to subpopulations of lymphoid cells, being present in either T cells (LAT, LIME, and TRIM), B cells (NTAL), or subsets of both cell types (PAG and SIT). Their expression in neoplastic lymphoid cells broadly reflects that of normal lymphoid tissue, including the positivity of plasma cells and myeloma/plasmacytoma for LIME, NTAL, PAG, and SIT. However, this study also revealed some reactions that may be of diagnostic/prognostic value. For example, lymphocytic lymphoma and mantle-cell lymphoma showed similar profiles but differed clearly from follicle-center lymphoma, whereas PAG tended to be selectively expressed in germinal center-derived subsets of diffuse large B-cell lymphoma. These molecules represent a potentially important addition to the panel of immunophenotypic markers detectable in routine biopsies that can be used in hematopathologic studies. PMID:16160011

  18. A hybrid graph-theoretic method for mining overlapping functional modules in large sparse protein interaction networks.

    Zhang, Shihua; Liu, Hong-Wei; Ning, Xue-Mei; Zhang, Xiang-Sun

    2009-01-01

    Modular architecture, which encompasses groups of genes/proteins involved in elementary biological functional units, is a basic form of the organisation of interacting proteins. Here, we propose a method that combines the Line Graph Transformation (LGT) and clique percolation-clustering algorithm to detect network modules, which may overlap each other in large sparse PPI networks. The resulting modules by the present method show a high coverage among yeast, fly, and worm PPI networks, respectively. Our analysis of the yeast PPI network suggests that most of these modules have well-biological significance in context of protein localisation, function annotation, and protein complexes. PMID:19432377

  19. Yeast Interacting Proteins Database: YCL032W, YLR423C [Yeast Interacting Proteins Database

    Full Text Available YCL032W STE50 Protein involved in mating response, invasive/filamentous growth, and...lved in mating response, invasive/filamentous growth, and osmotolerance, acts as an adaptor that links G pro

  20. Dynamic Proteomic Characteristics and Network Integration Revealing Key Proteins for Two Kernel Tissue Developments in Popcorn.

    Dong, Yongbin; Wang, Qilei; Zhang, Long; Du, Chunguang; Xiong, Wenwei; Chen, Xinjian; Deng, Fei; Ma, Zhiyan; Qiao, Dahe; Hu, Chunhui; Ren, Yangliu; Li, Yuling

    2015-01-01

    The formation and development of maize kernel is a complex dynamic physiological and biochemical process that involves the temporal and spatial expression of many proteins and the regulation of metabolic pathways. In this study, the protein profiles of the endosperm and pericarp at three important developmental stages were analyzed by isobaric tags for relative and absolute quantification (iTRAQ) labeling coupled with LC-MS/MS in popcorn inbred N04. Comparative quantitative proteomic analyses among developmental stages and between tissues were performed, and the protein networks were integrated. A total of 6,876 proteins were identified, of which 1,396 were nonredundant. Specific proteins and different expression patterns were observed across developmental stages and tissues. The functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the development of the tissues. The whole, endosperm-specific and pericarp-specific protein networks integrated 125, 9 and 77 proteins, respectively, which were involved in 54 KEGG pathways and reflected their complex metabolic interactions. Confirmation for the iTRAQ endosperm proteins by two-dimensional gel electrophoresis showed that 44.44% proteins were commonly found. However, the concordance between mRNA level and the protein abundance varied across different proteins, stages, tissues and inbred lines, according to the gene cloning and expression analyses of four relevant proteins with important functions and different expression levels. But the result by western blot showed their same expression tendency for the four proteins as by iTRAQ. These results could provide new insights into the developmental mechanisms of endosperm and pericarp, and grain formation in maize. PMID:26587848

  1. Dynamic Proteomic Characteristics and Network Integration Revealing Key Proteins for Two Kernel Tissue Developments in Popcorn.

    Yongbin Dong

    Full Text Available The formation and development of maize kernel is a complex dynamic physiological and biochemical process that involves the temporal and spatial expression of many proteins and the regulation of metabolic pathways. In this study, the protein profiles of the endosperm and pericarp at three important developmental stages were analyzed by isobaric tags for relative and absolute quantification (iTRAQ labeling coupled with LC-MS/MS in popcorn inbred N04. Comparative quantitative proteomic analyses among developmental stages and between tissues were performed, and the protein networks were integrated. A total of 6,876 proteins were identified, of which 1,396 were nonredundant. Specific proteins and different expression patterns were observed across developmental stages and tissues. The functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the development of the tissues. The whole, endosperm-specific and pericarp-specific protein networks integrated 125, 9 and 77 proteins, respectively, which were involved in 54 KEGG pathways and reflected their complex metabolic interactions. Confirmation for the iTRAQ endosperm proteins by two-dimensional gel electrophoresis showed that 44.44% proteins were commonly found. However, the concordance between mRNA level and the protein abundance varied across different proteins, stages, tissues and inbred lines, according to the gene cloning and expression analyses of four relevant proteins with important functions and different expression levels. But the result by western blot showed their same expression tendency for the four proteins as by iTRAQ. These results could provide new insights into the developmental mechanisms of endosperm and pericarp, and grain formation in maize.

  2. Mass-action equilibrium and non-specific interactions in protein binding networks

    Maslov, Sergei

    2009-03-01

    Large-scale protein binding networks serve as a paradigm of complex properties of living cells. These networks are naturally weighted with edges characterized by binding strength and protein-nodes -- by their concentrations. However, the state-of-the-art high-throughput experimental techniques generate just a binary (yes or no) information about individual interactions. As a result, most of the previous research concentrated just on topology of these networks. In a series of recent publications [1-4] my collaborators and I went beyond purely topological studies and calculated the mass-action equilibrium of a genome-wide binding network using experimentally determined protein concentrations, localizations, and reliable binding interactions in baker's yeast. We then studied how this equilibrium responds to large perturbations [1-2] and noise [3] in concentrations of proteins. We demonstrated that the change in the equilibrium concentration of a protein exponentially decays (and sign-alternates) with its network distance away from the perturbed node. This explains why, despite a globally connected topology, individual functional modules in such networks are able to operate fairly independently. In a separate study [4] we quantified the interplay between specific and non-specific binding interactions under crowded conditions inside living cells. We show how the need to limit the waste of resources constrains the number of types and concentrations of proteins that are present at the same time and at the same place in yeast cells. [1] S Maslov, I. Ispolatov, PNAS 104:13655 (2007). [2] S. Maslov, K. Sneppen, I. Ispolatov, New J. of Phys. 9: 273 (2007). [3] K-K. Yan, D. Walker, S. Maslov, PRL accepted (2008). [4] J. Zhang, S. Maslov, and E. I. Shakhnovich, Mol Syst Biol 4, 210 (2008).

  3. Building and analyzing protein interactome networks by cross-species comparisons

    Blackman Barron

    2010-03-01

    Full Text Available Abstract Background A genomic catalogue of protein-protein interactions is a rich source of information, particularly for exploring the relationships between proteins. Numerous systems-wide and small-scale experiments have been conducted to identify interactions; however, our knowledge of all interactions for any one species is incomplete, and alternative means to expand these network maps is needed. We therefore took a comparative biology approach to predict protein-protein interactions across five species (human, mouse, fly, worm, and yeast and developed InterologFinder for research biologists to easily navigate this data. We also developed a confidence score for interactions based on available experimental evidence and conservation across species. Results The connectivity of the resultant networks was determined to have scale-free distribution, small-world properties, and increased local modularity, indicating that the added interactions do not disrupt our current understanding of protein network structures. We show examples of how these improved interactomes can be used to analyze a genome-scale dataset (RNAi screen and to assign new function to proteins. Predicted interactions within this dataset were tested by co-immunoprecipitation, resulting in a high rate of validation, suggesting the high quality of networks produced. Conclusions Protein-protein interactions were predicted in five species, based on orthology. An InteroScore, a score accounting for homology, number of orthologues with evidence of interactions, and number of unique observations of interactions, is given to each known and predicted interaction. Our website http://www.interologfinder.org provides research biologists intuitive access to this data.

  4. Revisiting date and party hubs: novel approaches to role assignment in protein interaction networks.

    Sumeet Agarwal

    2010-06-01

    Full Text Available The idea of "date" and "party" hubs has been influential in the study of protein-protein interaction networks. Date hubs display low co-expression with their partners, whilst party hubs have high co-expression. It was proposed that party hubs are local coordinators whereas date hubs are global connectors. Here, we show that the reported importance of date hubs to network connectivity can in fact be attributed to a tiny subset of them. Crucially, these few, extremely central, hubs do not display particularly low expression correlation, undermining the idea of a link between this quantity and hub function. The date/party distinction was originally motivated by an approximately bimodal distribution of hub co-expression; we show that this feature is not always robust to methodological changes. Additionally, topological properties of hubs do not in general correlate with co-expression. However, we find significant correlations between interaction centrality and the functional similarity of the interacting proteins. We suggest that thinking in terms of a date/party dichotomy for hubs in protein interaction networks is not meaningful, and it might be more useful to conceive of roles for protein-protein interactions rather than for individual proteins.

  5. Membrane tubule formation by banana-shaped proteins with or without transient network structure

    Noguchi, Hiroshi

    2016-02-01

    In living cells, membrane morphology is regulated by various proteins. Many membrane reshaping proteins contain a Bin/Amphiphysin/Rvs (BAR) domain, which consists of a banana-shaped rod. The BAR domain bends the biomembrane along the rod axis and the features of this anisotropic bending have recently been studied. Here, we report on the role of the BAR protein rods in inducing membrane tubulation, using large-scale coarse-grained simulations. We reveal that a small spontaneous side curvature perpendicular to the rod can drastically alter the tubulation dynamics at high protein density, whereas no significant difference is obtained at low density. A percolated network is intermediately formed depending on the side curvature. This network suppresses tubule protrusion, leading to the slow formation of fewer tubules. Thus, the side curvature, which is generated by protein-protein and membrane-protein interactions, plays a significant role in tubulation dynamics. We also find that positive surface tensions and the vesicle membrane curvature can stabilize this network structure by suppressing the tubulation.

  6. Functional protein networks unifying limb girdle muscular dystrophy

    Morrée, Antoine de

    2011-01-01

    Limb Girdle Muscular Dystrophy (LGMD) is a rare progressive heterogeneous disorder that can be caused by mutations in at least 21 different genes. These genes are often widely expressed and encode proteins with highly differing functions. And yet mutations in all of them give rise to a similar clini

  7. Eukaryotic LYR Proteins Interact with Mitochondrial Protein Complexes.

    Angerer, Heike

    2015-01-01

    In eukaryotic cells, mitochondria host ancient essential bioenergetic and biosynthetic pathways. LYR (leucine/tyrosine/arginine) motif proteins (LYRMs) of the Complex1_LYR-like superfamily interact with protein complexes of bacterial origin. Many LYR proteins function as extra subunits (LYRM3 and LYRM6) or novel assembly factors (LYRM7, LYRM8, ACN9 and FMC1) of the oxidative phosphorylation (OXPHOS) core complexes. Structural insights into complex I accessory subunits LYRM6 and LYRM3 have been provided by analyses of EM and X-ray structures of complex I from bovine and the yeast Yarrowia lipolytica, respectively. Combined structural and biochemical studies revealed that LYRM6 resides at the matrix arm close to the ubiquinone reduction site. For LYRM3, a position at the distal proton-pumping membrane arm facing the matrix space is suggested. Both LYRMs are supposed to anchor an acyl-carrier protein (ACPM) independently to complex I. The function of this duplicated protein interaction of ACPM with respiratory complex I is still unknown. Analysis of protein-protein interaction screens, genetic analyses and predicted multi-domain LYRMs offer further clues on an interaction network and adaptor-like function of LYR proteins in mitochondria. PMID:25686363

  8. Eukaryotic LYR Proteins Interact with Mitochondrial Protein Complexes

    Heike Angerer

    2015-02-01

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

  9. Regulation of lifespan, metabolism, and stress responses by the Drosophila SH2B protein, Lnk.

    Cathy Slack

    2010-03-01

    Full Text Available Drosophila Lnk is the single ancestral orthologue of a highly conserved family of structurally-related intracellular adaptor proteins, the SH2B proteins. As adaptors, they lack catalytic activity but contain several protein-protein interaction domains, thus playing a critical role in signal transduction from receptor tyrosine kinases to form protein networks. Physiological studies of SH2B function in mammals have produced conflicting data. However, a recent study in Drosophila has shown that Lnk is an important regulator of the insulin/insulin-like growth factor (IGF-1 signaling (IIS pathway during growth, functioning in parallel to the insulin receptor substrate, Chico. As this pathway also has an evolutionary conserved role in the determination of organism lifespan, we investigated whether Lnk is required for normal lifespan in Drosophila. Phenotypic analysis of mutants for Lnk revealed that loss of Lnk function results in increased lifespan and improved survival under conditions of oxidative stress and starvation. Starvation resistance was found to be associated with increased metabolic stores of carbohydrates and lipids indicative of impaired metabolism. Biochemical and genetic data suggest that Lnk functions in both the IIS and Ras/Mitogen activated protein Kinase (MapK signaling pathways. Microarray studies support this model, showing transcriptional feedback onto genes in both pathways as well as indicating global changes in both lipid and carbohydrate metabolism. Finally, our data also suggest that Lnk itself may be a direct target of the IIS responsive transcription factor, dFoxo, and that dFoxo may repress Lnk expression. We therefore describe novel functions for a member of the SH2B protein family and provide the first evidence for potential mechanisms of SH2B regulation. Our findings suggest that IIS signaling in Drosophila may require the activity of a second intracellular adaptor, thereby yielding fundamental new insights into the

  10. Multiplex matrix network analysis of protein complexes in the human TCR signalosome.

    Smith, Stephen E P; Neier, Steven C; Reed, Brendan K; Davis, Tessa R; Sinnwell, Jason P; Eckel-Passow, Jeanette E; Sciallis, Gabriel F; Wieland, Carilyn N; Torgerson, Rochelle R; Gil, Diana; Neuhauser, Claudia; Schrum, Adam G

    2016-01-01

    Multiprotein complexes transduce cellular signals through extensive interaction networks, but the ability to analyze these networks in cells from small clinical biopsies is limited. To address this, we applied an adaptable multiplex matrix system to physiologically relevant signaling protein complexes isolated from a cell line or from human patient samples. Focusing on the proximal T cell receptor (TCR) signalosome, we assessed 210 pairs of PiSCES (proteins in shared complexes detected by exposed surface epitopes). Upon stimulation of Jurkat cells with superantigen-loaded antigen-presenting cells, this system produced high-dimensional data that enabled visualization of network activity. A comprehensive analysis platform generated PiSCES biosignatures by applying unsupervised hierarchical clustering, principal component analysis, an adaptive nonparametric with empirical cutoff analysis, and weighted correlation network analysis. We generated PiSCES biosignatures from 4-mm skin punch biopsies from control patients or patients with the autoimmune skin disease alopecia areata. This analysis distinguished disease patients from the controls, detected enhanced basal TCR signaling in the autoimmune patients, and identified a potential signaling network signature that may be indicative of disease. Thus, generation of PiSCES biosignatures represents an approach that can provide information about the activity of protein signaling networks in samples including low-abundance primary cells from clinical biopsies. PMID:27485017

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

    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

  12. Integration and visualization of non-coding RNA and protein interaction networks

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

    2015-01-01

    Non-coding RNAs (ncRNAs) fulfill a diverse set of biological functions relying on interactions with other molecular entities. The advent of new experimental and computational approaches makes it possible to study ncRNAs and their associations on an unprecedented scale. We present RAIN (RNA Association and Interaction Networks) - a database that combines ncRNA-ncRNA, ncRNA-mRNA and ncRNA-protein interactions with large-scale protein association networks available in the STRING database. By int...

  13. Modification of gene duplicability during the evolution of protein interaction network.

    Matteo D'Antonio

    2011-04-01

    Full Text Available Duplications of genes encoding highly connected and essential proteins are selected against in several species but not in human, where duplicated genes encode highly connected proteins. To understand when and how gene duplicability changed in evolution, we compare gene and network properties in four species (Escherichia coli, yeast, fly, and human that are representative of the increase in evolutionary complexity, defined as progressive growth in the number of genes, cells, and cell types. We find that the origin and conservation of a gene significantly correlates with the properties of the encoded protein in the protein-protein interaction network. All four species preserve a core of singleton and central hubs that originated early in evolution, are highly conserved, and accomplish basic biological functions. Another group of hubs appeared in metazoans and duplicated in vertebrates, mostly through vertebrate-specific whole genome duplication. Such recent and duplicated hubs are frequently targets of microRNAs and show tissue-selective expression, suggesting that these are alternative mechanisms to control their dosage. Our study shows how networks modified during evolution and contributes to explaining the occurrence of somatic genetic diseases, such as cancer, in terms of network perturbations.

  14. ModuleRole: a tool for modulization, role determination and visualization in protein-protein interaction networks.

    Guipeng Li

    Full Text Available Rapidly increasing amounts of (physical and genetic protein-protein interaction (PPI data are produced by various high-throughput techniques, and interpretation of these data remains a major challenge. In order to gain insight into the organization and structure of the resultant large complex networks formed by interacting molecules, using simulated annealing, a method based on the node connectivity, we developed ModuleRole, a user-friendly web server tool which finds modules in PPI network and defines the roles for every node, and produces files for visualization in Cytoscape and Pajek. For given proteins, it analyzes the PPI network from BioGRID database, finds and visualizes the modules these proteins form, and then defines the role every node plays in this network, based on two topological parameters Participation Coefficient and Z-score. This is the first program which provides interactive and very friendly interface for biologists to find and visualize modules and roles of proteins in PPI network. It can be tested online at the website http://www.bioinfo.org/modulerole/index.php, which is free and open to all users and there is no login requirement, with demo data provided by "User Guide" in the menu Help. Non-server application of this program is considered for high-throughput data with more than 200 nodes or user's own interaction datasets. Users are able to bookmark the web link to the result page and access at a later time. As an interactive and highly customizable application, ModuleRole requires no expert knowledge in graph theory on the user side and can be used in both Linux and Windows system, thus a very useful tool for biologist to analyze and visualize PPI networks from databases such as BioGRID.ModuleRole is implemented in Java and C, and is freely available at http://www.bioinfo.org/modulerole/index.php. Supplementary information (user guide, demo data is also available at this website. API for ModuleRole used for this

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

    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.; Legrain, Pierre

    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 geno...

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

    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.; Legrain, Pierre

    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 (L¯ike 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 ge...

  17. Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins.

    Champeimont, Raphaël; Laine, Elodie; Hu, Shuang-Wei; Penin, Francois; Carbone, Alessandra

    2016-01-01

    A novel computational approach of coevolution analysis allowed us to reconstruct the protein-protein interaction network of the Hepatitis C Virus (HCV) at the residue resolution. For the first time, coevolution analysis of an entire viral genome was realized, based on a limited set of protein sequences with high sequence identity within genotypes. The identified coevolving residues constitute highly relevant predictions of protein-protein interactions for further experimental identification of HCV protein complexes. The method can be used to analyse other viral genomes and to predict the associated protein interaction networks. PMID:27198619

  18. Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins

    Champeimont, Raphaël; Laine, Elodie; Hu, Shuang-Wei; Penin, Francois; Carbone, Alessandra

    2016-05-01

    A novel computational approach of coevolution analysis allowed us to reconstruct the protein-protein interaction network of the Hepatitis C Virus (HCV) at the residue resolution. For the first time, coevolution analysis of an entire viral genome was realized, based on a limited set of protein sequences with high sequence identity within genotypes. The identified coevolving residues constitute highly relevant predictions of protein-protein interactions for further experimental identification of HCV protein complexes. The method can be used to analyse other viral genomes and to predict the associated protein interaction networks.

  19. Topological robustness analysis of protein interaction networks reveals key targets for overcoming chemotherapy resistance in glioma

    Azevedo, Hátylas; Moreira-Filho, Carlos Alberto

    2015-11-01

    Biological networks display high robustness against random failures but are vulnerable to targeted attacks on central nodes. Thus, network topology analysis represents a powerful tool for investigating network susceptibility against targeted node removal. Here, we built protein interaction networks associated with chemoresistance to temozolomide, an alkylating agent used in glioma therapy, and analyzed their modular structure and robustness against intentional attack. These networks showed functional modules related to DNA repair, immunity, apoptosis, cell stress, proliferation and migration. Subsequently, network vulnerability was assessed by means of centrality-based attacks based on the removal of node fractions in descending orders of degree, betweenness, or the product of degree and betweenness. This analysis revealed that removing nodes with high degree and high betweenness was more effective in altering networks’ robustness parameters, suggesting that their corresponding proteins may be particularly relevant to target temozolomide resistance. In silico data was used for validation and confirmed that central nodes are more relevant for altering proliferation rates in temozolomide-resistant glioma cell lines and for predicting survival in glioma patients. Altogether, these results demonstrate how the analysis of network vulnerability to topological attack facilitates target prioritization for overcoming cancer chemoresistance.

  20. Protein Secondary Structure Prediction using Pattern Recognition Neural Network

    P.V. Nageswara Rao

    2010-06-01

    Full Text Available Proteins are key biological molecules with diverse functions. With newer technologies producing more data (genomics, proteomics than can be annotated manually, in silico methods of predicting their structure and thereafter their function has been christened the Holy Grail of structural bioinformatics. Successful secondary structureprediction provides a starting point for direct tertiary structure modeling; in addition it improves sequence analysis and sequence-structure binding for structure and function determination. Using machine learning and data mining process, we developed a pattern recognition technique based on statistical for predicting protein secondary structure from the component amino acid sequence. By applying this technique, a performance score of Q8=72.3% was achieved. This compares well with other established techniques, such as NN-I and GOR IV which achieved Q3 scores of 64.05% and 63.19% respectively when predictions are made on single sequence alone.

  1. Functional protein networks unifying limb girdle muscular dystrophy

    de Morrée, Antoine

    2011-01-01

    Limb Girdle Muscular Dystrophy (LGMD) is a rare progressive heterogeneous disorder that can be caused by mutations in at least 21 different genes. These genes are often widely expressed and encode proteins with highly differing functions. And yet mutations in all of them give rise to a similar clinical presentation: adult onset muscle weakness, with muscles of the pelvic and shoulder girdle as predominantly affected muscle groups. This thesis explores a potential molecular mechanism that unif...

  2. A restricted set of apical proteins recycle through the trans-Golgi network in MDCK cells.

    Brändli, A W; Simons, K

    1989-01-01

    Sorting of newly synthesized proteins destined for the apical plasma membrane takes place in the trans-Golgi network (TGN) in MDCK cells. This process is most likely receptor mediated and requires components that recycle between both compartments. We have developed an assay to detect apical proteins that recycle through the sialyltransferase-containing TGN. Cell surface glycoproteins were exogalactosylated apically using a mutant cell line derived from MDCK, MDCKII-RCAr. The mutant exhibits i...

  3. Supervised maximum-likelihood weighting of composite protein networks for complex prediction

    Yong Chern Han

    2012-12-01

    Full Text Available Abstract Background Protein complexes participate in many important cellular functions, so finding the set of existent complexes is essential for understanding the organization and regulation of processes in the cell. With the availability of large amounts of high-throughput protein-protein interaction (PPI data, many algorithms have been proposed to discover protein complexes from PPI networks. However, such approaches are hindered by the high rate of noise in high-throughput PPI data, including spurious and missing interactions. Furthermore, many transient interactions are detected between proteins that are not from the same complex, while not all proteins from the same complex may actually interact. As a result, predicted complexes often do not match true complexes well, and many true complexes go undetected. Results We address these challenges by integrating PPI data with other heterogeneous data sources to construct a composite protein network, and using a supervised maximum-likelihood approach to weight each edge based on its posterior probability of belonging to a complex. We then use six different clustering algorithms, and an aggregative clustering strategy, to discover complexes in the weighted network. We test our method on Saccharomyces cerevisiae and Homo sapiens, and show that complex discovery is improved: compared to previously proposed supervised and unsupervised weighting approaches, our method recalls more known complexes, achieves higher precision at all recall levels, and generates novel complexes of greater functional similarity. Furthermore, our maximum-likelihood approach allows learned parameters to be used to visualize and evaluate the evidence of novel predictions, aiding human judgment of their credibility. Conclusions Our approach integrates multiple data sources with supervised learning to create a weighted composite protein network, and uses six clustering algorithms with an aggregative clustering strategy to

  4. A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction

    Spencer, Matt; Eickholt, Jesse; Cheng, Jianlin

    2014-01-01

    Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary structure predictions, which are increasingly demanded due to the rapid discovery of proteins. Although recent developments have slightly exceeded previous methods of SS prediction, accuracy has stagnated around 80% and many wonder if prediction cannot be advanced beyond this ceiling. Disciplines that have traditionally employed neural networks are experimenting with novel deep learning techniques in atte...

  5. A network model to investigate structural and electrical properties of proteins

    Alfinito, E; Reggiani, L

    2007-01-01

    One of the main trend in to date research and development is the miniaturization of electronic devices. In this perspective, integrated nanodevices based on proteins or biomolecules are attracting a major interest. In fact, it has been shown that proteins like bacteriorhodopsin and azurin, manifest electrical properties which are promising for the development of active components in the field of molecular electronics. Here we focus on two relevant kinds of proteins: The bovine rhodopsin, prototype of GPCR protein, and the enzyme acetylcholinesterase (AChE), whose inhibition is one of the most qualified treatments of Alzheimer disease. Both these proteins exert their functioning starting with a conformational change of their native structure. Our guess is that such a change should be accompanied with a detectable variation of their electrical properties. To investigate this conjecture, we present an impedance network model of proteins, able to estimate the different electrical response associated with the diff...

  6. Integration of relational and hierarchical network information for protein function prediction

    Jiang Xiaoyu

    2008-08-01

    Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

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

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

    2009-01-01

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

  8. Proteomic dissection of biological pathways/processes through profiling protein-protein interaction networks

    2010-01-01

    Cellular functions, either under the normal or pathological conditions or under different stresses, are the results of the coordinated action of multiple proteins interacting in macromolecular complexes or assemblies. The precise determination of the specific composition of protein complexes, especially using scalable and high-throughput methods, represents a systematic approach toward revealing particular cellular biological functions. In this regard, the direct profiling protein-protein interactions (PPIs) represent an efficient way to dissect functional pathways for revealing novel protein functions. In this review, we illustrate the technological evolution for the large-scale and precise identification of PPIs toward higher physiologically relevant accuracy. These techniques aim at improving the efficiency of complex pull-down, the signal specificity and accuracy in distinguishing specific PPIs, and the accuracy of identifying physiological relevant PPIs. A newly developed streamline proteomic approach for mapping the binary relationship of PPIs in a protein complex is introduced.

  9. A multilayer protein-protein interaction network analysis of different life stages in Caenorhabditis elegans

    Shinde, Pramod; Jalan, Sarika

    2015-12-01

    Molecular networks act as the backbone of cellular activities, providing an excellent opportunity to understand the developmental changes in an organism. While network data usually constitute only stationary network graphs, constructing a multilayer PPI network may provide clues to the particular developmental role at each stage of life and may unravel the importance of these developmental changes. The developmental biology model of Caenorhabditis elegans analyzed here provides a ripe platform to understand the patterns of evolution during the life stages of an organism. In the present study, the widely studied network properties exhibit overall similar statistics for all the PPI layers. Further, the analysis of the degree-degree correlation and spectral properties not only reveals crucial differences in each PPI layer but also indicates the presence of the varying complexity among them. The PPI layer of the nematode life stage exhibits various network properties different to the rest of the PPI layers, indicating the specific role of cellular diversity and developmental transitions at this stage. The framework presented here provides a direction to explore and understand the developmental changes occurring in the different life stages of an organism.

  10. Comparative interactomics analysis of protein family interaction networks using PSIMAP (protein structural interactome map

    Park, D; Lee, S; Bolser, D.; Schroeder, M.; Lappe, M.; Oh, D.; Bhak, J.

    2005-01-01

    Motivation: Many genomes have been completely sequenced. However, detecting and analyzing their protein–protein interactions by experimental methods such as co-immunoprecipitation, tandem affinity purification and Y2H is not as fast as genome sequencing. Therefore, a computational prediction method based on the known protein structural interactions will be useful to analyze large-scale protein–protein interaction rules within and among complete genomes. Results: We confirmed that all the pred...

  11. Interplay between Chaperones and Protein Disorder Promotes the Evolution of Protein Networks

    Sebastian Pechmann; Judith Frydman

    2014-01-01

    Evolution is driven by mutations, which lead to new protein functions but come at a cost to protein stability. Non-conservative substitutions are of interest in this regard because they may most profoundly affect both function and stability. Accordingly, organisms must balance the benefit of accepting advantageous substitutions with the possible cost of deleterious effects on protein folding and stability. We here examine factors that systematically promote non-conservative mutations at the p...

  12. Protein coalitions in a core mammalian biochemical network linked by rapidly evolving proteins

    Tsoka Sophia

    2011-05-01

    Full Text Available Abstract Background Cellular ATP levels are generated by glucose-stimulated mitochondrial metabolism and determine metabolic responses, such as glucose-stimulated insulin secretion (GSIS from the β-cells of pancreatic islets. We describe an analysis of the evolutionary processes affecting the core enzymes involved in glucose-stimulated insulin secretion in mammals. The proteins involved in this system belong to ancient enzymatic pathways: glycolysis, the TCA cycle and oxidative phosphorylation. Results We identify two sets of proteins, or protein coalitions, in this group of 77 enzymes with distinct evolutionary patterns. Members of the glycolysis, TCA cycle, metabolite transport, pyruvate and NADH shuttles have low rates of protein sequence evolution, as inferred from a human-mouse comparison, and relatively high rates of evolutionary gene duplication. Respiratory chain and glutathione pathway proteins evolve faster, exhibiting lower rates of gene duplication. A small number of proteins in the system evolve significantly faster than co-pathway members and may serve as rapidly evolving adapters, linking groups of co-evolving genes. Conclusions Our results provide insights into the evolution of the involved proteins. We find evidence for two coalitions of proteins and the role of co-adaptation in protein evolution is identified and could be used in future research within a functional context.

  13. N-terminal tyrosine modulation of the endocytic adaptor function of the beta-arrestins.

    Marion, Sébastien; Fralish, Gregory B; Laporte, Stéphane; Caron, Marc G; Barak, Larry S

    2007-06-29

    The highly homologous beta-arrestin1 and -2 adaptor proteins play important roles in the function of G protein-coupled receptors. Either beta-arrestin variant can function as a molecular chaperone for clathrin-mediated receptor internalization. This role depends primarily upon two distinct, contiguous C-terminal beta-arrestin motifs recognizing clathrin and the beta-adaptin subunit of AP2. However, a molecular basis is lacking to explain the different endocytic efficacies of the two beta-arrestin isoforms and the observation that beta-arrestin N-terminal substitution mutants can act as dominant negative inhibitors of receptor endocytosis. Despite the near identity of the beta-arrestins throughout their N termini, sequence variability is present at a small number of residues and includes tyrosine to phenylalanine substitutions. Here we show that corresponding N-terminal (Y/F)VTL sequences in beta-arrestin1 and -2 differentially regulate mu-adaptin binding. Our results indicate that the beta-arrestin1 Tyr-54 lessens the interaction with mu-adaptin and moreover is a Src phosphorylation site. A gain of endocytic function is obtained with the beta-arrestin1 Y54F substitution, which improves both the beta-arrestin1 interaction with mu-adaptin and the ability to enhance beta2-adrenergic receptor internalization. These data indicate that beta-arrestin2 utilizes mu-adaptin as an endocytic partner, and that the inability of beta-arrestin1 to sustain a similar degree of interaction with mu-adaptin may result from coordination of Tyr-54 by neighboring residues or its modification by Src kinase. Additionally, these naturally occurring variations in beta-arrestins may also differentially regulate the composition of the signaling complexes organized on the receptor. PMID:17456469

  14. Enhancing the prioritization of disease-causing genes through tissue specific protein interaction networks.

    Oded Magger

    Full Text Available The prioritization of candidate disease-causing genes is a fundamental challenge in the post-genomic era. Current state of the art methods exploit a protein-protein interaction (PPI network for this task. They are based on the observation that genes causing phenotypically-similar diseases tend to lie close to one another in a PPI network. However, to date, these methods have used a static picture of human PPIs, while diseases impact specific tissues in which the PPI networks may be dramatically different. Here, for the first time, we perform a large-scale assessment of the contribution of tissue-specific information to gene prioritization. By integrating tissue-specific gene expression data with PPI information, we construct tissue-specific PPI networks for 60 tissues and investigate their prioritization power. We find that tissue-specific PPI networks considerably improve the prioritization results compared to those obtained using a generic PPI network. Furthermore, they allow predicting novel disease-tissue associations, pointing to sub-clinical tissue effects that may escape early detection.

  15. A quantitative analysis of contractility in active cytoskeletal protein networks.

    Bendix, Poul M; Koenderink, Gijsje H; Cuvelier, Damien; Dogic, Zvonimir; Koeleman, Bernard N; Brieher, William M; Field, Christine M; Mahadevan, L; Weitz, David A

    2008-04-15

    Cells actively produce contractile forces for a variety of processes including cytokinesis and motility. Contractility is known to rely on myosin II motors which convert chemical energy from ATP hydrolysis into forces on actin filaments. However, the basic physical principles of cell contractility remain poorly understood. We reconstitute contractility in a simplified model system of purified F-actin, muscle myosin II motors, and alpha-actinin cross-linkers. We show that contractility occurs above a threshold motor concentration and within a window of cross-linker concentrations. We also quantify the pore size of the bundled networks and find contractility to occur at a critical distance between the bundles. We propose a simple mechanism of contraction based on myosin filaments pulling neighboring bundles together into an aggregated structure. Observations of this reconstituted system in both bulk and low-dimensional geometries show that the contracting gels pull on and deform their surface with a contractile force of approximately 1 microN, or approximately 100 pN per F-actin bundle. Cytoplasmic extracts contracting in identical environments show a similar behavior and dependence on myosin as the reconstituted system. Our results suggest that cellular contractility can be sensitively regulated by tuning the (local) activity of molecular motors and the cross-linker density and binding affinity. PMID:18192374

  16. Salivary Defense Proteins: Their Network and Role in Innate and Acquired Oral Immunity

    Gábor Fábián

    2012-04-01

    Full Text Available There are numerous defense proteins present in the saliva. Although some of these molecules are present in rather low concentrations, their effects are additive and/or synergistic, resulting in an efficient molecular defense network of the oral cavity. Moreover, local concentrations of these proteins near the mucosal surfaces (mucosal transudate, periodontal sulcus (gingival crevicular fluid and oral wounds and ulcers (transudate may be much greater, and in many cases reinforced by immune and/or inflammatory reactions of the oral mucosa. Some defense proteins, like salivary immunoglobulins and salivary chaperokine HSP70/HSPAs (70 kDa heat shock proteins, are involved in both innate and acquired immunity. Cationic peptides and other defense proteins like lysozyme, bactericidal/permeability increasing protein (BPI, BPI-like proteins, PLUNC (palate lung and nasal epithelial clone proteins, salivary amylase, cystatins, prolin-rich proteins, mucins, peroxidases, statherin and others are primarily responsible for innate immunity. In this paper, this complex system and function of the salivary defense proteins will be reviewed.

  17. Elastic network model of allosteric regulation in protein kinase PDK1

    Williams Gareth

    2010-05-01

    Full Text Available Abstract Background Structural switches upon binding of phosphorylated moieties underpin many signalling networks. The ligand activation is a form of allosteric modulation of the protein, where the binding site is remote from the structural change in the protein. Recently this structural switch has been elegantly demonstrated with the crystallisation of the activated form of 3-phosphoinositide-dependent protein kinase-1 (PDK1. The purpose of the present work is to determine whether the allosteric coupling in PDK1 emerges at the level of a simple coarse grained model of protein dynamics. Results It is shown here that the allosteric effects of the agonist binding to the small lobe upon the activation loop in the large lobe of PDK1 are explainable within a simple 'ball and spring' elastic network model (ENM of protein dynamics. In particular, the model shows that the bound phospho peptide mimetic fluctuations have a high degree of correlation with the activation loop of PDK1. Conclusions The ENM approach to small molecule activation of proteins may offer a first pass predictive methodology where affinity is encoded in residues remote from the active site, and aid in the design of specific protein agonists that enhance the allosteric coupling and antagonist that repress it.

  18. Prioritizing cancer-related genes with aberrant methylation based on a weighted protein-protein interaction network

    Lv Jie

    2011-10-01

    Full Text Available Abstract Background As an important epigenetic modification, DNA methylation plays a crucial role in the development of mammals and in the occurrence of complex diseases. Genes that interact directly or indirectly may have the same or similar functions in the biological processes in which they are involved and together contribute to the related disease phenotypes. The complicated relations between genes can be clearly represented using network theory. A protein-protein interaction (PPI network offers a platform from which to systematically identify disease-related genes from the relations between genes with similar functions. Results We constructed a weighted human PPI network (WHPN using DNA methylation correlations based on human protein-protein interactions. WHPN represents the relationships of DNA methylation levels in gene pairs for four cancer types. A cancer-associated subnetwork (CASN was obtained from WHPN by selecting genes associated with seed genes which were known to be methylated in the four cancers. We found that CASN had a more densely connected network community than WHPN, indicating that the genes in CASN were much closer to seed genes. We prioritized 154 potential cancer-related genes with aberrant methylation in CASN by neighborhood-weighting decision rule. A function enrichment analysis for GO and KEGG indicated that the optimized genes were mainly involved in the biological processes of regulating cell apoptosis and programmed cell death. An analysis of expression profiling data revealed that many of the optimized genes were expressed differentially in the four cancers. By examining the PubMed co-citations, we found 43 optimized genes were related with cancers and aberrant methylation, and 10 genes were validated to be methylated aberrantly in cancers. Of 154 optimized genes, 27 were as diagnostic markers and 20 as prognostic markers previously identified in literature for cancers and other complex diseases by searching Pub

  19. Identification of T1D susceptibility genes within the MHC region by combining protein interaction networks and SNP genotyping data

    Brorsson, C.; Hansen, Niclas Tue; Hansen, Kasper Lage;

    2009-01-01

    genes. We have developed a novel method that combines single nucleotide polymorphism (SNP) genotyping data with protein-protein interaction (ppi) networks to identify disease-associated network modules enriched for proteins encoded from the MHC region. Approximately 2500 SNPs located in the 4 Mb MHC...... region were analysed in 1000 affected offspring trios generated by the Type 1 Diabetes Genetics Consortium (T1DGC). The most associated SNP in each gene was chosen and genes were mapped to ppi networks for identification of interaction partners. The association testing and resulting interacting protein...

  20. Protein-protein interaction network construction for cancer using a new L1/2-penalized Net-SVM model.

    Chai, H; Huang, H H; Jiang, H K; Liang, Y; Xia, L Y

    2016-01-01

    Identifying biomarker genes and characterizing interaction pathways with high-dimensional and low-sample size microarray data is a major challenge in computational biology. In this field, the construction of protein-protein interaction (PPI) networks using disease-related selected genes has garnered much attention. Support vector machines (SVMs) are commonly used to classify patients, and a number of useful tools such as lasso, elastic net, SCAD, or other regularization methods can be combined with SVM models to select genes that are related to a disease. In the current study, we propose a new Net-SVM model that is different from other SVM models as it is combined with L1/2-norm regularization, which has good performance with high-dimensional and low-sample size microarray data for cancer classification, gene selection, and PPI network construction. Both simulation studies and real data experiments demonstrated that our proposed method outperformed other regularization methods such as lasso, SCAD, and elastic net. In conclusion, our model may help to select fewer but more relevant genes, and can be used to construct simple and informative PPI networks that are highly relevant to cancer. PMID:27525863

  1. Identification of Lung-Cancer-Related Genes with the Shortest Path Approach in a Protein-Protein Interaction Network

    Bi-Qing Li

    2013-01-01

    Full Text Available Lung cancer is one of the leading causes of cancer mortality worldwide. The main types of lung cancer are small cell lung cancer (SCLC and nonsmall cell lung cancer (NSCLC. In this work, a computational method was proposed for identifying lung-cancer-related genes with a shortest path approach in a protein-protein interaction (PPI network. Based on the PPI data from STRING, a weighted PPI network was constructed. 54 NSCLC- and 84 SCLC-related genes were retrieved from associated KEGG pathways. Then the shortest paths between each pair of these 54 NSCLC genes and 84 SCLC genes were obtained with Dijkstra’s algorithm. Finally, all the genes on the shortest paths were extracted, and 25 and 38 shortest genes with a permutation P value less than 0.05 for NSCLC and SCLC were selected for further analysis. Some of the shortest path genes have been reported to be related to lung cancer. Intriguingly, the candidate genes we identified from the PPI network contained more cancer genes than those identified from the gene expression profiles. Furthermore, these genes possessed more functional similarity with the known cancer genes than those identified from the gene expression profiles. This study proved the efficiency of the proposed method and showed promising results.

  2. POINeT: protein interactome with sub-network analysis and hub prioritization

    Lai Jin-Mei

    2009-04-01

    Full Text Available Abstract Background Protein-protein interactions (PPIs are critical to every aspect of biological processes. Expansion of all PPIs from a set of given queries often results in a complex PPI network lacking spatiotemporal consideration. Moreover, the reliability of available PPI resources, which consist of low- and high-throughput data, for network construction remains a significant challenge. Even though a number of software tools are available to facilitate PPI network analysis, an integrated tool is crucial to alleviate the burden on querying across multiple web servers and software tools. Results We have constructed an integrated web service, POINeT, to simplify the process of PPI searching, analysis, and visualization. POINeT merges PPI and tissue-specific expression data from multiple resources. The tissue-specific PPIs and the numbers of research papers supporting the PPIs can be filtered with user-adjustable threshold values and are dynamically updated in the viewer. The network constructed in POINeT can be readily analyzed with, for example, the built-in centrality calculation module and an integrated network viewer. Nodes in global networks can also be ranked and filtered using various network analysis formulas, i.e., centralities. To prioritize the sub-network, we developed a ranking filtered method (S3 to uncover potential novel mediators in the midbody network. Several examples are provided to illustrate the functionality of POINeT. The network constructed from four schizophrenia risk markers suggests that EXOC4 might be a novel marker for this disease. Finally, a liver-specific PPI network has been filtered with adult and fetal liver expression profiles. Conclusion The functionalities provided by POINeT are highly improved compared to previous version of POINT. POINeT enables the identification and ranking of potential novel genes involved in a sub-network. Combining with tissue-specific gene expression profiles, PPIs specific to

  3. Getting to the Edge: Protein dynamical networks as a new frontier in plant-microbe interactions

    Cassandra C Garbutt

    2014-06-01

    Full Text Available A systems perspective on diverse phenotypes, mechanisms of infection, and responses to environmental stresses can lead to considerable advances in agriculture and medicine. A significant promise of systems biology within plants is the development of disease-resistant crop varieties, which would maximize yield output for food, clothing, building materials and biofuel production. A systems or -omics perspective frames the next frontier in the search for enhanced knowledge of plant network biology. The functional understanding of network structure and dynamics s is vital to expanding our knowledge of how the intercellular communication processes are executed. . This review article will systematically discuss various levels of organization of systems biology beginning with the building blocks termed –omes and ending with complex transcriptional and protein-protein interaction networks. We will also highlight the prevailing computational modeling approaches of biological regulatory network dynamics. The latest developments in the -omics approach will be reviewed and discussed to underline and highlight novel technologies and research directions in plant network biology.

  4. Stepping motor adaptor actuator for a commercial uhv linear motion feedthrough

    An adaptor coupling has been developed that will allow the attachment of a standard stepping motor to a precision commercial (Varian) uhv linear motion feedthrough. The assembly, consisting of the motor, motor adaptor, limit switches, etc. is clamped to the feedthrough body which can be done under vacuum conditions if necessary. With a 500 step/rev. stepping motor the resolution is 1.27 μm per step. We presently use this assembly in a remote location for the precise positioning of a beam sensing monitor. 2 refs., 3 figs

  5. A mathematical model for generating bipartite graphs and its application to protein networks

    Complex systems arise in many different contexts from large communication systems and transportation infrastructures to molecular biology. Most of these systems can be organized into networks composed of nodes and interacting edges. Here, we present a theoretical model that constructs bipartite networks with the particular feature that the degree distribution can be tuned depending on the probability rate of fundamental processes. We then use this model to investigate protein-domain networks. A protein can be composed of up to hundreds of domains. Each domain represents a conserved sequence segment with specific functional tasks. We analyze the distribution of domains in Homo sapiens and Arabidopsis thaliana organisms and the statistical analysis shows that while (a) the number of domain types shared by k proteins exhibits a power-law distribution, (b) the number of proteins composed of k types of domains decays as an exponential distribution. The proposed mathematical model generates bipartite graphs and predicts the emergence of this mixing of (a) power-law and (b) exponential distributions. Our theoretical and computational results show that this model requires (1) growth process and (2) copy mechanism.

  6. Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs

    Casey, Fergal

    2011-08-22

    Abstract Background Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks. Results We examined triplet motifs in a network of quantitative epistatic genetic relationships, and found a non-random distribution of particular motif classes. Individual motif classes were found to be associated with different functional properties, suggestive of an underlying biological significance. These associations were apparent not only for motif classes, but for individual positions within the motifs. As expected, NNN (all negative) motifs were strongly associated with previously reported genetic (i.e. synthetic lethal) interactions, while PPP (all positive) motifs were associated with protein complexes. The two other motif classes (NNP: a positive interaction spanned by two negative interactions, and NPP: a negative spanned by two positives) showed very distinct functional associations, with physical interactions dominating for the former but alternative enrichments, typical of biochemical pathways, dominating for the latter. Conclusion We present a model showing how NNP motifs can be used to recognize supportive relationships between protein complexes, while NPP motifs often identify opposing or regulatory behaviour between a gene and an associated pathway. The ability to use motifs to point toward underlying biological organizational themes is likely to be increasingly important as more extensive epistasis mapping projects in higher organisms begin.

  7. A mathematical model for generating bipartite graphs and its application to protein networks

    Nacher, J C [Department of Complex Systems, Future University-Hakodate (Japan); Ochiai, T [Faculty of Engineering, Toyama Prefectural University (Japan); Hayashida, M; Akutsu, T [Bioinformatics Center, Institute for Chemical Research, Kyoto University (Japan)

    2009-12-04

    Complex systems arise in many different contexts from large communication systems and transportation infrastructures to molecular biology. Most of these systems can be organized into networks composed of nodes and interacting edges. Here, we present a theoretical model that constructs bipartite networks with the particular feature that the degree distribution can be tuned depending on the probability rate of fundamental processes. We then use this model to investigate protein-domain networks. A protein can be composed of up to hundreds of domains. Each domain represents a conserved sequence segment with specific functional tasks. We analyze the distribution of domains in Homo sapiens and Arabidopsis thaliana organisms and the statistical analysis shows that while (a) the number of domain types shared by k proteins exhibits a power-law distribution, (b) the number of proteins composed of k types of domains decays as an exponential distribution. The proposed mathematical model generates bipartite graphs and predicts the emergence of this mixing of (a) power-law and (b) exponential distributions. Our theoretical and computational results show that this model requires (1) growth process and (2) copy mechanism.

  8. STITCH 2: an interaction network database for small molecules and proteins

    Kuhn, Michael; Szklarczyk, Damian; Franceschini, Andrea;

    2010-01-01

    Over the last years, the publicly available knowledge on interactions between small molecules and proteins has been steadily increasing. To create a network of interactions, STITCH aims to integrate the data dispersed over the literature and various databases of biological pathways, drug......-target relationships and binding affinities. In STITCH 2, the number of relevant interactions is increased by incorporation of BindingDB, PharmGKB and the Comparative Toxicogenomics Database. The resulting network can be explored interactively or used as the basis for large-scale analyses. To facilitate links to other...

  9. Prediction of protein-protein interaction network using a multi-objective optimization approach.

    Chowdhury, Archana; Rakshit, Pratyusha; Konar, Amit

    2016-06-01

    Protein-Protein Interactions (PPIs) are very important as they coordinate almost all cellular processes. This paper attempts to formulate PPI prediction problem in a multi-objective optimization framework. The scoring functions for the trial solution deal with simultaneous maximization of functional similarity, strength of the domain interaction profiles, and the number of common neighbors of the proteins predicted to be interacting. The above optimization problem is solved using the proposed Firefly Algorithm with Nondominated Sorting. Experiments undertaken reveal that the proposed PPI prediction technique outperforms existing methods, including gene ontology-based Relative Specific Similarity, multi-domain-based Domain Cohesion Coupling method, domain-based Random Decision Forest method, Bagging with REP Tree, and evolutionary/swarm algorithm-based approaches, with respect to sensitivity, specificity, and F1 score. PMID:26846814

  10. Genetic Deletion of the Clathrin Adaptor GGA3 Reduces Anxiety and Alters GABAergic Transmission

    Albrecht, David; Lomoio, Selene; Haydon, Philip G.; Moss, Stephen J.; Tesco, Giuseppina

    2016-01-01

    Golgi-localized γ-ear-containing ARF binding protein 3 (GGA3) is a monomeric clathrin adaptor that has been shown to regulate the trafficking of the Beta-site APP-cleaving enzyme (BACE1), which is required for production of the Alzheimer’s disease (AD)-associated amyloid βpeptide. Our previous studies have shown that BACE1 is degraded via the lysosomal pathway and that depletion of GGA3 results in increased BACE1 levels and activity owing to impaired lysosomal trafficking and degradation. We further demonstrated the role of GGA3 in the regulation of BACE1 in vivo by showing that BACE1 levels are increased in the brain of GGA3 null mice. We report here that GGA3 deletion results in novelty-induced hyperactivity and decreased anxiety-like behaviors. Given the pivotal role of GABAergic transmission in the regulation of anxiety-like behaviors, we performed electrophysiological recordings in hippocampal slices and found increased phasic and decreased tonic inhibition in the dentate gyrus granule cells (DGGC). Moreover, we found that the number of inhibitory synapses is increased in the dentate gyrus of GGA3 null mice in further support of the electrophysiological data. Thus, the increased GABAergic transmission is a leading candidate mechanism underlying the reduced anxiety-like behaviors observed in GGA3 null mice. All together these findings suggest that GGA3 plays a key role in GABAergic transmission. Since BACE1 levels are elevated in the brain of GGA3 null mice, it is possible that at least some of these phenotypes are a consequence of increased processing of BACE1 substrates. PMID:27192432

  11. Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks

    Kirouac Daniel C

    2012-05-01

    Full Text Available Abstract Background Understanding the information-processing capabilities of signal transduction networks, how those networks are disrupted in disease, and rationally designing therapies to manipulate diseased states require systematic and accurate reconstruction of network topology. Data on networks central to human physiology, such as the inflammatory signalling networks analyzed here, are found in a multiplicity of on-line resources of pathway and interactome databases (Cancer CellMap, GeneGo, KEGG, NCI-Pathway Interactome Database (NCI-PID, PANTHER, Reactome, I2D, and STRING. We sought to determine whether these databases contain overlapping information and whether they can be used to construct high reliability prior knowledge networks for subsequent modeling of experimental data. Results We have assembled an ensemble network from multiple on-line sources representing a significant portion of all machine-readable and reconcilable human knowledge on proteins and protein interactions involved in inflammation. This ensemble network has many features expected of complex signalling networks assembled from high-throughput data: a power law distribution of both node degree and edge annotations, and topological features of a “bow tie” architecture in which diverse pathways converge on a highly conserved set of enzymatic cascades focused around PI3K/AKT, MAPK/ERK, JAK/STAT, NFκB, and apoptotic signaling. Individual pathways exhibit “fuzzy” modularity that is statistically significant but still involving a majority of “cross-talk” interactions. However, we find that the most widely used pathway databases are highly inconsistent with respect to the actual constituents and interactions in this network. Using a set of growth factor signalling networks as examples (epidermal growth factor, transforming growth factor-beta, tumor necrosis factor, and wingless, we find a multiplicity of network topologies in which receptors couple to downstream

  12. The network of P(II) signalling protein interactions in unicellular cyanobacteria.

    Forchhammer, Karl

    2010-01-01

    P(II) signalling proteins constitute a large superfamily of signal perception and transduction proteins, which is represented in all domains of life and whose members play central roles in coordinating nitrogen assimilation. Generally, P(II) proteins act as sensors of the cellular adenylylate energy charge and 2-oxoglutarate level, and in response to these signals, they regulate central nitrogen assimilatory processes at various levels of control (from nutrient transport to gene expression) through protein-protein interactions with P(II) receptor proteins. An examination of the phylogeny of cyanobacteria reveals that specific functions of P(II) signalling evolved in this microbial lineage, which are not found in other prokaryotes. At least one of these functions, regulation of arginine biosynthesis by controlling the key enzyme N-acetyl-L: -glutamate kinase (NAGK), was transmitted by the ancestral cyanobacterium, which gave rise to chloroplasts, into the eukaryotic domain and was conserved during the evolution of planta. We have investigated in some detail the P(II) signalling protein, its signal perception and its interactions with receptors in the unicellular cyanobacteria Synechococcus elongatus PCC 7942 and Synechocystis PCC 6803 and have performed comparative analysis with Arabidopsis thaliana P(II)-NAGK interaction. This chapter will summarize these studies and will describe the emerging picture of a complex network of P(II) protein interactions in the unicellular cyanobacteria. PMID:20532736

  13. A human phenome-interactome network of protein complexes implicated in genetic disorders

    Hansen, Kasper Lage; Karlberg, Erik, Olof, Linnart; Størling, Zenia, Marian;

    2007-01-01

    We performed a systematic, large-scale analysis of human protein complexes comprising gene products implicated in many different categories of human disease to create a phenome-interactome network. This was done by integrating quality-controlled interactions of human proteins with a validated......, computationally derived phenotype similarity score, permitting identification of previously unknown complexes likely to be associated with disease. Using a phenomic ranking of protein complexes linked to human disease, we developed a Bayesian predictor that in 298 of 669 linkage intervals correctly ranks the...... known disease-causing protein as the top candidate, and in 870 intervals with no identified disease-causing gene, provides novel candidates implicated in disorders such as retinitis pigmentosa, epithelial ovarian cancer, inflammatory bowel disease, amyotrophic lateral sclerosis, Alzheimer disease, type...

  14. Artificial neural networks trained to detect viral and phage structural proteins.

    Seguritan, Victor; Alves, Nelson; Arnoult, Michael; Raymond, Amy; Lorimer, Don; Burgin, Alex B; Salamon, Peter; Segall, Anca M

    2012-01-01

    Phages play critical roles in the survival and pathogenicity of their hosts, via lysogenic conversion factors, and in nutrient redistribution, via cell lysis. Analyses of phage- and viral-encoded genes in environmental samples provide insights into the physiological impact of viruses on microbial communities and human health. However, phage ORFs are extremely diverse of which over 70% of them are dissimilar to any genes with annotated functions in GenBank. Better identification of viruses would also aid in better detection and diagnosis of disease, in vaccine development, and generally in better understanding the physiological potential of any environment. In contrast to enzymes, viral structural protein function can be much more challenging to detect from sequence data because of low sequence conservation, few known conserved catalytic sites or sequence domains, and relatively limited experimental data. We have designed a method of predicting phage structural protein sequences that uses Artificial Neural Networks (ANNs). First, we trained ANNs to classify viral structural proteins using amino acid frequency; these correctly classify a large fraction of test cases with a high degree of specificity and sensitivity. Subsequently, we added estimates of protein isoelectric points as a feature to ANNs that classify specialized families of proteins, namely major capsid and tail proteins. As expected, these more specialized ANNs are more accurate than the structural ANNs. To experimentally validate the ANN predictions, several ORFs with no significant similarities to known sequences that are ANN-predicted structural proteins were examined by transmission electron microscopy. Some of these self-assembled into structures strongly resembling virion structures. Thus, our ANNs are new tools for identifying phage and potential prophage structural proteins that are difficult or impossible to detect by other bioinformatic analysis. The networks will be valuable when sequence is

  15. The cost and capacity of signaling in the Escherichia coli protein reaction network

    In systems biology new ways are required to analyze the large amount of existing data on regulation of cellular processes. Recent work can be roughly classified into either dynamical models of well-described subsystems, or coarse-grained descriptions of the topology of the molecular networks at the scale of the whole organism. In order to bridge these two disparate approaches one needs to develop simplified descriptions of dynamics and topological measures which address the propagation of signals in molecular networks. Transmission of a signal across a reaction node depends on the presence of other reactants. It will typically be more demanding to transmit a signal across a reaction node with more input links. Sending signals along a path with several subsequent reaction nodes also increases the constraints on the presence of other proteins in the overall network. Therefore counting in and out links along reactions of a potential pathway can give insight into the signaling properties of a particular molecular network. Here, we consider the directed network of protein regulation in E. coli, characterizing its modularity in terms of its potential to transmit signals. We demonstrate that the simplest measure based on identifying subnetworks of strong components, within which each node could send a signal to every other node, does indeed partition the network into functional modules. We suggest that the total number of reactants needed to send a signal between two nodes in the network can be considered as the cost associated with transmitting this signal. Similarly we define spread as the number of reaction products that could be influenced by transmission of a successful signal. Our considerations open for a new class of network measures that implicitly utilize the constrained repertoire of chemical modifications of any biological molecule. The counting of cost and spread connects the topology of networks to the specificity of signaling across the network. Thereby, we

  16. A network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases.

    Scott-Boyer, Marie Pier; Lacroix, Sébastien; Scotti, Marco; Morine, Melissa J; Kaput, Jim; Priami, Corrado

    2016-01-01

    The involvement of vitamins and other micronutrients in intermediary metabolism was elucidated in the mid 1900's at the level of individual biochemical reactions. Biochemical pathways remain the foundational knowledgebase for understanding how micronutrient adequacy modulates health in all life stages. Current daily recommended intakes were usually established on the basis of the association of a single nutrient to a single, most sensitive adverse effect and thus neglect interdependent and pleiotropic effects of micronutrients on biological systems. Hence, the understanding of the impact of overt or sub-clinical nutrient deficiencies on biological processes remains incomplete. Developing a more complete view of the role of micronutrients and their metabolic products in protein-mediated reactions is of importance. We thus integrated and represented cofactor-protein interaction data from multiple and diverse sources into a multi-layer network representation that links cofactors, cofactor-interacting proteins, biological processes, and diseases. Network representation of this information is a key feature of the present analysis and enables the integration of data from individual biochemical reactions and protein-protein interactions into a systems view, which may guide strategies for targeted nutritional interventions aimed at improving health and preventing diseases. PMID:26777674

  17. Water and molecular chaperones act as weak links of protein folding networks: energy landscape and punctuated equilibrium changes point towards a game theory of proteins.

    Kovács, István A; Szalay, Máté S; Csermely, Peter

    2005-04-25

    Water molecules and molecular chaperones efficiently help the protein folding process. Here we describe their action in the context of the energy and topological networks of proteins. In energy terms water and chaperones were suggested to decrease the activation energy between various local energy minima smoothing the energy landscape, rescuing misfolded proteins from conformational traps and stabilizing their native structure. In kinetic terms water and chaperones may make the punctuated equilibrium of conformational changes less punctuated and help protein relaxation. Finally, water and chaperones may help the convergence of multiple energy landscapes during protein-macromolecule interactions. We also discuss the possibility of the introduction of protein games to narrow the multitude of the energy landscapes when a protein binds to another macromolecule. Both water and chaperones provide a diffuse set of rapidly fluctuating weak links (low affinity and low probability interactions), which allow the generalization of all these statements to a multitude of networks. PMID:15848154

  18. Expression Profiling of Human Genetic and Protein Interaction Networks in Type 1 Diabetes

    Brunak, Søren; Bergholdt, R; Brorsson, C;

    2009-01-01

    : oxidative stress, regulation of transcription and apoptosis. To understand biological systems, integration of genetic and functional information is necessary, and the current study has used this approach to improve understanding of T1D and the underlying biological mechanisms.......Proteins contributing to a complex disease are often members of the same functional pathways. Elucidation of such pathways may provide increased knowledge about functional mechanisms underlying disease. By combining genetic interactions in Type 1 Diabetes (T1D) with protein interaction data we have...... previously identified sets of genes, likely to represent distinct cellular pathways involved in T1D risk. Here we evaluate the candidate genes involved in these putative interaction networks not only at the single gene level, but also in the context of the networks of which they form an integral part. m...

  19. Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks

    A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, ≥90 % fraction of the residues, with an error rate smaller than ca 3.5 %, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed (φ, ψ) torsion angles of ca 12º. TALOS-N also reports sidechain χ1 rotameric states for about 50 % of the residues, and a consistency with reference structures of 89 %. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts

  20. Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks

    Shen Yang; Bax, Ad, E-mail: bax@nih.gov [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States)

    2013-07-15

    A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, {>=}90 % fraction of the residues, with an error rate smaller than ca 3.5 %, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed ({phi}, {psi}) torsion angles of ca 12 Masculine-Ordinal-Indicator . TALOS-N also reports sidechain {chi}{sup 1} rotameric states for about 50 % of the residues, and a consistency with reference structures of 89 %. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts.

  1. Analytical reduction of combinatorial complexity arising from multiple protein modification sites.

    Birtwistle, Marc R

    2015-02-01

    Combinatorial complexity is a major obstacle to ordinary differential equation (ODE) modelling of biochemical networks. For example, a protein with 10 sites that can each be unphosphorylated, phosphorylated or bound to adaptor protein requires 3(10) ODEs. This problem is often dealt with by making ad hoc assumptions which have unclear validity and disallow modelling of site-specific dynamics. Such site-specific dynamics, however, are important in many biological systems. We show here that for a common biological situation where adaptors bind modified sites, binding is slow relative to modification/demodification, and binding to one modified site hinders binding to other sites, for a protein with n modification sites and m adaptor proteins the number of ODEs needed to simulate the site-specific dynamics of biologically relevant, lumped bound adaptor states is independent of the number of modification sites and equal to m + 1, giving a significant reduction in system size. These considerations can be relaxed considerably while retaining reasonably accurate descriptions of the true system dynamics. We apply the theory to model, using only 11 ODEs, the dynamics of ligand-induced phosphorylation of nine tyrosines on epidermal growth factor receptor (EGFR) and primary recruitment of six signalling proteins (Grb2, PI3K, PLCγ1, SHP2, RasA1 and Shc1). The model quantitatively accounts for experimentally determined site-specific phosphorylation and dephosphorylation rates, differential affinities of binding proteins for the phosphorylated sites and binding protein expression levels. Analysis suggests that local concentration of site-specific phosphatases such as SHP2 in membrane subdomains by a factor of approximately 10(7) is critical for effective site-specific regulation. We further show how our framework can be extended with minimal effort to consider binding cooperativity between Grb2 and c-Cbl, which is important for receptor trafficking. Our theory has potentially

  2. Identifying Novel Candidate Genes Related to Apoptosis from a Protein-Protein Interaction Network

    Baoman Wang

    2015-01-01

    Full Text Available Apoptosis is the process of programmed cell death (PCD that occurs in multicellular organisms. This process of normal cell death is required to maintain the balance of homeostasis. In addition, some diseases, such as obesity, cancer, and neurodegenerative diseases, can be cured through apoptosis, which produces few side effects. An effective comprehension of the mechanisms underlying apoptosis will be helpful to prevent and treat some diseases. The identification of genes related to apoptosis is essential to uncover its underlying mechanisms. In this study, a computational method was proposed to identify novel candidate genes related to apoptosis. First, protein-protein interaction information was used to construct a weighted graph. Second, a shortest path algorithm was applied to the graph to search for new candidate genes. Finally, the obtained genes were filtered by a permutation test. As a result, 26 genes were obtained, and we discuss their likelihood of being novel apoptosis-related genes by collecting evidence from published literature.

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

    Rajagopala, Seesandra Venkatappa

    2015-01-01

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

  4. Predicting the effect of missense mutations on protein function: analysis with Bayesian networks

    Care Matthew A

    2006-09-01

    Full Text Available Abstract Background A number of methods that use both protein structural and evolutionary information are available to predict the functional consequences of missense mutations. However, many of these methods break down if either one of the two types of data are missing. Furthermore, there is a lack of rigorous assessment of how important the different factors are to prediction. Results Here we use Bayesian networks to predict whether or not a missense mutation will affect the function of the protein. Bayesian networks provide a concise representation for inferring models from data, and are known to generalise well to new data. More importantly, they can handle the noisy, incomplete and uncertain nature of biological data. Our Bayesian network achieved comparable performance with previous machine learning methods. The predictive performance of learned model structures was no better than a naïve Bayes classifier. However, analysis of the posterior distribution of model structures allows biologically meaningful interpretation of relationships between the input variables. Conclusion The ability of the Bayesian network to make predictions when only structural or evolutionary data was observed allowed us to conclude that structural information is a significantly better predictor of the functional consequences of a missense mutation than evolutionary information, for the dataset used. Analysis of the posterior distribution of model structures revealed that the top three strongest connections with the class node all involved structural nodes. With this in mind, we derived a simplified Bayesian network that used just these three structural descriptors, with comparable performance to that of an all node network.

  5. A network model to correlate conformational change and the impedance spectrum of single proteins

    Alfinito, Eleonora; Pennetta, Cecilia; Reggiani, Lino

    2008-02-01

    Integrated nanodevices based on proteins or biomolecules are attracting increasing interest in today's research. In fact, it has been shown that proteins such as azurin and bacteriorhodopsin manifest some electrical properties that are promising for the development of active components of molecular electronic devices. Here we focus on two relevant kinds of protein: bovine rhodopsin, prototype of G-protein-coupled-receptor (GPCR) proteins, and the enzyme acetylcholinesterase (AChE), whose inhibition is one of the most qualified treatments of Alzheimer's disease. Both these proteins exert their function starting with a conformational change of their native structure. Our guess is that such a change should be accompanied with a detectable variation of their electrical properties. To investigate this conjecture, we present an impedance network model of proteins, able to estimate the different impedance spectra associated with the different configurations. The distinct types of conformational change of rhodopsin and AChE agree with their dissimilar electrical responses. In particular, for rhodopsin the model predicts variations of the impedance spectra up to about 30%, while for AChE the same variations are limited to about 10%, which supports the existence of a dynamical equilibrium between its native and complexed states.

  6. A network model to correlate conformational change and the impedance spectrum of single proteins

    Alfinito, Eleonora; Pennetta, Cecilia; Reggiani, Lino [Dipartimento di Ingegneria dell' Innovazione, Universita del Salento, Via Arnesano, Lecce (Italy); Consorzio Nazionale Interuniversitario per le Scienze Fisiche della Materia (CNISM) (Italy)

    2008-02-13

    Integrated nanodevices based on proteins or biomolecules are attracting increasing interest in today's research. In fact, it has been shown that proteins such as azurin and bacteriorhodopsin manifest some electrical properties that are promising for the development of active components of molecular electronic devices. Here we focus on two relevant kinds of protein: bovine rhodopsin, prototype of G-protein-coupled-receptor (GPCR) proteins, and the enzyme acetylcholinesterase (AChE), whose inhibition is one of the most qualified treatments of Alzheimer's disease. Both these proteins exert their function starting with a conformational change of their native structure. Our guess is that such a change should be accompanied with a detectable variation of their electrical properties. To investigate this conjecture, we present an impedance network model of proteins, able to estimate the different impedance spectra associated with the different configurations. The distinct types of conformational change of rhodopsin and AChE agree with their dissimilar electrical responses. In particular, for rhodopsin the model predicts variations of the impedance spectra up to about 30%, while for AChE the same variations are limited to about 10%, which supports the existence of a dynamical equilibrium between its native and complexed states.

  7. Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features.

    Aguilar, Daniel; Oliva, Baldo; Marino Buslje, Cristina

    2012-01-01

    Amino acids committed to a particular function correlate tightly along evolution and tend to form clusters in the 3D structure of the protein. Consequently, a protein can be seen as a network of co-evolving clusters of residues. The goal of this work is two-fold: first, we have combined mutual information and structural data to describe the amino acid networks within a protein and their interactions. Second, we have investigated how this information can be used to improve methods of prediction of functional residues by reducing the search space. As a main result, we found that clusters of co-evolving residues related to the catalytic site of an enzyme have distinguishable topological properties in the network. We also observed that these clusters usually evolve independently, which could be related to a fail-safe mechanism. Finally, we discovered a significant enrichment of functional residues (e.g. metal binding, susceptibility to detrimental mutations) in the clusters, which could be the foundation of new prediction tools. PMID:22848494

  8. Transmembrane adaptor molecules: a new category of lymphoid-cell markers

    Tedoldi, S.; Paterson, J.C.; Hansmann, M.-L.; Natkunam, Y.; Rüdiger, T.; Angelisová, Pavla; Du, M.Q.; Roberton, H.; Roncador, G.; Sanchez, L.; Pozzobon, M.; Masir, N.; Barry, R.; Pileri, S.; Mason, D.Y.; Marafioti, T.; Hořejší, Václav

    2006-01-01

    Roč. 107, č. 1 (2006), s. 213-221. ISSN 0006-4971 R&D Projects: GA MŠk(CZ) 1M0506 Institutional research plan: CEZ:AV0Z50520514 Keywords : transmembrane adaptors * PAG * LIME Subject RIV: EC - Immunology Impact factor: 10.370, year: 2006

  9. Linear motif-mediated interactions have contributed to the evolution of modularity in complex protein interaction networks.

    Inhae Kim

    2014-10-01

    Full Text Available The modular architecture of protein-protein interaction (PPI networks is evident in diverse species with a wide range of complexity. However, the molecular components that lead to the evolution of modularity in PPI networks have not been clearly identified. Here, we show that weak domain-linear motif interactions (DLIs are more likely to connect different biological modules than strong domain-domain interactions (DDIs. This molecular division of labor is essential for the evolution of modularity in the complex PPI networks of diverse eukaryotic species. In particular, DLIs may compensate for the reduction in module boundaries that originate from increased connections between different modules in complex PPI networks. In addition, we show that the identification of biological modules can be greatly improved by including molecular characteristics of protein interactions. Our findings suggest that transient interactions have played a unique role in shaping the architecture and modularity of biological networks over the course of evolution.

  10. Note: Network random walk model of two-state protein folding: Test of the theory

    Berezhkovskii, Alexander M.; Murphy, Ronan D.; Buchete, Nicolae-Viorel

    2013-01-01

    We study two-state protein folding in the framework of a toy model of protein dynamics. This model has an important advantage: it allows for an analytical solution for the sum of folding and unfolding rate constants [A. M. Berezhkovskii, F. Tofoleanu, and N.-V. Buchete, J. Chem. Theory Comput. 7, 2370 (2011), 10.1021/ct200281d] and hence for the reactive flux at equilibrium. We use the model to test the Kramers-type formula for the reactive flux, which was derived assuming that the protein dynamics is described by a Markov random walk on a network of complex connectivity [A. Berezhkovskii, G. Hummer, and A. Szabo, J. Chem. Phys. 130, 205102 (2009), 10.1063/1.3139063]. It is shown that the Kramers-type formula leads to the same result for the reactive flux as the sum of the rate constants.

  11. Uncovering the protein lysine and arginine methylation network in Arabidopsis chloroplasts.

    Alban, Claude; Tardif, Marianne; Mininno, Morgane; Brugière, Sabine; Gilgen, Annabelle; Ma, Sheng; Mazzoleni, Meryl; Gigarel, Océane; Martin-Laffon, Jacqueline; Ferro, Myriam; Ravanel, Stéphane

    2014-01-01

    Post-translational modification of proteins by the addition of methyl groups to the side chains of Lys and Arg residues is proposed to play important roles in many cellular processes. In plants, identification of non-histone methylproteins at a cellular or subcellular scale is still missing. To gain insights into the extent of this modification in chloroplasts we used a bioinformatics approach to identify protein methyltransferases targeted to plastids and set up a workflow to specifically identify Lys and Arg methylated proteins from proteomic data used to produce the Arabidopsis chloroplast proteome. With this approach we could identify 31 high-confidence Lys and Arg methylation sites from 23 chloroplastic proteins, of which only two were previously known to be methylated. These methylproteins are split between the stroma, thylakoids and envelope sub-compartments. They belong to essential metabolic processes, including photosynthesis, and to the chloroplast biogenesis and maintenance machinery (translation, protein import, division). Also, the in silico identification of nine protein methyltransferases that are known or predicted to be targeted to plastids provided a foundation to build the enzymes/substrates relationships that govern methylation in chloroplasts. Thereby, using in vitro methylation assays with chloroplast stroma as a source of methyltransferases we confirmed the methylation sites of two targets, plastid ribosomal protein L11 and the β-subunit of ATP synthase. Furthermore, a biochemical screening of recombinant chloroplastic protein Lys methyltransferases allowed us to identify the enzymes involved in the modification of these substrates. The present study provides a useful resource to build the methyltransferases/methylproteins network and to elucidate the role of protein methylation in chloroplast biology. PMID:24748391

  12. Identifying Functional Mechanisms of Gene and Protein Regulatory Networks in Response to a Broader Range of Environmental Stresses

    Cheng-Wei Li

    2010-01-01

    Full Text Available Cellular responses to sudden environmental stresses or physiological changes provide living organisms with the opportunity for final survival and further development. Therefore, it is an important topic to understand protective mechanisms against environmental stresses from the viewpoint of gene and protein networks. We propose two coupled nonlinear stochastic dynamic models to reconstruct stress-activated gene and protein regulatory networks via microarray data in response to environmental stresses. According to the reconstructed gene/protein networks, some possible mutual interactions, feedforward and feedback loops are found for accelerating response and filtering noises in these signaling pathways. A bow-tie core network is also identified to coordinate mutual interactions and feedforward loops, feedback inhibitions, feedback activations, and cross talks to cope efficiently with a broader range of environmental stresses with limited proteins and pathways.

  13. Mining quasi-bicliques from HIV-1-human protein interaction network: a multiobjective biclustering approach.

    Maulik, Ujjwal; Mukhopadhyay, Anirban; Bhattacharyya, Malay; Kaderali, Lars; Brors, Benedikt; Bandyopadhyay, Sanghamitra; Eils, Roland

    2013-01-01

    In this work, we model the problem of mining quasi-bicliques from weighted viral-host protein-protein interaction network as a biclustering problem for identifying strong interaction modules. In this regard, a multiobjective genetic algorithm-based biclustering technique is proposed that simultaneously optimizes three objective functions to obtain dense biclusters having high mean interaction strengths. The performance of the proposed technique has been compared with that of other existing biclustering methods on an artificial data. Subsequently, the proposed biclustering method is applied on the records of biologically validated and predicted interactions between a set of HIV-1 proteins and a set of human proteins to identify strong interaction modules. For this, the entire interaction information is realized as a bipartite graph. We have further investigated the biological significance of the obtained biclusters. The human proteins involved in the strong interaction module have been found to share common biological properties and they are identified as the gateways of viral infection leading to various diseases. These human proteins can be potential drug targets for developing anti-HIV drugs. PMID:23929866

  14. Mining Quasi-Bicliques from HIV-1--Human Protein Interaction Network: A Multiobjective Biclustering Approach.

    Maulik, Ujjwal; Mukhopadhyay, Anirban; Bhattacharyya, Malay; Kaderali, Lars; Brors, Benedikt; Bandyopadhyay, Sanghamitra; Eils, Roland

    2012-11-28

    In this work, we model the problem of mining quasi-bicliques from weighted viral-host protein-protein interaction network as a biclustering problem for identifying strong interaction modules. In this regard, a multiobjective genetic algorithm based biclustering technique is proposed that simultaneously optimizes three objective functions to obtain dense biclusters having high mean interaction strengths. The performance of the proposed technique has been compared with that of other existing biclustering methods on an artificial data. Subsequently, the proposed biclustering method is applied on the records of biologically validated and predicted interactions between a set of HIV-1 proteins and a set of human proteins to identify strong interaction modules. For this, the entire interaction information is realized as a bipartite graph. We have further investigated the biological significance of the obtained biclusters. The human proteins involved in the strong interaction module have been found to share common biological properties and they are identified as the gateways of viral infection leading to various diseases. These human proteins can be potential drug targets for developing anti-HIV drugs. PMID:23209057

  15. Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise

    Correia, Catarina; Oliveira, Guiomar; Vicente, Astrid M.

    2014-01-01

    Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical “noise” that warrant further analysis for causal variants. PMID:25409314

  16. Water and molecular chaperones act as weak links of protein folding networks: energy landscape and punctuated equilibrium changes point towards a game theory of proteins

    Kovacs, Istvan A.; Szalay, Mate S.; Csermely, Peter

    2004-01-01

    Water molecules and molecular chaperones efficiently help the protein folding process. Here we describe their action in the context of the energy and topological networks of proteins. In energy terms water and chaperones were suggested to decrease the activation energy between various local energy minima smoothing the energy landscape, rescuing misfolded proteins from conformational traps and stabilizing their native structure. In kinetic terms water and chaperones may make the punctuated equ...

  17. Using likelihood-free inference to compare evolutionary dynamics of the protein networks of H. pylori and P. falciparum.

    Oliver Ratmann

    2007-11-01

    Full Text Available Gene duplication with subsequent interaction divergence is one of the primary driving forces in the evolution of genetic systems. Yet little is known about the precise mechanisms and the role of duplication divergence in the evolution of protein networks from the prokaryote and eukaryote domains. We developed a novel, model-based approach for Bayesian inference on biological network data that centres on approximate Bayesian computation, or likelihood-free inference. Instead of computing the intractable likelihood of the protein network topology, our method summarizes key features of the network and, based on these, uses a MCMC algorithm to approximate the posterior distribution of the model parameters. This allowed us to reliably fit a flexible mixture model that captures hallmarks of evolution by gene duplication and subfunctionalization to protein interaction network data of Helicobacter pylori and Plasmodium falciparum. The 80% credible intervals for the duplication-divergence component are [0.64, 0.98] for H. pylori and [0.87, 0.99] for P. falciparum. The remaining parameter estimates are not inconsistent with sequence data. An extensive sensitivity analysis showed that incompleteness of PIN data does not largely affect the analysis of models of protein network evolution, and that the degree sequence alone barely captures the evolutionary footprints of protein networks relative to other statistics. Our likelihood-free inference approach enables a fully Bayesian analysis of a complex and highly stochastic system that is otherwise intractable at present. Modelling the evolutionary history of PIN data, it transpires that only the simultaneous analysis of several global aspects of protein networks enables credible and consistent inference to be made from available datasets. Our results indicate that gene duplication has played a larger part in the network evolution of the eukaryote than in the prokaryote, and suggests that single gene

  18. Neural Network Based on GA-BP Algorithm and its Application in the Protein Secondary Structure Prediction

    YANG Yang; LI Kai-yang

    2006-01-01

    The advantages and disadvantages of genetic algorithm and BP algorithm are introduced. A neural network based on GA-BP algorithm is proposed and applied in the prediction of protein secondary structure, which combines the advantages of BP and GA. The prediction and training on the neural network are made respectively based on 4 structure classifications of protein so as to get higher rate of predication-the highest prediction rate 75.65%, the average prediction rate 65.04%.

  19. A fast iterative-clique percolation method for identifying functional modules in protein interaction networks

    Penggang SUN; Lin GAO

    2009-01-01

    Accumulating evidence suggests that biological systems are composed of interacting, separable, functional modules-groups of vertices within which connections are dense but between which they are sparse. Identifying these modules is likely through capturing the biologically mean-ingful interactions. In recent years, many algorithms have been developed for detecting such structures. These al-gorithms, however, are computationally demanding, which limits their applications. In this paper, we propose a fast iterative-clique percolation method (ICPM) for identifying overlapping functional modules in protein-protein interac-tion (PPI) networks. Our method is based on clique percola-tion method (CPM), and it not only considers the degree of nodes to minimize the search space (the vertices in k-cliques must have the degree of k - 1 at least), but also converts k-cliques to (k - 1)-cliques. It finds k-cliques by append-ing one node to (k - 1)-cliques. By testing our method on PPI networks, our analysis of the yeast PPI network suggeststhat most of these modules have well-supported biological significance.

  20. Comparison of two different stochastic models for extracting protein regulatory pathways using Bayesian networks.

    Grzegorczyk, Marco

    2008-01-01

    Toxicoproteomics integrates traditional toxicology and systems biology and seeks to infer the architecture of biochemical pathways in biological systems that are affected by and respond to chemical and environmental exposures. Different reverse engineering methods for extracting biochemical regulatory networks from data have been proposed and it is important to understand their relative strengths and weaknesses. To shed some light onto this problem, Werhli et al. (2006) cross-compared three widely used methodologies, relevance networks, graphical Gaussian models, and Bayesian networks (BN), on real cytometric and synthetic expression data. This study continues with the evaluation and compares the learning performances of two different stochastic models (BGe and BDe) for BN. Cytometric protein expression data from the RAF-signaling pathway were used for the cross-method comparison. Understanding this pathway is an important task, as it is known that RAF is a critical signaling protein whose deregulation leads to carcinogenesis. When the more flexible BDe model is employed, a data discretization, which usually incurs an inevitable information loss, is needed. However, the results of the study reveal that the BDe model is preferable to the BGe model when a sufficiently large number of observations from the pathway are available. PMID:18569581

  1. Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins.

    Rozenblatt-Rosen, Orit; Deo, Rahul C; Padi, Megha; Adelmant, Guillaume; Calderwood, Michael A; Rolland, Thomas; Grace, Miranda; Dricot, Amélie; Askenazi, Manor; Tavares, Maria; Pevzner, Samuel J; Abderazzaq, Fieda; Byrdsong, Danielle; Carvunis, Anne-Ruxandra; Chen, Alyce A; Cheng, Jingwei; Correll, Mick; Duarte, Melissa; Fan, Changyu; Feltkamp, Mariet C; Ficarro, Scott B; Franchi, Rachel; Garg, Brijesh K; Gulbahce, Natali; Hao, Tong; Holthaus, Amy M; James, Robert; Korkhin, Anna; Litovchick, Larisa; Mar, Jessica C; Pak, Theodore R; Rabello, Sabrina; Rubio, Renee; Shen, Yun; Singh, Saurav; Spangle, Jennifer M; Tasan, Murat; Wanamaker, Shelly; Webber, James T; Roecklein-Canfield, Jennifer; Johannsen, Eric; Barabási, Albert-László; Beroukhim, Rameen; Kieff, Elliott; Cusick, Michael E; Hill, David E; Münger, Karl; Marto, Jarrod A; Quackenbush, John; Roth, Frederick P; DeCaprio, James A; Vidal, Marc

    2012-07-26

    Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer. PMID:22810586

  2. A quantitative approach to analyzing genome reductive evolution using protein-protein interaction networks: A case study ofMycobacterium leprae

    Richard O Akinola

    2016-03-01

    Full Text Available The advance in high-throughput sequencing technologies has yielded complete genome sequences of several organisms, including complete bacterial genomes. The growing number of these available sequenced genomes has enabled analyses of their dynamics, as well as the molecular and evolutionary processes which these organisms are under. Comparative genomics of different bacterial genomes have highlighted their genome size and gene content in association with lifestyles and adaptation to various environments and have contributed to enhancing our understanding of the mechanisms of their evolution. Protein-protein functional interactions mediate many essential processes for maintaining the stability of the biological systems under changing environmental conditions. Thus, these interactions play crucial roles in the evolutionary processes of different organisms, especially for obligate intracellular bacteria, proven to generally have reduced genome sizes compared to their nearest free-living relatives. In this study, we used the approach based on the Renormalization Group (RG analysis technique and the Maximum-Excluded-Mass-Burning (MEMB model to investigate the evolutionary process of genome reduction in relation to the organization of functional networks of two organisms. Using a Mycobacterium leprae (MLP network in comparison with a Mycobacterium tuberculosis (MTB network as a case study, we show that reductive evolution in MLP was as a result of removal of important proteins from neighbours of corresponding orthologous MTB proteins. While each orthologous MTB protein had an increase in number of interacting partners in most instances, the corresponding MLP protein had lost some of them. This work provides a quantitative model for mapping reductive evolution and protein-protein functional interaction network organization in terms of roles played by different proteins in the network structure.

  3. SynGAP regulates protein synthesis and homeostatic synaptic plasticity in developing cortical networks.

    Chih-Chieh Wang

    Full Text Available Disrupting the balance between excitatory and inhibitory neurotransmission in the developing brain has been causally linked with intellectual disability (ID and autism spectrum disorders (ASD. Excitatory synapse strength is regulated in the central nervous system by controlling the number of postsynaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs. De novo genetic mutations of the synaptic GTPase-activating protein (SynGAP are associated with ID and ASD. SynGAP is enriched at excitatory synapses and genetic suppression of SynGAP increases excitatory synaptic strength. However, exactly how SynGAP acts to maintain synaptic AMPAR content is unclear. We show here that SynGAP limits excitatory synaptic strength, in part, by suppressing protein synthesis in cortical neurons. The data presented here from in vitro, rat and mouse cortical networks, demonstrate that regulation of translation by SynGAP involves ERK, mTOR, and the small GTP-binding protein Rheb. Furthermore, these data show that GluN2B-containing NMDARs and the cognitive kinase CaMKII act upstream of SynGAP and that this signaling cascade is required for proper translation-dependent homeostatic synaptic plasticity of excitatory synapses in developing cortical networks.

  4. Detection of alpha-rod protein repeats using a neural network and application to huntingtin.

    Palidwor, Gareth A; Shcherbinin, Sergey; Huska, Matthew R; Rasko, Tamas; Stelzl, Ulrich; Arumughan, Anup; Foulle, Raphaele; Porras, Pablo; Sanchez-Pulido, Luis; Wanker, Erich E; Andrade-Navarro, Miguel A

    2009-03-01

    A growing number of solved protein structures display an elongated structural domain, denoted here as alpha-rod, composed of stacked pairs of anti-parallel alpha-helices. Alpha-rods are flexible and expose a large surface, which makes them suitable for protein interaction. Although most likely originating by tandem duplication of a two-helix unit, their detection using sequence similarity between repeats is poor. Here, we show that alpha-rod repeats can be detected using a neural network. The network detects more repeats than are identified by domain databases using multiple profiles, with a low level of false positives (definition of domains in huntingtin and the first validation of predicted interactions between fragments of huntingtin, which sets up directions toward functional characterization of this protein. An implementation of the repeat detection algorithm is available as a Web server with a simple graphical output: http://www.ogic.ca/projects/ard. This can be further visualized using BiasViz, a graphic tool for representation of multiple sequence alignments. PMID:19282972

  5. Predicting protein structural classes based on complex networks and recurrence analysis.

    Olyaee, Mohammad H; Yaghoubi, Ali; Yaghoobi, Mahdi

    2016-09-01

    Protein sequences are divided into four structural classes. The determination of class is a challenging and beneficial task in the bioinformatics field. Several methods have been proposed to this end, but most utilize too many features and produce unsuitable results. In the present, features are extracted based on the predicted secondary structures. At first, predicted secondary structure sequences are mapped into two time series by the chaos game representation. Then, a recurrence matrix is calculated from each of the time series. The recurrence matrix is identified with the adjacency matrix of a complex network and measures are applied for the characterization of complex networks to these recurrence matrixes. For a given protein sequence, a total of 24 characteristic features can be calculated and these are fed into Fisher's discriminated analysis algorithm for classification. To examine the proposed method, two widely used low similarity benchmark datasets design and test its performance. A comparison with the results of existing methods shows that the current study's approach provides a satisfactory performance for protein structural class prediction. PMID:27320678

  6. Bottom-up study of flaw tolerance properties of protein networks

    Qin, Zhao; Buehler, Markus

    2012-02-01

    We study the material properties of an intermediate filament proten network by computational modeling using a bottom-up approach. We start with an atomic model of each filament's and obtain the mechanical behavior of them. We then use these parameters in setting up a mesoscale model of the network material at scales of micrometers. Using this multi-scale method, we report a detailed analysis of the associated deformation and failure mechanisms of this hierarchical material. Our modeling reveals that a structure transition that occurs at the proteins' secondary structure level is crucial for the networks' flaw tolerance property, which implies that the material retains its mechanical function despite the existence of large defects. We also examine the effect of crosslink strength on the failure properties. We discover that relatively weaker crosslinks lead to a more flaw tolerant network that is 23% stronger. This unexpected behavior is caused by that the crosslink strength functions as a switch to alter the failure mechanism. Weak crosslinks are able to efficiently diffuse the stress around the crack tip, making the crack more difficult to propagate. We compare our results to that of elastic and softening materials and find that the effect of crosslink strength is much smaller in those systems. These findings imply that the mechanical properties of both the filaments and interfaces among filaments are critical for bioinspired material designs, challenging the conventional paradigm in engineering design.

  7. GBNV encoded movement protein (NSm) remodels ER network via C-terminal coiled coil domain

    Singh, Pratibha; Savithri, H.S., E-mail: bchss@biochem.iisc.ernet.in

    2015-08-15

    Plant viruses exploit the host machinery for targeting the viral genome–movement protein complex to plasmodesmata (PD). The mechanism by which the non-structural protein m (NSm) of Groundnut bud necrosis virus (GBNV) is targeted to PD was investigated using Agrobacterium mediated transient expression of NSm and its fusion proteins in Nicotiana benthamiana. GFP:NSm formed punctuate structures that colocalized with mCherry:plasmodesmata localized protein 1a (PDLP 1a) confirming that GBNV NSm localizes to PD. Unlike in other movement proteins, the C-terminal coiled coil domain of GBNV NSm was shown to be involved in the localization of NSm to PD, as deletion of this domain resulted in the cytoplasmic localization of NSm. Treatment with Brefeldin A demonstrated the role of ER in targeting GFP NSm to PD. Furthermore, mCherry:NSm co-localized with ER–GFP (endoplasmic reticulum targeting peptide (HDEL peptide fused with GFP). Co-expression of NSm with ER–GFP showed that the ER-network was transformed into vesicles indicating that NSm interacts with ER and remodels it. Mutations in the conserved hydrophobic region of NSm (residues 130–138) did not abolish the formation of vesicles. Additionally, the conserved prolines at positions 140 and 142 were found to be essential for targeting the vesicles to the cell membrane. Further, systematic deletion of amino acid residues from N- and C-terminus demonstrated that N-terminal 203 amino acids are dispensable for the vesicle formation. On the other hand, the C-terminal coiled coil domain when expressed alone could also form vesicles. These results suggest that GBNV NSm remodels the ER network by forming vesicles via its interaction through the C-terminal coiled coil domain. Interestingly, NSm interacts with NP in vitro and coexpression of these two proteins in planta resulted in the relocalization of NP to PD and this relocalization was abolished when the N-terminal unfolded region of NSm was deleted. Thus, the NSm

  8. GBNV encoded movement protein (NSm) remodels ER network via C-terminal coiled coil domain

    Plant viruses exploit the host machinery for targeting the viral genome–movement protein complex to plasmodesmata (PD). The mechanism by which the non-structural protein m (NSm) of Groundnut bud necrosis virus (GBNV) is targeted to PD was investigated using Agrobacterium mediated transient expression of NSm and its fusion proteins in Nicotiana benthamiana. GFP:NSm formed punctuate structures that colocalized with mCherry:plasmodesmata localized protein 1a (PDLP 1a) confirming that GBNV NSm localizes to PD. Unlike in other movement proteins, the C-terminal coiled coil domain of GBNV NSm was shown to be involved in the localization of NSm to PD, as deletion of this domain resulted in the cytoplasmic localization of NSm. Treatment with Brefeldin A demonstrated the role of ER in targeting GFP NSm to PD. Furthermore, mCherry:NSm co-localized with ER–GFP (endoplasmic reticulum targeting peptide (HDEL peptide fused with GFP). Co-expression of NSm with ER–GFP showed that the ER-network was transformed into vesicles indicating that NSm interacts with ER and remodels it. Mutations in the conserved hydrophobic region of NSm (residues 130–138) did not abolish the formation of vesicles. Additionally, the conserved prolines at positions 140 and 142 were found to be essential for targeting the vesicles to the cell membrane. Further, systematic deletion of amino acid residues from N- and C-terminus demonstrated that N-terminal 203 amino acids are dispensable for the vesicle formation. On the other hand, the C-terminal coiled coil domain when expressed alone could also form vesicles. These results suggest that GBNV NSm remodels the ER network by forming vesicles via its interaction through the C-terminal coiled coil domain. Interestingly, NSm interacts with NP in vitro and coexpression of these two proteins in planta resulted in the relocalization of NP to PD and this relocalization was abolished when the N-terminal unfolded region of NSm was deleted. Thus, the NSm

  9. Network single-walled carbon nanotube biosensors for fast and highly sensitive detection of proteins

    Hu Pingan; Zhang Jia; Wen Zhenzhong [Research Centre for Micro/Nanotechnology, Harbin Institute of Technology, No. 2 YiKuang Street, Harbin 150080 (China); Zhang Can, E-mail: hupa@hit.edu.cn [Centre for Advanced Photonics and Electronics, University of Cambridge, Cambridge CB3 0FA (United Kingdom)

    2011-08-19

    Detection of proteins is powerfully assayed in the diagnosis of diseases. A strategy for the development of an ultrahigh sensitivity biosensor based on a network single-walled carbon nanotube (SWNT) field-effect transistor (FET) has been demonstrated. Metallic SWNTs (m-SWNTs) in the network nanotube FET were selectively removed or cut via a carefully controlled procedure of electrical break-down (BD), and left non-conducting m-SWNTs which magnified the Schottky barrier (SB) area. This nanotube FET exhibited ultrahigh sensitivity and fast response to biomolecules. The lowest detection limit of 0.5 pM was achieved by exploiting streptavidin (SA) or a biotin/SA pair as the research model, and BD-treated nanotube biosensors had a 2 x 10{sup 4}-fold lower minimum detectable concentration than the device without BD treatment. The response time is in the range of 0.3-3 min.

  10. Phylogeny, Functional Annotation, and Protein Interaction Network Analyses of the Xenopus tropicalis Basic Helix-Loop-Helix Transcription Factors

    Wuyi Liu

    2013-01-01

    Full Text Available The previous survey identified 70 basic helix-loop-helix (bHLH proteins, but it was proved to be incomplete, and the functional information and regulatory networks of frog bHLH transcription factors were not fully known. Therefore, we conducted an updated genome-wide survey in the Xenopus tropicalis genome project databases and identified 105 bHLH sequences. Among the retrieved 105 sequences, phylogenetic analyses revealed that 103 bHLH proteins belonged to 43 families or subfamilies with 46, 26, 11, 3, 15, and 4 members in the corresponding supergroups. Next, gene ontology (GO enrichment analyses showed 65 significant GO annotations of biological processes and molecular functions and KEGG pathways counted in frequency. To explore the functional pathways, regulatory gene networks, and/or related gene groups coding for Xenopus tropicalis bHLH proteins, the identified bHLH genes were put into the databases KOBAS and STRING to get the signaling information of pathways and protein interaction networks according to available public databases and known protein interactions. From the genome annotation and pathway analysis using KOBAS, we identified 16 pathways in the Xenopus tropicalis genome. From the STRING interaction analysis, 68 hub proteins were identified, and many hub proteins created a tight network or a functional module within the protein families.

  11. In-silico designing of a potent analogue against HIV-1 Nef protein and protease by predicting its interaction network with host cell proteins

    Shikha Pal

    2013-01-01

    Full Text Available Background: HIV-1 has numerous proteins encoded within its genome, which acquaints it with the required arsenal to establish a favorable host cell environment suitable for viral replication and pathogenesis. Among these proteins, one protein that is indispensable and ambiguous is the Nef protein. Aim: Interaction of Nef protein with different host-cell protein was predicted and subsequently the down regulation of cluster of differentiation 4 (CD4 was targeted through designing of inhibitors of Nef protein for either preventing or if not at least delaying pathogenesis. Materials and Methods: The interaction network of Nef protein with host-cell proteins were predicted by PIMRider. Analogue of Lopinavir were prepared and evaluated considering all factors affecting the drug stability and toxicity. Finally Docking simulation were performed using an Auto-Dock Tool 4.0. Results: In the interaction network of Nef protein with different host-cell proteins it was found out that 22 host cell proteins are involved in the interaction and execution of different types of functions in host cell but these functions are altered with the interaction with the Nef protein. After extensive and controlled in silico analysis it has been observed that the analogue LOPI1 binds to Nef protein (2NEF at CD4 interacting site residues giving minimum binding energy of −7.68 Kcal/mole, low Ki value of 2.34 μM, maximum number of hydrogen bonds (8, good absorption, distribution, metabolism and excretion properties, and less toxicity in comparison with the standard Lopinavir against HIV1 protease (1HPV. Conclusion: The newly designed analogue (LOPI1 is showing significant in silico interaction with Nef protein and protease and can be taken forward as a potent drug lead, which may finally emerge out to be even better than the standard Lopinavir.

  12. Fault tolerance in protein interaction networks: stable bipartite subgraphs and redundant pathways.

    Arthur Brady

    Full Text Available As increasing amounts of high-throughput data for the yeast interactome become available, more system-wide properties are uncovered. One interesting question concerns the fault tolerance of protein interaction networks: whether there exist alternative pathways that can perform some required function if a gene essential to the main mechanism is defective, absent or suppressed. A signature pattern for redundant pathways is the BPM (between-pathway model motif, introduced by Kelley and Ideker. Past methods proposed to search the yeast interactome for BPM motifs have had several important limitations. First, they have been driven heuristically by local greedy searches, which can lead to the inclusion of extra genes that may not belong in the motif; second, they have been validated solely by functional coherence of the putative pathways using GO enrichment, making it difficult to evaluate putative BPMs in the absence of already known biological annotation. We introduce stable bipartite subgraphs, and show they form a clean and efficient way of generating meaningful BPMs which naturally discard extra genes included by local greedy methods. We show by GO enrichment measures that our BPM set outperforms previous work, covering more known complexes and functional pathways. Perhaps most importantly, since our BPMs are initially generated by examining the genetic-interaction network only, the location of edges in the protein-protein physical interaction network can then be used to statistically validate each candidate BPM, even with sparse GO annotation (or none at all. We uncover some interesting biological examples of previously unknown putative redundant pathways in such areas as vesicle-mediated transport and DNA repair.

  13. Identification of Top-ranked Proteins within a Directional Protein Interaction Network using the PageRank Algorithm: Applications in Humans and Plants.

    Li, Xiu-Qing; Xing, Tim; Du, Donglei

    2016-01-01

    Somatic mutation of signal transduction genes or key nodes of the cellular protein network can cause severe diseases in humans but can sometimes genetically improve plants, likely because growth is determinate in animals but indeterminate in plants. This article reviews protein networks; human protein ranking; the mitogen-activated protein kinase (MAPK) and insulin (phospho- inositide 3kinase [PI3K]/phosphatase and tensin homolog [PTEN]/protein kinase B [AKT]) signaling pathways; human diseases caused by somatic mutations to the PI3K/PTEN/ AKT pathway; use of the MAPK pathway in plant molecular breeding; and protein domain evolution. Casitas B-lineage lymphoma (CBL), PTEN, MAPK1 and PIK3CA are among PIK3CA the top-ranked proteins in directional rankings. Eight proteins (ACVR1, CDC42, RAC1, RAF1, RHOA, TGFBR1, TRAF2, and TRAF6) are ranked in the top 50 key players in both signal emission and signal reception and in interaction with many other proteins. Top-ranked proteins likely have major impacts on the network function. Such proteins are targets for drug discovery, because their mutations are implicated in various cancers and overgrowth syndromes. Appropriately managing food intake may help reduce the growth of tumors or malformation of tissues. The role of the protein kinase C/ fatty acid synthase pathway in fat deposition in PTEN/PI3K patients should be investigated. Both the MAPK and insulin signaling pathways exist in plants, and MAPK pathway engineering can improve plant tolerance to biotic and abiotic stresses such as salinity. PMID:26637164

  14. Mitochondrial trafficking in neurons and the role of the Miro family of GTPase proteins.

    Birsa, Nicol; Norkett, Rosalind; Higgs, Nathalie; Lopez-Domenech, Guillermo; Kittler, Josef T

    2013-12-01

    Correct mitochondrial dynamics are essential to neuronal function. These dynamics include mitochondrial trafficking and quality-control systems that maintain a precisely distributed and healthy mitochondrial network, so that local energy demands or Ca2+-buffering requirements within the intricate architecture of the neuron can be met. Mitochondria make use of molecular machinery that couples these organelles to microtubule-based transport via kinesin and dynein motors, facilitating the required long-range movements. These motors in turn are associated with a variety of adaptor proteins allowing additional regulation of the complex dynamics demonstrated by these organelles. Over recent years, a number of new motor and adaptor proteins have been added to a growing list of components implicated in mitochondrial trafficking and distribution. Yet, there are major questions that remain to be addressed about the regulation of mitochondrial transport complexes. One of the core components of this machinery, the mitochondrial Rho GTPases Miro1 (mitochondrial Rho 1) and Miro2 have received special attention due to their Ca2+-sensing and GTPase abilities, marking Miro an exceptional candidate for co-ordinating mitochondrial dynamics and intracellular signalling pathways. In the present paper, we discuss the wealth of literature regarding Miro-mediated mitochondrial transport in neurons and recently highlighted involvement of Miro proteins in mitochondrial turnover, emerging as a key process affected in neurodegeneration. PMID:24256248

  15. Hydrogen bond networks determine emergent mechanical and thermodynamic properties across a protein family

    Dallakyan Sargis

    2008-08-01

    Full Text Available Abstract Background Gram-negative bacteria use periplasmic-binding proteins (bPBP to transport nutrients through the periplasm. Despite immense diversity within the recognized substrates, all members of the family share a common fold that includes two domains that are separated by a conserved hinge. The hinge allows the protein to cycle between open (apo and closed (ligated conformations. Conformational changes within the proteins depend on a complex interplay of mechanical and thermodynamic response, which is manifested as an increase in thermal stability and decrease of flexibility upon ligand binding. Results We use a distance constraint model (DCM to quantify the give and take between thermodynamic stability and mechanical flexibility across the bPBP family. Quantitative stability/flexibility relationships (QSFR are readily evaluated because the DCM links mechanical and thermodynamic properties. We have previously demonstrated that QSFR is moderately conserved across a mesophilic/thermophilic RNase H pair, whereas the observed variance indicated that different enthalpy-entropy mechanisms allow similar mechanical response at their respective melting temperatures. Our predictions of heat capacity and free energy show marked diversity across the bPBP family. While backbone flexibility metrics are mostly conserved, cooperativity correlation (long-range couplings also demonstrate considerable amount of variation. Upon ligand removal, heat capacity, melting point, and mechanical rigidity are, as expected, lowered. Nevertheless, significant differences are found in molecular cooperativity correlations that can be explained by the detailed nature of the hydrogen bond network. Conclusion Non-trivial mechanical and thermodynamic variation across the family is explained by differences within the underlying H-bond networks. The mechanism is simple; variation within the H-bond networks result in altered mechanical linkage properties that directly affect

  16. Water molecule network and active site flexibility of apo protein tyrosine phosphatase 1B

    Pedersen, A.K.; Peters, Günther H.J.; Møller, K.B.;

    2004-01-01

    Protein tyrosine phosphatase 1B (PTP1B) plays a key role as a negative regulator of insulin and leptin signalling and is therefore considered to be an important molecular target for the treatment of type 2 diabetes and obesity. Detailed structural information about the structure of PTP1B, including...... the conformation and flexibility of active-site residues as well as the water-molecule network, is a key issue in understanding ligand binding and enzyme kinetics and in structure-based drug design. A 1.95 Angstrom apo PTP1B structure has been obtained, showing four highly coordinated water molecules...

  17. Dissecting spatio-temporal protein networks driving human heart development and related disorders

    Hansen, Kasper Lage; Mølgård, Kjeld; Greenway, Steven; Wakimoto, Hiroko; Gorham, Joshua M.; Workman, Christopher; Bendsen, Eske; Hansen, Niclas Tue; Rigina, Olga; Roque, Francisco José Sousa Simões Almeida; Wiese, Cornelia; Christoffels, Vincent M.; Roberts, Amy E.; Smoot, Leslie B.; Pu, William T.; Donahoe, Patricia K.; Tommerup, Niels; Brunak, Søren; Seidman, Christine E.; Seidman, Jonathan G.; Larsen, Lars A.

    2010-01-01

    development, we combined detailed phenotype information from deleterious mutations in 255 genes with high-confidence experimental interactome data, and coupled the results to thorough experimental validation. Hereby, we made the first systematic analysis of spatio-temporal protein networks driving many stages...... blocks, and suggests how mutations in the same genes can lead to diverse phenotypes. We observe a striking temporal correlation between organ complexity and the number of discrete functional modules coordinating morphogenesis. Our analysis elucidates the organization and composition of spatio...

  18. Digital Operation of Microelectronic Circuits Analogous to Protein Hydrogen Bonding Networks

    Elitsa Gieva

    2012-12-01

    Full Text Available Two hydrogen bonding networks with water molecules and branching residues extracted from β-lactamase protein are investigated and their proton transfer characteristics are studied by creating analogous electrical circuits consisting of block-elements. The block-elements and their proton transfer are described by polynomials that are coded in Matlab and in Verilog-A for use in the Spectre simulator of Cadence IC design system. DC and digital pulse analyses are performed to demonstrate that some circuit outputs behave as repeaters while other - behave as inverters. The results also showed that the HBN circuits might behave as a D-latch and a demultiplexer.

  19. The effects of rehabilitative training on neural function and the expression of glial fibrillary acidic protein and ionized calcium binding adaptor molecule-1 after traumatic brain injury%康复训练对脑损伤后大鼠神经功能及胶原纤维酸性蛋白和离子钙接头分子表达的影响

    刘苏; 沈光宇; 吴勤峰; 张志军; 郭爱松; 李欣嫄; 邹玉婷

    2012-01-01

    目的 研究康复功能训练对大鼠脑损伤神经功能恢复及损伤边缘皮质胶原纤维酸性蛋白(GFAP)和离子钙接头分子(Iba-1)表达的影响.方法 SD大鼠131只,按随机数字表法选取30只为假手术组,其余101只制作脑损伤模型.剔除制模未达标大鼠11只,余90只按随机数字表法分为康复训练组、制动组和自由活动组,每组30只大鼠.康复训练组于术后第4天开始每天给予平衡、旋转、行走等功能训练,每项15min,共训练45min,每周6d;制动组置于网状笼内固定;自由活动组和假手术组置于普通笼内饲养.在术后第3天及术后1、2、3和4周对上述4组分别进行神经和运动功能评估,观察其恢复状况;同时采用免疫荧光染色观察损伤区边缘皮质GFAP和Iba-1的表达.结果 康复训练组术后2、3和4周在功能评估方面优于制动组和自由活动组(P<0.05);术后4周自由活动组较制动组的神经运动功能也有所恢复(P<0.05).脑损伤术后2、3和4周康复训练组GFAP阳性细胞灰度值和术后3、4周康复训练组Iba-1阳性细胞平均灰度值均明显低于制动组和自由活动组(P<0.01).结论 康复功能训练可促进大鼠脑损伤的神经功能恢复,其机制可能与损伤区边缘皮质星形胶质细胞和小胶质细胞的活化数目减少有关.%Objective To study the effectsof rehabilitative training on neural function and the expression of glial fibrillary acidic protein (GFAP) and ionized calcium binding adaptor molecule-1 (Iba-1) in rats after traumatic brain injury.Methods A left hemisphere traumatic brain injury model was established in ninety Sprague-Dawley rats.They were then randomly divided into a rehabilitation training group,an immobilization group and a free-running group,with 30 rats in each group.Another thirty rats received sham injury as the shamoperated group.Beginning 4 days post-operation the rats of the rehabilitation training group were given

  20. Yeast Gga coat proteins function with clathrin in Golgi to endosome transport.

    Costaguta, G; Stefan, C J; Bensen, E S; Emr, S D; Payne, G S

    2001-06-01

    Gga proteins represent a newly recognized, evolutionarily conserved protein family with homology to the "ear" domain of the clathrin adaptor AP-1 gamma subunit. Yeast cells contain two Gga proteins, Gga1p and Gga2p, that have been proposed to act in transport between the trans-Golgi network and endosomes. Here we provide genetic and physical evidence that yeast Gga proteins function in trans-Golgi network clathrin coats. Deletion of Gga2p (gga2Delta), the major Gga protein, accentuates growth and alpha-factor maturation defects in cells carrying a temperature-sensitive allele of the clathrin heavy chain gene. Cells carrying either gga2Delta or a deletion of the AP-1 beta subunit gene (apl2Delta) alone are phenotypically normal, but cells carrying both gga2Delta and apl2Delta are defective in growth, alpha-factor maturation, and transport of carboxypeptidase S to the vacuole. Disruption of both GGA genes and APL2 results in cells so severely compromised in growth that they form only microcolonies. Gga proteins can bind clathrin in vitro and cofractionate with clathrin-coated vesicles. Our results indicate that yeast Gga proteins play an important role in cargo-selective clathrin-mediated protein traffic from the trans-Golgi network to endosomes. PMID:11408593

  1. Synapse formation is regulated by the signaling adaptor GIT1

    Zhang, Huaye; Webb, Donna J.; Asmussen, Hannelore; Horwitz, Alan F.

    2003-01-01

    Dendritic spines in the central nervous system undergo rapid actin-based shape changes, making actin regulators potential modulators of spine morphology and synapse formation. Although several potential regulators and effectors for actin organization have been identified, the mechanisms by which these molecules assemble and localize are not understood. Here we show that the G protein–coupled receptor kinase–interacting protein (GIT)1 serves such a function by targeting actin regulators and lo...

  2. Features analysis for identification of date and party hubs in protein interaction network of Saccharomyces Cerevisiae

    Araabi Babak N

    2010-12-01

    Full Text Available Abstract Background It has been understood that biological networks have modular organizations which are the sources of their observed complexity. Analysis of networks and motifs has shown that two types of hubs, party hubs and date hubs, are responsible for this complexity. Party hubs are local coordinators because of their high co-expressions with their partners, whereas date hubs display low co-expressions and are assumed as global connectors. However there is no mutual agreement on these concepts in related literature with different studies reporting their results on different data sets. We investigated whether there is a relation between the biological features of Saccharomyces Cerevisiae's proteins and their roles as non-hubs, intermediately connected, party hubs, and date hubs. We propose a classifier that separates these four classes. Results We extracted different biological characteristics including amino acid sequences, domain contents, repeated domains, functional categories, biological processes, cellular compartments, disordered regions, and position specific scoring matrix from various sources. Several classifiers are examined and the best feature-sets based on average correct classification rate and correlation coefficients of the results are selected. We show that fusion of five feature-sets including domains, Position Specific Scoring Matrix-400, cellular compartments level one, and composition pairs with two and one gaps provide the best discrimination with an average correct classification rate of 77%. Conclusions We study a variety of known biological feature-sets of the proteins and show that there is a relation between domains, Position Specific Scoring Matrix-400, cellular compartments level one, composition pairs with two and one gaps of Saccharomyces Cerevisiae's proteins, and their roles in the protein interaction network as non-hubs, intermediately connected, party hubs and date hubs. This study also confirms the

  3. ER Adaptor SCAP Translocates and Recruits IRF3 to Perinuclear Microsome Induced by Cytosolic Microbial DNAs.

    Wei Chen

    2016-02-01

    Full Text Available Stimulator of interferon genes (STING, also known as MITA, ERIS or MPYS induces the activation of TBK1 kinase and IRF3 transcription factor, upon sensing of microbial DNAs. How IRF3 is recruited onto the STING signalosome remains unknown. We report here that silencing of the ER adaptor SCAP markedly impairs the IRF3-responsive gene expression induced by STING. Scap knockdown mice are more susceptible to HSV-1 infection. Interestingly, SCAP translocates from ER, via Golgi, to perinuclear microsome in a STING-dependent manner. Mechanistically, the N-terminal transmembrane domain of SCAP interacts with STING, and the C-terminal cytosolic domain of SCAP binds to IRF3, thus recruiting IRF3 onto STING signalosome. Mis-localization of SCAP abolishes its antiviral function. Collectively, this study characterizes SCAP as an essential adaptor in the STING signaling pathway, uncovering a critical missing link in DNAs-triggered host antiviral responses.

  4. Clathrin and HA2 adaptors: effects of potassium depletion, hypertonic medium, and cytosol acidification

    1993-01-01

    The effects of methods known to perturb endocytosis from clathrin- coated pits on the localization of clathrin and HA2 adaptors in HEp-2 carcinoma cells have been studied by immunofluorescence and ultrastructural immunogold microscopy, using internalization of transferrin as a functional assay. Potassium depletion, as well as incubation in hypertonic medium, remove membrane-associated clathrin lattices: flat clathrin lattices and coated pits from the plasma membrane, and clathrin-coated vesic...

  5. The adaptor molecule Trif contributes to murine host defense during Leptospiral infection.

    Jayaraman, Priya A; Devlin, Amy A; Miller, Jennifer C; Scholle, Frank

    2016-09-01

    Leptospirosis is a zoonotic disease and is caused by pathogenic species of the Leptospira genus, including Leptospira interrogans (L. interrogans). Humans, domestic and wild animals are susceptible to acute or chronic infection. The innate immune response is a critical defense mechanism against Leptospira interrogans, and has been investigated in mouse models. Murine Toll-like receptors (TLRs) have been shown to be key factors in sensing and responding to L. interrogans infection. Specifically, TLR2, TLR4 and the TLR adaptor molecule MyD88 are essential for host defense against L. interrogans; however, the role of the TLR adaptor molecule TIR-domain-containing adaptor-inducing interferon β (TRIF) in the response to L. interrogans has not been previously determined. In the present study, TRIF was found to play an important role during leptospiral infection. Following challenge with L. interrogans, Trif(-/-) mice exhibited delayed weight gain compared to wild-type mice. Moreover, Trif(-/-) mice exhibited an increase in L. interrogans burden in the kidneys, lungs, and blood at early time points (less than 7days post infection). Multiple components of the innate immune responses were dampened in response to leptospiral infection including transcription and production of cytokines, and the humoral response, which suggested that TRIF contributes to expression and production of cytokines important for the host defense against L. interrogans. PMID:27259371

  6. A Network of Multi-Tasking Proteins at the DNA Replication Fork Preserves Genome Stability.

    2005-12-01

    Full Text Available To elucidate the network that maintains high fidelity genome replication, we have introduced two conditional mutant alleles of DNA2, an essential DNA replication gene, into each of the approximately 4,700 viable yeast deletion mutants and determined the fitness of the double mutants. Fifty-six DNA2-interacting genes were identified. Clustering analysis of genomic synthetic lethality profiles of each of 43 of the DNA2-interacting genes defines a network (consisting of 322 genes and 876 interactions whose topology provides clues as to how replication proteins coordinate regulation and repair to protect genome integrity. The results also shed new light on the functions of the query gene DNA2, which, despite many years of study, remain controversial, especially its proposed role in Okazaki fragment processing and the nature of its in vivo substrates. Because of the multifunctional nature of virtually all proteins at the replication fork, the meaning of any single genetic interaction is inherently ambiguous. The multiplexing nature of the current studies, however, combined with follow-up supporting experiments, reveals most if not all of the unique pathways requiring Dna2p. These include not only Okazaki fragment processing and DNA repair but also chromatin dynamics.

  7. Regulation of ITAM adaptor molecules and their receptors by inhibition of calcineurin-NFAT signalling during late stage osteoclast differentiation

    Highlights: ► Calcineurin/NFAT inhibitors FK506 and VIVIT treated human PBMC derived osteoclasts in vitro. ► Differential regulation of ITAM receptors and adaptor molecules by calcineurin/NFAT inhibitors. ► FK506 and VIVIT suppress ITAM factors during late phase osteoclast differentiation. -- Abstract: Osteoclasts are specialised bone resorptive cells responsible for both physiological and pathological bone loss. Osteoclast differentiation and activity is dependent upon receptor activator NF-kappa-B ligand (RANKL) interacting with its receptor RANK to induce the transcription factor, nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 1 (NFATc1). The immunoreceptor tyrosine-based activation motif (ITAM)-dependent pathway has been identified as a co-stimulatory pathway in osteoclasts. Osteoclast-associated receptor (OSCAR) and triggering receptor expressed in myeloid cells (TREM2) are essential receptors that pair with adaptor molecules Fc receptor common gamma chain (FcRγ) and DNAX-activating protein 12 kDa (DAP12) respectively to induce calcium signalling. Treatment with calcineurin-NFAT inhibitors, Tacrolimus (FK506) and the 11R-VIVIT (VIVIT) peptide, reduces NFATc1 expression consistent with a reduction in osteoclast differentiation and activity. This study aimed to investigate the effects of inhibiting calcineurin-NFAT signalling on the expression of ITAM factors and late stage osteoclast genes including cathepsin K (CathK), Beta 3 integrin (β3) and Annexin VIII (AnnVIII). Human peripheral blood mononuclear cells (PBMCs) were differentiated with RANKL and macrophage-colony stimulating factor (M-CSF) over 10 days in the presence or absence of FK506 or VIVIT. Osteoclast formation (as assessed by tartrate resistant acid phosphatase (TRAP)) and activity (assessed by dentine pit resorption) were significantly reduced with treatment. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis demonstrated that FK506 treatment

  8. Regulation of ITAM adaptor molecules and their receptors by inhibition of calcineurin-NFAT signalling during late stage osteoclast differentiation

    Zawawi, M.S.F. [Universiti Sains Malaysia (USM) (Malaysia); Discipline of Anatomy and Pathology, School of Medical Sciences, University of Adelaide, Adelaide, SA 5005 (Australia); Dharmapatni, A.A.S.S.K.; Cantley, M.D. [Discipline of Anatomy and Pathology, School of Medical Sciences, University of Adelaide, Adelaide, SA 5005 (Australia); McHugh, K.P. [University of Florida, College of Dentistry, Fl (United States); Haynes, D.R. [Discipline of Anatomy and Pathology, School of Medical Sciences, University of Adelaide, Adelaide, SA 5005 (Australia); Crotti, T.N., E-mail: tania.crotti@adelaide.edu.au [Discipline of Anatomy and Pathology, School of Medical Sciences, University of Adelaide, Adelaide, SA 5005 (Australia)

    2012-10-19

    Highlights: Black-Right-Pointing-Pointer Calcineurin/NFAT inhibitors FK506 and VIVIT treated human PBMC derived osteoclasts in vitro. Black-Right-Pointing-Pointer Differential regulation of ITAM receptors and adaptor molecules by calcineurin/NFAT inhibitors. Black-Right-Pointing-Pointer FK506 and VIVIT suppress ITAM factors during late phase osteoclast differentiation. -- Abstract: Osteoclasts are specialised bone resorptive cells responsible for both physiological and pathological bone loss. Osteoclast differentiation and activity is dependent upon receptor activator NF-kappa-B ligand (RANKL) interacting with its receptor RANK to induce the transcription factor, nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 1 (NFATc1). The immunoreceptor tyrosine-based activation motif (ITAM)-dependent pathway has been identified as a co-stimulatory pathway in osteoclasts. Osteoclast-associated receptor (OSCAR) and triggering receptor expressed in myeloid cells (TREM2) are essential receptors that pair with adaptor molecules Fc receptor common gamma chain (FcR{gamma}) and DNAX-activating protein 12 kDa (DAP12) respectively to induce calcium signalling. Treatment with calcineurin-NFAT inhibitors, Tacrolimus (FK506) and the 11R-VIVIT (VIVIT) peptide, reduces NFATc1 expression consistent with a reduction in osteoclast differentiation and activity. This study aimed to investigate the effects of inhibiting calcineurin-NFAT signalling on the expression of ITAM factors and late stage osteoclast genes including cathepsin K (CathK), Beta 3 integrin ({beta}3) and Annexin VIII (AnnVIII). Human peripheral blood mononuclear cells (PBMCs) were differentiated with RANKL and macrophage-colony stimulating factor (M-CSF) over 10 days in the presence or absence of FK506 or VIVIT. Osteoclast formation (as assessed by tartrate resistant acid phosphatase (TRAP)) and activity (assessed by dentine pit resorption) were significantly reduced with treatment. Quantitative real

  9. A protein network-guided screen for cell cycle regulators in Drosophila

    Kashat Maria A

    2011-05-01

    Full Text Available Abstract Background Large-scale RNAi-based screens are playing a critical role in defining sets of genes that regulate specific cellular processes. Numerous screens have been completed and in some cases more than one screen has examined the same cellular process, enabling a direct comparison of the genes identified in separate screens. Surprisingly, the overlap observed between the results of similar screens is low, suggesting that RNAi screens have relatively high levels of false positives, false negatives, or both. Results We re-examined genes that were identified in two previous RNAi-based cell cycle screens to identify potential false positives and false negatives. We were able to confirm many of the originally observed phenotypes and to reveal many likely false positives. To identify potential false negatives from the previous screens, we used protein interaction networks to select genes for re-screening. We demonstrate cell cycle phenotypes for a significant number of these genes and show that the protein interaction network is an efficient predictor of new cell cycle regulators. Combining our results with the results of the previous screens identified a group of validated, high-confidence cell cycle/cell survival regulators. Examination of the subset of genes from this group that regulate the G1/S cell cycle transition revealed the presence of multiple members of three structurally related protein complexes: the eukaryotic translation initiation factor 3 (eIF3 complex, the COP9 signalosome, and the proteasome lid. Using a combinatorial RNAi approach, we show that while all three of these complexes are required for Cdk2/Cyclin E activity, the eIF3 complex is specifically required for some other step that limits the G1/S cell cycle transition. Conclusions Our results show that false positives and false negatives each play a significant role in the lack of overlap that is observed between similar large-scale RNAi-based screens. Our results

  10. IntNetDB v1.0: an integrated protein-protein interaction network database generated by a probabilistic model

    Han Jing-Dong J

    2006-11-01

    Full Text Available Abstract Background Although protein-protein interaction (PPI networks have been explored by various experimental methods, the maps so built are still limited in coverage and accuracy. To further expand the PPI network and to extract more accurate information from existing maps, studies have been carried out to integrate various types of functional relationship data. A frequently updated database of computationally analyzed potential PPIs to provide biological researchers with rapid and easy access to analyze original data as a biological network is still lacking. Results By applying a probabilistic model, we integrated 27 heterogeneous genomic, proteomic and functional annotation datasets to predict PPI networks in human. In addition to previously studied data types, we show that phenotypic distances and genetic interactions can also be integrated to predict PPIs. We further built an easy-to-use, updatable integrated PPI database, the Integrated Network Database (IntNetDB online, to provide automatic prediction and visualization of PPI network among genes of interest. The networks can be visualized in SVG (Scalable Vector Graphics format for zooming in or out. IntNetDB also provides a tool to extract topologically highly connected network neighborhoods from a specific network for further exploration and research. Using the MCODE (Molecular Complex Detections algorithm, 190 such neighborhoods were detected among all the predicted interactions. The predicted PPIs can also be mapped to worm, fly and mouse interologs. Conclusion IntNetDB includes 180,010 predicted protein-protein interactions among 9,901 human proteins and represents a useful resource for the research community. Our study has increased prediction coverage by five-fold. IntNetDB also provides easy-to-use network visualization and analysis tools that allow biological researchers unfamiliar with computational biology to access and analyze data over the internet. The web interface of

  11. A library of 7TM receptor C-terminal tails. Interactions with the proposed post-endocytic sorting proteins ERM-binding phosphoprotein 50 (EBP50), N-ethylmaleimide-sensitive factor (NSF), sorting nexin 1 (SNX1), and G protein-coupled receptor-associated sorting protein (GASP)

    Heydorn, Arne; Søndergaard, Birgitte P; Ersbøll, Bjarne;

    2004-01-01

    Adaptor and scaffolding proteins determine the cellular targeting, the spatial, and thereby the functional association of G protein-coupled seven-transmembrane receptors with co-receptors, transducers, and downstream effectors and the adaptors determine post-signaling events such as receptor sequ...... that the tail library provides useful information on the general importance of certain adaptor proteins, for example, in this case, ruling out EBP50 as being a broad spectrum-recycling adaptor....... proteins previously proposed to be involved in post-endocytotic sorting of receptors. Of the two proteins suggested to target receptors for recycling to the cell membrane, which is the route believed to be taken by a majority of receptors, ERM (ezrin-radixin-moesin)-binding phosphoprotein 50 (EBP50) bound...

  12. A library of 7TM receptor C-terminal tails - Interactions with the proposed post-endocytic sorting proteins ERM-binding phosphoprotein 50 (EBP50), N-ethylmaleimide-sensitive factor (NSF), sorting nexin 1 (SNX1), and G protein-coupled receptor-associated sorting protein (GASP)

    Heydorn, A.; Sondergaard, B.P.; Ersbøll, Bjarne Kjær;

    2004-01-01

    Adaptor and scaffolding proteins determine the cellular targeting, the spatial, and thereby the functional association of G protein-coupled seven-transmembrane receptors with co-receptors, transducers, and downstream effectors and the adaptors determine post-signaling events such as receptor sequ...... that the tail library provides useful information on the general importance of certain adaptor proteins, for example, in this case, ruling out EBP50 as being a broad spectrum-recycling adaptor....... proteins previously proposed to be involved in post-endocytotic sorting of receptors. Of the two proteins suggested to target receptors for recycling to the cell membrane, which is the route believed to be taken by a majority of receptors, ERM (ezrin-radixin-moesin)binding phosphoprotein 50 (EBP50) bound...

  13. Systematically characterizing and prioritizing chemosensitivity related gene based on Gene Ontology and protein interaction network

    Chen Xin

    2012-10-01

    Full Text Available Abstract Background The identification of genes that predict in vitro cellular chemosensitivity of cancer cells is of great importance. Chemosensitivity related genes (CRGs have been widely utilized to guide clinical and cancer chemotherapy decisions. In addition, CRGs potentially share functional characteristics and network features in protein interaction networks (PPIN. Methods In this study, we proposed a method to identify CRGs based on Gene Ontology (GO and PPIN. Firstly, we documented 150 pairs of drug-CCRG (curated chemosensitivity related gene from 492 published papers. Secondly, we characterized CCRGs from the perspective of GO and PPIN. Thirdly, we prioritized CRGs based on CCRGs’ GO and network characteristics. Lastly, we evaluated the performance of the proposed method. Results We found that CCRG enriched GO terms were most often related to chemosensitivity and exhibited higher similarity scores compared to randomly selected genes. Moreover, CCRGs played key roles in maintaining the connectivity and controlling the information flow of PPINs. We then prioritized CRGs using CCRG enriched GO terms and CCRG network characteristics in order to obtain a database of predicted drug-CRGs that included 53 CRGs, 32 of which have been reported to affect susceptibility to drugs. Our proposed method identifies a greater number of drug-CCRGs, and drug-CCRGs are much more significantly enriched in predicted drug-CRGs, compared to a method based on the correlation of gene expression and drug activity. The mean area under ROC curve (AUC for our method is 65.2%, whereas that for the traditional method is 55.2%. Conclusions Our method not only identifies CRGs with expression patterns strongly correlated with drug activity, but also identifies CRGs in which expression is weakly correlated with drug activity. This study provides the framework for the identification of signatures that predict in vitro cellular chemosensitivity and offers a valuable

  14. The relationship between the adaptor molecule caspase recruitment domain-containing protein 9 and anti-tuberculosis immunity%衔接分子胱天蛋白酶募集域蛋白9与抗结核免疫的相关性

    孙蕾; 郑锦辉; 王毳; 费思平; 赵卓

    2013-01-01

    结核病是一种慢性传染病,全球每年有170万例患者死于结核病.我国结核病患者例数居世界第二位,也是耐药结核病流行严重的国家之一,因结核病死亡的人数超过其他传染病死亡人数的总和.因此,研制有效的抗结核药物和新型疫苗迫在眉睫.这需要对宿主与Mtb相互作用机制、抗原提呈细胞(antigen presenting cell.APC)内部信号传导机制及其关键分子进行深入理解.宿主感染Mtb后,通过模式以别受体(pattern recognition receptors,PRRs)识别Mtb表面病原体相关分子模式(pathogen-associated molecular patterns,PAMPs),并将信号传递给衔接分子,后者启动下游的信号级联反应,诱导固有免疫细胞合成细胞因子,活化宿主免疫机制.本综述对一种重要的衔接分子胱天蛋白酶募集域蛋白9(caspase rccruitment domain-containing protein 9,CARD9)及其与抗结核免疫的相关性进行简要阐述,为结核病的治疗和疫苗的研制提供参考.

  15. Dephosphorylation of the adaptor LAT and phospholipase C-γ by SHP-1 inhibits natural killer cell cytotoxicity.

    Matalon, Omri; Fried, Sophia; Ben-Shmuel, Aviad; Pauker, Maor H; Joseph, Noah; Keizer, Danielle; Piterburg, Marina; Barda-Saad, Mira

    2016-01-01

    Natural killer (NK) cells discriminate between healthy cells and virally infected or transformed self-cells by tuning activating and inhibitory signals received through cell surface receptors. Inhibitory receptors inhibit NK cell function by recruiting and activating the tyrosine phosphatase Src homology 2 (SH2) domain-containing protein tyrosine phosphatase-1 (SHP-1) to the plasma membrane. However, to date, the guanine nucleotide exchange factor VAV1 is the only direct SHP-1 substrate identified in NK cells. We reveal that the adaptor protein linker for activation of T cells (LAT) as well as phospholipase C-γ1 (PLC-γ1) and PLC-γ2 are SHP-1 substrates. Dephosphorylation of Tyr(132) in LAT by SHP-1 in NK cells abrogated the recruitment of PLC-γ1 and PLC-γ2 to the immunological synapse between the NK cell and a cancer cell target, which reduced NK cell degranulation and target cell killing. Furthermore, the ubiquitylation of LAT by the E3 ubiquitin ligases c-Cbl and Cbl-b, which was induced by LAT phosphorylation, led to the degradation of LAT in response to the engagement of inhibitory receptors on NK cells, which abrogated NK cell cytotoxicity. Knockdown of the Cbl proteins blocked LAT ubiquitylation, which promoted NK cell function. Expression of a ubiquitylation-resistant mutant LAT blocked inhibitory receptor signaling, enabling cells to become activated. Together, these data identify previously uncharacterized SHP-1 substrates and inhibitory mechanisms that determine the response of NK cells. PMID:27221712

  16. Discovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments.

    García-Alonso, Luz; Alonso, Roberto; Vidal, Enrique; Amadoz, Alicia; de María, Alejandro; Minguez, Pablo; Medina, Ignacio; Dopazo, Joaquín

    2012-11-01

    Genomic experiments (e.g. differential gene expression, single-nucleotide polymorphism association) typically produce ranked list of genes. We present a simple but powerful approach which uses protein-protein interaction data to detect sub-networks within such ranked lists of genes or proteins. We performed an exhaustive study of network parameters that allowed us concluding that the average number of components and the average number of nodes per component are the parameters that best discriminate between real and random networks. A novel aspect that increases the efficiency of this strategy in finding sub-networks is that, in addition to direct connections, also connections mediated by intermediate nodes are considered to build up the sub-networks. The possibility of using of such intermediate nodes makes this approach more robust to noise. It also overcomes some limitations intrinsic to experimental designs based on differential expression, in which some nodes are invariant across conditions. The proposed approach can also be used for candidate disease-gene prioritization. Here, we demonstrate the usefulness of the approach by means of several case examples that include a differential expression analysis in Fanconi Anemia, a genome-wide association study of bipolar disorder and a genome-scale study of essentiality in cancer genes. An efficient and easy-to-use web interface (available at http://www.babelomics.org) based on HTML5 technologies is also provided to run the algorithm and represent the network. PMID:22844098

  17. A Quantitative Approach to Analyzing Genome Reductive Evolution Using Protein–Protein Interaction Networks: A Case Study of Mycobacterium leprae

    Akinola, Richard O.; Mazandu, Gaston K.; Mulder, Nicola J.

    2016-01-01

    The advance in high-throughput sequencing technologies has yielded complete genome sequences of several organisms, including complete bacterial genomes. The growing number of these available sequenced genomes has enabled analyses of their dynamics, as well as the molecular and evolutionary processes which these organisms are under. Comparative genomics of different bacterial genomes have highlighted their genome size and gene content in association with lifestyles and adaptation to various environments and have contributed to enhancing our understanding of the mechanisms of their evolution. Protein–protein functional interactions mediate many essential processes for maintaining the stability of the biological systems under changing environmental conditions. Thus, these interactions play crucial roles in the evolutionary processes of different organisms, especially for obligate intracellular bacteria, proven to generally have reduced genome sizes compared to their nearest free-living relatives. In this study, we used the approach based on the Renormalization Group (RG) analysis technique and the Maximum-Excluded-Mass-Burning (MEMB) model to investigate the evolutionary process of genome reduction in relation to the organization of functional networks of two organisms. Using a Mycobacterium leprae (MLP) network in comparison with a Mycobacterium tuberculosis (MTB) network as a case study, we show that reductive evolution in MLP was as a result of removal of important proteins from neighbors of corresponding orthologous MTB proteins. While each orthologous MTB protein had an increase in number of interacting partners in most instances, the corresponding MLP protein had lost some of them. This work provides a quantitative model for mapping reductive evolution and protein–protein functional interaction network organization in terms of roles played by different proteins in the network structure. PMID:27066064

  18. De novo design of protein homo-oligomers with modular hydrogen-bond network-mediated specificity.

    Boyken, Scott E; Chen, Zibo; Groves, Benjamin; Langan, Robert A; Oberdorfer, Gustav; Ford, Alex; Gilmore, Jason M; Xu, Chunfu; DiMaio, Frank; Pereira, Jose Henrique; Sankaran, Banumathi; Seelig, Georg; Zwart, Peter H; Baker, David

    2016-05-01

    In nature, structural specificity in DNA and proteins is encoded differently: In DNA, specificity arises from modular hydrogen bonds in the core of the double helix, whereas in proteins, specificity arises largely from buried hydrophobic packing complemented by irregular peripheral polar interactions. Here, we describe a general approach for designing a wide range of protein homo-oligomers with specificity determined by modular arrays of central hydrogen-bond networks. We use the approach to design dimers, trimers, and tetramers consisting of two concentric rings of helices, including previously not seen triangular, square, and supercoiled topologies. X-ray crystallography confirms that the structures overall, and the hydrogen-bond networks in particular, are nearly identical to the design models, and the networks confer interaction specificity in vivo. The ability to design extensive hydrogen-bond networks with atomic accuracy enables the programming of protein interaction specificity for a broad range of synthetic biology applications; more generally, our results demonstrate that, even with the tremendous diversity observed in nature, there are fundamentally new modes of interaction to be discovered in proteins. PMID:27151862

  19. Using co-occurrence network structure to extract synonymous gene and protein names from MEDLINE abstracts

    Spackman K

    2005-04-01

    Full Text Available Abstract Background Text-mining can assist biomedical researchers in reducing information overload by extracting useful knowledge from large collections of text. We developed a novel text-mining method based on analyzing the network structure created by symbol co-occurrences as a way to extend the capabilities of knowledge extraction. The method was applied to the task of automatic gene and protein name synonym extraction. Results Performance was measured on a test set consisting of about 50,000 abstracts from one year of MEDLINE. Synonyms retrieved from curated genomics databases were used as a gold standard. The system obtained a maximum F-score of 22.21% (23.18% precision and 21.36% recall, with high efficiency in the use of seed pairs. Conclusion The method performs comparably with other studied methods, does not rely on sophisticated named-entity recognition, and requires little initial seed knowledge.

  20. UbiNet: an online resource for exploring the functional associations and regulatory networks of protein ubiquitylation.

    Nguyen, Van-Nui; Huang, Kai-Yao; Weng, Julia Tzu-Ya; Lai, K Robert; Lee, Tzong-Yi

    2016-01-01

    Protein ubiquitylation catalyzed by E3 ubiquitin ligases are crucial in the regulation of many cellular processes. Owing to the high throughput of mass spectrometry-based proteomics, a number of methods have been developed for the experimental determination of ubiquitylation sites, leading to a large collection of ubiquitylation data. However, there exist no resources for the exploration of E3-ligase-associated regulatory networks of for ubiquitylated proteins in humans. Therefore, the UbiNet database was developed to provide a full investigation of protein ubiquitylation networks by incorporating experimentally verified E3 ligases, ubiquitylated substrates and protein-protein interactions (PPIs). To date, UbiNet has accumulated 43 948 experimentally verified ubiquitylation sites from 14 692 ubiquitylated proteins of humans. Additionally, we have manually curated 499 E3 ligases as well as two E1 activating and 46 E2 conjugating enzymes. To delineate the regulatory networks among E3 ligases and ubiquitylated proteins, a total of 430 530 PPIs were integrated into UbiNet for the exploration of ubiquitylation networks with an interactive network viewer. A case study demonstrated that UbiNet was able to decipher a scheme for the ubiquitylation of tumor proteins p63 and p73 that is consistent with their functions. Although the essential role of Mdm2 in p53 regulation is well studied, UbiNet revealed that Mdm2 and additional E3 ligases might be implicated in the regulation of other tumor proteins by protein ubiquitylation. Moreover, UbiNet could identify potential substrates for a specific E3 ligase based on PPIs and substrate motifs. With limited knowledge about the mechanisms through which ubiquitylated proteins are regulated by E3 ligases, UbiNet offers users an effective means for conducting preliminary analyses of protein ubiquitylation. The UbiNet database is now freely accessible via http://csb.cse.yzu.edu.tw/UbiNet/ The content is regularly updated with the

  1. Genetic adaptation of the antibacterial human innate immunity network

    Lazarus Ross

    2011-07-01

    Full Text Available Abstract Background Pathogens have represented an important selective force during the adaptation of modern human populations to changing social and other environmental conditions. The evolution of the immune system has therefore been influenced by these pressures. Genomic scans have revealed that immune system is one of the functions enriched with genes under adaptive selection. Results Here, we describe how the innate immune system has responded to these challenges, through the analysis of resequencing data for 132 innate immunity genes in two human populations. Results are interpreted in the context of the functional and interaction networks defined by these genes. Nucleotide diversity is lower in the adaptors and modulators functional classes, and is negatively correlated with the centrality of the proteins within the interaction network. We also produced a list of candidate genes under positive or balancing selection in each population detected by neutrality tests and showed that some functional classes are preferential targets for selection. Conclusions We found evidence that the role of each gene in the network conditions the capacity to evolve or their evolvability: genes at the core of the network are more constrained, while adaptation mostly occurred at particular positions at the network edges. Interestingly, the functional classes containing most of the genes with signatures of balancing selection are involved in autoinflammatory and autoimmune diseases, suggesting a counterbalance between the beneficial and deleterious effects of the immune response.

  2. Dynamic correlation networks in human peroxisome proliferator-activated receptor-γ nuclear receptor protein.

    Fidelak, Jeremy; Ferrer, Silvia; Oberlin, Michael; Moras, Dino; Dejaegere, Annick; Stote, Roland H

    2010-10-01

    Peroxisome proliferator-activated receptor-γ nuclear receptor (PPAR-γ) belongs to the superfamily of nuclear receptor proteins that function as ligand-dependent transcription factors and plays a specific physiological role as a regulator of lipid metabolism. A number of experimental studies have suggested that allostery plays an important role in the functioning of PPAR-γ. Here we use normal-mode analysis of PPAR-γ to characterize a network of dynamically coupled amino acids that link physiologically relevant binding surfaces such as the ligand-dependent activation domain AF-2 with the ligand binding site and the heterodimer interface. Multiple calculations were done in both the presence and absence of the agonist rosiglitazone, and the differences in dynamics were characterized. The global dynamics of the ligand binding domain were affected by the ligand, and in particular, changes to the network of dynamically correlated amino acids were observed with only small changes in conformation. These results suggest that changes in dynamic couplings can be functionally significant with respect to the transmission of allosteric signals. PMID:20496064

  3. Detection of regulatory circuits by integrating the cellular networks of protein–protein interactions and transcription regulation

    Yeger-Lotem, Esti; Margalit, Hanah

    2003-01-01

    The post-genomic era is marked by huge amounts of data generated by large-scale functional genomic and proteomic experiments. A major challenge is to integrate the various types of genome-scale information in order to reveal the intra- and inter- relationships between genes and proteins that constitute a living cell. Here we present a novel application of classical graph algorithms to integrate the cellular networks of protein–protein interactions and transcription regulation. We demonstrate ...

  4. Prediction of the anti-inflammatory mechanisms of curcumin by module-based protein interaction network analysis

    Yanxiong Gan; Shichao Zheng; Jan P A Baak; Silei Zhao; Yongfeng Zheng; Nini Luo; Wan Liao; Chaomei Fu

    2015-01-01

    Curcumin, the medically active component from Curcuma longa (Turmeric), is widely used to treat inflammatory diseases. Protein interaction network (PIN) analysis was used to predict its mechanisms of molecular action. Targets of curcumin were obtained based on ChEMBL and STITCH databases. Protein–protein interactions (PPIs) were extracted from the String database. The PIN of curcumin was constructed by Cytoscape and the function modules identified by gene ontology (GO) enrichment analysis bas...

  5. Adaptor bypass mutations of Bacillus subtilis spx suggest a mechanism for YjbH-enhanced proteolysis of the regulator Spx by ClpXP

    Chan, Chio Mui; Hahn, Erik; Zuber, Peter

    2014-01-01

    Summary The global regulator, Spx, is under proteolytic control exerted by the adaptor YjbH and ATP-dependent protease ClpXP in Bacillus subtilis. While YjbH is observed to bind the Spx C-terminus, YjbH shows little affinity for ClpXP, indicating adaptor activity that does not operate by tethering. Chimeric proteins derived from B. subtilis AbrB and the Spx C-terminus showed that a 28 residue C-terminal section of Spx (AbrB28), but not the last 12 or 16 residues (AbrB12, AbrB16), was required for YjbH interaction and for ClpXP proteolysis, although the rate of AbrB28 proteolysis was not affected by YjbH addition. The result suggested that the YjbH-targeted 28 residue segment of the Spx C-terminus bears a ClpXP-recognition element(s) that is hidden in the intact Spx protein. Residue substitutions in the conserved helix α6 of the C-terminal region generated Spx substrates that were degraded by ClpXP at accelerated rates compared to wild type Spx, and showed reduced dependency on the YjbH activity. The residue substitutions also weakened the interaction between Spx and YjbH. The results suggest a model in which YjbH, through interaction with residues of α6 helix, exposes the C-terminus of Spx for recognition and proteolysis by ClpXP. PMID:24942655

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

    Nielsen Jens; Jouhten Paula; Nandy Subir K

    2010-01-01

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

  7. Evidence for an evolutionary relationship between the large adaptor nucleoporin Nup192 and karyopherins.

    Stuwe, Tobias; Lin, Daniel H; Collins, Leslie N; Hurt, Ed; Hoelz, André

    2014-02-18

    Nucleocytoplasmic transport is facilitated by nuclear pore complexes (NPCs), which are massive proteinaceous transport channels embedded in the nuclear envelope. Nup192 is a major component of an adaptor nucleoporin subcomplex proposed to link the NPC coat with the central transport channel. Here, we present the structure of the ∼110-kDa N-terminal domain (NTD) of Nup192 at 2.7-Å resolution. The structure reveals an open ring-shaped architecture composed of Huntingtin, EF3, PP2A, and TOR1 (HEAT) and Armadillo (ARM) repeats. A comparison of different conformations indicates that the NTD consists of two rigid halves connected by a flexible hinge. Unexpectedly, the two halves of the ring are structurally related to karyopherin-α (Kap-α) and β-karyopherin family members. Biochemically, we identify a conserved patch that binds an unstructured segment in Nup53 and show that a C-terminal tail region binds to a putative helical fragment in Nic96. The Nup53 segment that binds Nup192 is a classical nuclear localization-like sequence that interacts with Kap-α in a mutually exclusive and mechanistically distinct manner. The disruption of the Nup53 and Nic96 binding sites in vivo yields growth and mRNA export defects, revealing their critical role in proper NPC function. Surprisingly, both interactions are dispensable for NPC localization, suggesting that Nup192 possesses another nucleoporin interaction partner. These data indicate that the structured domains in the adaptor nucleoporin complex are held together by peptide interactions that resemble those found in karyopherin•cargo complexes and support the proposal that the adaptor nucleoporins arose from ancestral karyopherins. PMID:24505056

  8. DNA as Tunable Adaptor for siRNA Polyplex Stabilization and Functionalization.

    Heissig, Philipp; Klein, Philipp M; Hadwiger, Philipp; Wagner, Ernst

    2016-01-01

    siRNA and microRNA are promising therapeutic agents, which are engaged in a natural mechanism called RNA interference that modulates gene expression posttranscriptionally. For intracellular delivery of such nucleic acid triggers, we use sequence-defined cationic polymers manufactured through solid phase chemistry. They consist of an oligoethanamino amide core for siRNA complexation and optional domains for nanoparticle shielding and cell targeting. Due to the small size of siRNA, electrostatic complexes with polycations are less stable, and consequently intracellular delivery is less efficient. Here we use DNA oligomers as adaptors to increase size and charge of cargo siRNA, resulting in increased polyplex stability, which in turn boosts transfection efficiency. Extending a single siRNA with a 181-nucleotide DNA adaptor is sufficient to provide maximum gene silencing aided by cationic polymers. Interestingly, this simple strategy was far more effective than merging defined numbers (4-10) of siRNA units into one DNA scaffolded construct. For DNA attachment, the 3' end of the siRNA passenger strand was beneficial over the 5' end. The impact of the attachment site however was resolved by introducing bioreducible disulfides at the connection point. We also show that DNA adaptors provide the opportunity to readily link additional functional domains to siRNA. Exemplified by the covalent conjugation of the endosomolytic influenza peptide INF-7 to siRNA via a DNA backbone strand and complexing this construct with a targeting polymer, we could form a highly functional polyethylene glycol-shielded polyplex to downregulate a luciferase gene in folate receptor-positive cells. PMID:26928236

  9. Benchmarking Deep Networks for Predicting Residue-Specific Quality of Individual Protein Models in CASP11

    Liu, Tong; Wang, Yiheng; Eickholt, Jesse; Wang, Zheng

    2016-01-01

    Quality assessment of a protein model is to predict the absolute or relative quality of a protein model using computational methods before the native structure is available. Single-model methods only need one model as input and can predict the absolute residue-specific quality of an individual model. Here, we have developed four novel single-model methods (Wang_deep_1, Wang_deep_2, Wang_deep_3, and Wang_SVM) based on stacked denoising autoencoders (SdAs) and support vector machines (SVMs). We evaluated these four methods along with six other methods participating in CASP11 at the global and local levels using Pearson’s correlation coefficients and ROC analysis. As for residue-specific quality assessment, our four methods achieved better performance than most of the six other CASP11 methods in distinguishing the reliably modeled residues from the unreliable measured by ROC analysis; and our SdA-based method Wang_deep_1 has achieved the highest accuracy, 0.77, compared to SVM-based methods and our ensemble of an SVM and SdAs. However, we found that Wang_deep_2 and Wang_deep_3, both based on an ensemble of multiple SdAs and an SVM, performed slightly better than Wang_deep_1 in terms of ROC analysis, indicating that integrating an SVM with deep networks works well in terms of certain measurements.

  10. Benchmarking Deep Networks for Predicting Residue-Specific Quality of Individual Protein Models in CASP11

    Liu, Tong; Wang, Yiheng; Eickholt, Jesse; Wang, Zheng

    2016-01-01

    Quality assessment of a protein model is to predict the absolute or relative quality of a protein model using computational methods before the native structure is available. Single-model methods only need one model as input and can predict the absolute residue-specific quality of an individual model. Here, we have developed four novel single-model methods (Wang_deep_1, Wang_deep_2, Wang_deep_3, and Wang_SVM) based on stacked denoising autoencoders (SdAs) and support vector machines (SVMs). We evaluated these four methods along with six other methods participating in CASP11 at the global and local levels using Pearson’s correlation coefficients and ROC analysis. As for residue-specific quality assessment, our four methods achieved better performance than most of the six other CASP11 methods in distinguishing the reliably modeled residues from the unreliable measured by ROC analysis; and our SdA-based method Wang_deep_1 has achieved the highest accuracy, 0.77, compared to SVM-based methods and our ensemble of an SVM and SdAs. However, we found that Wang_deep_2 and Wang_deep_3, both based on an ensemble of multiple SdAs and an SVM, performed slightly better than Wang_deep_1 in terms of ROC analysis, indicating that integrating an SVM with deep networks works well in terms of certain measurements. PMID:26763289

  11. The role of palmitoylation and transmembrane domain in sorting of transmembrane adaptor proteins

    Chum, Tomáš; Glatzová, Daniela; Kvíčalová, Zuzana; Malínský, Jan; Brdička, Tomáš; Cebecauer, Marek

    2016-01-01

    Roč. 129, č. 1 (2016), s. 95-107. ISSN 0021-9533 Institutional support: RVO:61388955 ; RVO:68378050 ; RVO:68378041 Keywords : LAT * PAG * Palmitoylation Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 5.432, year: 2014

  12. Merkel Cell Polyomavirus Small T Antigen Targets the NEMO Adaptor Protein To Disrupt Inflammatory Signaling

    Griffiths, David A.; Abdul-Sada, Hussein; Knight, Laura M.; Jackson, Brian R.; Richards, Kathryn; Prescott, Emma L.; Peach, A. Howard S.; Blair, G. Eric; MacDonald, Andrew; Whitehouse, Adrian

    2013-01-01

    Merkel cell carcinoma (MCC) is a highly aggressive nonmelanoma skin cancer arising from epidermal mechanoreceptor Merkel cells. In 2008, a novel human polyomavirus, Merkel cell polyomavirus (MCPyV), was identified and is strongly implicated in MCC pathogenesis. Currently, little is known regarding the virus-host cell interactions which support virus replication and virus-induced mechanisms in cellular transformation and metastasis. Here we identify a new function of MCPyV small T antigen (ST)...

  13. Transmembrane adaptor proteins in membrane microdomains: important regulators of immunoreceptor signaling

    Hořejší, Václav

    2004-01-01

    Roč. 29, 1-2 (2004), s. 43-49. ISSN 0165-2478 R&D Projects: GA MŠk LN00A026 Institutional research plan: CEZ:AV0Z5052915 Keywords : immunoreceptor * signalling Subject RIV: EC - Immunology Impact factor: 2.136, year: 2004

  14. The transmembrane region is responsible for targeting of adaptor protein LAX into "heavy rafts''

    Hrdinka, Matouš; Otáhal, Pavel; Hořejší, Václav

    2012-01-01

    Roč. 7, č. 5 (2012), e36330. E-ISSN 1932-6203 R&D Projects: GA ČR GEMEM/09/E011; GA MŠk 1M0506 Institutional research plan: CEZ:AV0Z50520514 Keywords : LAX * transmembrane domain * DRM Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.730, year: 2012

  15. Proteometabolomic Study of Compatible Interaction in Tomato Fruit Challenged with Sclerotinia rolfsii Illustrates Novel Protein Network during Disease Progression.

    Ghosh, Sudip; Narula, Kanika; Sinha, Arunima; Ghosh, Rajgourab; Jawa, Priyanka; Chakraborty, Niranjan; Chakraborty, Subhra

    2016-01-01

    Fruit is an assimilator of metabolites, nutrients, and signaling molecules, thus considered as potential target for pathogen attack. In response to patho-stress, such as fungal invasion, plants reorganize their proteome, and reconfigure their physiology in the infected organ. This remodeling is coordinated by a poorly understood signal transduction network, hormonal cascades, and metabolite reallocation. The aim of the study was to explore organ-based proteomic alterations in the susceptibility of heterotrophic fruit to necrotrophic fungal attack. We conducted time-series protein profiling of Sclerotinia rolfsii invaded tomato (Solanum lycopersicum) fruit. The differential display of proteome revealed 216 patho-stress responsive proteins (PSRPs) that change their abundance by more than 2.5-fold. Mass spectrometric analyses led to the identification of 56 PSRPs presumably involved in disease progression; regulating diverse functions viz. metabolism, signaling, redox homeostasis, transport, stress-response, protein folding, modification and degradation, development. Metabolome study indicated differential regulation of organic acid, amino acids, and carbohydrates paralleling with the proteomics analysis. Further, we interrogated the proteome data using network analysis that identified two significant functional protein hubs centered around malate dehydrogenase, T-complex protein 1 subunit gamma, and ATP synthase beta. This study reports, for the first-time, kinetically controlled patho-stress responsive protein network during post-harvest storage in a sink tissue, particularly fruit and constitute the basis toward understanding the onset and context of disease signaling and metabolic pathway alterations. The network representation may facilitate the prioritization of candidate proteins for quality improvement in storage organ. PMID:27507973

  16. Interaction networks in protein folding via atomic-resolution experiments and long-time-scale molecular dynamics simulations

    Sborgi, Lorenzo; Verma, Abhinav; Piana, Stefano;

    2015-01-01

    to investigate the folding of gpW, a protein with two-state-like, fast folding dynamics and cooperative equilibrium unfolding behavior. Experiments and simulations expose a remarkably complex pattern of structural changes that occur at the atomic level and from which the detailed network of residue...

  17. Effects of developmental exposure to a Commercial PBDE mixture (DE-71) on protein networks in the rat Cerebellum and Hippocampus

    Title (20 words): Effects of developmental exposure to a Commercial PBDE mixture (DE-71) on protein networks in the rat Cerebellum and Hippocampus. Introduction (120 words): Polybrominated diphenyl ethers (PBDE5) possess neurotoxic effects similar to those of PCBs. The cellular a...

  18. Elucidating Common Structural Features of Human Pathogenic Variations Using Large-Scale Atomic-Resolution Protein Networks

    Das, Jishnu; Lee, Hao Ran; Sagar, Adithya; Fragoza, Robert; Liang, Jin; Wei, Xiaomu; Wang, Xiujuan; Mort, Matthew; Stenson, Peter D.; Cooper, David N.; Yu, Haiyuan

    2016-01-01

    With the rapid growth of structural genomics, numerous protein crystal structures have become available. However, the parallel increase in knowledge of the functional principles underlying biological processes, and more specifically the underlying molecular mechanisms of disease, has been less dramatic. This notwithstanding, the study of complex cellular networks has made possible the inference of protein functions on a large scale. Here, we combine the scale of network systems biology with the resolution of traditional structural biology to generate a large-scale atomic-resolution interactome-network comprising 3,398 interactions between 2,890 proteins with a well-defined interaction interface and interface residues for each interaction. Within the framework of this atomic-resolution network, we have explored the structural principles underlying variations causing human-inherited disease. We find that in-frame pathogenic variations are enriched at both the interface and in the interacting domain, suggesting that variations not only at interface “hot-spots,” but in the entire interacting domain can result in alterations of interactions. Further, the sites of pathogenic variations are closely related to the biophysical strength of the interactions they perturb. Finally, we show that biochemical alterations consequent to these variations are considerably more disruptive than evolutionary changes, with the most significant alterations at the protein interaction interface. PMID:24599843

  19. Pathway Detection from Protein Interaction Networks and Gene Expression Data Using Color-Coding Methods and A* Search Algorithms

    Cheng-Yu Yeh

    2012-01-01

    Full Text Available With the large availability of protein interaction networks and microarray data supported, to identify the linear paths that have biological significance in search of a potential pathway is a challenge issue. We proposed a color-coding method based on the characteristics of biological network topology and applied heuristic search to speed up color-coding method. In the experiments, we tested our methods by applying to two datasets: yeast and human prostate cancer networks and gene expression data set. The comparisons of our method with other existing methods on known yeast MAPK pathways in terms of precision and recall show that we can find maximum number of the proteins and perform comparably well. On the other hand, our method is more efficient than previous ones and detects the paths of length 10 within 40 seconds using CPU Intel 1.73GHz and 1GB main memory running under windows operating system.

  20. Pleiotropy constrains the evolution of protein but not regulatory sequences in a transcription regulatory network influencing complex social behaviours

    Daria eMolodtsova

    2014-12-01

    Full Text Available It is increasingly apparent that genes and networks that influence complex behaviour are evolutionary conserved, which is paradoxical considering that behaviour is labile over evolutionary timescales. How does adaptive change in behaviour arise if behaviour is controlled by conserved, pleiotropic, and likely evolutionary constrained genes? Pleiotropy and connectedness are known to constrain the general rate of protein evolution, prompting some to suggest that the evolution of complex traits, including behaviour, is fuelled by regulatory sequence evolution. However, we seldom have data on the strength of selection on mutations in coding and regulatory sequences, and this hinders our ability to study how pleiotropy influences coding and regulatory sequence evolution. Here we use population genomics to estimate the strength of selection on coding and regulatory mutations for a transcriptional regulatory network that influences complex behaviour of honey bees. We found that replacement mutations in highly connected transcription factors and target genes experience significantly stronger negative selection relative to weakly connected transcription factors and targets. Adaptively evolving proteins were significantly more likely to reside at the periphery of the regulatory network, while proteins with signs of negative selection were near the core of the network. Interestingly, connectedness and network structure had minimal influence on the strength of selection on putative regulatory sequences for both transcription factors and their targets. Our study indicates that adaptive evolution of complex behaviour can arise because of positive selection on protein-coding mutations in peripheral genes, and on regulatory sequence mutations in both transcription factors and their targets throughout the network.